diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml
index 621bf57f7ce..b19f44eb024 100644
--- a/.github/ISSUE_TEMPLATE/config.yml
+++ b/.github/ISSUE_TEMPLATE/config.yml
@@ -4,6 +4,6 @@ contact_links:
- name: Have you read the docs?
url: https://ogx-ai.github.io/docs
about: Much help can be found in the docs
- - name: Chat on Slack
- url: https://join.slack.com/t/ogx-ai/shared_invite/zt-3uyw5bxj9-tSEwsNZncgkGEKbd4dXIpw
- about: Maybe chatting with the community can help
+ - name: Join the Discord community
+ url: https://discord.gg/bUYRqEvK6
+ about: Ask questions and chat with the community
diff --git a/.github/actions/install-ogx-client/action.yml b/.github/actions/install-ogx-client/action.yml
index 3d9a9f1fcc4..74f715312fc 100644
--- a/.github/actions/install-ogx-client/action.yml
+++ b/.github/actions/install-ogx-client/action.yml
@@ -30,7 +30,7 @@ runs:
id: configure
shell: bash
run: |
- # If sdk_install_url is provided (e.g., from Stainless preview), use it directly
+ # If sdk_install_url is provided, use it directly
if [ -n "${{ inputs.sdk_install_url }}" ]; then
echo "Using provided sdk_install_url: ${{ inputs.sdk_install_url }}"
echo "install-after-sync=true" >> $GITHUB_OUTPUT
diff --git a/.github/actions/launch-gpu-runner/action.yml b/.github/actions/launch-gpu-runner/action.yml
new file mode 100644
index 00000000000..2e4f6dfa5aa
--- /dev/null
+++ b/.github/actions/launch-gpu-runner/action.yml
@@ -0,0 +1,82 @@
+name: 'Launch GPU EC2 Runner'
+description: 'Launch GPU-enabled EC2 instance as GitHub Actions self-hosted runner (wrapper for machulav/ec2-github-runner)'
+
+on:
+ workflow_dispatch:
+inputs:
+ mode:
+ description: 'Mode: start or stop'
+ required: true
+ github-token:
+ description: 'GitHub Personal Access Token with repo scope for runner registration'
+ required: true
+ instance-type:
+ description: 'EC2 instance type (e.g., g6.2xlarge, g5.2xlarge, g6.8xlarge)'
+ required: false
+ default: 'g6.2xlarge'
+ aws-region:
+ description: 'AWS region'
+ required: true
+ availability-zones-config:
+ description: 'JSON array of AZ configs with imageId, subnetId, securityGroupId for fallback'
+ required: false
+ default: ''
+ # For stop mode
+ label:
+ description: 'Runner label (for stop mode)'
+ required: false
+ ec2-instance-id:
+ description: 'EC2 instance ID (for stop mode)'
+ required: false
+ # Optional
+ ec2-instance-tags:
+ description: 'JSON array of tags to apply to EC2 instance'
+ required: false
+ default: '[]'
+ runner-home-dir:
+ description: 'Home directory for the runner'
+ required: false
+ default: ''
+ iam-role-name:
+ description: 'IAM role name to attach to the instance (optional, for enhanced security)'
+ required: false
+ default: ''
+
+outputs:
+ label:
+ description: 'Unique label for the launched runner'
+ value: ${{ steps.ec2-runner.outputs.label }}
+ ec2-instance-id:
+ description: 'EC2 instance ID'
+ value: ${{ steps.ec2-runner.outputs.ec2-instance-id }}
+
+runs:
+ using: 'composite'
+ steps:
+ - name: Start EC2 runner
+ if: inputs.mode == 'start'
+ id: ec2-runner
+ uses: machulav/ec2-github-runner@343a1b2ae682e681c3cec9a235d882da17ff04ef # v2.6.1
+ env:
+ AWS_DEFAULT_REGION: ${{ inputs.aws-region }}
+ AWS_REGION: ${{ inputs.aws-region }}
+ with:
+ mode: start
+ github-token: ${{ inputs.github-token }}
+ ec2-instance-type: ${{ inputs.instance-type }}
+ aws-resource-tags: ${{ inputs.ec2-instance-tags }}
+ runner-home-dir: ${{ inputs.runner-home-dir }}
+ iam-role-name: ${{ inputs.iam-role-name }}
+ availability-zones-config: ${{ inputs.availability-zones-config }}
+
+ - name: Stop EC2 runner
+ if: inputs.mode == 'stop'
+ uses: machulav/ec2-github-runner@343a1b2ae682e681c3cec9a235d882da17ff04ef # v2.6.1
+ env:
+ AWS_DEFAULT_REGION: ${{ inputs.aws-region }}
+ AWS_REGION: ${{ inputs.aws-region }}
+ with:
+ mode: stop
+ github-token: ${{ inputs.github-token }}
+ label: ${{ inputs.label }}
+ ec2-instance-id: ${{ inputs.ec2-instance-id }}
diff --git a/.github/actions/run-and-record-tests/action.yml b/.github/actions/run-and-record-tests/action.yml
index c74f233fe97..1737e5ac20c 100644
--- a/.github/actions/run-and-record-tests/action.yml
+++ b/.github/actions/run-and-record-tests/action.yml
@@ -24,6 +24,10 @@ inputs:
description: 'Regex pattern to pass to pytest -k'
required: false
default: ''
+ text-model:
+ description: 'Text model override to pass to integration-tests.sh'
+ required: false
+ default: ''
target-branch:
description: 'Target branch for recording commits (for PRs, use the PR head branch)'
required: false
@@ -56,28 +60,37 @@ runs:
INPUT_SUITE: ${{ inputs.suite }}
INPUT_SUBDIRS: ${{ inputs.subdirs }}
INPUT_PATTERN: ${{ inputs.pattern }}
+ INPUT_TEXT_MODEL: ${{ inputs.text-model }}
run: |
- SCRIPT_ARGS="--stack-config ${INPUT_STACK_CONFIG} --inference-mode ${INPUT_INFERENCE_MODE}"
+ SCRIPT_ARGS=(
+ --stack-config "${INPUT_STACK_CONFIG}"
+ --inference-mode "${INPUT_INFERENCE_MODE}"
+ )
# Add optional arguments only if they are provided
if [ -n "${INPUT_SETUP}" ]; then
- SCRIPT_ARGS="${SCRIPT_ARGS} --setup ${INPUT_SETUP}"
+ SCRIPT_ARGS+=(--setup "${INPUT_SETUP}")
fi
if [ -n "${INPUT_SUITE}" ]; then
- SCRIPT_ARGS="${SCRIPT_ARGS} --suite ${INPUT_SUITE}"
+ SCRIPT_ARGS+=(--suite "${INPUT_SUITE}")
fi
if [ -n "${INPUT_SUBDIRS}" ]; then
- SCRIPT_ARGS="${SCRIPT_ARGS} --subdirs ${INPUT_SUBDIRS}"
+ SCRIPT_ARGS+=(--subdirs "${INPUT_SUBDIRS}")
fi
if [ -n "${INPUT_PATTERN}" ]; then
- SCRIPT_ARGS="${SCRIPT_ARGS} --pattern ${INPUT_PATTERN}"
+ SCRIPT_ARGS+=(--pattern "${INPUT_PATTERN}")
+ fi
+ if [ -n "${INPUT_TEXT_MODEL}" ]; then
+ SCRIPT_ARGS+=(--text-model "${INPUT_TEXT_MODEL}")
fi
echo "=== Running command ==="
- echo "uv run --no-sync ./scripts/integration-tests.sh $SCRIPT_ARGS"
+ printf 'uv run --no-sync ./scripts/integration-tests.sh'
+ printf ' %q' "${SCRIPT_ARGS[@]}"
+ printf '\n'
echo ""
- uv run --no-sync ./scripts/integration-tests.sh $SCRIPT_ARGS | tee "pytest-${INPUT_INFERENCE_MODE}.log"
+ uv run --no-sync ./scripts/integration-tests.sh "${SCRIPT_ARGS[@]}" | tee "pytest-${INPUT_INFERENCE_MODE}.log"
- name: Commit and push recordings
diff --git a/.github/actions/setup-test-environment/action.yml b/.github/actions/setup-test-environment/action.yml
index 9cbf866e64b..e9086bbb5c5 100644
--- a/.github/actions/setup-test-environment/action.yml
+++ b/.github/actions/setup-test-environment/action.yml
@@ -27,6 +27,10 @@ inputs:
description: 'Explicit branch override (used by scheduled CI to pass the matrix branch)'
required: false
default: ''
+ enable-hf-cache:
+ description: 'Whether to cache HuggingFace models and datasets'
+ required: false
+ default: 'true'
runs:
using: 'composite'
@@ -40,6 +44,7 @@ runs:
branch: ${{ inputs.branch }}
- name: Cache HuggingFace models and datasets
+ if: ${{ inputs.enable-hf-cache == 'true' }}
uses: actions/cache@v4
with:
path: ~/.cache/huggingface
@@ -48,6 +53,7 @@ runs:
hf-cache-${{ runner.os }}-
- name: Pre-download HuggingFace assets for offline use
+ if: ${{ inputs.enable-hf-cache == 'true' }}
shell: bash
env:
HF_HUB_ENABLE_HF_TRANSFER: "1"
@@ -74,7 +80,7 @@ runs:
setup: ${{ inputs.setup }}
- name: Setup vllm
- if: ${{ startsWith(inputs.setup, 'vllm') && inputs.inference-mode != 'replay' }}
+ if: ${{ startsWith(inputs.setup, 'vllm') && !startsWith(inputs.setup, 'vllm-gpu-') && inputs.inference-mode != 'replay' }}
uses: ./.github/actions/setup-vllm
- name: Start Postgres service
diff --git a/.github/actions/setup-vllm-gpu/action.yml b/.github/actions/setup-vllm-gpu/action.yml
new file mode 100644
index 00000000000..820c5ff37fb
--- /dev/null
+++ b/.github/actions/setup-vllm-gpu/action.yml
@@ -0,0 +1,269 @@
+name: 'Setup vLLM GPU'
+description: 'Install vLLM with GPU support and start vLLM server with gpt-oss:20b'
+
+inputs:
+ model:
+ description: 'Model to serve (e.g., gpt-oss:20b, Qwen/Qwen3-0.6B)'
+ required: false
+ default: 'gpt-oss:20b'
+ port:
+ description: 'Port for vLLM server'
+ required: false
+ default: '8000'
+ gpu-memory-utilization:
+ description: 'GPU memory utilization (0.0-1.0)'
+ required: false
+ default: '0.85'
+ max-model-len:
+ description: 'Maximum model context length'
+ required: false
+ default: '8192'
+ quantization:
+ description: 'Optional vLLM quantization method (awq, gptq, or none)'
+ required: false
+ default: 'none'
+ vllm-version:
+ description: 'vLLM version to install, or latest for the newest available release'
+ required: false
+ default: '0.22.1'
+
+outputs:
+ vllm-url:
+ description: 'URL of the vLLM server'
+ value: 'http://localhost:${{ inputs.port }}/v1'
+ model-name:
+ description: 'Name of the model being served'
+ value: ${{ inputs.model }}
+
+runs:
+ using: 'composite'
+ steps:
+ - name: Verify GPU availability
+ shell: bash
+ run: |
+ echo "=== GPU Information ==="
+ nvidia-smi
+ echo ""
+ echo "=== CUDA Version ==="
+ nvcc --version || echo "nvcc not found in PATH"
+ echo ""
+ echo "=== Environment ==="
+ echo "CUDA_HOME: ${CUDA_HOME:-not set}"
+ echo "LD_LIBRARY_PATH: ${LD_LIBRARY_PATH:-not set}"
+
+ - name: Configure CUDA environment
+ shell: bash
+ run: |
+ if [ -z "${CUDA_HOME:-}" ]; then
+ if [ -d /usr/local/cuda-13.0 ]; then
+ export CUDA_HOME=/usr/local/cuda-13.0
+ elif [ -d /usr/local/cuda ]; then
+ export CUDA_HOME=/usr/local/cuda
+ elif [ -d /usr/local/cuda-12.8 ]; then
+ export CUDA_HOME=/usr/local/cuda-12.8
+ elif [ -d /usr/local/cuda-12.4 ]; then
+ export CUDA_HOME=/usr/local/cuda-12.4
+ else
+ export CUDA_HOME=/usr/local/cuda
+ fi
+ fi
+ echo "CUDA_HOME=${CUDA_HOME}" >> $GITHUB_ENV
+
+ export LD_LIBRARY_PATH="/usr/lib64:${LD_LIBRARY_PATH:-}:${CUDA_HOME}/lib64"
+ echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" >> $GITHUB_ENV
+
+ export PATH="${CUDA_HOME}/bin:${PATH}"
+ echo "PATH=${PATH}" >> $GITHUB_ENV
+
+ - name: Install uv
+ uses: astral-sh/setup-uv@1e862dfacbd1d6d858c55d9b792c756523627244 # v7.1.4
+ with:
+ enable-cache: ${{ env.UV_NO_CACHE != 'true' }}
+
+ - name: Install Python dependencies
+ shell: bash
+ run: |
+ # Create virtual environment
+ uv venv --python 3.12 /tmp/vllm-env
+ source /tmp/vllm-env/bin/activate
+
+ - name: Install vLLM with GPU support
+ shell: bash
+ env:
+ VLLM_VERSION: ${{ inputs.vllm-version }}
+ run: |
+ source /tmp/vllm-env/bin/activate
+
+ echo "=== Installing vLLM with CUDA support ==="
+ if [ "$VLLM_VERSION" = "latest" ]; then
+ uv pip install --no-config vllm --torch-backend=auto
+ else
+ uv pip install --no-config "vllm==$VLLM_VERSION" --torch-backend=auto
+ fi
+
+ echo "=== Verifying installation ==="
+ python -c "import torch; print(f'PyTorch version: {torch.__version__}')"
+ python -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}')"
+ python -c "import torch; print(f'CUDA device count: {torch.cuda.device_count()}')"
+ vllm --version
+
+ - name: Patch vLLM metrics route discovery
+ shell: bash
+ run: |
+ source /tmp/vllm-env/bin/activate
+
+ python - <<'PY'
+ from __future__ import annotations
+
+ from pathlib import Path
+ import prometheus_fastapi_instrumentator.routing as routing
+
+ routing_path = Path(routing.__file__)
+ source = routing_path.read_text()
+ old = "route_name = route.path"
+ new = (
+ "route_name = getattr(route, 'path', None)\n"
+ " if route_name is None:\n"
+ " continue"
+ )
+ if old not in source:
+ raise SystemExit(f"Expected route.path assignment not found in {routing_path}")
+ routing_path.write_text(source.replace(old, new, 1))
+ print(f"Patched {routing_path}")
+ PY
+
+ - name: Resolve model identifier
+ shell: bash
+ env:
+ MODEL: ${{ inputs.model }}
+ run: |
+ source /tmp/vllm-env/bin/activate
+
+ LOAD_MODEL="$MODEL"
+ SERVED_MODEL_NAME="$MODEL"
+
+ case "$MODEL" in
+ gpt-oss:20b)
+ LOAD_MODEL="openai/gpt-oss-20b"
+ ;;
+ esac
+
+ echo "VLLM_LOAD_MODEL=$LOAD_MODEL" >> $GITHUB_ENV
+ echo "VLLM_SERVED_MODEL_NAME=$SERVED_MODEL_NAME" >> $GITHUB_ENV
+ echo "Resolved load model: $LOAD_MODEL"
+ echo "Served model name: $SERVED_MODEL_NAME"
+
+ - name: Start vLLM server
+ shell: bash
+ env:
+ MODEL: ${{ inputs.model }}
+ PORT: ${{ inputs.port }}
+ GPU_MEM: ${{ inputs.gpu-memory-utilization }}
+ MAX_LEN: ${{ inputs.max-model-len }}
+ QUANT: ${{ inputs.quantization }}
+ VLLM_LOAD_MODEL: ${{ env.VLLM_LOAD_MODEL }}
+ VLLM_SERVED_MODEL_NAME: ${{ env.VLLM_SERVED_MODEL_NAME }}
+ run: |
+ source /tmp/vllm-env/bin/activate
+
+ echo "=== Starting vLLM server ==="
+ echo "Model: $MODEL"
+ echo "Load Model: $VLLM_LOAD_MODEL"
+ echo "Port: $PORT"
+ echo "GPU Memory Utilization: $GPU_MEM"
+ echo "Max Model Length: $MAX_LEN"
+ echo "Quantization: $QUANT"
+ echo ""
+
+ # Build vLLM command
+ VLLM_CMD="vllm serve $VLLM_LOAD_MODEL \
+ --host 0.0.0.0 \
+ --port $PORT \
+ --tensor-parallel-size 1 \
+ --gpu-memory-utilization $GPU_MEM \
+ --max-model-len $MAX_LEN \
+ --enable-auto-tool-choice \
+ --tool-call-parser openai \
+ --served-model-name $VLLM_SERVED_MODEL_NAME \
+ --dtype auto"
+
+ # Add quantization if specified
+ if [ "$QUANT" != "none" ]; then
+ VLLM_CMD="$VLLM_CMD --quantization $QUANT"
+ fi
+
+ echo "Command: $VLLM_CMD"
+ echo ""
+
+ # Start vLLM in background
+ $VLLM_CMD > /tmp/vllm-server.log 2>&1 &
+ VLLM_PID=$!
+ echo "vLLM server started with PID: $VLLM_PID"
+ echo "VLLM_PID=$VLLM_PID" >> $GITHUB_ENV
+
+ # Save PID for cleanup
+ echo $VLLM_PID > /tmp/vllm.pid
+
+ - name: Wait for vLLM server to be ready
+ shell: bash
+ env:
+ PORT: ${{ inputs.port }}
+ run: |
+ echo "=== Waiting for vLLM server to be ready ==="
+ echo "Health check URL: http://localhost:$PORT/health"
+ echo ""
+
+ # Wait up to 10 minutes for server to be ready
+ timeout 600 bash -c "
+ until curl -f http://localhost:$PORT/health > /dev/null 2>&1; do
+ echo \"Waiting for vLLM server... (checking http://localhost:$PORT/health)\"
+
+ # Check if process is still running
+ if ! kill -0 \$VLLM_PID 2>/dev/null; then
+ echo \"ERROR: vLLM process died!\"
+ echo \"Last 50 lines of vLLM log:\"
+ tail -n 50 /tmp/vllm-server.log
+ exit 1
+ fi
+
+ sleep 5
+ done
+ " || {
+ echo "ERROR: vLLM server failed to start within 10 minutes"
+ echo "=== vLLM Server Log ==="
+ cat /tmp/vllm-server.log
+ exit 1
+ }
+
+ echo "✓ vLLM server is ready!"
+ echo ""
+ echo "=== Testing models endpoint ==="
+ curl -sS -f http://localhost:$PORT/v1/models | python3 -m json.tool
+
+ echo ""
+ echo "=== Testing chat completion endpoint ==="
+ if [ -z "${VLLM_SERVED_MODEL_NAME:-}" ]; then
+ echo "ERROR: VLLM_SERVED_MODEL_NAME is not set"
+ exit 1
+ fi
+ cat > /tmp/vllm-smoke-request.json <= floors
+that should stay in sync. This script scans those files and bumps any matching
+>= constraint to the new version.
+
+Exit code 0 always. Outputs:
+ - One line per file/match explaining what happened.
+ - A final "updated=true" or "updated=false" line (for CI consumption).
+ - If any files were changed, a "changed_files=,,..." line.
+"""
+
+import argparse
+import re
+import sys
+from pathlib import Path
+
+
+def parse_version(version_str: str) -> tuple[int, ...]:
+ return tuple(int(x) for x in version_str.split("."))
+
+
+def normalize_pkg_pattern(pkg_name: str) -> str:
+ """Convert a package name into a regex pattern matching any PEP 503 equivalent."""
+ return re.sub(r"[-_.]", "[-_.]", pkg_name.lower())
+
+
+def update_pip_packages_line(line: str, pkg_name: str, new_version: str) -> tuple[str, bool, str]:
+ """Update the >= floor for a package inside a pip_packages string literal.
+
+ Matches entries like "pypdf>=6.7.2" or "mcp>=1.23.0,<2.0" inside Python
+ string literals on the given line.
+
+ Returns (new_line, changed, reason).
+ """
+ pkg_pattern = normalize_pkg_pattern(pkg_name)
+ lower_bound_re = re.compile(rf'("(?:{pkg_pattern})(?:\[[^\]]*\])?>=)([\d]+(?:\.[\d]+)*)', re.IGNORECASE)
+
+ match = lower_bound_re.search(line)
+ if not match:
+ return line, False, f"no >= lower bound for {pkg_name} on this line"
+
+ old_version = match.group(2)
+ if parse_version(new_version) <= parse_version(old_version):
+ return line, False, f"{pkg_name}: new version {new_version} <= current floor {old_version}"
+
+ upper_bound_re = re.compile(rf'"(?:{pkg_pattern})(?:\[[^\]]*\])?>=(?:[^"]*),<([\d]+(?:\.[\d]+)*)"', re.IGNORECASE)
+ upper_match = upper_bound_re.search(line)
+ if upper_match:
+ upper_version = upper_match.group(1)
+ if parse_version(new_version) >= parse_version(upper_version):
+ return line, False, (f"{pkg_name}: new version {new_version} >= upper bound <{upper_version}, skipping")
+
+ new_line = lower_bound_re.sub(lambda m: m.group(1) + new_version, line)
+ return new_line, True, f"{pkg_name}: updated >= floor from {old_version} to {new_version}"
+
+
+def find_matching_lines(lines: list[str], pkg_name: str) -> list[int]:
+ """Find line indices containing a pip_packages string literal for the given package with a >= floor."""
+ pkg_pattern = normalize_pkg_pattern(pkg_name)
+ pattern = re.compile(rf'"(?:{pkg_pattern})(?:\[[^\]]*\])?>=', re.IGNORECASE)
+ return [i for i, line in enumerate(lines) if pattern.search(line)]
+
+
+def update_file(filepath: Path, pkg_name: str, new_version: str) -> tuple[bool, list[str]]:
+ """Update all pip_packages >= floors for pkg_name in a single file.
+
+ Returns (changed, messages).
+ """
+ content = filepath.read_text()
+ lines = content.splitlines(keepends=True)
+ matching = find_matching_lines(lines, pkg_name)
+
+ if not matching:
+ return False, []
+
+ changed = False
+ messages = []
+ for idx in matching:
+ new_line, did_change, reason = update_pip_packages_line(lines[idx], pkg_name, new_version)
+ if did_change:
+ lines[idx] = new_line
+ changed = True
+ messages.append(f"UPDATED {filepath}: {reason}")
+ else:
+ messages.append(f"SKIP {filepath}: {reason}")
+
+ if changed:
+ filepath.write_text("".join(lines))
+
+ return changed, messages
+
+
+def main() -> int:
+ parser = argparse.ArgumentParser(description="Update pip_packages version floors in provider registry files")
+ parser.add_argument("--dependency-name", required=True)
+ parser.add_argument("--dependency-version", required=True)
+ parser.add_argument(
+ "--registry-dir",
+ default="src/ogx/providers/registry",
+ help="Path to the provider registry directory (default: src/ogx/providers/registry)",
+ )
+ args = parser.parse_args()
+
+ registry_dir = Path(args.registry_dir)
+ if not registry_dir.is_dir():
+ print(f"Registry directory not found: {registry_dir}", file=sys.stderr)
+ print("updated=false")
+ return 0
+
+ changed_files: list[str] = []
+
+ for py_file in sorted(registry_dir.glob("*.py")):
+ if py_file.name == "__init__.py":
+ continue
+ changed, messages = update_file(py_file, args.dependency_name, args.dependency_version)
+ for msg in messages:
+ print(msg)
+ if changed:
+ changed_files.append(str(py_file))
+
+ if changed_files:
+ print("updated=true")
+ print(f"changed_files={','.join(changed_files)}")
+ else:
+ print("updated=false")
+
+ return 0
+
+
+if __name__ == "__main__":
+ sys.exit(main())
diff --git a/.github/workflows/README.md b/.github/workflows/README.md
index 6b6c57121f9..f1915853155 100644
--- a/.github/workflows/README.md
+++ b/.github/workflows/README.md
@@ -17,9 +17,11 @@ OGX uses GitHub Actions for Continuous Integration (CI). Below is a table detail
| Integration Auth Tests | [integration-auth-tests.yml](integration-auth-tests.yml) | Run the integration test suite with Kubernetes authentication |
| Integration Responses, Conversations & Prompts Auth Tests | [integration-responses-conversations-auth-tests.yml](integration-responses-conversations-auth-tests.yml) | Run responses, conversations, and prompts auth tests with Kubernetes authentication |
| SqlStore Integration Tests | [integration-sql-store-tests.yml](integration-sql-store-tests.yml) | Run the integration test suite with SqlStore |
-| Messages API - Claude Code CLI Smoke Test | [integration-tests-messages-cli.yml](integration-tests-messages-cli.yml) | Drive the real Claude Code CLI against /v1/messages (live, Ollama) |
+| Responses API - Codex CLI Smoke Test | [integration-tests-codex-cli.yml](integration-tests-codex-cli.yml) | Manually drive the real Codex CLI against /v1/responses |
+| Messages API - Claude Code Client Smoke Tests | [integration-tests-messages-clients.yml](integration-tests-messages-clients.yml) | Drive the Claude Code CLI and Agent SDK against /v1/messages (live, Ollama) |
| Integration Tests (Replay) | [integration-tests.yml](integration-tests.yml) | Run the integration test suites from tests/integration in replay mode |
| Vector IO Integration Tests | [integration-vector-io-tests.yml](integration-vector-io-tests.yml) | Run the integration test suite with various VectorIO providers |
+| Launch GPU EC2 Runner | [launch-gpu-ec2-runner.yml](launch-gpu-ec2-runner.yml) | GPU recording for gpt-oss:20b (${{ inputs.suite }} suite) |
| OpenAPI Generator SDK Validation | [openapi-generator-validation.yml](openapi-generator-validation.yml) | Validate OpenAPI Generator SDK generation |
| OpenResponses Conformance Tests | [openresponses-conformance.yml](openresponses-conformance.yml) | Run OpenResponses conformance tests against ogx Responses API |
| Post-release automation | [post-release.yml](post-release.yml) | Post-release automation |
@@ -29,12 +31,14 @@ OGX uses GitHub Actions for Continuous Integration (CI). Below is a table detail
| Publish OpenAPI SDK to PyPI | [publish-openapi-sdk.yml](publish-openapi-sdk.yml) | Publish ogx-open-client to PyPI |
| Build, test, and publish packages | [pypi.yml](pypi.yml) | Build, test, and publish packages |
| Integration Tests (Record) | [record-integration-tests.yml](record-integration-tests.yml) | Auto-record missing test recordings for PR |
+| vLLM GPU Recording | [record-vllm-gpu-tests.yml](record-vllm-gpu-tests.yml) | GPU recording for gpt-oss:20b (${{ inputs.suite }} suite) |
| Release Branch Scheduled CI | [release-branch-scheduled-ci.yml](release-branch-scheduled-ci.yml) | Scheduled CI checks for active release branches |
| Check semantic PR titles | [semantic-pr.yml](semantic-pr.yml) | Ensure that PR titles follow the conventional commit spec |
-| Stainless SDK Builds | [stainless-builds.yml](stainless-builds.yml) | Build Stainless SDK from OpenAPI spec changes |
| Close stale issues and PRs | [stale_bot.yml](stale_bot.yml) | Run the Stale Bot action |
| Test External Providers Installed via Module | [test-external-provider-module.yml](test-external-provider-module.yml) | Test External Provider installation via Python module |
| Test External API and Providers | [test-external.yml](test-external.yml) | Test the External API and Provider mechanisms |
| Trigger Docs Deploy | [trigger-docs-deploy.yml](trigger-docs-deploy.yml) | Trigger docs site rebuild after docs change |
+| Trivy Scheduled Security Scan | [trivy-scheduled.yml](trivy-scheduled.yml) | Trivy Scheduled Security Scan |
+| Trivy Security Scan | [trivy-security.yml](trivy-security.yml) | Trivy Security Scan |
| UI Tests | [ui-unit-tests.yml](ui-unit-tests.yml) | Run the UI test suite |
| Unit Tests | [unit-tests.yml](unit-tests.yml) | Run the unit test suite |
diff --git a/.github/workflows/backward-compat.yml b/.github/workflows/backward-compat.yml
index 3d8eb94519f..e36b28bbca4 100644
--- a/.github/workflows/backward-compat.yml
+++ b/.github/workflows/backward-compat.yml
@@ -41,7 +41,7 @@ jobs:
python-version: '3.12'
- name: Install uv
- uses: astral-sh/setup-uv@08807647e7069bb48b6ef5acd8ec9567f424441b # v8.1.0
+ uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # v8.2.0
with:
enable-cache: true
@@ -451,7 +451,7 @@ jobs:
python-version: '3.12'
- name: Install uv
- uses: astral-sh/setup-uv@08807647e7069bb48b6ef5acd8ec9567f424441b # v8.1.0
+ uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # v8.2.0
with:
enable-cache: true
diff --git a/.github/workflows/build-distributions.yml b/.github/workflows/build-distributions.yml
index 00480e12023..64c55d1d162 100644
--- a/.github/workflows/build-distributions.yml
+++ b/.github/workflows/build-distributions.yml
@@ -20,6 +20,7 @@ on:
permissions:
contents: read
actions: write
+ security-events: write
env:
IMAGE_PREFIX: ogx/distribution
@@ -138,3 +139,23 @@ jobs:
run: |
LOCAL_IMAGE_NAME="${IMAGE_PREFIX}-${DISTRO_NAME}:${IMAGE_TAG}"
bash scripts/verify-config-labels.sh "${LOCAL_IMAGE_NAME}"
+
+ - name: Scan container image with Trivy
+ uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
+ env:
+ DISTRO_NAME: ${{ matrix.distro }}
+ IMAGE_TAG: ${{ needs.generate-matrix.outputs.version }}
+ with:
+ image-ref: '${{ env.IMAGE_PREFIX }}-${{ matrix.distro }}:${{ needs.generate-matrix.outputs.version }}'
+ scan-type: 'image'
+ severity: 'CRITICAL,HIGH'
+ exit-code: '0'
+ format: 'sarif'
+ output: 'trivy-container-${{ matrix.distro }}.sarif'
+
+ - name: Upload container scan results to GitHub Security
+ uses: github/codeql-action/upload-sarif@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ if: always()
+ with:
+ sarif_file: 'trivy-container-${{ matrix.distro }}.sarif'
+ category: 'trivy-container-${{ matrix.distro }}'
diff --git a/.github/workflows/ci-status.yml b/.github/workflows/ci-status.yml
index ca1eda6a418..eabe425d68a 100644
--- a/.github/workflows/ci-status.yml
+++ b/.github/workflows/ci-status.yml
@@ -19,7 +19,7 @@ concurrency:
jobs:
ci-status:
runs-on: ubuntu-latest
- timeout-minutes: 60
+ timeout-minutes: 180
permissions:
checks: read
steps:
@@ -43,8 +43,8 @@ jobs:
const excludedApps = new Set(['mergify']);
const terminalStatuses = new Set(['completed']);
- const successConclusions = new Set(['success', 'skipped', 'neutral']);
- const failureConclusions = new Set(['failure', 'cancelled', 'timed_out']);
+ const successConclusions = new Set(['success', 'skipped', 'neutral', 'cancelled']);
+ const failureConclusions = new Set(['failure', 'timed_out']);
while (true) {
const { data: checkRuns } = await github.rest.checks.listForRef({
@@ -92,10 +92,12 @@ jobs:
if (failed.length > 0) {
for (const cr of failed) {
- core.error(`${cr.name} concluded with: ${cr.conclusion}`);
+ core.warning(`${cr.name} concluded with: ${cr.conclusion} — waiting for re-run`);
}
- core.setFailed(`${failed.length} CI check(s) failed.`);
- return;
+ core.info(`${failed.length} check(s) failed. Waiting 30s for re-runs before giving up...`);
+ core.info('Re-run the failed job(s) and ci-status will pick up the result automatically.');
+ await new Promise(r => setTimeout(r, 30000));
+ continue;
}
const succeeded = completed.filter(cr => successConclusions.has(cr.conclusion));
diff --git a/.github/workflows/codeql.yml b/.github/workflows/codeql.yml
index a6720eda6bd..13ea3979a88 100644
--- a/.github/workflows/codeql.yml
+++ b/.github/workflows/codeql.yml
@@ -23,7 +23,7 @@ jobs:
# Initializes CodeQL tools for scanning.
- name: Initialize CodeQL
- uses: github/codeql-action/init@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ uses: github/codeql-action/init@8aad20d150bbac5944a9f9d289da16a4b0d87c1e # v3
with:
languages: ${{ matrix.language }}
# "security-extended" is recommended for higher severity coverage - not necessary can be removed to speed up
@@ -32,6 +32,6 @@ jobs:
# Scans the code and uploads results to GitHub Security tab.
# The "Fail on High" logic is handled by Branch Protection Rules in Settings
- name: Perform CodeQL Analysis
- uses: github/codeql-action/analyze@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ uses: github/codeql-action/analyze@8aad20d150bbac5944a9f9d289da16a4b0d87c1e # v3
with:
category: "/language:${{ matrix.language }}"
diff --git a/.github/workflows/commit-constraint-updates.yml b/.github/workflows/commit-constraint-updates.yml
index 2bf268acd0a..9ba87e6fbdf 100644
--- a/.github/workflows/commit-constraint-updates.yml
+++ b/.github/workflows/commit-constraint-updates.yml
@@ -103,11 +103,13 @@ jobs:
CHANGED=$(jq -r '.changed' constraint-update/change-info.json)
DEP_NAME=$(jq -r '.dep_name' constraint-update/change-info.json)
DEP_VERSION=$(jq -r '.dep_version' constraint-update/change-info.json)
+ REGISTRY_CHANGED=$(jq -r '.registry_changed // "false"' constraint-update/change-info.json)
{
echo "changed=$CHANGED"
echo "dep_name=$DEP_NAME"
echo "dep_version=$DEP_VERSION"
+ echo "registry_changed=$REGISTRY_CHANGED"
} >> "$GITHUB_OUTPUT"
if [ "$CHANGED" != "true" ]; then
@@ -226,6 +228,16 @@ jobs:
echo "Copied updated src/ogx_api/uv.lock"
fi
+ - name: Copy updated registry files to repo
+ if: steps.download-update.outputs.skip != 'true' && steps.changes.outputs.skip != 'true' && steps.pr-info.outputs.skip != 'true'
+ run: |
+ for f in constraint-update/src/ogx/providers/registry/*.py; do
+ [ -f "$f" ] || continue
+ target="src/ogx/providers/registry/$(basename "$f")"
+ cp "$f" "$target"
+ echo "Copied updated $target"
+ done
+
- name: Commit and push constraint updates
id: commit
if: steps.download-update.outputs.skip != 'true' && steps.changes.outputs.skip != 'true' && steps.pr-info.outputs.skip != 'true'
@@ -241,13 +253,16 @@ jobs:
git config user.name "github-actions[bot]"
git config user.email "github-actions[bot]@users.noreply.github.com"
- if [[ -z $(git status --porcelain pyproject.toml uv.lock src/ogx_api/pyproject.toml src/ogx_api/uv.lock) ]]; then
+ TRACKED_FILES=(pyproject.toml uv.lock src/ogx_api/pyproject.toml src/ogx_api/uv.lock)
+ mapfile -t REGISTRY_FILES < <(find src/ogx/providers/registry -name '*.py' 2>/dev/null)
+
+ if [[ -z $(git status --porcelain "${TRACKED_FILES[@]}" "${REGISTRY_FILES[@]}") ]]; then
echo "No changes to commit"
echo "pushed=false" >> "$GITHUB_OUTPUT"
exit 0
fi
- git add pyproject.toml uv.lock src/ogx_api/pyproject.toml src/ogx_api/uv.lock
+ git add "${TRACKED_FILES[@]}" "${REGISTRY_FILES[@]}"
git commit -s -m "fix(deps): update constraint-dependencies for ${DEP_NAME}"
if [ "$IS_FORK_PR" = "true" ]; then
@@ -281,18 +296,25 @@ jobs:
PR_NUMBER: ${{ steps.pr-info.outputs.pr_number }}
DEP_NAME: ${{ steps.changes.outputs.dep_name }}
DEP_VERSION: ${{ steps.changes.outputs.dep_version }}
+ REGISTRY_CHANGED: ${{ steps.changes.outputs.registry_changed }}
with:
script: |
const prNumber = parseInt(process.env.PR_NUMBER, 10);
const depName = process.env.DEP_NAME;
const depVersion = process.env.DEP_VERSION;
+ const registryChanged = process.env.REGISTRY_CHANGED === 'true';
const runUrl = `${context.serverUrl}/${context.repo.owner}/${context.repo.repo}/actions/runs/${context.runId}`;
const COMMENT_MARKER = '';
+ let body = `Updated \`pyproject.toml\` constraint for \`${depName}\` to \`>=${depVersion}\` ` +
+ `and regenerated \`uv.lock\`.`;
+ if (registryChanged) {
+ body += `\nAlso updated \`pip_packages\` version floor in provider registry files.`;
+ }
+
const message = `${COMMENT_MARKER}\n` +
`✅ **Constraint-dependencies updated**\n\n` +
- `Updated \`pyproject.toml\` constraint for \`${depName}\` to \`>=${depVersion}\` ` +
- `and regenerated \`uv.lock\`.\n\n` +
+ `${body}\n\n` +
`[View commit workflow](${runUrl})`;
try {
diff --git a/.github/workflows/commit-recordings.yml b/.github/workflows/commit-recordings.yml
index 0eb02e6d5a8..0e151e35793 100644
--- a/.github/workflows/commit-recordings.yml
+++ b/.github/workflows/commit-recordings.yml
@@ -1,11 +1,11 @@
-# Commits recordings from the record-integration-tests.yml workflow back to PRs.
+# Commits recordings from recording workflows back to PRs.
# This workflow runs with elevated permissions but only executes trusted code from the base repo.
-# Triggered via workflow_run after record-integration-tests.yml completes successfully.
+# Triggered via workflow_run after recording workflows complete successfully.
name: Commit Recordings
on:
workflow_run:
- workflows: ["Integration Tests (Record)"]
+ workflows: ["Integration Tests (Record)", "Launch GPU EC2 Runner", "vLLM GPU Recording"]
types:
- completed
@@ -105,6 +105,7 @@ jobs:
let headRepo = null;
let headRef = null;
let headSha = null;
+ let commitMode = null;
// Try to load from metadata artifact first
if (fs.existsSync('pr-info.json')) {
@@ -114,12 +115,30 @@ jobs:
headRepo = metadata.pr_head_repo;
headRef = metadata.pr_head_ref;
headSha = metadata.pr_head_sha;
- console.log(`Loaded PR info from metadata: PR #${prNumber}`);
+ commitMode = metadata.commit_mode || null;
+ console.log(`Loaded PR info from metadata: PR #${prNumber}, commit_mode=${commitMode}`);
} catch (e) {
console.log(`Failed to parse metadata: ${e.message}`);
}
}
+ // Branch mode: a dispatch on a branch (e.g. main) with no PR.
+ // Open a fresh PR with the recordings instead of pushing to an existing PR branch.
+ if (commitMode === 'branch') {
+ if (!headRef || !headRepo) {
+ console.log('Branch mode requested but base branch/repo missing, skipping');
+ core.setOutput('skip', 'true');
+ return;
+ }
+ console.log(`Branch mode: will open a recordings PR against ${headRepo}@${headRef}`);
+ core.setOutput('commit_to_branch', 'true');
+ core.setOutput('base_branch', headRef);
+ core.setOutput('head_repo', headRepo);
+ core.setOutput('head_ref', headRef);
+ core.setOutput('is_fork_pr', 'false');
+ return;
+ }
+
// Fallback: check if triggered by pull_request event
if (!prNumber) {
const runInfo = await github.rest.actions.getWorkflowRun({
@@ -148,6 +167,18 @@ jobs:
}
}
+ const prData = await github.rest.pulls.get({
+ owner: context.repo.owner,
+ repo: context.repo.repo,
+ pull_number: prNumber,
+ });
+
+ if (prData.data.head.sha !== headSha) {
+ core.warning(`PR #${prNumber} moved from ${headSha} to ${prData.data.head.sha}; skipping stale recording artifacts.`);
+ core.setOutput('skip', 'true');
+ return;
+ }
+
core.setOutput('pr_number', prNumber);
core.setOutput('head_repo', headRepo);
core.setOutput('head_ref', headRef);
@@ -234,11 +265,15 @@ jobs:
id: commit
if: steps.pr-info.outputs.skip != 'true'
env:
- GH_TOKEN: ${{ steps.pr-info.outputs.is_fork_pr == 'true' && secrets.RELEASE_PAT || github.token }}
+ # Branch mode and fork pushes need RELEASE_PAT: it can push to the base repo and,
+ # for branch mode, lets the opened PR trigger CI (github.token-created PRs don't).
+ GH_TOKEN: ${{ (steps.pr-info.outputs.is_fork_pr == 'true' || steps.pr-info.outputs.commit_to_branch == 'true') && secrets.RELEASE_PAT || github.token }}
PR_NUMBER: ${{ steps.pr-info.outputs.pr_number }}
HEAD_REPO: ${{ steps.pr-info.outputs.head_repo }}
HEAD_REF: ${{ steps.pr-info.outputs.head_ref }}
IS_FORK_PR: ${{ steps.pr-info.outputs.is_fork_pr }}
+ COMMIT_TO_BRANCH: ${{ steps.pr-info.outputs.commit_to_branch }}
+ BASE_BRANCH: ${{ steps.pr-info.outputs.base_branch }}
BASE_REPO: ${{ github.repository }}
run: |
# Configure git
@@ -255,8 +290,29 @@ jobs:
echo "Recording changes detected, committing..."
git add tests/integration/recordings/ tests/integration/*/recordings/
+ # Branch mode: open a new PR against the dispatched branch instead of pushing
+ # recordings into an existing PR branch.
+ if [ "$COMMIT_TO_BRANCH" = "true" ]; then
+ NEW_BRANCH="ci/update-recordings-${GITHUB_RUN_ID}"
+ echo "Branch mode: committing recordings to $NEW_BRANCH and opening a PR against $BASE_BRANCH"
+ git checkout -b "$NEW_BRANCH"
+ git commit -m "ci: update integration test recordings
+
+ Co-Authored-By: github-actions[bot] "
+ git push "https://x-access-token:${GH_TOKEN}@github.com/${BASE_REPO}.git" "HEAD:${NEW_BRANCH}"
+ gh pr create \
+ --repo "$BASE_REPO" \
+ --base "$BASE_BRANCH" \
+ --head "$NEW_BRANCH" \
+ --title "ci: update integration test recordings" \
+ --body "Automated recording refresh from the [record workflow](${GITHUB_SERVER_URL}/${BASE_REPO}/actions/runs/${GITHUB_RUN_ID}) dispatched on \`${BASE_BRANCH}\`."
+ echo "pushed=true" >> "$GITHUB_OUTPUT"
+ exit 0
+ fi
+
git commit -m "Recordings update from CI
+ Signed-off-by: github-actions[bot]
Co-Authored-By: github-actions[bot] "
# Push to PR branch
@@ -285,7 +341,7 @@ jobs:
fi
- name: Comment on PR
- if: steps.commit.outputs.pushed == 'true'
+ if: steps.commit.outputs.pushed == 'true' && steps.pr-info.outputs.commit_to_branch != 'true'
uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
env:
PR_NUMBER: ${{ steps.pr-info.outputs.pr_number }}
diff --git a/.github/workflows/dependabot-constraints.yml b/.github/workflows/dependabot-constraints.yml
index 58d51cb87b3..81cad22157b 100644
--- a/.github/workflows/dependabot-constraints.yml
+++ b/.github/workflows/dependabot-constraints.yml
@@ -44,7 +44,7 @@ jobs:
python-version: '3.12'
- name: Set up uv
- uses: astral-sh/setup-uv@08807647e7069bb48b6ef5acd8ec9567f424441b # v8.1.0
+ uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # v8.2.0
- name: Parse dependency info from Dependabot commit
id: parse
@@ -117,6 +117,27 @@ jobs:
echo "changed=$changed" >> "$GITHUB_OUTPUT"
+ - name: Update pip_packages version floors in provider registry
+ if: steps.parse.outputs.skip != 'true'
+ id: registry
+ env:
+ DEP_NAME: ${{ steps.parse.outputs.dep_name }}
+ DEP_VERSION: ${{ steps.parse.outputs.dep_version }}
+ run: |
+ output=$(python3 .github/scripts/update_registry_deps.py \
+ --dependency-name "$DEP_NAME" \
+ --dependency-version "$DEP_VERSION")
+
+ echo "$output"
+
+ if echo "$output" | grep -q "updated=true"; then
+ changed_files=$(echo "$output" | grep "^changed_files=" | cut -d= -f2)
+ echo "changed=true" >> "$GITHUB_OUTPUT"
+ echo "changed_files=$changed_files" >> "$GITHUB_OUTPUT"
+ else
+ echo "changed=false" >> "$GITHUB_OUTPUT"
+ fi
+
- name: Regenerate uv.lock files
if: steps.update.outputs.changed == 'true'
env:
@@ -170,21 +191,30 @@ jobs:
- name: Prepare constraint update artifact
if: steps.parse.outputs.skip != 'true'
env:
- CHANGED: ${{ steps.update.outputs.changed }}
+ PYPROJECT_CHANGED: ${{ steps.update.outputs.changed }}
+ REGISTRY_CHANGED: ${{ steps.registry.outputs.changed }}
+ REGISTRY_FILES: ${{ steps.registry.outputs.changed_files }}
DEP_NAME: ${{ steps.parse.outputs.dep_name }}
DEP_VERSION: ${{ steps.parse.outputs.dep_version }}
TARGET_PYPROJECTS: ${{ steps.target.outputs.pyprojects }}
run: |
+ if [ "$PYPROJECT_CHANGED" = "true" ] || [ "$REGISTRY_CHANGED" = "true" ]; then
+ CHANGED=true
+ else
+ CHANGED=false
+ fi
+
mkdir -p constraint-update
cat > constraint-update/change-info.json <> "$GITHUB_PATH"
"$HOME/.local/bin/claude" --version
- - name: Run Claude Code CLI smoke test
+ - name: Install Claude Agent SDK
+ run: uv pip install "claude-agent-sdk==${CLAUDE_AGENT_SDK_VERSION}"
+
+ - name: Run Claude Code client smoke tests
uses: ./.github/actions/run-and-record-tests
with:
stack-config: 'server:ci-tests'
setup: 'ollama'
suite: 'messages'
inference-mode: 'live'
- pattern: 'test_claude_code_cli_smoke'
+ # Selects both test_claude_code_cli_smoke and test_claude_agent_sdk_smoke.
+ # Must stay a single shell word: run-and-record-tests passes --pattern
+ # unquoted, so a -k expression with spaces would be split into separate
+ # arguments.
+ pattern: 'test_claude'
diff --git a/.github/workflows/integration-tests.yml b/.github/workflows/integration-tests.yml
index a933d4c29a4..447adf88cdf 100644
--- a/.github/workflows/integration-tests.yml
+++ b/.github/workflows/integration-tests.yml
@@ -51,7 +51,7 @@ on:
required: false
type: string
default: 'default'
- description: 'Matrix configuration key from ci_matrix.json (e.g., "default", "stainless")'
+ description: 'Matrix configuration key from ci_matrix.json (e.g., "default")'
matrix_json:
required: false
type: string
@@ -87,8 +87,7 @@ concurrency:
# Limit permissions of the GITHUB_TOKEN to the minimum required.
# Default mode is 'replay' which only needs read access.
-# When called via workflow_call (e.g., from stainless-builds.yml with record-if-missing),
-# the caller's permissions apply.
+# When called via workflow_call, the caller's permissions apply.
permissions:
contents: read
@@ -204,6 +203,7 @@ jobs:
WATSONX_PROJECT_ID: replay-mode-dummy-project
VERTEX_AI_PROJECT: ${{ matrix.config.setup == 'vertexai' && 'replay-mode-dummy-project' || '' }}
VERTEX_AI_LOCATION: ${{ matrix.config.setup == 'vertexai' && 'global' || '' }}
+ AWS_BEDROCK_BEARER_TOKEN: replay-mode-dummy-key
AWS_BEARER_TOKEN_BEDROCK: replay-mode-dummy-key
AWS_DEFAULT_REGION: us-west-2
GEMINI_API_KEY: replay-mode-dummy-key
diff --git a/.github/workflows/integration-vector-io-tests.yml b/.github/workflows/integration-vector-io-tests.yml
index 1fcbe3fe839..0ef00a8b1cc 100644
--- a/.github/workflows/integration-vector-io-tests.yml
+++ b/.github/workflows/integration-vector-io-tests.yml
@@ -195,10 +195,23 @@ jobs:
docker logs infinispan
exit 1
+ - name: Cache Hugging Face models
+ uses: actions/cache@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
+ with:
+ path: ~/.cache/huggingface
+ key: hf-${{ runner.os }}-${{ matrix.python-version }}-nomic-embed-text-v1.5
+
- name: Build OGX
run: |
uv run --no-sync ogx stack list-deps ci-tests | xargs -L1 uv pip install
+ - name: Pre-download embedding model
+ run: |
+ uv run --no-sync python - <<'PY'
+ from sentence_transformers import SentenceTransformer
+ SentenceTransformer("nomic-ai/nomic-embed-text-v1.5", trust_remote_code=True)
+ PY
+
- name: Check Storage and Memory Available Before Tests
if: ${{ always() }}
run: |
@@ -207,6 +220,8 @@ jobs:
- name: Run Vector IO Integration Tests
env:
+ HF_HUB_OFFLINE: "1"
+ TRANSFORMERS_OFFLINE: "1"
ENABLE_CHROMADB: ${{ matrix.vector-io-provider == 'remote::chromadb' && 'true' || '' }}
CHROMADB_URL: ${{ matrix.vector-io-provider == 'remote::chromadb' && 'http://localhost:8000' || '' }}
ENABLE_PGVECTOR: ${{ matrix.vector-io-provider == 'remote::pgvector' && 'true' || '' }}
diff --git a/.github/workflows/launch-gpu-ec2-runner.yml b/.github/workflows/launch-gpu-ec2-runner.yml
new file mode 100644
index 00000000000..d0a96a2c2c1
--- /dev/null
+++ b/.github/workflows/launch-gpu-ec2-runner.yml
@@ -0,0 +1,429 @@
+name: 'Launch GPU EC2 Runner'
+
+run-name: GPU recording for gpt-oss:20b (${{ inputs.suite }} suite)
+
+on:
+ workflow_dispatch:
+ inputs:
+ suite:
+ description: 'Test suite to run'
+ required: false
+ type: choice
+ default: 'base'
+ options:
+ - base
+ - responses
+ - vllm-reasoning
+ pr_number:
+ description: 'PR number to commit recordings back to. Leave empty to use the open PR for this branch.'
+ required: false
+ type: string
+
+concurrency:
+ group: gpu-vllm-record-${{ github.run_id }}
+ cancel-in-progress: false # Don't cancel - EC2 cleanup is critical
+
+# OIDC authentication for AWS - no long-lived credentials!
+permissions:
+ contents: read
+ pull-requests: read # Required to locate the PR branch for the commit-recordings workflow
+ actions: read # Required for the hosted cleanup job to watch the GPU job state
+ id-token: write # Required for OIDC authentication to AWS
+
+jobs:
+ # Job 0: Publish PR metadata for the trusted follow-up commit workflow
+ compute-pr-info:
+ runs-on: ubuntu-latest
+ outputs:
+ pr_number: ${{ steps.pr-info.outputs.pr_number }}
+ pr_head_ref: ${{ steps.pr-info.outputs.pr_head_ref }}
+ pr_head_sha: ${{ steps.pr-info.outputs.pr_head_sha }}
+ pr_head_repo: ${{ steps.pr-info.outputs.pr_head_repo }}
+ is_fork_pr: ${{ steps.pr-info.outputs.is_fork_pr }}
+ steps:
+ - name: Locate PR branch
+ id: pr-info
+ uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
+ env:
+ INPUT_PR_NUMBER: ${{ inputs.pr_number }}
+ with:
+ script: |
+ const inputPrNumber = process.env.INPUT_PR_NUMBER;
+ let pr = null;
+
+ if (inputPrNumber) {
+ const response = await github.rest.pulls.get({
+ owner: context.repo.owner,
+ repo: context.repo.repo,
+ pull_number: Number(inputPrNumber),
+ });
+ pr = response.data;
+ } else {
+ const branch = context.ref.replace('refs/heads/', '');
+ const response = await github.rest.pulls.list({
+ owner: context.repo.owner,
+ repo: context.repo.repo,
+ state: 'open',
+ head: `${context.repo.owner}:${branch}`,
+ per_page: 1,
+ });
+ pr = response.data[0];
+ }
+
+ if (!pr) {
+ core.setFailed('No open PR found for this workflow run. Pass pr_number when dispatching from a non-PR branch.');
+ return;
+ }
+
+ if (pr.head.repo.full_name !== `${context.repo.owner}/${context.repo.repo}`) {
+ core.setFailed('GPU recording only supports same-repository PR branches.');
+ return;
+ }
+
+ if (pr.head.sha !== context.sha) {
+ core.setFailed(`Dispatch this workflow from the PR branch head. PR #${pr.number} is at ${pr.head.sha}, but this run is using ${context.sha}.`);
+ return;
+ }
+
+ core.setOutput('pr_number', String(pr.number));
+ core.setOutput('pr_head_ref', pr.head.ref);
+ core.setOutput('pr_head_sha', pr.head.sha);
+ core.setOutput('pr_head_repo', pr.head.repo.full_name);
+ core.setOutput('is_fork_pr', String(pr.head.repo.full_name !== `${context.repo.owner}/${context.repo.repo}`));
+
+ - name: Create PR metadata artifact
+ if: steps.pr-info.outputs.pr_number != ''
+ env:
+ PR_NUMBER: ${{ steps.pr-info.outputs.pr_number }}
+ PR_HEAD_REF: ${{ steps.pr-info.outputs.pr_head_ref }}
+ PR_HEAD_SHA: ${{ steps.pr-info.outputs.pr_head_sha }}
+ PR_HEAD_REPO: ${{ steps.pr-info.outputs.pr_head_repo }}
+ IS_FORK_PR: ${{ steps.pr-info.outputs.is_fork_pr }}
+ run: |
+ mkdir -p pr-metadata
+ cat > pr-metadata/pr-info.json <> "$GITHUB_OUTPUT"
+
+ - name: Run integration tests (record mode)
+ uses: ./.github/actions/run-and-record-tests
+ with:
+ stack-config: 'server:ci-tests'
+ setup: 'vllm-gpu-gpt-oss'
+ inference-mode: 'record'
+ suite: ${{ inputs.suite }}
+ pattern: ${{ steps.test-pattern.outputs.pattern }}
+ skip-commit: 'true' # Don't commit here - upload as artifacts
+
+ - name: Upload recordings as artifacts
+ if: always()
+ uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+ with:
+ name: recordings-vllm-gpu-gpt-oss-${{ inputs.suite }}-${{ github.run_id }}-${{ github.run_attempt || '1' }}
+ path: |
+ tests/integration/recordings/
+ tests/integration/*/recordings/
+ retention-days: 7
+ if-no-files-found: error
+
+ - name: Upload vLLM logs
+ if: always()
+ run: |
+ if [ -f /tmp/vllm-server.log ]; then
+ cat /tmp/vllm-server.log
+ fi
+
+ - name: Disk space after tests
+ if: always()
+ run: |
+ echo "=== Disk Space After Tests ==="
+ df -h
+
+ # Job 3: Stop GPU EC2 instance (ALWAYS runs for cleanup)
+ stop-gpu-runner:
+ needs: start-gpu-runner
+ runs-on: ubuntu-latest
+ if: ${{ always() }} # CRITICAL: Always cleanup, even on failure or cancellation
+ steps:
+ - name: Checkout code
+ uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+ with:
+ persist-credentials: false
+
+ - name: Configure AWS credentials via OIDC
+ if: needs.start-gpu-runner.outputs.instance-id != ''
+ uses: aws-actions/configure-aws-credentials@e3dd6a429d7300a6a4c196c26e071d42e0343502 # v4.0.2
+ with:
+ role-to-assume: ${{ secrets.AWS_ROLE_ARN }}
+ aws-region: us-east-2
+ role-session-name: GitHubActions-vLLM-GPU-Cleanup-${{ github.run_id }}
+
+ - name: Wait for GPU test job before cleanup
+ if: needs.start-gpu-runner.outputs.instance-id != ''
+ env:
+ GH_TOKEN: ${{ github.token }}
+ RECORD_JOB_NAME: record-vllm-tests
+ RUN_ID: ${{ github.run_id }}
+ REPOSITORY: ${{ github.repository }}
+ run: |
+ queued_deadline=$((SECONDS + 1200))
+ absolute_deadline=$((SECONDS + 7200))
+
+ while true; do
+ job_status="$(
+ gh api "repos/${REPOSITORY}/actions/runs/${RUN_ID}/jobs" --paginate \
+ --jq ".jobs[] | select(.name == \"${RECORD_JOB_NAME}\") | [.status, (.conclusion // \"\")] | @tsv" \
+ | tail -n 1
+ )"
+
+ status="$(printf '%s' "$job_status" | cut -f1)"
+ conclusion="$(printf '%s' "$job_status" | cut -f2)"
+
+ if [ "$status" = "completed" ]; then
+ echo "GPU test job completed with conclusion: ${conclusion:-unknown}"
+ break
+ fi
+
+ if [ -z "$status" ]; then
+ echo "Waiting for GPU test job to be created..."
+ else
+ echo "GPU test job status: $status"
+ fi
+
+ if [ "$status" != "in_progress" ] && [ "$SECONDS" -ge "$queued_deadline" ]; then
+ echo "GPU test job did not start within 20 minutes; cleaning up the EC2 runner."
+ break
+ fi
+
+ if [ "$SECONDS" -ge "$absolute_deadline" ]; then
+ echo "GPU test job exceeded the 2 hour cleanup deadline; cleaning up the EC2 runner."
+ break
+ fi
+
+ sleep 30
+ done
+
+ - name: Stop EC2 runner
+ if: needs.start-gpu-runner.outputs.instance-id != ''
+ uses: ./.github/actions/launch-gpu-runner
+ with:
+ mode: stop
+ github-token: ${{ secrets.RELEASE_PAT }}
+ aws-region: us-east-2
+ label: ${{ needs.start-gpu-runner.outputs.label }}
+ ec2-instance-id: ${{ needs.start-gpu-runner.outputs.instance-id }}
+
+ - name: Cleanup summary
+ if: needs.start-gpu-runner.outputs.instance-id != ''
+ run: |
+ echo "GPU runner terminated successfully"
+ echo " Instance ID: ${{ needs.start-gpu-runner.outputs.instance-id }}"
+
+ - name: Cleanup skipped
+ if: needs.start-gpu-runner.outputs.instance-id == ''
+ run: |
+ echo "No EC2 instance id was produced by start-gpu-runner; nothing to terminate."
+
+ # Job 4: Summary and next steps
+ summary:
+ needs: [start-gpu-runner, record-vllm-tests, stop-gpu-runner]
+ runs-on: ubuntu-latest
+ if: always()
+ steps:
+ - name: Workflow summary
+ run: |
+ {
+ echo "## vLLM GPU Recording Summary"
+ echo ""
+ echo "**Model**: gpt-oss:20b"
+ echo "**Instance Type**: g6.2xlarge"
+ echo "**Test Suite**: ${{ inputs.suite }}"
+ echo ""
+
+ if [ "${{ needs.record-vllm-tests.result }}" == "success" ]; then
+ echo "**Test Status**: Successful"
+ echo ""
+ echo "Recordings have been uploaded as artifacts. The trusted Commit Recordings workflow will commit them back to the PR branch when PR metadata is available."
+ else
+ echo "**Test Status**: Failed"
+ echo ""
+ echo "Check the test logs for errors."
+ fi
+
+ echo ""
+ echo "**Cleanup Status**: ${{ needs.stop-gpu-runner.result == 'success' && 'Instance terminated' || 'Check manually' }}"
+ } >> "$GITHUB_STEP_SUMMARY"
+
+ - name: Check for cleanup issues
+ if: needs.stop-gpu-runner.result != 'success'
+ run: |
+ echo "::warning::EC2 instance cleanup may have failed! Check AWS console for orphaned instances."
+ echo "Instance ID: ${{ needs.start-gpu-runner.outputs.instance-id }}"
diff --git a/.github/workflows/openapi-generator-validation.yml b/.github/workflows/openapi-generator-validation.yml
index 4a8f1863528..e7eb537ad79 100644
--- a/.github/workflows/openapi-generator-validation.yml
+++ b/.github/workflows/openapi-generator-validation.yml
@@ -185,9 +185,9 @@ jobs:
echo "OpenAPI spec generated successfully"
ls -lh openapi.yml
- - name: Generate Python SDK (for CI testing with ogx_client name)
+ - name: Generate Python SDK
working-directory: client-sdks/openapi
- run: make sdk OPEN=0
+ run: make sdk OPEN=1
- name: Validate generated SDK
working-directory: client-sdks/openapi
@@ -217,16 +217,14 @@ jobs:
- name: Install generated SDK
run: |
- echo "Installing OpenAPI-generated SDK (ogx_client)..."
- # Uninstall existing client (note: uv pip uninstall doesn't support -y flag)
- uv pip uninstall ogx-client || true
+ echo "Reinstalling OpenAPI-generated SDK (ogx_open_client)..."
+ uv pip uninstall ogx-open-client || true
- # Install SDK using uv pip - this ensures proper editable install
+ # Install SDK using uv pip
uv pip install -e client-sdks/openapi/sdks/python
echo "Verifying installation..."
- # Use 'uv run python' to ensure we use the correct Python in the venv
- uv run python -c "import ogx_client; print(f'Installed: {ogx_client.__name__}')"
+ uv run python -c "import ogx_open_client; print(f'Installed: {ogx_open_client.__name__}')"
- name: Setup Ollama (for integration tests)
if: runner.os == 'Linux'
@@ -244,7 +242,7 @@ jobs:
|| echo "::warning::Some integration tests failed - this may indicate SDK compatibility issues"
# Show which SDK is actually being used
- uv run python -c "import ogx_client; import inspect; print(f'SDK location: {inspect.getfile(ogx_client)}')"
+ uv run python -c "import ogx_open_client; import inspect; print(f'SDK location: {inspect.getfile(ogx_open_client)}')"
- name: Summary
if: runner.os == 'Linux'
@@ -257,5 +255,5 @@ jobs:
echo "✅ Integration tests executed (check logs for results)"
echo ""
echo "**Platform**: ${{ matrix.os }}"
- echo "**Package**: ogx_client (OpenAPI-generated)"
+ echo "**Package**: ogx_open_client (OpenAPI-generated)"
} >> "$GITHUB_STEP_SUMMARY"
diff --git a/.github/workflows/openresponses-conformance.yml b/.github/workflows/openresponses-conformance.yml
index df7f1ac3a47..3a20a7abb12 100644
--- a/.github/workflows/openresponses-conformance.yml
+++ b/.github/workflows/openresponses-conformance.yml
@@ -2,9 +2,8 @@ name: OpenResponses Conformance Tests
run-name: Run OpenResponses conformance tests against ogx Responses API
-# This job is OPTIONAL and informational — it tracks progress toward full
-# conformance with the OpenResponses spec (https://openresponses.org).
-# Failures are expected while gaps remain in the Responses API implementation.
+# This job is REQUIRED — it enforces conformance with the OpenResponses spec
+# (https://openresponses.org). Any failing conformance test fails the job.
# See: https://github.com/ogx-ai/ogx/issues/4818
#
# Inference calls are replayed from checked-in recordings under
@@ -18,8 +17,10 @@ on:
- main
- 'release-[0-9]+.[0-9]+.x'
paths:
- - 'src/ogx/providers/inline/agents/**'
- - 'src/ogx/apis/agents/**'
+ - 'src/ogx/providers/inline/responses/**'
+ - 'src/ogx_api/responses/**'
+ - 'src/ogx_api/openai_responses.py'
+ - 'src/ogx/core/server/auth.py'
- 'tests/integration/openresponses/**'
- '.github/workflows/openresponses-conformance.yml'
pull_request:
@@ -27,8 +28,10 @@ on:
- main
- 'release-[0-9]+.[0-9]+.x'
paths:
- - 'src/ogx/providers/inline/agents/**'
- - 'src/ogx/apis/agents/**'
+ - 'src/ogx/providers/inline/responses/**'
+ - 'src/ogx_api/responses/**'
+ - 'src/ogx_api/openai_responses.py'
+ - 'src/ogx/core/server/auth.py'
- 'tests/integration/openresponses/**'
- '.github/workflows/openresponses-conformance.yml'
merge_group:
@@ -139,9 +142,8 @@ jobs:
{
echo "## OpenResponses Conformance Test Results"
echo ""
- echo "> **Note:** These tests are **informational only** and track progress toward full"
- echo "> [OpenResponses](https://www.openresponses.org) API conformance."
- echo "> Failures are expected while gaps remain in the Responses API implementation."
+ echo "> These tests enforce [OpenResponses](https://www.openresponses.org) API"
+ echo "> conformance. Any failing test fails this job."
echo "> See [#4818](https://github.com/ogx-ai/ogx/issues/4818)."
echo ""
echo "**Model:** \`$INFERENCE_MODEL\`"
@@ -212,6 +214,19 @@ jobs:
} >> "$GITHUB_STEP_SUMMARY"
fi
+ - name: Enforce conformance
+ run: |
+ if [ ! -f /tmp/openresponses-results.json ] || ! jq -e '.summary' /tmp/openresponses-results.json > /dev/null 2>&1; then
+ echo "::error::No parseable OpenResponses conformance results were produced."
+ exit 1
+ fi
+ FAILED=$(jq -r '.summary.failed' /tmp/openresponses-results.json)
+ if [ "$FAILED" -gt 0 ]; then
+ echo "::error::$FAILED OpenResponses conformance test(s) failed."
+ exit 1
+ fi
+ echo "All OpenResponses conformance tests passed."
+
- name: Upload conformance test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
diff --git a/.github/workflows/post-release.yml b/.github/workflows/post-release.yml
index 792f12a8d8e..2aa322bf48c 100644
--- a/.github/workflows/post-release.yml
+++ b/.github/workflows/post-release.yml
@@ -120,7 +120,7 @@ jobs:
echo "Pushed tag $DEV_TAG to main ($MAIN_SHA)"
- name: Set up uv
- uses: astral-sh/setup-uv@08807647e7069bb48b6ef5acd8ec9567f424441b # v8.1.0
+ uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # v8.2.0
# -----------------------------------------------------------------------
# Step B: Bump fallback_version on main and open PR
diff --git a/.github/workflows/pre-commit.yml b/.github/workflows/pre-commit.yml
index 9cd58583b62..08dabaecf88 100644
--- a/.github/workflows/pre-commit.yml
+++ b/.github/workflows/pre-commit.yml
@@ -52,7 +52,7 @@ jobs:
cache-dependency-path: 'src/ogx_ui/'
- name: Set up uv
- uses: astral-sh/setup-uv@08807647e7069bb48b6ef5acd8ec9567f424441b # v8.1.0
+ uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # v8.2.0
- name: Install npm dependencies
run: npm ci
diff --git a/.github/workflows/publish-openapi-sdk.yml b/.github/workflows/publish-openapi-sdk.yml
index c1e6905f494..e200a13746b 100644
--- a/.github/workflows/publish-openapi-sdk.yml
+++ b/.github/workflows/publish-openapi-sdk.yml
@@ -13,6 +13,10 @@ on:
options:
- testpypi
- pypi
+ version:
+ description: 'Version override (e.g., "1.2.0"). Leave empty to auto-detect from tag or fallback_version.'
+ required: false
+ type: string
dry_run:
description: 'Dry run (build only, no publish)'
type: boolean
@@ -27,13 +31,40 @@ concurrency:
permissions:
contents: read
- id-token: write # Required for trusted publishing to PyPI
jobs:
- publish-sdk:
+ compute-version:
+ name: Compute version
+ runs-on: ubuntu-latest
+ outputs:
+ version: ${{ steps.version.outputs.version }}
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+
+ - name: Compute SDK version
+ id: version
+ run: |
+ if [ -n "${{ inputs.version }}" ]; then
+ # Explicit override from workflow_dispatch
+ VERSION="${{ inputs.version }}"
+ elif [[ "$GITHUB_REF" == refs/tags/openapi-sdk-v* ]]; then
+ # Extract version from tag: openapi-sdk-v1.2.0 -> 1.2.0
+ VERSION="${GITHUB_REF#refs/tags/openapi-sdk-v}"
+ else
+ # Fall back to fallback_version from pyproject.toml
+ VERSION=$(python3 -c "
+ import tomllib, pathlib
+ p = tomllib.loads(pathlib.Path('pyproject.toml').read_text())
+ print(p.get('tool', {}).get('setuptools_scm', {}).get('fallback_version', '0.0.0.dev0'))
+ ")
+ fi
+ echo "version=${VERSION}" >> "$GITHUB_OUTPUT"
+ echo "Computed version: ${VERSION}"
+
+ build-sdk:
+ needs: compute-version
runs-on: ubuntu-latest
- environment:
- name: ${{ github.event.inputs.publish_to == 'pypi' && 'pypi-production' || 'testpypi' }}
steps:
- name: Checkout repository
@@ -63,14 +94,15 @@ jobs:
echo "=== OpenAPI Generator version ==="
openapi-generator-cli version
- echo "=== SDK version from pyproject.toml ==="
- make version
+ echo "=== SDK version ==="
+ echo "${{ needs.compute-version.outputs.version }}"
- name: Generate OpenAPI SDK
working-directory: client-sdks/openapi
run: |
- echo "Generating SDK with OPEN=1 (ogx_open_client)..."
- make sdk OPEN=1
+ VERSION="${{ needs.compute-version.outputs.version }}"
+ echo "Generating SDK with OPEN=1 (ogx_open_client) at version ${VERSION}..."
+ make sdk OPEN=1 VERSION="${VERSION}"
- name: Verify SDK generation
working-directory: client-sdks/openapi
@@ -100,65 +132,80 @@ jobs:
echo "Built distribution files:"
ls -lh dist/
- - name: Publish to TestPyPI (dry-run or manual)
- if: |
- (github.event_name == 'workflow_dispatch' && inputs.publish_to == 'testpypi' && inputs.dry_run == false) ||
- (github.event_name == 'push' && startsWith(github.ref, 'refs/tags/openapi-sdk-v') && !contains(github.ref, '-rc') && !contains(github.ref, '-alpha') && !contains(github.ref, '-beta'))
- working-directory: client-sdks/openapi/sdks/python
- run: |
- echo "Publishing to TestPyPI..."
- uv publish --publish-url https://test.pypi.org/legacy/ dist/*
- env:
- UV_PUBLISH_TOKEN: ${{ secrets.TEST_PYPI_API_TOKEN }}
-
- - name: Publish to PyPI (production)
- if: |
- github.event_name == 'workflow_dispatch' &&
- inputs.publish_to == 'pypi' &&
- inputs.dry_run == false
- working-directory: client-sdks/openapi/sdks/python
- run: |
- echo "Publishing to PyPI..."
- uv publish dist/*
- env:
- UV_PUBLISH_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
-
- name: Upload build artifacts
- uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v4.6.0
+ uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: python-sdk-dist
path: client-sdks/openapi/sdks/python/dist/
retention-days: 30
+ publish-testpypi:
+ if: |
+ (github.event_name == 'workflow_dispatch' && inputs.publish_to == 'testpypi' && inputs.dry_run == false) ||
+ (github.event_name == 'push' && startsWith(github.ref, 'refs/tags/openapi-sdk-v') && !contains(github.ref, '-rc') && !contains(github.ref, '-alpha') && !contains(github.ref, '-beta'))
+ needs: build-sdk
+ runs-on: ubuntu-latest
+ environment: testpypi
+ permissions:
+ id-token: write
+ steps:
+ - name: Download build artifacts
+ uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
+ with:
+ name: python-sdk-dist
+ path: dist
+
+ - name: Publish to TestPyPI
+ uses: pypa/gh-action-pypi-publish@cef221092ed1bacb1cc03d23a2d87d1d172e277b # v1.14.0
+ with:
+ repository-url: https://test.pypi.org/legacy/
+ packages-dir: dist/
+ verbose: true
+
- name: Summary
run: |
{
echo "## SDK Publishing Summary"
echo ""
echo "- **Event**: ${{ github.event_name }}"
- echo "- **Dry Run**: ${{ inputs.dry_run || 'false' }}"
- echo "- **Target**: ${{ inputs.publish_to || 'testpypi (default)' }}"
+ echo "- **Target**: TestPyPI"
echo "- **Package**: ogx-open-client"
echo ""
+ echo "✅ Package published to TestPyPI"
+ echo "Install with: \`pip install --index-url https://test.pypi.org/simple/ ogx-open-client\`"
+ } >> "$GITHUB_STEP_SUMMARY"
+
+ publish-pypi:
+ if: |
+ github.event_name == 'workflow_dispatch' &&
+ inputs.publish_to == 'pypi' &&
+ inputs.dry_run == false
+ needs: build-sdk
+ runs-on: ubuntu-latest
+ permissions:
+ id-token: write
+ steps:
+ - name: Download build artifacts
+ uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
+ with:
+ name: python-sdk-dist
+ path: dist
+
+ - name: Publish to PyPI
+ uses: pypa/gh-action-pypi-publish@cef221092ed1bacb1cc03d23a2d87d1d172e277b # v1.14.0
+ with:
+ packages-dir: dist/
+ verbose: true
- if [ "${{ inputs.dry_run }}" = "true" ]; then
- echo "✅ Package built successfully (dry-run, not published)"
- elif [ "${{ inputs.publish_to }}" = "testpypi" ]; then
- echo "✅ Package published to TestPyPI"
- echo "Install with: \`pip install --index-url https://test.pypi.org/simple/ ogx-open-client\`"
- elif [ "${{ github.event_name }}" = "push" ]; then
- # Check for pre-release tags (same logic as publish step)
- case "${{ github.ref }}" in
- *"-rc"*|*"-alpha"*|*"-beta"*)
- echo "✅ Package built successfully (pre-release tag, not published)"
- ;;
- *)
- echo "✅ Package published to TestPyPI"
- echo "Install with: \`pip install --index-url https://test.pypi.org/simple/ ogx-open-client\`"
- ;;
- esac
- else
- echo "✅ Package published to PyPI"
- echo "Install with: \`pip install ogx-open-client\`"
- fi
+ - name: Summary
+ run: |
+ {
+ echo "## SDK Publishing Summary"
+ echo ""
+ echo "- **Event**: ${{ github.event_name }}"
+ echo "- **Target**: PyPI (production)"
+ echo "- **Package**: ogx-open-client"
+ echo ""
+ echo "✅ Package published to PyPI"
+ echo "Install with: \`pip install ogx-open-client\`"
} >> "$GITHUB_STEP_SUMMARY"
diff --git a/.github/workflows/pypi.yml b/.github/workflows/pypi.yml
index 153ccf76a58..d3902d68cb9 100644
--- a/.github/workflows/pypi.yml
+++ b/.github/workflows/pypi.yml
@@ -65,6 +65,15 @@
# published successfully but image builds failed. Requires "version" to be
# set to the already-published version.
#
+# package_name: PyPI package to bundle in the Docker images. Defaults to "ogx".
+# Set to "llama-stack" to publish images for pre-rename releases (e.g. 0.5.0),
+# which were published under the old package name. The CLI binary and home
+# directory are derived automatically ("llama-stack" -> "llama"/".llama").
+#
+# skip_latest: When true, production image builds are tagged only with the
+# version and not also as "latest". Use when backfilling an older release so
+# it does not become the default image users pull.
+#
# =============================================================================
name: Build, test, and publish packages
@@ -120,6 +129,16 @@ on:
required: false
type: boolean
default: false
+ package_name:
+ description: 'PyPI package to bundle in Docker images. Use "llama-stack" for pre-rename releases (e.g. 0.5.0).'
+ required: false
+ type: string
+ default: 'ogx'
+ skip_latest:
+ description: 'Do not also tag/push images as "latest". Use when backfilling an older release so it does not become the default pull.'
+ required: false
+ type: boolean
+ default: false
env:
LC_ALL: en_US.UTF-8
@@ -206,6 +225,11 @@ jobs:
path: .
type: local
registry: pypi
+ # OpenAPI-generated SDK (built from spec in this repo)
+ - package: ogx-open-client
+ path: client-sdks/openapi
+ type: openapi-sdk
+ registry: pypi
# External packages (client SDKs from other repos)
- package: ogx-client-python
repo: ogx-ai/ogx-client-python
@@ -227,7 +251,7 @@ jobs:
if [ "$PACKAGES" == "all" ]; then
echo "skip=false" >> "$GITHUB_OUTPUT"
- elif [ "$PACKAGES" == "ogx-only" ] && [ "$TYPE" == "local" ]; then
+ elif [ "$PACKAGES" == "ogx-only" ] && { [ "$TYPE" == "local" ] || [ "$TYPE" == "openapi-sdk" ]; }; then
echo "skip=false" >> "$GITHUB_OUTPUT"
elif [ "$PACKAGES" == "clients-only" ] && [ "$TYPE" == "external" ]; then
echo "skip=false" >> "$GITHUB_OUTPUT"
@@ -238,13 +262,13 @@ jobs:
# === LOCAL PACKAGE STEPS ===
- name: Checkout local repo
- if: steps.should-build.outputs.skip != 'true' && matrix.type == 'local'
+ if: steps.should-build.outputs.skip != 'true' && (matrix.type == 'local' || matrix.type == 'openapi-sdk')
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
fetch-depth: 0 # for setuptools-scm
- name: Install dependent PRs if needed
- if: steps.should-build.outputs.skip != 'true' && matrix.type == 'local'
+ if: steps.should-build.outputs.skip != 'true' && (matrix.type == 'local' || matrix.type == 'openapi-sdk')
uses: depends-on/depends-on-action@826c144163ac67bf08347590a5f81afd45da63ca # main
with:
token: ${{ secrets.GITHUB_TOKEN }}
@@ -296,7 +320,7 @@ jobs:
- name: Install uv
if: steps.should-build.outputs.skip != 'true' && matrix.registry == 'pypi'
- uses: astral-sh/setup-uv@08807647e7069bb48b6ef5acd8ec9567f424441b # v8.1.0
+ uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # v8.2.0
- name: Install build dependencies
if: steps.should-build.outputs.skip != 'true' && matrix.registry == 'pypi'
@@ -331,6 +355,48 @@ jobs:
env:
SETUPTOOLS_SCM_PRETEND_VERSION: ${{ needs.compute-version.outputs.version }}
+ # === OPENAPI SDK BUILD (ogx-open-client) ===
+ - name: Set up Java (openapi-sdk)
+ if: steps.should-build.outputs.skip != 'true' && matrix.type == 'openapi-sdk'
+ uses: actions/setup-java@be666c2fcd27ec809703dec50e508c2fdc7f6654 # v5.2.0
+ with:
+ distribution: 'temurin'
+ java-version: '11'
+
+ - name: Set up Node.js (openapi-sdk)
+ if: steps.should-build.outputs.skip != 'true' && matrix.type == 'openapi-sdk'
+ uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+ with:
+ node-version: '20'
+
+ - name: Install openapi-generator-cli (openapi-sdk)
+ if: steps.should-build.outputs.skip != 'true' && matrix.type == 'openapi-sdk'
+ run: npm install -g @openapitools/openapi-generator-cli
+
+ - name: Generate and build OpenAPI SDK
+ if: steps.should-build.outputs.skip != 'true' && matrix.type == 'openapi-sdk'
+ working-directory: ${{ matrix.path }}
+ run: |
+ VERSION="${{ needs.compute-version.outputs.version }}"
+ echo "Generating SDK with OPEN=1 (ogx_open_client) at version ${VERSION}..."
+ make sdk OPEN=1 VERSION="${VERSION}"
+
+ cd sdks/python
+ echo "Building Python package..."
+ uv build --out-dir ../../dist --no-build-isolation
+
+ - name: Verify OpenAPI SDK generation
+ if: steps.should-build.outputs.skip != 'true' && matrix.type == 'openapi-sdk'
+ working-directory: ${{ matrix.path }}
+ run: |
+ PY_FILE_COUNT=$(find sdks/python -name "*.py" | wc -l)
+ echo "Generated Python files: $PY_FILE_COUNT"
+ if [ "$PY_FILE_COUNT" -le 10 ]; then
+ echo "::error::Too few Python files generated (expected > 10, got $PY_FILE_COUNT)"
+ exit 1
+ fi
+ echo "SDK generated successfully"
+
# === EXTERNAL PYTHON PACKAGE BUILD ===
- name: Check and bump version if exists on PyPI
if: steps.should-build.outputs.skip != 'true' && matrix.type == 'external' && matrix.registry == 'pypi'
@@ -506,7 +572,7 @@ jobs:
run: uv pip install --system twine check-wheel-contents
- name: Check wheel contents (local)
- if: steps.should-build.outputs.skip != 'true' && matrix.type == 'local' && matrix.registry == 'pypi'
+ if: steps.should-build.outputs.skip != 'true' && (matrix.type == 'local' || matrix.type == 'openapi-sdk') && matrix.registry == 'pypi'
run: check-wheel-contents --ignore W002,W004 ${{ matrix.path }}/dist/*.whl
- name: Check wheel contents (external)
@@ -514,7 +580,7 @@ jobs:
run: check-wheel-contents --ignore W002,W004 external-repo/dist/*.whl
- name: Validate package with twine (local)
- if: steps.should-build.outputs.skip != 'true' && matrix.type == 'local' && matrix.registry == 'pypi'
+ if: steps.should-build.outputs.skip != 'true' && (matrix.type == 'local' || matrix.type == 'openapi-sdk') && matrix.registry == 'pypi'
run: twine check ${{ matrix.path }}/dist/*
- name: Validate package with twine (external)
@@ -523,7 +589,7 @@ jobs:
# === LIST AND UPLOAD ARTIFACTS ===
- name: List dist contents (local)
- if: steps.should-build.outputs.skip != 'true' && matrix.type == 'local'
+ if: steps.should-build.outputs.skip != 'true' && (matrix.type == 'local' || matrix.type == 'openapi-sdk')
run: ls -la ${{ matrix.path }}/dist/
- name: List dist contents (external Python)
@@ -540,7 +606,7 @@ jobs:
ls -la dist/
- name: Upload artifacts (local)
- if: steps.should-build.outputs.skip != 'true' && matrix.type == 'local'
+ if: steps.should-build.outputs.skip != 'true' && (matrix.type == 'local' || matrix.type == 'openapi-sdk')
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: Packages-${{ matrix.package }}
@@ -567,7 +633,7 @@ jobs:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Install uv
- uses: astral-sh/setup-uv@08807647e7069bb48b6ef5acd8ec9567f424441b # v8.1.0
+ uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # v8.2.0
with:
python-version: ${{ matrix.python-version }}
@@ -608,6 +674,14 @@ jobs:
path: dist-client-ts
continue-on-error: true
+ - name: Download ogx-open-client artifacts
+ id: download-open-client
+ uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
+ with:
+ name: Packages-ogx-open-client
+ path: dist-open-client
+ continue-on-error: true
+
- name: Create venv and install Python packages
run: |
uv venv .venv
@@ -629,6 +703,11 @@ jobs:
uv pip install dist-stack/*.whl
fi
+ if [ -d "dist-open-client" ] && ls dist-open-client/*.whl 1>/dev/null 2>&1; then
+ echo "Installing ogx-open-client..."
+ uv pip install dist-open-client/*.whl
+ fi
+
- name: List Wheel Contents (ogx-api)
if: steps.download-api.outcome == 'success'
run: |
@@ -662,6 +741,10 @@ jobs:
python -c "import ogx_client; print(f'ogx_client imported successfully from {ogx_client.__file__}')"
fi
+ if [ -d "dist-open-client" ] && ls dist-open-client/*.whl 1>/dev/null 2>&1; then
+ python -c "import ogx_open_client; print(f'ogx_open_client imported successfully from {ogx_open_client.__file__}')"
+ fi
+
- name: Verify TypeScript package
if: steps.download-client-ts.outcome == 'success'
run: |
@@ -681,7 +764,7 @@ jobs:
fi
# Publish packages to PyPI/npm
- # Order: ogx-client-python, ogx-client-typescript, ogx-api, ogx
+ # Order: ogx-client-python, ogx-client-typescript, ogx-open-client, ogx-api, ogx
publish-packages:
name: Publish ${{ matrix.package }}
if: |
@@ -708,6 +791,9 @@ jobs:
- package: ogx-client-typescript
registry: npm
type: external
+ - package: ogx-open-client
+ registry: pypi
+ type: openapi-sdk
- package: ogx-api
registry: pypi
type: local
@@ -726,7 +812,7 @@ jobs:
if [ "$PACKAGES" == "all" ]; then
echo "skip=false" >> "$GITHUB_OUTPUT"
- elif [ "$PACKAGES" == "ogx-only" ] && [ "$TYPE" == "local" ]; then
+ elif [ "$PACKAGES" == "ogx-only" ] && { [ "$TYPE" == "local" ] || [ "$TYPE" == "openapi-sdk" ]; }; then
echo "skip=false" >> "$GITHUB_OUTPUT"
elif [ "$PACKAGES" == "clients-only" ] && [ "$TYPE" == "external" ]; then
echo "skip=false" >> "$GITHUB_OUTPUT"
@@ -792,7 +878,7 @@ jobs:
matrix.registry == 'pypi' &&
steps.check-artifacts.outputs.has_artifacts == 'true' &&
steps.pypi-target.outputs.is_production == 'true'
- uses: sigstore/gh-action-sigstore-python@04cffa1d795717b140764e8b640de88853c92acc # v3.3.0
+ uses: sigstore/gh-action-sigstore-python@5b79a39c381910c090341a2c9b0bf022c8b387e1 # v3.4.0
with:
inputs: >-
./dist/*.tar.gz
@@ -949,39 +1035,78 @@ jobs:
DRY_RUN="${{ inputs.dry_run }}"
EVENT="${{ github.event_name }}"
+ # PyPI package to bundle. Pre-rename releases (e.g. 0.5.0) shipped as
+ # "llama-stack"; the CLI binary is derived by stripping the "-stack"
+ # suffix ("llama-stack" -> "llama", "ogx" -> "ogx").
+ PACKAGE_NAME="${{ inputs.package_name || 'ogx' }}"
+ CLI_NAME="${PACKAGE_NAME%-stack}"
+ # Backfilling a non-ogx (pre-rename) package pins old dependencies that
+ # can conflict with the latest OTel auto-instrumentation packages, so
+ # make the bootstrap best-effort for those builds. The ogx path stays
+ # strict.
+ if [ "$PACKAGE_NAME" == "ogx" ]; then OTEL_BEST_EFFORT=""; else OTEL_BEST_EFFORT="1"; fi
+ {
+ echo "package_name=${PACKAGE_NAME}"
+ echo "cli_name=${CLI_NAME}"
+ echo "otel_best_effort=${OTEL_BEST_EFFORT}"
+ } >> "$GITHUB_OUTPUT"
+
if [ "$EVENT" == "release" ] || [ "$DRY_RUN" == "off" ]; then
+ if [ "${{ inputs.skip_latest }}" == "true" ]; then
+ TAGS="${IMAGE}:${VERSION}"
+ LATEST_NOTE=""
+ else
+ TAGS="${IMAGE}:${VERSION},${IMAGE}:latest"
+ LATEST_NOTE=" + latest"
+ fi
{
echo "install_mode=pypi"
- echo "tags=${IMAGE}:${VERSION},${IMAGE}:latest"
+ echo "tags=${TAGS}"
echo "version_arg=PYPI_VERSION=${VERSION}"
} >> "$GITHUB_OUTPUT"
- echo "Publishing production image: ${IMAGE}:${VERSION} + latest"
+ echo "Publishing production image: ${IMAGE}:${VERSION}${LATEST_NOTE} (package: ${PACKAGE_NAME})"
else
{
echo "install_mode=test-pypi"
echo "tags=${IMAGE}:test-${VERSION}"
echo "version_arg=TEST_PYPI_VERSION=${VERSION}"
} >> "$GITHUB_OUTPUT"
- echo "Publishing test image: ${IMAGE}:test-${VERSION}"
+ echo "Publishing test image: ${IMAGE}:test-${VERSION} (package: ${PACKAGE_NAME})"
fi
- name: Wait for package on test PyPI
if: steps.meta.outputs.install_mode == 'test-pypi'
run: |
VERSION="${{ needs.compute-version.outputs.version }}"
- URL="https://test.pypi.org/pypi/ogx/${VERSION}/json"
+ PACKAGE_NAME="${{ steps.meta.outputs.package_name }}"
+ URL="https://test.pypi.org/pypi/${PACKAGE_NAME}/${VERSION}/json"
echo "Polling ${URL} ..."
for i in $(seq 1 20); do
if curl -sf "$URL" -o /dev/null; then
- echo "ogx==${VERSION} is available on test PyPI"
+ echo "${PACKAGE_NAME}==${VERSION} is available on test PyPI"
exit 0
fi
echo "Attempt ${i}/20: not yet available, waiting 30s..."
sleep 30
done
- echo "::error::ogx==${VERSION} did not appear on test PyPI after 10 minutes"
+ echo "::error::${PACKAGE_NAME}==${VERSION} did not appear on test PyPI after 10 minutes"
exit 1
+ - name: Generate config labels
+ id: labels
+ run: |
+ # Embed distribution configs as OCI labels (see scripts/generate-config-labels.sh).
+ # generate-config-labels.sh emits alternating "--label"/"key=value" lines for
+ # docker CLI; build-push-action wants bare "key=value" lines, so drop the flags.
+ LABELS=$(bash scripts/generate-config-labels.sh \
+ "${{ matrix.distro }}" "${{ needs.compute-version.outputs.version }}" \
+ | grep -v '^--label$')
+ {
+ echo "labels<> "$GITHUB_OUTPUT"
+
- name: Build and push Docker image
uses: docker/build-push-action@f9f3042f7e2789586610d6e8b85c8f03e5195baf # v7.2.0
with:
@@ -990,7 +1115,62 @@ jobs:
platforms: ${{ matrix.platforms }}
push: true
tags: ${{ steps.meta.outputs.tags }}
+ labels: ${{ steps.labels.outputs.labels }}
build-args: |
DISTRO_NAME=${{ matrix.distro }}
INSTALL_MODE=${{ steps.meta.outputs.install_mode }}
+ PACKAGE_NAME=${{ steps.meta.outputs.package_name }}
+ CLI_NAME=${{ steps.meta.outputs.cli_name }}
+ OTEL_BEST_EFFORT=${{ steps.meta.outputs.otel_best_effort }}
${{ steps.meta.outputs.version_arg }}
+
+ scan-docker-images:
+ name: Scan Docker ${{ matrix.distro }}
+ if: |
+ always() &&
+ needs.publish-docker-images.result == 'success'
+ permissions:
+ contents: read
+ security-events: write
+ runs-on: ubuntu-latest
+ needs: [publish-docker-images, compute-version]
+ strategy:
+ fail-fast: false
+ matrix:
+ include:
+ - distro: starter
+ - distro: postgres-demo
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+
+ - name: Determine image tag
+ id: tag
+ run: |
+ VERSION="${{ needs.compute-version.outputs.version }}"
+ DRY_RUN="${{ inputs.dry_run }}"
+ EVENT="${{ github.event_name }}"
+ if [ "$EVENT" == "release" ] || [ "$DRY_RUN" == "off" ]; then
+ echo "tag=${VERSION}" >> "$GITHUB_OUTPUT"
+ else
+ echo "tag=test-${VERSION}" >> "$GITHUB_OUTPUT"
+ fi
+
+ - name: Scan published image with Trivy
+ uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
+ with:
+ image-ref: 'ogxai/distribution-${{ matrix.distro }}:${{ steps.tag.outputs.tag }}'
+ scan-type: 'image'
+ scanners: 'vuln'
+ severity: 'CRITICAL,HIGH'
+ exit-code: '0'
+ format: 'sarif'
+ output: 'trivy-image-${{ matrix.distro }}.sarif'
+ trivy-config: 'trivy.yaml'
+
+ - name: Upload Trivy image scan results to GitHub Security
+ uses: github/codeql-action/upload-sarif@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ if: always()
+ with:
+ sarif_file: 'trivy-image-${{ matrix.distro }}.sarif'
+ category: 'trivy-image-${{ matrix.distro }}'
diff --git a/.github/workflows/record-integration-tests.yml b/.github/workflows/record-integration-tests.yml
index 52408f671f5..8444b256dd7 100644
--- a/.github/workflows/record-integration-tests.yml
+++ b/.github/workflows/record-integration-tests.yml
@@ -51,6 +51,11 @@ on:
type: string
required: false
default: ''
+ commit_mode:
+ description: 'How to land recordings: pr (commit to PR branch), branch (open a new PR against the dispatched branch), none (artifacts only). Leave blank to auto-select.'
+ type: string
+ required: false
+ default: ''
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || inputs.pr_number || github.run_number }}
@@ -74,6 +79,7 @@ jobs:
pr_head_repo: ${{ steps.compute.outputs.pr_head_repo }}
is_fork_pr: ${{ steps.compute.outputs.is_fork_pr }}
providers_to_run: ${{ steps.compute.outputs.providers_to_run }}
+ commit_mode: ${{ steps.compute.outputs.commit_mode }}
steps:
- name: Compute PR metadata
id: compute
@@ -84,6 +90,7 @@ jobs:
EVENT_NAME: ${{ github.event_name }}
INPUT_PR_NUMBER: ${{ inputs.pr_number }}
INPUT_PROVIDERS: ${{ inputs.providers }}
+ INPUT_COMMIT_MODE: ${{ inputs.commit_mode }}
REPO: ${{ github.repository }}
REF_NAME: ${{ github.ref_name }}
SHA: ${{ github.sha }}
@@ -123,6 +130,18 @@ jobs:
IS_FORK_PR="false"
fi
+ # Determine how recordings should land.
+ # - PR-targeted runs (pull_request event, or dispatch with a pr_number) commit to the PR branch.
+ # - Dispatch on a branch with no PR (e.g. main) opens a new PR with the refreshed recordings.
+ # An explicit commit_mode input overrides the auto-selection.
+ if [ -n "$INPUT_COMMIT_MODE" ]; then
+ COMMIT_MODE="$INPUT_COMMIT_MODE"
+ elif [ "$PR_NUMBER" = "manual" ]; then
+ COMMIT_MODE="branch"
+ else
+ COMMIT_MODE="pr"
+ fi
+
# Determine which providers to run
# Security: For pull_request, only run ollama variants (no secrets needed)
# Manual workflow_dispatch uses input providers (defaults to API providers)
@@ -140,6 +159,7 @@ jobs:
echo "pr_head_repo=${HEAD_REPO}"
echo "is_fork_pr=${IS_FORK_PR}"
echo "providers_to_run=${PROVIDERS}"
+ echo "commit_mode=${COMMIT_MODE}"
} >> "$GITHUB_OUTPUT"
echo "Recording for PR #${PR_NUMBER}"
@@ -148,6 +168,7 @@ jobs:
echo " Repo: ${HEAD_REPO}"
echo " Fork PR: ${IS_FORK_PR}"
echo " Providers: ${PROVIDERS}"
+ echo " Commit mode: ${COMMIT_MODE}"
# Upload PR metadata for companion workflow
upload-pr-metadata:
@@ -162,6 +183,7 @@ jobs:
PR_HEAD_SHA: ${{ needs.compute-pr-info.outputs.pr_head_sha }}
PR_HEAD_REPO: ${{ needs.compute-pr-info.outputs.pr_head_repo }}
IS_FORK_PR: ${{ needs.compute-pr-info.outputs.is_fork_pr }}
+ COMMIT_MODE: ${{ needs.compute-pr-info.outputs.commit_mode }}
run: |
mkdir -p pr-metadata
cat > pr-metadata/pr-info.json < pr-metadata/pr-info.json <> "$GITHUB_OUTPUT"
+
+ - name: Run integration tests (record mode)
+ uses: ./.github/actions/run-and-record-tests
+ with:
+ stack-config: 'server:ci-tests'
+ setup: 'vllm-gpu-gpt-oss'
+ inference-mode: 'record'
+ suite: ${{ inputs.suite }}
+ pattern: ${{ steps.test-pattern.outputs.pattern }}
+ skip-commit: 'true' # Don't commit here - upload as artifacts
+
+ - name: Upload recordings as artifacts
+ if: always()
+ uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+ with:
+ name: recordings-vllm-gpu-gpt-oss-${{ inputs.suite }}-${{ github.run_id }}-${{ github.run_attempt || '1' }}
+ path: |
+ tests/integration/recordings/
+ tests/integration/*/recordings/
+ retention-days: 7
+ if-no-files-found: error
+
+ - name: Upload vLLM logs
+ if: always()
+ run: |
+ if [ -f /tmp/vllm-server.log ]; then
+ cat /tmp/vllm-server.log
+ fi
+
+ - name: Disk space after tests
+ if: always()
+ run: |
+ echo "=== Disk Space After Tests ==="
+ df -h
+
+ # Job 3: Stop GPU EC2 instance (ALWAYS runs for cleanup)
+ stop-gpu-runner:
+ needs: start-gpu-runner
+ runs-on: ubuntu-latest
+ if: ${{ always() }} # CRITICAL: Always cleanup, even on failure or cancellation
+ steps:
+ - name: Checkout code
+ uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+ with:
+ persist-credentials: false
+
+ - name: Configure AWS credentials via OIDC
+ if: needs.start-gpu-runner.outputs.instance-id != ''
+ uses: aws-actions/configure-aws-credentials@e3dd6a429d7300a6a4c196c26e071d42e0343502 # v4.0.2
+ with:
+ role-to-assume: ${{ secrets.AWS_ROLE_ARN }}
+ aws-region: us-east-2
+ role-session-name: GitHubActions-vLLM-GPU-Cleanup-${{ github.run_id }}
+
+ - name: Wait for GPU test job before cleanup
+ if: needs.start-gpu-runner.outputs.instance-id != ''
+ env:
+ GH_TOKEN: ${{ github.token }}
+ RECORD_JOB_NAME: record-vllm-tests
+ RUN_ID: ${{ github.run_id }}
+ REPOSITORY: ${{ github.repository }}
+ run: |
+ queued_deadline=$((SECONDS + 1200))
+ absolute_deadline=$((SECONDS + 7200))
+
+ while true; do
+ job_status="$(
+ gh api "repos/${REPOSITORY}/actions/runs/${RUN_ID}/jobs" --paginate \
+ --jq ".jobs[] | select(.name == \"${RECORD_JOB_NAME}\") | [.status, (.conclusion // \"\")] | @tsv" \
+ | tail -n 1
+ )"
+
+ status="$(printf '%s' "$job_status" | cut -f1)"
+ conclusion="$(printf '%s' "$job_status" | cut -f2)"
+
+ if [ "$status" = "completed" ]; then
+ echo "GPU test job completed with conclusion: ${conclusion:-unknown}"
+ break
+ fi
+
+ if [ -z "$status" ]; then
+ echo "Waiting for GPU test job to be created..."
+ else
+ echo "GPU test job status: $status"
+ fi
+
+ if [ "$status" != "in_progress" ] && [ "$SECONDS" -ge "$queued_deadline" ]; then
+ echo "GPU test job did not start within 20 minutes; cleaning up the EC2 runner."
+ break
+ fi
+
+ if [ "$SECONDS" -ge "$absolute_deadline" ]; then
+ echo "GPU test job exceeded the 2 hour cleanup deadline; cleaning up the EC2 runner."
+ break
+ fi
+
+ sleep 30
+ done
+
+ - name: Stop EC2 runner
+ if: needs.start-gpu-runner.outputs.instance-id != ''
+ uses: ./.github/actions/launch-gpu-runner
+ with:
+ mode: stop
+ github-token: ${{ secrets.RELEASE_PAT }}
+ aws-region: us-east-2
+ label: ${{ needs.start-gpu-runner.outputs.label }}
+ ec2-instance-id: ${{ needs.start-gpu-runner.outputs.instance-id }}
+
+ - name: Cleanup summary
+ if: needs.start-gpu-runner.outputs.instance-id != ''
+ run: |
+ echo "GPU runner terminated successfully"
+ echo " Instance ID: ${{ needs.start-gpu-runner.outputs.instance-id }}"
+
+ - name: Cleanup skipped
+ if: needs.start-gpu-runner.outputs.instance-id == ''
+ run: |
+ echo "No EC2 instance id was produced by start-gpu-runner; nothing to terminate."
+
+ # Job 4: Summary and next steps
+ summary:
+ needs: [start-gpu-runner, record-vllm-tests, stop-gpu-runner]
+ runs-on: ubuntu-latest
+ if: always()
+ steps:
+ - name: Workflow summary
+ run: |
+ {
+ echo "## vLLM GPU Recording Summary"
+ echo ""
+ echo "**Model**: gpt-oss:20b"
+ echo "**Instance Type**: g6.2xlarge"
+ echo "**Test Suite**: ${{ inputs.suite }}"
+ echo ""
+
+ if [ "${{ needs.record-vllm-tests.result }}" == "success" ]; then
+ echo "**Test Status**: Successful"
+ echo ""
+ echo "Recordings have been uploaded as artifacts. The trusted Commit Recordings workflow will commit them back to the PR branch when PR metadata is available."
+ else
+ echo "**Test Status**: Failed"
+ echo ""
+ echo "Check the test logs for errors."
+ fi
+
+ echo ""
+ echo "**Cleanup Status**: ${{ needs.stop-gpu-runner.result == 'success' && 'Instance terminated' || 'Check manually' }}"
+ } >> "$GITHUB_STEP_SUMMARY"
+
+ - name: Check for cleanup issues
+ if: needs.stop-gpu-runner.result != 'success'
+ run: |
+ echo "::warning::EC2 instance cleanup may have failed! Check AWS console for orphaned instances."
+ echo "Instance ID: ${{ needs.start-gpu-runner.outputs.instance-id }}"
diff --git a/.github/workflows/release-branch-scheduled-ci.yml b/.github/workflows/release-branch-scheduled-ci.yml
index f3ce2195eed..08e51737190 100644
--- a/.github/workflows/release-branch-scheduled-ci.yml
+++ b/.github/workflows/release-branch-scheduled-ci.yml
@@ -173,7 +173,7 @@ jobs:
ref: ${{ matrix.branch }}
- name: Install uv
- uses: astral-sh/setup-uv@08807647e7069bb48b6ef5acd8ec9567f424441b # v8.1.0
+ uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # v8.2.0
with:
python-version: ${{ matrix.python-version }}
activate-environment: true
diff --git a/.github/workflows/stainless-builds.yml b/.github/workflows/stainless-builds.yml
deleted file mode 100644
index 6370d84b9e0..00000000000
--- a/.github/workflows/stainless-builds.yml
+++ /dev/null
@@ -1,277 +0,0 @@
-name: Stainless SDK Builds
-run-name: Build Stainless SDK from OpenAPI spec changes
-
-# SECURITY NOTE: This workflow uses pull_request_target, which runs with access to
-# secrets and a privileged GITHUB_TOKEN even for fork PRs.
-#
-# Security measures in place:
-# 1. The preview and merge jobs only use Stainless actions that read OAS/config files
-# without executing arbitrary code from the PR.
-#
-# 2. The integration tests are called with security flags:
-# - matrix_json: Pre-defined matrix to skip generate_ci_matrix.py execution
-# - disable_cache: Prevents cache poisoning
-# - Composite actions in integration-tests.yml use full repo paths with pinned SHA
-# so they're loaded from a trusted commit, not from PR checkout
-#
-# References:
-# - https://securitylab.github.com/research/github-actions-preventing-pwn-requests/
-
-on:
- pull_request_target:
- types:
- - opened
- - synchronize
- - reopened
- - closed
- paths:
- - "client-sdks/stainless/**"
- - ".github/workflows/stainless-builds.yml" # this workflow
- workflow_dispatch:
- inputs:
- pr_number:
- description: 'PR number to run Stainless build for. Leave empty to force-upload the current OpenAPI spec from main.'
- required: false
- type: number
- sdk_install_url:
- description: 'Python SDK install URL (optional, for testing specific builds)'
- required: false
- type: string
-
-concurrency:
- group: ${{ github.workflow }}-${{ github.event.pull_request.number || inputs.pr_number || github.run_id }}
- cancel-in-progress: true
-
-env:
- # Stainless organization name.
- STAINLESS_ORG: llamastack
-
- # Stainless project name.
- STAINLESS_PROJECT: llama-stack-client
-
- # Path to your OpenAPI spec.
- OAS_PATH: ./client-sdks/stainless/openapi.yml
-
- # Path to your Stainless config. Optional; only provide this if you prefer
- # to maintain the ground truth Stainless config in your own repo.
- CONFIG_PATH: ./client-sdks/stainless/config.yml
-
- # When to fail the job based on build conclusion.
- # Options: "never" | "note" | "warning" | "error" | "fatal".
- FAIL_ON: error
-
- # In your repo secrets, configure:
- # - STAINLESS_API_KEY: a Stainless API key, which you can generate on the
- # Stainless organization dashboard
-
-jobs:
- force-upload:
- # Push the OpenAPI spec from main to Stainless without a PR. Triggered
- # manually via workflow_dispatch with no pr_number. Skips preview and
- # integration tests; just uploads the spec on the main branch.
- if: github.event_name == 'workflow_dispatch' && inputs.pr_number == ''
- runs-on: ubuntu-latest
- permissions:
- contents: read
- steps:
- - name: Checkout main
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- with:
- ref: main
-
- - name: Upload OpenAPI spec to Stainless
- uses: stainless-api/upload-openapi-spec-action/build@020053e7fbf853281174bd3029eb3bfa7a54c039 # 1.13.0
- with:
- stainless_api_key: ${{ secrets.STAINLESS_API_KEY }}
- org: ${{ env.STAINLESS_ORG }}
- project: ${{ env.STAINLESS_PROJECT }}
- oas_path: ${{ env.OAS_PATH }}
- config_path: ${{ env.CONFIG_PATH }}
- fail_on: ${{ env.FAIL_ON }}
- branch: main
- make_comment: false
-
- compute-branch:
- if: github.event_name == 'pull_request_target' || (github.event_name == 'workflow_dispatch' && inputs.pr_number != '')
- runs-on: ubuntu-latest
- outputs:
- preview_branch: ${{ steps.compute.outputs.preview_branch }}
- base_branch: ${{ steps.compute.outputs.base_branch }}
- merge_branch: ${{ steps.compute.outputs.merge_branch }}
- pr_head_repo: ${{ steps.compute.outputs.pr_head_repo }}
- pr_head_ref: ${{ steps.compute.outputs.pr_head_ref }}
- pr_head_sha: ${{ steps.compute.outputs.pr_head_sha }}
- pr_base_sha: ${{ steps.compute.outputs.pr_base_sha }}
- pr_base_ref: ${{ steps.compute.outputs.pr_base_ref }}
- pr_title: ${{ steps.compute.outputs.pr_title }}
- is_fork_pr: ${{ steps.compute.outputs.is_fork_pr }}
- steps:
- - name: Fetch PR details for workflow_dispatch
- if: github.event_name == 'workflow_dispatch'
- id: fetch-pr
- env:
- GH_TOKEN: ${{ github.token }}
- run: |
- PR_DATA=$(gh pr view ${{ inputs.pr_number }} --repo ${{ github.repository }} --json headRefName,headRepository,headRefOid,baseRefName,baseRefOid,headRepositoryOwner,title)
- echo "pr_data=$PR_DATA" >> "$GITHUB_OUTPUT"
-
- - name: Compute branch names
- id: compute
- # Pass PR title via environment variable to prevent shell injection.
- # Direct interpolation of ${{ github.event.pull_request.title }} into bash
- # allows command substitution via backticks or $() in PR titles.
- env:
- PR_TITLE_FROM_EVENT: ${{ github.event.pull_request.title }}
- HEAD_REF_FROM_EVENT: ${{ github.event.pull_request.head.ref }}
- run: |
- if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
- # Extract from fetched PR data (jq -r safely handles special characters)
- PR_DATA='${{ steps.fetch-pr.outputs.pr_data }}'
- FORK_OWNER=$(echo "$PR_DATA" | jq -r '.headRepositoryOwner.login')
- REPO_NAME=$(echo "$PR_DATA" | jq -r '.headRepository.name')
- HEAD_REPO="${FORK_OWNER}/${REPO_NAME}"
- BRANCH_NAME=$(echo "$PR_DATA" | jq -r '.headRefName')
- HEAD_SHA=$(echo "$PR_DATA" | jq -r '.headRefOid')
- BASE_SHA=$(echo "$PR_DATA" | jq -r '.baseRefOid')
- BASE_REF=$(echo "$PR_DATA" | jq -r '.baseRefName')
- PR_TITLE=$(echo "$PR_DATA" | jq -r '.title')
- else
- # Use pull_request_target event data
- HEAD_REPO="${{ github.event.pull_request.head.repo.full_name }}"
- BRANCH_NAME="$HEAD_REF_FROM_EVENT"
- FORK_OWNER="${{ github.event.pull_request.head.repo.owner.login }}"
- HEAD_SHA="${{ github.event.pull_request.head.sha }}"
- BASE_SHA="${{ github.event.pull_request.base.sha }}"
- BASE_REF="${{ github.event.pull_request.base.ref }}"
- # Use environment variable to prevent shell injection from PR titles
- PR_TITLE="$PR_TITLE_FROM_EVENT"
- fi
-
- BASE_REPO="${{ github.repository }}"
-
- if [ "$HEAD_REPO" != "$BASE_REPO" ]; then
- # Fork PR: prefix with fork owner for isolation
- if [ -z "$FORK_OWNER" ]; then
- echo "Error: Fork PR detected but fork owner is empty" >&2
- exit 1
- fi
- PREVIEW_BRANCH="preview/${FORK_OWNER}/${BRANCH_NAME}"
- BASE_BRANCH="preview/base/${FORK_OWNER}/${BRANCH_NAME}"
- IS_FORK_PR="true"
- else
- # Same-repo PR
- PREVIEW_BRANCH="preview/${BRANCH_NAME}"
- BASE_BRANCH="preview/base/${BRANCH_NAME}"
- IS_FORK_PR="false"
- fi
-
- {
- echo "preview_branch=${PREVIEW_BRANCH}"
- echo "base_branch=${BASE_BRANCH}"
- echo "merge_branch=${PREVIEW_BRANCH}"
- echo "pr_head_repo=${HEAD_REPO}"
- echo "pr_head_ref=${BRANCH_NAME}"
- echo "pr_head_sha=${HEAD_SHA}"
- echo "pr_base_sha=${BASE_SHA}"
- echo "pr_base_ref=${BASE_REF}"
- echo "pr_title=${PR_TITLE}"
- echo "is_fork_pr=${IS_FORK_PR}"
- } >> "$GITHUB_OUTPUT"
-
- preview:
- needs: compute-branch
- # Skip preview if workflow_dispatch provides sdk_install_url, or if PR is being closed
- if: |
- (github.event_name == 'workflow_dispatch' && inputs.sdk_install_url == '') ||
- (github.event_name == 'pull_request_target' && github.event.action != 'closed')
- runs-on: ubuntu-latest
- permissions:
- contents: read
- pull-requests: write
- outputs:
- sdk_install_url: ${{ fromJSON(steps.run-preview.outputs.outcomes || '{}').python.install_url || '' }}
- steps:
- # Checkout the PR's code to access the OpenAPI spec and config files.
- # This is necessary to read the spec/config from the PR (including from forks).
- - name: Checkout repository
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- with:
- repository: ${{ needs.compute-branch.outputs.pr_head_repo }}
- ref: ${{ needs.compute-branch.outputs.pr_head_sha }}
- fetch-depth: 2
-
- - name: Run preview builds
- id: run-preview
- uses: stainless-api/upload-openapi-spec-action/preview@020053e7fbf853281174bd3029eb3bfa7a54c039 # 1.13.0
- env:
- PR_NUMBER: ${{ inputs.pr_number || github.event.pull_request.number }}
- with:
- stainless_api_key: ${{ secrets.STAINLESS_API_KEY }}
- org: ${{ env.STAINLESS_ORG }}
- project: ${{ env.STAINLESS_PROJECT }}
- oas_path: ${{ env.OAS_PATH }}
- config_path: ${{ env.CONFIG_PATH }}
- fail_on: ${{ env.FAIL_ON }}
- base_sha: ${{ needs.compute-branch.outputs.pr_base_sha }}
- base_ref: ${{ needs.compute-branch.outputs.pr_base_ref }}
- head_sha: ${{ needs.compute-branch.outputs.pr_head_sha }}
- branch: ${{ needs.compute-branch.outputs.preview_branch }}
- base_branch: ${{ needs.compute-branch.outputs.base_branch }}
- commit_message: ${{ needs.compute-branch.outputs.pr_title }}
- make_comment: true
-
- run-integration-tests:
- needs: [compute-branch, preview]
- if: |
- always() &&
- (needs.preview.result == 'success' || needs.preview.result == 'skipped') &&
- (github.event_name == 'workflow_dispatch' || github.event.action != 'closed')
- uses: ./.github/workflows/integration-tests.yml
- with:
- # Use provided sdk_install_url from workflow_dispatch, or from preview build
- sdk_install_url: ${{ inputs.sdk_install_url || needs.preview.outputs.sdk_install_url }}
- # Hardcoded matrix avoids running generate_ci_matrix.py from the PR checkout
- matrix_json: '{"include":[{"suite":"base","setup":"ollama","inference_mode":"record-if-missing"}]}'
- # Disable caching to prevent cache poisoning from fork PRs
- disable_cache: true
- test-all-client-versions: false
- pr_head_sha: ${{ needs.compute-branch.outputs.pr_head_sha }}
- pr_head_ref: ${{ needs.compute-branch.outputs.pr_head_ref }}
- is_fork_pr: ${{ needs.compute-branch.outputs.is_fork_pr == 'true' }}
-
- merge:
- needs: compute-branch
- if: github.event_name == 'pull_request_target' && github.event.action == 'closed' && github.event.pull_request.merged == true
- runs-on: ubuntu-latest
- permissions:
- contents: read
- pull-requests: write
- steps:
- # Checkout the PR's code to access the OpenAPI spec and config files.
- # This is necessary to read the spec/config from the PR (including from forks).
- - name: Checkout repository
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- with:
- repository: ${{ needs.compute-branch.outputs.pr_head_repo }}
- ref: ${{ needs.compute-branch.outputs.pr_head_sha }}
- fetch-depth: 2
-
- # Note that this only merges in changes that happened on the last build on
- # the computed preview branch. It's possible that there are OAS/config
- # changes that haven't been built, if the preview job didn't finish
- # before this step starts. In theory we want to wait for all builds
- # against the preview branch to complete, but assuming that
- # the preview job happens before the PR merge, it should be fine.
- - name: Run merge build
- uses: stainless-api/upload-openapi-spec-action/merge@020053e7fbf853281174bd3029eb3bfa7a54c039 # 1.13.0
- with:
- stainless_api_key: ${{ secrets.STAINLESS_API_KEY }}
- org: ${{ env.STAINLESS_ORG }}
- project: ${{ env.STAINLESS_PROJECT }}
- oas_path: ${{ env.OAS_PATH }}
- config_path: ${{ env.CONFIG_PATH }}
- fail_on: ${{ env.FAIL_ON }}
- base_sha: ${{ needs.compute-branch.outputs.pr_base_sha }}
- base_ref: ${{ needs.compute-branch.outputs.pr_base_ref }}
- head_sha: ${{ needs.compute-branch.outputs.pr_head_sha }}
- merge_branch: ${{ needs.compute-branch.outputs.merge_branch }}
diff --git a/.github/workflows/trivy-scheduled.yml b/.github/workflows/trivy-scheduled.yml
new file mode 100644
index 00000000000..9bf23d9cf13
--- /dev/null
+++ b/.github/workflows/trivy-scheduled.yml
@@ -0,0 +1,101 @@
+name: Trivy Scheduled Security Scan
+
+on:
+ schedule:
+ - cron: '23 3 * * 1'
+ workflow_dispatch:
+
+permissions:
+ contents: read
+ security-events: write
+
+jobs:
+ repo-scan:
+ name: Repository scan
+ runs-on: ubuntu-latest
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+
+ - name: Run Trivy vulnerability scanner
+ uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
+ with:
+ scan-type: 'fs'
+ scan-ref: '.'
+ scanners: 'vuln'
+ format: 'sarif'
+ output: 'trivy-scheduled-vuln.sarif'
+ exit-code: '0'
+ trivy-config: 'trivy.yaml'
+
+ - name: Upload vulnerability results to GitHub Security
+ uses: github/codeql-action/upload-sarif@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ if: always()
+ with:
+ sarif_file: 'trivy-scheduled-vuln.sarif'
+ category: 'trivy-scheduled-vuln'
+
+ - name: Run Trivy secret scanner
+ uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
+ with:
+ scan-type: 'fs'
+ scan-ref: '.'
+ scanners: 'secret'
+ format: 'sarif'
+ output: 'trivy-scheduled-secret.sarif'
+ exit-code: '0'
+
+ - name: Upload secret results to GitHub Security
+ uses: github/codeql-action/upload-sarif@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ if: always()
+ with:
+ sarif_file: 'trivy-scheduled-secret.sarif'
+ category: 'trivy-scheduled-secret'
+
+ - name: Run Trivy misconfiguration scanner
+ uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
+ with:
+ scan-type: 'config'
+ scan-ref: '.'
+ scanners: 'misconfig'
+ format: 'sarif'
+ output: 'trivy-scheduled-misconfig.sarif'
+ exit-code: '0'
+
+ - name: Upload misconfiguration results to GitHub Security
+ uses: github/codeql-action/upload-sarif@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ if: always()
+ with:
+ sarif_file: 'trivy-scheduled-misconfig.sarif'
+ category: 'trivy-scheduled-misconfig'
+
+ image-scan:
+ name: Scan ${{ matrix.distro }} image
+ runs-on: ubuntu-latest
+ strategy:
+ fail-fast: false
+ matrix:
+ distro:
+ - starter
+ - postgres-demo
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+
+ - name: Scan published image with Trivy
+ uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
+ with:
+ image-ref: 'ogxai/distribution-${{ matrix.distro }}:latest'
+ scan-type: 'image'
+ scanners: 'vuln'
+ format: 'sarif'
+ output: 'trivy-image-${{ matrix.distro }}.sarif'
+ exit-code: '0'
+ trivy-config: 'trivy.yaml'
+
+ - name: Upload image scan results to GitHub Security
+ uses: github/codeql-action/upload-sarif@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ if: always()
+ with:
+ sarif_file: 'trivy-image-${{ matrix.distro }}.sarif'
+ category: 'trivy-scheduled-image-${{ matrix.distro }}'
diff --git a/.github/workflows/trivy-security.yml b/.github/workflows/trivy-security.yml
new file mode 100644
index 00000000000..794e84fc6c5
--- /dev/null
+++ b/.github/workflows/trivy-security.yml
@@ -0,0 +1,119 @@
+name: Trivy Security Scan
+
+on:
+ merge_group:
+ pull_request:
+ branches:
+ - main
+ - "release-**"
+ paths:
+ - 'uv.lock'
+ - 'pyproject.toml'
+ - 'src/ogx_api/pyproject.toml'
+ - 'src/ogx_ui/package-lock.json'
+ - 'containers/Containerfile'
+ - 'src/ogx_ui/Containerfile'
+ - 'docs/docs/distributions/k8s/**'
+ - 'docs/docs/distributions/eks/**'
+ - '.trivyignore'
+ - 'trivy.yaml'
+ push:
+ branches:
+ - main
+ paths:
+ - 'uv.lock'
+ - 'pyproject.toml'
+ - 'src/ogx_api/pyproject.toml'
+ - 'src/ogx_ui/package-lock.json'
+ - 'containers/Containerfile'
+ - 'src/ogx_ui/Containerfile'
+ - 'docs/docs/distributions/k8s/**'
+ - 'docs/docs/distributions/eks/**'
+ - '.trivyignore'
+ - 'trivy.yaml'
+
+concurrency:
+ group: ${{ github.workflow }}-${{ github.ref }}
+ cancel-in-progress: true
+
+permissions:
+ contents: read
+ security-events: write
+
+jobs:
+ vulnerability-scan:
+ name: Dependency vulnerabilities
+ runs-on: ubuntu-latest
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+
+ - name: Run Trivy vulnerability scanner
+ uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
+ with:
+ scan-type: 'fs'
+ scan-ref: '.'
+ scanners: 'vuln'
+ format: 'sarif'
+ output: 'trivy-vuln.sarif'
+ severity: 'CRITICAL,HIGH'
+ exit-code: '0'
+ trivy-config: 'trivy.yaml'
+
+ - name: Upload vulnerability results to GitHub Security
+ uses: github/codeql-action/upload-sarif@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ if: always()
+ with:
+ sarif_file: 'trivy-vuln.sarif'
+ category: 'trivy-vuln'
+
+ misconfig-scan:
+ name: IaC misconfigurations
+ runs-on: ubuntu-latest
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+
+ - name: Run Trivy misconfiguration scanner
+ uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
+ with:
+ scan-type: 'config'
+ scan-ref: '.'
+ scanners: 'misconfig'
+ format: 'sarif'
+ output: 'trivy-misconfig.sarif'
+ severity: 'CRITICAL,HIGH,MEDIUM'
+ exit-code: '0'
+ trivy-config: 'trivy.yaml'
+
+ - name: Upload misconfiguration results to GitHub Security
+ uses: github/codeql-action/upload-sarif@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ if: always()
+ with:
+ sarif_file: 'trivy-misconfig.sarif'
+ category: 'trivy-misconfig'
+
+ secret-scan:
+ name: Secret detection
+ runs-on: ubuntu-latest
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+
+ - name: Run Trivy secret scanner
+ uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
+ with:
+ scan-type: 'fs'
+ scan-ref: '.'
+ scanners: 'secret'
+ format: 'sarif'
+ output: 'trivy-secret.sarif'
+ exit-code: '0'
+ trivy-config: 'trivy.yaml'
+
+ - name: Upload secret detection results to GitHub Security
+ uses: github/codeql-action/upload-sarif@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v3
+ if: always()
+ with:
+ sarif_file: 'trivy-secret.sarif'
+ category: 'trivy-secret'
diff --git a/.markdownlintignore b/.markdownlintignore
new file mode 100644
index 00000000000..e6329c8402d
--- /dev/null
+++ b/.markdownlintignore
@@ -0,0 +1 @@
+paper.md
diff --git a/.trivyignore b/.trivyignore
new file mode 100644
index 00000000000..ce33f5e1f52
--- /dev/null
+++ b/.trivyignore
@@ -0,0 +1,9 @@
+# Trivy ignore file for OGX
+# https://aquasecurity.github.io/trivy/latest/docs/configuration/filtering/#trivyignore
+#
+# Add CVE IDs or vulnerability IDs (one per line) for accepted risks.
+# Document the reason for each exclusion.
+#
+# Example:
+# # CVE-YYYY-NNNNN:
+# CVE-YYYY-NNNNN
diff --git a/ARCHITECTURE.md b/ARCHITECTURE.md
index 3eb64ab606e..6879d771726 100644
--- a/ARCHITECTURE.md
+++ b/ARCHITECTURE.md
@@ -20,7 +20,9 @@ Client (ogx-client SDK or raw HTTP)
v
FastAPI Server (src/ogx/core/server/server.py)
|
- |-- AuthenticationMiddleware (token validation, user extraction)
+ |-- AuthenticationMiddleware (token validation, user + tenant_id extraction)
+ |-- TenancyMiddleware (enforces tenancy mode: disabled/single/multi)
+ |-- RouteAuthorizationMiddleware (route-level access policies)
|
v
Route Dispatch
@@ -115,7 +117,7 @@ The full list of auto-routed pairs is defined in `builtin_automatically_routed_a
The `ogx_api` package defines all public-facing types and protocols:
-- **Protocols** -- Python `Protocol` classes like `Inference`, `Responses` that define the API contract. HTTP routes are defined via FastAPI routers in `fastapi_routes.py` modules.
+- **Protocols** -- Python `Protocol` classes like `Inference`, `Responses`, `Skills` that define the API contract. HTTP routes are defined via FastAPI routers in `fastapi_routes.py` modules.
- **Data Types** -- Pydantic models for requests, responses, and resources (e.g., `Model`, `VectorStore`, `ChatCompletionRequest`).
- **Provider Specs** -- `InlineProviderSpec`, `RemoteProviderSpec`, and related types that define how providers are declared.
- **Internal utilities** -- KVStore and SqlStore abstract interfaces live here so third-party providers can use them without depending on the full server.
@@ -152,7 +154,7 @@ storage:
| PostgreSQL| `PostgresKVStoreConfig` | Production deployments |
| MongoDB | `MongoDBKVStoreConfig` | Document-oriented |
-Used by: distribution registry, quota tracking, provider state.
+Used by: distribution registry, quota tracking, provider state, skills metadata.
### SqlStore
@@ -165,6 +167,16 @@ Used by: distribution registry, quota tracking, provider state.
Used by: inference store (chat completion logs), conversations, prompts.
+### AuthorizedSqlStore and Tenant Isolation
+
+`AuthorizedSqlStore` wraps a `SqlStore` and adds two independent enforcement layers:
+
+1. **Tenant isolation** -- a non-bypassable `WHERE tenant_id = ?` filter applied before any access control check. When tenancy is enabled (`single` or `multi` mode), every table gets a `tenant_id` column. Writes stamp the authenticated user's tenant_id; reads and mutations are scoped to it. Missing tenant context in `multi` mode produces a `1=0` clause (default deny -- see nothing).
+
+2. **ABAC (Attribute-Based Access Control)** -- `owner_principal` and `access_attributes` columns enable policy-based rules like `user is owner`. This operates within a tenant, not across tenants.
+
+Tenancy mode is set process-wide during `Stack.initialize()` via `set_default_tenancy_mode()`, so existing call sites using the `authorized_sqlstore()` factory work without changes.
+
### Distribution Registry
`src/ogx/core/store/` implements `DistributionRegistry`, which tracks all registered resources (models, vector stores, tool groups, prompts, etc.) across providers. It persists to the configured KVStore so resources survive server restarts.
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index a7f2b147253..1ce0b01d66f 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -129,7 +129,7 @@ Please avoid picking up too many issues at once. This helps you stay focused and
### I have a question
-1. Open a "discussion-type" issue or use [Slack](https://join.slack.com/t/ogx-ai/shared_invite/zt-3uyw5bxj9-tSEwsNZncgkGEKbd4dXIpw).
+1. Open a "discussion-type" issue or use [Discord](https://discord.gg/bUYRqEvK6).
### Opening a Pull Request
diff --git a/README.md b/README.md
index b082fb41204..15a37621bb9 100644
--- a/README.md
+++ b/README.md
@@ -5,14 +5,14 @@
-
+
-[**Quick Start**](https://ogx-ai.github.io/docs/getting_started/quickstart) | [**Documentation**](https://ogx-ai.github.io/docs) | [**OpenAI API Compatibility**](https://ogx-ai.github.io/docs/api-openai) | [**Discord**](https://discord.gg/ZAFjsrcw)
+[**Quick Start**](https://ogx-ai.github.io/docs/getting_started/quickstart) | [**Documentation**](https://ogx-ai.github.io/docs) | [**OpenAI API Compatibility**](https://ogx-ai.github.io/docs/api-openai) | [**Discord**](https://discord.gg/bUYRqEvK6)
> [!IMPORTANT]
> **Llama Stack is now OGX.** The name changed, and so did the mission — model-agnostic, multi-SDK, production-grade. [Read the full announcement →](https://ogx-ai.github.io/blog/from-llama-stack-to-ogx)
@@ -41,6 +41,7 @@ response = client.chat.completions.create(
- **Responses API** — server-side agentic orchestration with tool calling, MCP server integration, and built-in file search (RAG) in a single API call ([learn more](https://ogx-ai.github.io/docs/api-openai))
- **Vector Stores & Files** — `/v1/vector_stores` and `/v1/files` for managed document storage and search
- **Batches** — `/v1/batches` for offline batch processing
+- **Skills** — `/v1alpha/skills` for managing versioned skill bundles (zip archives with SKILL.md manifests) that agents can invoke
- **[Open Responses](https://www.openresponses.org/) conformant** — the Responses API implementation passes the Open Responses conformance test suite
- **Multi-SDK support** — use the [Anthropic SDK](https://docs.anthropic.com/en/api/messages) (`/v1/messages`) or [Google GenAI SDK](https://ai.google.dev/gemini-api/docs/interactions) (`/v1alpha/interactions`) natively alongside the OpenAI API
@@ -97,7 +98,7 @@ The official `ogx_client` SDK is recommended for most use cases. The `ogx_open_c
## Community
-We hold regular community calls every Thursday at 09:00 AM PST — see the [Community Event on Discord](https://discord.gg/ZAFjsrcw) for details.
+We hold regular community calls every Thursday at 09:00 AM PST — see the [Community Event on Discord](https://discord.gg/bUYRqEvK6) for details.
[](https://www.star-history.com/#ogx-ai/ogx&Date)
diff --git a/benchmarking/k8s-benchmark/stack-configmap.yaml b/benchmarking/k8s-benchmark/stack-configmap.yaml
index 20ae53f1772..cb1a6426f2a 100644
--- a/benchmarking/k8s-benchmark/stack-configmap.yaml
+++ b/benchmarking/k8s-benchmark/stack-configmap.yaml
@@ -21,9 +21,6 @@ data:
- provider_id: sentence-transformers
provider_type: inline::sentence-transformers
config: {}
- - provider_id: transformers
- provider_type: inline::transformers
- config: {}
files:
- provider_id: builtin-files
provider_type: inline::localfs
@@ -111,7 +108,7 @@ data:
model_type: embedding
- metadata: {}
model_id: Qwen/Qwen3-Reranker-0.6B
- provider_id: transformers
+ provider_id: sentence-transformers
model_type: rerank
- model_id: ${env.INFERENCE_MODEL}
provider_id: vllm-inference
diff --git a/benchmarking/k8s-benchmark/stack_run_config.yaml b/benchmarking/k8s-benchmark/stack_run_config.yaml
index 7eccb979c6b..6103f8e5be2 100644
--- a/benchmarking/k8s-benchmark/stack_run_config.yaml
+++ b/benchmarking/k8s-benchmark/stack_run_config.yaml
@@ -18,9 +18,6 @@ providers:
- provider_id: sentence-transformers
provider_type: inline::sentence-transformers
config: {}
- - provider_id: transformers
- provider_type: inline::transformers
- config: {}
files:
- provider_id: builtin-files
provider_type: inline::localfs
@@ -108,7 +105,7 @@ registered_resources:
model_type: embedding
- metadata: {}
model_id: Qwen/Qwen3-Reranker-0.6B
- provider_id: transformers
+ provider_id: sentence-transformers
model_type: rerank
- model_id: ${env.INFERENCE_MODEL}
provider_id: vllm-inference
diff --git a/benchmarking/rag/config.yaml b/benchmarking/rag/config.yaml
index 6ffba494805..40f5b0c6985 100644
--- a/benchmarking/rag/config.yaml
+++ b/benchmarking/rag/config.yaml
@@ -23,8 +23,6 @@ providers:
provider_type: inline::sentence-transformers
config:
trust_remote_code: true
- - provider_id: transformers
- provider_type: inline::transformers
vector_io:
- provider_id: milvus
provider_type: remote::milvus
@@ -99,7 +97,7 @@ vector_stores:
provider_id: sentence-transformers
model_id: nomic-ai/nomic-embed-text-v1.5
default_reranker_model:
- provider_id: transformers
+ provider_id: sentence-transformers
model_id: Qwen/Qwen3-Reranker-0.6B
default_search_mode: hybrid
file_search_params:
diff --git a/client-sdks/openapi/Makefile b/client-sdks/openapi/Makefile
index 3f78b626e58..dbb1e7004cd 100644
--- a/client-sdks/openapi/Makefile
+++ b/client-sdks/openapi/Makefile
@@ -33,8 +33,8 @@ PROCESSED_SPEC := openapi-hierarchical.yml
HIERARCHY_FILE := api-hierarchy.yml
SDK_OUTPUT_DIR := sdks/python
-# Extract version from root pyproject.toml
-VERSION := $(shell grep 'fallback_version' ../../pyproject.toml | cut -d'"' -f2)
+# Extract version from root pyproject.toml; override with make VERSION=X.Y.Z
+VERSION ?= $(shell grep 'fallback_version' ../../pyproject.toml | cut -d'"' -f2)
.PHONY: all sdk openapi hierarchy clean help version check-generator generate-config
diff --git a/client-sdks/openapi/build_hierarchy.py b/client-sdks/openapi/build_hierarchy.py
index d671808ab6a..fe217e4400e 100755
--- a/client-sdks/openapi/build_hierarchy.py
+++ b/client-sdks/openapi/build_hierarchy.py
@@ -162,6 +162,47 @@ def mark_unwrappable_list_responses(spec: dict[str, Any]) -> int:
return count
+def reorder_data_field_first(spec: dict[str, Any]) -> int:
+ """Ensure 'data' is the first property in list/page response schemas.
+
+ The model_generic.mustache template emits __iter__/__getitem__/__len__ methods
+ only for the first array field in a model (using the {{#-first}} guard). If a
+ non-array field like 'object' comes before 'data', the iteration methods are
+ skipped, making the model non-iterable and breaking code that does
+ `for item in response`.
+
+ Returns the number of schemas reordered.
+ """
+ schemas = spec.get("components", {}).get("schemas", {})
+ count = 0
+
+ for schema_def in schemas.values():
+ if not isinstance(schema_def, dict):
+ continue
+ props = schema_def.get("properties")
+ if not isinstance(props, dict) or "data" not in props:
+ continue
+ data_prop = props.get("data", {})
+ if not isinstance(data_prop, dict):
+ continue
+ # Only reorder if data is an array type and not already first
+ is_array = data_prop.get("type") == "array" or "items" in data_prop
+ if not is_array:
+ continue
+ keys = list(props.keys())
+ if keys[0] == "data":
+ continue
+ # Reorder: data first, then everything else in original order
+ reordered = {"data": props["data"]}
+ for key in keys:
+ if key != "data":
+ reordered[key] = props[key]
+ schema_def["properties"] = reordered
+ count += 1
+
+ return count
+
+
def mark_streaming_operations(spec: dict[str, Any]) -> int:
"""Add x-streaming vendor extensions for operations with text/event-stream responses.
@@ -338,6 +379,10 @@ def process_openapi(input_file: str, output_file: str, hierarchy_file: str) -> N
if streaming:
print(f" Marked {streaming} endpoints with streaming type metadata")
+ reordered = reorder_data_field_first(spec)
+ if reordered:
+ print(f" Reordered 'data' to first property in {reordered} schemas")
+
# --- Write output ---
with open(output_file, "w") as f:
yaml_handler.dump(spec, f)
diff --git a/client-sdks/openapi/openapi-config.json b/client-sdks/openapi/openapi-config.json
index 46b484378b5..25cadbebbf5 100644
--- a/client-sdks/openapi/openapi-config.json
+++ b/client-sdks/openapi/openapi-config.json
@@ -1,6 +1,6 @@
{
- "packageName": "ogx_client",
- "projectName": "ogx-client",
+ "packageName": "ogx_open_client",
+ "projectName": "ogx-open-client",
"packageVersion": "0.5.0.dev0",
"removeOperationIdPrefix": true,
"removeOperationIdPrefixDelimiter": "_",
@@ -8,35 +8,35 @@
"files": {
"_types.mustache": {
"templateType": "SupportingFiles",
- "destinationFilename": "ogx_client/_types.py"
+ "destinationFilename": "ogx_open_client/_types.py"
},
"_exceptions.mustache": {
"templateType": "SupportingFiles",
- "destinationFilename": "ogx_client/_exceptions.py"
+ "destinationFilename": "ogx_open_client/_exceptions.py"
},
"_version.mustache": {
"templateType": "SupportingFiles",
- "destinationFilename": "ogx_client/_version.py"
+ "destinationFilename": "ogx_open_client/_version.py"
},
"ogx_client.mustache": {
"templateType": "SupportingFiles",
- "destinationFilename": "ogx_client/ogx_client.py"
+ "destinationFilename": "ogx_open_client/ogx_client.py"
},
"async_api_client.mustache": {
"templateType": "SupportingFiles",
- "destinationFilename": "ogx_client/async_api_client.py"
+ "destinationFilename": "ogx_open_client/async_api_client.py"
},
"async_api_response.mustache": {
"templateType": "SupportingFiles",
- "destinationFilename": "ogx_client/async_api_response.py"
+ "destinationFilename": "ogx_open_client/async_api_response.py"
},
"async_stream.mustache": {
"templateType": "SupportingFiles",
- "destinationFilename": "ogx_client/async_stream.py"
+ "destinationFilename": "ogx_open_client/async_stream.py"
},
"stream.mustache": {
"templateType": "SupportingFiles",
- "destinationFilename": "ogx_client/stream.py"
+ "destinationFilename": "ogx_open_client/stream.py"
}
}
}
diff --git a/client-sdks/openapi/templates/python/api_response.mustache b/client-sdks/openapi/templates/python/api_response.mustache
index 6a0843448ee..7e9c28f03d6 100644
--- a/client-sdks/openapi/templates/python/api_response.mustache
+++ b/client-sdks/openapi/templates/python/api_response.mustache
@@ -1,21 +1,59 @@
"""API response object."""
from __future__ import annotations
-from typing import Generic, Mapping, TypeVar
+import json as _json
+from typing import Any, Generic, Mapping, TypeVar
from pydantic import Field, StrictInt, StrictBytes, BaseModel
T = TypeVar("T")
class ApiResponse(BaseModel, Generic[T]):
"""
- API response object
+ API response object.
+
+ Supports two construction styles:
+ - Normal: ApiResponse(status_code=200, headers=..., data=..., raw_data=b"...")
+ - Stainless-compatible: ApiResponse(raw=httpx_response, cast_to=MyModel, ...)
+ Used by OGXAsLibraryClient to wrap in-process responses.
"""
status_code: StrictInt = Field(description="HTTP status code")
headers: Mapping[str, str] | None = Field(None, description="HTTP headers")
- data: T = Field(description="Deserialized data given the data type")
- raw_data: StrictBytes = Field(description="Raw data (HTTP response body)")
+ data: T = Field(default=None, description="Deserialized data given the data type")
+ raw_data: StrictBytes = Field(default=b"", description="Raw data (HTTP response body)")
model_config = {
"arbitrary_types_allowed": True
}
+
+ def __init__(self, *, raw: Any = None, cast_to: Any = None, **kwargs: Any) -> None:
+ # Accept and ignore stainless-specific kwargs (client, options, stream, stream_cls, retries_taken)
+ for key in ("client", "options", "stream", "stream_cls", "retries_taken"):
+ kwargs.pop(key, None)
+ if raw is not None:
+ super().__init__(
+ status_code=raw.status_code,
+ headers=dict(raw.headers) if raw.headers else None,
+ data=None,
+ raw_data=raw.content if isinstance(raw.content, bytes) else b"",
+ **kwargs,
+ )
+ object.__setattr__(self, "_raw", raw)
+ object.__setattr__(self, "_cast_to", cast_to)
+ else:
+ super().__init__(**kwargs)
+ object.__setattr__(self, "_raw", None)
+ object.__setattr__(self, "_cast_to", None)
+
+ def parse(self, *, to: Any = None) -> Any:
+ """Parse the raw response into the target type."""
+ cast_to = to or getattr(self, "_cast_to", None)
+ raw = getattr(self, "_raw", None)
+ if raw is None or cast_to is None:
+ return self.data
+ data = raw.json()
+ if hasattr(cast_to, "from_dict"):
+ return cast_to.from_dict(data)
+ if hasattr(cast_to, "model_validate"):
+ return cast_to.model_validate(data)
+ return data
diff --git a/client-sdks/openapi/templates/python/async_api_response.mustache b/client-sdks/openapi/templates/python/async_api_response.mustache
index 764991c7983..7033d2eeb5d 100644
--- a/client-sdks/openapi/templates/python/async_api_response.mustache
+++ b/client-sdks/openapi/templates/python/async_api_response.mustache
@@ -9,18 +9,32 @@ T = TypeVar("T")
class AsyncApiResponse(Generic[T]):
"""
- Async API response object
- """
+ Async API response object.
- def __init__(self, response: httpx.Response) -> None:
- """
- Initialize AsyncApiResponse.
+ Supports two construction styles:
+ - Normal: AsyncApiResponse(response=httpx_response)
+ - Stainless-compatible: AsyncApiResponse(raw=httpx_response, cast_to=MyModel, stream=True, stream_cls=AsyncStream[T], ...)
+ Used by OGXAsLibraryClient to wrap in-process responses.
+ """
- :param response: httpx.Response object
- """
- self._response = response
+ def __init__(
+ self,
+ response: httpx.Response | None = None,
+ *,
+ raw: httpx.Response | None = None,
+ cast_to: Any = None,
+ stream: bool = False,
+ stream_cls: Any = None,
+ **kwargs: Any,
+ ) -> None:
+ self._response = response or raw
+ if self._response is None:
+ raise ValueError("Either 'response' or 'raw' must be provided")
self._data: T | None = None
self._raw_data: bytes | None = None
+ self._cast_to = cast_to
+ self._stream = stream
+ self._stream_cls = stream_cls
@property
def status_code(self) -> int:
@@ -70,23 +84,39 @@ class AsyncApiResponse(Generic[T]):
"""
Parse the response data.
+ Handles both normal and stainless-compatible construction styles.
+
:param cast_to: Optional type to cast the response to
:return: Parsed response data
"""
- if cast_to is None:
+ # Stainless-compatible streaming: construct the stream class directly
+ if self._stream and self._stream_cls:
+ from typing import get_args
+ args = get_args(self._stream_cls)
+ chunk_type = args[0] if args else None
+ return self._stream_cls( # type: ignore
+ response=self._response,
+ client=None,
+ cast_to=chunk_type,
+ )
+
+ # Stainless-compatible non-streaming: use stored cast_to
+ effective_cast_to = cast_to or self._cast_to
+ if effective_cast_to is None:
return await self.json() # type: ignore
# Handle different response types
- if cast_to == bytes:
+ if effective_cast_to == bytes:
return await self.read() # type: ignore
- elif cast_to == str:
+ elif effective_cast_to == str:
return await self.text() # type: ignore
else:
# Assume JSON response that can be parsed
json_data = await self.json()
- if hasattr(cast_to, 'model_validate'):
- # Pydantic model
- return cast_to.model_validate(json_data) # type: ignore
+ if hasattr(effective_cast_to, 'from_dict'):
+ return effective_cast_to.from_dict(json_data) # type: ignore
+ elif hasattr(effective_cast_to, 'model_validate'):
+ return effective_cast_to.model_validate(json_data) # type: ignore
else:
return json_data # type: ignore
diff --git a/client-sdks/openapi/templates/python/async_stream.mustache b/client-sdks/openapi/templates/python/async_stream.mustache
index ae15798802a..fcc27bac5be 100644
--- a/client-sdks/openapi/templates/python/async_stream.mustache
+++ b/client-sdks/openapi/templates/python/async_stream.mustache
@@ -21,16 +21,17 @@ class AsyncStream(Generic[T]):
def __init__(
self,
response: httpx.Response,
- client: AsyncApiClient,
+ client: AsyncApiClient | None = None,
*,
cast_to: type[T] | None = None,
decoder: Callable[[str], T] | None = None,
+ **kwargs: Any,
) -> None:
"""
Initialize AsyncStream.
:param response: httpx.Response object with streaming enabled
- :param client: AsyncApiClient instance
+ :param client: AsyncApiClient instance (optional for library client usage)
:param cast_to: Optional type to cast streamed data to
:param decoder: Optional custom decoder function
"""
diff --git a/client-sdks/openapi/templates/python/httpx/rest.mustache b/client-sdks/openapi/templates/python/httpx/rest.mustache
index 4dc8409ebe3..0c7adefac2e 100644
--- a/client-sdks/openapi/templates/python/httpx/rest.mustache
+++ b/client-sdks/openapi/templates/python/httpx/rest.mustache
@@ -145,11 +145,14 @@ class RESTClientObject:
k, v = param
if isinstance(v, tuple) and len(v) == 3:
files.append((k, v))
+ elif isinstance(v, dict):
+ # Flatten nested dicts into bracket-notation keys
+ # e.g. {"anchor": "created_at", "seconds": 3600}
+ # becomes expires_after[anchor]=created_at&expires_after[seconds]=3600
+ for subkey, subval in v.items():
+ data[f"{k}[{subkey}]"] = str(subval) if not isinstance(subval, str) else subval
else:
- # Ensures that dict objects are serialized
- if isinstance(v, dict):
- v = json.dumps(v)
- elif isinstance(v, int):
+ if isinstance(v, int):
v = str(v)
data[k] = v
diff --git a/client-sdks/openapi/templates/python/model_anyof.mustache b/client-sdks/openapi/templates/python/model_anyof.mustache
index e5e1c0e7c7d..b2ea1b65327 100644
--- a/client-sdks/openapi/templates/python/model_anyof.mustache
+++ b/client-sdks/openapi/templates/python/model_anyof.mustache
@@ -127,10 +127,15 @@ class {{classname}}({{#parent}}{{{.}}}{{/parent}}{{^parent}}BaseModel{{/parent}}
error_messages.append(str(e))
{{/isPrimitiveType}}
{{^isPrimitiveType}}
- if not isinstance(v, {{{dataType}}}):
- error_messages.append(f"Error! Input type `{type(v)}` is not `{{{dataType}}}`")
- else:
+ if isinstance(v, {{{dataType}}}):
return v
+ if isinstance(v, (str, int)):
+ try:
+ v = {{{dataType}}}(v)
+ return v
+ except Exception:
+ pass
+ error_messages.append(f"Error! Input type `{type(v)}` is not `{{{dataType}}}`")
{{/isPrimitiveType}}
{{/isContainer}}
diff --git a/client-sdks/openapi/templates/python/model_generic.mustache b/client-sdks/openapi/templates/python/model_generic.mustache
index 3895ba9e041..ba64a780656 100644
--- a/client-sdks/openapi/templates/python/model_generic.mustache
+++ b/client-sdks/openapi/templates/python/model_generic.mustache
@@ -151,15 +151,18 @@ class {{classname}}({{#parent}}{{{.}}}{{/parent}}{{^parent}}BaseModel{{/parent}}
return value.actual_instance
# If the value is a dict, unwrap any OneOf instances in its values
+ # Only create a new dict if unwrapping is actually needed, to preserve
+ # mutability of the original (e.g. additional_properties)
if isinstance(value, dict):
- unwrapped = {}
- for k, v in value.items():
- # Check if this is a OneOf wrapper with actual_instance
- if hasattr(v, 'actual_instance') and v.actual_instance is not None:
- unwrapped[k] = v.actual_instance
- else:
- unwrapped[k] = v
- return unwrapped
+ needs_unwrap = any(
+ hasattr(v, 'actual_instance') and v.actual_instance is not None
+ for v in value.values()
+ )
+ if needs_unwrap:
+ return {
+ k: v.actual_instance if hasattr(v, 'actual_instance') and v.actual_instance is not None else v
+ for k, v in value.items()
+ }
return value
diff --git a/client-sdks/openapi/templates/python/ogx_client.mustache b/client-sdks/openapi/templates/python/ogx_client.mustache
index 4fd2f59746a..998b3c8ee56 100644
--- a/client-sdks/openapi/templates/python/ogx_client.mustache
+++ b/client-sdks/openapi/templates/python/ogx_client.mustache
@@ -43,6 +43,7 @@ class OgxClient:
cookie: str | None = None,
default_headers: Mapping[str, str] | None = None,
provider_data: Mapping[str, Any] | None = None,
+ api_key: str | None = None,
**kwargs,
) -> None:
"""
@@ -54,7 +55,10 @@ class OgxClient:
header_name: Optional header name for authentication.
header_value: Optional header value for authentication.
cookie: Optional cookie string for authentication.
+ api_key: Optional API key (stored for compatibility with stainless SDK consumers).
"""
+ self.api_key = api_key
+
# Handle string URL as configuration
if isinstance(configuration, str):
configuration = Configuration(host=configuration)
@@ -136,6 +140,7 @@ class AsyncOgxClient:
header_name: str | None = None,
header_value: str | None = None,
cookie: str | None = None,
+ api_key: str | None = None,
**kwargs,
) -> None:
"""
@@ -147,7 +152,10 @@ class AsyncOgxClient:
header_name: Optional header name for authentication.
header_value: Optional header value for authentication.
cookie: Optional cookie string for authentication.
+ api_key: Optional API key (stored for compatibility with stainless SDK consumers).
"""
+ self.api_key = api_key
+
# Handle string URL as configuration
if isinstance(configuration, str):
configuration = Configuration(host=configuration)
diff --git a/client-sdks/openapi/templates/python/partial_api.mustache b/client-sdks/openapi/templates/python/partial_api.mustache
index 0c14c068afd..2f6273a8863 100644
--- a/client-sdks/openapi/templates/python/partial_api.mustache
+++ b/client-sdks/openapi/templates/python/partial_api.mustache
@@ -35,6 +35,12 @@
{{#bodyParam}}{{^isPrimitiveType}}
# If body param not provided, construct from kwargs
if {{paramName}} is None and kwargs:
+ # Merge extra_body contents into top-level kwargs (OpenAI SDK convention).
+ # The OpenAI SDK treats extra_body as a dict whose keys are merged into
+ # the request body; replicate that behavior here.
+ _extra_body = kwargs.pop("extra_body", None)
+ if isinstance(_extra_body, dict):
+ kwargs.update(_extra_body)
try:
# Try proper type conversion via from_json
{{paramName}} = {{{dataType}}}.from_json(json.dumps(kwargs))
diff --git a/client-sdks/openapi/templates/python/rest.mustache b/client-sdks/openapi/templates/python/rest.mustache
index 757843b20be..5cc5114cb54 100644
--- a/client-sdks/openapi/templates/python/rest.mustache
+++ b/client-sdks/openapi/templates/python/rest.mustache
@@ -198,11 +198,14 @@ class RESTClientObject:
if isinstance(v, tuple) and len(v) == 3:
# File tuple: (filename, file_content, content_type)
files.append((k, v))
+ elif isinstance(v, dict):
+ # Flatten nested dicts into bracket-notation keys
+ # e.g. {"anchor": "created_at", "seconds": 3600}
+ # becomes expires_after[anchor]=created_at&expires_after[seconds]=3600
+ for subkey, subval in v.items():
+ data[f"{k}[{subkey}]"] = str(subval) if not isinstance(subval, str) else subval
else:
- # Regular field
- if isinstance(v, dict):
- v = json.dumps(v)
- elif isinstance(v, int):
+ if isinstance(v, int):
v = str(v)
data[k] = v
diff --git a/client-sdks/stainless/openapi.yml b/client-sdks/stainless/openapi.yml
index 962e8cb5c17..d85d75d7427 100644
--- a/client-sdks/stainless/openapi.yml
+++ b/client-sdks/stainless/openapi.yml
@@ -2173,7 +2173,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: List vector stores (OpenAI-compatible).
description: List vector stores (OpenAI-compatible).
operationId: openai_list_vector_stores_v1_vector_stores_get
@@ -2254,7 +2254,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Create a vector store (OpenAI-compatible).
description: Create a vector store (OpenAI-compatible).
operationId: openai_create_vector_store_v1_vector_stores_post
@@ -2298,7 +2298,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve a vector store (OpenAI-compatible).
description: Retrieve a vector store (OpenAI-compatible).
operationId: openai_retrieve_vector_store_v1_vector_stores__vector_store_id__get
@@ -2342,7 +2342,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Update a vector store (OpenAI-compatible).
description: Update a vector store (OpenAI-compatible).
operationId: openai_update_vector_store_v1_vector_stores__vector_store_id__post
@@ -2395,7 +2395,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Delete a vector store (OpenAI-compatible).
description: Delete a vector store (OpenAI-compatible).
operationId: openai_delete_vector_store_v1_vector_stores__vector_store_id__delete
@@ -2440,7 +2440,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Create a vector store file batch (OpenAI-compatible).
description: Create a vector store file batch (OpenAI-compatible).
operationId: openai_create_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches_post
@@ -2494,7 +2494,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve a vector store file batch (OpenAI-compatible).
description: Retrieve a vector store file batch (OpenAI-compatible).
operationId: openai_retrieve_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches__batch_id__get
@@ -2550,7 +2550,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Cancel a vector store file batch (OpenAI-compatible).
description: Cancel a vector store file batch (OpenAI-compatible).
operationId: openai_cancel_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches__batch_id__cancel_post
@@ -2606,7 +2606,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: List files in a vector store file batch (OpenAI-compatible).
description: List files in a vector store file batch (OpenAI-compatible).
operationId: openai_list_files_in_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches__batch_id__files_get
@@ -2717,7 +2717,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: List files in a vector store (OpenAI-compatible).
description: List files in a vector store (OpenAI-compatible).
operationId: openai_list_files_in_vector_store_v1_vector_stores__vector_store_id__files_get
@@ -2821,7 +2821,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Attach a file to a vector store (OpenAI-compatible).
description: Attach a file to a vector store (OpenAI-compatible).
operationId: openai_attach_file_to_vector_store_v1_vector_stores__vector_store_id__files_post
@@ -2875,7 +2875,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve a vector store file (OpenAI-compatible).
description: Retrieve a vector store file (OpenAI-compatible).
operationId: openai_retrieve_vector_store_file_v1_vector_stores__vector_store_id__files__file_id__get
@@ -2930,7 +2930,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Update a vector store file (OpenAI-compatible).
description: Update a vector store file (OpenAI-compatible).
operationId: openai_update_vector_store_file_v1_vector_stores__vector_store_id__files__file_id__post
@@ -2978,7 +2978,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Delete a vector store file (OpenAI-compatible).
description: Delete a vector store file (OpenAI-compatible).
operationId: openai_delete_vector_store_file_v1_vector_stores__vector_store_id__files__file_id__delete
@@ -3034,7 +3034,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve vector store file contents (OpenAI-compatible).
description: Retrieve vector store file contents (OpenAI-compatible).
operationId: openai_retrieve_vector_store_file_contents_v1_vector_stores__vector_store_id__files__file_id__content_get
@@ -3112,7 +3112,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Search a vector store (OpenAI-compatible).
description: Search a vector store (OpenAI-compatible).
operationId: openai_search_vector_store_v1_vector_stores__vector_store_id__search_post
@@ -4045,113 +4045,548 @@ paths:
input="What is the capital of France?",
)
print(interaction.outputs[0].text)
-components:
- schemas:
- Error:
- description: Error response from the API. Roughly follows RFC 7807.
- properties:
- status:
- title: Status
- type: integer
- title:
- title: Title
- type: string
- detail:
- title: Detail
- type: string
- instance:
+ /v1alpha/skills:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/ListSkillsResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: List skills
+ description: List all skills.
+ operationId: list_skills_v1alpha_skills_get
+ parameters:
+ - name: after
+ in: query
+ required: false
+ schema:
anyOf:
- type: string
- type: 'null'
- nullable: true
- required:
- - status
- - title
- - detail
- title: Error
- type: object
- ListBatchesResponse:
- properties:
- object:
- type: string
- title: Object
+ description: Cursor for pagination
+ title: After
+ description: Cursor for pagination
+ - name: limit
+ in: query
+ required: false
+ schema:
+ type: integer
+ description: Maximum number of results
+ default: 20
+ title: Limit
+ description: Maximum number of results
+ - name: order
+ in: query
+ required: false
+ schema:
enum:
- - list
- data:
- items:
- $ref: '#/components/schemas/Batch'
- type: array
- title: Data
- description: List of batch objects
- first_id:
- anyOf:
- - type: string
- - type: 'null'
- description: ID of the first batch in the list
- last_id:
- anyOf:
- - type: string
- - type: 'null'
- description: ID of the last batch in the list
- has_more:
- type: boolean
- title: Has More
- description: Whether there are more batches available
- default: false
- type: object
- required:
- - data
- title: ListBatchesResponse
- description: Response containing a list of batch objects.
- CreateBatchRequest:
- properties:
- input_file_id:
- type: string
- title: Input File Id
- description: The ID of an uploaded file containing requests for the batch.
- endpoint:
- type: string
- title: Endpoint
- description: The endpoint to be used for all requests in the batch.
- completion_window:
+ - asc
+ - desc
type: string
- title: Completion Window
- description: The time window within which the batch should be processed.
- enum:
- - 24h
- metadata:
- anyOf:
- - additionalProperties:
- type: string
- type: object
- - type: 'null'
- description: Optional metadata for the batch.
- idempotency_key:
- anyOf:
- - type: string
- - type: 'null'
- description: Optional idempotency key. When provided, enables idempotent behavior.
- type: object
- required:
- - input_file_id
- - endpoint
- - completion_window
- title: CreateBatchRequest
- description: Request model for creating a batch.
- Batch:
- properties:
- id:
+ description: Sort order by created_at
+ default: desc
+ title: Order
+ description: Sort order by created_at
+ post:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/Skill'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Create skill
+ description: Create a skill by uploading a zip bundle containing a SKILL.md manifest.
+ operationId: create_skill_v1alpha_skills_post
+ requestBody:
+ required: true
+ content:
+ multipart/form-data:
+ schema:
+ $ref: '#/components/schemas/Body_create_skill_v1alpha_skills_post'
+ /v1alpha/skills/{skill_id}:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/Skill'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Get skill
+ description: Get metadata for a specific skill.
+ operationId: get_skill_v1alpha_skills__skill_id__get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
type: string
- title: Id
- completion_window:
+ title: Skill Id
+ post:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/Skill'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Update skill
+ description: Update a skill's default version.
+ operationId: update_skill_v1alpha_skills__skill_id__post
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
type: string
- title: Completion Window
- created_at:
- type: integer
- title: Created At
- endpoint:
+ title: Skill Id
+ requestBody:
+ required: true
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillUpdateRequest'
+ delete:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillDeleteResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Delete skill
+ description: Delete a skill and all its versions.
+ operationId: delete_skill_v1alpha_skills__skill_id__delete
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
type: string
- title: Endpoint
+ title: Skill Id
+ /v1alpha/skills/{skill_id}/content:
+ get:
+ responses:
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ '204':
+ description: The skill bundle as a zip archive.
+ tags:
+ - Skills
+ summary: Get skill content
+ description: Download the default version's zip bundle.
+ operationId: get_skill_content_v1alpha_skills__skill_id__content_get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ /v1alpha/skills/{skill_id}/versions:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/ListSkillVersionsResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: List skill versions
+ description: List all versions of a skill.
+ operationId: list_skill_versions_v1alpha_skills__skill_id__versions_get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: after
+ in: query
+ required: false
+ schema:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ title: After
+ description: Cursor for pagination
+ - name: limit
+ in: query
+ required: false
+ schema:
+ type: integer
+ description: Maximum number of results
+ default: 20
+ title: Limit
+ description: Maximum number of results
+ - name: order
+ in: query
+ required: false
+ schema:
+ enum:
+ - asc
+ - desc
+ type: string
+ description: Sort order by version
+ default: desc
+ title: Order
+ description: Sort order by version
+ post:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillVersion'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Create skill version
+ description: Upload a new version of a skill.
+ operationId: create_skill_version_v1alpha_skills__skill_id__versions_post
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ requestBody:
+ required: true
+ content:
+ multipart/form-data:
+ schema:
+ $ref: '#/components/schemas/Body_create_skill_version_v1alpha_skills__skill_id__versions_post'
+ /v1alpha/skills/{skill_id}/versions/{version}:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillVersion'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Get skill version
+ description: Get metadata for a specific skill version.
+ operationId: get_skill_version_v1alpha_skills__skill_id__versions__version__get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: version
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Version
+ delete:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillVersionDeleteResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Delete skill version
+ description: Delete a specific version of a skill.
+ operationId: delete_skill_version_v1alpha_skills__skill_id__versions__version__delete
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: version
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Version
+ /v1alpha/skills/{skill_id}/versions/{version}/content:
+ get:
+ responses:
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ '204':
+ description: The skill bundle as a zip archive.
+ tags:
+ - Skills
+ summary: Get skill version content
+ description: Download a specific version's zip bundle.
+ operationId: get_skill_version_content_v1alpha_skills__skill_id__versions__version__content_get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: version
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Version
+components:
+ schemas:
+ Error:
+ description: Error response from the API. Roughly follows RFC 7807.
+ properties:
+ status:
+ title: Status
+ type: integer
+ title:
+ title: Title
+ type: string
+ detail:
+ title: Detail
+ type: string
+ instance:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ required:
+ - status
+ - title
+ - detail
+ title: Error
+ type: object
+ ListBatchesResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/Batch'
+ type: array
+ title: Data
+ description: List of batch objects
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first batch in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last batch in the list
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more batches available
+ default: false
+ type: object
+ required:
+ - data
+ title: ListBatchesResponse
+ description: Response containing a list of batch objects.
+ CreateBatchRequest:
+ properties:
+ input_file_id:
+ type: string
+ title: Input File Id
+ description: The ID of an uploaded file containing requests for the batch.
+ endpoint:
+ type: string
+ title: Endpoint
+ description: The endpoint to be used for all requests in the batch.
+ completion_window:
+ type: string
+ title: Completion Window
+ description: The time window within which the batch should be processed.
+ enum:
+ - 24h
+ metadata:
+ anyOf:
+ - additionalProperties:
+ type: string
+ type: object
+ - type: 'null'
+ description: Optional metadata for the batch.
+ idempotency_key:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional idempotency key. When provided, enables idempotent behavior.
+ type: object
+ required:
+ - input_file_id
+ - endpoint
+ - completion_window
+ title: CreateBatchRequest
+ description: Request model for creating a batch.
+ Batch:
+ properties:
+ id:
+ type: string
+ title: Id
+ completion_window:
+ type: string
+ title: Completion Window
+ created_at:
+ type: integer
+ title: Created At
+ endpoint:
+ type: string
+ title: Endpoint
input_file_id:
type: string
title: Input File Id
@@ -5160,7 +5595,7 @@ components:
tool_calls:
description: The tool calls of the delta.
items:
- $ref: '#/components/schemas/ChatCompletionMessageToolCall'
+ $ref: '#/components/schemas/ChoiceDeltaToolCall'
title: Tool Calls
type: array
nullable: true
@@ -6651,25 +7086,25 @@ components:
title: OpenAIFileObject
description: OpenAI File object as defined in the OpenAI Files API.
ExpiresAfter:
+ description: Control expiration of uploaded files.
properties:
anchor:
- type: string
- title: Anchor
description: The anchor point for expiration, must be 'created_at'.
+ title: Anchor
+ type: string
enum:
- created_at
seconds:
- type: integer
- maximum: 2592000.0
- minimum: 3600.0
- title: Seconds
description: Seconds until expiration, between 3600 (1 hour) and 2592000 (30 days).
- type: object
+ maximum: 2592000
+ minimum: 3600
+ title: Seconds
+ type: integer
required:
- anchor
- seconds
title: ExpiresAfter
- description: Control expiration of uploaded files.
+ type: object
OpenAIFileDeleteResponse:
properties:
id:
@@ -7382,6 +7817,10 @@ components:
store:
type: boolean
title: Store
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
input:
items:
$ref: '#/components/schemas/OpenAIResponseMessageOutputUnion'
@@ -7477,6 +7916,7 @@ components:
- medium
- high
- type: 'null'
+ default: medium
type: object
title: OpenAIResponseText
description: Text response configuration for OpenAI responses.
@@ -7795,6 +8235,10 @@ components:
store:
type: boolean
title: Store
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
type: object
required:
- created_at
@@ -10509,8 +10953,24 @@ components:
title: Tools
description: Tools available to the model.
tool_choice:
- title: Tool Choice
+ oneOf:
+ - $ref: '#/components/schemas/_ToolChoiceAuto'
+ title: _ToolChoiceAuto
+ - $ref: '#/components/schemas/_ToolChoiceAny'
+ title: _ToolChoiceAny
+ - $ref: '#/components/schemas/_ToolChoiceNone'
+ title: _ToolChoiceNone
+ - $ref: '#/components/schemas/_ToolChoiceTool'
+ title: _ToolChoiceTool
+ title: _ToolChoiceAuto | ... (4 variants)
description: "How the model should select tools. One of: 'auto', 'any', 'none', or {type: 'tool', name: '...'}."
+ discriminator:
+ propertyName: type
+ mapping:
+ any: '#/components/schemas/_ToolChoiceAny'
+ auto: '#/components/schemas/_ToolChoiceAuto'
+ none: '#/components/schemas/_ToolChoiceNone'
+ tool: '#/components/schemas/_ToolChoiceTool'
stream:
type: boolean
title: Stream
@@ -11125,6 +11585,33 @@ components:
Represents token usage details including input tokens, output tokens, a
breakdown of output tokens, and the total tokens used. Only populated on
batches created after September 7, 2025.
+ Body_create_skill_v1alpha_skills_post:
+ properties:
+ file:
+ type: string
+ title: File
+ description: Zip archive containing the skill bundle.
+ format: binary
+ type: object
+ required:
+ - file
+ title: Body_create_skill_v1alpha_skills_post
+ Body_create_skill_version_v1alpha_skills__skill_id__versions_post:
+ properties:
+ file:
+ type: string
+ title: File
+ description: Zip archive containing the skill bundle.
+ format: binary
+ default:
+ type: boolean
+ title: Default
+ description: Whether to set this version as the default.
+ default: false
+ type: object
+ required:
+ - file
+ title: Body_create_skill_version_v1alpha_skills__skill_id__versions_post
Body_process_file_v1alpha_file_processors_process_post:
properties:
file:
@@ -11163,11 +11650,9 @@ components:
description: The intended purpose of the uploaded file.
expires_after:
anyOf:
- - $ref: '#/components/schemas/ExpiresAfter'
- title: ExpiresAfter
+ - type: string
- type: 'null'
description: Optional expiration settings for the file.
- title: ExpiresAfter
type: object
required:
- file
@@ -11305,52 +11790,55 @@ components:
CompactResponseRequest:
properties:
model:
- type: string
- title: Model
+ anyOf:
+ - $ref: '#/components/schemas/ModelIdsResponses'
+ - type: string
+ - type: 'null'
description: The model to use for generating the compacted summary.
input:
anyOf:
- - type: string
- - items:
- anyOf:
- - oneOf:
- - $ref: '#/components/schemas/OpenAIResponseMessage-Input'
- title: OpenAIResponseMessage-Input
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
- title: OpenAIResponseOutputMessageWebSearchToolCall-Input
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
- title: OpenAIResponseOutputMessageFileSearchToolCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
- title: OpenAIResponseOutputMessageFunctionToolCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
- title: OpenAIResponseOutputMessageMCPCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
- title: OpenAIResponseOutputMessageMCPListTools
- - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
- title: OpenAIResponseMCPApprovalRequest
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
- title: OpenAIResponseOutputMessageReasoningItem
- discriminator:
- propertyName: type
- mapping:
- file_search_call: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
- function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
- mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
- mcp_call: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
- mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
- message: '#/components/schemas/OpenAIResponseMessage-Input'
- reasoning: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
- web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
- title: OpenAIResponseMessage-Input | ... (8 variants)
- - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
- title: OpenAIResponseInputFunctionToolCallOutput
- - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
- title: OpenAIResponseMCPApprovalResponse
- - $ref: '#/components/schemas/OpenAIResponseCompaction'
- title: OpenAIResponseCompaction
- title: OpenAIResponseInputFunctionToolCallOutput | OpenAIResponseMCPApprovalResponse | OpenAIResponseCompaction
- type: array
- title: list[OpenAIResponseMessageUnion | OpenAIResponseInputFunctionToolCallOutput | ...]
+ - oneOf:
+ - type: string
+ - items:
+ anyOf:
+ - oneOf:
+ - $ref: '#/components/schemas/OpenAIResponseMessage-Input'
+ title: OpenAIResponseMessage-Input
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
+ title: OpenAIResponseOutputMessageWebSearchToolCall-Input
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
+ title: OpenAIResponseOutputMessageFileSearchToolCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
+ title: OpenAIResponseOutputMessageFunctionToolCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
+ title: OpenAIResponseOutputMessageMCPCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
+ title: OpenAIResponseOutputMessageMCPListTools
+ - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
+ title: OpenAIResponseMCPApprovalRequest
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
+ title: OpenAIResponseOutputMessageReasoningItem
+ discriminator:
+ propertyName: type
+ mapping:
+ file_search_call: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
+ function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
+ mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
+ mcp_call: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
+ mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
+ message: '#/components/schemas/OpenAIResponseMessage-Input'
+ reasoning: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
+ web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
+ title: OpenAIResponseMessage-Input | ... (8 variants)
+ - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
+ title: OpenAIResponseInputFunctionToolCallOutput
+ - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
+ title: OpenAIResponseMCPApprovalResponse
+ - $ref: '#/components/schemas/OpenAIResponseCompaction'
+ title: OpenAIResponseCompaction
+ title: OpenAIResponseInputFunctionToolCallOutput | OpenAIResponseMCPApprovalResponse | OpenAIResponseCompaction
+ type: array
+ title: list[OpenAIResponseMessageUnion | OpenAIResponseInputFunctionToolCallOutput | ...]
- type: 'null'
title: string | list[OpenAIResponseMessageUnion | OpenAIResponseInputFunctionToolCallOutput | ...]
description: Input message(s) to compact.
@@ -11741,6 +12229,11 @@ components:
type: object
- type: 'null'
description: Dictionary of metadata key-value pairs to attach to the response.
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: A stable identifier used to associate the request with an end user, for safety monitoring. Echoed back on the response.
truncation:
allOf:
- $ref: '#/components/schemas/ResponseTruncation'
@@ -12390,6 +12883,72 @@ components:
- has_more
title: ListMessageBatchesResponse
description: Response from GET /v1/messages/batches.
+ ListSkillVersionsResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/SkillVersion'
+ type: array
+ title: Data
+ description: List of skill version objects
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more results
+ default: false
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first item in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last item in the list
+ type: object
+ required:
+ - data
+ title: ListSkillVersionsResponse
+ description: Response from listing skill versions.
+ ListSkillsResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/Skill'
+ type: array
+ title: Data
+ description: List of skill objects
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more results
+ default: false
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first item in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last item in the list
+ type: object
+ required:
+ - data
+ title: ListSkillsResponse
+ description: Response from listing skills.
ListToolsResponse:
properties:
data:
@@ -13711,6 +14270,146 @@ components:
- version
title: SetDefaultVersionBodyRequest
description: Request body model for setting the default version of a prompt.
+ Skill:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: Unique identifier for the skill
+ created_at:
+ type: integer
+ title: Created At
+ description: Unix timestamp when the skill was created
+ default_version:
+ type: string
+ title: Default Version
+ description: Version used when no version is specified
+ default: '1'
+ description:
+ type: string
+ title: Description
+ description: Description of what the skill does
+ latest_version:
+ type: string
+ title: Latest Version
+ description: Most recently uploaded version number
+ default: '1'
+ name:
+ type: string
+ title: Name
+ description: Human-readable name from SKILL.md frontmatter
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill
+ type: object
+ required:
+ - id
+ - created_at
+ - description
+ - name
+ title: Skill
+ description: A skill resource. Matches OpenAI Skill wire format.
+ SkillDeleteResponse:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: ID of the deleted skill
+ deleted:
+ type: boolean
+ title: Deleted
+ description: Whether the skill was successfully deleted
+ default: true
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.deleted
+ type: object
+ required:
+ - id
+ title: SkillDeleteResponse
+ description: Response from deleting a skill. Matches OpenAI DeletedSkill wire format.
+ SkillUpdateRequest:
+ properties:
+ default_version:
+ type: string
+ title: Default Version
+ description: Version number to set as the default
+ type: object
+ required:
+ - default_version
+ title: SkillUpdateRequest
+ description: Request to update a skill's default version.
+ SkillVersion:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: Unique identifier for this version
+ created_at:
+ type: integer
+ title: Created At
+ description: Unix timestamp when this version was created
+ description:
+ type: string
+ title: Description
+ description: Description of the skill version
+ name:
+ type: string
+ title: Name
+ description: Name of the skill version
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.version
+ skill_id:
+ type: string
+ title: Skill Id
+ description: ID of the parent skill
+ version:
+ type: string
+ title: Version
+ description: Version number as a string
+ type: object
+ required:
+ - id
+ - created_at
+ - description
+ - name
+ - skill_id
+ - version
+ title: SkillVersion
+ description: A specific version of a skill. Matches OpenAI SkillVersion wire format.
+ SkillVersionDeleteResponse:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: ID of the deleted skill
+ deleted:
+ type: boolean
+ title: Deleted
+ description: Whether the version was successfully deleted
+ default: true
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.version.deleted
+ version:
+ type: string
+ title: Version
+ description: Version that was deleted
+ type: object
+ required:
+ - id
+ - version
+ title: SkillVersionDeleteResponse
+ description: Response from deleting a skill version. Matches OpenAI DeletedSkillVersion wire format.
UpdatePromptBodyRequest:
properties:
prompt:
@@ -13967,11 +14666,64 @@ components:
- type: 'null'
timezone:
anyOf:
- - type: string
+ - type: string
+ - type: 'null'
+ type: object
+ title: WebSearchUserLocation
+ description: Approximate user location to refine web search results.
+ _ToolChoiceAny:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - any
+ disable_parallel_tool_use:
+ anyOf:
+ - type: boolean
+ - type: 'null'
+ type: object
+ title: _ToolChoiceAny
+ _ToolChoiceAuto:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - auto
+ disable_parallel_tool_use:
+ anyOf:
+ - type: boolean
+ - type: 'null'
+ type: object
+ title: _ToolChoiceAuto
+ _ToolChoiceNone:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - none
+ type: object
+ title: _ToolChoiceNone
+ _ToolChoiceTool:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - tool
+ name:
+ type: string
+ title: Name
+ disable_parallel_tool_use:
+ anyOf:
+ - type: boolean
- type: 'null'
type: object
- title: WebSearchUserLocation
- description: Approximate user location to refine web search results.
+ required:
+ - name
+ title: _ToolChoiceTool
_URLOrData:
properties:
url:
@@ -14622,6 +15374,7 @@ components:
- batches
- vector_io
- tool_runtime
+ - container_runtime
- models
- vector_stores
- tool_groups
@@ -14630,8 +15383,10 @@ components:
- prompts
- conversations
- connectors
+ - containers
- messages
- interactions
+ - skills
- inspect
- admin
title: Api
@@ -15422,219 +16177,929 @@ components:
embedding_model:
title: Embedding Model
type: string
- embedding_dimension:
- title: Embedding Dimension
- type: integer
+ embedding_dimension:
+ title: Embedding Dimension
+ type: integer
+ required:
+ - content
+ - chunk_id
+ - chunk_metadata
+ - embedding
+ - embedding_model
+ - embedding_dimension
+ title: EmbeddedChunk
+ type: object
+ VectorStoreCreateRequest:
+ description: Request to create a vector store.
+ properties:
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ description:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ file_ids:
+ items:
+ type: string
+ title: File Ids
+ type: array
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/VectorStoreExpirationAfter'
+ title: VectorStoreExpirationAfter
+ - type: 'null'
+ nullable: true
+ title: VectorStoreExpirationAfter
+ chunking_strategy:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ metadata:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ title: VectorStoreCreateRequest
+ type: object
+ VectorStoreModifyRequest:
+ description: Request to modify a vector store.
+ properties:
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/VectorStoreExpirationAfter'
+ title: VectorStoreExpirationAfter
+ - type: 'null'
+ nullable: true
+ title: VectorStoreExpirationAfter
+ metadata:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ title: VectorStoreModifyRequest
+ type: object
+ VectorStoreSearchRequest:
+ description: Request to search a vector store.
+ properties:
+ query:
+ anyOf:
+ - type: string
+ - items:
+ type: string
+ type: array
+ title: list[string]
+ title: string | list[string]
+ filters:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ max_num_results:
+ default: 10
+ maximum: 50
+ minimum: 1
+ title: Max Num Results
+ type: integer
+ ranking_options:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ rewrite_query:
+ default: false
+ title: Rewrite Query
+ type: boolean
+ required:
+ - query
+ title: VectorStoreSearchRequest
+ type: object
+ ChunkForDeletion:
+ description: Information needed to delete a chunk from a vector store.
+ properties:
+ chunk_id:
+ title: Chunk Id
+ type: string
+ document_id:
+ title: Document Id
+ type: string
+ required:
+ - chunk_id
+ - document_id
+ title: ChunkForDeletion
+ type: object
+ DeleteChunksRequest:
+ description: Request body for deleting chunks from a vector store.
+ properties:
+ vector_store_id:
+ description: The ID of the vector store to delete chunks from.
+ title: Vector Store Id
+ type: string
+ chunks:
+ description: The list of chunks to delete.
+ items:
+ $ref: '#/components/schemas/ChunkForDeletion'
+ title: Chunks
+ type: array
+ required:
+ - vector_store_id
+ - chunks
+ title: DeleteChunksRequest
+ type: object
+ ListBatchesRequest:
+ description: Request model for listing batches.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional cursor for pagination. Returns batches after this ID.
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of batches to return. Defaults to 20.
+ title: Limit
+ type: integer
+ title: ListBatchesRequest
+ type: object
+ RetrieveBatchRequest:
+ description: Request model for retrieving a batch.
+ properties:
+ batch_id:
+ description: The ID of the batch to retrieve.
+ title: Batch Id
+ type: string
+ required:
+ - batch_id
+ title: RetrieveBatchRequest
+ type: object
+ CancelBatchRequest:
+ description: Request model for canceling a batch.
+ properties:
+ batch_id:
+ description: The ID of the batch to cancel.
+ title: Batch Id
+ type: string
+ required:
+ - batch_id
+ title: CancelBatchRequest
+ type: object
+ JobStatus:
+ description: Status of a job execution.
+ enum:
+ - completed
+ - in_progress
+ - failed
+ - scheduled
+ - cancelled
+ title: JobStatus
+ type: string
+ Job:
+ description: A job execution instance with status tracking.
+ properties:
+ job_id:
+ title: Job Id
+ type: string
+ status:
+ $ref: '#/components/schemas/JobStatus'
+ required:
+ - job_id
+ - status
+ title: Job
+ type: object
+ DialogType:
+ description: Parameter type for dialog data with semantic output labels.
+ properties:
+ type:
+ title: Type
+ type: string
+ enum:
+ - dialog
+ title: DialogType
+ type: object
+ ContainerExpiresAfter:
+ description: |-
+ Control expiration of a container.
+
+ Anchored on ``last_active_at`` (each shell execution or file operation
+ refreshes the anchor). Operator-set bounds protect the host from
+ long-lived sandboxes.
+ properties:
+ anchor:
+ description: The anchor point for expiration. Must be 'last_active_at'.
+ title: Anchor
+ type: string
+ enum:
+ - last_active_at
+ minutes:
+ description: Minutes of inactivity after the anchor before the container expires.
+ maximum: 1440
+ minimum: 1
+ title: Minutes
+ type: integer
+ required:
+ - minutes
+ title: ContainerExpiresAfter
+ type: object
+ NetworkCredential:
+ description: |-
+ A named credential available to outbound network calls.
+
+ The ``value`` should be a secret reference (e.g. ``${env.MY_SECRET}``)
+ in operator-supplied configuration, never a raw secret in a request body.
+ properties:
+ name:
+ description: Logical name used by the container to look up the credential.
+ title: Name
+ type: string
+ value:
+ description: Secret reference or literal value to be injected into the container.
+ format: password
+ title: Value
+ type: string
+ writeOnly: true
+ required:
+ - name
+ - value
+ title: NetworkCredential
+ type: object
+ NetworkDomainCredential:
+ description: Bind a ``NetworkCredential`` to a specific outbound domain.
+ properties:
+ domain:
+ description: Fully-qualified domain name to which the credential applies.
+ title: Domain
+ type: string
+ credential:
+ $ref: '#/components/schemas/NetworkCredential'
+ description: Credential injected on outbound calls to this domain.
required:
- - content
- - chunk_id
- - chunk_metadata
- - embedding
- - embedding_model
- - embedding_dimension
- title: EmbeddedChunk
+ - domain
+ - credential
+ title: NetworkDomainCredential
type: object
- VectorStoreCreateRequest:
- description: Request to create a vector store.
+ NetworkPolicyMode:
+ description: Egress policy mode applied to a container's outbound network.
+ enum:
+ - deny
+ - allow_list
+ - allow_all
+ title: NetworkPolicyMode
+ type: string
+ NetworkPolicy:
+ description: |-
+ Operator-set egress policy for a container.
+
+ A NetworkPolicy is the *upper bound* — request-supplied
+ ``NetworkPolicyExtended`` values may only narrow this policy.
+ properties:
+ mode:
+ $ref: '#/components/schemas/NetworkPolicyMode'
+ default: deny
+ description: Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.
+ allow_domains:
+ description: Domains permitted for outbound traffic. Used when mode is 'allow_list'.
+ items:
+ type: string
+ title: Allow Domains
+ type: array
+ deny_domains:
+ description: Domains explicitly blocked. Takes precedence over 'allow_domains'.
+ items:
+ type: string
+ title: Deny Domains
+ type: array
+ title: NetworkPolicy
+ type: object
+ NetworkPolicyExtended:
+ description: |-
+ Request-layer extension of an operator NetworkPolicy.
+
+ The request may add domain credentials and narrow allow/deny lists, but
+ cannot expand the operator default — enforcement is performed at the API
+ layer; see issue #5892 task 8.
+ properties:
+ mode:
+ $ref: '#/components/schemas/NetworkPolicyMode'
+ default: deny
+ description: Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.
+ allow_domains:
+ description: Domains permitted for outbound traffic. Used when mode is 'allow_list'.
+ items:
+ type: string
+ title: Allow Domains
+ type: array
+ deny_domains:
+ description: Domains explicitly blocked. Takes precedence over 'allow_domains'.
+ items:
+ type: string
+ title: Deny Domains
+ type: array
+ domain_credentials:
+ description: Per-domain credentials injected on outbound calls from this container.
+ items:
+ $ref: '#/components/schemas/NetworkDomainCredential'
+ title: Domain Credentials
+ type: array
+ title: NetworkPolicyExtended
+ type: object
+ ContainerStatus:
+ description: Lifecycle status of a container.
+ enum:
+ - active
+ - expired
+ title: ContainerStatus
+ type: string
+ Container:
+ description: |-
+ A sandboxed execution environment.
+
+ Mirrors the OpenAI Containers API resource with OGX-specific extensions
+ for network policy and image selection.
properties:
+ id:
+ description: Identifier for the container.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container'.
+ title: Object
+ type: string
+ enum:
+ - container
+ created_at:
+ description: Unix timestamp (in seconds) for when the container was created.
+ title: Created At
+ type: integer
+ status:
+ $ref: '#/components/schemas/ContainerStatus'
+ description: Current lifecycle status.
+ last_active_at:
+ description: Unix timestamp (in seconds) of the last operation performed against this container.
+ title: Last Active At
+ type: integer
name:
anyOf:
- type: string
- type: 'null'
+ description: Human-readable name for the container.
nullable: true
- description:
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration settings.
+ nullable: true
+ title: ContainerExpiresAfter
+ image:
anyOf:
- type: string
- type: 'null'
+ description: Container image used to run the sandbox. May be operator-locked.
+ nullable: true
+ network_policy:
+ anyOf:
+ - $ref: '#/components/schemas/NetworkPolicy'
+ title: NetworkPolicy
+ - type: 'null'
+ description: Effective network policy after layering operator defaults with request extensions.
+ nullable: true
+ title: NetworkPolicy
+ required:
+ - id
+ - created_at
+ - status
+ - last_active_at
+ title: Container
+ type: object
+ ContainerCreateRequest:
+ description: Request body for ``POST /containers``.
+ properties:
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Human-readable name for the container.
nullable: true
file_ids:
+ description: Files (from the Files API) to seed into the container at /mnt/data/.
items:
type: string
title: File Ids
type: array
expires_after:
anyOf:
- - $ref: '#/components/schemas/VectorStoreExpirationAfter'
- title: VectorStoreExpirationAfter
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
- type: 'null'
+ description: Inactivity-based expiration settings.
nullable: true
- title: VectorStoreExpirationAfter
- chunking_strategy:
+ title: ContainerExpiresAfter
+ image:
anyOf:
- - additionalProperties: true
- type: object
+ - type: string
- type: 'null'
+ description: Requested container image. The operator policy may pin or reject this value.
nullable: true
- metadata:
+ network_policy:
anyOf:
- - additionalProperties: true
- type: object
+ - $ref: '#/components/schemas/NetworkPolicyExtended'
+ title: NetworkPolicyExtended
- type: 'null'
+ description: Request-supplied network policy extension. Must be a subset of the operator default.
nullable: true
- title: VectorStoreCreateRequest
+ title: NetworkPolicyExtended
+ title: ContainerCreateRequest
type: object
- VectorStoreModifyRequest:
- description: Request to modify a vector store.
+ ListContainersRequest:
+ description: Query parameters for ``GET /containers``.
properties:
- name:
+ after:
anyOf:
- type: string
- type: 'null'
+ description: Cursor for pagination. Returns containers after this ID.
nullable: true
- expires_after:
+ limit:
anyOf:
- - $ref: '#/components/schemas/VectorStoreExpirationAfter'
- title: VectorStoreExpirationAfter
+ - maximum: 100
+ minimum: 1
+ type: integer
- type: 'null'
- nullable: true
- title: VectorStoreExpirationAfter
- metadata:
+ default: 20
+ description: Maximum number of containers to return (1-100).
+ order:
anyOf:
- - additionalProperties: true
- type: object
+ - $ref: '#/components/schemas/Order'
+ title: Order
- type: 'null'
- nullable: true
- title: VectorStoreModifyRequest
+ default: desc
+ description: Sort order by created_at timestamp ('asc' or 'desc').
+ title: Order
+ title: ListContainersRequest
type: object
- VectorStoreSearchRequest:
- description: Request to search a vector store.
+ ListContainersResponse:
+ description: Response for ``GET /containers``.
properties:
- query:
+ object:
+ description: The object type, which is always 'list'.
+ title: Object
+ type: string
+ enum:
+ - list
+ data:
+ description: The list of containers.
+ items:
+ $ref: '#/components/schemas/Container'
+ title: Data
+ type: array
+ first_id:
anyOf:
- type: string
- - items:
- type: string
- type: array
- title: list[string]
- title: string | list[string]
- filters:
+ - type: 'null'
+ description: ID of the first container in the page.
+ nullable: true
+ last_id:
anyOf:
- - additionalProperties: true
- type: object
+ - type: string
- type: 'null'
+ description: ID of the last container in the page.
nullable: true
- max_num_results:
- default: 10
- maximum: 50
- minimum: 1
- title: Max Num Results
+ has_more:
+ description: Whether more containers exist beyond this page.
+ title: Has More
+ type: boolean
+ required:
+ - data
+ - has_more
+ title: ListContainersResponse
+ type: object
+ GetContainerRequest:
+ properties:
+ container_id:
+ description: The ID of the container to retrieve.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: GetContainerRequest
+ type: object
+ DeleteContainerRequest:
+ properties:
+ container_id:
+ description: The ID of the container to delete.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: DeleteContainerRequest
+ type: object
+ ContainerDeleteResponse:
+ description: Response for ``DELETE /containers/{container_id}``.
+ properties:
+ id:
+ description: The container identifier that was deleted.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container'.
+ title: Object
+ type: string
+ enum:
+ - container
+ deleted:
+ description: Whether the container was successfully deleted.
+ title: Deleted
+ type: boolean
+ required:
+ - id
+ - deleted
+ title: ContainerDeleteResponse
+ type: object
+ ContainerFileSource:
+ description: Origin of a file inside a container.
+ enum:
+ - user
+ - assistant
+ title: ContainerFileSource
+ type: string
+ ContainerFile:
+ description: A file present inside a container's filesystem.
+ properties:
+ id:
+ description: Identifier of the container file.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container.file'.
+ title: Object
+ type: string
+ enum:
+ - container.file
+ container_id:
+ description: ID of the container holding the file.
+ title: Container Id
+ type: string
+ created_at:
+ description: Unix timestamp (in seconds) when the file was created.
+ title: Created At
type: integer
- ranking_options:
+ bytes:
+ description: Size of the file in bytes.
+ title: Bytes
+ type: integer
+ path:
+ description: Absolute path to the file inside the container.
+ title: Path
+ type: string
+ source:
+ $ref: '#/components/schemas/ContainerFileSource'
+ description: Whether the file was supplied by the user or written by the model.
+ required:
+ - id
+ - container_id
+ - created_at
+ - bytes
+ - path
+ - source
+ title: ContainerFile
+ type: object
+ UploadContainerFileRequest:
+ description: |-
+ Path parameters for ``POST /containers/{container_id}/files``.
+
+ The file content itself is supplied as a multipart upload and not part of
+ this Pydantic body; see ``fastapi_routes.py``.
+ properties:
+ container_id:
+ description: The ID of the container to upload into.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: UploadContainerFileRequest
+ type: object
+ ListContainerFilesRequest:
+ properties:
+ container_id:
+ description: The ID of the container whose files should be listed.
+ title: Container Id
+ type: string
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination.
+ nullable: true
+ limit:
+ anyOf:
+ - maximum: 100
+ minimum: 1
+ type: integer
+ - type: 'null'
+ default: 20
+ description: Maximum number of files to return (1-100).
+ order:
+ anyOf:
+ - $ref: '#/components/schemas/Order'
+ title: Order
+ - type: 'null'
+ default: desc
+ description: Sort order by created_at timestamp.
+ title: Order
+ required:
+ - container_id
+ title: ListContainerFilesRequest
+ type: object
+ ListContainerFilesResponse:
+ properties:
+ object:
+ description: The object type, which is always 'list'.
+ title: Object
+ type: string
+ enum:
+ - list
+ data:
+ description: The list of files in the container.
+ items:
+ $ref: '#/components/schemas/ContainerFile'
+ title: Data
+ type: array
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first file in the page.
+ nullable: true
+ last_id:
anyOf:
- - additionalProperties: true
- type: object
+ - type: string
- type: 'null'
+ description: ID of the last file in the page.
nullable: true
- rewrite_query:
- default: false
- title: Rewrite Query
+ has_more:
+ description: Whether more files exist beyond this page.
+ title: Has More
type: boolean
required:
- - query
- title: VectorStoreSearchRequest
+ - data
+ - has_more
+ title: ListContainerFilesResponse
type: object
- ChunkForDeletion:
- description: Information needed to delete a chunk from a vector store.
+ GetContainerFileRequest:
properties:
- chunk_id:
- title: Chunk Id
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
type: string
- document_id:
- title: Document Id
+ file_id:
+ description: The ID of the container file to retrieve.
+ title: File Id
type: string
required:
- - chunk_id
- - document_id
- title: ChunkForDeletion
+ - container_id
+ - file_id
+ title: GetContainerFileRequest
type: object
- DeleteChunksRequest:
- description: Request body for deleting chunks from a vector store.
+ GetContainerFileContentRequest:
properties:
- vector_store_id:
- description: The ID of the vector store to delete chunks from.
- title: Vector Store Id
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to download.
+ title: File Id
type: string
- chunks:
- description: The list of chunks to delete.
- items:
- $ref: '#/components/schemas/ChunkForDeletion'
- title: Chunks
- type: array
required:
- - vector_store_id
- - chunks
- title: DeleteChunksRequest
+ - container_id
+ - file_id
+ title: GetContainerFileContentRequest
type: object
- ListBatchesRequest:
- description: Request model for listing batches.
+ DeleteContainerFileRequest:
properties:
- after:
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to delete.
+ title: File Id
+ type: string
+ required:
+ - container_id
+ - file_id
+ title: DeleteContainerFileRequest
+ type: object
+ ContainerFileDeleteResponse:
+ properties:
+ id:
+ description: The container file identifier that was deleted.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container.file'.
+ title: Object
+ type: string
+ enum:
+ - container.file
+ deleted:
+ description: Whether the file was successfully deleted.
+ title: Deleted
+ type: boolean
+ required:
+ - id
+ - deleted
+ title: ContainerFileDeleteResponse
+ type: object
+ ShellEnvironmentContainerAuto:
+ description: |-
+ Provider-managed container environment.
+
+ The provider lazily creates and reuses a container for the calling
+ response chain. Useful when the caller does not need to persist or
+ reference the container across responses.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - container_auto
+ image:
anyOf:
- type: string
- type: 'null'
- description: Optional cursor for pagination. Returns batches after this ID.
+ description: Optional preferred container image.
nullable: true
- limit:
- default: 20
- description: Maximum number of batches to return. Defaults to 20.
- title: Limit
- type: integer
- title: ListBatchesRequest
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration for the auto-created container.
+ nullable: true
+ title: ContainerExpiresAfter
+ title: ShellEnvironmentContainerAuto
type: object
- RetrieveBatchRequest:
- description: Request model for retrieving a batch.
+ ShellEnvironmentContainerReference:
+ description: Reference an existing container by ID.
properties:
- batch_id:
- description: The ID of the batch to retrieve.
- title: Batch Id
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - container_reference
+ container_id:
+ description: The ID of an existing container to execute inside.
+ title: Container Id
type: string
required:
- - batch_id
- title: RetrieveBatchRequest
+ - container_id
+ title: ShellEnvironmentContainerReference
type: object
- CancelBatchRequest:
- description: Request model for canceling a batch.
+ ShellEnvironmentLocal:
+ description: |-
+ Local (non-container) execution mode.
+
+ Only available when the operator has explicitly enabled local mode in
+ the ContainerRuntime provider configuration.
properties:
- batch_id:
- description: The ID of the batch to cancel.
- title: Batch Id
+ type:
+ description: Discriminator.
+ title: Type
type: string
- required:
- - batch_id
- title: CancelBatchRequest
+ enum:
+ - local
+ working_directory:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional working directory for local execution.
+ nullable: true
+ title: ShellEnvironmentLocal
type: object
- JobStatus:
- description: Status of a job execution.
- enum:
- - completed
- - in_progress
- - failed
- - scheduled
- - cancelled
- title: JobStatus
- type: string
- Job:
- description: A job execution instance with status tracking.
+ ShellOutcomeSuccess:
+ description: Process exited cleanly with status 0.
properties:
- job_id:
- title: Job Id
+ type:
+ description: Discriminator.
+ title: Type
type: string
- status:
- $ref: '#/components/schemas/JobStatus'
+ enum:
+ - success
+ exit_code:
+ description: Process exit code (always 0 for success).
+ title: Exit Code
+ type: integer
+ enum:
+ - 0
+ title: ShellOutcomeSuccess
+ type: object
+ ShellOutcomeFailure:
+ description: Process exited with a non-zero status.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - failure
+ exit_code:
+ description: Process exit code.
+ title: Exit Code
+ type: integer
+ reason:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Human-readable failure reason, if known.
+ nullable: true
required:
- - job_id
- - status
- title: Job
+ - exit_code
+ title: ShellOutcomeFailure
type: object
- DialogType:
- description: Parameter type for dialog data with semantic output labels.
+ ShellOutcomeTimeout:
+ description: Process was terminated for exceeding its time budget.
properties:
type:
+ description: Discriminator.
title: Type
type: string
enum:
- - dialog
- title: DialogType
+ - timeout
+ elapsed_seconds:
+ description: Wall-clock seconds elapsed before termination.
+ title: Elapsed Seconds
+ type: number
+ required:
+ - elapsed_seconds
+ title: ShellOutcomeTimeout
+ type: object
+ ShellCallOutput:
+ description: |-
+ Captured output of a single shell execution.
+
+ Consumed by the Responses provider to construct ``ShellCallOutputItem``
+ entries on the output stream.
+ properties:
+ stdout:
+ description: UTF-8 decoded standard output (truncated by the runtime if oversized).
+ title: Stdout
+ type: string
+ stderr:
+ description: UTF-8 decoded standard error (truncated by the runtime if oversized).
+ title: Stderr
+ type: string
+ outcome:
+ description: How the shell process terminated.
+ discriminator:
+ mapping:
+ failure: '#/components/schemas/ShellOutcomeFailure'
+ success: '#/components/schemas/ShellOutcomeSuccess'
+ timeout: '#/components/schemas/ShellOutcomeTimeout'
+ propertyName: type
+ oneOf:
+ - $ref: '#/components/schemas/ShellOutcomeSuccess'
+ title: ShellOutcomeSuccess
+ - $ref: '#/components/schemas/ShellOutcomeFailure'
+ title: ShellOutcomeFailure
+ - $ref: '#/components/schemas/ShellOutcomeTimeout'
+ title: ShellOutcomeTimeout
+ title: ShellOutcomeSuccess | ShellOutcomeFailure | ShellOutcomeTimeout
+ duration_ms:
+ description: Wall-clock duration of the shell call in milliseconds.
+ minimum: 0
+ title: Duration Ms
+ type: integer
+ container_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the container the call executed in, when applicable. Null for local mode.
+ nullable: true
+ required:
+ - stdout
+ - stderr
+ - outcome
+ - duration_ms
+ title: ShellCallOutput
type: object
ConversationMessage:
description: OpenAI-compatible message item for conversations.
@@ -16030,6 +17495,68 @@ components:
- prompt_id
title: DeletePromptRequest
type: object
+ SkillVersionCreateRequest:
+ description: Request to create a new skill version. Matches OpenAI VersionCreateParams.
+ properties:
+ default:
+ type: boolean
+ default: false
+ description: Whether to set this version as the default
+ title: Default
+ title: SkillVersionCreateRequest
+ type: object
+ ListSkillsRequest:
+ description: Request parameters for listing skills.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of results
+ maximum: 100
+ minimum: 1
+ title: Limit
+ type: integer
+ order:
+ default: desc
+ description: Sort order by created_at
+ enum:
+ - asc
+ - desc
+ title: Order
+ type: string
+ title: ListSkillsRequest
+ type: object
+ ListSkillVersionsRequest:
+ description: Request parameters for listing skill versions.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of results
+ maximum: 100
+ minimum: 1
+ title: Limit
+ type: integer
+ order:
+ default: desc
+ description: Sort order by version
+ enum:
+ - asc
+ - desc
+ title: Order
+ type: string
+ title: ListSkillVersionsRequest
+ type: object
OpenAIResponseMessageOutputUnion:
anyOf:
- oneOf:
@@ -16163,6 +17690,46 @@ components:
- type
- custom
description: A call to a custom tool created by the model.
+ ChoiceDeltaToolCall:
+ properties:
+ id:
+ anyOf:
+ - type: string
+ description: Unique identifier for the tool call.
+ - type: 'null'
+ description: Unique identifier for the tool call.
+ type:
+ anyOf:
+ - type: string
+ description: Must be 'function' to identify this as a function call.
+ enum:
+ - function
+ - type: 'null'
+ description: Must be 'function' to identify this as a function call.
+ function:
+ anyOf:
+ - properties:
+ name:
+ type: string
+ title: Name
+ description: Name of the function to call.
+ arguments:
+ type: string
+ title: Arguments
+ description: Arguments to pass to the function as a JSON string.
+ type: object
+ - type: 'null'
+ description: Function call details.
+ index:
+ type: integer
+ description: The index of the tool call being streamed.
+ type: object
+ description: A tool call delta in a streaming chat completion chunk.
+ required:
+ - index
+ ModelIdsResponses:
+ type: string
+ description: Model identifier.
responses:
BadRequest400:
description: The request was invalid or malformed
@@ -16261,6 +17828,8 @@ tags:
- description: Tool listing and management.
name: Tools
x-displayName: Tools
+- description: OpenAI-compatible vector store management and search.
+ name: Vector Stores
- description: ''
name: VectorIO
- description: OpenAI Responses API for agent orchestration with tool use, multi-turn conversations, and background processing.
@@ -16287,6 +17856,7 @@ x-tagGroups:
- ToolGroups
- ToolRuntime
- Tools
+ - Vector Stores
- VectorIO
security:
- Default: []
diff --git a/containers/Containerfile b/containers/Containerfile
index 22dd485bb6c..41a3a5c0faa 100644
--- a/containers/Containerfile
+++ b/containers/Containerfile
@@ -27,6 +27,14 @@ ARG PYPI_VERSION=""
ARG TEST_PYPI_VERSION=""
ARG KEEP_WORKSPACE=""
ARG DISTRO_NAME="starter"
+# PyPI package to install (e.g. "ogx", or "llama-stack" for pre-rename releases).
+ARG PACKAGE_NAME="ogx"
+# CLI binary the package provides (e.g. "ogx", or "llama" for llama-stack).
+ARG CLI_NAME="ogx"
+# Tolerate failures of the OpenTelemetry per-library bootstrap. Used when
+# backfilling older releases whose pinned deps conflict with the latest
+# auto-instrumentation packages. The default ("") keeps the bootstrap strict.
+ARG OTEL_BEST_EFFORT=""
ARG RUN_CONFIG_PATH=""
ARG UV_HTTP_TIMEOUT=500
ARG UV_EXTRA_INDEX_URL=""
@@ -68,6 +76,8 @@ ENV PYPI_VERSION=${PYPI_VERSION}
ENV TEST_PYPI_VERSION=${TEST_PYPI_VERSION}
ENV KEEP_WORKSPACE=${KEEP_WORKSPACE}
ENV DISTRO_NAME=${DISTRO_NAME}
+ENV PACKAGE_NAME=${PACKAGE_NAME}
+ENV CLI_NAME=${CLI_NAME}
ENV RUN_CONFIG_PATH=${RUN_CONFIG_PATH}
# Copy the repository so editable installs and run configurations are available.
@@ -88,6 +98,13 @@ RUN set -eux; \
# Install ogx
# Use UV_EXTRA_INDEX_URL inline only for editable install with RC dependencies
+# When a version is pinned, also pin the matching API package. The meta package
+# depends on "-api" without a version constraint, so an unpinned install
+# would resolve to the latest API package, which is incompatible with older
+# meta-package releases (e.g. llama-stack 0.5.2 + llama-stack-api 0.7.x).
+# The API package is installed first and best-effort: very old releases
+# (e.g. llama-stack < 0.4.0) bundled the API in the meta package and have no
+# separate "-api" distribution, so a missing pin is not an error.
RUN set -eux; \
SAVED_UV_EXTRA_INDEX_URL="${UV_EXTRA_INDEX_URL:-}"; \
SAVED_UV_INDEX_STRATEGY="${UV_INDEX_STRATEGY:-}"; \
@@ -106,15 +123,21 @@ RUN set -eux; \
elif [ "$INSTALL_MODE" = "test-pypi" ]; then \
uv pip install --no-cache fastapi libcst; \
if [ -n "$TEST_PYPI_VERSION" ]; then \
- uv pip install --no-cache --extra-index-url https://test.pypi.org/simple/ --index-strategy unsafe-best-match "ogx==$TEST_PYPI_VERSION"; \
+ if ! uv pip install --no-cache --extra-index-url https://test.pypi.org/simple/ --index-strategy unsafe-best-match "${PACKAGE_NAME}-api==$TEST_PYPI_VERSION"; then \
+ echo "No ${PACKAGE_NAME}-api==$TEST_PYPI_VERSION found; assuming the API is bundled in ${PACKAGE_NAME}"; \
+ fi; \
+ uv pip install --no-cache --extra-index-url https://test.pypi.org/simple/ --index-strategy unsafe-best-match "${PACKAGE_NAME}==$TEST_PYPI_VERSION"; \
else \
- uv pip install --no-cache --extra-index-url https://test.pypi.org/simple/ --index-strategy unsafe-best-match ogx; \
+ uv pip install --no-cache --extra-index-url https://test.pypi.org/simple/ --index-strategy unsafe-best-match "$PACKAGE_NAME"; \
fi; \
else \
if [ -n "$PYPI_VERSION" ]; then \
- uv pip install --no-cache "ogx==$PYPI_VERSION"; \
+ if ! uv pip install --no-cache "${PACKAGE_NAME}-api==$PYPI_VERSION"; then \
+ echo "No ${PACKAGE_NAME}-api==$PYPI_VERSION found; assuming the API is bundled in ${PACKAGE_NAME}"; \
+ fi; \
+ uv pip install --no-cache "${PACKAGE_NAME}==$PYPI_VERSION"; \
else \
- uv pip install --no-cache ogx; \
+ uv pip install --no-cache "$PACKAGE_NAME"; \
fi; \
fi;
@@ -129,15 +152,27 @@ RUN set -eux; \
echo "DISTRO_NAME must be provided" >&2; \
exit 1; \
fi; \
- deps="$(ogx stack list-deps "$DISTRO_NAME")"; \
+ deps="$("$CLI_NAME" stack list-deps "$DISTRO_NAME")"; \
if [ -n "$deps" ]; then \
printf '%s\n' "$deps" | xargs -L1 uv pip install --no-cache; \
fi
-# Install OpenTelemetry auto-instrumentation support
+# Install OpenTelemetry auto-instrumentation support.
+# The base distro/exporter install is required. The per-library bootstrap
+# (opentelemetry-bootstrap -a install) selects the latest instrumentation
+# packages, which can conflict with the pinned dependencies of older releases
+# being backfilled. With OTEL_BEST_EFFORT=1 a bootstrap failure is logged and
+# tolerated instead of failing the build.
RUN set -eux; \
pip install --no-cache opentelemetry-distro opentelemetry-exporter-otlp; \
- opentelemetry-bootstrap -a install
+ if ! opentelemetry-bootstrap -a install; then \
+ if [ "$OTEL_BEST_EFFORT" = "1" ]; then \
+ echo "opentelemetry-bootstrap failed; continuing without full auto-instrumentation (OTEL_BEST_EFFORT=1)" >&2; \
+ else \
+ echo "opentelemetry-bootstrap failed" >&2; \
+ exit 1; \
+ fi; \
+ fi
# Pre-cache tiktoken cl100k_base encoding at build time so the server never
# attempts a runtime download to openaipublic.blob.core.windows.net.
@@ -171,18 +206,20 @@ if env | grep -q '^OTEL_'; then
export OTEL_PYTHON_DISABLED_INSTRUMENTATIONS="${OTEL_PYTHON_DISABLED_INSTRUMENTATIONS:+$OTEL_PYTHON_DISABLED_INSTRUMENTATIONS,}asyncpg,sqlite3"
fi
+CLI_NAME="${CLI_NAME:-ogx}"
+
if [ -n "$RUN_CONFIG_PATH" ] && [ -f "$RUN_CONFIG_PATH" ]; then
- exec $CMD_PREFIX ogx stack run "$RUN_CONFIG_PATH" "$@"
+ exec $CMD_PREFIX "$CLI_NAME" stack run "$RUN_CONFIG_PATH" "$@"
fi
if [ -n "$DISTRO_NAME" ]; then
- exec $CMD_PREFIX ogx stack run "$DISTRO_NAME" "$@"
+ exec $CMD_PREFIX "$CLI_NAME" stack run "$DISTRO_NAME" "$@"
fi
-exec $CMD_PREFIX ogx stack run "$@"
+exec $CMD_PREFIX "$CLI_NAME" stack run "$@"
EOF
RUN chmod +x /usr/local/bin/ogx-entrypoint.sh
-RUN mkdir -p /.ogx /.cache && chmod -R g+rw /app /.ogx /.cache
+RUN mkdir -p "/.${CLI_NAME}" /.cache && chmod -R g+rw /app "/.${CLI_NAME}" /.cache
ENTRYPOINT ["/usr/local/bin/ogx-entrypoint.sh"]
diff --git a/docs/blog/2026-01-13-introducing-llama-stack.md b/docs/blog/2026-01-13-introducing-llama-stack.md
index 98f6cc4add2..a3e173d9e1a 100644
--- a/docs/blog/2026-01-13-introducing-llama-stack.md
+++ b/docs/blog/2026-01-13-introducing-llama-stack.md
@@ -103,7 +103,7 @@ See the [OGX Office Hours Content Calendar](https://docs.google.com/document/d/1
We'd love to have you join our growing community:
- [Star us on GitHub](https://github.com/ogx-ai/ogx)
-- [Join our Discord](https://discord.gg/ZAFjsrcw)
+- [Join our Discord](https://discord.gg/bUYRqEvK6)
- [Read the Documentation](/docs)
- [Report Issues](https://github.com/ogx-ai/ogx/issues)
diff --git a/docs/blog/2026-03-01-building-agentic-flows.md b/docs/blog/2026-03-01-building-agentic-flows.md
index 6d4105da932..4410d15352e 100644
--- a/docs/blog/2026-03-01-building-agentic-flows.md
+++ b/docs/blog/2026-03-01-building-agentic-flows.md
@@ -332,4 +332,4 @@ To learn more:
- [Conversations API documentation](/docs/api-openai/conformance#conversations)
- [OpenAI API compatibility](/docs/api-openai)
- [Vector Stores documentation](/docs/building_applications/rag)
-- [Join our Discord](https://discord.gg/ZAFjsrcw)
+- [Join our Discord](https://discord.gg/bUYRqEvK6)
diff --git a/docs/blog/2026-04-28-from-llama-stack-to-ogx.md b/docs/blog/2026-04-28-from-llama-stack-to-ogx.md
index d0e85af3059..30f4ae4590c 100644
--- a/docs/blog/2026-04-28-from-llama-stack-to-ogx.md
+++ b/docs/blog/2026-04-28-from-llama-stack-to-ogx.md
@@ -138,6 +138,6 @@ The rename clears the way for the project to grow in the direction it's already
The name is new. The mission is sharper. The server is the same one you've been using — just with a name that finally matches what it does.
-Get started at [ogx-ai.github.io/docs](https://ogx-ai.github.io/docs), or join the conversation on [Discord](https://discord.gg/ZAFjsrcw).
+Get started at [ogx-ai.github.io/docs](https://ogx-ai.github.io/docs), or join the conversation on [Discord](https://discord.gg/bUYRqEvK6).
— Charlie, Francisco, Matt, Raghu, Seb
diff --git a/docs/blog/2026-05-05-opencode-blog.md b/docs/blog/2026-05-05-opencode-blog.md
index bd5bd8ea5df..e855e314f79 100644
--- a/docs/blog/2026-05-05-opencode-blog.md
+++ b/docs/blog/2026-05-05-opencode-blog.md
@@ -1,6 +1,6 @@
---
slug: opencode-blog
-title: "OpenCode ❤️ OGX"
+title: "OGX ❤️ OpenCode"
authors: [nathan-weinberg]
tags: []
date: 2026-05-05
diff --git a/docs/blog/2026-05-11-consistent-agentic-api-layer.md b/docs/blog/2026-05-11-consistent-agentic-api-layer.md
index df5eeb6e68d..4e00aa6ac59 100644
--- a/docs/blog/2026-05-11-consistent-agentic-api-layer.md
+++ b/docs/blog/2026-05-11-consistent-agentic-api-layer.md
@@ -125,4 +125,4 @@ OGX already supports the core API surfaces. The work ahead is deepening that sup
The goal is straightforward: any agent, any framework, any model, any infrastructure. One server.
-If your team is building agents and doesn't want to bet on a single vendor's API contract, [get started with OGX](https://ogx-ai.github.io/docs) or join the conversation on [Discord](https://discord.gg/ZAFjsrcw).
+If your team is building agents and doesn't want to bet on a single vendor's API contract, [get started with OGX](https://ogx-ai.github.io/docs) or join the conversation on [Discord](https://discord.gg/bUYRqEvK6).
diff --git a/docs/blog/2026-05-12-ogx-v1.md b/docs/blog/2026-05-12-ogx-v1.md
index 15b67c9957c..f4d2f8c8332 100644
--- a/docs/blog/2026-05-12-ogx-v1.md
+++ b/docs/blog/2026-05-12-ogx-v1.md
@@ -182,6 +182,6 @@ v1 means we're confident enough to put a number on it. The APIs are stable. The
If you've been waiting for the right time to try OGX, this is it.
-[Get started](https://ogx-ai.github.io/docs/getting_started/quickstart) | [Documentation](https://ogx-ai.github.io/docs) | [GitHub](https://github.com/ogx-ai/ogx) | [Discord](https://discord.gg/ZAFjsrcw)
+[Get started](https://ogx-ai.github.io/docs/getting_started/quickstart) | [Documentation](https://ogx-ai.github.io/docs) | [GitHub](https://github.com/ogx-ai/ogx) | [Discord](https://discord.gg/bUYRqEvK6)
--- The OGX Team
diff --git a/docs/blog/2026-06-09-claude-code-integration.md b/docs/blog/2026-06-09-claude-code-integration.md
new file mode 100644
index 00000000000..8e8d0b02952
--- /dev/null
+++ b/docs/blog/2026-06-09-claude-code-integration.md
@@ -0,0 +1,265 @@
+---
+slug: claude-code-integration
+title: "Using Claude Code with Any Model via OGX"
+authors: [leseb, cdoern]
+tags: [claude-code, anthropic, integration, tutorial, vllm, ollama, openai]
+date: 2026-06-09
+---
+
+Claude Code is one of the best coding assistants available. But what if you want to use it with GPT-4o, Qwen, Llama, or a model running on your own hardware? OGX makes that possible. A single command connects Claude Code to your OGX server, auto-discovers your models, and maps them to Claude's haiku/sonnet/opus tiers.
+
+This post walks through the setup, explains how the translation works under the hood, and shows how to configure multi-provider routing so different Claude Code model tiers hit different backends.
+
+
+
+## The idea
+
+Claude Code talks to the Anthropic Messages API (`/v1/messages`). OGX implements that API. When Claude Code sends a request, OGX receives it, translates the format if needed, and forwards it to whatever inference provider you've configured — OpenAI, vLLM, Ollama, Fireworks, Groq, Bedrock, or any of the other [supported providers](https://ogx-ai.github.io/docs/providers).
+
+
+
+The translation layer handles message format conversion, tool call transformations, streaming event reformatting, and extended thinking (including signature deltas and redacted thinking blocks). For providers that already support the Messages API natively (Ollama and vLLM with compatible models), OGX passes requests through directly — no translation overhead.
+
+## Quick start
+
+Two commands. Two minutes.
+
+### 1. Start OGX
+
+Pick your provider and start the server:
+
+```bash
+# With OpenAI
+export OPENAI_API_KEY="your-key-here"
+ogx run starter
+
+# With vLLM
+export VLLM_URL="http://localhost:8000/v1"
+ogx run starter
+
+# With Ollama
+export OLLAMA_URL="http://localhost:11434/v1"
+ogx run starter
+```
+
+### 2. Connect Claude Code
+
+```bash
+ogx connect claude
+```
+
+That's it. The command queries your OGX server for available models, maps them to Claude's haiku/sonnet/opus tiers, sets the right environment variables (including unsetting any Vertex/Bedrock variables that would bypass OGX), and launches Claude Code.
+
+### What `ogx connect claude` does
+
+```text
+ogx connect claude
+ |
+ v
+ GET /v1/models (discover available models)
+ |
+ v
+ Map models to Claude tiers (haiku/sonnet/opus)
+ |
+ v
+ Launch claude with ANTHROPIC_BASE_URL + tier env vars
+```
+
+No manual environment variable setup. No remembering which model names map to which tiers. No Vertex/Bedrock conflicts.
+
+## Model configuration
+
+### Default behavior
+
+With no flags, `ogx connect claude` maps all three Claude tiers to the first available LLM model on your OGX server.
+
+### One model for all tiers
+
+```bash
+ogx connect claude --model openai/gpt-4o
+```
+
+### Different models per tier
+
+This is the real power — route fast tasks to cheap local models and complex reasoning to cloud APIs:
+
+```bash
+ogx connect claude \
+ --haiku-model openai/gpt-4o-mini \
+ --sonnet-model openai/gpt-4o \
+ --opus-model openai/o1
+```
+
+### Shell integration with `--print-env`
+
+Instead of launching Claude Code, print the environment variables for manual use:
+
+```bash
+eval "$(ogx connect claude --print-env --model openai/gpt-4o)"
+claude "Hello world"
+```
+
+### Forwarding arguments to Claude Code
+
+Anything after `--` is passed through to `claude`:
+
+```bash
+ogx connect claude -- -p "Write a hello world function"
+```
+
+## Provider setup examples
+
+### OpenAI
+
+```bash
+# Terminal 1
+export OPENAI_API_KEY="sk-..."
+ogx run starter
+
+# Terminal 2
+ogx connect claude --model openai/gpt-4o
+```
+
+### vLLM with Qwen
+
+```bash
+# Start vLLM
+vllm serve Qwen/Qwen3-8B --api-key fake
+
+# Terminal 1
+export VLLM_URL="http://localhost:8000/v1"
+ogx run starter
+
+# Terminal 2
+ogx connect claude --model vllm/Qwen/Qwen3-8B
+```
+
+### Ollama with Llama
+
+```bash
+ollama serve
+ollama pull llama3.3:70b
+
+# Terminal 1
+export OLLAMA_URL="http://localhost:11434/v1"
+ogx run starter
+
+# Terminal 2
+ogx connect claude --model ollama/llama3.3:70b
+```
+
+### Multiple providers with per-tier routing
+
+```bash
+# Terminal 1
+export VLLM_URL="http://localhost:8000/v1"
+export OPENAI_API_KEY="sk-..."
+ogx run starter
+
+# Terminal 2
+ogx connect claude \
+ --haiku-model vllm/Qwen/Qwen3-8B \
+ --sonnet-model openai/gpt-4o \
+ --opus-model openai/o1
+```
+
+## What's supported
+
+All core Claude Code features work through OGX:
+
+- **Multi-turn conversations** with system messages and streaming
+- **Tool use** — file operations, shell commands, code execution (these run in Claude Code's runtime, not OGX)
+- **Extended thinking** — full support including signature deltas and redacted thinking blocks in passthrough mode; clear error when attempting thinking in translation mode
+- **Token counting** via `/v1/messages/count_tokens`
+- **Prompt caching** — `cache_control` breakpoints from the Anthropic SDK are forwarded correctly in passthrough mode
+- **Any inference provider** — OpenAI, vLLM, Ollama, Fireworks, Together, Groq, Bedrock, etc.
+
+Provider capabilities differ:
+
+| Provider | Native Messages API | Thinking Support | Prompt Caching |
+|----------|-------------------|------------------|----------------|
+| OpenAI | ❌ (translated) | ⚠️ (via reasoning) | ❌ |
+| vLLM | ✅ | ❌ | ❌ |
+| Ollama | ✅ | ❌ | ❌ |
+| Bedrock, Fireworks, Groq, Together | ❌ (translated) | ❌ | ❌ |
+
+## Advanced: custom model mappings
+
+For more control over how Claude model names map to providers, register models explicitly via the API:
+
+```bash
+curl http://localhost:8321/v1/models \
+ -H "Content-Type: application/json" \
+ -d '{
+ "model_id": "claude-haiku-4-5-20251001",
+ "provider_id": "vllm",
+ "provider_model_id": "Qwen/Qwen3-8B",
+ "model_type": "llm"
+ }'
+```
+
+Or declaratively in `config.yaml`:
+
+```yaml
+registered_resources:
+ models:
+ - model_id: claude-haiku-4-5-20251001
+ provider_id: vllm
+ provider_model_id: Qwen/Qwen3-8B
+ model_type: llm
+```
+
+## Claude Agent SDK
+
+If you're building custom agents with the Claude Agent SDK, OGX works as a drop-in backend:
+
+```python
+from claude_agent_sdk import Agent
+
+agent = Agent(
+ base_url="http://localhost:8321",
+ api_key="fake",
+ model="vllm/Qwen/Qwen3-8B",
+)
+
+response = agent.send("Write a function to parse CSV files")
+```
+
+## Manual setup (without `ogx connect claude`)
+
+If you prefer to configure environment variables yourself:
+
+```bash
+export ANTHROPIC_BASE_URL="http://localhost:8321"
+export ANTHROPIC_AUTH_TOKEN="ogx"
+
+# Map Claude model tiers to your backend models
+export ANTHROPIC_DEFAULT_HAIKU_MODEL="openai/gpt-4o-mini"
+export ANTHROPIC_DEFAULT_SONNET_MODEL="openai/gpt-4o"
+export ANTHROPIC_DEFAULT_OPUS_MODEL="openai/o1"
+
+# Unset any Vertex/Bedrock variables
+unset CLAUDE_CODE_USE_VERTEX
+unset ANTHROPIC_VERTEX_PROJECT_ID
+unset CLAUDE_CODE_USE_BEDROCK
+
+claude "Write a hello world function in Python"
+```
+
+## Troubleshooting
+
+**`max_tokens` errors with OpenAI models** — Claude Code requests token limits based on Claude model specs, which may exceed what the backend model supports. Use a model with higher token limits, or use per-tier flags to route different workloads appropriately.
+
+**"Failed to connect to OGX server"** — The OGX server isn't running or isn't reachable. Start it with `ogx run starter`.
+
+**"Failed to find any LLM models"** — The server is running but has no LLM models registered. Check your distribution config and ensure at least one inference provider is configured.
+
+**Claude Code ignores `ANTHROPIC_BASE_URL` (manual setup only)** — If `CLAUDE_CODE_USE_VERTEX=1` or similar is set, Claude Code bypasses `ANTHROPIC_BASE_URL`. The `ogx connect claude` command handles this automatically. For manual setup, unset those variables first.
+
+**Slow cloud provider responses** — Expected. Claude Code → OGX → provider adds a network hop. Use local providers (vLLM, Ollama) for lower latency. The format translation itself adds only ~5-20ms.
+
+**Tool use not working** — Tool execution happens in Claude Code's runtime, not OGX. Make sure Claude Code has the right permissions and your model supports tool use.
+
+## What's next
+
+The [full documentation](https://ogx-ai.github.io/docs/building_applications/claude_code_integration) covers the complete CLI reference, performance tuning, and provider-specific configuration. If you run into issues or want to improve the integration, [open an issue](https://github.com/ogx-ai/ogx/issues) or join us on [Discord](https://discord.gg/ZAFjsrcw).
diff --git a/docs/blog/2026-06-16-claude-code-blog.md b/docs/blog/2026-06-16-claude-code-blog.md
new file mode 100644
index 00000000000..e356f3b4b5b
--- /dev/null
+++ b/docs/blog/2026-06-16-claude-code-blog.md
@@ -0,0 +1,58 @@
+---
+slug: claude-code-blog
+title: "OGX ❤️ Claude Code"
+authors: [nathan-weinberg]
+tags: []
+date: 2026-06-16
+---
+
+[Claude Code](https://claude.com/product/claude-code) is an AI coding tool developed and maintained by Anthropic. It has become an industry leader for AI coding assistance and allows users to create plans, manage agents, develop their own custom skills, and more.
+
+Today we are happy to announce `ogx connect` support for Claude Code, allowing OGX users to launch Claude Code directly and access models on their OGX server. Our configuration allows the use of a single model for all tasks as well as custom mappings of up to three models for differing tasks.
+
+Using OGX as your backend for Claude Code can provide some strong advantages over different backend options:
+
+- Control your budget by offering a mixture of different models from different sources, rather than relying on a single backend provider
+- Take advantage of Claude Code's mapping of models to seemlessly switch between self-hosted and SaaS options with no server interactions required
+- Ensure redundancy by never being reliant on one SaaS backend, always keeping Claude Code running for users of your OGX server
+
+In this blog I am going to share how to start running Claude Code using models on an OGX server, using a remote server that has both self-hosted and SaaS models enabled.
+
+The blog assumes you already have the OGX server up and running on a remote host - see our [Getting Started guide](https://ogx-ai.github.io/docs/getting_started/quickstart) to learn more.
+
+## Download Claude Code
+
+Our first step here is to actually download and install Claude Code. You can see all the downloading options from [the Claude Code website](https://claude.com/product/claude-code) but generally the below `curl` command is suifficient in most cases.
+
+```bash
+curl -fsSL https://claude.ai/install.sh | bash
+```
+
+## Use Claude Code with OGX
+
+As mentioned before, this blog assumes an OGX server is already running at `myremoteserver.com:8321` - in this case, we are also making the following assumptions:
+
+- The `remote::vllm` provider is enabled, serving the `Qwen/Qwen3-8B` model
+- The `remote::gemini` provider is enabled, with the `gemini-2.5-pro` model available
+- The `remote::openai` provider is enabled, with the `gpt-4o` model available
+- No authentication has been added
+
+You can verify what models your OGX server has available with `curl http://myremoteserver.com:8321/v1/models`
+
+Now comes the easy part - run this simple command below to start up Claude Code with your specific models:
+
+```bash
+ogx connect claude \
+ --haiku-model vllm/Qwen/Qwen3-8B \
+ --sonnet-model gemini/models/gemini-2.5-pro \
+ --opus-model openai/gpt-4o \
+ --url http://myremoteserver.com:8321/v1
+```
+
+You should be greeted by a Claude Code TUI that looks something like this:
+
+
+
+Running `/model` should show the models you've selected as they were configured:
+
+
diff --git a/docs/blog/2026-06-23-guardrails-responses-api.md b/docs/blog/2026-06-23-guardrails-responses-api.md
new file mode 100644
index 00000000000..a4b1f2adfe8
--- /dev/null
+++ b/docs/blog/2026-06-23-guardrails-responses-api.md
@@ -0,0 +1,415 @@
+---
+slug: guardrails-responses-api
+title: "Under the Hood: How OGX Enforces Guardrails Inside the Agentic Loop"
+authors:
+ - leseb
+tags: [responses-api, guardrails, safety, streaming, agents]
+date: 2026-06-23
+---
+
+AI agents that call tools, search documents, and reason over multiple turns are powerful, but they also need boundaries. A model that can execute a web search or query your internal knowledge base should not be free to produce harmful content along the way.
+
+OGX implements guardrails as a first-class feature of the Responses API. Unlike bolt-on moderation that checks content after the fact, OGX validates content at two critical points inside the agentic loop: before inference starts and while user-visible text and reasoning output streams. This post explains exactly how that works, why the design choices matter, and how to use it in practice.
+
+
+
+## The problem with post-hoc moderation
+
+Most moderation systems work outside the generation pipeline. You send a prompt to the model, get a response, then send that response to a moderation endpoint. If the content is flagged, you discard it and show an error.
+
+This approach has two problems:
+
+1. **Wasted compute.** The model generates the full response before you discover it violates a policy. For long, multi-turn agentic responses with tool calls, this can mean minutes of wasted work.
+2. **Latency gap during streaming.** If you are streaming tokens to the user, you either block the entire stream until moderation completes (defeating the purpose of streaming) or you show tokens before they are validated (defeating the purpose of moderation).
+
+OGX solves both problems by embedding guardrail checks directly inside the response orchestration loop.
+
+## How to use guardrails
+
+From the client side, guardrails are a single boolean on the Responses API:
+
+```python
+from openai import OpenAI
+
+client = OpenAI(base_url="http://localhost:8321/v1", api_key="unused")
+
+response = client.responses.create(
+ model="openai/gpt-4o-mini",
+ input="Summarize this text.",
+ extra_body={"guardrails": True},
+)
+print(response.output_text)
+```
+
+Setting `guardrails` to `True` tells the server to run request input plus generated text and reasoning content through the configured moderation endpoint. If the content is flagged, or if moderation cannot be completed safely, the response is replaced with a refusal. No shield IDs, no model lists, no moderation credentials on the client side.
+
+The same parameter works with streaming, tool calls, MCP, and multi-turn conversations. No changes to your orchestration logic are needed.
+
+### Why a boolean?
+
+Earlier versions of OGX required clients to pass a list of shield identifiers (e.g., `"guardrails": ["llama-guard", "content-filter"]`), and the server would resolve each ID to a registered provider, manage routing tables, and coordinate multiple safety backends. This created real operational complexity: six safety providers with different auth, configuration, and edge cases, all for a feature that most deployments use as a simple yes/no gate.
+
+The new design replaces all of that with server-side moderation configuration and a boolean on the client. The platform administrator picks the moderation service once; application developers just flip the switch.
+
+## Server configuration
+
+Guardrails require a `moderation_endpoint` to be configured on the builtin responses provider. This is the URL of any OpenAI-compatible `/v1/moderations` endpoint. If the endpoint requires authentication, configure `moderation_headers` beside it.
+
+```yaml
+providers:
+ responses:
+ - provider_id: builtin
+ provider_type: inline::builtin
+ config:
+ moderation_endpoint: "https://api.openai.com/v1/moderations"
+ moderation_headers:
+ Authorization: "Bearer ${env.OPENAI_API_KEY}"
+```
+
+You can point this at OpenAI's moderation API, an OpenAI-compatible gateway in front of a hosted content safety service, a self-hosted moderation model, or any service that accepts `POST {"input": "text"}` and returns `{"results": [{"flagged": bool, "categories": {...}}]}`. The server makes a direct HTTP call — no proxy layer, no routing table, no provider abstraction in between.
+
+`moderation_headers` are server-side only. They are never exposed to clients, and they are treated as sensitive configuration when OGX redacts config output. This keeps moderation credentials on the platform side and out of application requests.
+
+If a client sends `guardrails: True` but no `moderation_endpoint` is configured, the server returns an error immediately rather than silently skipping validation:
+
+```python
+if enable_guardrails and not self.moderation_endpoint:
+ raise ServiceNotEnabledError(
+ "moderation_endpoint",
+ provider_specific_message=(
+ "Guardrails require a moderation endpoint to be configured "
+ "on the server. Contact your platform administrator to set "
+ "'moderation_endpoint' on the responses provider, or remove "
+ "the 'guardrails' parameter from your request."
+ ),
+ )
+```
+
+## The agentic loop
+
+To understand where guardrails fit, you need to understand how OGX orchestrates a Responses API call. The core of the implementation is the `StreamingResponseOrchestrator` class, which runs an iterative loop that interleaves inference, tool execution, and content validation.
+
+Here is the high-level flow:
+
+```text
+1. Client sends request with input, tools, and guardrails: True
+2. Server converts input to chat completion messages
+3. INPUT GUARDRAIL CHECK ← validates all user messages
+4. If violation → return refusal immediately
+5. Enter agentic loop:
+ a. Call inference (chat completion) with current messages
+ b. Buffer generated text/reasoning chunks
+ └── OUTPUT GUARDRAIL CHECK ← validates buffered content in batches
+ └── If violation → replace stream with refusal
+ c. Parse tool calls from model output
+ d. Execute server-side tools (web search, file search, MCP)
+ e. Append tool results to message history
+ f. If more tool calls needed → go to (a)
+ g. If only client-side function calls → return to client
+6. Emit final response (completed / incomplete / failed)
+```
+
+The loop continues until one of these conditions is met:
+
+- The model produces a final text response with no tool calls
+- The maximum iteration count is reached (default: 10)
+- Only client-side function calls remain (the client needs to execute them)
+- A guardrail violation is detected
+- The `max_output_tokens` budget is exhausted
+
+Each iteration through the loop is a full inference call. The model sees the accumulated conversation history including previous tool results, so it can reason about what it has learned and decide what to do next.
+
+## Checkpoint 1: input validation
+
+Before the agentic loop begins, OGX checks the user's input against the moderation endpoint:
+
+```python
+if self.enable_guardrails:
+ combined_text = interleaved_content_as_str(
+ [msg.content for msg in self.ctx.messages]
+ )
+ input_violation_message = await run_guardrails(
+ self.moderation_endpoint,
+ combined_text,
+ headers=self.moderation_headers,
+ )
+ if input_violation_message:
+ yield await self._create_refusal_response(input_violation_message)
+ return
+```
+
+This flattens all input messages into a single text string and sends it to the moderation endpoint. If the content is flagged, the entire response is short-circuited: no inference call happens, no tokens are generated, no tools are executed. The client receives a `response.completed` event containing a refusal content part instead of the model's output.
+
+This matters because it prevents the model from ever seeing harmful input. Without input validation, a jailbreak prompt could manipulate the model into producing harmful tool calls or responses that might pass output validation in isolation.
+
+## Checkpoint 2: batched streaming validation
+
+Output validation is more nuanced. During streaming, the model generates tokens one at a time. Calling the moderation endpoint for every token would be prohibitively slow. But waiting for the entire response would defeat the purpose of streaming.
+
+OGX takes a middle path: **batched chunk validation**. Here is how it works:
+
+```text
+For each streaming chunk from the inference provider:
+ 1. Accumulate text and reasoning content deltas
+ 2. Buffer the streaming event (don't emit to client yet)
+ 3. Track characters since last check
+
+ When characters >= 200:
+ a. Send accumulated text to moderation endpoint
+ b. If violation:
+ - Discard all buffered events
+ - Emit refusal response
+ - Stop processing the stream
+ c. If clean:
+ - Emit all buffered events to client
+ - Reset character counter
+
+ After stream ends:
+ Final guardrail check on any remaining buffered content
+```
+
+The 200-character batch size is a deliberate tradeoff. Smaller batches catch violations sooner but increase moderation API calls. Larger batches reduce overhead but delay detection. 200 characters is roughly a sentence, which gives the moderation model enough context to make accurate judgments while keeping latency acceptable.
+
+Here is the core of the batched validation logic:
+
+```python
+_GUARDRAIL_BATCH_CHARS = 200
+
+# Inside _process_streaming_chunks:
+# Reasoning characters count toward the batch threshold alongside text content.
+guardrail_check_due = chars_since_last_check >= _GUARDRAIL_BATCH_CHARS
+
+if self.enable_guardrails and guardrail_check_due:
+ accumulated_text = "".join(chat_response_content + reasoning_text_accumulated)
+ violation_message = await run_guardrails(
+ self.moderation_endpoint,
+ accumulated_text,
+ headers=self.moderation_headers,
+ )
+ if violation_message:
+ pending_guardrail_events.clear()
+ yield await self._create_refusal_response(violation_message)
+ self.violation_detected = True
+ return
+ for event in pending_guardrail_events:
+ yield event
+ pending_guardrail_events.clear()
+ chars_since_last_check = 0
+```
+
+A key detail: each validation call sends the **entire accumulated text so far** — including both text content and reasoning content — not just the new batch. This gives the moderation model full context for content whose risk depends on previous sentences.
+
+### What happens when reasoning is present
+
+Some models produce reasoning content (chain-of-thought) alongside their text output. Reasoning events are user-visible in the Responses stream, so they must pass through guardrail validation just like text content.
+
+When guardrails are enabled, reasoning events are buffered alongside text events and included in the accumulated text sent to the moderation endpoint. Reasoning characters count toward the 200-character batch threshold, so reasoning-only responses still trigger timely moderation checks. No reasoning content reaches the client until it has been validated.
+
+### The final flush
+
+After the inference stream ends, there may be buffered events that have not reached the 200-character threshold. OGX runs one final guardrail check on this remaining content before emitting it:
+
+```python
+if self.enable_guardrails and pending_guardrail_events:
+ accumulated_text = "".join(chat_response_content + reasoning_text_accumulated)
+ violation_message = await run_guardrails(
+ self.moderation_endpoint,
+ accumulated_text,
+ headers=self.moderation_headers,
+ )
+ if violation_message:
+ pending_guardrail_events.clear()
+ yield await self._create_refusal_response(violation_message)
+ self.violation_detected = True
+ return
+ for event in pending_guardrail_events:
+ yield event
+```
+
+This ensures the final buffered text and reasoning events are validated before they reach the client, regardless of how the stream ends.
+
+## The moderation call
+
+The `run_guardrails` function is intentionally simple. It makes a single HTTP POST to the configured endpoint using the OpenAI moderation format:
+
+```python
+async def run_guardrails(
+ moderation_endpoint: str | None,
+ messages: str,
+ headers: dict[str, str] | None = None,
+) -> str | None:
+ if not messages or not moderation_endpoint:
+ return None
+
+ async with httpx.AsyncClient(timeout=httpx.Timeout(30.0)) as client:
+ try:
+ resp = await client.post(
+ moderation_endpoint,
+ json={"input": messages},
+ headers=headers,
+ )
+ resp.raise_for_status()
+ except (httpx.HTTPError, httpx.InvalidURL):
+ logger.warning(
+ "Failed to call moderation endpoint", endpoint=moderation_endpoint
+ )
+ return "Failed to validate content: moderation service unavailable"
+
+ try:
+ data = resp.json()
+ except Exception:
+ logger.warning(
+ "Failed to parse moderation response as JSON", endpoint=moderation_endpoint
+ )
+ return (
+ "Failed to validate content: moderation service returned invalid response"
+ )
+
+ results = data.get("results") if isinstance(data, dict) else None
+ if not isinstance(results, list):
+ logger.warning(
+ "Moderation endpoint returned unexpected format",
+ endpoint=moderation_endpoint,
+ )
+ return "Failed to validate content: moderation response has unexpected format"
+ if not results:
+ logger.warning(
+ "Moderation endpoint returned no results", endpoint=moderation_endpoint
+ )
+ return "Failed to validate content: moderation response has unexpected format"
+
+ for result in results:
+ if not isinstance(result, dict):
+ logger.warning(
+ "Failed to parse moderation result entry", endpoint=moderation_endpoint
+ )
+ return (
+ "Failed to validate content: moderation response has unexpected format"
+ )
+ flagged = result.get("flagged")
+ if not isinstance(flagged, bool):
+ logger.warning(
+ "Failed to parse moderation result flagged field",
+ endpoint=moderation_endpoint,
+ )
+ return (
+ "Failed to validate content: moderation response has unexpected format"
+ )
+ categories = result.get("categories", {})
+ if not isinstance(categories, dict):
+ logger.warning(
+ "Failed to parse moderation result categories",
+ endpoint=moderation_endpoint,
+ )
+ return (
+ "Failed to validate content: moderation response has unexpected format"
+ )
+ if flagged:
+ flagged_cats = [c for c, f in categories.items() if f]
+ msg = "Content blocked by safety guardrails"
+ if flagged_cats:
+ msg += f" (flagged for: {', '.join(flagged_cats)})"
+ return msg
+
+ return None
+```
+
+A key detail: this function **fails closed**. If the moderation service is unreachable, returns an error, or returns a malformed response, the function returns a blocking message rather than `None`. Content is never allowed through when the moderation check cannot be performed. Only a clean, parseable response with `"flagged": false` returns `None`.
+
+No provider abstraction, no routing table, no shield resolution. One HTTP call, one JSON response. The moderation endpoint is expected to return the [OpenAI moderation response format](https://platform.openai.com/docs/api-reference/moderations/object): a `results` array where each element has `flagged` (boolean) and `categories` (dict of category names to booleans). The optional `headers` parameter lets the server pass authentication credentials configured via `moderation_headers` in the provider config.
+
+This simplicity is a feature. The previous implementation required registering safety providers, managing shield routing tables, resolving guardrail IDs to model IDs, and coordinating multiple backends through an internal Safety API. All of that infrastructure existed to support a `/v1/moderations` proxy endpoint that clients could call directly — but the only place where server-side moderation actually adds value is inside the agentic loop, where the orchestrator needs to check content mid-generation. That is exactly what `run_guardrails` does.
+
+## The refusal response
+
+When a guardrail violation is detected at either checkpoint, OGX constructs a complete `response.completed` event with a refusal content part:
+
+```python
+async def _create_refusal_response(self, violation_message: str):
+ refusal_content = OpenAIResponseContentPartRefusal(refusal=violation_message)
+ refusal_response = OpenAIResponseObject(
+ id=self.response_id,
+ status="completed",
+ output=[
+ OpenAIResponseMessage(
+ role="assistant",
+ content=[refusal_content],
+ )
+ ],
+ # ... other fields preserved
+ )
+ return OpenAIResponseObjectStreamResponseCompleted(response=refusal_response)
+```
+
+The refusal is a proper Responses API object. Clients that handle the `refusal` content type can display an appropriate message. The violation message includes which categories were flagged, so applications can take context-appropriate action.
+
+## Guardrails and the multi-turn tool loop
+
+Guardrails interact with the agentic loop in an important way: they check generated text and reasoning content, not raw tool results or tool-call arguments. Here is why.
+
+Server-side tools (web search, file search, MCP) are executed by the server in a controlled environment. Their results are structured data that gets injected into the conversation history for the next inference call. The model then reasons about those results and produces text output, which is where guardrails apply.
+
+This design means:
+
+- A web search result containing harmful content will not trigger a guardrail violation on its own
+- But if the model incorporates that harmful content into text or reasoning output, that output goes through moderation
+- Tool calls themselves are not blocked by guardrails; tool authorization remains a separate control from content moderation
+
+When a violation is detected mid-loop, the `violation_detected` flag stops all further processing:
+
+```python
+async for stream_event_or_result in self._process_streaming_chunks(
+ completion_result, output_messages
+):
+ if isinstance(stream_event_or_result, ChatCompletionResult):
+ completion_result_data = stream_event_or_result
+ else:
+ yield stream_event_or_result
+
+# If violation detected, skip the rest of processing
+if self.violation_detected:
+ return
+```
+
+No further inference iterations are made, no more tools are executed, and no more buffered text or reasoning events are emitted.
+
+## Design principles
+
+Several principles guided this implementation:
+
+**Fail closed, not open.** If guardrails are requested and no moderation endpoint is configured, the request fails rather than proceeding without validation.
+
+**No unvalidated buffered content.** Text and reasoning events are held until the current guardrail batch passes. When a violation is detected during streaming, the current buffer is discarded, a refusal is emitted, and generation stops.
+
+**Validation with context.** Each output guardrail check sends the full accumulated text, not just the latest batch. This helps catch content whose risk only becomes clear when multiple chunks are read together.
+
+**Minimal latency impact.** Input validation adds one moderation call before inference. Output validation adds roughly one call per 200 characters of text and reasoning output, plus a final check for any remaining buffered content.
+
+**Guardrails are opt-in.** When `guardrails` is not set, no moderation checks are performed, and streaming events flow directly to the client.
+
+**Configuration belongs on the server.** The choice of moderation service is an infrastructure decision, not an application decision. Platform administrators set `moderation_endpoint` once; application developers just pass `guardrails: True`.
+
+## What was removed and why
+
+The previous guardrails implementation was built on top of a full Safety API subsystem: protocol definitions, routing tables, a shield registry, seven safety providers (Llama Guard, Prompt Guard, Code Scanner, Bedrock, NVIDIA, SambaNova, Passthrough), and a standalone `/v1/moderations` proxy endpoint.
+
+All of that has been removed. The standalone `/v1/moderations` endpoint added a network hop for zero value — clients already know how to call moderation services directly. The provider abstraction existed to support that proxy, but the only server-side value is guardrails during generation, where the orchestrator needs to run moderation checks mid-stream. That is now a direct HTTP call from the responses provider.
+
+The result is less code, fewer moving parts, and a clearer contract: one endpoint, optional server-side headers, one HTTP call per check, and one boolean flag on the request.
+
+## Try it
+
+If you are running OGX, you can add guardrails to any existing Responses API call:
+
+```python
+response = client.responses.create(
+ model="openai/gpt-4o-mini",
+ input="Your prompt here",
+ tools=[{"type": "web_search_preview"}],
+ extra_body={"guardrails": True},
+)
+```
+
+Guardrails work inside the same Responses API loop that handles streaming, tool calling, MCP, file search, multi-turn conversations, and reasoning models. Text and reasoning content pass through the same moderation path regardless of which features the response uses.
+
+For more details on the implementation, see the source in [`streaming.py`](https://github.com/ogx-ai/ogx/blob/main/src/ogx/providers/inline/responses/builtin/responses/streaming.py) and [`utils.py`](https://github.com/ogx-ai/ogx/blob/main/src/ogx/providers/inline/responses/builtin/responses/utils.py).
diff --git a/docs/blog/images/claude-code-home.png b/docs/blog/images/claude-code-home.png
new file mode 100644
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diff --git a/docs/blog/images/claude-code-models.png b/docs/blog/images/claude-code-models.png
new file mode 100644
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diff --git a/docs/docs/api-anthropic-messages/conformance.mdx b/docs/docs/api-anthropic-messages/conformance.mdx
index c00a6e72eaf..74a526a5666 100644
--- a/docs/docs/api-anthropic-messages/conformance.mdx
+++ b/docs/docs/api-anthropic-messages/conformance.mdx
@@ -82,7 +82,7 @@ Below is a detailed breakdown of conformance issues and missing properties for e
| `requestBody.content.application/json.properties.requests.items.properties.params.properties.stream` | Default changed: None -> False |
| `requestBody.content.application/json.properties.requests.items.properties.params.properties.system` | Nullable added (Anthropic non-nullable); Union variants added: 3; Union variants removed: 2 |
| `requestBody.content.application/json.properties.requests.items.properties.params.properties.thinking` | Type added: ['object']; Union variants removed: 3 |
-| `requestBody.content.application/json.properties.requests.items.properties.params.properties.tool_choice` | Union variants removed: 4 |
+| `requestBody.content.application/json.properties.requests.items.properties.params.properties.tool_choice` | Union variants added: 4; Union variants removed: 4 |
| `requestBody.content.application/json.properties.requests.items.properties.params.properties.tools.items` | Union variants added: 4; Union variants removed: 16 |
| `responses.200.content.application/json.properties.type` | Default changed: message_batch -> None |
@@ -178,7 +178,7 @@ Below is a detailed breakdown of conformance issues and missing properties for e
| `requestBody.content.application/json.properties.stream` | Default changed: None -> False |
| `requestBody.content.application/json.properties.system` | Nullable added (Anthropic non-nullable); Union variants added: 3; Union variants removed: 2 |
| `requestBody.content.application/json.properties.thinking` | Type added: ['object']; Union variants removed: 3 |
-| `requestBody.content.application/json.properties.tool_choice` | Union variants removed: 4 |
+| `requestBody.content.application/json.properties.tool_choice` | Union variants added: 4; Union variants removed: 4 |
| `requestBody.content.application/json.properties.tools.items` | Union variants added: 4; Union variants removed: 16 |
| `responses.200.content.application/json.properties.content.items` | Union variants added: 6; Union variants removed: 12 |
| `responses.200.content.application/json.properties.model` | Type added: ['string']; Union variants removed: 17 |
diff --git a/docs/docs/api-openai/conformance.mdx b/docs/docs/api-openai/conformance.mdx
index b822dda9f03..c0dca165b5a 100644
--- a/docs/docs/api-openai/conformance.mdx
+++ b/docs/docs/api-openai/conformance.mdx
@@ -21,9 +21,9 @@ This documentation is auto-generated from the OpenAI API specification compariso
| **Overall Conformance Score** | 93.7% |
| **Endpoints Implemented** | 29/146 |
| **Total Properties Checked** | 3432 |
-| **Schema/Type Issues** | 152 |
+| **Schema/Type Issues** | 150 |
| **Missing Properties** | 65 |
-| **Total Issues to Fix** | 217 |
+| **Total Issues to Fix** | 215 |
## Integration Test Coverage
@@ -50,7 +50,7 @@ Categories are sorted by conformance score (lowest first, needing most attention
| Embeddings | 78.6% | 14 | 3 | 0 |
| Vector stores | 82.9% | 310 | 41 | 12 |
| Files | 92.9% | 42 | 1 | 2 |
-| Responses | 95.5% | 223 | 10 | 0 |
+| Responses | 96.4% | 223 | 8 | 0 |
| Chat | 98.7% | 449 | 5 | 1 |
| Conversations | 99.3% | 2165 | 15 | 1 |
@@ -724,7 +724,7 @@ Below is a detailed breakdown of conformance issues and missing properties for e
### Responses
-**Score:** 95.5% · **Issues:** 10 · **Missing:** 0
+**Score:** 96.4% · **Issues:** 8 · **Missing:** 0
#### `/responses`
@@ -750,12 +750,10 @@ Below is a detailed breakdown of conformance issues and missing properties for e
**POST**
-Schema Issues (3)
+Schema Issues (1)
| Property | Issues | Tested |
|----------|--------|--------|
-| `requestBody.content.application/json.properties.input` | Union variants added: 2; Union variants removed: 1 | Yes |
-| `requestBody.content.application/json.properties.model` | Type added: ['string']; Union variants removed: 3 | Yes |
| `responses.200.content.application/json.properties.output.items` | Union variants added: 4 | Yes |
diff --git a/docs/docs/api-openai/provider_matrix.md b/docs/docs/api-openai/provider_matrix.md
index a60a77fde16..4b0faccd856 100644
--- a/docs/docs/api-openai/provider_matrix.md
+++ b/docs/docs/api-openai/provider_matrix.md
@@ -19,13 +19,13 @@ inference provider, based on integration test results.
| Provider | Tested | Passing | Failing | Coverage |
|----------|--------|---------|---------|----------|
-| azure | 111 | 111 | 0 | 85% |
-| bedrock | 27 | 27 | 0 | 21% |
+| azure | 111 | 111 | 0 | 82% |
+| bedrock | 27 | 27 | 0 | 20% |
| ollama | 2 | 2 | 0 | 2% |
-| openai | 130 | 130 | 0 | 100% |
-| vertexai | 70 | 70 | 0 | 54% |
+| openai | 136 | 136 | 0 | 100% |
+| vertexai | 70 | 70 | 0 | 52% |
| vllm | 3 | 3 | 0 | 2% |
-| watsonx | 53 | 53 | 0 | 41% |
+| watsonx | 61 | 61 | 0 | 45% |
## Provider Details
@@ -100,8 +100,9 @@ Models, endpoints, and versions used during test recordings.
| Feature | azure | bedrock | ollama | openai | vertexai | vllm | watsonx |
| --- | --- | --- | --- | --- | --- | --- | --- |
-| mcp authorization backward compatibility | ✅ | ✅ | — | ✅ | — | — | — |
-| mcp authorization bearer | ✅ | ✅ | — | ✅ | — | — | — |
+| mcp authorization backward compatibility | ✅ | ✅ | — | ✅ | — | — | ⏭️ |
+| mcp authorization bearer | ✅ | ✅ | — | ✅ | — | — | ⏭️ |
+| mcp authorization error when header provided | ⏭️ | ⏭️ | — | ✅ | — | — | ✅ |
## Openai Responses
@@ -165,8 +166,13 @@ Models, endpoints, and versions used during test recordings.
| Feature | azure | bedrock | ollama | openai | vertexai | vllm | watsonx |
| --- | --- | --- | --- | --- | --- | --- | --- |
| reasoning basic streaming | ✅ | ✅ | ⏭️ | ✅ | ✅ | ✅ | ✅ |
-| reasoning multi turn passthrough | ⏭️ | ✅ | ✅ | ✅ | ⏭️ | ✅ | ⏭️ |
-| reasoning non streaming | ⏭️ | ✅ | ✅ | ✅ | ⏭️ | ✅ | ⏭️ |
+| reasoning multi turn passthrough | ⏭️ | ✅ | ✅ | ✅ | ⏭️ | ✅ | ✅ |
+| reasoning no summary without request | ⏭️ | ⏭️ | ⏭️ | ✅ | ⏭️ | ⏭️ | ✅ |
+| reasoning non streaming | ⏭️ | ✅ | ✅ | ✅ | ⏭️ | ✅ | ✅ |
+| reasoning summary event ordering | ⏭️ | ⏭️ | ⏭️ | ✅ | ⏭️ | ⏭️ | ✅ |
+| reasoning summary non streaming | ⏭️ | ⏭️ | ⏭️ | ✅ | ⏭️ | ⏭️ | ✅ |
+| reasoning summary streaming | ⏭️ | ⏭️ | ⏭️ | ✅ | ⏭️ | ⏭️ | ✅ |
+| reasoning summary usage included | ⏭️ | ⏭️ | ⏭️ | ✅ | ⏭️ | ⏭️ | ✅ |
## Responses Access Control
diff --git a/docs/docs/building_applications/codex_cli_integration.mdx b/docs/docs/building_applications/codex_cli_integration.mdx
index 353cdff4d24..3fec196388d 100644
--- a/docs/docs/building_applications/codex_cli_integration.mdx
+++ b/docs/docs/building_applications/codex_cli_integration.mdx
@@ -1,6 +1,6 @@
# Codex CLI Integration (Alpha)
-OGX can act as a proxy server for [Codex CLI](https://github.com/openai/codex), enabling you to use your existing Codex workflows while leveraging OGX's unified provider architecture and conversation compaction features.
+OGX includes built-in support for connecting [Codex CLI](https://github.com/openai/codex) with a single command. You can launch Codex against a running OGX server without manually editing your existing `~/.codex/config.toml`.
:::warning Alpha Feature
This integration is in early development (alpha status). While core functionality works well, some features like memory persistence are not yet supported. Configuration may change in future releases.
@@ -12,32 +12,118 @@ This integration is in early development (alpha status). While core functionalit
```bash
export OPENAI_API_KEY="your-key-here"
-ogx stack run starter
+ogx run starter
```
-### 2. Configure Codex CLI
+### 2. Connect Codex
-Add the following to your `~/.codex/config.toml`:
+```bash
+ogx connect codex
+```
+
+That launches Codex with an OGX-specific session config and model catalog generated from the models currently exposed by your running OGX server. Your existing `~/.codex/config.toml` is left unchanged.
+
+## How It Works
+
+The `ogx connect codex` command:
+
+1. Queries the running OGX server for available models
+2. Filters out embedding models
+3. Selects the requested model or defaults to the first available non-embedding model
+4. Generates a temporary Codex session home with an OGX provider profile and model catalog
+5. Launches `codex -p ogx`, or `codex exec -p ogx ` when `--exec` is provided
+
+```text
+ogx connect codex
+ |
+ v
+ GET /v1/models (discover available models)
+ |
+ v
+Build OGX model catalog + select default model
+ |
+ v
+Launch codex -p ogx using a generated session config
+ |
+ v
+ Codex TUI (connected to OGX)
+```
+
+## CLI Reference
+
+```bash
+ogx connect codex [--model MODEL] [--url URL] [--exec PROMPT]
+```
+
+| Flag | Default | Description |
+|------|---------|-------------|
+| `--model` | First available model | Model to pre-select for Codex |
+| `--url` | `http://localhost:8321/v1` | Full OGX OpenAI-compatible API base URL, including `/v1`. Also reads `OGX_BASE_URL`. |
+| `--exec` | Interactive Codex | Run Codex non-interactively with the provided prompt. Uses the same generated OGX session config as the interactive command. |
+
+## Configuration Examples
+
+### With a specific default model
+
+```bash
+ogx connect codex --model openai/gpt-4o
+```
+
+### With a remote OGX server
+
+```bash
+ogx connect codex --url https://ogx.example.com/v1
+```
+
+### Non-interactive one-shot prompt
+
+```bash
+ogx connect codex --exec "Write a hello world function in Python"
+```
+
+That runs `codex exec -p ogx` with the generated temporary OGX profile instead of opening the Codex TUI.
+
+### With OGX bearer auth
+
+```bash
+export OGX_API_KEY="your-ogx-access-token"
+ogx connect codex --url https://ogx.example.com/v1
+```
+
+### With passthrough provider credentials
+
+If your OGX deployment expects per-request provider data, export it as JSON before launching Codex:
+
+```bash
+export OGX_PROVIDER_DATA='{"passthrough_api_key":"provider-token"}'
+ogx connect codex
+```
+
+The generated Codex profile forwards that value as `X-OGX-Provider-Data` on every request, which lets OGX reuse the existing passthrough / provider-data auth path.
+
+## Manual Configuration
+
+If you prefer to manage Codex configuration yourself, add an OGX provider and model catalog to your Codex config:
+
+Create `~/.codex/ogx.config.toml`:
```toml
model = "openai/gpt-4o"
model_provider = "ogx"
+model_catalog_json = "/absolute/path/to/ogx-model-catalog.json"
+
+[features]
+multi_agent = false
[model_providers.ogx]
-name = "OpenAI"
+name = "OGX"
base_url = "http://localhost:8321/v1"
wire_api = "responses"
supports_websockets = false
+env_key = "OGX_API_KEY"
+env_http_headers = { "X-OGX-Provider-Data" = "OGX_PROVIDER_DATA" }
```
-### 3. Test the integration
-
-```bash
-codex "Write a hello world function in Python"
-```
-
-## How It Works
-
The integration works as a proxy chain: **Codex CLI → OGX → LLM Provider (OpenAI, etc.)**
Key benefits:
@@ -50,7 +136,9 @@ Key benefits:
### Model Compatibility
-Choose models that are available from your OGX server and compatible with the Responses API:
+`ogx connect codex` only offers the non-embedding model IDs returned by `GET /v1/models`, then writes those exact IDs into the generated Codex model catalog. That keeps Codex `/model` choices in sync with the running OGX server and preserves OGX metadata such as context length, descriptions, and any available reasoning-effort hints.
+
+Choose model IDs that OGX exposes and that Codex can use through the Responses API path configured above:
- `openai/gpt-4o`, `openai/gpt-4o-mini`, `openai/gpt-5.4`
- `anthropic/claude-3-5-sonnet-20241022`
- `ollama/llama3.2:3b`
@@ -62,8 +150,9 @@ Use provider-prefixed model IDs (for example `openai/gpt-4o`), and keep `wire_ap
Current limitations of this alpha integration:
1. **No memory persistence**: Conversation history isn't saved between Codex sessions
-2. **Limited error handling**: Some provider-specific errors may not surface clearly
-3. **Performance overhead**: Additional proxy layer adds latency
+2. **No Codex multi-agent tools**: The generated OGX profile disables Codex multi-agent tools because current OGX Responses models do not accept Codex's `namespace` tool shape
+3. **Limited error handling**: Some provider-specific errors may not surface clearly
+4. **Performance overhead**: Additional proxy layer adds latency
## Troubleshooting
@@ -73,6 +162,12 @@ Current limitations of this alpha integration:
**Tool execution failures**: Check that Codex has proper permissions for file/shell operations.
+**"Failed to find 'codex' in PATH"**: Install Codex from the [Codex GitHub repository](https://github.com/openai/codex) and make sure the `codex` binary is available on your shell path.
+
+**"Failed to connect to OGX server"**: Start the OGX server first with `ogx run ` or point `--url` at a reachable server.
+
+**Authenticated deployments**: Set `OGX_API_KEY` when your OGX deployment requires bearer auth. Set `OGX_PROVIDER_DATA` when OGX expects request-scoped passthrough credentials.
+
## Future Development
Planned improvements:
diff --git a/docs/docs/building_applications/opencode_integration.mdx b/docs/docs/building_applications/opencode_integration.mdx
index f126b95783c..d9c40f6c262 100644
--- a/docs/docs/building_applications/opencode_integration.mdx
+++ b/docs/docs/building_applications/opencode_integration.mdx
@@ -31,7 +31,7 @@ That's it. OpenCode starts with all your OGX models available and the first mode
The `ogx connect opencode` command:
1. Queries the running OGX server for available models
-2. Filters out non-LLM models (embeddings, rerankers)
+2. Filters out embedding models
3. Generates an OpenCode provider configuration with all discovered models
4. Launches OpenCode with the configuration via the `OPENCODE_CONFIG_CONTENT` environment variable
diff --git a/docs/docs/building_applications/rag_benchmarks.mdx b/docs/docs/building_applications/rag_benchmarks.mdx
index 59ba535e8de..17ef4ffcc9c 100644
--- a/docs/docs/building_applications/rag_benchmarks.mdx
+++ b/docs/docs/building_applications/rag_benchmarks.mdx
@@ -139,7 +139,7 @@ The same benchmark code runs against both OpenAI and OGX — the only difference
| Component | Configuration |
|---|---|
| **Embedding model** | `nomic-ai/nomic-embed-text-v1.5` (sentence-transformers) |
-| **Reranker model** | `Qwen/Qwen3-Reranker-0.6B` (transformers) |
+| **Reranker model** | `Qwen/Qwen3-Reranker-0.6B` (sentence-transformers) |
| **Vector database** | Milvus (standalone, remote) |
| **Chunk size** | 512 tokens |
| **Chunk overlap** | 128 tokens |
diff --git a/docs/docs/building_applications/tools.mdx b/docs/docs/building_applications/tools.mdx
index 10ebc528be8..ffea327b852 100644
--- a/docs/docs/building_applications/tools.mdx
+++ b/docs/docs/building_applications/tools.mdx
@@ -34,7 +34,7 @@ Built-in tool groups are automatically registered based on your configured `tool
### Web Search
-You have three providers to execute the web search tool calls generated by a model: Brave Search, Bing Search, and Tavily Search. Configure any of these as a `tool_runtime` provider and the `builtin::websearch` tool group will be auto-registered.
+You have four providers to execute the web search tool calls generated by a model: Brave Search, Bing Search, Tavily Search, and Nimble Search. Configure any of these as a `tool_runtime` provider and the `builtin::websearch` tool group will be auto-registered.
The tool requires an API key which can be provided either in the configuration or through the request header `X-OGX-Provider-Data`. The format of the header is:
```
diff --git a/docs/docs/contributing/index.mdx b/docs/docs/contributing/index.mdx
index d1aebb99e76..ae612ce5b47 100644
--- a/docs/docs/contributing/index.mdx
+++ b/docs/docs/contributing/index.mdx
@@ -137,7 +137,7 @@ Please avoid picking up too many issues at once. This helps you stay focused and
### I have a question
-1. Open a "discussion-type" issue or use [Discord](https://discord.gg/ZAFjsrcw).
+1. Open a "discussion-type" issue or use [Discord](https://discord.gg/bUYRqEvK6).
### Opening a Pull Request
diff --git a/docs/docs/distributions/configuration.mdx b/docs/docs/distributions/configuration.mdx
index 5bfc28eb07e..ec1fdff6a49 100644
--- a/docs/docs/distributions/configuration.mdx
+++ b/docs/docs/distributions/configuration.mdx
@@ -251,6 +251,8 @@ server:
tls_certfile: "/path/to/cert.pem" # Optional: Path to TLS certificate for HTTPS
tls_keyfile: "/path/to/key.pem" # Optional: Path to TLS key for HTTPS
registry_refresh_interval_seconds: 300 # Optional: Interval between registry refreshes (default: 300)
+ tenancy: # Optional: Multi-tenancy isolation (default: disabled)
+ mode: "disabled" # "disabled", "single", or "multi"
```
### Registry Refresh Interval
@@ -639,47 +641,201 @@ Regex patterns can be used to match resources based on naming conventions. For e
- Use anchors (`^` and `$`) when you need exact matching (default behavior uses `re.match()` which anchors at the start but not the end)
- Invalid regex patterns will log a warning and be treated as non-matches
-### Multi-Tenant Isolation for Conversations and Responses
+### Multi-Tenancy
-In a multi-tenant deployment, you typically want to ensure that each
-user's conversations, responses, and files are isolated from other
-users. Unlike registry resources (models, vector stores, etc.) which are
-identified by types like `model::my-model`, stored data uses the
-`sql_record::::` resource type pattern. Each
-record is automatically stamped with the authenticated user's identity
-when created, and the `user is owner` condition can be used to restrict
-access to only the user who created the record.
+OGX provides two layers of data isolation that can be used independently
+or together:
-The relevant `sql_record` table names are:
+1. **Tenant isolation** (`server.tenancy`) — a hard partition key
+ (`tenant_id`) applied to every stored row. Tenants cannot see each
+ other's data regardless of access policy. This is the primary
+ isolation boundary for multi-tenant deployments.
+2. **Owner-based access control** (`access_policy` with `user is owner`)
+ — attribute-based rules that control which user within a tenant can
+ read, update, or delete a given record. This is a sharing mechanism
+ within a tenant, not an isolation boundary on its own.
-| Table Name | Description |
-|---|---|
-| `openai_conversations` | Conversation sessions |
-| `conversation_items` | Messages and items within conversations |
-| `responses` | Stored responses (table name is configurable in provider config) |
-| `openai_files` | Uploaded files |
+For production multi-tenant deployments, use tenant isolation. Owner-based
+access control is useful for single-tenant setups where you want per-user
+record isolation, or as an additional layer within a tenant.
+
+#### Tenancy Modes
+
+The `server.tenancy` section configures tenant isolation. There are
+three modes:
+
+| Mode | Behavior |
+|------|----------|
+| `disabled` (default) | No tenant column, no filtering. Current behavior preserved. |
+| `single` | All records are stamped with a single configured `default_tenant_id`. Useful for dedicated single-tenant deployments that want a migration path to `multi`. |
+| `multi` | Every request must resolve a `tenant_id` from authentication. Requests without a tenant are rejected (401). Records are partitioned by tenant. |
+
+#### Tenant Resolution by Auth Provider
+
+Each authentication provider can resolve a `tenant_id` from the
+incoming request. The resolution mechanism depends on the provider type:
+
+| Provider | Config field | Source |
+|----------|-------------|--------|
+| `upstream_header` | `tenant_header` | HTTP header set by the upstream gateway |
+| `oauth2_token` | `tenant_claim` | JWT claim (JWKS) or introspection response field |
+| `kubernetes` | `tenant_claim` | Kubernetes user claim (resolved via `claims_mapping`) |
+| `custom` | `tenant_field` | Field in the auth endpoint JSON response |
+
+Tenant IDs are validated and normalized: lowercase, alphanumeric with
+hyphens and underscores, max 128 characters, matching
+`[a-z0-9][a-z0-9-_]{0,127}`.
+
+#### Example: Single-Tenant Deployment
+
+A dedicated deployment where all data belongs to one tenant. No auth
+required — useful for development or single-customer deployments:
+
+```yaml
+server:
+ port: 8321
+ tenancy:
+ mode: "single"
+ default_tenant_id: "acme-corp"
+```
+
+All records are automatically stamped with `tenant_id: "acme-corp"`.
+This creates a clean migration path — when you later move to `multi`
+mode, existing data is already tagged.
+
+#### Example: Multi-Tenant with Upstream Gateway (Authorino, Istio)
+
+The most common production pattern. An upstream gateway (Authorino,
+Istio, or a reverse proxy) authenticates the request and injects
+identity headers. OGX trusts these headers and extracts the tenant from
+a dedicated header:
+
+```yaml
+server:
+ port: 8321
+ tenancy:
+ mode: "multi"
+ auth:
+ provider_config:
+ type: "upstream_header"
+ principal_header: "x-auth-user-id"
+ tenant_header: "x-tenant-id"
+ attributes_header: "x-auth-attributes"
+```
+
+The gateway is responsible for setting `x-tenant-id` on every request.
+If the header is missing, OGX rejects the request with a 401.
-The following example shows a complete access policy that allows any
-authenticated user to use models and create new resources, while
-ensuring that conversations, responses, and files can only be accessed
-by the user who created them:
+#### Example: Multi-Tenant with OAuth2/OIDC (Keycloak)
+
+Extract the tenant from a JWT claim. Configure your identity provider
+to include a tenant claim in the token:
```yaml
server:
port: 8321
+ tenancy:
+ mode: "multi"
auth:
provider_config:
type: "oauth2_token"
+ tenant_claim: "tenant"
+ jwks:
+ uri: ${env.KEYCLOAK_URL}/realms/ogx/protocol/openid-connect/certs
+ issuer: ${env.KEYCLOAK_URL}/realms/ogx
+ audience: "ogx"
+```
+
+This reads the `tenant` claim from the JWT payload. For example, a
+decoded token with `{"sub": "alice", "tenant": "acme-corp", ...}` would
+resolve `tenant_id: "acme-corp"`. Any claim name can be used — set
+`tenant_claim` to match your IdP's token structure (e.g., `"org"`,
+`"organization_id"`, `"tid"`).
+
+#### Example: Multi-Tenant with Kubernetes Auth
+
+Use a Kubernetes user claim as the tenant identifier. The `tenant_claim`
+is resolved through the same `claims_mapping` path used for access
+attributes:
+
+```yaml
+server:
+ port: 8321
+ tenancy:
+ mode: "multi"
+ auth:
+ provider_config:
+ type: "kubernetes"
+ api_server_url: "https://kubernetes.default.svc"
+ tenant_claim: "extra.tenant"
+ claims_mapping:
+ username: "roles"
+ groups: "roles"
+```
+
+Here `tenant_claim: "extra.tenant"` extracts the first value from
+`userInfo.extra.tenant` (for example, `"tenant-a"`) as the tenant
+partition key. Use a claim whose value already matches the tenant ID
+format; raw Kubernetes usernames such as
+`system:serviceaccount:tenant-a:default` are not valid tenant IDs.
+
+#### Example: Multi-Tenant with Custom Auth Endpoint
+
+Extract the tenant from your custom auth endpoint's response. The
+endpoint must return the tenant identifier in a known field:
+
+```yaml
+server:
+ port: 8321
+ tenancy:
+ mode: "multi"
+ auth:
+ provider_config:
+ type: "custom"
+ endpoint: "https://auth.example.com/validate"
+ tenant_field: "tenant_id"
+```
+
+The custom endpoint's JSON response should include the tenant field:
+
+```json
+{
+ "principal": "alice",
+ "attributes": {
+ "roles": ["user"],
+ "teams": ["ml-team"]
+ },
+ "tenant_id": "acme-corp",
+ "message": "Authentication successful"
+}
+```
+
+#### Combining Tenant Isolation with Access Control
+
+Tenant isolation and access control operate at different levels. Tenant
+isolation partitions data between organizations. Access control governs
+what individual users can do within their tenant. For full production
+isolation, use both:
+
+```yaml
+server:
+ port: 8321
+ tenancy:
+ mode: "multi"
+ auth:
+ provider_config:
+ type: "oauth2_token"
+ tenant_claim: "tenant"
jwks:
uri: "https://my-auth-provider.com/jwks"
access_policy:
- # Allow all authenticated users to use configured models for inference
+ # All authenticated users can use configured models
- permit:
actions: [read]
resource: model::*
description: Any authenticated user can use configured models
- # File isolation
+ # File isolation — users can only access their own files
- permit:
actions: [create]
resource: sql_record::openai_files::*
@@ -724,20 +880,77 @@ server:
description: Users can only access their own responses
```
-With this policy:
-- Any user with a valid token can call inference endpoints and create new conversations, responses, and files.
-- A user can only list, read, update, or delete their own conversations, responses, and files. Attempts to access another user's resources will be denied.
-- The `user is owner` condition works by comparing the authenticated user's principal (from the JWT token) against the `owner_principal` stored on each record.
+With this configuration:
+- **Tenant isolation** ensures that users in `acme-corp` never see data
+ from `beta-inc`, regardless of access policy rules.
+- **Owner isolation** ensures that Alice within `acme-corp` cannot read
+ Bob's conversations, even though they share a tenant.
+- The `user is owner` condition compares the authenticated user's
+ principal (from the JWT `sub` claim) against the `owner_principal`
+ stored on each record.
+
+:::note
+Tenant isolation is enforced at the storage layer independently of
+access policies. Even if the access policy permits all actions, a user
+can only see rows that match their `tenant_id`. This is a non-bypassable
+filter — there is no policy rule that can override it.
+:::
+
+#### Owner-Based Isolation Without Tenancy
+
+For single-tenant deployments or development environments where you want
+per-user record isolation without a tenant partition, you can use
+`user is owner` conditions in the access policy alone:
+
+```yaml
+server:
+ port: 8321
+ auth:
+ provider_config:
+ type: "oauth2_token"
+ jwks:
+ uri: "https://my-auth-provider.com/jwks"
+ access_policy:
+ - permit:
+ actions: [read]
+ resource: model::*
+ description: Any authenticated user can use configured models
+ - permit:
+ actions: [create]
+ resource: sql_record::*
+ description: Any authenticated user can create records
+ - permit:
+ actions: [read, update, delete]
+ resource: sql_record::*
+ when: user is owner
+ description: Users can only access records they created
+```
+
+This provides user-level isolation through access control but does not
+create a hard tenant boundary. If two users share an attribute value
+(e.g., `teams=["engineering"]`), a policy using `user in owner teams`
+could grant cross-user access. For production multi-tenant deployments,
+use `server.tenancy.mode: "multi"` instead.
:::note
If no explicit `access_policy` is specified, OGX applies a
default policy where all users can access resources defined in config
(like models) but dynamically created resources can only be accessed by
-the user that created them. However, for production multi-tenant
-deployments it is recommended to define an explicit policy like the
-example above.
+the user that created them.
:::
+#### SQL Record Table Names
+
+The following table names are used for `sql_record` resource types in
+access policies:
+
+| Table Name | Description |
+|---|---|
+| `openai_conversations` | Conversation sessions |
+| `conversation_items` | Messages and items within conversations |
+| `responses` | Stored responses (table name is configurable in provider config) |
+| `openai_files` | Uploaded files |
+
### Route-Level Authorization
Route-level authorization provides infrastructure-level access control for OGX API routes. This feature allows administrators to restrict which API routes can be accessed based on user attributes (when authentication is enabled) or to globally block/allow specific routes (without authentication).
diff --git a/docs/docs/distributions/k8s/stack-configmap.yaml b/docs/docs/distributions/k8s/stack-configmap.yaml
index 440437af24d..e35e5beddd6 100644
--- a/docs/docs/distributions/k8s/stack-configmap.yaml
+++ b/docs/docs/distributions/k8s/stack-configmap.yaml
@@ -21,9 +21,6 @@ data:
- provider_id: sentence-transformers
provider_type: inline::sentence-transformers
config: {}
- - provider_id: transformers
- provider_type: inline::transformers
- config: {}
vector_io:
- provider_id: ${env.ENABLE_CHROMADB:+chromadb}
provider_type: remote::chromadb
diff --git a/docs/docs/distributions/k8s/stack_run_config.yaml b/docs/docs/distributions/k8s/stack_run_config.yaml
index 30cba35811f..05f1cfeaadd 100644
--- a/docs/docs/distributions/k8s/stack_run_config.yaml
+++ b/docs/docs/distributions/k8s/stack_run_config.yaml
@@ -18,9 +18,6 @@ providers:
- provider_id: sentence-transformers
provider_type: inline::sentence-transformers
config: {}
- - provider_id: transformers
- provider_type: inline::transformers
- config: {}
vector_io:
- provider_id: ${env.ENABLE_CHROMADB:+chromadb}
provider_type: remote::chromadb
@@ -126,5 +123,5 @@ vector_stores:
provider_id: sentence-transformers
model_id: nomic-ai/nomic-embed-text-v1.5
default_reranker_model:
- provider_id: transformers
+ provider_id: sentence-transformers
model_id: Qwen/Qwen3-Reranker-0.6B
diff --git a/docs/docs/distributions/self_hosted_distro/starter.md b/docs/docs/distributions/self_hosted_distro/starter.md
index d7c320b2014..1e782acdf7e 100644
--- a/docs/docs/distributions/self_hosted_distro/starter.md
+++ b/docs/docs/distributions/self_hosted_distro/starter.md
@@ -18,7 +18,7 @@ The starter distribution consists of the following provider configurations:
| files | `inline::localfs` |
| inference | `remote::openai`, `remote::fireworks`, `remote::together`, `remote::ollama`, `remote::anthropic`, `remote::gemini`, `remote::groq`, `remote::sambanova`, `remote::vllm`, `remote::cerebras`, `remote::llama-openai-compat`, `remote::nvidia`, `inline::sentence-transformers` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::file-search`, `remote::model-context-protocol` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `remote::nimble-search`, `inline::file-search`, `remote::model-context-protocol` |
| vector_io | `inline::faiss`, `inline::sqlite-vec`, `inline::milvus`, `remote::chromadb`, `remote::pgvector`, `remote::qdrant`, `remote::weaviate`, `remote::elasticsearch`, `remote::infinispan` |
## Inference Providers
@@ -125,6 +125,7 @@ The following environment variables can be configured:
- `BRAVE_SEARCH_API_KEY`: Brave Search API key
- `TAVILY_SEARCH_API_KEY`: Tavily Search API key
+- `NIMBLE_API_KEY`: Nimble Search API key
## Enabling Providers
diff --git a/docs/docs/index.mdx b/docs/docs/index.mdx
index 0ed5c6fdfe2..e716e212002 100644
--- a/docs/docs/index.mdx
+++ b/docs/docs/index.mdx
@@ -97,7 +97,7 @@ OGX has a pluggable provider architecture across every API, not just inference.
- **23 inference providers:** Ollama, vLLM, OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, Gemini, Vertex AI, NVIDIA NIM, Fireworks, Together AI, Groq, SambaNova, Cerebras, WatsonX, and more
- **15 vector store providers:** FAISS, SQLite-vec, ChromaDB, Qdrant, Milvus, PGVector, Weaviate, Elasticsearch, and more
- **Built-in guardrails support:** Responses guardrails call an external OpenAI-compatible moderation endpoint configured by `moderation_endpoint`
-- **6 tool runtimes:** File Search, Brave/Bing/Tavily web search, Wolfram Alpha, MCP
+- **7 tool runtimes:** File Search, Brave/Bing/Tavily/Nimble web search, Wolfram Alpha, MCP
Develop locally with Ollama and FAISS. Deploy to production with vLLM and PGVector. Wrap Bedrock or Vertex without lock-in. Same API surface, different backend.
diff --git a/docs/docs/providers/container_runtime/index.mdx b/docs/docs/providers/container_runtime/index.mdx
new file mode 100644
index 00000000000..0f8e8e48fba
--- /dev/null
+++ b/docs/docs/providers/container_runtime/index.mdx
@@ -0,0 +1,10 @@
+---
+sidebar_label: Container Runtime
+title: Container Runtime
+---
+
+# Container Runtime
+
+## Overview
+
+This section contains documentation for all available providers for the **container_runtime** API.
diff --git a/docs/docs/providers/file_processors/inline_unstructured.mdx b/docs/docs/providers/file_processors/inline_unstructured.mdx
new file mode 100644
index 00000000000..418de6ff9a2
--- /dev/null
+++ b/docs/docs/providers/file_processors/inline_unstructured.mdx
@@ -0,0 +1,256 @@
+---
+description: |
+ [Unstructured](https://github.com/Unstructured-IO/unstructured) is a comprehensive document
+ processing library supporting 65+ file formats including PDF, Office documents (DOCX, PPTX, XLSX),
+ email formats (EML, MSG), legacy formats (DOC, XLS), HTML, Markdown, and audio transcription.
+
+ This provider uses the local Unstructured library for offline document processing. For cloud-based
+ processing with better table extraction, use `remote::unstructured-api` instead.
+
+ ## Features
+
+ - 65+ format support - broadest format coverage of any OGX file processor
+ - Email processing - EML and MSG email formats (unique to Unstructured)
+ - Legacy formats - DOC, XLS, and other legacy Office formats
+ - Audio transcription - MP3, WAV, M4A via Whisper
+ - Local processing - no network required, cost-effective for high volume
+ - Structure-aware chunking - preserves document sections and headings
+
+ ## Limitations
+
+ WARNING: Table detection is unreliable in local mode (GitHub issue [#2997](https://github.com/Unstructured-IO/unstructured/issues/2997)).
+ For production table extraction, use `remote::unstructured-api` instead.
+
+ ## System Requirements
+
+ Required system dependencies:
+ - `libmagic-dev` - file type detection
+ - `poppler-utils` - PDF processing
+ - `tesseract-ocr` - OCR support
+
+ Optional (for Office documents):
+ - `libreoffice` - Office document conversion (~800 MB)
+
+ ### macOS
+ ```bash
+ brew install libmagic poppler tesseract
+ # Optional: brew install libreoffice
+ ```
+
+ ### Ubuntu/Debian
+ ```bash
+ sudo apt-get update && sudo apt-get install -y \
+ libmagic-dev \
+ poppler-utils \
+ tesseract-ocr
+ # Optional: sudo apt-get install -y libreoffice
+ ```
+
+ ### Docker (Recommended)
+ ```dockerfile
+ FROM python:3.12-slim
+
+ RUN apt-get update && apt-get install -y \
+ libmagic-dev \
+ poppler-utils \
+ tesseract-ocr \
+ && rm -rf /var/lib/apt/lists/*
+
+ RUN pip install ogx[unstructured-local]
+ ```
+
+ ## Installation
+
+ ```bash
+ pip install "ogx[unstructured-local]"
+ ```
+
+ Then install system dependencies as shown above.
+
+ ## Usage
+
+ Start OGX with the Unstructured file processor:
+
+ ```bash
+ ogx stack run \
+ --providers "file_processors=inline::unstructured" \
+ --port 8321
+ ```
+
+ Or add it to a custom `run.yaml`:
+
+ ```yaml
+ file_processors:
+ - provider_id: unstructured
+ provider_type: inline::unstructured
+ config:
+ strategy: auto # or 'fast', 'hi_res', 'ocr_only'
+ skip_infer_table_types: ["pdf"] # Workaround for table issues
+ ```
+
+ ## When to Use
+
+ **Use `inline::unstructured` when:**
+ - You need email format support (EML, MSG)
+ - You need legacy Office formats (DOC, XLS)
+ - You need audio transcription
+ - You need offline/local processing
+ - You need the broadest format coverage
+
+ **Use `inline::docling` when:**
+ - You need precise token-based chunking
+ - You need best-in-class table extraction
+ - You primarily process PDF/DOCX/PPTX
+
+ **Use `remote::unstructured-api` when:**
+ - You need reliable table extraction
+ - You have network connectivity and API key
+ - You want to avoid system dependencies
+
+ ## Documentation
+
+ See [Unstructured's documentation](https://docs.unstructured.io/) for more details.
+sidebar_label: Unstructured
+title: inline::unstructured
+---
+
+# inline::unstructured
+
+## Description
+
+
+[Unstructured](https://github.com/Unstructured-IO/unstructured) is a comprehensive document
+processing library supporting 65+ file formats including PDF, Office documents (DOCX, PPTX, XLSX),
+email formats (EML, MSG), legacy formats (DOC, XLS), HTML, Markdown, and audio transcription.
+
+This provider uses the local Unstructured library for offline document processing. For cloud-based
+processing with better table extraction, use `remote::unstructured-api` instead.
+
+## Features
+
+- 65+ format support - broadest format coverage of any OGX file processor
+- Email processing - EML and MSG email formats (unique to Unstructured)
+- Legacy formats - DOC, XLS, and other legacy Office formats
+- Audio transcription - MP3, WAV, M4A via Whisper
+- Local processing - no network required, cost-effective for high volume
+- Structure-aware chunking - preserves document sections and headings
+
+## Limitations
+
+WARNING: Table detection is unreliable in local mode (GitHub issue [#2997](https://github.com/Unstructured-IO/unstructured/issues/2997)).
+For production table extraction, use `remote::unstructured-api` instead.
+
+## System Requirements
+
+Required system dependencies:
+- `libmagic-dev` - file type detection
+- `poppler-utils` - PDF processing
+- `tesseract-ocr` - OCR support
+
+Optional (for Office documents):
+- `libreoffice` - Office document conversion (~800 MB)
+
+### macOS
+```bash
+brew install libmagic poppler tesseract
+# Optional: brew install libreoffice
+```
+
+### Ubuntu/Debian
+```bash
+sudo apt-get update && sudo apt-get install -y \
+ libmagic-dev \
+ poppler-utils \
+ tesseract-ocr
+# Optional: sudo apt-get install -y libreoffice
+```
+
+### Docker (Recommended)
+```dockerfile
+FROM python:3.12-slim
+
+RUN apt-get update && apt-get install -y \
+ libmagic-dev \
+ poppler-utils \
+ tesseract-ocr \
+ && rm -rf /var/lib/apt/lists/*
+
+RUN pip install ogx[unstructured-local]
+```
+
+## Installation
+
+```bash
+pip install "ogx[unstructured-local]"
+```
+
+Then install system dependencies as shown above.
+
+## Usage
+
+Start OGX with the Unstructured file processor:
+
+```bash
+ogx stack run \
+ --providers "file_processors=inline::unstructured" \
+ --port 8321
+```
+
+Or add it to a custom `run.yaml`:
+
+```yaml
+file_processors:
+ - provider_id: unstructured
+ provider_type: inline::unstructured
+ config:
+ strategy: auto # or 'fast', 'hi_res', 'ocr_only'
+ skip_infer_table_types: ["pdf"] # Workaround for table issues
+```
+
+## When to Use
+
+**Use `inline::unstructured` when:**
+- You need email format support (EML, MSG)
+- You need legacy Office formats (DOC, XLS)
+- You need audio transcription
+- You need offline/local processing
+- You need the broadest format coverage
+
+**Use `inline::docling` when:**
+- You need precise token-based chunking
+- You need best-in-class table extraction
+- You primarily process PDF/DOCX/PPTX
+
+**Use `remote::unstructured-api` when:**
+- You need reliable table extraction
+- You have network connectivity and API key
+- You want to avoid system dependencies
+
+## Documentation
+
+See [Unstructured's documentation](https://docs.unstructured.io/) for more details.
+
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `strategy` | `Literal[auto, fast, hi_res, ocr_only]` | No | auto | Partitioning strategy for document processing. 'auto' (default) intelligently selects the best approach based on document type. 'fast' uses text extraction without layout analysis (fastest). 'hi_res' uses layout models for better structure detection (slowest). 'ocr_only' uses Tesseract OCR for scanned documents. WARNING: Table detection is unreliable in local mode due to known issue (https://github.com/Unstructured-IO/unstructured/issues/2997). Use remote::unstructured-api for production table extraction. |
+| `default_chunk_size_tokens` | `int` | No | 800 | Default chunk size in tokens when chunking_strategy type is 'auto' |
+| `default_chunk_overlap_tokens` | `int` | No | 400 | Default chunk overlap in tokens when chunking_strategy type is 'auto' |
+| `include_page_breaks` | `bool` | No | True | Include PageBreak elements in output for supported formats (PDF, PPTX, HTML) |
+| `skip_infer_table_types` | `list[str]` | No | ['pdf'] | File types to skip table inference for (workaround for local table detection issues). Example: ['pdf', 'docx']. Set to empty list [] to attempt table detection for all formats. Note: Table detection is unreliable in local mode; use remote::unstructured-api for reliable tables. |
+| `extract_images_in_pdf` | `bool` | No | False | Extract images from PDFs. Requires strategy='hi_res'. May fail on some systems due to missing dependencies. Set to True only if you need image extraction and have verified it works in your environment. |
+| `languages` | `list[str]` | No | ['eng'] | OCR language codes for Tesseract (e.g., ['eng', 'spa', 'deu']). Additional language packs must be installed separately via tesseract-ocr-{lang}. |
+
+## Sample Configuration
+
+```yaml
+strategy: auto
+default_chunk_size_tokens: 800
+default_chunk_overlap_tokens: 400
+skip_infer_table_types:
+- pdf
+languages:
+- eng
+```
diff --git a/docs/docs/providers/inference/inline_transformers.mdx b/docs/docs/providers/inference/inline_transformers.mdx
deleted file mode 100644
index 001956c85dc..00000000000
--- a/docs/docs/providers/inference/inline_transformers.mdx
+++ /dev/null
@@ -1,17 +0,0 @@
----
-description: "Transformers inference provider for neural rerank."
-sidebar_label: Transformers
-title: inline::transformers
----
-
-# inline::transformers
-
-## Description
-
-Transformers inference provider for neural rerank.
-
-## Sample Configuration
-
-```yaml
-{}
-```
diff --git a/docs/docs/providers/responses/inline_builtin.mdx b/docs/docs/providers/responses/inline_builtin.mdx
index 489bb18e909..c5dab2ec04a 100644
--- a/docs/docs/providers/responses/inline_builtin.mdx
+++ b/docs/docs/providers/responses/inline_builtin.mdx
@@ -92,6 +92,7 @@ Be concise, structured, and focused on helping the next LLM seamlessly continue
| `compaction_config.tokenizer_encoding` | `str \| None` | No | | Default tiktoken encoding name for token counting (e.g. 'o200k_base', 'cl100k_base'). Applied as a server-level default after any per-request override via extra_body. If not set, encoding is resolved from the model name via tiktoken, then model-family prefix mappings, then character-based estimation. |
| `compaction_config.model_tokenizer_mappings` | `dict[str, str]` | No | {'llama': 'cl100k_base', 'mistral': 'cl100k_base', 'claude': 'cl100k_base', 'gemma': 'cl100k_base', 'qwen': 'cl100k_base', 'phi': 'cl100k_base', 'deepseek': 'cl100k_base'} | Map model name prefixes to tiktoken encoding names. Used as a heuristic fallback when tiktoken cannot resolve the model name directly. Matching is case-insensitive on the model name after stripping any provider prefix (e.g., 'ollama/llama3.2:3b' matches the 'llama' prefix). Admins can extend this to support custom or fine-tuned models. |
| `moderation_endpoint` | `str \| None` | No | | URL of an OpenAI-compatible /v1/moderations endpoint for guardrails. The endpoint must accept POST {"input": "text"} and return {"results": [{"flagged": bool, "categories": {...}}]}. |
+| `moderation_headers` | `dict[str, str] \| None` | No | | HTTP headers to send with moderation endpoint requests. Use this to provide authentication for hosted moderation services (e.g., {'Authorization': 'Bearer sk-...'}). These headers are server-side only and never exposed to clients. |
## Sample Configuration
diff --git a/docs/docs/providers/skills/index.mdx b/docs/docs/providers/skills/index.mdx
new file mode 100644
index 00000000000..a0b1f7fb10e
--- /dev/null
+++ b/docs/docs/providers/skills/index.mdx
@@ -0,0 +1,20 @@
+---
+description: |
+ Skills API for managing versioned skill bundles.
+
+ Skills are zip archives containing a SKILL.md manifest and supporting files.
+ Conforms to the OpenAI Skills API wire format.
+sidebar_label: Skills
+title: Skills
+---
+
+# Skills
+
+## Overview
+
+Skills API for managing versioned skill bundles.
+
+Skills are zip archives containing a SKILL.md manifest and supporting files.
+Conforms to the OpenAI Skills API wire format.
+
+This section contains documentation for all available providers for the **skills** API.
diff --git a/docs/docs/providers/skills/inline_builtin.mdx b/docs/docs/providers/skills/inline_builtin.mdx
new file mode 100644
index 00000000000..f552664549d
--- /dev/null
+++ b/docs/docs/providers/skills/inline_builtin.mdx
@@ -0,0 +1,27 @@
+---
+description: "Built-in skills provider using Files API for bundle storage."
+sidebar_label: Builtin
+title: inline::builtin
+---
+
+# inline::builtin
+
+## Description
+
+Built-in skills provider using Files API for bundle storage.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `persistence` | `KVStoreReference` | No | | KV store reference for skill metadata persistence |
+| `persistence.namespace` | `str` | No | | Key prefix for KVStore backends |
+| `persistence.backend` | `str` | No | | Name of backend from storage.backends |
+
+## Sample Configuration
+
+```yaml
+persistence:
+ namespace: skills
+ backend: kv_default
+```
diff --git a/docs/docs/providers/tool_runtime/remote_bing-search.mdx b/docs/docs/providers/tool_runtime/remote_bing-search.mdx
index 6f7a01af525..17a089436df 100644
--- a/docs/docs/providers/tool_runtime/remote_bing-search.mdx
+++ b/docs/docs/providers/tool_runtime/remote_bing-search.mdx
@@ -16,11 +16,11 @@ Bing Search tool for web search capabilities using Microsoft's search engine.
|-------|------|----------|---------|-------------|
| `timeout` | `float` | No | 30.0 | Overall HTTP timeout in seconds for requests to external services. |
| `connect_timeout` | `float` | No | 10.0 | TCP connect timeout in seconds. Shorter than the overall timeout to fail fast on unreachable hosts. |
-| `api_key` | `str \| None` | No | | |
+| `api_key` | `SecretStr \| None` | No | | The Bing Search API Key. Can be overridden per-request via X-OGX-Provider-Data header. |
| `top_k` | `int` | No | 3 | |
## Sample Configuration
```yaml
-api_key: ${env.BING_API_KEY:}
+api_key: ${env.BING_API_KEY:=}
```
diff --git a/docs/docs/providers/tool_runtime/remote_brave-search.mdx b/docs/docs/providers/tool_runtime/remote_brave-search.mdx
index 92410b286d1..d022950ee9a 100644
--- a/docs/docs/providers/tool_runtime/remote_brave-search.mdx
+++ b/docs/docs/providers/tool_runtime/remote_brave-search.mdx
@@ -16,7 +16,7 @@ Brave Search tool for web search capabilities with privacy-focused results.
|-------|------|----------|---------|-------------|
| `timeout` | `float` | No | 30.0 | Overall HTTP timeout in seconds for requests to external services. |
| `connect_timeout` | `float` | No | 10.0 | TCP connect timeout in seconds. Shorter than the overall timeout to fail fast on unreachable hosts. |
-| `api_key` | `str \| None` | No | | The Brave Search API Key |
+| `api_key` | `SecretStr \| None` | No | | The Brave Search API Key. Can be overridden per-request via X-OGX-Provider-Data header. |
| `max_results` | `int` | No | 3 | The maximum number of results to return |
## Sample Configuration
diff --git a/docs/docs/providers/tool_runtime/remote_nimble-search.mdx b/docs/docs/providers/tool_runtime/remote_nimble-search.mdx
new file mode 100644
index 00000000000..485a78e81dc
--- /dev/null
+++ b/docs/docs/providers/tool_runtime/remote_nimble-search.mdx
@@ -0,0 +1,29 @@
+---
+description: "Nimble Search tool for web search via Nimble's SERP-backed search API."
+sidebar_label: Remote - Nimble-Search
+title: remote::nimble-search
+---
+
+# remote::nimble-search
+
+## Description
+
+Nimble Search tool for web search via Nimble's SERP-backed search API.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `timeout` | `float` | No | 30.0 | Overall HTTP timeout in seconds for requests to external services. |
+| `connect_timeout` | `float` | No | 10.0 | TCP connect timeout in seconds. Shorter than the overall timeout to fail fast on unreachable hosts. |
+| `api_key` | `SecretStr \| None` | No | | The Nimble API key, sent as a Bearer token. Can be overridden per-request via the X-OGX-Provider-Data header. |
+| `max_results` | `int` | No | 3 | The maximum number of results to return |
+| `search_depth` | `Literal[lite, deep]` | No | lite | Content richness: 'lite' returns title, URL, and description; 'deep' returns full page content |
+
+## Sample Configuration
+
+```yaml
+api_key: ${env.NIMBLE_API_KEY:=}
+max_results: 3
+search_depth: lite
+```
diff --git a/docs/docs/providers/tool_runtime/remote_tavily-search.mdx b/docs/docs/providers/tool_runtime/remote_tavily-search.mdx
index 5633439536c..4d172efe94b 100644
--- a/docs/docs/providers/tool_runtime/remote_tavily-search.mdx
+++ b/docs/docs/providers/tool_runtime/remote_tavily-search.mdx
@@ -16,7 +16,7 @@ Tavily Search tool for AI-optimized web search with structured results.
|-------|------|----------|---------|-------------|
| `timeout` | `float` | No | 30.0 | Overall HTTP timeout in seconds for requests to external services. |
| `connect_timeout` | `float` | No | 10.0 | TCP connect timeout in seconds. Shorter than the overall timeout to fail fast on unreachable hosts. |
-| `api_key` | `str \| None` | No | | The Tavily Search API Key |
+| `api_key` | `SecretStr \| None` | No | | The Tavily Search API Key. Can be overridden per-request via X-OGX-Provider-Data header. |
| `max_results` | `int` | No | 3 | The maximum number of results to return |
## Sample Configuration
diff --git a/docs/docs/references/ogx_cli_reference/index.md b/docs/docs/references/ogx_cli_reference/index.md
index 1409f2e613b..88f64e79024 100644
--- a/docs/docs/references/ogx_cli_reference/index.md
+++ b/docs/docs/references/ogx_cli_reference/index.md
@@ -31,7 +31,7 @@ You have two ways to install OGX:
## `ogx` subcommands
1. `stack`: Allows you to build a stack using the `ogx` distribution and run a OGX server. You can read more about how to build a OGX distribution in the [Build your own Distribution](../../distributions/building_distro) documentation.
-2. `connect`: Connect third-party tools to the running OGX server. Supports [`claude`](../../building_applications/claude_code_integration) and [`opencode`](../../building_applications/opencode_integration).
+2. `connect`: Connect third-party tools to the running OGX server. Supports [`claude`](../../building_applications/claude_code_integration), [`opencode`](../../building_applications/opencode_integration), and [`codex`](../../building_applications/codex_cli_integration).
For downloading models, we recommend using the [Hugging Face CLI](https://huggingface.co/docs/huggingface_hub/guides/cli). See [Downloading models](#downloading-models) for more information.
diff --git a/docs/docusaurus.config.ts b/docs/docusaurus.config.ts
index dcd13369c13..476d0b26975 100644
--- a/docs/docusaurus.config.ts
+++ b/docs/docusaurus.config.ts
@@ -208,7 +208,7 @@ const config: Config = {
items: [
{
label: 'Discord',
- href: 'https://discord.gg/ZAFjsrcw',
+ href: 'https://discord.gg/bUYRqEvK6',
},
{
label: 'Issues',
diff --git a/docs/gpu-runners.md b/docs/gpu-runners.md
new file mode 100644
index 00000000000..5a8d1d9f662
--- /dev/null
+++ b/docs/gpu-runners.md
@@ -0,0 +1,405 @@
+# GPU Runners for vLLM Recording
+
+This guide explains how to use GPU-enabled self-hosted runners to re-record vLLM integration tests with larger models like `gpt-oss:20b`.
+
+## Overview
+
+GPU runners allow us to:
+
+- Test larger models (20B parameters) that don't fit on CPU runners
+- Faster inference with GPU acceleration
+- More realistic production-like test environment
+- On-demand re-recording via workflow_dispatch
+
+**Cost**: ~$0.43 per run (30 min on g6.2xlarge), ~$1.72/month for weekly runs
+
+## Quick Start
+
+### Trigger a GPU Recording Run
+
+1. Go to **Actions** tab in GitHub
+2. Select **vLLM GPU Recording** workflow
+3. Click **Run workflow**
+4. Configure:
+ - **Suite**: `base` (default)
+5. Click **Run workflow**
+
+The workflow will:
+
+1. Launch a GPU EC2 instance (5 min)
+2. Set up the CUDA environment and install the pinned vLLM runtime (5 min)
+3. Run tests in record mode (~20 min)
+4. Upload recordings as artifacts
+5. Terminate the EC2 instance
+
+**Total time**: ~30 minutes
+
+### Download Recordings
+
+1. Wait for the workflow to complete
+2. Go to the workflow run summary
+3. Download the `vllm-gpu-recordings-*` artifact
+4. Extract and commit the recordings to your PR
+
+## Architecture
+
+```text
+┌─────────────────────────────────────────────────┐
+│ Workflow Trigger (manual) │
+│ - Select test suite │
+└────────────────┬────────────────────────────────┘
+ │
+ ▼
+┌─────────────────────────────────────────────────┐
+│ Job 1: Start GPU EC2 Runner │
+│ - AWS OIDC authentication (no long-lived keys!)│
+│ - Multi-AZ fallback in us-east-2 │
+│ - Launch g6.2xlarge with GPU AMI │
+│ - Register as GitHub Actions runner │
+└────────────────┬────────────────────────────────┘
+ │
+ ▼
+┌─────────────────────────────────────────────────┐
+│ Job 2: Run vLLM Recording Tests │
+│ - Runs on GPU runner (permissions: {}) │
+│ - Install vLLM with CUDA support │
+│ - Start vLLM server with gpt-oss:20b │
+│ - Run integration tests in record mode │
+│ - Upload recordings as artifacts │
+└────────────────┬────────────────────────────────┘
+ │
+ ▼
+┌─────────────────────────────────────────────────┐
+│ Job 3: Stop GPU EC2 Runner │
+│ - Wait for the GPU job or queued-job timeout │
+│ - Terminate instance │
+└─────────────────────────────────────────────────┘
+```
+
+## AWS Prerequisites
+
+### Required AWS Resources
+
+You must set up the following in AWS before using GPU runners:
+
+#### 1. IAM Role for OIDC Authentication
+
+Create an IAM role that GitHub Actions can assume via OIDC:
+
+```json
+{
+ "Version": "2012-10-17",
+ "Statement": [
+ {
+ "Effect": "Allow",
+ "Principal": {
+ "Federated": "arn:aws:iam::YOUR_ACCOUNT_ID:oidc-provider/token.actions.githubusercontent.com"
+ },
+ "Action": "sts:AssumeRoleWithWebIdentity",
+ "Condition": {
+ "StringEquals": {
+ "token.actions.githubusercontent.com:aud": "sts.amazonaws.com"
+ },
+ "StringLike": {
+ "token.actions.githubusercontent.com:sub": "repo:YOUR_ORG/llama-stack:*"
+ }
+ }
+ }
+ ]
+}
+```
+
+Attach this policy to the role:
+
+```json
+{
+ "Version": "2012-10-17",
+ "Statement": [
+ {
+ "Effect": "Allow",
+ "Action": [
+ "ec2:RunInstances",
+ "ec2:TerminateInstances",
+ "ec2:DescribeInstances",
+ "ec2:DescribeInstanceStatus",
+ "ec2:CreateTags",
+ "ec2:DescribeImages",
+ "ec2:DescribeSubnets",
+ "ec2:DescribeSecurityGroups"
+ ],
+ "Resource": "*",
+ "Condition": {
+ "StringEquals": {
+ "aws:RequestedRegion": ["us-east-2"]
+ }
+ }
+ }
+ ]
+}
+```
+
+#### 2. VPC and Subnets
+
+You need subnets in `us-east-2` for the first version:
+
+**us-east-2 (Primary)**:
+
+- us-east-2a: `subnet-02d230cffd9385bd4`
+- us-east-2b: `subnet-024298cefa3bedd61`
+- us-east-2c: `subnet-04701a08396b2ed01`
+
+#### 3. Security Groups
+
+Create a security group in `us-east-2` with:
+
+**Inbound Rules**:
+
+- None (runners connect outbound only)
+
+**Outbound Rules**:
+
+- Port 443 (HTTPS): `0.0.0.0/0` - GitHub API, HuggingFace, PyPI
+- Port 80 (HTTP): `0.0.0.0/0` - Package downloads
+
+#### 4. GPU-Enabled AMI
+
+Use a GPU-capable AMI in `us-east-2` with:
+
+- Base OS: RHEL 9
+- NVIDIA drivers
+- CUDA 13.0 runtime
+- Docker with NVIDIA Container Toolkit
+- Python 3.12
+
+The current DevOps AMI is `ami-090a815de2a7461f2`
+(`vllm-rhel9-nvidia-ami-1781031435`). It includes NVIDIA drivers, CUDA 13.0,
+and vLLM 0.22.1 from the image build. The workflow still creates `/tmp/vllm-env`
+and installs the pinned vLLM version there during each run, so the AMI supplies
+the GPU driver/CUDA base while the action controls the Python runtime used by
+the tests.
+
+### GitHub Configuration
+
+#### Secrets
+
+Add these to **Settings > Secrets and variables > Actions > Secrets**:
+
+- `AWS_ROLE_ARN`: ARN of the IAM role for OIDC (e.g., `arn:aws:iam::123456789012:role/GitHubActionsRole`)
+- `RELEASE_PAT`: GitHub Personal Access Token with `repo` scope
+
+#### Variables
+
+Add these to **Settings > Secrets and variables > Actions > Variables**:
+
+**us-east-2**:
+
+- `SUBNET_US_EAST_2A`: `subnet-02d230cffd9385bd4`
+- `SUBNET_US_EAST_2B`: `subnet-024298cefa3bedd61`
+- `SUBNET_US_EAST_2C`: `subnet-04701a08396b2ed01`
+- `AWS_EC2_AMI_US_EAST_2`: `ami-090a815de2a7461f2`
+- `SECURITY_GROUP_ID_US_EAST_2`: `sg-06300447c4a5fbef3`
+
+## Security
+
+### OIDC Authentication
+
+We use **OpenID Connect (OIDC)** to authenticate with AWS instead of long-lived access keys:
+
+- ✅ No static AWS credentials stored in GitHub
+- ✅ Automatic token rotation
+- ✅ Fine-grained permissions per workflow
+- ✅ Better audit trail in AWS CloudTrail
+
+The workflow requests temporary credentials from AWS STS using OIDC tokens from GitHub.
+
+### Test Job Isolation
+
+The test job runs with **no permissions** (`permissions: {}`):
+
+- ✅ Cannot access GitHub secrets
+- ✅ Cannot write to repository
+- ✅ Prevents credential theft from untrusted code
+
+This is critical because the test job runs potentially untrusted code on PRs.
+
+### Cleanup Guarantees
+
+The cleanup job always runs on a hosted runner (`if: always()`):
+
+- ✅ EC2 instance terminated even on failure
+- ✅ EC2 instance terminated even on manual cancellation
+- ✅ EC2 instance terminated if the self-hosted test job never starts
+- ✅ Prevents orphaned instances and cost overruns
+
+The hosted cleanup job polls the GPU test job before termination. If the GPU job
+does not leave the queue within the configured wait period, cleanup proceeds so
+the EC2 runner is not left running indefinitely.
+
+## Instance Types
+
+| Instance | GPU | Memory | vCPUs | Cost/hr | Best For |
+|----------|-----|--------|-------|---------|----------|
+| **g6.2xlarge** | 1x L4 (24GB) | 24 GB | 8 | $0.86 | **gpt-oss:20b (recommended)** |
+| g5.2xlarge | 1x A10G (24GB) | 24 GB | 8 | $1.21 | Alternative for gpt-oss:20b |
+| g6.8xlarge | 1x L4 (24GB) | 24 GB | 32 | $1.38 | More vCPUs if needed |
+| g6e.12xlarge | 4x L40S (192GB) | 192 GB | 48 | $5.44 | 70B+ models (future) |
+
+**Note**: `gpt-oss:20b` ships with MXFP4-quantized MoE weights and is served without an extra vLLM `--quantization` flag in this workflow.
+
+## Cost Estimates
+
+| Scenario | Frequency | Instance | Cost/Run | Monthly Cost |
+|----------|-----------|----------|----------|--------------|
+| Weekly re-recording | 1x/week | g6.2xlarge | $0.43 | **$1.72** |
+| Daily testing | 1x/day | g6.2xlarge | $0.43 | **$12.90** |
+| On-demand (PRs) | 10x/month | g6.2xlarge | $0.43 | **$4.30** |
+| With spot instances | 1x/week | g6.2xlarge (spot) | $0.09-$0.17 | **$0.36-$0.68** |
+
+**Recommendation**: Use on-demand workflow_dispatch only. Add scheduled runs later if needed.
+
+## Troubleshooting
+
+### Workflow fails to launch EC2 instance
+
+**Problem**: "InsufficientInstanceCapacity" error
+
+**Solution**: The workflow automatically tries fallback subnet/AZ placements in `us-east-2`. If all fail:
+
+1. Check AWS Service Health Dashboard for capacity issues
+2. Try a different instance type (g5.2xlarge instead of g6.2xlarge)
+3. Try again during off-peak hours
+
+### vLLM server fails to start
+
+**Problem**: Server doesn't respond to health checks
+
+**Solutions**:
+
+1. Check vLLM logs in workflow output
+2. Verify GPU is detected: look for `nvidia-smi` output
+3. Check CUDA installation: `nvcc --version`
+4. Try a lower `max-model-len` or `gpu-memory-utilization` if startup fails due to memory pressure
+
+### Tests fail but recordings not uploaded
+
+**Problem**: No artifacts in workflow run
+
+**Solutions**:
+
+1. Check if tests actually created recordings
+2. Verify `tests/integration/*/recordings/` directories exist
+3. Check workflow logs for artifact upload errors
+
+### EC2 instance not terminated
+
+**Problem**: Instance still running after workflow completes
+
+**Solutions**:
+
+1. Check stop-gpu-runner job logs for errors
+2. Manually terminate instance via AWS console
+3. Set up CloudWatch alarm for long-running instances (see Phase 2)
+
+### Cost overruns
+
+**Problem**: Unexpected AWS charges
+
+**Solutions**:
+
+1. Check for orphaned instances in AWS EC2 console (filter by tag: `Purpose: vllm-gpu-recording`)
+2. Set up AWS Budget alerts (see `IMPLEMENTATION_PLAN.md` Phase 2)
+3. Review CloudWatch metrics for runner usage
+
+## Performance Tuning
+
+### Reduce Model Load Time
+
+**Current**: ~5 minutes to download gpt-oss:20b
+
+**Options**:
+
+1. **Pre-cache in AMI**: Include model in GPU AMI (~0 min load time)
+2. **EBS snapshot**: Attach pre-loaded model volume (~1 min)
+3. **S3 cache**: Download from S3 instead of HuggingFace (~2 min)
+
+See `IMPLEMENTATION_PLAN.md` Task #5 for implementation.
+
+### Reduce Costs with Spot Instances
+
+**Current**: $0.43 per run (on-demand)
+**With spot**: $0.09-$0.17 per run (60-90% savings)
+
+Spot instances can be interrupted, but for test workloads this is acceptable.
+
+See `IMPLEMENTATION_PLAN.md` Task #3 for implementation.
+
+## Adding New Models
+
+To add a new model for GPU testing, first add a model input to
+`.github/workflows/record-vllm-gpu-tests.yml`, then wire that value through
+`setup-vllm-gpu`.
+
+After that, add the new setup to the test matrix:
+
+ ```json
+ "gpu-vllm": [
+ {"suite": "base", "setup": "vllm-gpu-gpt-oss"},
+ {"suite": "base", "setup": "vllm-gpu-your-model"}
+ ]
+ ```
+
+Create the setup in `tests/integration/suites.py`:
+
+ ```python
+ "vllm-gpu-your-model": Setup(
+ name="vllm-gpu",
+ defaults={"text_model": "vllm/your-model"},
+ )
+ ```
+
+Choose an instance type:
+
+- < 20B params: `g6.2xlarge` (24GB)
+- 20-70B params: `g6.8xlarge` or `g6e.12xlarge` (192GB)
+- 70B+ params: `g6e.12xlarge` (192GB) or `g6e.48xlarge` (384GB)
+
+## Monitoring
+
+### CloudWatch Dashboards
+
+Create a dashboard to track:
+
+- Total GPU runner costs (daily/weekly/monthly)
+- Instance launch success rate
+- Average test duration
+- Failures by reason
+
+See `IMPLEMENTATION_PLAN.md` Task #4 for setup.
+
+### Cost Allocation Tags
+
+All EC2 instances are tagged with:
+
+- `Project`: llama-stack
+- `Purpose`: vllm-gpu-recording
+- `Model`: gpt-oss:20b
+- `GitHubRepository`: your-org/llama-stack
+- `GitHubRunId`: 12345
+
+Enable cost allocation in **AWS Billing > Cost Allocation Tags** to track costs by tag.
+
+## References
+
+- **Implementation Plan**: `IMPLEMENTATION_PLAN.md`
+- **AWS EC2 Instance Types**:
+- **vLLM Documentation**:
+- **GitHub OIDC**:
+
+## Support
+
+For issues or questions:
+
+- Create an issue in the repository
+- Check existing issues for similar problems
+- Review troubleshooting section above
+- Contact: Charles Doern (@cdoern)
diff --git a/docs/sidebars.ts b/docs/sidebars.ts
index 04d11c82ab2..6a3429a09ea 100644
--- a/docs/sidebars.ts
+++ b/docs/sidebars.ts
@@ -252,6 +252,7 @@ const sidebars: SidebarsConfig = {
'providers/tool_runtime/remote_bing-search',
'providers/tool_runtime/remote_brave-search',
'providers/tool_runtime/remote_model-context-protocol',
+ 'providers/tool_runtime/remote_nimble-search',
'providers/tool_runtime/remote_tavily-search',
'providers/tool_runtime/remote_wolfram-alpha'
],
diff --git a/docs/src/pages/index.js b/docs/src/pages/index.js
index 6b38a45e0f4..9f3b04bb38a 100644
--- a/docs/src/pages/index.js
+++ b/docs/src/pages/index.js
@@ -885,7 +885,7 @@ function Bottom() {
GitHub
-
+
Discord
diff --git a/docs/static/anthropic-coverage.json b/docs/static/anthropic-coverage.json
index 833d3d68a3c..657993c798d 100644
--- a/docs/static/anthropic-coverage.json
+++ b/docs/static/anthropic-coverage.json
@@ -87,6 +87,7 @@
{
"property": "POST.requestBody.content.application/json.properties.requests.items.properties.params.properties.tool_choice",
"details": [
+ "Union variants added: 4",
"Union variants removed: 4"
]
},
@@ -239,6 +240,7 @@
{
"property": "POST.requestBody.content.application/json.properties.tool_choice",
"details": [
+ "Union variants added: 4",
"Union variants removed: 4"
]
},
diff --git a/docs/static/deprecated-ogx-spec.yaml b/docs/static/deprecated-ogx-spec.yaml
index b76b1863d4b..82c9212d6a4 100644
--- a/docs/static/deprecated-ogx-spec.yaml
+++ b/docs/static/deprecated-ogx-spec.yaml
@@ -1128,7 +1128,7 @@ components:
tool_calls:
description: The tool calls of the delta.
items:
- $ref: '#/components/schemas/ChatCompletionMessageToolCall'
+ $ref: '#/components/schemas/ChoiceDeltaToolCall'
title: Tool Calls
type: array
nullable: true
@@ -2619,25 +2619,25 @@ components:
title: OpenAIFileObject
description: OpenAI File object as defined in the OpenAI Files API.
ExpiresAfter:
+ description: Control expiration of uploaded files.
properties:
anchor:
- type: string
- title: Anchor
description: The anchor point for expiration, must be 'created_at'.
+ title: Anchor
+ type: string
enum:
- created_at
seconds:
- type: integer
- maximum: 2592000.0
- minimum: 3600.0
- title: Seconds
description: Seconds until expiration, between 3600 (1 hour) and 2592000 (30 days).
- type: object
+ maximum: 2592000
+ minimum: 3600
+ title: Seconds
+ type: integer
required:
- anchor
- seconds
title: ExpiresAfter
- description: Control expiration of uploaded files.
+ type: object
OpenAIFileDeleteResponse:
properties:
id:
@@ -3350,6 +3350,10 @@ components:
store:
type: boolean
title: Store
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
input:
items:
$ref: '#/components/schemas/OpenAIResponseMessageOutputUnion'
@@ -3445,6 +3449,7 @@ components:
- medium
- high
- type: 'null'
+ default: medium
type: object
title: OpenAIResponseText
description: Text response configuration for OpenAI responses.
@@ -3763,6 +3768,10 @@ components:
store:
type: boolean
title: Store
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
type: object
required:
- created_at
@@ -6776,6 +6785,72 @@ components:
- data
title: ListConnectorsResponse
description: Response containing a list of configured connectors
+ ListSkillVersionsResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/SkillVersion'
+ type: array
+ title: Data
+ description: List of skill version objects
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more results
+ default: false
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first item in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last item in the list
+ type: object
+ required:
+ - data
+ title: ListSkillVersionsResponse
+ description: Response from listing skill versions.
+ ListSkillsResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/Skill'
+ type: array
+ title: Data
+ description: List of skill objects
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more results
+ default: false
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first item in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last item in the list
+ type: object
+ required:
+ - data
+ title: ListSkillsResponse
+ description: Response from listing skills.
ListToolsResponse:
properties:
data:
@@ -7971,6 +8046,146 @@ components:
- version
title: SetDefaultVersionBodyRequest
description: Request body model for setting the default version of a prompt.
+ Skill:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: Unique identifier for the skill
+ created_at:
+ type: integer
+ title: Created At
+ description: Unix timestamp when the skill was created
+ default_version:
+ type: string
+ title: Default Version
+ description: Version used when no version is specified
+ default: '1'
+ description:
+ type: string
+ title: Description
+ description: Description of what the skill does
+ latest_version:
+ type: string
+ title: Latest Version
+ description: Most recently uploaded version number
+ default: '1'
+ name:
+ type: string
+ title: Name
+ description: Human-readable name from SKILL.md frontmatter
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill
+ type: object
+ required:
+ - id
+ - created_at
+ - description
+ - name
+ title: Skill
+ description: A skill resource. Matches OpenAI Skill wire format.
+ SkillDeleteResponse:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: ID of the deleted skill
+ deleted:
+ type: boolean
+ title: Deleted
+ description: Whether the skill was successfully deleted
+ default: true
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.deleted
+ type: object
+ required:
+ - id
+ title: SkillDeleteResponse
+ description: Response from deleting a skill. Matches OpenAI DeletedSkill wire format.
+ SkillUpdateRequest:
+ properties:
+ default_version:
+ type: string
+ title: Default Version
+ description: Version number to set as the default
+ type: object
+ required:
+ - default_version
+ title: SkillUpdateRequest
+ description: Request to update a skill's default version.
+ SkillVersion:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: Unique identifier for this version
+ created_at:
+ type: integer
+ title: Created At
+ description: Unix timestamp when this version was created
+ description:
+ type: string
+ title: Description
+ description: Description of the skill version
+ name:
+ type: string
+ title: Name
+ description: Name of the skill version
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.version
+ skill_id:
+ type: string
+ title: Skill Id
+ description: ID of the parent skill
+ version:
+ type: string
+ title: Version
+ description: Version number as a string
+ type: object
+ required:
+ - id
+ - created_at
+ - description
+ - name
+ - skill_id
+ - version
+ title: SkillVersion
+ description: A specific version of a skill. Matches OpenAI SkillVersion wire format.
+ SkillVersionDeleteResponse:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: ID of the deleted skill
+ deleted:
+ type: boolean
+ title: Deleted
+ description: Whether the version was successfully deleted
+ default: true
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.version.deleted
+ version:
+ type: string
+ title: Version
+ description: Version that was deleted
+ type: object
+ required:
+ - id
+ - version
+ title: SkillVersionDeleteResponse
+ description: Response from deleting a skill version. Matches OpenAI DeletedSkillVersion wire format.
UpdatePromptBodyRequest:
properties:
prompt:
@@ -8857,6 +9072,7 @@ components:
- batches
- vector_io
- tool_runtime
+ - container_runtime
- models
- vector_stores
- tool_groups
@@ -8865,8 +9081,10 @@ components:
- prompts
- conversations
- connectors
+ - containers
- messages
- interactions
+ - skills
- inspect
- admin
title: Api
@@ -9871,87 +10089,797 @@ components:
- dialog
title: DialogType
type: object
- ConversationMessage:
- description: OpenAI-compatible message item for conversations.
+ ContainerExpiresAfter:
+ description: |-
+ Control expiration of a container.
+
+ Anchored on ``last_active_at`` (each shell execution or file operation
+ refreshes the anchor). Operator-set bounds protect the host from
+ long-lived sandboxes.
properties:
- id:
- description: unique identifier for this message
- title: Id
- type: string
- content:
- description: message content
- items:
- additionalProperties: true
- type: object
- title: Content
- type: array
- role:
- description: message role
- title: Role
+ anchor:
+ description: The anchor point for expiration. Must be 'last_active_at'.
+ title: Anchor
type: string
- status:
- description: message status
- title: Status
+ enum:
+ - last_active_at
+ minutes:
+ description: Minutes of inactivity after the anchor before the container expires.
+ maximum: 1440
+ minimum: 1
+ title: Minutes
+ type: integer
+ required:
+ - minutes
+ title: ContainerExpiresAfter
+ type: object
+ NetworkCredential:
+ description: |-
+ A named credential available to outbound network calls.
+
+ The ``value`` should be a secret reference (e.g. ``${env.MY_SECRET}``)
+ in operator-supplied configuration, never a raw secret in a request body.
+ properties:
+ name:
+ description: Logical name used by the container to look up the credential.
+ title: Name
type: string
- type:
- title: Type
+ value:
+ description: Secret reference or literal value to be injected into the container.
+ format: password
+ title: Value
type: string
- enum:
- - message
- object:
- title: Object
+ writeOnly: true
+ required:
+ - name
+ - value
+ title: NetworkCredential
+ type: object
+ NetworkDomainCredential:
+ description: Bind a ``NetworkCredential`` to a specific outbound domain.
+ properties:
+ domain:
+ description: Fully-qualified domain name to which the credential applies.
+ title: Domain
type: string
- enum:
- - message
+ credential:
+ $ref: '#/components/schemas/NetworkCredential'
+ description: Credential injected on outbound calls to this domain.
required:
- - id
- - content
- - role
- - status
- title: ConversationMessage
+ - domain
+ - credential
+ title: NetworkDomainCredential
type: object
- ConversationItemCreateRequest:
- description: Request body for creating conversation items.
+ NetworkPolicyMode:
+ description: Egress policy mode applied to a container's outbound network.
+ enum:
+ - deny
+ - allow_list
+ - allow_all
+ title: NetworkPolicyMode
+ type: string
+ NetworkPolicy:
+ description: |-
+ Operator-set egress policy for a container.
+
+ A NetworkPolicy is the *upper bound* — request-supplied
+ ``NetworkPolicyExtended`` values may only narrow this policy.
properties:
- items:
- description: Items to include in the conversation context. You may add up to 20 items at a time.
+ mode:
+ $ref: '#/components/schemas/NetworkPolicyMode'
+ default: deny
+ description: Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.
+ allow_domains:
+ description: Domains permitted for outbound traffic. Used when mode is 'allow_list'.
items:
- discriminator:
- mapping:
- compaction: '#/components/schemas/OpenAIResponseCompaction'
- file_search_call: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
- function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
- function_call_output: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
- mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
- mcp_approval_response: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
- mcp_call: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
- mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
- message: '#/components/schemas/OpenAIResponseMessage'
- reasoning: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
- web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
- propertyName: type
- oneOf:
- - $ref: '#/components/schemas/OpenAIResponseMessage'
- title: OpenAIResponseMessage
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
- title: OpenAIResponseOutputMessageWebSearchToolCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
- title: OpenAIResponseOutputMessageFileSearchToolCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
- title: OpenAIResponseOutputMessageFunctionToolCall
- - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
- title: OpenAIResponseInputFunctionToolCallOutput
- - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
- title: OpenAIResponseMCPApprovalRequest
- - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
- title: OpenAIResponseMCPApprovalResponse
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
- title: OpenAIResponseOutputMessageMCPCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
- title: OpenAIResponseOutputMessageMCPListTools
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
- title: OpenAIResponseOutputMessageReasoningItem
- - $ref: '#/components/schemas/OpenAIResponseCompaction'
+ type: string
+ title: Allow Domains
+ type: array
+ deny_domains:
+ description: Domains explicitly blocked. Takes precedence over 'allow_domains'.
+ items:
+ type: string
+ title: Deny Domains
+ type: array
+ title: NetworkPolicy
+ type: object
+ NetworkPolicyExtended:
+ description: |-
+ Request-layer extension of an operator NetworkPolicy.
+
+ The request may add domain credentials and narrow allow/deny lists, but
+ cannot expand the operator default — enforcement is performed at the API
+ layer; see issue #5892 task 8.
+ properties:
+ mode:
+ $ref: '#/components/schemas/NetworkPolicyMode'
+ default: deny
+ description: Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.
+ allow_domains:
+ description: Domains permitted for outbound traffic. Used when mode is 'allow_list'.
+ items:
+ type: string
+ title: Allow Domains
+ type: array
+ deny_domains:
+ description: Domains explicitly blocked. Takes precedence over 'allow_domains'.
+ items:
+ type: string
+ title: Deny Domains
+ type: array
+ domain_credentials:
+ description: Per-domain credentials injected on outbound calls from this container.
+ items:
+ $ref: '#/components/schemas/NetworkDomainCredential'
+ title: Domain Credentials
+ type: array
+ title: NetworkPolicyExtended
+ type: object
+ ContainerStatus:
+ description: Lifecycle status of a container.
+ enum:
+ - active
+ - expired
+ title: ContainerStatus
+ type: string
+ Container:
+ description: |-
+ A sandboxed execution environment.
+
+ Mirrors the OpenAI Containers API resource with OGX-specific extensions
+ for network policy and image selection.
+ properties:
+ id:
+ description: Identifier for the container.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container'.
+ title: Object
+ type: string
+ enum:
+ - container
+ created_at:
+ description: Unix timestamp (in seconds) for when the container was created.
+ title: Created At
+ type: integer
+ status:
+ $ref: '#/components/schemas/ContainerStatus'
+ description: Current lifecycle status.
+ last_active_at:
+ description: Unix timestamp (in seconds) of the last operation performed against this container.
+ title: Last Active At
+ type: integer
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Human-readable name for the container.
+ nullable: true
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration settings.
+ nullable: true
+ title: ContainerExpiresAfter
+ image:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Container image used to run the sandbox. May be operator-locked.
+ nullable: true
+ network_policy:
+ anyOf:
+ - $ref: '#/components/schemas/NetworkPolicy'
+ title: NetworkPolicy
+ - type: 'null'
+ description: Effective network policy after layering operator defaults with request extensions.
+ nullable: true
+ title: NetworkPolicy
+ required:
+ - id
+ - created_at
+ - status
+ - last_active_at
+ title: Container
+ type: object
+ ContainerCreateRequest:
+ description: Request body for ``POST /containers``.
+ properties:
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Human-readable name for the container.
+ nullable: true
+ file_ids:
+ description: Files (from the Files API) to seed into the container at /mnt/data/.
+ items:
+ type: string
+ title: File Ids
+ type: array
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration settings.
+ nullable: true
+ title: ContainerExpiresAfter
+ image:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Requested container image. The operator policy may pin or reject this value.
+ nullable: true
+ network_policy:
+ anyOf:
+ - $ref: '#/components/schemas/NetworkPolicyExtended'
+ title: NetworkPolicyExtended
+ - type: 'null'
+ description: Request-supplied network policy extension. Must be a subset of the operator default.
+ nullable: true
+ title: NetworkPolicyExtended
+ title: ContainerCreateRequest
+ type: object
+ ListContainersRequest:
+ description: Query parameters for ``GET /containers``.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination. Returns containers after this ID.
+ nullable: true
+ limit:
+ anyOf:
+ - maximum: 100
+ minimum: 1
+ type: integer
+ - type: 'null'
+ default: 20
+ description: Maximum number of containers to return (1-100).
+ order:
+ anyOf:
+ - $ref: '#/components/schemas/Order'
+ title: Order
+ - type: 'null'
+ default: desc
+ description: Sort order by created_at timestamp ('asc' or 'desc').
+ title: Order
+ title: ListContainersRequest
+ type: object
+ ListContainersResponse:
+ description: Response for ``GET /containers``.
+ properties:
+ object:
+ description: The object type, which is always 'list'.
+ title: Object
+ type: string
+ enum:
+ - list
+ data:
+ description: The list of containers.
+ items:
+ $ref: '#/components/schemas/Container'
+ title: Data
+ type: array
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first container in the page.
+ nullable: true
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last container in the page.
+ nullable: true
+ has_more:
+ description: Whether more containers exist beyond this page.
+ title: Has More
+ type: boolean
+ required:
+ - data
+ - has_more
+ title: ListContainersResponse
+ type: object
+ GetContainerRequest:
+ properties:
+ container_id:
+ description: The ID of the container to retrieve.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: GetContainerRequest
+ type: object
+ DeleteContainerRequest:
+ properties:
+ container_id:
+ description: The ID of the container to delete.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: DeleteContainerRequest
+ type: object
+ ContainerDeleteResponse:
+ description: Response for ``DELETE /containers/{container_id}``.
+ properties:
+ id:
+ description: The container identifier that was deleted.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container'.
+ title: Object
+ type: string
+ enum:
+ - container
+ deleted:
+ description: Whether the container was successfully deleted.
+ title: Deleted
+ type: boolean
+ required:
+ - id
+ - deleted
+ title: ContainerDeleteResponse
+ type: object
+ ContainerFileSource:
+ description: Origin of a file inside a container.
+ enum:
+ - user
+ - assistant
+ title: ContainerFileSource
+ type: string
+ ContainerFile:
+ description: A file present inside a container's filesystem.
+ properties:
+ id:
+ description: Identifier of the container file.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container.file'.
+ title: Object
+ type: string
+ enum:
+ - container.file
+ container_id:
+ description: ID of the container holding the file.
+ title: Container Id
+ type: string
+ created_at:
+ description: Unix timestamp (in seconds) when the file was created.
+ title: Created At
+ type: integer
+ bytes:
+ description: Size of the file in bytes.
+ title: Bytes
+ type: integer
+ path:
+ description: Absolute path to the file inside the container.
+ title: Path
+ type: string
+ source:
+ $ref: '#/components/schemas/ContainerFileSource'
+ description: Whether the file was supplied by the user or written by the model.
+ required:
+ - id
+ - container_id
+ - created_at
+ - bytes
+ - path
+ - source
+ title: ContainerFile
+ type: object
+ UploadContainerFileRequest:
+ description: |-
+ Path parameters for ``POST /containers/{container_id}/files``.
+
+ The file content itself is supplied as a multipart upload and not part of
+ this Pydantic body; see ``fastapi_routes.py``.
+ properties:
+ container_id:
+ description: The ID of the container to upload into.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: UploadContainerFileRequest
+ type: object
+ ListContainerFilesRequest:
+ properties:
+ container_id:
+ description: The ID of the container whose files should be listed.
+ title: Container Id
+ type: string
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination.
+ nullable: true
+ limit:
+ anyOf:
+ - maximum: 100
+ minimum: 1
+ type: integer
+ - type: 'null'
+ default: 20
+ description: Maximum number of files to return (1-100).
+ order:
+ anyOf:
+ - $ref: '#/components/schemas/Order'
+ title: Order
+ - type: 'null'
+ default: desc
+ description: Sort order by created_at timestamp.
+ title: Order
+ required:
+ - container_id
+ title: ListContainerFilesRequest
+ type: object
+ ListContainerFilesResponse:
+ properties:
+ object:
+ description: The object type, which is always 'list'.
+ title: Object
+ type: string
+ enum:
+ - list
+ data:
+ description: The list of files in the container.
+ items:
+ $ref: '#/components/schemas/ContainerFile'
+ title: Data
+ type: array
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first file in the page.
+ nullable: true
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last file in the page.
+ nullable: true
+ has_more:
+ description: Whether more files exist beyond this page.
+ title: Has More
+ type: boolean
+ required:
+ - data
+ - has_more
+ title: ListContainerFilesResponse
+ type: object
+ GetContainerFileRequest:
+ properties:
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to retrieve.
+ title: File Id
+ type: string
+ required:
+ - container_id
+ - file_id
+ title: GetContainerFileRequest
+ type: object
+ GetContainerFileContentRequest:
+ properties:
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to download.
+ title: File Id
+ type: string
+ required:
+ - container_id
+ - file_id
+ title: GetContainerFileContentRequest
+ type: object
+ DeleteContainerFileRequest:
+ properties:
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to delete.
+ title: File Id
+ type: string
+ required:
+ - container_id
+ - file_id
+ title: DeleteContainerFileRequest
+ type: object
+ ContainerFileDeleteResponse:
+ properties:
+ id:
+ description: The container file identifier that was deleted.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container.file'.
+ title: Object
+ type: string
+ enum:
+ - container.file
+ deleted:
+ description: Whether the file was successfully deleted.
+ title: Deleted
+ type: boolean
+ required:
+ - id
+ - deleted
+ title: ContainerFileDeleteResponse
+ type: object
+ ShellEnvironmentContainerAuto:
+ description: |-
+ Provider-managed container environment.
+
+ The provider lazily creates and reuses a container for the calling
+ response chain. Useful when the caller does not need to persist or
+ reference the container across responses.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - container_auto
+ image:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional preferred container image.
+ nullable: true
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration for the auto-created container.
+ nullable: true
+ title: ContainerExpiresAfter
+ title: ShellEnvironmentContainerAuto
+ type: object
+ ShellEnvironmentContainerReference:
+ description: Reference an existing container by ID.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - container_reference
+ container_id:
+ description: The ID of an existing container to execute inside.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: ShellEnvironmentContainerReference
+ type: object
+ ShellEnvironmentLocal:
+ description: |-
+ Local (non-container) execution mode.
+
+ Only available when the operator has explicitly enabled local mode in
+ the ContainerRuntime provider configuration.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - local
+ working_directory:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional working directory for local execution.
+ nullable: true
+ title: ShellEnvironmentLocal
+ type: object
+ ShellOutcomeSuccess:
+ description: Process exited cleanly with status 0.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - success
+ exit_code:
+ description: Process exit code (always 0 for success).
+ title: Exit Code
+ type: integer
+ enum:
+ - 0
+ title: ShellOutcomeSuccess
+ type: object
+ ShellOutcomeFailure:
+ description: Process exited with a non-zero status.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - failure
+ exit_code:
+ description: Process exit code.
+ title: Exit Code
+ type: integer
+ reason:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Human-readable failure reason, if known.
+ nullable: true
+ required:
+ - exit_code
+ title: ShellOutcomeFailure
+ type: object
+ ShellOutcomeTimeout:
+ description: Process was terminated for exceeding its time budget.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - timeout
+ elapsed_seconds:
+ description: Wall-clock seconds elapsed before termination.
+ title: Elapsed Seconds
+ type: number
+ required:
+ - elapsed_seconds
+ title: ShellOutcomeTimeout
+ type: object
+ ShellCallOutput:
+ description: |-
+ Captured output of a single shell execution.
+
+ Consumed by the Responses provider to construct ``ShellCallOutputItem``
+ entries on the output stream.
+ properties:
+ stdout:
+ description: UTF-8 decoded standard output (truncated by the runtime if oversized).
+ title: Stdout
+ type: string
+ stderr:
+ description: UTF-8 decoded standard error (truncated by the runtime if oversized).
+ title: Stderr
+ type: string
+ outcome:
+ description: How the shell process terminated.
+ discriminator:
+ mapping:
+ failure: '#/components/schemas/ShellOutcomeFailure'
+ success: '#/components/schemas/ShellOutcomeSuccess'
+ timeout: '#/components/schemas/ShellOutcomeTimeout'
+ propertyName: type
+ oneOf:
+ - $ref: '#/components/schemas/ShellOutcomeSuccess'
+ title: ShellOutcomeSuccess
+ - $ref: '#/components/schemas/ShellOutcomeFailure'
+ title: ShellOutcomeFailure
+ - $ref: '#/components/schemas/ShellOutcomeTimeout'
+ title: ShellOutcomeTimeout
+ title: ShellOutcomeSuccess | ShellOutcomeFailure | ShellOutcomeTimeout
+ duration_ms:
+ description: Wall-clock duration of the shell call in milliseconds.
+ minimum: 0
+ title: Duration Ms
+ type: integer
+ container_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the container the call executed in, when applicable. Null for local mode.
+ nullable: true
+ required:
+ - stdout
+ - stderr
+ - outcome
+ - duration_ms
+ title: ShellCallOutput
+ type: object
+ ConversationMessage:
+ description: OpenAI-compatible message item for conversations.
+ properties:
+ id:
+ description: unique identifier for this message
+ title: Id
+ type: string
+ content:
+ description: message content
+ items:
+ additionalProperties: true
+ type: object
+ title: Content
+ type: array
+ role:
+ description: message role
+ title: Role
+ type: string
+ status:
+ description: message status
+ title: Status
+ type: string
+ type:
+ title: Type
+ type: string
+ enum:
+ - message
+ object:
+ title: Object
+ type: string
+ enum:
+ - message
+ required:
+ - id
+ - content
+ - role
+ - status
+ title: ConversationMessage
+ type: object
+ ConversationItemCreateRequest:
+ description: Request body for creating conversation items.
+ properties:
+ items:
+ description: Items to include in the conversation context. You may add up to 20 items at a time.
+ items:
+ discriminator:
+ mapping:
+ compaction: '#/components/schemas/OpenAIResponseCompaction'
+ file_search_call: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
+ function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
+ function_call_output: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
+ mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
+ mcp_approval_response: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
+ mcp_call: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
+ mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
+ message: '#/components/schemas/OpenAIResponseMessage'
+ reasoning: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
+ web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
+ propertyName: type
+ oneOf:
+ - $ref: '#/components/schemas/OpenAIResponseMessage'
+ title: OpenAIResponseMessage
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
+ title: OpenAIResponseOutputMessageWebSearchToolCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
+ title: OpenAIResponseOutputMessageFileSearchToolCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
+ title: OpenAIResponseOutputMessageFunctionToolCall
+ - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
+ title: OpenAIResponseInputFunctionToolCallOutput
+ - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
+ title: OpenAIResponseMCPApprovalRequest
+ - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
+ title: OpenAIResponseMCPApprovalResponse
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
+ title: OpenAIResponseOutputMessageMCPCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
+ title: OpenAIResponseOutputMessageMCPListTools
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
+ title: OpenAIResponseOutputMessageReasoningItem
+ - $ref: '#/components/schemas/OpenAIResponseCompaction'
title: OpenAIResponseCompaction
title: OpenAIResponseMessage | ... (11 variants)
maxItems: 20
@@ -10265,6 +11193,68 @@ components:
- prompt_id
title: DeletePromptRequest
type: object
+ SkillVersionCreateRequest:
+ description: Request to create a new skill version. Matches OpenAI VersionCreateParams.
+ properties:
+ default:
+ type: boolean
+ default: false
+ description: Whether to set this version as the default
+ title: Default
+ title: SkillVersionCreateRequest
+ type: object
+ ListSkillsRequest:
+ description: Request parameters for listing skills.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of results
+ maximum: 100
+ minimum: 1
+ title: Limit
+ type: integer
+ order:
+ default: desc
+ description: Sort order by created_at
+ enum:
+ - asc
+ - desc
+ title: Order
+ type: string
+ title: ListSkillsRequest
+ type: object
+ ListSkillVersionsRequest:
+ description: Request parameters for listing skill versions.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of results
+ maximum: 100
+ minimum: 1
+ title: Limit
+ type: integer
+ order:
+ default: desc
+ description: Sort order by version
+ enum:
+ - asc
+ - desc
+ title: Order
+ type: string
+ title: ListSkillVersionsRequest
+ type: object
OpenAIResponseMessageOutputUnion:
anyOf:
- oneOf:
@@ -10398,6 +11388,43 @@ components:
- type
- custom
description: A call to a custom tool created by the model.
+ ChoiceDeltaToolCall:
+ properties:
+ id:
+ anyOf:
+ - type: string
+ description: Unique identifier for the tool call.
+ - type: 'null'
+ description: Unique identifier for the tool call.
+ type:
+ anyOf:
+ - type: string
+ description: Must be 'function' to identify this as a function call.
+ enum:
+ - function
+ - type: 'null'
+ description: Must be 'function' to identify this as a function call.
+ function:
+ anyOf:
+ - properties:
+ name:
+ type: string
+ title: Name
+ description: Name of the function to call.
+ arguments:
+ type: string
+ title: Arguments
+ description: Arguments to pass to the function as a JSON string.
+ type: object
+ - type: 'null'
+ description: Function call details.
+ index:
+ type: integer
+ description: The index of the tool call being streamed.
+ type: object
+ description: A tool call delta in a streaming chat completion chunk.
+ required:
+ - index
responses:
BadRequest400:
description: The request was invalid or malformed
@@ -10496,6 +11523,8 @@ tags:
- description: Tool listing and management.
name: Tools
x-displayName: Tools
+- description: OpenAI-compatible vector store management and search.
+ name: Vector Stores
- description: ''
name: VectorIO
- description: OpenAI Responses API for agent orchestration with tool use, multi-turn conversations, and background processing.
@@ -10522,6 +11551,7 @@ x-tagGroups:
- ToolGroups
- ToolRuntime
- Tools
+ - Vector Stores
- VectorIO
security:
- Default: []
diff --git a/docs/static/experimental-ogx-spec.yaml b/docs/static/experimental-ogx-spec.yaml
index de40ef5fb28..be958577080 100644
--- a/docs/static/experimental-ogx-spec.yaml
+++ b/docs/static/experimental-ogx-spec.yaml
@@ -458,6 +458,441 @@ paths:
input="What is the capital of France?",
)
print(interaction.outputs[0].text)
+ /v1alpha/skills:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/ListSkillsResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: List skills
+ description: List all skills.
+ operationId: list_skills_v1alpha_skills_get
+ parameters:
+ - name: after
+ in: query
+ required: false
+ schema:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ title: After
+ description: Cursor for pagination
+ - name: limit
+ in: query
+ required: false
+ schema:
+ type: integer
+ description: Maximum number of results
+ default: 20
+ title: Limit
+ description: Maximum number of results
+ - name: order
+ in: query
+ required: false
+ schema:
+ enum:
+ - asc
+ - desc
+ type: string
+ description: Sort order by created_at
+ default: desc
+ title: Order
+ description: Sort order by created_at
+ post:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/Skill'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Create skill
+ description: Create a skill by uploading a zip bundle containing a SKILL.md manifest.
+ operationId: create_skill_v1alpha_skills_post
+ requestBody:
+ required: true
+ content:
+ multipart/form-data:
+ schema:
+ $ref: '#/components/schemas/Body_create_skill_v1alpha_skills_post'
+ /v1alpha/skills/{skill_id}:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/Skill'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Get skill
+ description: Get metadata for a specific skill.
+ operationId: get_skill_v1alpha_skills__skill_id__get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ post:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/Skill'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Update skill
+ description: Update a skill's default version.
+ operationId: update_skill_v1alpha_skills__skill_id__post
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ requestBody:
+ required: true
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillUpdateRequest'
+ delete:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillDeleteResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Delete skill
+ description: Delete a skill and all its versions.
+ operationId: delete_skill_v1alpha_skills__skill_id__delete
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ /v1alpha/skills/{skill_id}/content:
+ get:
+ responses:
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ '204':
+ description: The skill bundle as a zip archive.
+ tags:
+ - Skills
+ summary: Get skill content
+ description: Download the default version's zip bundle.
+ operationId: get_skill_content_v1alpha_skills__skill_id__content_get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ /v1alpha/skills/{skill_id}/versions:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/ListSkillVersionsResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: List skill versions
+ description: List all versions of a skill.
+ operationId: list_skill_versions_v1alpha_skills__skill_id__versions_get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: after
+ in: query
+ required: false
+ schema:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ title: After
+ description: Cursor for pagination
+ - name: limit
+ in: query
+ required: false
+ schema:
+ type: integer
+ description: Maximum number of results
+ default: 20
+ title: Limit
+ description: Maximum number of results
+ - name: order
+ in: query
+ required: false
+ schema:
+ enum:
+ - asc
+ - desc
+ type: string
+ description: Sort order by version
+ default: desc
+ title: Order
+ description: Sort order by version
+ post:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillVersion'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Create skill version
+ description: Upload a new version of a skill.
+ operationId: create_skill_version_v1alpha_skills__skill_id__versions_post
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ requestBody:
+ required: true
+ content:
+ multipart/form-data:
+ schema:
+ $ref: '#/components/schemas/Body_create_skill_version_v1alpha_skills__skill_id__versions_post'
+ /v1alpha/skills/{skill_id}/versions/{version}:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillVersion'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Get skill version
+ description: Get metadata for a specific skill version.
+ operationId: get_skill_version_v1alpha_skills__skill_id__versions__version__get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: version
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Version
+ delete:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillVersionDeleteResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Delete skill version
+ description: Delete a specific version of a skill.
+ operationId: delete_skill_version_v1alpha_skills__skill_id__versions__version__delete
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: version
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Version
+ /v1alpha/skills/{skill_id}/versions/{version}/content:
+ get:
+ responses:
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ '204':
+ description: The skill bundle as a zip archive.
+ tags:
+ - Skills
+ summary: Get skill version content
+ description: Download a specific version's zip bundle.
+ operationId: get_skill_version_content_v1alpha_skills__skill_id__versions__version__content_get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: version
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Version
components:
schemas:
Error:
@@ -1573,7 +2008,7 @@ components:
tool_calls:
description: The tool calls of the delta.
items:
- $ref: '#/components/schemas/ChatCompletionMessageToolCall'
+ $ref: '#/components/schemas/ChoiceDeltaToolCall'
title: Tool Calls
type: array
nullable: true
@@ -3064,25 +3499,25 @@ components:
title: OpenAIFileObject
description: OpenAI File object as defined in the OpenAI Files API.
ExpiresAfter:
+ description: Control expiration of uploaded files.
properties:
anchor:
- type: string
- title: Anchor
description: The anchor point for expiration, must be 'created_at'.
+ title: Anchor
+ type: string
enum:
- created_at
seconds:
- type: integer
- maximum: 2592000.0
- minimum: 3600.0
- title: Seconds
description: Seconds until expiration, between 3600 (1 hour) and 2592000 (30 days).
- type: object
+ maximum: 2592000
+ minimum: 3600
+ title: Seconds
+ type: integer
required:
- anchor
- seconds
title: ExpiresAfter
- description: Control expiration of uploaded files.
+ type: object
OpenAIFileDeleteResponse:
properties:
id:
@@ -3795,6 +4230,10 @@ components:
store:
type: boolean
title: Store
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
input:
items:
$ref: '#/components/schemas/OpenAIResponseMessageOutputUnion'
@@ -3890,6 +4329,7 @@ components:
- medium
- high
- type: 'null'
+ default: medium
type: object
title: OpenAIResponseText
description: Text response configuration for OpenAI responses.
@@ -4208,6 +4648,10 @@ components:
store:
type: boolean
title: Store
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
type: object
required:
- created_at
@@ -6835,6 +7279,33 @@ components:
Represents token usage details including input tokens, output tokens, a
breakdown of output tokens, and the total tokens used. Only populated on
batches created after September 7, 2025.
+ Body_create_skill_v1alpha_skills_post:
+ properties:
+ file:
+ type: string
+ title: File
+ description: Zip archive containing the skill bundle.
+ format: binary
+ type: object
+ required:
+ - file
+ title: Body_create_skill_v1alpha_skills_post
+ Body_create_skill_version_v1alpha_skills__skill_id__versions_post:
+ properties:
+ file:
+ type: string
+ title: File
+ description: Zip archive containing the skill bundle.
+ format: binary
+ default:
+ type: boolean
+ title: Default
+ description: Whether to set this version as the default.
+ default: false
+ type: object
+ required:
+ - file
+ title: Body_create_skill_version_v1alpha_skills__skill_id__versions_post
Body_process_file_v1alpha_file_processors_process_post:
properties:
file:
@@ -7629,6 +8100,72 @@ components:
- data
title: ListConnectorsResponse
description: Response containing a list of configured connectors
+ ListSkillVersionsResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/SkillVersion'
+ type: array
+ title: Data
+ description: List of skill version objects
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more results
+ default: false
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first item in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last item in the list
+ type: object
+ required:
+ - data
+ title: ListSkillVersionsResponse
+ description: Response from listing skill versions.
+ ListSkillsResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/Skill'
+ type: array
+ title: Data
+ description: List of skill objects
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more results
+ default: false
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first item in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last item in the list
+ type: object
+ required:
+ - data
+ title: ListSkillsResponse
+ description: Response from listing skills.
ListToolsResponse:
properties:
data:
@@ -8816,14 +9353,154 @@ components:
SetDefaultVersionBodyRequest:
properties:
version:
- type: integer
+ type: integer
+ title: Version
+ description: The version to set as default.
+ type: object
+ required:
+ - version
+ title: SetDefaultVersionBodyRequest
+ description: Request body model for setting the default version of a prompt.
+ Skill:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: Unique identifier for the skill
+ created_at:
+ type: integer
+ title: Created At
+ description: Unix timestamp when the skill was created
+ default_version:
+ type: string
+ title: Default Version
+ description: Version used when no version is specified
+ default: '1'
+ description:
+ type: string
+ title: Description
+ description: Description of what the skill does
+ latest_version:
+ type: string
+ title: Latest Version
+ description: Most recently uploaded version number
+ default: '1'
+ name:
+ type: string
+ title: Name
+ description: Human-readable name from SKILL.md frontmatter
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill
+ type: object
+ required:
+ - id
+ - created_at
+ - description
+ - name
+ title: Skill
+ description: A skill resource. Matches OpenAI Skill wire format.
+ SkillDeleteResponse:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: ID of the deleted skill
+ deleted:
+ type: boolean
+ title: Deleted
+ description: Whether the skill was successfully deleted
+ default: true
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.deleted
+ type: object
+ required:
+ - id
+ title: SkillDeleteResponse
+ description: Response from deleting a skill. Matches OpenAI DeletedSkill wire format.
+ SkillUpdateRequest:
+ properties:
+ default_version:
+ type: string
+ title: Default Version
+ description: Version number to set as the default
+ type: object
+ required:
+ - default_version
+ title: SkillUpdateRequest
+ description: Request to update a skill's default version.
+ SkillVersion:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: Unique identifier for this version
+ created_at:
+ type: integer
+ title: Created At
+ description: Unix timestamp when this version was created
+ description:
+ type: string
+ title: Description
+ description: Description of the skill version
+ name:
+ type: string
+ title: Name
+ description: Name of the skill version
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.version
+ skill_id:
+ type: string
+ title: Skill Id
+ description: ID of the parent skill
+ version:
+ type: string
+ title: Version
+ description: Version number as a string
+ type: object
+ required:
+ - id
+ - created_at
+ - description
+ - name
+ - skill_id
+ - version
+ title: SkillVersion
+ description: A specific version of a skill. Matches OpenAI SkillVersion wire format.
+ SkillVersionDeleteResponse:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: ID of the deleted skill
+ deleted:
+ type: boolean
+ title: Deleted
+ description: Whether the version was successfully deleted
+ default: true
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.version.deleted
+ version:
+ type: string
title: Version
- description: The version to set as default.
+ description: Version that was deleted
type: object
required:
+ - id
- version
- title: SetDefaultVersionBodyRequest
- description: Request body model for setting the default version of a prompt.
+ title: SkillVersionDeleteResponse
+ description: Response from deleting a skill version. Matches OpenAI DeletedSkillVersion wire format.
UpdatePromptBodyRequest:
properties:
prompt:
@@ -9710,6 +10387,7 @@ components:
- batches
- vector_io
- tool_runtime
+ - container_runtime
- models
- vector_stores
- tool_groups
@@ -9718,8 +10396,10 @@ components:
- prompts
- conversations
- connectors
+ - containers
- messages
- interactions
+ - skills
- inspect
- admin
title: Api
@@ -10510,219 +11190,929 @@ components:
embedding_model:
title: Embedding Model
type: string
- embedding_dimension:
- title: Embedding Dimension
- type: integer
+ embedding_dimension:
+ title: Embedding Dimension
+ type: integer
+ required:
+ - content
+ - chunk_id
+ - chunk_metadata
+ - embedding
+ - embedding_model
+ - embedding_dimension
+ title: EmbeddedChunk
+ type: object
+ VectorStoreCreateRequest:
+ description: Request to create a vector store.
+ properties:
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ description:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ file_ids:
+ items:
+ type: string
+ title: File Ids
+ type: array
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/VectorStoreExpirationAfter'
+ title: VectorStoreExpirationAfter
+ - type: 'null'
+ nullable: true
+ title: VectorStoreExpirationAfter
+ chunking_strategy:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ metadata:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ title: VectorStoreCreateRequest
+ type: object
+ VectorStoreModifyRequest:
+ description: Request to modify a vector store.
+ properties:
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/VectorStoreExpirationAfter'
+ title: VectorStoreExpirationAfter
+ - type: 'null'
+ nullable: true
+ title: VectorStoreExpirationAfter
+ metadata:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ title: VectorStoreModifyRequest
+ type: object
+ VectorStoreSearchRequest:
+ description: Request to search a vector store.
+ properties:
+ query:
+ anyOf:
+ - type: string
+ - items:
+ type: string
+ type: array
+ title: list[string]
+ title: string | list[string]
+ filters:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ max_num_results:
+ default: 10
+ maximum: 50
+ minimum: 1
+ title: Max Num Results
+ type: integer
+ ranking_options:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ rewrite_query:
+ default: false
+ title: Rewrite Query
+ type: boolean
+ required:
+ - query
+ title: VectorStoreSearchRequest
+ type: object
+ ChunkForDeletion:
+ description: Information needed to delete a chunk from a vector store.
+ properties:
+ chunk_id:
+ title: Chunk Id
+ type: string
+ document_id:
+ title: Document Id
+ type: string
+ required:
+ - chunk_id
+ - document_id
+ title: ChunkForDeletion
+ type: object
+ DeleteChunksRequest:
+ description: Request body for deleting chunks from a vector store.
+ properties:
+ vector_store_id:
+ description: The ID of the vector store to delete chunks from.
+ title: Vector Store Id
+ type: string
+ chunks:
+ description: The list of chunks to delete.
+ items:
+ $ref: '#/components/schemas/ChunkForDeletion'
+ title: Chunks
+ type: array
+ required:
+ - vector_store_id
+ - chunks
+ title: DeleteChunksRequest
+ type: object
+ ListBatchesRequest:
+ description: Request model for listing batches.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional cursor for pagination. Returns batches after this ID.
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of batches to return. Defaults to 20.
+ title: Limit
+ type: integer
+ title: ListBatchesRequest
+ type: object
+ RetrieveBatchRequest:
+ description: Request model for retrieving a batch.
+ properties:
+ batch_id:
+ description: The ID of the batch to retrieve.
+ title: Batch Id
+ type: string
+ required:
+ - batch_id
+ title: RetrieveBatchRequest
+ type: object
+ CancelBatchRequest:
+ description: Request model for canceling a batch.
+ properties:
+ batch_id:
+ description: The ID of the batch to cancel.
+ title: Batch Id
+ type: string
+ required:
+ - batch_id
+ title: CancelBatchRequest
+ type: object
+ JobStatus:
+ description: Status of a job execution.
+ enum:
+ - completed
+ - in_progress
+ - failed
+ - scheduled
+ - cancelled
+ title: JobStatus
+ type: string
+ Job:
+ description: A job execution instance with status tracking.
+ properties:
+ job_id:
+ title: Job Id
+ type: string
+ status:
+ $ref: '#/components/schemas/JobStatus'
+ required:
+ - job_id
+ - status
+ title: Job
+ type: object
+ DialogType:
+ description: Parameter type for dialog data with semantic output labels.
+ properties:
+ type:
+ title: Type
+ type: string
+ enum:
+ - dialog
+ title: DialogType
+ type: object
+ ContainerExpiresAfter:
+ description: |-
+ Control expiration of a container.
+
+ Anchored on ``last_active_at`` (each shell execution or file operation
+ refreshes the anchor). Operator-set bounds protect the host from
+ long-lived sandboxes.
+ properties:
+ anchor:
+ description: The anchor point for expiration. Must be 'last_active_at'.
+ title: Anchor
+ type: string
+ enum:
+ - last_active_at
+ minutes:
+ description: Minutes of inactivity after the anchor before the container expires.
+ maximum: 1440
+ minimum: 1
+ title: Minutes
+ type: integer
+ required:
+ - minutes
+ title: ContainerExpiresAfter
+ type: object
+ NetworkCredential:
+ description: |-
+ A named credential available to outbound network calls.
+
+ The ``value`` should be a secret reference (e.g. ``${env.MY_SECRET}``)
+ in operator-supplied configuration, never a raw secret in a request body.
+ properties:
+ name:
+ description: Logical name used by the container to look up the credential.
+ title: Name
+ type: string
+ value:
+ description: Secret reference or literal value to be injected into the container.
+ format: password
+ title: Value
+ type: string
+ writeOnly: true
required:
- - content
- - chunk_id
- - chunk_metadata
- - embedding
- - embedding_model
- - embedding_dimension
- title: EmbeddedChunk
+ - name
+ - value
+ title: NetworkCredential
type: object
- VectorStoreCreateRequest:
- description: Request to create a vector store.
+ NetworkDomainCredential:
+ description: Bind a ``NetworkCredential`` to a specific outbound domain.
+ properties:
+ domain:
+ description: Fully-qualified domain name to which the credential applies.
+ title: Domain
+ type: string
+ credential:
+ $ref: '#/components/schemas/NetworkCredential'
+ description: Credential injected on outbound calls to this domain.
+ required:
+ - domain
+ - credential
+ title: NetworkDomainCredential
+ type: object
+ NetworkPolicyMode:
+ description: Egress policy mode applied to a container's outbound network.
+ enum:
+ - deny
+ - allow_list
+ - allow_all
+ title: NetworkPolicyMode
+ type: string
+ NetworkPolicy:
+ description: |-
+ Operator-set egress policy for a container.
+
+ A NetworkPolicy is the *upper bound* — request-supplied
+ ``NetworkPolicyExtended`` values may only narrow this policy.
+ properties:
+ mode:
+ $ref: '#/components/schemas/NetworkPolicyMode'
+ default: deny
+ description: Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.
+ allow_domains:
+ description: Domains permitted for outbound traffic. Used when mode is 'allow_list'.
+ items:
+ type: string
+ title: Allow Domains
+ type: array
+ deny_domains:
+ description: Domains explicitly blocked. Takes precedence over 'allow_domains'.
+ items:
+ type: string
+ title: Deny Domains
+ type: array
+ title: NetworkPolicy
+ type: object
+ NetworkPolicyExtended:
+ description: |-
+ Request-layer extension of an operator NetworkPolicy.
+
+ The request may add domain credentials and narrow allow/deny lists, but
+ cannot expand the operator default — enforcement is performed at the API
+ layer; see issue #5892 task 8.
+ properties:
+ mode:
+ $ref: '#/components/schemas/NetworkPolicyMode'
+ default: deny
+ description: Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.
+ allow_domains:
+ description: Domains permitted for outbound traffic. Used when mode is 'allow_list'.
+ items:
+ type: string
+ title: Allow Domains
+ type: array
+ deny_domains:
+ description: Domains explicitly blocked. Takes precedence over 'allow_domains'.
+ items:
+ type: string
+ title: Deny Domains
+ type: array
+ domain_credentials:
+ description: Per-domain credentials injected on outbound calls from this container.
+ items:
+ $ref: '#/components/schemas/NetworkDomainCredential'
+ title: Domain Credentials
+ type: array
+ title: NetworkPolicyExtended
+ type: object
+ ContainerStatus:
+ description: Lifecycle status of a container.
+ enum:
+ - active
+ - expired
+ title: ContainerStatus
+ type: string
+ Container:
+ description: |-
+ A sandboxed execution environment.
+
+ Mirrors the OpenAI Containers API resource with OGX-specific extensions
+ for network policy and image selection.
properties:
+ id:
+ description: Identifier for the container.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container'.
+ title: Object
+ type: string
+ enum:
+ - container
+ created_at:
+ description: Unix timestamp (in seconds) for when the container was created.
+ title: Created At
+ type: integer
+ status:
+ $ref: '#/components/schemas/ContainerStatus'
+ description: Current lifecycle status.
+ last_active_at:
+ description: Unix timestamp (in seconds) of the last operation performed against this container.
+ title: Last Active At
+ type: integer
name:
anyOf:
- type: string
- type: 'null'
+ description: Human-readable name for the container.
nullable: true
- description:
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration settings.
+ nullable: true
+ title: ContainerExpiresAfter
+ image:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Container image used to run the sandbox. May be operator-locked.
+ nullable: true
+ network_policy:
+ anyOf:
+ - $ref: '#/components/schemas/NetworkPolicy'
+ title: NetworkPolicy
+ - type: 'null'
+ description: Effective network policy after layering operator defaults with request extensions.
+ nullable: true
+ title: NetworkPolicy
+ required:
+ - id
+ - created_at
+ - status
+ - last_active_at
+ title: Container
+ type: object
+ ContainerCreateRequest:
+ description: Request body for ``POST /containers``.
+ properties:
+ name:
anyOf:
- type: string
- type: 'null'
+ description: Human-readable name for the container.
nullable: true
file_ids:
+ description: Files (from the Files API) to seed into the container at /mnt/data/.
items:
type: string
title: File Ids
type: array
expires_after:
anyOf:
- - $ref: '#/components/schemas/VectorStoreExpirationAfter'
- title: VectorStoreExpirationAfter
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
- type: 'null'
+ description: Inactivity-based expiration settings.
nullable: true
- title: VectorStoreExpirationAfter
- chunking_strategy:
+ title: ContainerExpiresAfter
+ image:
anyOf:
- - additionalProperties: true
- type: object
+ - type: string
- type: 'null'
+ description: Requested container image. The operator policy may pin or reject this value.
nullable: true
- metadata:
+ network_policy:
anyOf:
- - additionalProperties: true
- type: object
+ - $ref: '#/components/schemas/NetworkPolicyExtended'
+ title: NetworkPolicyExtended
- type: 'null'
+ description: Request-supplied network policy extension. Must be a subset of the operator default.
nullable: true
- title: VectorStoreCreateRequest
+ title: NetworkPolicyExtended
+ title: ContainerCreateRequest
type: object
- VectorStoreModifyRequest:
- description: Request to modify a vector store.
+ ListContainersRequest:
+ description: Query parameters for ``GET /containers``.
properties:
- name:
+ after:
anyOf:
- type: string
- type: 'null'
+ description: Cursor for pagination. Returns containers after this ID.
nullable: true
- expires_after:
+ limit:
anyOf:
- - $ref: '#/components/schemas/VectorStoreExpirationAfter'
- title: VectorStoreExpirationAfter
+ - maximum: 100
+ minimum: 1
+ type: integer
- type: 'null'
- nullable: true
- title: VectorStoreExpirationAfter
- metadata:
+ default: 20
+ description: Maximum number of containers to return (1-100).
+ order:
anyOf:
- - additionalProperties: true
- type: object
+ - $ref: '#/components/schemas/Order'
+ title: Order
- type: 'null'
- nullable: true
- title: VectorStoreModifyRequest
+ default: desc
+ description: Sort order by created_at timestamp ('asc' or 'desc').
+ title: Order
+ title: ListContainersRequest
type: object
- VectorStoreSearchRequest:
- description: Request to search a vector store.
+ ListContainersResponse:
+ description: Response for ``GET /containers``.
properties:
- query:
+ object:
+ description: The object type, which is always 'list'.
+ title: Object
+ type: string
+ enum:
+ - list
+ data:
+ description: The list of containers.
+ items:
+ $ref: '#/components/schemas/Container'
+ title: Data
+ type: array
+ first_id:
anyOf:
- type: string
- - items:
- type: string
- type: array
- title: list[string]
- title: string | list[string]
- filters:
+ - type: 'null'
+ description: ID of the first container in the page.
+ nullable: true
+ last_id:
anyOf:
- - additionalProperties: true
- type: object
+ - type: string
- type: 'null'
+ description: ID of the last container in the page.
nullable: true
- max_num_results:
- default: 10
- maximum: 50
- minimum: 1
- title: Max Num Results
+ has_more:
+ description: Whether more containers exist beyond this page.
+ title: Has More
+ type: boolean
+ required:
+ - data
+ - has_more
+ title: ListContainersResponse
+ type: object
+ GetContainerRequest:
+ properties:
+ container_id:
+ description: The ID of the container to retrieve.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: GetContainerRequest
+ type: object
+ DeleteContainerRequest:
+ properties:
+ container_id:
+ description: The ID of the container to delete.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: DeleteContainerRequest
+ type: object
+ ContainerDeleteResponse:
+ description: Response for ``DELETE /containers/{container_id}``.
+ properties:
+ id:
+ description: The container identifier that was deleted.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container'.
+ title: Object
+ type: string
+ enum:
+ - container
+ deleted:
+ description: Whether the container was successfully deleted.
+ title: Deleted
+ type: boolean
+ required:
+ - id
+ - deleted
+ title: ContainerDeleteResponse
+ type: object
+ ContainerFileSource:
+ description: Origin of a file inside a container.
+ enum:
+ - user
+ - assistant
+ title: ContainerFileSource
+ type: string
+ ContainerFile:
+ description: A file present inside a container's filesystem.
+ properties:
+ id:
+ description: Identifier of the container file.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container.file'.
+ title: Object
+ type: string
+ enum:
+ - container.file
+ container_id:
+ description: ID of the container holding the file.
+ title: Container Id
+ type: string
+ created_at:
+ description: Unix timestamp (in seconds) when the file was created.
+ title: Created At
type: integer
- ranking_options:
+ bytes:
+ description: Size of the file in bytes.
+ title: Bytes
+ type: integer
+ path:
+ description: Absolute path to the file inside the container.
+ title: Path
+ type: string
+ source:
+ $ref: '#/components/schemas/ContainerFileSource'
+ description: Whether the file was supplied by the user or written by the model.
+ required:
+ - id
+ - container_id
+ - created_at
+ - bytes
+ - path
+ - source
+ title: ContainerFile
+ type: object
+ UploadContainerFileRequest:
+ description: |-
+ Path parameters for ``POST /containers/{container_id}/files``.
+
+ The file content itself is supplied as a multipart upload and not part of
+ this Pydantic body; see ``fastapi_routes.py``.
+ properties:
+ container_id:
+ description: The ID of the container to upload into.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: UploadContainerFileRequest
+ type: object
+ ListContainerFilesRequest:
+ properties:
+ container_id:
+ description: The ID of the container whose files should be listed.
+ title: Container Id
+ type: string
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination.
+ nullable: true
+ limit:
+ anyOf:
+ - maximum: 100
+ minimum: 1
+ type: integer
+ - type: 'null'
+ default: 20
+ description: Maximum number of files to return (1-100).
+ order:
+ anyOf:
+ - $ref: '#/components/schemas/Order'
+ title: Order
+ - type: 'null'
+ default: desc
+ description: Sort order by created_at timestamp.
+ title: Order
+ required:
+ - container_id
+ title: ListContainerFilesRequest
+ type: object
+ ListContainerFilesResponse:
+ properties:
+ object:
+ description: The object type, which is always 'list'.
+ title: Object
+ type: string
+ enum:
+ - list
+ data:
+ description: The list of files in the container.
+ items:
+ $ref: '#/components/schemas/ContainerFile'
+ title: Data
+ type: array
+ first_id:
anyOf:
- - additionalProperties: true
- type: object
+ - type: string
- type: 'null'
+ description: ID of the first file in the page.
nullable: true
- rewrite_query:
- default: false
- title: Rewrite Query
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last file in the page.
+ nullable: true
+ has_more:
+ description: Whether more files exist beyond this page.
+ title: Has More
type: boolean
required:
- - query
- title: VectorStoreSearchRequest
+ - data
+ - has_more
+ title: ListContainerFilesResponse
type: object
- ChunkForDeletion:
- description: Information needed to delete a chunk from a vector store.
+ GetContainerFileRequest:
properties:
- chunk_id:
- title: Chunk Id
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
type: string
- document_id:
- title: Document Id
+ file_id:
+ description: The ID of the container file to retrieve.
+ title: File Id
type: string
required:
- - chunk_id
- - document_id
- title: ChunkForDeletion
+ - container_id
+ - file_id
+ title: GetContainerFileRequest
type: object
- DeleteChunksRequest:
- description: Request body for deleting chunks from a vector store.
+ GetContainerFileContentRequest:
properties:
- vector_store_id:
- description: The ID of the vector store to delete chunks from.
- title: Vector Store Id
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to download.
+ title: File Id
type: string
- chunks:
- description: The list of chunks to delete.
- items:
- $ref: '#/components/schemas/ChunkForDeletion'
- title: Chunks
- type: array
required:
- - vector_store_id
- - chunks
- title: DeleteChunksRequest
+ - container_id
+ - file_id
+ title: GetContainerFileContentRequest
type: object
- ListBatchesRequest:
- description: Request model for listing batches.
+ DeleteContainerFileRequest:
properties:
- after:
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to delete.
+ title: File Id
+ type: string
+ required:
+ - container_id
+ - file_id
+ title: DeleteContainerFileRequest
+ type: object
+ ContainerFileDeleteResponse:
+ properties:
+ id:
+ description: The container file identifier that was deleted.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container.file'.
+ title: Object
+ type: string
+ enum:
+ - container.file
+ deleted:
+ description: Whether the file was successfully deleted.
+ title: Deleted
+ type: boolean
+ required:
+ - id
+ - deleted
+ title: ContainerFileDeleteResponse
+ type: object
+ ShellEnvironmentContainerAuto:
+ description: |-
+ Provider-managed container environment.
+
+ The provider lazily creates and reuses a container for the calling
+ response chain. Useful when the caller does not need to persist or
+ reference the container across responses.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - container_auto
+ image:
anyOf:
- type: string
- type: 'null'
- description: Optional cursor for pagination. Returns batches after this ID.
+ description: Optional preferred container image.
nullable: true
- limit:
- default: 20
- description: Maximum number of batches to return. Defaults to 20.
- title: Limit
- type: integer
- title: ListBatchesRequest
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration for the auto-created container.
+ nullable: true
+ title: ContainerExpiresAfter
+ title: ShellEnvironmentContainerAuto
type: object
- RetrieveBatchRequest:
- description: Request model for retrieving a batch.
+ ShellEnvironmentContainerReference:
+ description: Reference an existing container by ID.
properties:
- batch_id:
- description: The ID of the batch to retrieve.
- title: Batch Id
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - container_reference
+ container_id:
+ description: The ID of an existing container to execute inside.
+ title: Container Id
type: string
required:
- - batch_id
- title: RetrieveBatchRequest
+ - container_id
+ title: ShellEnvironmentContainerReference
type: object
- CancelBatchRequest:
- description: Request model for canceling a batch.
+ ShellEnvironmentLocal:
+ description: |-
+ Local (non-container) execution mode.
+
+ Only available when the operator has explicitly enabled local mode in
+ the ContainerRuntime provider configuration.
properties:
- batch_id:
- description: The ID of the batch to cancel.
- title: Batch Id
+ type:
+ description: Discriminator.
+ title: Type
type: string
- required:
- - batch_id
- title: CancelBatchRequest
+ enum:
+ - local
+ working_directory:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional working directory for local execution.
+ nullable: true
+ title: ShellEnvironmentLocal
type: object
- JobStatus:
- description: Status of a job execution.
- enum:
- - completed
- - in_progress
- - failed
- - scheduled
- - cancelled
- title: JobStatus
- type: string
- Job:
- description: A job execution instance with status tracking.
+ ShellOutcomeSuccess:
+ description: Process exited cleanly with status 0.
properties:
- job_id:
- title: Job Id
+ type:
+ description: Discriminator.
+ title: Type
type: string
- status:
- $ref: '#/components/schemas/JobStatus'
+ enum:
+ - success
+ exit_code:
+ description: Process exit code (always 0 for success).
+ title: Exit Code
+ type: integer
+ enum:
+ - 0
+ title: ShellOutcomeSuccess
+ type: object
+ ShellOutcomeFailure:
+ description: Process exited with a non-zero status.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - failure
+ exit_code:
+ description: Process exit code.
+ title: Exit Code
+ type: integer
+ reason:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Human-readable failure reason, if known.
+ nullable: true
required:
- - job_id
- - status
- title: Job
+ - exit_code
+ title: ShellOutcomeFailure
type: object
- DialogType:
- description: Parameter type for dialog data with semantic output labels.
+ ShellOutcomeTimeout:
+ description: Process was terminated for exceeding its time budget.
properties:
type:
+ description: Discriminator.
title: Type
type: string
enum:
- - dialog
- title: DialogType
+ - timeout
+ elapsed_seconds:
+ description: Wall-clock seconds elapsed before termination.
+ title: Elapsed Seconds
+ type: number
+ required:
+ - elapsed_seconds
+ title: ShellOutcomeTimeout
+ type: object
+ ShellCallOutput:
+ description: |-
+ Captured output of a single shell execution.
+
+ Consumed by the Responses provider to construct ``ShellCallOutputItem``
+ entries on the output stream.
+ properties:
+ stdout:
+ description: UTF-8 decoded standard output (truncated by the runtime if oversized).
+ title: Stdout
+ type: string
+ stderr:
+ description: UTF-8 decoded standard error (truncated by the runtime if oversized).
+ title: Stderr
+ type: string
+ outcome:
+ description: How the shell process terminated.
+ discriminator:
+ mapping:
+ failure: '#/components/schemas/ShellOutcomeFailure'
+ success: '#/components/schemas/ShellOutcomeSuccess'
+ timeout: '#/components/schemas/ShellOutcomeTimeout'
+ propertyName: type
+ oneOf:
+ - $ref: '#/components/schemas/ShellOutcomeSuccess'
+ title: ShellOutcomeSuccess
+ - $ref: '#/components/schemas/ShellOutcomeFailure'
+ title: ShellOutcomeFailure
+ - $ref: '#/components/schemas/ShellOutcomeTimeout'
+ title: ShellOutcomeTimeout
+ title: ShellOutcomeSuccess | ShellOutcomeFailure | ShellOutcomeTimeout
+ duration_ms:
+ description: Wall-clock duration of the shell call in milliseconds.
+ minimum: 0
+ title: Duration Ms
+ type: integer
+ container_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the container the call executed in, when applicable. Null for local mode.
+ nullable: true
+ required:
+ - stdout
+ - stderr
+ - outcome
+ - duration_ms
+ title: ShellCallOutput
type: object
ConversationMessage:
description: OpenAI-compatible message item for conversations.
@@ -11118,6 +12508,68 @@ components:
- prompt_id
title: DeletePromptRequest
type: object
+ SkillVersionCreateRequest:
+ description: Request to create a new skill version. Matches OpenAI VersionCreateParams.
+ properties:
+ default:
+ type: boolean
+ default: false
+ description: Whether to set this version as the default
+ title: Default
+ title: SkillVersionCreateRequest
+ type: object
+ ListSkillsRequest:
+ description: Request parameters for listing skills.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of results
+ maximum: 100
+ minimum: 1
+ title: Limit
+ type: integer
+ order:
+ default: desc
+ description: Sort order by created_at
+ enum:
+ - asc
+ - desc
+ title: Order
+ type: string
+ title: ListSkillsRequest
+ type: object
+ ListSkillVersionsRequest:
+ description: Request parameters for listing skill versions.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of results
+ maximum: 100
+ minimum: 1
+ title: Limit
+ type: integer
+ order:
+ default: desc
+ description: Sort order by version
+ enum:
+ - asc
+ - desc
+ title: Order
+ type: string
+ title: ListSkillVersionsRequest
+ type: object
OpenAIResponseMessageOutputUnion:
anyOf:
- oneOf:
@@ -11251,6 +12703,43 @@ components:
- type
- custom
description: A call to a custom tool created by the model.
+ ChoiceDeltaToolCall:
+ properties:
+ id:
+ anyOf:
+ - type: string
+ description: Unique identifier for the tool call.
+ - type: 'null'
+ description: Unique identifier for the tool call.
+ type:
+ anyOf:
+ - type: string
+ description: Must be 'function' to identify this as a function call.
+ enum:
+ - function
+ - type: 'null'
+ description: Must be 'function' to identify this as a function call.
+ function:
+ anyOf:
+ - properties:
+ name:
+ type: string
+ title: Name
+ description: Name of the function to call.
+ arguments:
+ type: string
+ title: Arguments
+ description: Arguments to pass to the function as a JSON string.
+ type: object
+ - type: 'null'
+ description: Function call details.
+ index:
+ type: integer
+ description: The index of the tool call being streamed.
+ type: object
+ description: A tool call delta in a streaming chat completion chunk.
+ required:
+ - index
responses:
BadRequest400:
description: The request was invalid or malformed
@@ -11349,6 +12838,8 @@ tags:
- description: Tool listing and management.
name: Tools
x-displayName: Tools
+- description: OpenAI-compatible vector store management and search.
+ name: Vector Stores
- description: ''
name: VectorIO
- description: OpenAI Responses API for agent orchestration with tool use, multi-turn conversations, and background processing.
@@ -11375,6 +12866,7 @@ x-tagGroups:
- ToolGroups
- ToolRuntime
- Tools
+ - Vector Stores
- VectorIO
security:
- Default: []
diff --git a/docs/static/img/claude-code-flow.svg b/docs/static/img/claude-code-flow.svg
new file mode 100644
index 00000000000..50b14272317
--- /dev/null
+++ b/docs/static/img/claude-code-flow.svg
@@ -0,0 +1,211 @@
+
diff --git a/docs/static/ogx-spec.yaml b/docs/static/ogx-spec.yaml
index c85585bb94b..49101c06dbf 100644
--- a/docs/static/ogx-spec.yaml
+++ b/docs/static/ogx-spec.yaml
@@ -2171,7 +2171,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: List vector stores (OpenAI-compatible).
description: List vector stores (OpenAI-compatible).
operationId: openai_list_vector_stores_v1_vector_stores_get
@@ -2252,7 +2252,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Create a vector store (OpenAI-compatible).
description: Create a vector store (OpenAI-compatible).
operationId: openai_create_vector_store_v1_vector_stores_post
@@ -2296,7 +2296,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve a vector store (OpenAI-compatible).
description: Retrieve a vector store (OpenAI-compatible).
operationId: openai_retrieve_vector_store_v1_vector_stores__vector_store_id__get
@@ -2340,7 +2340,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Update a vector store (OpenAI-compatible).
description: Update a vector store (OpenAI-compatible).
operationId: openai_update_vector_store_v1_vector_stores__vector_store_id__post
@@ -2393,7 +2393,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Delete a vector store (OpenAI-compatible).
description: Delete a vector store (OpenAI-compatible).
operationId: openai_delete_vector_store_v1_vector_stores__vector_store_id__delete
@@ -2438,7 +2438,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Create a vector store file batch (OpenAI-compatible).
description: Create a vector store file batch (OpenAI-compatible).
operationId: openai_create_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches_post
@@ -2492,7 +2492,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve a vector store file batch (OpenAI-compatible).
description: Retrieve a vector store file batch (OpenAI-compatible).
operationId: openai_retrieve_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches__batch_id__get
@@ -2548,7 +2548,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Cancel a vector store file batch (OpenAI-compatible).
description: Cancel a vector store file batch (OpenAI-compatible).
operationId: openai_cancel_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches__batch_id__cancel_post
@@ -2604,7 +2604,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: List files in a vector store file batch (OpenAI-compatible).
description: List files in a vector store file batch (OpenAI-compatible).
operationId: openai_list_files_in_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches__batch_id__files_get
@@ -2715,7 +2715,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: List files in a vector store (OpenAI-compatible).
description: List files in a vector store (OpenAI-compatible).
operationId: openai_list_files_in_vector_store_v1_vector_stores__vector_store_id__files_get
@@ -2819,7 +2819,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Attach a file to a vector store (OpenAI-compatible).
description: Attach a file to a vector store (OpenAI-compatible).
operationId: openai_attach_file_to_vector_store_v1_vector_stores__vector_store_id__files_post
@@ -2873,7 +2873,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve a vector store file (OpenAI-compatible).
description: Retrieve a vector store file (OpenAI-compatible).
operationId: openai_retrieve_vector_store_file_v1_vector_stores__vector_store_id__files__file_id__get
@@ -2928,7 +2928,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Update a vector store file (OpenAI-compatible).
description: Update a vector store file (OpenAI-compatible).
operationId: openai_update_vector_store_file_v1_vector_stores__vector_store_id__files__file_id__post
@@ -2976,7 +2976,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Delete a vector store file (OpenAI-compatible).
description: Delete a vector store file (OpenAI-compatible).
operationId: openai_delete_vector_store_file_v1_vector_stores__vector_store_id__files__file_id__delete
@@ -3032,7 +3032,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve vector store file contents (OpenAI-compatible).
description: Retrieve vector store file contents (OpenAI-compatible).
operationId: openai_retrieve_vector_store_file_contents_v1_vector_stores__vector_store_id__files__file_id__content_get
@@ -3110,7 +3110,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Search a vector store (OpenAI-compatible).
description: Search a vector store (OpenAI-compatible).
operationId: openai_search_vector_store_v1_vector_stores__vector_store_id__search_post
@@ -4713,7 +4713,7 @@ components:
tool_calls:
description: The tool calls of the delta.
items:
- $ref: '#/components/schemas/ChatCompletionMessageToolCall'
+ $ref: '#/components/schemas/ChoiceDeltaToolCall'
title: Tool Calls
type: array
nullable: true
@@ -6204,25 +6204,25 @@ components:
title: OpenAIFileObject
description: OpenAI File object as defined in the OpenAI Files API.
ExpiresAfter:
+ description: Control expiration of uploaded files.
properties:
anchor:
- type: string
- title: Anchor
description: The anchor point for expiration, must be 'created_at'.
+ title: Anchor
+ type: string
enum:
- created_at
seconds:
- type: integer
- maximum: 2592000.0
- minimum: 3600.0
- title: Seconds
description: Seconds until expiration, between 3600 (1 hour) and 2592000 (30 days).
- type: object
+ maximum: 2592000
+ minimum: 3600
+ title: Seconds
+ type: integer
required:
- anchor
- seconds
title: ExpiresAfter
- description: Control expiration of uploaded files.
+ type: object
OpenAIFileDeleteResponse:
properties:
id:
@@ -6935,6 +6935,10 @@ components:
store:
type: boolean
title: Store
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
input:
items:
$ref: '#/components/schemas/OpenAIResponseMessageOutputUnion'
@@ -7030,6 +7034,7 @@ components:
- medium
- high
- type: 'null'
+ default: medium
type: object
title: OpenAIResponseText
description: Text response configuration for OpenAI responses.
@@ -7348,6 +7353,10 @@ components:
store:
type: boolean
title: Store
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
type: object
required:
- created_at
@@ -10062,8 +10071,24 @@ components:
title: Tools
description: Tools available to the model.
tool_choice:
- title: Tool Choice
+ oneOf:
+ - $ref: '#/components/schemas/_ToolChoiceAuto'
+ title: _ToolChoiceAuto
+ - $ref: '#/components/schemas/_ToolChoiceAny'
+ title: _ToolChoiceAny
+ - $ref: '#/components/schemas/_ToolChoiceNone'
+ title: _ToolChoiceNone
+ - $ref: '#/components/schemas/_ToolChoiceTool'
+ title: _ToolChoiceTool
+ title: _ToolChoiceAuto | ... (4 variants)
description: "How the model should select tools. One of: 'auto', 'any', 'none', or {type: 'tool', name: '...'}."
+ discriminator:
+ propertyName: type
+ mapping:
+ any: '#/components/schemas/_ToolChoiceAny'
+ auto: '#/components/schemas/_ToolChoiceAuto'
+ none: '#/components/schemas/_ToolChoiceNone'
+ tool: '#/components/schemas/_ToolChoiceTool'
stream:
type: boolean
title: Stream
@@ -10690,11 +10715,9 @@ components:
description: The intended purpose of the uploaded file.
expires_after:
anyOf:
- - $ref: '#/components/schemas/ExpiresAfter'
- title: ExpiresAfter
+ - type: string
- type: 'null'
description: Optional expiration settings for the file.
- title: ExpiresAfter
type: object
required:
- file
@@ -10832,54 +10855,57 @@ components:
CompactResponseRequest:
properties:
model:
- type: string
- title: Model
+ anyOf:
+ - $ref: '#/components/schemas/ModelIdsResponses'
+ - type: string
+ - type: 'null'
description: The model to use for generating the compacted summary.
input:
anyOf:
- - type: string
- - items:
- anyOf:
- - oneOf:
+ - oneOf:
+ - type: string
+ - items:
+ anyOf:
+ - oneOf:
+ - $ref: '#/components/schemas/OpenAIResponseMessage-Input'
+ title: OpenAIResponseMessage-Input
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
+ title: OpenAIResponseOutputMessageWebSearchToolCall-Input
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
+ title: OpenAIResponseOutputMessageFileSearchToolCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
+ title: OpenAIResponseOutputMessageFunctionToolCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
+ title: OpenAIResponseOutputMessageMCPCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
+ title: OpenAIResponseOutputMessageMCPListTools
+ - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
+ title: OpenAIResponseMCPApprovalRequest
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
+ title: OpenAIResponseOutputMessageReasoningItem
+ discriminator:
+ propertyName: type
+ mapping:
+ file_search_call: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
+ function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
+ mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
+ mcp_call: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
+ mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
+ message: '#/components/schemas/OpenAIResponseMessage-Input'
+ reasoning: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
+ web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
+ title: OpenAIResponseMessage-Input | ... (8 variants)
+ - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
+ title: OpenAIResponseInputFunctionToolCallOutput
+ - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
+ title: OpenAIResponseMCPApprovalResponse
+ - $ref: '#/components/schemas/OpenAIResponseCompaction'
+ title: OpenAIResponseCompaction
- $ref: '#/components/schemas/OpenAIResponseMessage-Input'
title: OpenAIResponseMessage-Input
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
- title: OpenAIResponseOutputMessageWebSearchToolCall-Input
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
- title: OpenAIResponseOutputMessageFileSearchToolCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
- title: OpenAIResponseOutputMessageFunctionToolCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
- title: OpenAIResponseOutputMessageMCPCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
- title: OpenAIResponseOutputMessageMCPListTools
- - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
- title: OpenAIResponseMCPApprovalRequest
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
- title: OpenAIResponseOutputMessageReasoningItem
- discriminator:
- propertyName: type
- mapping:
- file_search_call: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
- function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
- mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
- mcp_call: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
- mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
- message: '#/components/schemas/OpenAIResponseMessage-Input'
- reasoning: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
- web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
- title: OpenAIResponseMessage-Input | ... (8 variants)
- - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
- title: OpenAIResponseInputFunctionToolCallOutput
- - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
- title: OpenAIResponseMCPApprovalResponse
- - $ref: '#/components/schemas/OpenAIResponseCompaction'
- title: OpenAIResponseCompaction
- - $ref: '#/components/schemas/OpenAIResponseMessage-Input'
- title: OpenAIResponseMessage-Input
- title: OpenAIResponseInputFunctionToolCallOutput | ... (4 variants)
- type: array
- title: list[OpenAIResponseMessageUnion | OpenAIResponseInputFunctionToolCallOutput | ...]
+ title: OpenAIResponseInputFunctionToolCallOutput | ... (4 variants)
+ type: array
+ title: list[OpenAIResponseMessageUnion | OpenAIResponseInputFunctionToolCallOutput | ...]
- type: 'null'
title: string | list[OpenAIResponseMessageUnion | OpenAIResponseInputFunctionToolCallOutput | ...]
description: Input message(s) to compact.
@@ -11272,6 +11298,11 @@ components:
type: object
- type: 'null'
description: Dictionary of metadata key-value pairs to attach to the response.
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: A stable identifier used to associate the request with an end user, for safety monitoring. Echoed back on the response.
truncation:
allOf:
- $ref: '#/components/schemas/ResponseTruncation'
@@ -11539,6 +11570,72 @@ components:
- has_more
title: ListMessageBatchesResponse
description: Response from GET /v1/messages/batches.
+ ListSkillVersionsResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/SkillVersion'
+ type: array
+ title: Data
+ description: List of skill version objects
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more results
+ default: false
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first item in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last item in the list
+ type: object
+ required:
+ - data
+ title: ListSkillVersionsResponse
+ description: Response from listing skill versions.
+ ListSkillsResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/Skill'
+ type: array
+ title: Data
+ description: List of skill objects
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more results
+ default: false
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first item in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last item in the list
+ type: object
+ required:
+ - data
+ title: ListSkillsResponse
+ description: Response from listing skills.
ListToolsResponse:
properties:
data:
@@ -12860,6 +12957,146 @@ components:
- version
title: SetDefaultVersionBodyRequest
description: Request body model for setting the default version of a prompt.
+ Skill:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: Unique identifier for the skill
+ created_at:
+ type: integer
+ title: Created At
+ description: Unix timestamp when the skill was created
+ default_version:
+ type: string
+ title: Default Version
+ description: Version used when no version is specified
+ default: '1'
+ description:
+ type: string
+ title: Description
+ description: Description of what the skill does
+ latest_version:
+ type: string
+ title: Latest Version
+ description: Most recently uploaded version number
+ default: '1'
+ name:
+ type: string
+ title: Name
+ description: Human-readable name from SKILL.md frontmatter
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill
+ type: object
+ required:
+ - id
+ - created_at
+ - description
+ - name
+ title: Skill
+ description: A skill resource. Matches OpenAI Skill wire format.
+ SkillDeleteResponse:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: ID of the deleted skill
+ deleted:
+ type: boolean
+ title: Deleted
+ description: Whether the skill was successfully deleted
+ default: true
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.deleted
+ type: object
+ required:
+ - id
+ title: SkillDeleteResponse
+ description: Response from deleting a skill. Matches OpenAI DeletedSkill wire format.
+ SkillUpdateRequest:
+ properties:
+ default_version:
+ type: string
+ title: Default Version
+ description: Version number to set as the default
+ type: object
+ required:
+ - default_version
+ title: SkillUpdateRequest
+ description: Request to update a skill's default version.
+ SkillVersion:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: Unique identifier for this version
+ created_at:
+ type: integer
+ title: Created At
+ description: Unix timestamp when this version was created
+ description:
+ type: string
+ title: Description
+ description: Description of the skill version
+ name:
+ type: string
+ title: Name
+ description: Name of the skill version
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.version
+ skill_id:
+ type: string
+ title: Skill Id
+ description: ID of the parent skill
+ version:
+ type: string
+ title: Version
+ description: Version number as a string
+ type: object
+ required:
+ - id
+ - created_at
+ - description
+ - name
+ - skill_id
+ - version
+ title: SkillVersion
+ description: A specific version of a skill. Matches OpenAI SkillVersion wire format.
+ SkillVersionDeleteResponse:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: ID of the deleted skill
+ deleted:
+ type: boolean
+ title: Deleted
+ description: Whether the version was successfully deleted
+ default: true
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.version.deleted
+ version:
+ type: string
+ title: Version
+ description: Version that was deleted
+ type: object
+ required:
+ - id
+ - version
+ title: SkillVersionDeleteResponse
+ description: Response from deleting a skill version. Matches OpenAI DeletedSkillVersion wire format.
UpdatePromptBodyRequest:
properties:
prompt:
@@ -13121,29 +13358,82 @@ components:
type: object
title: WebSearchUserLocation
description: Approximate user location to refine web search results.
- _URLOrData:
+ _ToolChoiceAny:
properties:
- url:
- anyOf:
- - $ref: '#/components/schemas/URL'
- title: URL
- - type: 'null'
- title: URL
- data:
+ type:
+ type: string
+ title: Type
+ enum:
+ - any
+ disable_parallel_tool_use:
anyOf:
- - type: string
+ - type: boolean
- type: 'null'
- contentEncoding: base64
type: object
- title: _URLOrData
- description: A URL or a base64 encoded string
- _WebSearchUserLocation:
+ title: _ToolChoiceAny
+ _ToolChoiceAuto:
properties:
type:
type: string
title: Type
enum:
- - approximate
+ - auto
+ disable_parallel_tool_use:
+ anyOf:
+ - type: boolean
+ - type: 'null'
+ type: object
+ title: _ToolChoiceAuto
+ _ToolChoiceNone:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - none
+ type: object
+ title: _ToolChoiceNone
+ _ToolChoiceTool:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - tool
+ name:
+ type: string
+ title: Name
+ disable_parallel_tool_use:
+ anyOf:
+ - type: boolean
+ - type: 'null'
+ type: object
+ required:
+ - name
+ title: _ToolChoiceTool
+ _URLOrData:
+ properties:
+ url:
+ anyOf:
+ - $ref: '#/components/schemas/URL'
+ title: URL
+ - type: 'null'
+ title: URL
+ data:
+ anyOf:
+ - type: string
+ - type: 'null'
+ contentEncoding: base64
+ type: object
+ title: _URLOrData
+ description: A URL or a base64 encoded string
+ _WebSearchUserLocation:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - approximate
city:
anyOf:
- type: string
@@ -13771,6 +14061,7 @@ components:
- batches
- vector_io
- tool_runtime
+ - container_runtime
- models
- vector_stores
- tool_groups
@@ -13779,8 +14070,10 @@ components:
- prompts
- conversations
- connectors
+ - containers
- messages
- interactions
+ - skills
- inspect
- admin
title: Api
@@ -14785,184 +15078,894 @@ components:
- dialog
title: DialogType
type: object
- ConversationMessage:
- description: OpenAI-compatible message item for conversations.
+ ContainerExpiresAfter:
+ description: |-
+ Control expiration of a container.
+
+ Anchored on ``last_active_at`` (each shell execution or file operation
+ refreshes the anchor). Operator-set bounds protect the host from
+ long-lived sandboxes.
properties:
- id:
- description: unique identifier for this message
- title: Id
- type: string
- content:
- description: message content
- items:
- additionalProperties: true
- type: object
- title: Content
- type: array
- role:
- description: message role
- title: Role
- type: string
- status:
- description: message status
- title: Status
- type: string
- type:
- title: Type
- type: string
- enum:
- - message
- object:
- title: Object
+ anchor:
+ description: The anchor point for expiration. Must be 'last_active_at'.
+ title: Anchor
type: string
enum:
- - message
+ - last_active_at
+ minutes:
+ description: Minutes of inactivity after the anchor before the container expires.
+ maximum: 1440
+ minimum: 1
+ title: Minutes
+ type: integer
required:
- - id
- - content
- - role
- - status
- title: ConversationMessage
+ - minutes
+ title: ContainerExpiresAfter
type: object
- ConversationItemCreateRequest:
- description: Request body for creating conversation items.
+ NetworkCredential:
+ description: |-
+ A named credential available to outbound network calls.
+
+ The ``value`` should be a secret reference (e.g. ``${env.MY_SECRET}``)
+ in operator-supplied configuration, never a raw secret in a request body.
properties:
- items:
- description: Items to include in the conversation context. You may add up to 20 items at a time.
- items:
- discriminator:
- mapping:
- compaction: '#/components/schemas/OpenAIResponseCompaction'
- file_search_call: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
- function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
- function_call_output: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
- mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
- mcp_approval_response: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
- mcp_call: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
- mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
- message: '#/components/schemas/OpenAIResponseMessage'
- reasoning: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
- web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
- propertyName: type
- oneOf:
- - $ref: '#/components/schemas/OpenAIResponseMessage'
- title: OpenAIResponseMessage
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
- title: OpenAIResponseOutputMessageWebSearchToolCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
- title: OpenAIResponseOutputMessageFileSearchToolCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
- title: OpenAIResponseOutputMessageFunctionToolCall
- - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
- title: OpenAIResponseInputFunctionToolCallOutput
- - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
- title: OpenAIResponseMCPApprovalRequest
- - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
- title: OpenAIResponseMCPApprovalResponse
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
- title: OpenAIResponseOutputMessageMCPCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
- title: OpenAIResponseOutputMessageMCPListTools
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
- title: OpenAIResponseOutputMessageReasoningItem
- - $ref: '#/components/schemas/OpenAIResponseCompaction'
- title: OpenAIResponseCompaction
- title: OpenAIResponseMessage | ... (11 variants)
- maxItems: 20
- title: Items
- type: array
+ name:
+ description: Logical name used by the container to look up the credential.
+ title: Name
+ type: string
+ value:
+ description: Secret reference or literal value to be injected into the container.
+ format: password
+ title: Value
+ type: string
+ writeOnly: true
required:
- - items
- title: ConversationItemCreateRequest
+ - name
+ - value
+ title: NetworkCredential
type: object
- GetConversationRequest:
- description: Request model for getting a conversation by ID.
+ NetworkDomainCredential:
+ description: Bind a ``NetworkCredential`` to a specific outbound domain.
properties:
- conversation_id:
- description: The conversation identifier.
- title: Conversation Id
+ domain:
+ description: Fully-qualified domain name to which the credential applies.
+ title: Domain
type: string
+ credential:
+ $ref: '#/components/schemas/NetworkCredential'
+ description: Credential injected on outbound calls to this domain.
required:
- - conversation_id
- title: GetConversationRequest
+ - domain
+ - credential
+ title: NetworkDomainCredential
type: object
- DeleteConversationRequest:
- description: Request model for deleting a conversation.
+ NetworkPolicyMode:
+ description: Egress policy mode applied to a container's outbound network.
+ enum:
+ - deny
+ - allow_list
+ - allow_all
+ title: NetworkPolicyMode
+ type: string
+ NetworkPolicy:
+ description: |-
+ Operator-set egress policy for a container.
+
+ A NetworkPolicy is the *upper bound* — request-supplied
+ ``NetworkPolicyExtended`` values may only narrow this policy.
properties:
- conversation_id:
- description: The conversation identifier.
- title: Conversation Id
- type: string
- required:
- - conversation_id
- title: DeleteConversationRequest
+ mode:
+ $ref: '#/components/schemas/NetworkPolicyMode'
+ default: deny
+ description: Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.
+ allow_domains:
+ description: Domains permitted for outbound traffic. Used when mode is 'allow_list'.
+ items:
+ type: string
+ title: Allow Domains
+ type: array
+ deny_domains:
+ description: Domains explicitly blocked. Takes precedence over 'allow_domains'.
+ items:
+ type: string
+ title: Deny Domains
+ type: array
+ title: NetworkPolicy
type: object
- RetrieveItemRequest:
- description: Request model for retrieving a conversation item.
+ NetworkPolicyExtended:
+ description: |-
+ Request-layer extension of an operator NetworkPolicy.
+
+ The request may add domain credentials and narrow allow/deny lists, but
+ cannot expand the operator default — enforcement is performed at the API
+ layer; see issue #5892 task 8.
properties:
- conversation_id:
- description: The conversation identifier.
- title: Conversation Id
- type: string
- item_id:
- description: The item identifier.
- title: Item Id
- type: string
- required:
- - conversation_id
- - item_id
- title: RetrieveItemRequest
+ mode:
+ $ref: '#/components/schemas/NetworkPolicyMode'
+ default: deny
+ description: Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.
+ allow_domains:
+ description: Domains permitted for outbound traffic. Used when mode is 'allow_list'.
+ items:
+ type: string
+ title: Allow Domains
+ type: array
+ deny_domains:
+ description: Domains explicitly blocked. Takes precedence over 'allow_domains'.
+ items:
+ type: string
+ title: Deny Domains
+ type: array
+ domain_credentials:
+ description: Per-domain credentials injected on outbound calls from this container.
+ items:
+ $ref: '#/components/schemas/NetworkDomainCredential'
+ title: Domain Credentials
+ type: array
+ title: NetworkPolicyExtended
type: object
- ListItemsRequest:
- description: Request model for listing items in a conversation.
+ ContainerStatus:
+ description: Lifecycle status of a container.
+ enum:
+ - active
+ - expired
+ title: ContainerStatus
+ type: string
+ Container:
+ description: |-
+ A sandboxed execution environment.
+
+ Mirrors the OpenAI Containers API resource with OGX-specific extensions
+ for network policy and image selection.
properties:
- conversation_id:
- description: The conversation identifier.
- title: Conversation Id
+ id:
+ description: Identifier for the container.
+ title: Id
type: string
- after:
+ object:
+ description: The object type, which is always 'container'.
+ title: Object
+ type: string
+ enum:
+ - container
+ created_at:
+ description: Unix timestamp (in seconds) for when the container was created.
+ title: Created At
+ type: integer
+ status:
+ $ref: '#/components/schemas/ContainerStatus'
+ description: Current lifecycle status.
+ last_active_at:
+ description: Unix timestamp (in seconds) of the last operation performed against this container.
+ title: Last Active At
+ type: integer
+ name:
anyOf:
- type: string
- type: 'null'
- description: An item ID to list items after, used in pagination.
+ description: Human-readable name for the container.
nullable: true
- include:
+ expires_after:
anyOf:
- - items:
- $ref: '#/components/schemas/ConversationItemInclude'
- type: array
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
- type: 'null'
- description: Specify additional output data to include in the response.
+ description: Inactivity-based expiration settings.
nullable: true
- limit:
+ title: ContainerExpiresAfter
+ image:
anyOf:
- - type: integer
+ - type: string
- type: 'null'
- description: A limit on the number of objects to be returned (1-100, default 20).
+ description: Container image used to run the sandbox. May be operator-locked.
nullable: true
- order:
+ network_policy:
anyOf:
- - enum:
- - asc
- - desc
- type: string
+ - $ref: '#/components/schemas/NetworkPolicy'
+ title: NetworkPolicy
- type: 'null'
- description: The order to return items in (asc or desc, default desc).
+ description: Effective network policy after layering operator defaults with request extensions.
nullable: true
+ title: NetworkPolicy
required:
- - conversation_id
- title: ListItemsRequest
+ - id
+ - created_at
+ - status
+ - last_active_at
+ title: Container
type: object
- DeleteItemRequest:
- description: Request model for deleting a conversation item.
+ ContainerCreateRequest:
+ description: Request body for ``POST /containers``.
properties:
- conversation_id:
- description: The conversation identifier.
- title: Conversation Id
- type: string
- item_id:
- description: The item identifier.
- title: Item Id
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Human-readable name for the container.
+ nullable: true
+ file_ids:
+ description: Files (from the Files API) to seed into the container at /mnt/data/.
+ items:
+ type: string
+ title: File Ids
+ type: array
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration settings.
+ nullable: true
+ title: ContainerExpiresAfter
+ image:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Requested container image. The operator policy may pin or reject this value.
+ nullable: true
+ network_policy:
+ anyOf:
+ - $ref: '#/components/schemas/NetworkPolicyExtended'
+ title: NetworkPolicyExtended
+ - type: 'null'
+ description: Request-supplied network policy extension. Must be a subset of the operator default.
+ nullable: true
+ title: NetworkPolicyExtended
+ title: ContainerCreateRequest
+ type: object
+ ListContainersRequest:
+ description: Query parameters for ``GET /containers``.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination. Returns containers after this ID.
+ nullable: true
+ limit:
+ anyOf:
+ - maximum: 100
+ minimum: 1
+ type: integer
+ - type: 'null'
+ default: 20
+ description: Maximum number of containers to return (1-100).
+ order:
+ anyOf:
+ - $ref: '#/components/schemas/Order'
+ title: Order
+ - type: 'null'
+ default: desc
+ description: Sort order by created_at timestamp ('asc' or 'desc').
+ title: Order
+ title: ListContainersRequest
+ type: object
+ ListContainersResponse:
+ description: Response for ``GET /containers``.
+ properties:
+ object:
+ description: The object type, which is always 'list'.
+ title: Object
+ type: string
+ enum:
+ - list
+ data:
+ description: The list of containers.
+ items:
+ $ref: '#/components/schemas/Container'
+ title: Data
+ type: array
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first container in the page.
+ nullable: true
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last container in the page.
+ nullable: true
+ has_more:
+ description: Whether more containers exist beyond this page.
+ title: Has More
+ type: boolean
+ required:
+ - data
+ - has_more
+ title: ListContainersResponse
+ type: object
+ GetContainerRequest:
+ properties:
+ container_id:
+ description: The ID of the container to retrieve.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: GetContainerRequest
+ type: object
+ DeleteContainerRequest:
+ properties:
+ container_id:
+ description: The ID of the container to delete.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: DeleteContainerRequest
+ type: object
+ ContainerDeleteResponse:
+ description: Response for ``DELETE /containers/{container_id}``.
+ properties:
+ id:
+ description: The container identifier that was deleted.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container'.
+ title: Object
+ type: string
+ enum:
+ - container
+ deleted:
+ description: Whether the container was successfully deleted.
+ title: Deleted
+ type: boolean
+ required:
+ - id
+ - deleted
+ title: ContainerDeleteResponse
+ type: object
+ ContainerFileSource:
+ description: Origin of a file inside a container.
+ enum:
+ - user
+ - assistant
+ title: ContainerFileSource
+ type: string
+ ContainerFile:
+ description: A file present inside a container's filesystem.
+ properties:
+ id:
+ description: Identifier of the container file.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container.file'.
+ title: Object
+ type: string
+ enum:
+ - container.file
+ container_id:
+ description: ID of the container holding the file.
+ title: Container Id
+ type: string
+ created_at:
+ description: Unix timestamp (in seconds) when the file was created.
+ title: Created At
+ type: integer
+ bytes:
+ description: Size of the file in bytes.
+ title: Bytes
+ type: integer
+ path:
+ description: Absolute path to the file inside the container.
+ title: Path
+ type: string
+ source:
+ $ref: '#/components/schemas/ContainerFileSource'
+ description: Whether the file was supplied by the user or written by the model.
+ required:
+ - id
+ - container_id
+ - created_at
+ - bytes
+ - path
+ - source
+ title: ContainerFile
+ type: object
+ UploadContainerFileRequest:
+ description: |-
+ Path parameters for ``POST /containers/{container_id}/files``.
+
+ The file content itself is supplied as a multipart upload and not part of
+ this Pydantic body; see ``fastapi_routes.py``.
+ properties:
+ container_id:
+ description: The ID of the container to upload into.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: UploadContainerFileRequest
+ type: object
+ ListContainerFilesRequest:
+ properties:
+ container_id:
+ description: The ID of the container whose files should be listed.
+ title: Container Id
+ type: string
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination.
+ nullable: true
+ limit:
+ anyOf:
+ - maximum: 100
+ minimum: 1
+ type: integer
+ - type: 'null'
+ default: 20
+ description: Maximum number of files to return (1-100).
+ order:
+ anyOf:
+ - $ref: '#/components/schemas/Order'
+ title: Order
+ - type: 'null'
+ default: desc
+ description: Sort order by created_at timestamp.
+ title: Order
+ required:
+ - container_id
+ title: ListContainerFilesRequest
+ type: object
+ ListContainerFilesResponse:
+ properties:
+ object:
+ description: The object type, which is always 'list'.
+ title: Object
+ type: string
+ enum:
+ - list
+ data:
+ description: The list of files in the container.
+ items:
+ $ref: '#/components/schemas/ContainerFile'
+ title: Data
+ type: array
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first file in the page.
+ nullable: true
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last file in the page.
+ nullable: true
+ has_more:
+ description: Whether more files exist beyond this page.
+ title: Has More
+ type: boolean
+ required:
+ - data
+ - has_more
+ title: ListContainerFilesResponse
+ type: object
+ GetContainerFileRequest:
+ properties:
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to retrieve.
+ title: File Id
+ type: string
+ required:
+ - container_id
+ - file_id
+ title: GetContainerFileRequest
+ type: object
+ GetContainerFileContentRequest:
+ properties:
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to download.
+ title: File Id
+ type: string
+ required:
+ - container_id
+ - file_id
+ title: GetContainerFileContentRequest
+ type: object
+ DeleteContainerFileRequest:
+ properties:
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to delete.
+ title: File Id
+ type: string
+ required:
+ - container_id
+ - file_id
+ title: DeleteContainerFileRequest
+ type: object
+ ContainerFileDeleteResponse:
+ properties:
+ id:
+ description: The container file identifier that was deleted.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container.file'.
+ title: Object
+ type: string
+ enum:
+ - container.file
+ deleted:
+ description: Whether the file was successfully deleted.
+ title: Deleted
+ type: boolean
+ required:
+ - id
+ - deleted
+ title: ContainerFileDeleteResponse
+ type: object
+ ShellEnvironmentContainerAuto:
+ description: |-
+ Provider-managed container environment.
+
+ The provider lazily creates and reuses a container for the calling
+ response chain. Useful when the caller does not need to persist or
+ reference the container across responses.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - container_auto
+ image:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional preferred container image.
+ nullable: true
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration for the auto-created container.
+ nullable: true
+ title: ContainerExpiresAfter
+ title: ShellEnvironmentContainerAuto
+ type: object
+ ShellEnvironmentContainerReference:
+ description: Reference an existing container by ID.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - container_reference
+ container_id:
+ description: The ID of an existing container to execute inside.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: ShellEnvironmentContainerReference
+ type: object
+ ShellEnvironmentLocal:
+ description: |-
+ Local (non-container) execution mode.
+
+ Only available when the operator has explicitly enabled local mode in
+ the ContainerRuntime provider configuration.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - local
+ working_directory:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional working directory for local execution.
+ nullable: true
+ title: ShellEnvironmentLocal
+ type: object
+ ShellOutcomeSuccess:
+ description: Process exited cleanly with status 0.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - success
+ exit_code:
+ description: Process exit code (always 0 for success).
+ title: Exit Code
+ type: integer
+ enum:
+ - 0
+ title: ShellOutcomeSuccess
+ type: object
+ ShellOutcomeFailure:
+ description: Process exited with a non-zero status.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - failure
+ exit_code:
+ description: Process exit code.
+ title: Exit Code
+ type: integer
+ reason:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Human-readable failure reason, if known.
+ nullable: true
+ required:
+ - exit_code
+ title: ShellOutcomeFailure
+ type: object
+ ShellOutcomeTimeout:
+ description: Process was terminated for exceeding its time budget.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - timeout
+ elapsed_seconds:
+ description: Wall-clock seconds elapsed before termination.
+ title: Elapsed Seconds
+ type: number
+ required:
+ - elapsed_seconds
+ title: ShellOutcomeTimeout
+ type: object
+ ShellCallOutput:
+ description: |-
+ Captured output of a single shell execution.
+
+ Consumed by the Responses provider to construct ``ShellCallOutputItem``
+ entries on the output stream.
+ properties:
+ stdout:
+ description: UTF-8 decoded standard output (truncated by the runtime if oversized).
+ title: Stdout
+ type: string
+ stderr:
+ description: UTF-8 decoded standard error (truncated by the runtime if oversized).
+ title: Stderr
+ type: string
+ outcome:
+ description: How the shell process terminated.
+ discriminator:
+ mapping:
+ failure: '#/components/schemas/ShellOutcomeFailure'
+ success: '#/components/schemas/ShellOutcomeSuccess'
+ timeout: '#/components/schemas/ShellOutcomeTimeout'
+ propertyName: type
+ oneOf:
+ - $ref: '#/components/schemas/ShellOutcomeSuccess'
+ title: ShellOutcomeSuccess
+ - $ref: '#/components/schemas/ShellOutcomeFailure'
+ title: ShellOutcomeFailure
+ - $ref: '#/components/schemas/ShellOutcomeTimeout'
+ title: ShellOutcomeTimeout
+ title: ShellOutcomeSuccess | ShellOutcomeFailure | ShellOutcomeTimeout
+ duration_ms:
+ description: Wall-clock duration of the shell call in milliseconds.
+ minimum: 0
+ title: Duration Ms
+ type: integer
+ container_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the container the call executed in, when applicable. Null for local mode.
+ nullable: true
+ required:
+ - stdout
+ - stderr
+ - outcome
+ - duration_ms
+ title: ShellCallOutput
+ type: object
+ ConversationMessage:
+ description: OpenAI-compatible message item for conversations.
+ properties:
+ id:
+ description: unique identifier for this message
+ title: Id
+ type: string
+ content:
+ description: message content
+ items:
+ additionalProperties: true
+ type: object
+ title: Content
+ type: array
+ role:
+ description: message role
+ title: Role
+ type: string
+ status:
+ description: message status
+ title: Status
+ type: string
+ type:
+ title: Type
+ type: string
+ enum:
+ - message
+ object:
+ title: Object
+ type: string
+ enum:
+ - message
+ required:
+ - id
+ - content
+ - role
+ - status
+ title: ConversationMessage
+ type: object
+ ConversationItemCreateRequest:
+ description: Request body for creating conversation items.
+ properties:
+ items:
+ description: Items to include in the conversation context. You may add up to 20 items at a time.
+ items:
+ discriminator:
+ mapping:
+ compaction: '#/components/schemas/OpenAIResponseCompaction'
+ file_search_call: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
+ function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
+ function_call_output: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
+ mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
+ mcp_approval_response: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
+ mcp_call: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
+ mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
+ message: '#/components/schemas/OpenAIResponseMessage'
+ reasoning: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
+ web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
+ propertyName: type
+ oneOf:
+ - $ref: '#/components/schemas/OpenAIResponseMessage'
+ title: OpenAIResponseMessage
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
+ title: OpenAIResponseOutputMessageWebSearchToolCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
+ title: OpenAIResponseOutputMessageFileSearchToolCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
+ title: OpenAIResponseOutputMessageFunctionToolCall
+ - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
+ title: OpenAIResponseInputFunctionToolCallOutput
+ - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
+ title: OpenAIResponseMCPApprovalRequest
+ - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
+ title: OpenAIResponseMCPApprovalResponse
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
+ title: OpenAIResponseOutputMessageMCPCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
+ title: OpenAIResponseOutputMessageMCPListTools
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
+ title: OpenAIResponseOutputMessageReasoningItem
+ - $ref: '#/components/schemas/OpenAIResponseCompaction'
+ title: OpenAIResponseCompaction
+ title: OpenAIResponseMessage | ... (11 variants)
+ maxItems: 20
+ title: Items
+ type: array
+ required:
+ - items
+ title: ConversationItemCreateRequest
+ type: object
+ GetConversationRequest:
+ description: Request model for getting a conversation by ID.
+ properties:
+ conversation_id:
+ description: The conversation identifier.
+ title: Conversation Id
+ type: string
+ required:
+ - conversation_id
+ title: GetConversationRequest
+ type: object
+ DeleteConversationRequest:
+ description: Request model for deleting a conversation.
+ properties:
+ conversation_id:
+ description: The conversation identifier.
+ title: Conversation Id
+ type: string
+ required:
+ - conversation_id
+ title: DeleteConversationRequest
+ type: object
+ RetrieveItemRequest:
+ description: Request model for retrieving a conversation item.
+ properties:
+ conversation_id:
+ description: The conversation identifier.
+ title: Conversation Id
+ type: string
+ item_id:
+ description: The item identifier.
+ title: Item Id
+ type: string
+ required:
+ - conversation_id
+ - item_id
+ title: RetrieveItemRequest
+ type: object
+ ListItemsRequest:
+ description: Request model for listing items in a conversation.
+ properties:
+ conversation_id:
+ description: The conversation identifier.
+ title: Conversation Id
+ type: string
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: An item ID to list items after, used in pagination.
+ nullable: true
+ include:
+ anyOf:
+ - items:
+ $ref: '#/components/schemas/ConversationItemInclude'
+ type: array
+ - type: 'null'
+ description: Specify additional output data to include in the response.
+ nullable: true
+ limit:
+ anyOf:
+ - type: integer
+ - type: 'null'
+ description: A limit on the number of objects to be returned (1-100, default 20).
+ nullable: true
+ order:
+ anyOf:
+ - enum:
+ - asc
+ - desc
+ type: string
+ - type: 'null'
+ description: The order to return items in (asc or desc, default desc).
+ nullable: true
+ required:
+ - conversation_id
+ title: ListItemsRequest
+ type: object
+ DeleteItemRequest:
+ description: Request model for deleting a conversation item.
+ properties:
+ conversation_id:
+ description: The conversation identifier.
+ title: Conversation Id
+ type: string
+ item_id:
+ description: The item identifier.
+ title: Item Id
type: string
required:
- conversation_id
@@ -15179,6 +16182,68 @@ components:
- prompt_id
title: DeletePromptRequest
type: object
+ SkillVersionCreateRequest:
+ description: Request to create a new skill version. Matches OpenAI VersionCreateParams.
+ properties:
+ default:
+ type: boolean
+ default: false
+ description: Whether to set this version as the default
+ title: Default
+ title: SkillVersionCreateRequest
+ type: object
+ ListSkillsRequest:
+ description: Request parameters for listing skills.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of results
+ maximum: 100
+ minimum: 1
+ title: Limit
+ type: integer
+ order:
+ default: desc
+ description: Sort order by created_at
+ enum:
+ - asc
+ - desc
+ title: Order
+ type: string
+ title: ListSkillsRequest
+ type: object
+ ListSkillVersionsRequest:
+ description: Request parameters for listing skill versions.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of results
+ maximum: 100
+ minimum: 1
+ title: Limit
+ type: integer
+ order:
+ default: desc
+ description: Sort order by version
+ enum:
+ - asc
+ - desc
+ title: Order
+ type: string
+ title: ListSkillVersionsRequest
+ type: object
OpenAIResponseMessageOutputUnion:
anyOf:
- oneOf:
@@ -15312,6 +16377,46 @@ components:
- type
- custom
description: A call to a custom tool created by the model.
+ ChoiceDeltaToolCall:
+ properties:
+ id:
+ anyOf:
+ - type: string
+ description: Unique identifier for the tool call.
+ - type: 'null'
+ description: Unique identifier for the tool call.
+ type:
+ anyOf:
+ - type: string
+ description: Must be 'function' to identify this as a function call.
+ enum:
+ - function
+ - type: 'null'
+ description: Must be 'function' to identify this as a function call.
+ function:
+ anyOf:
+ - properties:
+ name:
+ type: string
+ title: Name
+ description: Name of the function to call.
+ arguments:
+ type: string
+ title: Arguments
+ description: Arguments to pass to the function as a JSON string.
+ type: object
+ - type: 'null'
+ description: Function call details.
+ index:
+ type: integer
+ description: The index of the tool call being streamed.
+ type: object
+ description: A tool call delta in a streaming chat completion chunk.
+ required:
+ - index
+ ModelIdsResponses:
+ type: string
+ description: Model identifier.
responses:
BadRequest400:
description: The request was invalid or malformed
@@ -15410,6 +16515,8 @@ tags:
- description: Tool listing and management.
name: Tools
x-displayName: Tools
+- description: OpenAI-compatible vector store management and search.
+ name: Vector Stores
- description: ''
name: VectorIO
- description: OpenAI Responses API for agent orchestration with tool use, multi-turn conversations, and background processing.
@@ -15436,6 +16543,7 @@ x-tagGroups:
- ToolGroups
- ToolRuntime
- Tools
+ - Vector Stores
- VectorIO
security:
- Default: []
diff --git a/docs/static/openai-coverage.json b/docs/static/openai-coverage.json
index 9eb467b3319..2b24cf5560e 100644
--- a/docs/static/openai-coverage.json
+++ b/docs/static/openai-coverage.json
@@ -128,9 +128,9 @@
},
"conformance": {
"score": 93.7,
- "issues": 152,
+ "issues": 150,
"missing_properties": 65,
- "total_problems": 217,
+ "total_problems": 215,
"total_properties": 3432
}
},
@@ -1303,8 +1303,8 @@
]
},
"Responses": {
- "score": 95.5,
- "issues": 10,
+ "score": 96.4,
+ "issues": 8,
"missing_properties": 0,
"total_properties": 223,
"endpoints": [
@@ -1376,20 +1376,6 @@
"method": "POST",
"missing_properties": [],
"conformance_issues": [
- {
- "property": "POST.requestBody.content.application/json.properties.input",
- "details": [
- "Union variants added: 2",
- "Union variants removed: 1"
- ]
- },
- {
- "property": "POST.requestBody.content.application/json.properties.model",
- "details": [
- "Type added: ['string']",
- "Union variants removed: 3"
- ]
- },
{
"property": "POST.responses.200.content.application/json.properties.output.items",
"details": [
@@ -1398,7 +1384,7 @@
}
],
"missing_count": 0,
- "issues_count": 3
+ "issues_count": 1
}
]
}
diff --git a/docs/static/stainless-ogx-spec.yaml b/docs/static/stainless-ogx-spec.yaml
index 962e8cb5c17..d85d75d7427 100644
--- a/docs/static/stainless-ogx-spec.yaml
+++ b/docs/static/stainless-ogx-spec.yaml
@@ -2173,7 +2173,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: List vector stores (OpenAI-compatible).
description: List vector stores (OpenAI-compatible).
operationId: openai_list_vector_stores_v1_vector_stores_get
@@ -2254,7 +2254,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Create a vector store (OpenAI-compatible).
description: Create a vector store (OpenAI-compatible).
operationId: openai_create_vector_store_v1_vector_stores_post
@@ -2298,7 +2298,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve a vector store (OpenAI-compatible).
description: Retrieve a vector store (OpenAI-compatible).
operationId: openai_retrieve_vector_store_v1_vector_stores__vector_store_id__get
@@ -2342,7 +2342,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Update a vector store (OpenAI-compatible).
description: Update a vector store (OpenAI-compatible).
operationId: openai_update_vector_store_v1_vector_stores__vector_store_id__post
@@ -2395,7 +2395,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Delete a vector store (OpenAI-compatible).
description: Delete a vector store (OpenAI-compatible).
operationId: openai_delete_vector_store_v1_vector_stores__vector_store_id__delete
@@ -2440,7 +2440,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Create a vector store file batch (OpenAI-compatible).
description: Create a vector store file batch (OpenAI-compatible).
operationId: openai_create_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches_post
@@ -2494,7 +2494,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve a vector store file batch (OpenAI-compatible).
description: Retrieve a vector store file batch (OpenAI-compatible).
operationId: openai_retrieve_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches__batch_id__get
@@ -2550,7 +2550,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Cancel a vector store file batch (OpenAI-compatible).
description: Cancel a vector store file batch (OpenAI-compatible).
operationId: openai_cancel_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches__batch_id__cancel_post
@@ -2606,7 +2606,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: List files in a vector store file batch (OpenAI-compatible).
description: List files in a vector store file batch (OpenAI-compatible).
operationId: openai_list_files_in_vector_store_file_batch_v1_vector_stores__vector_store_id__file_batches__batch_id__files_get
@@ -2717,7 +2717,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: List files in a vector store (OpenAI-compatible).
description: List files in a vector store (OpenAI-compatible).
operationId: openai_list_files_in_vector_store_v1_vector_stores__vector_store_id__files_get
@@ -2821,7 +2821,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Attach a file to a vector store (OpenAI-compatible).
description: Attach a file to a vector store (OpenAI-compatible).
operationId: openai_attach_file_to_vector_store_v1_vector_stores__vector_store_id__files_post
@@ -2875,7 +2875,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve a vector store file (OpenAI-compatible).
description: Retrieve a vector store file (OpenAI-compatible).
operationId: openai_retrieve_vector_store_file_v1_vector_stores__vector_store_id__files__file_id__get
@@ -2930,7 +2930,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Update a vector store file (OpenAI-compatible).
description: Update a vector store file (OpenAI-compatible).
operationId: openai_update_vector_store_file_v1_vector_stores__vector_store_id__files__file_id__post
@@ -2978,7 +2978,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Delete a vector store file (OpenAI-compatible).
description: Delete a vector store file (OpenAI-compatible).
operationId: openai_delete_vector_store_file_v1_vector_stores__vector_store_id__files__file_id__delete
@@ -3034,7 +3034,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Retrieve vector store file contents (OpenAI-compatible).
description: Retrieve vector store file contents (OpenAI-compatible).
operationId: openai_retrieve_vector_store_file_contents_v1_vector_stores__vector_store_id__files__file_id__content_get
@@ -3112,7 +3112,7 @@ paths:
$ref: '#/components/responses/DefaultError'
description: Default Response
tags:
- - VectorIO
+ - Vector Stores
summary: Search a vector store (OpenAI-compatible).
description: Search a vector store (OpenAI-compatible).
operationId: openai_search_vector_store_v1_vector_stores__vector_store_id__search_post
@@ -4045,113 +4045,548 @@ paths:
input="What is the capital of France?",
)
print(interaction.outputs[0].text)
-components:
- schemas:
- Error:
- description: Error response from the API. Roughly follows RFC 7807.
- properties:
- status:
- title: Status
- type: integer
- title:
- title: Title
- type: string
- detail:
- title: Detail
- type: string
- instance:
+ /v1alpha/skills:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/ListSkillsResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: List skills
+ description: List all skills.
+ operationId: list_skills_v1alpha_skills_get
+ parameters:
+ - name: after
+ in: query
+ required: false
+ schema:
anyOf:
- type: string
- type: 'null'
- nullable: true
- required:
- - status
- - title
- - detail
- title: Error
- type: object
- ListBatchesResponse:
- properties:
- object:
- type: string
- title: Object
+ description: Cursor for pagination
+ title: After
+ description: Cursor for pagination
+ - name: limit
+ in: query
+ required: false
+ schema:
+ type: integer
+ description: Maximum number of results
+ default: 20
+ title: Limit
+ description: Maximum number of results
+ - name: order
+ in: query
+ required: false
+ schema:
enum:
- - list
- data:
- items:
- $ref: '#/components/schemas/Batch'
- type: array
- title: Data
- description: List of batch objects
- first_id:
- anyOf:
- - type: string
- - type: 'null'
- description: ID of the first batch in the list
- last_id:
- anyOf:
- - type: string
- - type: 'null'
- description: ID of the last batch in the list
- has_more:
- type: boolean
- title: Has More
- description: Whether there are more batches available
- default: false
- type: object
- required:
- - data
- title: ListBatchesResponse
- description: Response containing a list of batch objects.
- CreateBatchRequest:
- properties:
- input_file_id:
- type: string
- title: Input File Id
- description: The ID of an uploaded file containing requests for the batch.
- endpoint:
- type: string
- title: Endpoint
- description: The endpoint to be used for all requests in the batch.
- completion_window:
+ - asc
+ - desc
type: string
- title: Completion Window
- description: The time window within which the batch should be processed.
- enum:
- - 24h
- metadata:
- anyOf:
- - additionalProperties:
- type: string
- type: object
- - type: 'null'
- description: Optional metadata for the batch.
- idempotency_key:
- anyOf:
- - type: string
- - type: 'null'
- description: Optional idempotency key. When provided, enables idempotent behavior.
- type: object
- required:
- - input_file_id
- - endpoint
- - completion_window
- title: CreateBatchRequest
- description: Request model for creating a batch.
- Batch:
- properties:
- id:
+ description: Sort order by created_at
+ default: desc
+ title: Order
+ description: Sort order by created_at
+ post:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/Skill'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Create skill
+ description: Create a skill by uploading a zip bundle containing a SKILL.md manifest.
+ operationId: create_skill_v1alpha_skills_post
+ requestBody:
+ required: true
+ content:
+ multipart/form-data:
+ schema:
+ $ref: '#/components/schemas/Body_create_skill_v1alpha_skills_post'
+ /v1alpha/skills/{skill_id}:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/Skill'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Get skill
+ description: Get metadata for a specific skill.
+ operationId: get_skill_v1alpha_skills__skill_id__get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
type: string
- title: Id
- completion_window:
+ title: Skill Id
+ post:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/Skill'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Update skill
+ description: Update a skill's default version.
+ operationId: update_skill_v1alpha_skills__skill_id__post
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
type: string
- title: Completion Window
- created_at:
- type: integer
- title: Created At
- endpoint:
+ title: Skill Id
+ requestBody:
+ required: true
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillUpdateRequest'
+ delete:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillDeleteResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Delete skill
+ description: Delete a skill and all its versions.
+ operationId: delete_skill_v1alpha_skills__skill_id__delete
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
type: string
- title: Endpoint
+ title: Skill Id
+ /v1alpha/skills/{skill_id}/content:
+ get:
+ responses:
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ '204':
+ description: The skill bundle as a zip archive.
+ tags:
+ - Skills
+ summary: Get skill content
+ description: Download the default version's zip bundle.
+ operationId: get_skill_content_v1alpha_skills__skill_id__content_get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ /v1alpha/skills/{skill_id}/versions:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/ListSkillVersionsResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: List skill versions
+ description: List all versions of a skill.
+ operationId: list_skill_versions_v1alpha_skills__skill_id__versions_get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: after
+ in: query
+ required: false
+ schema:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ title: After
+ description: Cursor for pagination
+ - name: limit
+ in: query
+ required: false
+ schema:
+ type: integer
+ description: Maximum number of results
+ default: 20
+ title: Limit
+ description: Maximum number of results
+ - name: order
+ in: query
+ required: false
+ schema:
+ enum:
+ - asc
+ - desc
+ type: string
+ description: Sort order by version
+ default: desc
+ title: Order
+ description: Sort order by version
+ post:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillVersion'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Create skill version
+ description: Upload a new version of a skill.
+ operationId: create_skill_version_v1alpha_skills__skill_id__versions_post
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ requestBody:
+ required: true
+ content:
+ multipart/form-data:
+ schema:
+ $ref: '#/components/schemas/Body_create_skill_version_v1alpha_skills__skill_id__versions_post'
+ /v1alpha/skills/{skill_id}/versions/{version}:
+ get:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillVersion'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Get skill version
+ description: Get metadata for a specific skill version.
+ operationId: get_skill_version_v1alpha_skills__skill_id__versions__version__get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: version
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Version
+ delete:
+ responses:
+ '200':
+ description: Successful Response
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/SkillVersionDeleteResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ tags:
+ - Skills
+ summary: Delete skill version
+ description: Delete a specific version of a skill.
+ operationId: delete_skill_version_v1alpha_skills__skill_id__versions__version__delete
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: version
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Version
+ /v1alpha/skills/{skill_id}/versions/{version}/content:
+ get:
+ responses:
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ description: Bad Request
+ '429':
+ $ref: '#/components/responses/TooManyRequests429'
+ description: Too Many Requests
+ '500':
+ $ref: '#/components/responses/InternalServerError500'
+ description: Internal Server Error
+ default:
+ $ref: '#/components/responses/DefaultError'
+ description: Default Response
+ '204':
+ description: The skill bundle as a zip archive.
+ tags:
+ - Skills
+ summary: Get skill version content
+ description: Download a specific version's zip bundle.
+ operationId: get_skill_version_content_v1alpha_skills__skill_id__versions__version__content_get
+ parameters:
+ - name: skill_id
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Skill Id
+ - name: version
+ in: path
+ required: true
+ schema:
+ type: string
+ title: Version
+components:
+ schemas:
+ Error:
+ description: Error response from the API. Roughly follows RFC 7807.
+ properties:
+ status:
+ title: Status
+ type: integer
+ title:
+ title: Title
+ type: string
+ detail:
+ title: Detail
+ type: string
+ instance:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ required:
+ - status
+ - title
+ - detail
+ title: Error
+ type: object
+ ListBatchesResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/Batch'
+ type: array
+ title: Data
+ description: List of batch objects
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first batch in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last batch in the list
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more batches available
+ default: false
+ type: object
+ required:
+ - data
+ title: ListBatchesResponse
+ description: Response containing a list of batch objects.
+ CreateBatchRequest:
+ properties:
+ input_file_id:
+ type: string
+ title: Input File Id
+ description: The ID of an uploaded file containing requests for the batch.
+ endpoint:
+ type: string
+ title: Endpoint
+ description: The endpoint to be used for all requests in the batch.
+ completion_window:
+ type: string
+ title: Completion Window
+ description: The time window within which the batch should be processed.
+ enum:
+ - 24h
+ metadata:
+ anyOf:
+ - additionalProperties:
+ type: string
+ type: object
+ - type: 'null'
+ description: Optional metadata for the batch.
+ idempotency_key:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional idempotency key. When provided, enables idempotent behavior.
+ type: object
+ required:
+ - input_file_id
+ - endpoint
+ - completion_window
+ title: CreateBatchRequest
+ description: Request model for creating a batch.
+ Batch:
+ properties:
+ id:
+ type: string
+ title: Id
+ completion_window:
+ type: string
+ title: Completion Window
+ created_at:
+ type: integer
+ title: Created At
+ endpoint:
+ type: string
+ title: Endpoint
input_file_id:
type: string
title: Input File Id
@@ -5160,7 +5595,7 @@ components:
tool_calls:
description: The tool calls of the delta.
items:
- $ref: '#/components/schemas/ChatCompletionMessageToolCall'
+ $ref: '#/components/schemas/ChoiceDeltaToolCall'
title: Tool Calls
type: array
nullable: true
@@ -6651,25 +7086,25 @@ components:
title: OpenAIFileObject
description: OpenAI File object as defined in the OpenAI Files API.
ExpiresAfter:
+ description: Control expiration of uploaded files.
properties:
anchor:
- type: string
- title: Anchor
description: The anchor point for expiration, must be 'created_at'.
+ title: Anchor
+ type: string
enum:
- created_at
seconds:
- type: integer
- maximum: 2592000.0
- minimum: 3600.0
- title: Seconds
description: Seconds until expiration, between 3600 (1 hour) and 2592000 (30 days).
- type: object
+ maximum: 2592000
+ minimum: 3600
+ title: Seconds
+ type: integer
required:
- anchor
- seconds
title: ExpiresAfter
- description: Control expiration of uploaded files.
+ type: object
OpenAIFileDeleteResponse:
properties:
id:
@@ -7382,6 +7817,10 @@ components:
store:
type: boolean
title: Store
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
input:
items:
$ref: '#/components/schemas/OpenAIResponseMessageOutputUnion'
@@ -7477,6 +7916,7 @@ components:
- medium
- high
- type: 'null'
+ default: medium
type: object
title: OpenAIResponseText
description: Text response configuration for OpenAI responses.
@@ -7795,6 +8235,10 @@ components:
store:
type: boolean
title: Store
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
type: object
required:
- created_at
@@ -10509,8 +10953,24 @@ components:
title: Tools
description: Tools available to the model.
tool_choice:
- title: Tool Choice
+ oneOf:
+ - $ref: '#/components/schemas/_ToolChoiceAuto'
+ title: _ToolChoiceAuto
+ - $ref: '#/components/schemas/_ToolChoiceAny'
+ title: _ToolChoiceAny
+ - $ref: '#/components/schemas/_ToolChoiceNone'
+ title: _ToolChoiceNone
+ - $ref: '#/components/schemas/_ToolChoiceTool'
+ title: _ToolChoiceTool
+ title: _ToolChoiceAuto | ... (4 variants)
description: "How the model should select tools. One of: 'auto', 'any', 'none', or {type: 'tool', name: '...'}."
+ discriminator:
+ propertyName: type
+ mapping:
+ any: '#/components/schemas/_ToolChoiceAny'
+ auto: '#/components/schemas/_ToolChoiceAuto'
+ none: '#/components/schemas/_ToolChoiceNone'
+ tool: '#/components/schemas/_ToolChoiceTool'
stream:
type: boolean
title: Stream
@@ -11125,6 +11585,33 @@ components:
Represents token usage details including input tokens, output tokens, a
breakdown of output tokens, and the total tokens used. Only populated on
batches created after September 7, 2025.
+ Body_create_skill_v1alpha_skills_post:
+ properties:
+ file:
+ type: string
+ title: File
+ description: Zip archive containing the skill bundle.
+ format: binary
+ type: object
+ required:
+ - file
+ title: Body_create_skill_v1alpha_skills_post
+ Body_create_skill_version_v1alpha_skills__skill_id__versions_post:
+ properties:
+ file:
+ type: string
+ title: File
+ description: Zip archive containing the skill bundle.
+ format: binary
+ default:
+ type: boolean
+ title: Default
+ description: Whether to set this version as the default.
+ default: false
+ type: object
+ required:
+ - file
+ title: Body_create_skill_version_v1alpha_skills__skill_id__versions_post
Body_process_file_v1alpha_file_processors_process_post:
properties:
file:
@@ -11163,11 +11650,9 @@ components:
description: The intended purpose of the uploaded file.
expires_after:
anyOf:
- - $ref: '#/components/schemas/ExpiresAfter'
- title: ExpiresAfter
+ - type: string
- type: 'null'
description: Optional expiration settings for the file.
- title: ExpiresAfter
type: object
required:
- file
@@ -11305,52 +11790,55 @@ components:
CompactResponseRequest:
properties:
model:
- type: string
- title: Model
+ anyOf:
+ - $ref: '#/components/schemas/ModelIdsResponses'
+ - type: string
+ - type: 'null'
description: The model to use for generating the compacted summary.
input:
anyOf:
- - type: string
- - items:
- anyOf:
- - oneOf:
- - $ref: '#/components/schemas/OpenAIResponseMessage-Input'
- title: OpenAIResponseMessage-Input
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
- title: OpenAIResponseOutputMessageWebSearchToolCall-Input
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
- title: OpenAIResponseOutputMessageFileSearchToolCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
- title: OpenAIResponseOutputMessageFunctionToolCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
- title: OpenAIResponseOutputMessageMCPCall
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
- title: OpenAIResponseOutputMessageMCPListTools
- - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
- title: OpenAIResponseMCPApprovalRequest
- - $ref: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
- title: OpenAIResponseOutputMessageReasoningItem
- discriminator:
- propertyName: type
- mapping:
- file_search_call: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
- function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
- mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
- mcp_call: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
- mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
- message: '#/components/schemas/OpenAIResponseMessage-Input'
- reasoning: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
- web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
- title: OpenAIResponseMessage-Input | ... (8 variants)
- - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
- title: OpenAIResponseInputFunctionToolCallOutput
- - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
- title: OpenAIResponseMCPApprovalResponse
- - $ref: '#/components/schemas/OpenAIResponseCompaction'
- title: OpenAIResponseCompaction
- title: OpenAIResponseInputFunctionToolCallOutput | OpenAIResponseMCPApprovalResponse | OpenAIResponseCompaction
- type: array
- title: list[OpenAIResponseMessageUnion | OpenAIResponseInputFunctionToolCallOutput | ...]
+ - oneOf:
+ - type: string
+ - items:
+ anyOf:
+ - oneOf:
+ - $ref: '#/components/schemas/OpenAIResponseMessage-Input'
+ title: OpenAIResponseMessage-Input
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
+ title: OpenAIResponseOutputMessageWebSearchToolCall-Input
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
+ title: OpenAIResponseOutputMessageFileSearchToolCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
+ title: OpenAIResponseOutputMessageFunctionToolCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
+ title: OpenAIResponseOutputMessageMCPCall
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
+ title: OpenAIResponseOutputMessageMCPListTools
+ - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
+ title: OpenAIResponseMCPApprovalRequest
+ - $ref: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
+ title: OpenAIResponseOutputMessageReasoningItem
+ discriminator:
+ propertyName: type
+ mapping:
+ file_search_call: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall'
+ function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
+ mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest'
+ mcp_call: '#/components/schemas/OpenAIResponseOutputMessageMCPCall'
+ mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools'
+ message: '#/components/schemas/OpenAIResponseMessage-Input'
+ reasoning: '#/components/schemas/OpenAIResponseOutputMessageReasoningItem'
+ web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall-Input'
+ title: OpenAIResponseMessage-Input | ... (8 variants)
+ - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
+ title: OpenAIResponseInputFunctionToolCallOutput
+ - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse'
+ title: OpenAIResponseMCPApprovalResponse
+ - $ref: '#/components/schemas/OpenAIResponseCompaction'
+ title: OpenAIResponseCompaction
+ title: OpenAIResponseInputFunctionToolCallOutput | OpenAIResponseMCPApprovalResponse | OpenAIResponseCompaction
+ type: array
+ title: list[OpenAIResponseMessageUnion | OpenAIResponseInputFunctionToolCallOutput | ...]
- type: 'null'
title: string | list[OpenAIResponseMessageUnion | OpenAIResponseInputFunctionToolCallOutput | ...]
description: Input message(s) to compact.
@@ -11741,6 +12229,11 @@ components:
type: object
- type: 'null'
description: Dictionary of metadata key-value pairs to attach to the response.
+ safety_identifier:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: A stable identifier used to associate the request with an end user, for safety monitoring. Echoed back on the response.
truncation:
allOf:
- $ref: '#/components/schemas/ResponseTruncation'
@@ -12390,6 +12883,72 @@ components:
- has_more
title: ListMessageBatchesResponse
description: Response from GET /v1/messages/batches.
+ ListSkillVersionsResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/SkillVersion'
+ type: array
+ title: Data
+ description: List of skill version objects
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more results
+ default: false
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first item in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last item in the list
+ type: object
+ required:
+ - data
+ title: ListSkillVersionsResponse
+ description: Response from listing skill versions.
+ ListSkillsResponse:
+ properties:
+ object:
+ type: string
+ title: Object
+ enum:
+ - list
+ data:
+ items:
+ $ref: '#/components/schemas/Skill'
+ type: array
+ title: Data
+ description: List of skill objects
+ has_more:
+ type: boolean
+ title: Has More
+ description: Whether there are more results
+ default: false
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first item in the list
+ last_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the last item in the list
+ type: object
+ required:
+ - data
+ title: ListSkillsResponse
+ description: Response from listing skills.
ListToolsResponse:
properties:
data:
@@ -13711,6 +14270,146 @@ components:
- version
title: SetDefaultVersionBodyRequest
description: Request body model for setting the default version of a prompt.
+ Skill:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: Unique identifier for the skill
+ created_at:
+ type: integer
+ title: Created At
+ description: Unix timestamp when the skill was created
+ default_version:
+ type: string
+ title: Default Version
+ description: Version used when no version is specified
+ default: '1'
+ description:
+ type: string
+ title: Description
+ description: Description of what the skill does
+ latest_version:
+ type: string
+ title: Latest Version
+ description: Most recently uploaded version number
+ default: '1'
+ name:
+ type: string
+ title: Name
+ description: Human-readable name from SKILL.md frontmatter
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill
+ type: object
+ required:
+ - id
+ - created_at
+ - description
+ - name
+ title: Skill
+ description: A skill resource. Matches OpenAI Skill wire format.
+ SkillDeleteResponse:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: ID of the deleted skill
+ deleted:
+ type: boolean
+ title: Deleted
+ description: Whether the skill was successfully deleted
+ default: true
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.deleted
+ type: object
+ required:
+ - id
+ title: SkillDeleteResponse
+ description: Response from deleting a skill. Matches OpenAI DeletedSkill wire format.
+ SkillUpdateRequest:
+ properties:
+ default_version:
+ type: string
+ title: Default Version
+ description: Version number to set as the default
+ type: object
+ required:
+ - default_version
+ title: SkillUpdateRequest
+ description: Request to update a skill's default version.
+ SkillVersion:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: Unique identifier for this version
+ created_at:
+ type: integer
+ title: Created At
+ description: Unix timestamp when this version was created
+ description:
+ type: string
+ title: Description
+ description: Description of the skill version
+ name:
+ type: string
+ title: Name
+ description: Name of the skill version
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.version
+ skill_id:
+ type: string
+ title: Skill Id
+ description: ID of the parent skill
+ version:
+ type: string
+ title: Version
+ description: Version number as a string
+ type: object
+ required:
+ - id
+ - created_at
+ - description
+ - name
+ - skill_id
+ - version
+ title: SkillVersion
+ description: A specific version of a skill. Matches OpenAI SkillVersion wire format.
+ SkillVersionDeleteResponse:
+ properties:
+ id:
+ type: string
+ title: Id
+ description: ID of the deleted skill
+ deleted:
+ type: boolean
+ title: Deleted
+ description: Whether the version was successfully deleted
+ default: true
+ object:
+ type: string
+ title: Object
+ enum:
+ - skill.version.deleted
+ version:
+ type: string
+ title: Version
+ description: Version that was deleted
+ type: object
+ required:
+ - id
+ - version
+ title: SkillVersionDeleteResponse
+ description: Response from deleting a skill version. Matches OpenAI DeletedSkillVersion wire format.
UpdatePromptBodyRequest:
properties:
prompt:
@@ -13967,11 +14666,64 @@ components:
- type: 'null'
timezone:
anyOf:
- - type: string
+ - type: string
+ - type: 'null'
+ type: object
+ title: WebSearchUserLocation
+ description: Approximate user location to refine web search results.
+ _ToolChoiceAny:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - any
+ disable_parallel_tool_use:
+ anyOf:
+ - type: boolean
+ - type: 'null'
+ type: object
+ title: _ToolChoiceAny
+ _ToolChoiceAuto:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - auto
+ disable_parallel_tool_use:
+ anyOf:
+ - type: boolean
+ - type: 'null'
+ type: object
+ title: _ToolChoiceAuto
+ _ToolChoiceNone:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - none
+ type: object
+ title: _ToolChoiceNone
+ _ToolChoiceTool:
+ properties:
+ type:
+ type: string
+ title: Type
+ enum:
+ - tool
+ name:
+ type: string
+ title: Name
+ disable_parallel_tool_use:
+ anyOf:
+ - type: boolean
- type: 'null'
type: object
- title: WebSearchUserLocation
- description: Approximate user location to refine web search results.
+ required:
+ - name
+ title: _ToolChoiceTool
_URLOrData:
properties:
url:
@@ -14622,6 +15374,7 @@ components:
- batches
- vector_io
- tool_runtime
+ - container_runtime
- models
- vector_stores
- tool_groups
@@ -14630,8 +15383,10 @@ components:
- prompts
- conversations
- connectors
+ - containers
- messages
- interactions
+ - skills
- inspect
- admin
title: Api
@@ -15422,219 +16177,929 @@ components:
embedding_model:
title: Embedding Model
type: string
- embedding_dimension:
- title: Embedding Dimension
- type: integer
+ embedding_dimension:
+ title: Embedding Dimension
+ type: integer
+ required:
+ - content
+ - chunk_id
+ - chunk_metadata
+ - embedding
+ - embedding_model
+ - embedding_dimension
+ title: EmbeddedChunk
+ type: object
+ VectorStoreCreateRequest:
+ description: Request to create a vector store.
+ properties:
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ description:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ file_ids:
+ items:
+ type: string
+ title: File Ids
+ type: array
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/VectorStoreExpirationAfter'
+ title: VectorStoreExpirationAfter
+ - type: 'null'
+ nullable: true
+ title: VectorStoreExpirationAfter
+ chunking_strategy:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ metadata:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ title: VectorStoreCreateRequest
+ type: object
+ VectorStoreModifyRequest:
+ description: Request to modify a vector store.
+ properties:
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ nullable: true
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/VectorStoreExpirationAfter'
+ title: VectorStoreExpirationAfter
+ - type: 'null'
+ nullable: true
+ title: VectorStoreExpirationAfter
+ metadata:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ title: VectorStoreModifyRequest
+ type: object
+ VectorStoreSearchRequest:
+ description: Request to search a vector store.
+ properties:
+ query:
+ anyOf:
+ - type: string
+ - items:
+ type: string
+ type: array
+ title: list[string]
+ title: string | list[string]
+ filters:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ max_num_results:
+ default: 10
+ maximum: 50
+ minimum: 1
+ title: Max Num Results
+ type: integer
+ ranking_options:
+ anyOf:
+ - additionalProperties: true
+ type: object
+ - type: 'null'
+ nullable: true
+ rewrite_query:
+ default: false
+ title: Rewrite Query
+ type: boolean
+ required:
+ - query
+ title: VectorStoreSearchRequest
+ type: object
+ ChunkForDeletion:
+ description: Information needed to delete a chunk from a vector store.
+ properties:
+ chunk_id:
+ title: Chunk Id
+ type: string
+ document_id:
+ title: Document Id
+ type: string
+ required:
+ - chunk_id
+ - document_id
+ title: ChunkForDeletion
+ type: object
+ DeleteChunksRequest:
+ description: Request body for deleting chunks from a vector store.
+ properties:
+ vector_store_id:
+ description: The ID of the vector store to delete chunks from.
+ title: Vector Store Id
+ type: string
+ chunks:
+ description: The list of chunks to delete.
+ items:
+ $ref: '#/components/schemas/ChunkForDeletion'
+ title: Chunks
+ type: array
+ required:
+ - vector_store_id
+ - chunks
+ title: DeleteChunksRequest
+ type: object
+ ListBatchesRequest:
+ description: Request model for listing batches.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional cursor for pagination. Returns batches after this ID.
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of batches to return. Defaults to 20.
+ title: Limit
+ type: integer
+ title: ListBatchesRequest
+ type: object
+ RetrieveBatchRequest:
+ description: Request model for retrieving a batch.
+ properties:
+ batch_id:
+ description: The ID of the batch to retrieve.
+ title: Batch Id
+ type: string
+ required:
+ - batch_id
+ title: RetrieveBatchRequest
+ type: object
+ CancelBatchRequest:
+ description: Request model for canceling a batch.
+ properties:
+ batch_id:
+ description: The ID of the batch to cancel.
+ title: Batch Id
+ type: string
+ required:
+ - batch_id
+ title: CancelBatchRequest
+ type: object
+ JobStatus:
+ description: Status of a job execution.
+ enum:
+ - completed
+ - in_progress
+ - failed
+ - scheduled
+ - cancelled
+ title: JobStatus
+ type: string
+ Job:
+ description: A job execution instance with status tracking.
+ properties:
+ job_id:
+ title: Job Id
+ type: string
+ status:
+ $ref: '#/components/schemas/JobStatus'
+ required:
+ - job_id
+ - status
+ title: Job
+ type: object
+ DialogType:
+ description: Parameter type for dialog data with semantic output labels.
+ properties:
+ type:
+ title: Type
+ type: string
+ enum:
+ - dialog
+ title: DialogType
+ type: object
+ ContainerExpiresAfter:
+ description: |-
+ Control expiration of a container.
+
+ Anchored on ``last_active_at`` (each shell execution or file operation
+ refreshes the anchor). Operator-set bounds protect the host from
+ long-lived sandboxes.
+ properties:
+ anchor:
+ description: The anchor point for expiration. Must be 'last_active_at'.
+ title: Anchor
+ type: string
+ enum:
+ - last_active_at
+ minutes:
+ description: Minutes of inactivity after the anchor before the container expires.
+ maximum: 1440
+ minimum: 1
+ title: Minutes
+ type: integer
+ required:
+ - minutes
+ title: ContainerExpiresAfter
+ type: object
+ NetworkCredential:
+ description: |-
+ A named credential available to outbound network calls.
+
+ The ``value`` should be a secret reference (e.g. ``${env.MY_SECRET}``)
+ in operator-supplied configuration, never a raw secret in a request body.
+ properties:
+ name:
+ description: Logical name used by the container to look up the credential.
+ title: Name
+ type: string
+ value:
+ description: Secret reference or literal value to be injected into the container.
+ format: password
+ title: Value
+ type: string
+ writeOnly: true
+ required:
+ - name
+ - value
+ title: NetworkCredential
+ type: object
+ NetworkDomainCredential:
+ description: Bind a ``NetworkCredential`` to a specific outbound domain.
+ properties:
+ domain:
+ description: Fully-qualified domain name to which the credential applies.
+ title: Domain
+ type: string
+ credential:
+ $ref: '#/components/schemas/NetworkCredential'
+ description: Credential injected on outbound calls to this domain.
required:
- - content
- - chunk_id
- - chunk_metadata
- - embedding
- - embedding_model
- - embedding_dimension
- title: EmbeddedChunk
+ - domain
+ - credential
+ title: NetworkDomainCredential
type: object
- VectorStoreCreateRequest:
- description: Request to create a vector store.
+ NetworkPolicyMode:
+ description: Egress policy mode applied to a container's outbound network.
+ enum:
+ - deny
+ - allow_list
+ - allow_all
+ title: NetworkPolicyMode
+ type: string
+ NetworkPolicy:
+ description: |-
+ Operator-set egress policy for a container.
+
+ A NetworkPolicy is the *upper bound* — request-supplied
+ ``NetworkPolicyExtended`` values may only narrow this policy.
+ properties:
+ mode:
+ $ref: '#/components/schemas/NetworkPolicyMode'
+ default: deny
+ description: Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.
+ allow_domains:
+ description: Domains permitted for outbound traffic. Used when mode is 'allow_list'.
+ items:
+ type: string
+ title: Allow Domains
+ type: array
+ deny_domains:
+ description: Domains explicitly blocked. Takes precedence over 'allow_domains'.
+ items:
+ type: string
+ title: Deny Domains
+ type: array
+ title: NetworkPolicy
+ type: object
+ NetworkPolicyExtended:
+ description: |-
+ Request-layer extension of an operator NetworkPolicy.
+
+ The request may add domain credentials and narrow allow/deny lists, but
+ cannot expand the operator default — enforcement is performed at the API
+ layer; see issue #5892 task 8.
+ properties:
+ mode:
+ $ref: '#/components/schemas/NetworkPolicyMode'
+ default: deny
+ description: Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.
+ allow_domains:
+ description: Domains permitted for outbound traffic. Used when mode is 'allow_list'.
+ items:
+ type: string
+ title: Allow Domains
+ type: array
+ deny_domains:
+ description: Domains explicitly blocked. Takes precedence over 'allow_domains'.
+ items:
+ type: string
+ title: Deny Domains
+ type: array
+ domain_credentials:
+ description: Per-domain credentials injected on outbound calls from this container.
+ items:
+ $ref: '#/components/schemas/NetworkDomainCredential'
+ title: Domain Credentials
+ type: array
+ title: NetworkPolicyExtended
+ type: object
+ ContainerStatus:
+ description: Lifecycle status of a container.
+ enum:
+ - active
+ - expired
+ title: ContainerStatus
+ type: string
+ Container:
+ description: |-
+ A sandboxed execution environment.
+
+ Mirrors the OpenAI Containers API resource with OGX-specific extensions
+ for network policy and image selection.
properties:
+ id:
+ description: Identifier for the container.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container'.
+ title: Object
+ type: string
+ enum:
+ - container
+ created_at:
+ description: Unix timestamp (in seconds) for when the container was created.
+ title: Created At
+ type: integer
+ status:
+ $ref: '#/components/schemas/ContainerStatus'
+ description: Current lifecycle status.
+ last_active_at:
+ description: Unix timestamp (in seconds) of the last operation performed against this container.
+ title: Last Active At
+ type: integer
name:
anyOf:
- type: string
- type: 'null'
+ description: Human-readable name for the container.
nullable: true
- description:
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration settings.
+ nullable: true
+ title: ContainerExpiresAfter
+ image:
anyOf:
- type: string
- type: 'null'
+ description: Container image used to run the sandbox. May be operator-locked.
+ nullable: true
+ network_policy:
+ anyOf:
+ - $ref: '#/components/schemas/NetworkPolicy'
+ title: NetworkPolicy
+ - type: 'null'
+ description: Effective network policy after layering operator defaults with request extensions.
+ nullable: true
+ title: NetworkPolicy
+ required:
+ - id
+ - created_at
+ - status
+ - last_active_at
+ title: Container
+ type: object
+ ContainerCreateRequest:
+ description: Request body for ``POST /containers``.
+ properties:
+ name:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Human-readable name for the container.
nullable: true
file_ids:
+ description: Files (from the Files API) to seed into the container at /mnt/data/.
items:
type: string
title: File Ids
type: array
expires_after:
anyOf:
- - $ref: '#/components/schemas/VectorStoreExpirationAfter'
- title: VectorStoreExpirationAfter
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
- type: 'null'
+ description: Inactivity-based expiration settings.
nullable: true
- title: VectorStoreExpirationAfter
- chunking_strategy:
+ title: ContainerExpiresAfter
+ image:
anyOf:
- - additionalProperties: true
- type: object
+ - type: string
- type: 'null'
+ description: Requested container image. The operator policy may pin or reject this value.
nullable: true
- metadata:
+ network_policy:
anyOf:
- - additionalProperties: true
- type: object
+ - $ref: '#/components/schemas/NetworkPolicyExtended'
+ title: NetworkPolicyExtended
- type: 'null'
+ description: Request-supplied network policy extension. Must be a subset of the operator default.
nullable: true
- title: VectorStoreCreateRequest
+ title: NetworkPolicyExtended
+ title: ContainerCreateRequest
type: object
- VectorStoreModifyRequest:
- description: Request to modify a vector store.
+ ListContainersRequest:
+ description: Query parameters for ``GET /containers``.
properties:
- name:
+ after:
anyOf:
- type: string
- type: 'null'
+ description: Cursor for pagination. Returns containers after this ID.
nullable: true
- expires_after:
+ limit:
anyOf:
- - $ref: '#/components/schemas/VectorStoreExpirationAfter'
- title: VectorStoreExpirationAfter
+ - maximum: 100
+ minimum: 1
+ type: integer
- type: 'null'
- nullable: true
- title: VectorStoreExpirationAfter
- metadata:
+ default: 20
+ description: Maximum number of containers to return (1-100).
+ order:
anyOf:
- - additionalProperties: true
- type: object
+ - $ref: '#/components/schemas/Order'
+ title: Order
- type: 'null'
- nullable: true
- title: VectorStoreModifyRequest
+ default: desc
+ description: Sort order by created_at timestamp ('asc' or 'desc').
+ title: Order
+ title: ListContainersRequest
type: object
- VectorStoreSearchRequest:
- description: Request to search a vector store.
+ ListContainersResponse:
+ description: Response for ``GET /containers``.
properties:
- query:
+ object:
+ description: The object type, which is always 'list'.
+ title: Object
+ type: string
+ enum:
+ - list
+ data:
+ description: The list of containers.
+ items:
+ $ref: '#/components/schemas/Container'
+ title: Data
+ type: array
+ first_id:
anyOf:
- type: string
- - items:
- type: string
- type: array
- title: list[string]
- title: string | list[string]
- filters:
+ - type: 'null'
+ description: ID of the first container in the page.
+ nullable: true
+ last_id:
anyOf:
- - additionalProperties: true
- type: object
+ - type: string
- type: 'null'
+ description: ID of the last container in the page.
nullable: true
- max_num_results:
- default: 10
- maximum: 50
- minimum: 1
- title: Max Num Results
+ has_more:
+ description: Whether more containers exist beyond this page.
+ title: Has More
+ type: boolean
+ required:
+ - data
+ - has_more
+ title: ListContainersResponse
+ type: object
+ GetContainerRequest:
+ properties:
+ container_id:
+ description: The ID of the container to retrieve.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: GetContainerRequest
+ type: object
+ DeleteContainerRequest:
+ properties:
+ container_id:
+ description: The ID of the container to delete.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: DeleteContainerRequest
+ type: object
+ ContainerDeleteResponse:
+ description: Response for ``DELETE /containers/{container_id}``.
+ properties:
+ id:
+ description: The container identifier that was deleted.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container'.
+ title: Object
+ type: string
+ enum:
+ - container
+ deleted:
+ description: Whether the container was successfully deleted.
+ title: Deleted
+ type: boolean
+ required:
+ - id
+ - deleted
+ title: ContainerDeleteResponse
+ type: object
+ ContainerFileSource:
+ description: Origin of a file inside a container.
+ enum:
+ - user
+ - assistant
+ title: ContainerFileSource
+ type: string
+ ContainerFile:
+ description: A file present inside a container's filesystem.
+ properties:
+ id:
+ description: Identifier of the container file.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container.file'.
+ title: Object
+ type: string
+ enum:
+ - container.file
+ container_id:
+ description: ID of the container holding the file.
+ title: Container Id
+ type: string
+ created_at:
+ description: Unix timestamp (in seconds) when the file was created.
+ title: Created At
type: integer
- ranking_options:
+ bytes:
+ description: Size of the file in bytes.
+ title: Bytes
+ type: integer
+ path:
+ description: Absolute path to the file inside the container.
+ title: Path
+ type: string
+ source:
+ $ref: '#/components/schemas/ContainerFileSource'
+ description: Whether the file was supplied by the user or written by the model.
+ required:
+ - id
+ - container_id
+ - created_at
+ - bytes
+ - path
+ - source
+ title: ContainerFile
+ type: object
+ UploadContainerFileRequest:
+ description: |-
+ Path parameters for ``POST /containers/{container_id}/files``.
+
+ The file content itself is supplied as a multipart upload and not part of
+ this Pydantic body; see ``fastapi_routes.py``.
+ properties:
+ container_id:
+ description: The ID of the container to upload into.
+ title: Container Id
+ type: string
+ required:
+ - container_id
+ title: UploadContainerFileRequest
+ type: object
+ ListContainerFilesRequest:
+ properties:
+ container_id:
+ description: The ID of the container whose files should be listed.
+ title: Container Id
+ type: string
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination.
+ nullable: true
+ limit:
+ anyOf:
+ - maximum: 100
+ minimum: 1
+ type: integer
+ - type: 'null'
+ default: 20
+ description: Maximum number of files to return (1-100).
+ order:
+ anyOf:
+ - $ref: '#/components/schemas/Order'
+ title: Order
+ - type: 'null'
+ default: desc
+ description: Sort order by created_at timestamp.
+ title: Order
+ required:
+ - container_id
+ title: ListContainerFilesRequest
+ type: object
+ ListContainerFilesResponse:
+ properties:
+ object:
+ description: The object type, which is always 'list'.
+ title: Object
+ type: string
+ enum:
+ - list
+ data:
+ description: The list of files in the container.
+ items:
+ $ref: '#/components/schemas/ContainerFile'
+ title: Data
+ type: array
+ first_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the first file in the page.
+ nullable: true
+ last_id:
anyOf:
- - additionalProperties: true
- type: object
+ - type: string
- type: 'null'
+ description: ID of the last file in the page.
nullable: true
- rewrite_query:
- default: false
- title: Rewrite Query
+ has_more:
+ description: Whether more files exist beyond this page.
+ title: Has More
type: boolean
required:
- - query
- title: VectorStoreSearchRequest
+ - data
+ - has_more
+ title: ListContainerFilesResponse
type: object
- ChunkForDeletion:
- description: Information needed to delete a chunk from a vector store.
+ GetContainerFileRequest:
properties:
- chunk_id:
- title: Chunk Id
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
type: string
- document_id:
- title: Document Id
+ file_id:
+ description: The ID of the container file to retrieve.
+ title: File Id
type: string
required:
- - chunk_id
- - document_id
- title: ChunkForDeletion
+ - container_id
+ - file_id
+ title: GetContainerFileRequest
type: object
- DeleteChunksRequest:
- description: Request body for deleting chunks from a vector store.
+ GetContainerFileContentRequest:
properties:
- vector_store_id:
- description: The ID of the vector store to delete chunks from.
- title: Vector Store Id
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to download.
+ title: File Id
type: string
- chunks:
- description: The list of chunks to delete.
- items:
- $ref: '#/components/schemas/ChunkForDeletion'
- title: Chunks
- type: array
required:
- - vector_store_id
- - chunks
- title: DeleteChunksRequest
+ - container_id
+ - file_id
+ title: GetContainerFileContentRequest
type: object
- ListBatchesRequest:
- description: Request model for listing batches.
+ DeleteContainerFileRequest:
properties:
- after:
+ container_id:
+ description: The ID of the container holding the file.
+ title: Container Id
+ type: string
+ file_id:
+ description: The ID of the container file to delete.
+ title: File Id
+ type: string
+ required:
+ - container_id
+ - file_id
+ title: DeleteContainerFileRequest
+ type: object
+ ContainerFileDeleteResponse:
+ properties:
+ id:
+ description: The container file identifier that was deleted.
+ title: Id
+ type: string
+ object:
+ description: The object type, which is always 'container.file'.
+ title: Object
+ type: string
+ enum:
+ - container.file
+ deleted:
+ description: Whether the file was successfully deleted.
+ title: Deleted
+ type: boolean
+ required:
+ - id
+ - deleted
+ title: ContainerFileDeleteResponse
+ type: object
+ ShellEnvironmentContainerAuto:
+ description: |-
+ Provider-managed container environment.
+
+ The provider lazily creates and reuses a container for the calling
+ response chain. Useful when the caller does not need to persist or
+ reference the container across responses.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - container_auto
+ image:
anyOf:
- type: string
- type: 'null'
- description: Optional cursor for pagination. Returns batches after this ID.
+ description: Optional preferred container image.
nullable: true
- limit:
- default: 20
- description: Maximum number of batches to return. Defaults to 20.
- title: Limit
- type: integer
- title: ListBatchesRequest
+ expires_after:
+ anyOf:
+ - $ref: '#/components/schemas/ContainerExpiresAfter'
+ title: ContainerExpiresAfter
+ - type: 'null'
+ description: Inactivity-based expiration for the auto-created container.
+ nullable: true
+ title: ContainerExpiresAfter
+ title: ShellEnvironmentContainerAuto
type: object
- RetrieveBatchRequest:
- description: Request model for retrieving a batch.
+ ShellEnvironmentContainerReference:
+ description: Reference an existing container by ID.
properties:
- batch_id:
- description: The ID of the batch to retrieve.
- title: Batch Id
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - container_reference
+ container_id:
+ description: The ID of an existing container to execute inside.
+ title: Container Id
type: string
required:
- - batch_id
- title: RetrieveBatchRequest
+ - container_id
+ title: ShellEnvironmentContainerReference
type: object
- CancelBatchRequest:
- description: Request model for canceling a batch.
+ ShellEnvironmentLocal:
+ description: |-
+ Local (non-container) execution mode.
+
+ Only available when the operator has explicitly enabled local mode in
+ the ContainerRuntime provider configuration.
properties:
- batch_id:
- description: The ID of the batch to cancel.
- title: Batch Id
+ type:
+ description: Discriminator.
+ title: Type
type: string
- required:
- - batch_id
- title: CancelBatchRequest
+ enum:
+ - local
+ working_directory:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Optional working directory for local execution.
+ nullable: true
+ title: ShellEnvironmentLocal
type: object
- JobStatus:
- description: Status of a job execution.
- enum:
- - completed
- - in_progress
- - failed
- - scheduled
- - cancelled
- title: JobStatus
- type: string
- Job:
- description: A job execution instance with status tracking.
+ ShellOutcomeSuccess:
+ description: Process exited cleanly with status 0.
properties:
- job_id:
- title: Job Id
+ type:
+ description: Discriminator.
+ title: Type
type: string
- status:
- $ref: '#/components/schemas/JobStatus'
+ enum:
+ - success
+ exit_code:
+ description: Process exit code (always 0 for success).
+ title: Exit Code
+ type: integer
+ enum:
+ - 0
+ title: ShellOutcomeSuccess
+ type: object
+ ShellOutcomeFailure:
+ description: Process exited with a non-zero status.
+ properties:
+ type:
+ description: Discriminator.
+ title: Type
+ type: string
+ enum:
+ - failure
+ exit_code:
+ description: Process exit code.
+ title: Exit Code
+ type: integer
+ reason:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Human-readable failure reason, if known.
+ nullable: true
required:
- - job_id
- - status
- title: Job
+ - exit_code
+ title: ShellOutcomeFailure
type: object
- DialogType:
- description: Parameter type for dialog data with semantic output labels.
+ ShellOutcomeTimeout:
+ description: Process was terminated for exceeding its time budget.
properties:
type:
+ description: Discriminator.
title: Type
type: string
enum:
- - dialog
- title: DialogType
+ - timeout
+ elapsed_seconds:
+ description: Wall-clock seconds elapsed before termination.
+ title: Elapsed Seconds
+ type: number
+ required:
+ - elapsed_seconds
+ title: ShellOutcomeTimeout
+ type: object
+ ShellCallOutput:
+ description: |-
+ Captured output of a single shell execution.
+
+ Consumed by the Responses provider to construct ``ShellCallOutputItem``
+ entries on the output stream.
+ properties:
+ stdout:
+ description: UTF-8 decoded standard output (truncated by the runtime if oversized).
+ title: Stdout
+ type: string
+ stderr:
+ description: UTF-8 decoded standard error (truncated by the runtime if oversized).
+ title: Stderr
+ type: string
+ outcome:
+ description: How the shell process terminated.
+ discriminator:
+ mapping:
+ failure: '#/components/schemas/ShellOutcomeFailure'
+ success: '#/components/schemas/ShellOutcomeSuccess'
+ timeout: '#/components/schemas/ShellOutcomeTimeout'
+ propertyName: type
+ oneOf:
+ - $ref: '#/components/schemas/ShellOutcomeSuccess'
+ title: ShellOutcomeSuccess
+ - $ref: '#/components/schemas/ShellOutcomeFailure'
+ title: ShellOutcomeFailure
+ - $ref: '#/components/schemas/ShellOutcomeTimeout'
+ title: ShellOutcomeTimeout
+ title: ShellOutcomeSuccess | ShellOutcomeFailure | ShellOutcomeTimeout
+ duration_ms:
+ description: Wall-clock duration of the shell call in milliseconds.
+ minimum: 0
+ title: Duration Ms
+ type: integer
+ container_id:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: ID of the container the call executed in, when applicable. Null for local mode.
+ nullable: true
+ required:
+ - stdout
+ - stderr
+ - outcome
+ - duration_ms
+ title: ShellCallOutput
type: object
ConversationMessage:
description: OpenAI-compatible message item for conversations.
@@ -16030,6 +17495,68 @@ components:
- prompt_id
title: DeletePromptRequest
type: object
+ SkillVersionCreateRequest:
+ description: Request to create a new skill version. Matches OpenAI VersionCreateParams.
+ properties:
+ default:
+ type: boolean
+ default: false
+ description: Whether to set this version as the default
+ title: Default
+ title: SkillVersionCreateRequest
+ type: object
+ ListSkillsRequest:
+ description: Request parameters for listing skills.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of results
+ maximum: 100
+ minimum: 1
+ title: Limit
+ type: integer
+ order:
+ default: desc
+ description: Sort order by created_at
+ enum:
+ - asc
+ - desc
+ title: Order
+ type: string
+ title: ListSkillsRequest
+ type: object
+ ListSkillVersionsRequest:
+ description: Request parameters for listing skill versions.
+ properties:
+ after:
+ anyOf:
+ - type: string
+ - type: 'null'
+ description: Cursor for pagination
+ nullable: true
+ limit:
+ default: 20
+ description: Maximum number of results
+ maximum: 100
+ minimum: 1
+ title: Limit
+ type: integer
+ order:
+ default: desc
+ description: Sort order by version
+ enum:
+ - asc
+ - desc
+ title: Order
+ type: string
+ title: ListSkillVersionsRequest
+ type: object
OpenAIResponseMessageOutputUnion:
anyOf:
- oneOf:
@@ -16163,6 +17690,46 @@ components:
- type
- custom
description: A call to a custom tool created by the model.
+ ChoiceDeltaToolCall:
+ properties:
+ id:
+ anyOf:
+ - type: string
+ description: Unique identifier for the tool call.
+ - type: 'null'
+ description: Unique identifier for the tool call.
+ type:
+ anyOf:
+ - type: string
+ description: Must be 'function' to identify this as a function call.
+ enum:
+ - function
+ - type: 'null'
+ description: Must be 'function' to identify this as a function call.
+ function:
+ anyOf:
+ - properties:
+ name:
+ type: string
+ title: Name
+ description: Name of the function to call.
+ arguments:
+ type: string
+ title: Arguments
+ description: Arguments to pass to the function as a JSON string.
+ type: object
+ - type: 'null'
+ description: Function call details.
+ index:
+ type: integer
+ description: The index of the tool call being streamed.
+ type: object
+ description: A tool call delta in a streaming chat completion chunk.
+ required:
+ - index
+ ModelIdsResponses:
+ type: string
+ description: Model identifier.
responses:
BadRequest400:
description: The request was invalid or malformed
@@ -16261,6 +17828,8 @@ tags:
- description: Tool listing and management.
name: Tools
x-displayName: Tools
+- description: OpenAI-compatible vector store management and search.
+ name: Vector Stores
- description: ''
name: VectorIO
- description: OpenAI Responses API for agent orchestration with tool use, multi-turn conversations, and background processing.
@@ -16287,6 +17856,7 @@ x-tagGroups:
- ToolGroups
- ToolRuntime
- Tools
+ - Vector Stores
- VectorIO
security:
- Default: []
diff --git a/paper.bib b/paper.bib
new file mode 100644
index 00000000000..12e22eaf68c
--- /dev/null
+++ b/paper.bib
@@ -0,0 +1,188 @@
+@misc{ogx,
+ author = {{OGX Contributors}},
+ title = {{OGX} (Open GenAI Stack)},
+ year = {2026},
+ url = {https://github.com/ogx-ai/ogx},
+ note = {Formerly Llama Stack. \url{https://github.com/ogx-ai/ogx}}
+}
+
+@misc{ogxk8soperator,
+ author = {{OGX Contributors}},
+ title = {{OGX} Kubernetes Operator},
+ year = {2026},
+ url = {https://github.com/ogx-ai/ogx-k8s-operator},
+ note = {\url{https://github.com/ogx-ai/ogx-k8s-operator}}
+}
+
+@inproceedings{arceo2026securing,
+ author = {Arceo, Francisco Javier and Narsing, Varsha Prasad},
+ title = {Securing the Agent: Vendor-Neutral, Multitenant Enterprise Retrieval and Tool Use},
+ booktitle = {Proceedings of the ACM Conference on AI and Agentic Systems},
+ series = {ACM Conference on AI and Agentic Systems},
+ year = {2026},
+ isbn = {9798400724152},
+ publisher = {Association for Computing Machinery},
+ address = {New York, NY, USA},
+ pages = {862--872},
+ numpages = {11},
+ doi = {10.1145/3786335.3813145},
+ url = {https://doi.org/10.1145/3786335.3813145}
+}
+
+@manual{openresponses,
+ author = {{Open Responses Community}},
+ title = {Open Responses Specification},
+ year = {2026},
+ url = {https://www.openresponses.org/},
+ note = {\url{https://www.openresponses.org/}}
+}
+
+@inproceedings{kwon2023vllm,
+ author = {Kwon, Woosuk and Li, Zhuohan and Zhuang, Siyuan and Sheng, Ying and Zheng, Lianmin and Yu, Cody Hao and Gonzalez, Joseph E. and Zhang, Hao and Stoica, Ion},
+ title = {Efficient Memory Management for Large Language Model Serving with {PagedAttention}},
+ booktitle = {Proceedings of the 29th ACM Symposium on Operating Systems Principles},
+ year = {2023},
+ publisher = {Association for Computing Machinery},
+ address = {New York, NY, USA},
+ pages = {611--626},
+ doi = {10.1145/3600006.3613165}
+}
+
+@inproceedings{sglang,
+ author = {Zheng, Lianmin and Yin, Liangsheng and Xie, Zhiqiang and Huang, Jeff and Sun, Chuyue and Yu, Cody Hao and Cao, Shiyi and Kober, Christos and Shi, Liang and Wu, Chien-Sheng and Zhang, Hao and Sheng, Ying and Gonzalez, Joseph E. and Stoica, Ion and Ma, Wei-Lin},
+ title = {{SGLang}: Efficient Execution of Structured Language Model Programs},
+ booktitle = {Advances in Neural Information Processing Systems},
+ year = {2024},
+ volume = {37},
+ publisher = {Curran Associates, Inc.}
+}
+
+@manual{openaiResponsesAPI,
+ author = {{OpenAI}},
+ title = {Responses {API} Reference},
+ year = {2025},
+ url = {https://platform.openai.com/docs/api-reference/responses},
+ note = {\url{https://platform.openai.com/docs/api-reference/responses}}
+}
+
+@manual{mcp,
+ title = {Model Context Protocol Specification},
+ author = {{Anthropic}},
+ year = {2026},
+ url = {https://modelcontextprotocol.io/specification/},
+ note = {\url{https://modelcontextprotocol.io/specification/}}
+}
+
+@misc{langchain,
+ author = {{LangChain, Inc.}},
+ title = {{LangChain}: Build context-aware reasoning applications},
+ year = {2023},
+ url = {https://github.com/langchain-ai/langchain},
+ note = {\url{https://github.com/langchain-ai/langchain}}
+}
+
+@misc{langgraph,
+ author = {{LangChain, Inc.}},
+ title = {{LangGraph}: Build resilient language agents as graphs},
+ year = {2024},
+ url = {https://github.com/langchain-ai/langgraph},
+ note = {\url{https://github.com/langchain-ai/langgraph}}
+}
+
+@misc{llamaindex,
+ author = {{LlamaIndex}},
+ title = {{LlamaIndex}: Data framework for {LLM} applications},
+ year = {2022},
+ url = {https://github.com/run-llama/llama_index},
+ note = {\url{https://github.com/run-llama/llama_index}}
+}
+
+@misc{crewai,
+ author = {{CrewAI, Inc.}},
+ title = {{CrewAI}: Framework for orchestrating role-playing autonomous {AI} agents},
+ year = {2024},
+ url = {https://github.com/crewAIInc/crewAI},
+ note = {\url{https://github.com/crewAIInc/crewAI}}
+}
+
+@misc{haystack,
+ author = {{deepset}},
+ title = {{Haystack}: End-to-end {LLM} framework for building production-ready applications},
+ year = {2023},
+ url = {https://github.com/deepset-ai/haystack},
+ note = {\url{https://github.com/deepset-ai/haystack}}
+}
+
+@manual{databricksAgentFramework,
+ author = {{Databricks}},
+ title = {{Mosaic AI Agent Framework}},
+ year = {2025},
+ url = {https://www.databricks.com/product/machine-learning/retrieval-augmented-generation},
+ note = {\url{https://www.databricks.com/product/machine-learning/retrieval-augmented-generation}}
+}
+
+@misc{sqlitevec,
+ author = {Alex Garcia},
+ title = {sqlite-vec: A vector search {SQLite} extension},
+ year = {2024},
+ url = {https://github.com/asg017/sqlite-vec},
+ note = {\url{https://github.com/asg017/sqlite-vec}}
+}
+
+@article{mlflow,
+ author = {Zaharia, Matei A. and Chen, Andrew and Davidson, Aaron and Ghodsi, Ali and Hong, Sue Ann and Konwinski, Andy and Murching, Siddharth and Nykodym, Tomas and Ogilvie, Paul and Parkhe, Mani and Xie, Fen and Zumar, Corey},
+ title = {{Accelerating the Machine Learning Lifecycle with MLflow}},
+ journal = {IEEE Data Eng. Bull.},
+ volume = {41},
+ pages = {39--45},
+ year = {2018},
+ url = {https://api.semanticscholar.org/CorpusID:83459546}
+}
+
+@misc{llamastack,
+ author = {{Llama Stack Contributors}},
+ title = {Llama Stack},
+ year = {2025},
+ url = {https://github.com/llamastack/llama-stack},
+ note = {\url{https://github.com/llamastack/llama-stack}}
+}
+
+@misc{ibm_rag_milvus,
+ author = {{IBM Community}},
+ title = {Build {RAG} with {Llama Stack} and watsonx.data {Milvus}},
+ year = {2025},
+ url = {https://community.ibm.com/community/user/blogs/divya13/2025/05/08/build-rag-with-llama-stack-and-watsonxdata-milvus},
+ note = {\url{https://community.ibm.com/community/user/blogs/divya13/2025/05/08/build-rag-with-llama-stack-and-watsonxdata-milvus}}
+}
+
+@misc{oracle_oci_ogx,
+ author = {{Oracle}},
+ title = {Accelerating Enterprise Gen {AI} Applications Development on {OCI} with {Llama Stack} and {OCI AI} Blueprints},
+ year = {2025},
+ url = {https://blogs.oracle.com/ai-and-datascience/accelerating-enterprise-gen-ai-applications-development-on-oci-with-llama-stack-and-oci-ai-blueprints},
+ note = {\url{https://blogs.oracle.com/ai-and-datascience/accelerating-enterprise-gen-ai-applications-development-on-oci-with-llama-stack-and-oci-ai-blueprints}}
+}
+
+@misc{redhat_ops_agent,
+ author = {{Red Hat}},
+ title = {Generative {AI} Applications with {Llama Stack}: A Notebook-Guided Journey to an Intelligent Operations Agent},
+ year = {2025},
+ url = {https://www.redhat.com/en/blog/generative-ai-applications-llama-stack-notebook-guided-journey-intelligent-operations-agent},
+ note = {\url{https://www.redhat.com/en/blog/generative-ai-applications-llama-stack-notebook-guided-journey-intelligent-operations-agent}}
+}
+
+@misc{meta_connect_ogx,
+ author = {{Meta}},
+ title = {Llama Stack: Chapter One},
+ year = {2024},
+ url = {https://developers.facebook.com/m/meta-connect-developer-sessions/llama-stack-chapter-one/},
+ note = {\url{https://developers.facebook.com/m/meta-connect-developer-sessions/llama-stack-chapter-one/}}
+}
+
+@misc{ibm_techxchange_ogx,
+ author = {Clyburn, Cedric},
+ title = {Llama Stack: Kubernetes for {RAG} and {AI} Agents in Generative {AI}},
+ year = {2025},
+ url = {https://mediacenter.ibm.com/media/Llama+Stack+Kubernetes+for+RAG+AI+Agents+in+Generative+AI/1_xl78upq2},
+ note = {\url{https://mediacenter.ibm.com/media/Llama+Stack+Kubernetes+for+RAG+AI+Agents+in+Generative+AI/1_xl78upq2}}
+}
diff --git a/paper.md b/paper.md
new file mode 100644
index 00000000000..c92aee21605
--- /dev/null
+++ b/paper.md
@@ -0,0 +1,149 @@
+---
+title: 'OGX: An Open-Source, Vendor-Neutral Generative AI Application Server'
+tags:
+ - Python
+ - artificial intelligence
+ - large language models
+ - agentic AI
+ - retrieval-augmented generation
+ - OpenAI API
+ - server-side orchestration
+ - Kubernetes
+ - multitenancy
+authors:
+ - name: Francisco Javier Arceo
+ orcid: 0009-0009-7432-2006
+ affiliation: 1
+ corresponding: true
+ - name: Sébastien Han
+ affiliation: 1
+ - name: Matthew Farrellee
+ affiliation: 3
+ - name: Charlie Doern
+ affiliation: 1
+ - name: Yuan Tang
+ affiliation: 1
+ - name: Derek Higgins
+ affiliation: 1
+ - name: Varsha Prasad Narsing
+ orcid: 0009-0006-4421-3632
+ affiliation: 1
+ - name: Gordon Sim
+ affiliation: 1
+ - name: Sumanth Kamenani
+ affiliation: 1
+ - name: Ben Browning
+ affiliation: 1
+ - name: Raghotham Murthy
+ affiliation: 2
+affiliations:
+ - name: Red Hat AI, USA
+ index: 1
+ - name: Meta, USA
+ index: 2
+ - name: Independent
+ index: 3
+date: 2 June 2026
+bibliography: paper.bib
+---
+
+# Summary
+
+OGX (Open GenAI Stack), formerly Llama Stack [@llamastack], is an open-source AI application server and Python library that implements the APIs of major frontier labs (OpenAI, Anthropic, Google) with pluggable backend providers [@ogx]. Teams building agentic AI applications---such as retrieval-augmented generation (RAG) pipelines, multi-turn conversational agents, and tool-calling workflows---can develop against a single, stable API surface and deploy with any combination of inference engine, vector database, and safety backend, without changing application code.
+
+OGX's primary API focus is the Responses API for server-side agentic orchestration, conforming to the Open Responses specification [@openresponses]. The server also exposes Chat Completions, Embeddings, Vector Stores, Files, and Batches endpoints. Beyond OpenAI compatibility, OGX natively supports the Anthropic Messages API (`/v1/messages`) and Google GenAI Interactions API (`/v1alpha/interactions`), allowing teams using any of the three major client SDKs to connect to the same server. OGX supports over 20 inference providers (including vLLM, Ollama, OpenAI, Anthropic, Bedrock, and Gemini), 13 vector store backends, and 7 safety providers. It can run as an HTTP server for production deployments or be imported directly as a Python library for scripting and notebooks. A companion Kubernetes Operator [@ogxk8soperator] automates deployment lifecycle management through custom resources, supporting multi-architecture builds, hot-swappable distribution images, and both shared and per-tenant isolation topologies. Together, OGX and its operator serve as the self-hosted, model-agnostic backend for AI-powered developer tools such as Claude Code, Codex CLI, OpenCode, and OpenHands.
+
+# Statement of Need
+
+AI application development today is tightly coupled to proprietary API providers. While inference-only workloads can increasingly be swapped across providers---vLLM, for example, supports the Responses API for basic inference---applications that rely on the full stack (retrieval, tool calling, conversation state, safety guardrails) remain difficult to migrate without rewriting significant application logic. This coupling limits reproducibility, makes comparisons across model providers difficult, and prevents teams from running AI workloads on controlled infrastructure---a requirement in regulated, privacy-sensitive, and air-gapped environments.
+
+Existing open-source tools address parts of this problem but not the whole. Inference engines like vLLM [@kwon2023vllm] and SGLang [@sglang] serve models efficiently but do not provide retrieval, tool calling, or conversation management. Gateway proxies like LiteLLM route requests across providers but do not execute the agentic loop or manage vector stores. Client-side frameworks like LangChain [@langchain] and LangGraph [@langgraph] provide developer abstractions but push orchestration, state management, and security enforcement to the application layer.
+
+OGX fills this gap by providing a complete, self-hosted AI application server that implements the OpenAI API surface---with the Responses API as its primary focus---alongside Anthropic Messages and Google GenAI Interactions compatibility layers. Developers write code against standard endpoints (`/v1/responses`, `/v1/chat/completions`, `/v1/vector_stores`) and swap the underlying infrastructure through configuration, not code changes. This decouples three decisions that are currently entangled: which SDK to use, which model to run, and where to deploy.
+
+# State of the Field
+
+The AI application ecosystem has stratified into layers that each solve a subset of the deployment problem. OGX continues the Llama Stack project under a renamed, model-agnostic mission; the relevant comparison is therefore the server-side API layer that OGX provides versus adjacent inference engines, gateways, and client-side frameworks.
+
+**Inference engines** (vLLM [@kwon2023vllm], SGLang [@sglang], Ollama) focus on efficient model serving. They optimize throughput and latency but do not provide retrieval, conversation state, tool execution, or safety guardrails. An application using vLLM for inference must separately integrate a vector database, implement its own agentic loop, and manage multi-turn state.
+
+**API gateways** (LiteLLM, OpenRouter) provide a unified interface across multiple inference providers but act as pass-through proxies. They do not manage vector stores, execute tool calls, or maintain conversation history---they translate request formats between SDKs and providers.
+
+**Client-side frameworks** (LangChain [@langchain], LangGraph [@langgraph], LlamaIndex [@llamaindex], CrewAI [@crewai], Haystack [@haystack]) provide rich developer abstractions for building agents and RAG pipelines. However, they execute orchestration client-side, distributing security-critical logic across application code. These frameworks are complementary to OGX: they compose agent logic while OGX provides the server-side execution target they call into.
+
+**Proprietary platforms** (OpenAI's Responses API [@openaiResponsesAPI], Databricks Mosaic AI [@databricksAgentFramework]) offer integrated experiences but couple applications to a specific vendor's infrastructure and pricing.
+
+OGX occupies a distinct position: a self-hosted, vendor-neutral server that implements the full API surface---inference, retrieval, tool execution, conversation management, and safety---with pluggable providers at every layer. Its conformance to the Open Responses specification [@openresponses] ensures interoperability with any client that speaks the same protocol. It does not compete with client-side frameworks; it is the infrastructure they deploy against when reproducibility, provider portability, and centralized policy enforcement matter.
+
+# Software Design
+
+## Provider Architecture
+
+OGX's core abstraction is the pluggable provider. Each API capability (inference, vector storage, safety, tool runtime, file processing) is defined by a Protocol interface in the lightweight `ogx-api` package, allowing third-party providers to implement the contract without depending on the full server. Concrete providers implement these interfaces for specific backends: `remote::openai` and `remote::anthropic` for hosted APIs, `remote::vllm` for self-hosted GPU inference, `inline::faiss` and `remote::pgvector` for vector search, and so on. A routing layer dispatches requests to provider instances based on logical resource identifiers, enabling multiple providers to serve the same API simultaneously---for example, Ollama handling local models while OpenAI handles hosted models, both behind `/v1/chat/completions`.
+
+A *distribution* packages a specific set of providers and configuration into a deployable unit, decoupling application logic from infrastructure selection. This design favors reproducible configuration over ad hoc application code: teams can prototype with lightweight inline providers (Ollama, sqlite-vec [@sqlitevec]) and deploy to production backends (vLLM, pgvector) by changing the distribution, not the application.
+
+## Dual Deployment Model
+
+OGX runs in two modes. **Server mode** exposes HTTP endpoints accessible from any language or tool. **Library mode** allows direct Python import with zero network overhead, suitable for notebooks and scripts. Both modes use identical provider routing and API semantics.
+
+## Multi-SDK Compatibility
+
+OGX serves three client SDK protocols from a single server. The **OpenAI-compatible endpoints** (`/v1/chat/completions`, `/v1/responses`, `/v1/vector_stores`) are the primary interface and the Responses API implementation conforms to the Open Responses specification [@openresponses]. The **Anthropic Messages endpoint** (`/v1/messages`) and **Google GenAI Interactions endpoint** (`/v1alpha/interactions`) provide native compatibility for teams using those SDKs. This portability comes with a trade-off: OGX must normalize provider-specific behavior into stable API contracts while still exposing enough backend-specific configuration for real deployments.
+
+## Server-Side Agentic Orchestration
+
+The Responses API implements server-side agentic orchestration: the inference-tool-inference loop executes within the server process, not the client [@openaiResponsesAPI]. This centralizes security enforcement, tool authorization, and conversation state management, at the cost of moving some flexibility from application code into server configuration. Built-in tools include file search (RAG over vector stores), web search, code interpretation, and Model Context Protocol (MCP) [@mcp] integration for external tool servers.
+
+OGX is extending server-side execution with a Containers API and a Skills API. The Containers API (`/v1/containers`) manages sandboxed execution environments---matching the OpenAI Containers API---enabling models to execute shell commands in isolated Docker, Podman, or Kubernetes containers via a `shell` tool in the Responses API. The Skills API (`/v1alpha/skills`) manages versioned skill bundles that package tools, prompts, and configuration into reusable, composable units. Together, these APIs move code execution and task composition onto the server, extending the same trust-boundary principle that governs retrieval and tool authorization.
+
+Unlike inference engines and API gateways that treat requests as stateless, OGX manages state natively: the Conversations API persists multi-turn history with tenant-scoped isolation, the Prompts API provides versioned prompt templates, and a resource registry tracks models, vector stores, and files as first-class server objects. A Compaction API summarizes long histories to manage context window limits. Telemetry is built on OpenTelemetry (OTEL) with MLflow [@mlflow] tracing integration for logging spans, tool calls, and retrieval steps to existing ML experiment tracking infrastructure. This state and observability layer is what makes OGX a complete application server rather than a stateless proxy.
+
+For multitenant deployments, OGX provides attribute-based access control (ABAC) that enforces tenant isolation at the retrieval, tool execution, state management, and API routing layers. The security properties of this architecture have been formally analyzed and empirically validated [@arceo2026securing].
+
+## Kubernetes Operator
+
+The OGX Kubernetes Operator [@ogxk8soperator] provides declarative deployment through the `OGXServer` custom resource. A single CR specifies the distribution, replica count, storage, inference backend, and network policies. The operator manages full lifecycle reconciliation with support for both vanilla Kubernetes and OpenShift, ConfigMap-driven image overrides for fleet-wide updates, multi-architecture builds (amd64/arm64) with FIPS-compliant images, and shared instances with ABAC isolation, per-tenant namespace isolation, and hybrid topologies.
+
+# Example Usage
+
+The following example demonstrates building a RAG agent using the standard OpenAI SDK against an OGX server. The same code works regardless of which inference provider or vector store backend is configured:
+
+```python
+from openai import OpenAI
+
+client = OpenAI(base_url="http://localhost:8321/v1", api_key="unused")
+
+# Create a vector store and upload documents
+vector_store = client.vector_stores.create(name="docs")
+with open("manual.pdf", "rb") as file:
+ client.vector_stores.files.upload(vector_store_id=vector_store.id, file=file)
+
+# Query with server-side RAG via the Responses API
+response = client.responses.create(
+ model="meta-llama/Llama-3.2-3B-Instruct",
+ input="What are the installation requirements?",
+ tools=[{"type": "file_search", "vector_store_ids": [vector_store.id]}],
+)
+print(response.output_text)
+```
+
+Switching from a local Ollama backend to a production vLLM cluster requires changing only the server's distribution configuration---the client code above remains identical. Published tutorials demonstrate this portability across diverse enterprise backends, including IBM watsonx.ai with Milvus vector storage [@ibm_rag_milvus] and Oracle Cloud Infrastructure with OCI AI Blueprints [@oracle_oci_ogx].
+
+# Research Impact Statement
+
+OGX has realized impact through both public deployments and customer production use. Publicly documented examples under the former Llama Stack name include an intelligent OpenShift operations agent combining RAG, web search, and MCP tool integration for automated incident response [@redhat_ops_agent], enterprise RAG pipelines on IBM watsonx.data with Milvus [@ibm_rag_milvus], and generative AI application development on Oracle Cloud Infrastructure [@oracle_oci_ogx]. Maintainers report production deployments with customers in telecommunications, semiconductor manufacturing, financial services, insurance, and consulting. The framework has been presented at Meta Connect [@meta_connect_ogx] and IBM TechXchange [@ibm_techxchange_ogx] as a standardization layer for enterprise AI applications.
+
+The security architecture---specifically, the multitenant isolation model combining ABAC-gated retrieval, server-side orchestration, and pluggable provider backends---was formally analyzed in a peer-reviewed publication at the ACM Conference on AI and Agentic Systems [@arceo2026securing]. OGX conforms to the Open Responses specification [@openresponses] and serves as a reference implementation for open, vendor-neutral agentic AI APIs.
+
+As of June 2026, the project has over 8,400 GitHub stars, 242 contributors, 4,000 commits, and 68 releases across nearly two years of public development. Community engagement includes weekly contributor calls, an active Discord server, and integrations contributed by external organizations including Red Hat, IBM, Oracle, and Infinispan.
+
+# AI Usage Disclosure
+
+Generative AI tools, including GitHub Copilot and Anthropic Claude models available during development, were used for code completion, documentation drafting, and paper drafting. Assistance was limited to generating candidate text or code that human contributors reviewed, edited, tested, and validated. Core architectural decisions, API design, the security model, and final paper content were made by human authors.
+
+# Acknowledgements
+
+We thank Meta for creating and open-sourcing Llama Stack, now renamed OGX. We are grateful to Red Hat for supporting the development of OGX through employee time and infrastructure support. We thank the OGX contributor community for their sustained contributions to the project.
+
+# References
diff --git a/paper/ogx.bbl b/paper/ogx.bbl
new file mode 100644
index 00000000000..113a781270f
--- /dev/null
+++ b/paper/ogx.bbl
@@ -0,0 +1,126 @@
+\begin{thebibliography}{10}
+
+\bibitem{mcp}
+{Anthropic}.
+\newblock {\em Model Context Protocol Specification}, 2026.
+\newblock \url{https://modelcontextprotocol.io/specification/}.
+
+\bibitem{arceo2026securing}
+Francisco~Javier Arceo and Varsha~Prasad Narsing.
+\newblock Securing the agent: Vendor-neutral, multitenant enterprise retrieval
+ and tool use.
+\newblock In {\em Proceedings of the ACM Conference on AI and Agentic Systems},
+ CAIS '26, pages 862--872, New York, NY, USA, 2026. Association for Computing
+ Machinery.
+
+\bibitem{ibm_techxchange_ogx}
+Cedric Clyburn.
+\newblock Llama stack: Kubernetes for {RAG} and {AI} agents in generative {AI},
+ 2025.
+\newblock
+ \url{https://mediacenter.ibm.com/media/Llama+Stack+Kubernetes+for+RAG+AI+Agents+in+Generative+AI/1_xl78upq2}.
+
+\bibitem{crewai}
+{CrewAI, Inc.}
+\newblock {CrewAI}: Framework for orchestrating role-playing autonomous {AI}
+ agents, 2024.
+\newblock \url{https://github.com/crewAIInc/crewAI}.
+
+\bibitem{databricksAgentFramework}
+{Databricks}.
+\newblock {\em {Mosaic AI Agent Framework}}, 2025.
+\newblock
+ \url{https://www.databricks.com/product/machine-learning/retrieval-augmented-generation}.
+
+\bibitem{haystack}
+{deepset}.
+\newblock {Haystack}: End-to-end {LLM} framework for building production-ready
+ applications, 2023.
+\newblock \url{https://github.com/deepset-ai/haystack}.
+
+\bibitem{sqlitevec}
+Alex Garcia.
+\newblock sqlite-vec: A vector search {SQLite} extension, 2024.
+\newblock \url{https://github.com/asg017/sqlite-vec}.
+
+\bibitem{ibm_rag_milvus}
+{IBM Community}.
+\newblock Build {RAG} with {Llama Stack} and watsonx.data {Milvus}, 2025.
+\newblock
+ \url{https://community.ibm.com/community/user/blogs/divya13/2025/05/08/build-rag-with-llama-stack-and-watsonxdata-milvus}.
+
+\bibitem{kwon2023vllm}
+Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody~Hao Yu,
+ Joseph~E. Gonzalez, Hao Zhang, and Ion Stoica.
+\newblock Efficient memory management for large language model serving with
+ {PagedAttention}.
+\newblock In {\em Proceedings of the 29th ACM Symposium on Operating Systems
+ Principles}, pages 611--626, New York, NY, USA, 2023. Association for
+ Computing Machinery.
+
+\bibitem{langchain}
+{LangChain, Inc.}
+\newblock {LangChain}: Build context-aware reasoning applications, 2023.
+\newblock \url{https://github.com/langchain-ai/langchain}.
+
+\bibitem{langgraph}
+{LangChain, Inc.}
+\newblock {LangGraph}: Build resilient language agents as graphs, 2024.
+\newblock \url{https://github.com/langchain-ai/langgraph}.
+
+\bibitem{llamaindex}
+{LlamaIndex}.
+\newblock {LlamaIndex}: Data framework for {LLM} applications, 2022.
+\newblock \url{https://github.com/run-llama/llama_index}.
+
+\bibitem{meta_connect_ogx}
+{Meta}.
+\newblock Llama stack: Chapter one, 2024.
+\newblock
+ \url{https://developers.facebook.com/m/meta-connect-developer-sessions/llama-stack-chapter-one/}.
+
+\bibitem{ogxk8soperator}
+{OGX Contributors}.
+\newblock {OGX} kubernetes operator, 2026.
+\newblock \url{https://github.com/ogx-ai/ogx-k8s-operator}.
+
+\bibitem{openresponses}
+{Open Responses Community}.
+\newblock {\em Open Responses Specification}, 2026.
+\newblock \url{https://www.openresponses.org/}.
+
+\bibitem{openaiResponsesAPI}
+{OpenAI}.
+\newblock {\em Responses {API} Reference}, 2025.
+\newblock \url{https://platform.openai.com/docs/api-reference/responses}.
+
+\bibitem{oracle_oci_ogx}
+{Oracle}.
+\newblock Accelerating enterprise gen {AI} applications development on {OCI}
+ with {Llama Stack} and {OCI AI} blueprints, 2025.
+\newblock
+ \url{https://blogs.oracle.com/ai-and-datascience/accelerating-enterprise-gen-ai-applications-development-on-oci-with-llama-stack-and-oci-ai-blueprints}.
+
+\bibitem{redhat_ops_agent}
+{Red Hat}.
+\newblock Generative {AI} applications with {Llama Stack}: A notebook-guided
+ journey to an intelligent operations agent, 2025.
+\newblock
+ \url{https://www.redhat.com/en/blog/generative-ai-applications-llama-stack-notebook-guided-journey-intelligent-operations-agent}.
+
+\bibitem{mlflow}
+Matei~A. Zaharia, Andrew Chen, Aaron Davidson, Ali Ghodsi, Sue~Ann Hong, Andy
+ Konwinski, Siddharth Murching, Tomas Nykodym, Paul Ogilvie, Mani Parkhe, Fen
+ Xie, and Corey Zumar.
+\newblock {Accelerating the Machine Learning Lifecycle with MLflow}.
+\newblock {\em IEEE Data Eng. Bull.}, 41:39--45, 2018.
+
+\bibitem{sglang}
+Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, Jeff Huang, Chuyue Sun, Cody~Hao
+ Yu, Shiyi Cao, Christos Kober, Liang Shi, Chien-Sheng Wu, Hao Zhang, Ying
+ Sheng, Joseph~E. Gonzalez, Ion Stoica, and Wei-Lin Ma.
+\newblock {SGLang}: Efficient execution of structured language model programs.
+\newblock In {\em Advances in Neural Information Processing Systems},
+ volume~37. Curran Associates, Inc., 2024.
+
+\end{thebibliography}
diff --git a/paper/ogx.pdf b/paper/ogx.pdf
new file mode 100644
index 00000000000..6ef9f4cad6c
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diff --git a/paper/ogx.tex b/paper/ogx.tex
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index 00000000000..d4c2c87322b
--- /dev/null
+++ b/paper/ogx.tex
@@ -0,0 +1,387 @@
+\documentclass[11pt]{article}
+
+\usepackage[margin=1in]{geometry}
+\usepackage{lmodern}
+\usepackage[hyphens,spaces]{url}
+\usepackage{hyperref}
+\usepackage{tabularx}
+\usepackage{booktabs}
+\usepackage{xcolor}
+\usepackage{caption}
+\usepackage{enumitem}
+\usepackage{amssymb}
+\usepackage{tikz}
+\usetikzlibrary{
+ patterns,
+ positioning,
+ arrows.meta,
+ shapes.geometric,
+ shapes.symbols,
+ fit,
+ calc,
+ backgrounds
+}
+
+\definecolor{ProviderBlue}{RGB}{170,220,255}
+\definecolor{APIBlue}{RGB}{50,110,255}
+\definecolor{ToolsPurple}{RGB}{190,175,255}
+\definecolor{ToolYellow}{RGB}{245,235,170}
+\definecolor{ServerGreen}{RGB}{40,160,70}
+\definecolor{ClientOrange}{RGB}{245,166,35}
+
+\title{OGX: An Open-Source, Vendor-Neutral Generative AI Application Server}
+
+\author{}
+\date{June 2026}
+
+\makeatletter
+\renewcommand{\maketitle}{%
+ \begin{center}
+ {\LARGE\bfseries \@title\footnote{OGX (Open GenAI Stack): \url{https://github.com/ogx-ai/ogx} \,|\, Docs: \url{https://ogx-ai.github.io}} \par}
+ \vspace{1em}
+ {\large
+ Francisco Javier Arceo\textsuperscript{1},
+ S\'ebastien Han\textsuperscript{1},
+ Matthew Farrellee\textsuperscript{3},
+ Charlie Doern\textsuperscript{1},
+ Yuan Tang\textsuperscript{1},
+ Derek Higgins\textsuperscript{1},
+ Varsha Prasad Narsing\textsuperscript{1},
+ Gordon Sim\textsuperscript{1},
+ Sumanth Kamenani\textsuperscript{1},
+ Ben Browning\textsuperscript{1},
+ Raghotham Murthy\textsuperscript{2}
+ \par}
+ \vspace{0.5em}
+ {\normalsize \textsuperscript{1}Red Hat AI \quad \textsuperscript{2}Meta \quad \textsuperscript{3}Independent \par}
+ \vspace{0.5em}
+ {\normalsize \@date \par}
+ \end{center}
+ \vspace{1.5em}
+}
+\makeatother
+
+\begin{document}
+\maketitle
+
+\begin{abstract}
+OGX (Open GenAI Stack) is an open-source AI application server and Python library that implements the APIs of major frontier labs (OpenAI, Anthropic, Google) with pluggable backend providers. Developers building agentic AI applications---such as retrieval-augmented generation pipelines, multi-turn agents, and tool-calling workflows---can develop against a single API surface and deploy with any combination of inference engine, vector database, and safety backend, without changing application code. OGX's primary focus is the Responses API for server-side agentic orchestration, conforming to the Open Responses specification. The server also supports the Anthropic Messages API and Google GenAI Interactions API, decoupling SDK choice from model and deployment decisions. With over 20 inference providers, 13 vector store backends, and a companion Kubernetes Operator for production deployment, OGX serves as the self-hosted, model-agnostic backend for AI-powered developer tools including Claude Code, Codex CLI, OpenCode, and OpenHands. The project has over 8,400 GitHub stars, 242 contributors, and 4,000 commits across nearly two years of public development.
+\end{abstract}
+
+%% ============================================================
+\section{Introduction}
+
+AI application development today is tightly coupled to proprietary API providers. While inference-only workloads can increasingly be swapped across providers---vLLM, for example, supports the Responses API for basic inference---applications that rely on the full stack (retrieval, tool calling, conversation state, safety guardrails) remain difficult to migrate without rewriting significant application logic. This coupling limits deployment flexibility and prevents organizations from running AI workloads on their own infrastructure---a requirement in regulated industries and air-gapped environments.
+
+The problem is compounded by the emergence of AI-powered developer tools. Tools like Claude Code, Codex CLI, OpenCode, and OpenHands need a backend that can serve models, execute tools, manage conversation state, and handle retrieval---all through standard APIs. Organizations that want to self-host these capabilities currently must assemble and integrate multiple systems: an inference engine, a vector database, a tool execution runtime, and custom glue code to connect them.
+
+OGX addresses this by providing a complete, self-hosted AI application server that implements the OpenAI API surface---with the Responses API as its primary focus---alongside Anthropic Messages and Google GenAI Interactions compatibility layers. It decouples three decisions that are currently entangled: which SDK to use, which model to run, and where to deploy. Developers write code against standard endpoints and swap the underlying infrastructure through configuration, not code changes.
+
+This paper describes OGX's design, architecture, and positioning in the AI application ecosystem. Section~\ref{sec:field} surveys the state of the field. Section~\ref{sec:design} details the software design. Section~\ref{sec:operator} describes the Kubernetes Operator. Section~\ref{sec:impact} discusses research impact and adoption.
+
+%% ============================================================
+\section{State of the Field}
+\label{sec:field}
+
+The AI application ecosystem has stratified into layers that each solve a subset of the deployment problem. Table~\ref{tab:comparison} summarizes the landscape.
+
+\textbf{Inference engines} (vLLM~\cite{kwon2023vllm}, SGLang~\cite{sglang}, Ollama) focus on efficient model serving. They optimize throughput and latency but do not provide retrieval, conversation state, tool execution, or safety guardrails. An application using vLLM for inference must separately integrate a vector database, implement its own agentic loop, and manage multi-turn state.
+
+\textbf{API gateways} (LiteLLM, OpenRouter) provide a unified interface across multiple inference providers but act as pass-through proxies. They do not manage vector stores, execute tool calls, or maintain conversation history---they translate request formats between SDKs and providers.
+
+\textbf{Client-side frameworks} (LangChain~\cite{langchain}, LangGraph~\cite{langgraph}, LlamaIndex~\cite{llamaindex}, CrewAI~\cite{crewai}, Haystack~\cite{haystack}) provide rich developer abstractions for building agents and RAG pipelines. However, they execute orchestration client-side, distributing security-critical logic across application code. These frameworks are complementary to OGX: they compose agent logic while OGX provides the server-side execution target they call into.
+
+\textbf{Proprietary platforms} (OpenAI's Responses API~\cite{openaiResponsesAPI}, Databricks Mosaic AI~\cite{databricksAgentFramework}) offer integrated experiences but couple applications to a specific vendor's infrastructure and pricing.
+
+OGX occupies a distinct position: a self-hosted, vendor-neutral server that implements the full API surface---inference, retrieval, tool execution, conversation management, and safety---with pluggable providers at every layer. Its conformance to the Open Responses specification~\cite{openresponses} ensures interoperability with any client that speaks the same protocol.
+
+\begin{table}[htbp]
+ \centering
+ \small
+ \setlength{\tabcolsep}{4pt}
+ \renewcommand{\arraystretch}{1.15}
+ \begin{tabularx}{\textwidth}{@{}l|ccccc>{\raggedright\arraybackslash}X@{}}
+ \toprule
+ System & Inference & RAG & Tools & State & Safety & Deployment \\
+ \midrule
+ vLLM / SGLang & $\checkmark$ & -- & -- & -- & -- & Self-hosted \\
+ Ollama & $\checkmark$ & -- & -- & -- & -- & Local \\
+ LiteLLM & $\checkmark$$^*$ & -- & -- & -- & -- & Gateway \\
+ LangChain / LangGraph & $\checkmark$$^*$ & $\checkmark$ & $\checkmark$ & $\checkmark$ & -- & Client-side \\
+ OpenAI Platform & $\checkmark$ & $\checkmark$ & $\checkmark$ & $\checkmark$ & $\checkmark$ & SaaS \\
+ \textbf{OGX} & $\checkmark$ & $\checkmark$ & $\checkmark$ & $\checkmark$ & $\checkmark$ & Local \& Self-hosted \\
+ \bottomrule
+ \end{tabularx}
+ \caption{Feature comparison across AI application system categories. $^*$Proxy/wrapper---delegates to external provider.}
+ \label{tab:comparison}
+\end{table}
+
+%% ============================================================
+\section{Software Design}
+\label{sec:design}
+
+\subsection{Provider Architecture}
+
+OGX's core abstraction is the pluggable provider. Each API capability---inference, vector storage, safety, tool runtime, file processing---is defined by a Protocol interface. Concrete providers implement these interfaces for specific backends (Figure~\ref{fig:provider-arch}):
+\begin{itemize}[nosep]
+ \item \textbf{Inference:} \texttt{remote::openai}, \texttt{remote::anthropic}, \texttt{remote::vllm}, \texttt{remote::ollama}, \texttt{remote::bedrock}, \texttt{remote::ge\-mi\-ni}, and 15+ others.
+ \item \textbf{Vector stores:} \texttt{inline::faiss}, \texttt{inline::sqlite-vec}, \texttt{remote::pgvector}, \texttt{remote::qdrant}, \texttt{remote::milvus}, \texttt{remote::weaviate}, \texttt{remote::chromadb}, and others.
+ \item \textbf{Safety:} Content moderation providers for input/output guardrails.
+ \item \textbf{Tools:} Built-in tools (file search, web search, code interpreter) and MCP~\cite{mcp} integration for external tool servers.
+\end{itemize}
+
+A routing layer dispatches requests to provider instances based on logical resource identifiers, enabling multiple providers to serve the same API simultaneously. For example, Ollama can handle local models while OpenAI handles hosted models, both behind \texttt{/v1/chat/completions}. The routing table tracks which provider owns each resource (model, vector store, file), enabling auto-dispatch without client-side logic.
+
+\begin{figure}[htbp]
+ \centering
+ \resizebox{\textwidth}{!}{%
+ \begin{tikzpicture}[
+ box/.style={draw, rounded corners=4pt, minimum height=10mm,
+ align=center, font=\small},
+ provider/.style={draw, rounded corners=3pt, minimum width=16mm, minimum height=8mm,
+ align=center, font=\footnotesize, fill=ProviderBlue!40},
+ arrow/.style={-{Stealth[length=2mm]}, thick},
+ ]
+ % Top row: clients and harnesses centered around 0
+ \node[box, fill=gray!15, minimum width=42mm] (client) at (-3,4) {Client SDKs\\{\scriptsize OpenAI / Anthropic / Google}};
+ \node[box, fill=gray!15, minimum width=42mm] (harness) at (3,4) {Coding Harnesses\\{\scriptsize Claude Code / Codex / OpenCode}};
+
+ % API layer and router
+ \node[box, fill=ToolYellow!60, minimum width=88mm] (api) at (0,2.5)
+ {OGX API Layer\\{\scriptsize\texttt{/v1/responses} ~ \texttt{/v1/chat/completions} ~ \texttt{/v1/messages} ~ \texttt{/v1/vector\_stores} ~ \texttt{/v1/files}}};
+
+ \node[box, fill=ClientOrange!25, minimum width=88mm] (router) at (0,1)
+ {Provider Router\\{\scriptsize resource $\rightarrow$ provider dispatch}};
+
+ % 7 providers centered: positions at -6, -4, -2, 0, 2, 4, 6
+ \node[provider] (p1) at (-6,-0.8) {vLLM};
+ \node[provider] (p2) at (-4,-0.8) {Ollama};
+ \node[provider] (p3) at (-2,-0.8) {OpenAI};
+ \node[provider, fill=ToolsPurple!40] (p4) at (0,-0.8) {pgvector};
+ \node[provider, fill=ToolsPurple!40] (p5) at (2,-0.8) {FAISS};
+ \node[provider, fill=ServerGreen!25] (p6) at (4,-0.8) {S3};
+ \node[provider, fill=ServerGreen!25] (p7) at (6,-0.8) {localFS};
+
+ % Arrows
+ \draw[arrow] (client) -- (api);
+ \draw[arrow] (harness) -- (api);
+ \draw[arrow] (api) -- (router);
+ \draw[arrow] (router.south) -- (p1.north);
+ \draw[arrow] (router.south) -- (p2.north);
+ \draw[arrow] (router.south) -- (p3.north);
+ \draw[arrow] (router.south) -- (p4.north);
+ \draw[arrow] (router.south) -- (p5.north);
+ \draw[arrow] (router.south) -- (p6.north);
+ \draw[arrow] (router.south) -- (p7.north);
+
+ % Legend in a box
+ \node[draw, rounded corners=4pt, inner sep=5pt, fill=white] (legend) at (0,-2.5) {%
+ \begin{tikzpicture}[baseline=0pt]
+ \node[font=\scriptsize\bfseries, anchor=east] at (0,0) {Legend:};
+ \node[provider, minimum width=14mm, minimum height=5mm, font=\scriptsize, anchor=west] at (0.2,0) {Inference};
+ \node[provider, fill=ToolsPurple!40, minimum width=18mm, minimum height=5mm, font=\scriptsize, anchor=west] at (2.0,0) {Vector Stores};
+ \node[provider, fill=ServerGreen!25, minimum width=12mm, minimum height=5mm, font=\scriptsize, anchor=west] at (4.2,0) {Files};
+ \end{tikzpicture}%
+ };
+ \end{tikzpicture}%
+ }
+ \caption{Provider architecture: client requests are dispatched through the API layer and router to pluggable backend providers. Representative APIs and providers shown; OGX additionally exposes Containers, Skills, Safety, Prompts, Conversations, and Telemetry APIs.}
+ \label{fig:provider-arch}
+\end{figure}
+
+\subsection{Distributions}
+
+A \emph{distribution} packages a specific set of providers and configuration into a deployable unit, decoupling application logic from infrastructure selection. Developers prototype with lightweight inline providers (Ollama for inference, sqlite-vec~\cite{sqlitevec} for vectors) and deploy to production backends (vLLM~\cite{kwon2023vllm}, pgvector) by changing the distribution configuration, not the application code. OGX ships a \texttt{starter} distribution for quick setup and supports custom distributions for production environments.
+
+\subsection{Dual Deployment Model}
+
+OGX runs in two modes:
+\begin{itemize}[nosep]
+ \item \textbf{Server mode:} HTTP endpoints accessible from any language or tool. This is the production deployment model.
+ \item \textbf{Library mode:} Direct Python import with zero network overhead. Suitable for notebooks, scripts, and rapid prototyping.
+\end{itemize}
+Both modes use identical provider routing and API semantics. The recommended progression is: start with the library for prototyping, graduate to the server when you need multi-language access, scaling, or production isolation.
+
+\subsection{Multi-SDK Compatibility}
+
+OGX serves three client SDK protocols from a single server instance:
+\begin{itemize}[nosep]
+ \item \textbf{OpenAI-compatible endpoints} (\texttt{/v1/chat/completions}, \texttt{/v1/responses}, \texttt{/v1/vector\_stores}): the primary interface. The Responses API implementation conforms to the Open Responses specification~\cite{openresponses}.
+ \item \textbf{Anthropic Messages endpoint} (\texttt{/v1/messages}): native compatibility for teams using the Anthropic SDK.
+ \item \textbf{Google GenAI Interactions endpoint} (\texttt{/v1alpha/interactions}): native compatibility for teams using the Google GenAI SDK.
+\end{itemize}
+
+This means SDK choice, model selection, and deployment target are fully independent decisions. A team can use the Anthropic SDK to call an open-weight model served by vLLM through OGX, or use the OpenAI SDK to call Anthropic's Claude---the server handles the translation.
+
+\subsection{Server-Side Agentic Orchestration}
+
+The Responses API~\cite{openaiResponsesAPI} is OGX's primary API focus and implements server-side agentic orchestration: the inference$\rightarrow$tool$\rightarrow$inference loop executes within the server process, not the client. This design centralizes several critical concerns:
+
+\begin{itemize}[nosep]
+ \item \textbf{Tool authorization:} Tool calls are executed server-side with centralized authorization, not delegated to potentially untrusted clients.
+ \item \textbf{Conversation state:} Multi-turn state is managed server-side with tenant-scoped isolation.
+ \item \textbf{Safety guardrails:} Input and output safety checks are applied at each step of the agentic loop.
+ \item \textbf{Context management:} A Compaction API summarizes long conversation histories to manage context window limits.
+\end{itemize}
+
+Built-in tools include file search (RAG over vector stores with hybrid dense/sparse retrieval), web search, code interpretation, computer use, and Model Context Protocol (MCP)~\cite{mcp} integration for external tool servers.
+
+For multitenant deployments, OGX provides attribute-based access control (ABAC) that enforces tenant isolation at the retrieval, tool execution, state management, and API routing layers. The security properties of this architecture---specifically, how ABAC-gated retrieval eliminates cross-tenant data leakage while adding negligible overhead---have been formally analyzed and empirically validated~\cite{arceo2026securing}.
+
+\subsection{API Surface}
+
+OGX exposes over 20 APIs covering the full lifecycle of AI applications (Table~\ref{tab:apis}):
+
+\begin{itemize}[nosep]
+ \item \textbf{Inference APIs:} Chat Completions and Embeddings provide standard inference endpoints. The Responses API serves as the central agentic orchestration endpoint, coordinating multi-turn conversations, tool calling, and server-side execution~\cite{openaiResponsesAPI}.
+ \item \textbf{Data APIs:} Vector Stores and Search APIs support dense, sparse, and hybrid retrieval with structured metadata filtering for tenant isolation. The Files and File Processors APIs provide tenant-scoped file storage (S3, GCS, PVCs, local filesystem) with parsing and chunking for vector store ingestion. The Batches API supports offline processing.
+ \item \textbf{Agent and Tool APIs:} Built-in tools include file search (RAG over vector stores), web search, code interpreter, shell (via Containers), image generation, and computer use. External tools integrate via MCP~\cite{mcp}. Function Calling and Connectors enable custom tool integration.
+ \item \textbf{Execution APIs:} The Containers API (\texttt{/v1/containers}) manages sandboxed execution environments---matching the OpenAI Containers API---enabling models to execute shell commands in isolated Docker, Podman, or Kubernetes containers via a \texttt{shell} tool in the Responses API. The Skills API (\texttt{/v1alpha/skills}) manages versioned skill bundles that package tools, prompts, and configuration into reusable, composable units for domain-specific capabilities.
+ \item \textbf{State APIs:} The Conversations API persists multi-turn history with tenant-scoped isolation, eliminating client-side session stores. The Prompts API provides versioned prompt template management. A resource registry tracks models, vector stores, files, and tool groups as first-class server objects with ownership metadata. The Compaction API automatically summarizes long conversation histories to manage context window limits. This server-side state layer is a distinguishing feature---most inference engines and API gateways treat requests as stateless, requiring applications to build their own persistence. OGX manages this natively, enabling it to function as a complete application server rather than a stateless proxy.
+ \item \textbf{Safety APIs:} Content moderation providers apply input and output guardrails at each step of the agentic loop.
+ \item \textbf{Admin APIs:} Model registry for managing available models across providers. Telemetry via OpenTelemetry (OTEL) for observability and tracing of agent execution, with built-in MLflow~\cite{mlflow} tracing integration (which supports OTEL) for logging spans, tool calls, and retrieval steps to existing ML experiment tracking infrastructure.
+\end{itemize}
+
+\begin{table}[htbp]
+ \centering
+ \small
+ \setlength{\tabcolsep}{4pt}
+ \renewcommand{\arraystretch}{1.15}
+ \begin{tabularx}{\textwidth}{@{}l|X@{}}
+ \toprule
+ Category & APIs \\
+ \midrule
+ Inference & Chat Completions, Responses (agentic orchestration), Embeddings \\
+ Data & Vector Stores, Search, Files, File Processors, Batches \\
+ Agent/Tools & File search, web search, code interpreter, shell, image generation, computer use, MCP, Function Calling, Connectors \\
+ Execution & Containers (sandboxed environments), Skills (versioned bundles) \\
+ State & Conversations, Prompts, Compaction, Resource Registry \\
+ Safety & Content moderation (input/output guardrails) \\
+ Admin & Models, Telemetry (OTEL, MLflow tracing) \\
+ \bottomrule
+ \end{tabularx}
+ \caption{OGX API surface organized by category.}
+ \label{tab:apis}
+\end{table}
+
+%% ============================================================
+\section{Example Usage}
+\label{sec:examples}
+
+The following examples demonstrate OGX's portability: the same client code works regardless of which inference provider or vector store backend is configured on the server.
+
+\subsection{RAG Agent with the OpenAI SDK}
+
+Building a RAG agent requires only standard OpenAI SDK calls. The server handles document chunking, embedding, vector storage, retrieval, and context injection transparently:
+
+\begin{verbatim}
+from openai import OpenAI
+
+client = OpenAI(base_url="http://localhost:8321/v1",
+ api_key="unused")
+
+# Create a vector store and upload documents
+vector_store = client.vector_stores.create(name="docs")
+client.vector_stores.files.upload(
+ vector_store_id=vector_store.id,
+ file=open("manual.pdf", "rb"),
+)
+
+# Query with server-side RAG via the Responses API
+response = client.responses.create(
+ model="meta-llama/Llama-3.2-3B-Instruct",
+ input="What are the installation requirements?",
+ tools=[{"type": "file_search",
+ "vector_store_ids": [vector_store.id]}],
+)
+print(response.output_text)
+\end{verbatim}
+
+Switching from a local Ollama backend to a production vLLM cluster requires changing only the server's distribution configuration---the client code above remains identical.
+
+\subsection{Published Use Cases}
+
+OGX's provider portability has been demonstrated across diverse enterprise backends:
+
+\begin{itemize}[nosep]
+ \item \textbf{IBM watsonx.ai + Milvus:} Enterprise RAG pipeline using watsonx.ai for inference and watsonx.data Milvus for vector storage, with Llama Stack as the unifying orchestration layer~\cite{ibm_rag_milvus}.
+ \item \textbf{Oracle Cloud Infrastructure:} Generative AI application development using OCI AI Blueprints with Llama Stack for standardized API access~\cite{oracle_oci_ogx}.
+ \item \textbf{Red Hat OpenShift:} An intelligent operations agent combining agentic RAG, web search, and MCP tool integration (OpenShift cluster management, Slack notifications) for automated incident response~\cite{redhat_ops_agent}.
+\end{itemize}
+
+The framework has been presented at Meta Connect~\cite{meta_connect_ogx} and IBM TechXchange~\cite{ibm_techxchange_ogx} as a standardization layer for enterprise AI applications.
+
+%% ============================================================
+\section{Kubernetes Operator}
+\label{sec:operator}
+
+The OGX Kubernetes Operator~\cite{ogxk8soperator} provides declarative, production-grade deployment through the \texttt{OGXServer} custom resource definition (CRD). Written in Go using the operator-sdk framework, it automates the full lifecycle of OGX server deployments on Kubernetes and OpenShift.
+
+\subsection{Custom Resource Model}
+
+A single \texttt{OGXServer} CR specifies:
+\begin{itemize}[nosep]
+ \item \textbf{Distribution:} Which AI stack variant to deploy (e.g., \texttt{starter}, custom distributions).
+ \item \textbf{Workload:} Replica count, persistent storage size and mount paths, environment variable overrides for inference model configuration.
+ \item \textbf{Network:} External access configuration (hostname-based routing) and network policies (enabled by default per-CR).
+\end{itemize}
+
+The operator reconciles the desired state expressed in the CR with the actual cluster state, handling creation, scaling, updates, and teardown of OGX server pods.
+
+\subsection{Operational Features}
+
+\begin{itemize}[nosep]
+ \item \textbf{ConfigMap-driven image overrides:} Administrators update the \texttt{ogx-operator-config} ConfigMap with an \texttt{image-overrides} key, and all matching \texttt{OGXServer} resources restart with the new image---enabling fleet-wide image updates without redeploying the operator.
+ \item \textbf{ConfigMap-based configuration:} Users supply \texttt{config.yaml} content via ConfigMaps; the operator watches for changes and automatically restarts pods to load updated configuration.
+ \item \textbf{Multi-architecture builds:} Supports \texttt{linux/amd64} and \texttt{linux/arm64} with FIPS-compliant images built using native architecture-matched CI runners.
+ \item \textbf{Dual platform support:} First-class support for both vanilla Kubernetes (using cert-manager for webhook TLS) and OpenShift (using built-in service-serving-cert-signer).
+ \item \textbf{Quickstart scripts:} \texttt{hack/deploy-quickstart.sh} enables rapid setup with provider and model flags.
+\end{itemize}
+
+\subsection{Isolation Topologies}
+
+The operator supports three deployment topologies:
+\begin{enumerate}[nosep]
+ \item \textbf{Shared instances:} Multiple tenants share a single OGX server with ABAC-enforced logical isolation.
+ \item \textbf{Per-tenant instances:} Namespace-level isolation with Kubernetes RBAC, each tenant receiving a dedicated OGX server.
+ \item \textbf{Hybrid:} Shared inference with per-tenant data paths, balancing cost efficiency with isolation requirements.
+\end{enumerate}
+
+%% ============================================================
+\section{Research Impact and Adoption}
+\label{sec:impact}
+
+\subsection{Production Deployments}
+
+OGX is deployed in production across enterprises in telecommunications, semiconductor manufacturing, financial services, insurance, and consulting. These deployments use the full stack: pluggable inference providers, tenant-isolated vector stores, server-side agentic orchestration, and Kubernetes-based deployment via the operator. Published use cases span IBM watsonx.ai with Milvus vector storage~\cite{ibm_rag_milvus}, Oracle Cloud Infrastructure with OCI AI Blueprints~\cite{oracle_oci_ogx}, and Red Hat OpenShift with MCP-based operational agents~\cite{redhat_ops_agent}.
+
+\subsection{Academic Validation}
+
+The security architecture of OGX's multitenant isolation model was formally analyzed and empirically validated in a peer-reviewed publication at the ACM Conference on AI and Agentic Systems (CAIS '26)~\cite{arceo2026securing}. The evaluation demonstrated that ABAC-gated retrieval eliminates cross-tenant data leakage (0\% cross-tenant leakage rate) while adding approximately 19ms to the search path. The defense operates at the retrieval layer, making it resilient to prompt injection attacks regardless of model behavior.
+
+\subsection{Community and Ecosystem}
+
+As of June 2026, the project has:
+\begin{itemize}[nosep]
+ \item Over 8,400 GitHub stars and 1,300 forks.
+ \item 242 unique contributors and over 4,000 commits.
+ \item 68 releases across nearly two years of public development (since July 2024).
+ \item Weekly community contributor calls and an active Discord server.
+ \item Integrations contributed by external organizations including Red Hat, IBM, Oracle, and Infinispan.
+\end{itemize}
+
+OGX conforms to the Open Responses specification~\cite{openresponses} and serves as a reference implementation for open, vendor-neutral agentic AI APIs.
+
+\subsection{AI-Powered Developer Tools}
+
+OGX is designed to serve as the backend for AI-powered developer tools that implement OpenAI-compatible APIs, including Claude Code, Codex CLI, OpenCode, and OpenHands. By providing a self-hosted, model-agnostic server that speaks these protocols, OGX enables organizations to use these tools with any model on their own infrastructure.
+
+%% ============================================================
+\section{Acknowledgements}
+
+We thank Meta for creating and open-sourcing Llama Stack, the foundation from which OGX evolved. We are grateful to Red Hat for supporting the development of OGX. We thank the OGX contributor community for their sustained contributions to the project.
+
+\bibliographystyle{plain}
+\bibliography{references}
+
+\end{document}
diff --git a/paper/references.bib b/paper/references.bib
new file mode 100644
index 00000000000..343e9578fbf
--- /dev/null
+++ b/paper/references.bib
@@ -0,0 +1,188 @@
+@misc{ogx,
+ author = {{OGX Contributors}},
+ title = {{OGX} (Open GenAI Stack)},
+ year = {2026},
+ url = {https://github.com/ogx-ai/ogx},
+ note = {Formerly Llama Stack. \url{https://github.com/ogx-ai/ogx}}
+}
+
+@misc{ogxk8soperator,
+ author = {{OGX Contributors}},
+ title = {{OGX} Kubernetes Operator},
+ year = {2026},
+ url = {https://github.com/ogx-ai/ogx-k8s-operator},
+ note = {\url{https://github.com/ogx-ai/ogx-k8s-operator}}
+}
+
+@article{mlflow,
+ author = {Zaharia, Matei A. and Chen, Andrew and Davidson, Aaron and Ghodsi, Ali and Hong, Sue Ann and Konwinski, Andy and Murching, Siddharth and Nykodym, Tomas and Ogilvie, Paul and Parkhe, Mani and Xie, Fen and Zumar, Corey},
+ title = {{Accelerating the Machine Learning Lifecycle with MLflow}},
+ journal = {IEEE Data Eng. Bull.},
+ volume = {41},
+ pages = {39--45},
+ year = {2018},
+ url = {https://api.semanticscholar.org/CorpusID:83459546}
+}
+
+@misc{llamastack,
+ author = {{Llama Stack Contributors}},
+ title = {Llama Stack},
+ year = {2025},
+ url = {https://github.com/llamastack/llama-stack},
+ note = {\url{https://github.com/llamastack/llama-stack}}
+}
+
+@inproceedings{arceo2026securing,
+ author = {Arceo, Francisco Javier and Narsing, Varsha Prasad},
+ title = {Securing the Agent: Vendor-Neutral, Multitenant Enterprise Retrieval and Tool Use},
+ booktitle = {Proceedings of the ACM Conference on AI and Agentic Systems},
+ series = {CAIS '26},
+ year = {2026},
+ isbn = {9798400724152},
+ publisher = {Association for Computing Machinery},
+ address = {New York, NY, USA},
+ pages = {862--872},
+ numpages = {11},
+ doi = {10.1145/3786335.3813145},
+ url = {https://doi.org/10.1145/3786335.3813145}
+}
+
+@manual{openresponses,
+ author = {{Open Responses Community}},
+ title = {Open Responses Specification},
+ year = {2026},
+ url = {https://www.openresponses.org/},
+ note = {\url{https://www.openresponses.org/}}
+}
+
+@inproceedings{kwon2023vllm,
+ author = {Kwon, Woosuk and Li, Zhuohan and Zhuang, Siyuan and Sheng, Ying and Zheng, Lianmin and Yu, Cody Hao and Gonzalez, Joseph E. and Zhang, Hao and Stoica, Ion},
+ title = {Efficient Memory Management for Large Language Model Serving with {PagedAttention}},
+ booktitle = {Proceedings of the 29th ACM Symposium on Operating Systems Principles},
+ year = {2023},
+ publisher = {Association for Computing Machinery},
+ address = {New York, NY, USA},
+ pages = {611--626},
+ doi = {10.1145/3600006.3613165}
+}
+
+@inproceedings{sglang,
+ author = {Zheng, Lianmin and Yin, Liangsheng and Xie, Zhiqiang and Huang, Jeff and Sun, Chuyue and Yu, Cody Hao and Cao, Shiyi and Kober, Christos and Shi, Liang and Wu, Chien-Sheng and Zhang, Hao and Sheng, Ying and Gonzalez, Joseph E. and Stoica, Ion and Ma, Wei-Lin},
+ title = {{SGLang}: Efficient Execution of Structured Language Model Programs},
+ booktitle = {Advances in Neural Information Processing Systems},
+ year = {2024},
+ volume = {37},
+ publisher = {Curran Associates, Inc.}
+}
+
+@manual{openaiResponsesAPI,
+ author = {{OpenAI}},
+ title = {Responses {API} Reference},
+ year = {2025},
+ url = {https://platform.openai.com/docs/api-reference/responses},
+ note = {\url{https://platform.openai.com/docs/api-reference/responses}}
+}
+
+@manual{mcp,
+ title = {Model Context Protocol Specification},
+ author = {{Anthropic}},
+ year = {2026},
+ url = {https://modelcontextprotocol.io/specification/},
+ note = {\url{https://modelcontextprotocol.io/specification/}}
+}
+
+@misc{langchain,
+ author = {{LangChain, Inc.}},
+ title = {{LangChain}: Build context-aware reasoning applications},
+ year = {2023},
+ url = {https://github.com/langchain-ai/langchain},
+ note = {\url{https://github.com/langchain-ai/langchain}}
+}
+
+@misc{langgraph,
+ author = {{LangChain, Inc.}},
+ title = {{LangGraph}: Build resilient language agents as graphs},
+ year = {2024},
+ url = {https://github.com/langchain-ai/langgraph},
+ note = {\url{https://github.com/langchain-ai/langgraph}}
+}
+
+@misc{llamaindex,
+ author = {{LlamaIndex}},
+ title = {{LlamaIndex}: Data framework for {LLM} applications},
+ year = {2022},
+ url = {https://github.com/run-llama/llama_index},
+ note = {\url{https://github.com/run-llama/llama_index}}
+}
+
+@misc{crewai,
+ author = {{CrewAI, Inc.}},
+ title = {{CrewAI}: Framework for orchestrating role-playing autonomous {AI} agents},
+ year = {2024},
+ url = {https://github.com/crewAIInc/crewAI},
+ note = {\url{https://github.com/crewAIInc/crewAI}}
+}
+
+@misc{haystack,
+ author = {{deepset}},
+ title = {{Haystack}: End-to-end {LLM} framework for building production-ready applications},
+ year = {2023},
+ url = {https://github.com/deepset-ai/haystack},
+ note = {\url{https://github.com/deepset-ai/haystack}}
+}
+
+@manual{databricksAgentFramework,
+ author = {{Databricks}},
+ title = {{Mosaic AI Agent Framework}},
+ year = {2025},
+ url = {https://www.databricks.com/product/machine-learning/retrieval-augmented-generation},
+ note = {\url{https://www.databricks.com/product/machine-learning/retrieval-augmented-generation}}
+}
+
+@misc{sqlitevec,
+ author = {Alex Garcia},
+ title = {sqlite-vec: A vector search {SQLite} extension},
+ year = {2024},
+ url = {https://github.com/asg017/sqlite-vec},
+ note = {\url{https://github.com/asg017/sqlite-vec}}
+}
+
+@misc{ibm_rag_milvus,
+ author = {{IBM Community}},
+ title = {Build {RAG} with {Llama Stack} and watsonx.data {Milvus}},
+ year = {2025},
+ url = {https://community.ibm.com/community/user/blogs/divya13/2025/05/08/build-rag-with-llama-stack-and-watsonxdata-milvus},
+ note = {\url{https://community.ibm.com/community/user/blogs/divya13/2025/05/08/build-rag-with-llama-stack-and-watsonxdata-milvus}}
+}
+
+@misc{oracle_oci_ogx,
+ author = {{Oracle}},
+ title = {Accelerating Enterprise Gen {AI} Applications Development on {OCI} with {Llama Stack} and {OCI AI} Blueprints},
+ year = {2025},
+ url = {https://blogs.oracle.com/ai-and-datascience/accelerating-enterprise-gen-ai-applications-development-on-oci-with-llama-stack-and-oci-ai-blueprints},
+ note = {\url{https://blogs.oracle.com/ai-and-datascience/accelerating-enterprise-gen-ai-applications-development-on-oci-with-llama-stack-and-oci-ai-blueprints}}
+}
+
+@misc{redhat_ops_agent,
+ author = {{Red Hat}},
+ title = {Generative {AI} Applications with {Llama Stack}: A Notebook-Guided Journey to an Intelligent Operations Agent},
+ year = {2025},
+ url = {https://www.redhat.com/en/blog/generative-ai-applications-llama-stack-notebook-guided-journey-intelligent-operations-agent},
+ note = {\url{https://www.redhat.com/en/blog/generative-ai-applications-llama-stack-notebook-guided-journey-intelligent-operations-agent}}
+}
+
+@misc{meta_connect_ogx,
+ author = {{Meta}},
+ title = {Llama Stack: Chapter One},
+ year = {2024},
+ url = {https://developers.facebook.com/m/meta-connect-developer-sessions/llama-stack-chapter-one/},
+ note = {\url{https://developers.facebook.com/m/meta-connect-developer-sessions/llama-stack-chapter-one/}}
+}
+
+@misc{ibm_techxchange_ogx,
+ author = {Clyburn, Cedric},
+ title = {Llama Stack: Kubernetes for {RAG} and {AI} Agents in Generative {AI}},
+ year = {2025},
+ url = {https://mediacenter.ibm.com/media/Llama+Stack+Kubernetes+for+RAG+AI+Agents+in+Generative+AI/1_xl78upq2},
+ note = {\url{https://mediacenter.ibm.com/media/Llama+Stack+Kubernetes+for+RAG+AI+Agents+in+Generative+AI/1_xl78upq2}}
+}
diff --git a/pyproject.toml b/pyproject.toml
index 9ca2a600d38..e941dc4e43e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -3,28 +3,27 @@ requires = ["setuptools>=61.0", "setuptools-scm>=8.0"]
build-backend = "setuptools.build_meta"
[tool.setuptools_scm]
-fallback_version = "1.0.3.dev0"
+fallback_version = "1.1.4.dev0"
[tool.uv]
required-version = ">=0.7.0"
constraint-dependencies = [
"aiohttp>=3.13.4", # CVE-2026-34514 + 9 more: CRLF injection, header leak, DoS
"authlib>=1.6.11", # CVE-2026-41425 + 7 more: account takeover, JWE padding oracle, sig bypass
- "cryptography>=46.0.7", # CVE-2026-39892: buffer overflow; CVE-2026-34073: DNS constraint bypass
+ "cryptography>=48.0.1", # CVE-2026-39892: buffer overflow; CVE-2026-34073: DNS constraint bypass
"fonttools>=4.60.2",
"gitpython>=3.1.47", # Command injection via Git options bypass
"h11>=0.16.0",
"idna>=3.15",
- "pydantic>=2.11.9,<2.12.0", # 2.12 breaks int coercion in openai.types.model.Model during test replay
"lxml>=6.1.0", # CVE-2026-41066: XML entity expansion with default resolve_entities=True
"pillow>=12.2.0", # CVE-2026-40192 + 4 more: heap overflow, OOB write, DoS
"protobuf>=5.29.6", # CVE-2025-4565 + CVE-2026-0994: parsing vulnerabilities
"pyasn1>=0.6.3", # CVE-2026-30922: DoS via unbounded recursion
- "python-multipart>=0.0.27", # CVE-2026-40347: header injection; CVE-2026-42561: DoS via oversized headers
+ "python-multipart>=0.0.31", # CVE-2026-40347: header injection; CVE-2026-42561: DoS via oversized headers
"python-socketio>=5.14.0", # CVE-2025-61765: RCE via pickle deserialization
"requests>=2.34.2",
"setuptools<81", # milvus-lite imports pkg_resources; setuptools 81+ removes it
- "starlette>=1.0.1", # CVE-2026-48710
+ "starlette>=1.3.1", # CVE-2026-48710
"tornado>=6.5.5",
"urllib3>=2.7.0",
"transformers>=4.57.2,<5.0.0", # CVE-2026-1839 fix only in 5.x; ogx doesn't use Trainer; 5.x breaks HybridCache imports
@@ -56,17 +55,19 @@ dependencies = [
"jinja2>=3.1.6",
"jsonschema",
"ogx-api", # API and provider specifications (local dev via tool.uv.sources)
- "openai>=2.30.0",
+ "openai>=2.41.0",
"python-dotenv",
- "pyjwt[crypto]>=2.12.0", # Pull crypto to support RS256 for jwt. Requires 2.12.0+ to fix CVE-2026-32597.
+ "pyjwt[crypto]>=2.13.0", # Pull crypto to support RS256 for jwt. Requires 2.12.0+ to fix CVE-2026-32597.
"pydantic>=2.11.9",
"rich",
"structlog>=24.1.0",
"termcolor",
"tiktoken",
"uvicorn>=0.34.0", # server
+ "websockets>=14.0", # server - WebSocket transport for the Responses API
"opentelemetry-sdk>=1.42.1", # server
"opentelemetry-exporter-otlp-proto-http>=1.30.0", # server
+ "opentelemetry-exporter-otlp-proto-grpc>=1.30.0", # server (auto-instrumentation default)
"opentelemetry-distro>=0.60b1", # optional CLI instrumentation; only pre-releases on PyPI (latest 0.60b1)
"aiosqlite>=0.21.0", # server - for metadata store
"asyncpg", # for metadata store
@@ -78,7 +79,10 @@ dependencies = [
[project.optional-dependencies]
client = [
- "ogx-client>=1.0.2", # Optional for library-only usage
+ "ogx-client>=1.1.3", # Optional for library-only usage
+]
+openclient = [
+ "ogx-open-client>=1.0.2",
]
starter = [
"aiohttp",
@@ -94,7 +98,7 @@ starter = [
"faiss-cpu",
"fire",
"fireworks-ai<=0.17.16",
- "google-genai>=2.3.0",
+ "google-genai>=1.69.0,<2",
"langdetect",
"markitdown[all]",
"matplotlib",
@@ -106,10 +110,10 @@ starter = [
"pgvector>=0.3.0",
"pymilvus[milvus-lite]>=2.4.10",
"pymongo",
- "pypdf>=6.10.2",
+ "pypdf>=6.13.0",
"pythainlp",
"qdrant-client",
- "redis",
+ "redis>=8.0.0",
"requests",
"safetensors",
"scikit-learn",
@@ -134,15 +138,15 @@ dev = [
"pytest-cov",
"pytest-html",
"pytest-json-report",
- "pytest-socket", # For blocking network access in unit tests
+ "pytest-socket>=0.8.0", # For blocking network access in unit tests
"nbval", # For notebook testing
- "black",
+ "black>=26.5.1",
"ruff>=0.15.14",
"mypy",
"pre-commit>=4.4.0",
"ruamel.yaml", # needed for openapi generator
"openapi-spec-validator>=0.9.0",
- "ogx-client>=1.0.2",
+ "ogx-open-client>=1.0.2",
"boto3>=1.43.18",
"torch>=2.6.0",
]
@@ -153,7 +157,7 @@ type_checking = [
"types-setuptools",
"types-jsonschema",
"markitdown[all]",
- "pypdf>=6.10.2",
+ "pypdf>=6.13.0",
"pandas-stubs",
"types-psutil>=7.2.2.20260518",
"types-tqdm",
@@ -163,7 +167,7 @@ type_checking = [
"streamlit-option-menu",
"pandas",
"anthropic>=0.105.2",
- "databricks-sdk>=0.112.0",
+ "databricks-sdk>=0.114.0",
"fairscale",
"torchtune",
"trl>=1.5.0",
@@ -181,7 +185,7 @@ type_checking = [
"langchain-openai>=1.2.2",
"langchain-core",
"langgraph",
- "ogx-client>=1.0.2",
+ "ogx-open-client>=1.0.2",
]
test-common = [
"aiohttp",
@@ -191,7 +195,7 @@ test-common = [
"mcp>=1.23.0,<2.0",
"pgvector>=0.3.0",
"psycopg2-binary>=2.9.0",
- "pypdf>=6.10.2",
+ "pypdf>=6.13.0",
"sqlalchemy[asyncio]>=2.0.41",
]
# These are the dependencies required for running unit tests.
@@ -200,7 +204,7 @@ unit = [
"anthropic>=0.105.2",
"blobfile",
"coverage",
- "databricks-sdk>=0.112.0",
+ "databricks-sdk>=0.114.0",
"faiss-cpu",
"markitdown[all]",
"moto[s3]>=5.1.10",
@@ -218,7 +222,7 @@ test = [
"chromadb>=1.0.15",
"datasets>=4.0.0",
"elasticsearch>=8.16.0, <9.0.0",
- "google-genai>=2.3.0",
+ "google-genai>=1.69.0,<2",
"langchain-core",
"langchain-openai>=1.2.2",
"langgraph",
@@ -533,6 +537,7 @@ module = [
"google.genai.*",
"docling.*",
"docling_core.*",
+ "unstructured.*",
]
ignore_missing_imports = true
diff --git a/scripts/check_file_size.py b/scripts/check_file_size.py
index a565fe8f216..cc0439e94bd 100755
--- a/scripts/check_file_size.py
+++ b/scripts/check_file_size.py
@@ -25,6 +25,8 @@
# Pre-existing large files that haven't been split yet.
# Remove entries from this list as files get refactored.
GRANDFATHERED_FILES = {
+ "scripts/openapi_generator/schema_transforms.py",
+ "src/ogx/core/library_client.py",
"src/ogx/providers/inline/responses/builtin/responses/openai_responses.py",
"src/ogx/providers/inline/responses/builtin/responses/streaming.py",
"src/ogx/providers/inline/scoring/basic/utils/ifeval_word_list.py", # pure data file
@@ -37,6 +39,7 @@
"tests/integration/vector_io/test_openai_vector_stores.py",
"tests/integration/responses/test_openai_responses.py",
"tests/integration/responses/test_tool_responses.py",
+ "tests/unit/server/test_auth.py", # 1000+ lines after auth middleware refactor
}
diff --git a/scripts/generate_ci_matrix.py b/scripts/generate_ci_matrix.py
index 2601743033e..b5568b1a39d 100755
--- a/scripts/generate_ci_matrix.py
+++ b/scripts/generate_ci_matrix.py
@@ -88,7 +88,7 @@ def generate_matrix(schedule="", test_setup="", matrix_key="default", changed_fi
Args:
schedule: GitHub cron schedule string (e.g., "1 0 * * 0" for weekly)
test_setup: Manual test setup input (e.g., "ollama-vision")
- matrix_key: Matrix configuration key from ci_matrix.json (e.g., "default", "stainless")
+ matrix_key: Matrix configuration key from ci_matrix.json (e.g., "default")
changed_files: List of changed file paths for targeted PR testing
Returns:
diff --git a/scripts/integration-tests.sh b/scripts/integration-tests.sh
index 7ba4511a012..fcadc97ce93 100755
--- a/scripts/integration-tests.sh
+++ b/scripts/integration-tests.sh
@@ -347,7 +347,7 @@ if [[ "$STACK_CONFIG" == *"server:"* && "$COLLECT_ONLY" == false ]]; then
stop_server() {
echo "Stopping OGX Server..."
- pids=$(lsof -i :$OGX_PORT | awk 'NR>1 {print $2}')
+ pids=$(lsof -i :$OGX_PORT 2>/dev/null | awk 'NR>1 {print $2}' || true)
if [[ -n "$pids" ]]; then
echo "Killing OGX Server processes: $pids"
kill -9 $pids
@@ -503,6 +503,7 @@ if [[ "$STACK_CONFIG" == *"docker:"* && "$COLLECT_ONLY" == false ]]; then
[ -n "${GROQ_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e GROQ_API_KEY=$GROQ_API_KEY"
[ -n "${GEMINI_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e GEMINI_API_KEY=$GEMINI_API_KEY"
[ -n "${OLLAMA_URL:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e OLLAMA_URL=$OLLAMA_URL"
+ [ -n "${AWS_BEDROCK_BEARER_TOKEN:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e AWS_BEDROCK_BEARER_TOKEN=$AWS_BEDROCK_BEARER_TOKEN"
[ -n "${AWS_BEARER_TOKEN_BEDROCK:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e AWS_BEARER_TOKEN_BEDROCK=$AWS_BEARER_TOKEN_BEDROCK"
[ -n "${AWS_DEFAULT_REGION:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e AWS_DEFAULT_REGION=$AWS_DEFAULT_REGION"
[ -n "${VERTEX_AI_PROJECT:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e VERTEX_AI_PROJECT=$VERTEX_AI_PROJECT"
@@ -630,7 +631,7 @@ if [[ "$TYPESCRIPT_ONLY" == "false" ]]; then
$EXTRA_PARAMS \
--color=yes \
--embedding-model=sentence-transformers/nomic-ai/nomic-embed-text-v1.5 \
- --rerank-model=transformers/Qwen/Qwen3-Reranker-0.6B \
+ --rerank-model=sentence-transformers/Qwen/Qwen3-Reranker-0.6B \
--capture=tee-sys
exit_code=$?
else
diff --git a/scripts/openapi_generator/_legacy_order.py b/scripts/openapi_generator/_legacy_order.py
index b815cae2661..891b62a2c65 100644
--- a/scripts/openapi_generator/_legacy_order.py
+++ b/scripts/openapi_generator/_legacy_order.py
@@ -358,6 +358,7 @@
"name": "Tools",
"x-displayName": "Tools",
},
+ {"description": "OpenAI-compatible vector store management and search.", "name": "Vector Stores"},
{"description": "", "name": "VectorIO"},
{
"description": "OpenAI Responses API for agent orchestration with tool use, multi-turn conversations, and background processing.",
@@ -385,6 +386,7 @@
"ToolGroups",
"ToolRuntime",
"Tools",
+ "Vector Stores",
"VectorIO",
]
@@ -410,6 +412,7 @@
"ToolGroups",
"ToolRuntime",
"Tools",
+ "Vector Stores",
"VectorIO",
],
}
diff --git a/scripts/openapi_generator/_schema_output.py b/scripts/openapi_generator/_schema_output.py
index 4f9b0b985cd..5d11743a95f 100644
--- a/scripts/openapi_generator/_schema_output.py
+++ b/scripts/openapi_generator/_schema_output.py
@@ -18,6 +18,33 @@
from openapi_spec_validator import validate_spec
from openapi_spec_validator.exceptions import OpenAPISpecValidatorError
+
+def _fix_compact_request_schema(openapi_schema: dict[str, Any]) -> None:
+ """Align CompactResponseRequest with OpenAI's CompactResponseMethodPublicBody.
+
+ Fixes two structural mismatches:
+ 1. model: inject a ModelIdsResponses $ref so the anyOf variant count matches
+ 2. input: nest string + array variants inside a oneOf wrapper
+ """
+ schemas = openapi_schema.get("components", {}).get("schemas", {})
+ props = schemas.get("CompactResponseRequest", {}).get("properties", {})
+ if not props:
+ return
+
+ model_prop = props.get("model")
+ if isinstance(model_prop, dict) and "anyOf" in model_prop:
+ if not any(isinstance(v, dict) and "ModelIdsResponses" in v.get("$ref", "") for v in model_prop["anyOf"]):
+ schemas.setdefault("ModelIdsResponses", {"type": "string", "description": "Model identifier."})
+ model_prop["anyOf"].insert(0, {"$ref": "#/components/schemas/ModelIdsResponses"})
+
+ input_prop = props.get("input")
+ if isinstance(input_prop, dict) and "anyOf" in input_prop:
+ non_null = [v for v in input_prop["anyOf"] if not (isinstance(v, dict) and v.get("type") == "null")]
+ null_items = [v for v in input_prop["anyOf"] if isinstance(v, dict) and v.get("type") == "null"]
+ if len(non_null) >= 2 and null_items:
+ input_prop["anyOf"] = [{"oneOf": non_null}] + null_items
+
+
from ._legacy_order import (
LEGACY_OPERATION_KEYS,
LEGACY_PATH_ORDER,
diff --git a/scripts/openapi_generator/schema_transforms.py b/scripts/openapi_generator/schema_transforms.py
index ea91eebc2d4..108f9d6a507 100644
--- a/scripts/openapi_generator/schema_transforms.py
+++ b/scripts/openapi_generator/schema_transforms.py
@@ -16,6 +16,7 @@
_apply_legacy_sorting,
_dedupe_create_response_request_input_union_for_stainless,
_extract_duplicate_union_types,
+ _fix_compact_request_schema,
_write_yaml_file,
validate_openapi_schema,
)
@@ -904,6 +905,58 @@ def _inline_refs(obj: Any) -> None:
_inline_refs(openapi_schema)
+def _create_streaming_delta_tool_call(openapi_schema: dict[str, Any]) -> None:
+ """Create a streaming-friendly tool call schema for delta parsing.
+
+ The existing openapi.yml used the same ChatCompletionMessageToolCall schema for both
+ complete responses and streaming deltas, but streaming deltas on the wire include an
+ index field and omit id/type/function on continuation chunks. This function formalizes
+ the de-facto streaming protocol by creating a ChoiceDeltaToolCall variant with relaxed
+ field requirements, matching what the server actually sends.
+ """
+ schemas = openapi_schema.get("components", {}).get("schemas", {})
+ tc_schema = schemas.get("ChatCompletionMessageToolCall")
+ if not tc_schema:
+ return
+
+ delta_tc = copy.deepcopy(tc_schema)
+ delta_tc["description"] = "A tool call delta in a streaming chat completion chunk."
+ delta_props = delta_tc.get("properties", {})
+
+ # Add back `index` (required for correlating chunks across streaming deltas)
+ delta_props["index"] = {
+ "type": "integer",
+ "description": "The index of the tool call being streamed.",
+ }
+
+ # Make id and type optional (only present in the first chunk for a tool call)
+ for field in ("id", "type"):
+ if field in delta_props:
+ delta_props[field] = {
+ "anyOf": [delta_props[field], {"type": "null"}],
+ "description": delta_props[field].get("description", ""),
+ }
+
+ # Make function optional and its inner fields (name, arguments) not required
+ if "function" in delta_props:
+ func_schema = delta_props["function"]
+ func_schema.pop("required", None)
+ delta_props["function"] = {
+ "anyOf": [func_schema, {"type": "null"}],
+ "description": func_schema.pop("description", ""),
+ }
+
+ delta_tc["required"] = ["index"]
+ schemas["ChoiceDeltaToolCall"] = delta_tc
+
+ # Point the streaming delta's tool_calls to the new variant
+ delta_schema = schemas.get("OpenAIChoiceDelta")
+ if delta_schema:
+ tc_prop = delta_schema.get("properties", {}).get("tool_calls", {})
+ if "items" in tc_prop:
+ tc_prop["items"] = {"$ref": "#/components/schemas/ChoiceDeltaToolCall"}
+
+
def _fix_schema_issues(openapi_schema: dict[str, Any]) -> dict[str, Any]:
"""Fix common schema issues: exclusiveMinimum, null defaults, and add titles to unions."""
# Convert standalone const values to single-value enums (OpenAI style)
@@ -972,6 +1025,8 @@ def _fix_schema_issues(openapi_schema: dict[str, Any]) -> dict[str, Any]:
openapi_schema, "OpenAIChatCompletionCustomToolCall", "ChatCompletionMessageCustomToolCall"
)
+ _create_streaming_delta_tool_call(openapi_schema)
+
# Add discriminator to tool_calls items anyOf (OpenAI uses propertyName: "type")
if "components" in openapi_schema and "schemas" in openapi_schema["components"]:
msg_schema = openapi_schema["components"]["schemas"].get("OpenAIChatCompletionResponseMessage")
@@ -987,4 +1042,7 @@ def _fix_schema_issues(openapi_schema: dict[str, Any]) -> dict[str, Any]:
_fix_schema_recursive(schema_def)
_add_titles_to_unions(schema_def, schema_name)
+ # Run compact transforms AFTER titles are added so the new oneOf wrapper stays title-free.
+ _fix_compact_request_schema(openapi_schema)
+
return openapi_schema
diff --git a/src/ogx/cli/connect/claude.py b/src/ogx/cli/connect/claude.py
index 8ad8e997d15..d4ef35dc99d 100644
--- a/src/ogx/cli/connect/claude.py
+++ b/src/ogx/cli/connect/claude.py
@@ -69,7 +69,7 @@ def _add_arguments(self) -> None:
self.parser.add_argument(
"--url",
type=str,
- default=f"http://localhost:{default_port}",
+ default=f"http://localhost:{default_port}/v1",
help="OGX server URL.",
)
self.parser.add_argument(
@@ -196,7 +196,7 @@ def _resolve_model_mapping(
def _build_env(self, base_url: str, model_mapping: dict[str, str]) -> dict[str, str]:
env = {**os.environ}
- env["ANTHROPIC_BASE_URL"] = base_url
+ env["ANTHROPIC_BASE_URL"] = base_url.removesuffix("/v1")
env["ANTHROPIC_AUTH_TOKEN"] = "ogx" # noqa: S105 — placeholder, not a real secret
env.update(model_mapping)
for key in _VARS_TO_UNSET:
diff --git a/src/ogx/cli/connect/codex.py b/src/ogx/cli/connect/codex.py
new file mode 100644
index 00000000000..ea6fc99865e
--- /dev/null
+++ b/src/ogx/cli/connect/codex.py
@@ -0,0 +1,380 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import argparse
+import json
+import os
+import shutil
+import subprocess
+import sys
+import tempfile
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, NoReturn
+from urllib.parse import urlsplit, urlunsplit
+
+from openai import APIConnectionError, APIStatusError, APITimeoutError, OpenAI
+from termcolor import cprint
+
+from ogx.cli.subcommand import Subcommand
+from ogx.log import get_logger
+
+logger = get_logger(name=__name__, category="cli")
+
+
+def _exit_with_error(message: str) -> NoReturn:
+ cprint(message, color="red", file=sys.stderr)
+ raise SystemExit(1)
+
+
+@dataclass(frozen=True)
+class DiscoveredCodexModel:
+ """Model entry returned by OGX and adapted into the generated Codex catalog."""
+
+ model_id: str
+ custom_metadata: dict[str, Any]
+
+
+class CodexServerDiscovery:
+ """Probe the OGX server and normalize its model list for Codex."""
+
+ def __init__(self, *, timeout_seconds: float) -> None:
+ self.timeout_seconds = timeout_seconds
+
+ def normalize_base_url(self, raw_base_url: str) -> str:
+ base_url = raw_base_url.strip()
+ parsed = urlsplit(base_url)
+ if not parsed.scheme or not parsed.netloc:
+ _exit_with_error(
+ f"Failed to parse OGX base URL '{raw_base_url}'.\n"
+ "Provide a full OpenAI-compatible API base URL such as "
+ "http://localhost:8321/v1 or https://ogx.example.com/v1."
+ )
+ if not parsed.path.rstrip("/").endswith("/v1"):
+ _exit_with_error(
+ f"Failed to parse OGX base URL '{raw_base_url}'.\nInclude the OpenAI-compatible API path, such as /v1."
+ )
+
+ return urlunsplit((parsed.scheme, parsed.netloc, parsed.path, parsed.query, ""))
+
+ def fetch_models(self, base_url: str) -> list[DiscoveredCodexModel]:
+ default_headers = self.build_request_headers()
+ client = OpenAI(
+ base_url=base_url,
+ api_key=os.getenv("OGX_API_KEY", "unused"),
+ timeout=self.timeout_seconds,
+ default_headers=default_headers or None,
+ )
+ try:
+ response = client.models.list()
+ except APITimeoutError:
+ _exit_with_error(
+ f"Failed to connect to OGX server at {base_url}\n"
+ f"Timed out while querying available models after {self.timeout_seconds} seconds."
+ )
+ except APIConnectionError:
+ _exit_with_error(
+ f"Failed to connect to OGX server at {base_url}\nStart the server first with: ogx run "
+ )
+ except APIStatusError as e:
+ _exit_with_error(f"Failed to query models from OGX server at {base_url} (HTTP {e.status_code})")
+
+ models: list[DiscoveredCodexModel] = []
+ for model in response.data:
+ metadata = self.extract_custom_metadata(model)
+ if metadata.get("model_type") != "embedding":
+ models.append(DiscoveredCodexModel(model_id=model.id, custom_metadata=metadata))
+ return models
+
+ @staticmethod
+ def extract_custom_metadata(model: Any) -> dict[str, Any]:
+ metadata: dict[str, Any] = {}
+ model_extra = getattr(model, "model_extra", None)
+ if isinstance(model_extra, dict):
+ extra_custom_metadata = model_extra.get("custom_metadata")
+ if isinstance(extra_custom_metadata, dict):
+ metadata.update(extra_custom_metadata)
+
+ direct_custom_metadata = getattr(model, "custom_metadata", None)
+ if isinstance(direct_custom_metadata, dict):
+ metadata.update(direct_custom_metadata)
+
+ return metadata
+
+ @staticmethod
+ def build_request_headers() -> dict[str, str]:
+ headers: dict[str, str] = {}
+ provider_data = os.getenv("OGX_PROVIDER_DATA", "").strip()
+ if provider_data:
+ headers["X-OGX-Provider-Data"] = provider_data
+ return headers
+
+ @staticmethod
+ def select_default_model(
+ requested_model: str | None, available_models: list[DiscoveredCodexModel]
+ ) -> DiscoveredCodexModel:
+ available_model_ids = [model.model_id for model in available_models]
+ if requested_model:
+ if requested_model not in available_model_ids:
+ _exit_with_error(
+ f"Failed to find model '{requested_model}' on the OGX server.\n"
+ f"Available models: {', '.join(available_model_ids)}"
+ )
+ return next(model for model in available_models if model.model_id == requested_model)
+
+ return available_models[0]
+
+
+class CodexCatalogBuilder:
+ """Translate discovered OGX models into the generated Codex catalog schema."""
+
+ DEFAULT_CONTEXT_WINDOW = 128000
+
+ def __init__(
+ self,
+ *,
+ default_context_window: int = DEFAULT_CONTEXT_WINDOW,
+ ) -> None:
+ self.default_context_window = default_context_window
+
+ def build_model_catalog(
+ self, available_models: list[DiscoveredCodexModel], default_model: str
+ ) -> dict[str, list[dict[str, Any]]]:
+ return {
+ "models": [
+ self.build_model_catalog_entry(model, index=index, is_default=model.model_id == default_model)
+ for index, model in enumerate(available_models)
+ ]
+ }
+
+ def build_model_catalog_entry(self, model: DiscoveredCodexModel, *, index: int, is_default: bool) -> dict[str, Any]:
+ metadata = model.custom_metadata
+ context_window = self._coerce_int(
+ metadata.get("context_window") or metadata.get("context_length"),
+ self.default_context_window,
+ )
+ entry: dict[str, Any] = {
+ "slug": model.model_id,
+ "display_name": self._coerce_str(
+ metadata.get("display_name") or metadata.get("provider_model_id"),
+ model.model_id,
+ ),
+ "description": self._coerce_str(
+ metadata.get("description"),
+ f"Model exposed by the running OGX server as {model.model_id}.",
+ ),
+ "default_reasoning_level": None,
+ "context_window": context_window,
+ "max_context_window": context_window,
+ "auto_compact_token_limit": self._coerce_optional_int(metadata.get("auto_compact_token_limit")),
+ "shell_type": "default",
+ "additional_speed_tiers": [],
+ "service_tiers": [],
+ "default_service_tier": None,
+ "availability_nux": None,
+ "upgrade": None,
+ "base_instructions": "",
+ "model_messages": None,
+ "supports_reasoning_summaries": False,
+ "default_reasoning_summary": "auto",
+ "support_verbosity": False,
+ "default_verbosity": None,
+ "apply_patch_tool_type": None,
+ "web_search_tool_type": "text",
+ "truncation_policy": {"mode": "bytes", "limit": 10000},
+ "supports_parallel_tool_calls": False,
+ "supports_image_detail_original": False,
+ "effective_context_window_percent": 95,
+ "experimental_supported_tools": [],
+ "input_modalities": self._coerce_string_list(metadata.get("input_modalities"), fallback=["text"]),
+ "supported_reasoning_levels": [],
+ "used_fallback_model_metadata": False,
+ "supports_search_tool": False,
+ "visibility": "list",
+ "priority": 0 if is_default else index + 1,
+ "supported_in_api": True,
+ }
+
+ supported_reasoning_levels = self.build_reasoning_levels(metadata)
+ if supported_reasoning_levels:
+ entry["supported_reasoning_levels"] = supported_reasoning_levels
+ entry["default_reasoning_level"] = self._coerce_str(
+ metadata.get("default_reasoning_level") or metadata.get("defaultReasoningEffort"),
+ supported_reasoning_levels[0]["effort"],
+ )
+
+ return entry
+
+ @staticmethod
+ def build_reasoning_levels(metadata: dict[str, Any]) -> list[dict[str, str]]:
+ raw_levels = metadata.get("supported_reasoning_levels") or metadata.get("supportedReasoningEfforts") or []
+ if not isinstance(raw_levels, list):
+ return []
+
+ levels: list[dict[str, str]] = []
+ for item in raw_levels:
+ if not isinstance(item, dict):
+ continue
+ effort = item.get("effort") or item.get("reasoningEffort")
+ description = item.get("description")
+ if isinstance(effort, str) and isinstance(description, str):
+ levels.append({"effort": effort, "description": description})
+ return levels
+
+ @staticmethod
+ def _coerce_int(value: Any, fallback: int) -> int:
+ if isinstance(value, int) and value > 0:
+ return value
+ if isinstance(value, str) and value.isdigit():
+ parsed = int(value)
+ if parsed > 0:
+ return parsed
+ return fallback
+
+ @staticmethod
+ def _coerce_optional_int(value: Any) -> int | None:
+ if isinstance(value, int) and value > 0:
+ return value
+ if isinstance(value, str) and value.isdigit():
+ parsed = int(value)
+ if parsed > 0:
+ return parsed
+ return None
+
+ @staticmethod
+ def _coerce_str(value: Any, fallback: str) -> str:
+ if isinstance(value, str) and value.strip():
+ return value
+ return fallback
+
+ @staticmethod
+ def _coerce_string_list(value: Any, fallback: list[str]) -> list[str]:
+ if isinstance(value, list):
+ items = [item for item in value if isinstance(item, str) and item]
+ if items:
+ return items
+ return [*fallback]
+
+
+class CodexSessionBuilder:
+ """Render the generated Codex session files for an OGX-backed profile."""
+
+ def __init__(self, *, catalog_builder: CodexCatalogBuilder | None = None) -> None:
+ self.catalog_builder = catalog_builder or CodexCatalogBuilder()
+
+ def write_session_files(
+ self,
+ codex_home: Path,
+ base_url: str,
+ available_models: list[DiscoveredCodexModel],
+ default_model: str,
+ ) -> None:
+ model_catalog_path = codex_home / "ogx-model-catalog.json"
+ config_path = codex_home / "ogx.config.toml"
+ model_catalog_path.write_text(
+ json.dumps(self.catalog_builder.build_model_catalog(available_models, default_model), indent=2)
+ )
+ config_path.write_text(self.build_codex_config(base_url, model_catalog_path, default_model))
+
+ @staticmethod
+ def build_codex_config(base_url: str, model_catalog_path: Path, default_model: str) -> str:
+ env_http_headers = '{ "X-OGX-Provider-Data" = "OGX_PROVIDER_DATA" }'
+ config_lines = [
+ f"model = {json.dumps(default_model)}",
+ 'model_provider = "ogx"',
+ f"model_catalog_json = {json.dumps(str(model_catalog_path))}",
+ "",
+ "[features]",
+ "multi_agent = false",
+ "",
+ "[model_providers.ogx]",
+ 'name = "OGX"',
+ f"base_url = {json.dumps(base_url)}",
+ 'wire_api = "responses"',
+ "supports_websockets = false",
+ ]
+ if os.getenv("OGX_API_KEY", "").strip():
+ config_lines.extend(
+ [
+ 'env_key = "OGX_API_KEY"',
+ 'env_key_instructions = "Set OGX_API_KEY when your OGX deployment requires bearer authentication."',
+ ]
+ )
+ config_lines.extend(
+ [
+ f"env_http_headers = {env_http_headers}",
+ "",
+ ]
+ )
+ return "\n".join(config_lines)
+
+
+class ConnectCodex(Subcommand):
+ """Connect Codex to the running OGX server."""
+
+ MODEL_DISCOVERY_TIMEOUT_SECONDS = 20
+ DEFAULT_BASE_URL = "http://localhost:8321/v1"
+
+ def __init__(self, subparsers: argparse._SubParsersAction) -> None:
+ super().__init__()
+ self.discovery = CodexServerDiscovery(timeout_seconds=self.MODEL_DISCOVERY_TIMEOUT_SECONDS)
+ self.session_builder = CodexSessionBuilder()
+ self.parser = subparsers.add_parser(
+ "codex",
+ prog="ogx connect codex",
+ description="Launch Codex connected to the running OGX server.",
+ formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+ )
+ self._add_arguments()
+ self.parser.set_defaults(func=self._run_connect_codex_cmd)
+
+ def _add_arguments(self) -> None:
+ self.parser.add_argument(
+ "--model",
+ type=str,
+ default=None,
+ help="Default model ID. If omitted, the first available model is used.",
+ )
+ self.parser.add_argument(
+ "--url",
+ type=str,
+ default=os.getenv("OGX_BASE_URL", self.DEFAULT_BASE_URL),
+ help="OGX OpenAI-compatible API base URL, including /v1.",
+ )
+ self.parser.add_argument(
+ "--exec",
+ dest="exec_prompt",
+ type=str,
+ default=None,
+ help="Run Codex non-interactively with the provided prompt.",
+ )
+
+ def _run_connect_codex_cmd(self, args: argparse.Namespace) -> None:
+ if not shutil.which("codex"):
+ _exit_with_error("Failed to find 'codex' in PATH. Install it from https://github.com/openai/codex")
+
+ base_url = self.discovery.normalize_base_url(args.url)
+
+ models = self.discovery.fetch_models(base_url)
+ if not models:
+ _exit_with_error("Failed to find any LLM models on the OGX server.")
+
+ default_model = self.discovery.select_default_model(args.model, models)
+
+ logger.info("Connecting to Codex", default_model=default_model.model_id, models=len(models), base_url=base_url)
+
+ with tempfile.TemporaryDirectory(prefix="ogx-codex-") as codex_home:
+ codex_home_path = Path(codex_home)
+ self.session_builder.write_session_files(codex_home_path, base_url, models, default_model.model_id)
+ command = self._build_codex_command(args.exec_prompt)
+ env = {**os.environ, "CODEX_HOME": str(codex_home_path)}
+ result = subprocess.run(command, env=env)
+ sys.exit(result.returncode)
+
+ def _build_codex_command(self, exec_prompt: str | None = None) -> list[str]:
+ if exec_prompt:
+ return ["codex", "exec", "-p", "ogx", exec_prompt]
+ return ["codex", "-p", "ogx"]
diff --git a/src/ogx/cli/connect/connect.py b/src/ogx/cli/connect/connect.py
index de519e2e4ea..c8052a68a0c 100644
--- a/src/ogx/cli/connect/connect.py
+++ b/src/ogx/cli/connect/connect.py
@@ -10,6 +10,7 @@
from ogx.cli.subcommand import Subcommand
from .claude import ConnectClaude
+from .codex import ConnectCodex
from .opencode import ConnectOpenCode
@@ -34,4 +35,5 @@ def __init__(self, subparsers: argparse._SubParsersAction) -> None:
ConnectClaude.create(subparsers)
ConnectOpenCode.create(subparsers)
+ ConnectCodex.create(subparsers)
print_subcommand_description(self.parser, subparsers)
diff --git a/src/ogx/cli/stack/_list_deps.py b/src/ogx/cli/stack/_list_deps.py
index bf97f8c28bf..fb9701d6362 100644
--- a/src/ogx/cli/stack/_list_deps.py
+++ b/src/ogx/cli/stack/_list_deps.py
@@ -34,6 +34,7 @@
"uvicorn",
"opentelemetry-sdk",
"opentelemetry-exporter-otlp-proto-http",
+ "opentelemetry-exporter-otlp-proto-grpc",
]
diff --git a/src/ogx/cli/stack/lets_go.py b/src/ogx/cli/stack/lets_go.py
index bbe1d874038..916cd3bd4df 100644
--- a/src/ogx/cli/stack/lets_go.py
+++ b/src/ogx/cli/stack/lets_go.py
@@ -6,16 +6,20 @@
import argparse
import asyncio
+import contextlib
import enum
import importlib
+import inspect
+import logging # allow-direct-logging :: for direct logging control in _suppress_provider_logs
import os
import shutil
import subprocess
import sys
import tempfile
import warnings
+from collections.abc import Awaitable, Callable, Coroutine, Generator
from pathlib import Path
-from typing import Any
+from typing import Any, Protocol, runtime_checkable
import yaml
from termcolor import cprint
@@ -23,17 +27,78 @@
from ogx.cli.stack.run import _start_ui_development_server, _uvicorn_run
from ogx.cli.subcommand import Subcommand
from ogx.core.build import get_provider_dependencies
+from ogx.core.datatypes import Provider, QualifiedModel, StackConfig, VectorStoresConfig
from ogx.core.distribution import get_provider_registry
-from ogx.core.stack import replace_env_vars, run_config_from_dynamic_config_spec
+from ogx.core.stack import extract_env_var_references, replace_env_vars, run_config_from_dynamic_config_spec
from ogx.core.utils.config_dirs import DISTRIBS_BASE_DIR
from ogx.core.utils.dynamic import instantiate_class_type
from ogx.log import get_logger
-from ogx_api import Api, RemoteProviderSpec
+from ogx_api import Api, ModelType
from ogx_api.models.models import ModelInput
logger = get_logger(name=__name__, category="cli")
-# Model IDs that Claude Code looks for.
+
+# Type protocols for provider and config objects
+@runtime_checkable
+class ProbeableProvider(Protocol):
+ """Protocol for providers that support model listing and lifecycle management."""
+
+ async def list_models(self) -> list[Any]:
+ """Return list of available models."""
+ ...
+
+ def initialize(self) -> Coroutine[Any, Any, None] | None:
+ """Initialize provider (optional async)."""
+ ...
+
+ def shutdown(self) -> Coroutine[Any, Any, None] | None:
+ """Shutdown provider (optional async)."""
+ ...
+
+
+class _FactoryDispatcher:
+ """Determines factory function name and retrieves it from a module based on provider spec type.
+
+ Centralizes the isinstance-based dispatch logic, replacing runtime type checks
+ with a single point of control.
+ """
+
+ @staticmethod
+ def method_name_for_spec(spec: Any) -> str:
+ """Return the factory method name for a given provider spec.
+
+ Uses isinstance to determine spec type (isolated to this method).
+ Returns one of: "get_provider_impl", "get_adapter_impl", "get_auto_router_impl", "get_routing_table_impl".
+ """
+ # Import here to avoid circular imports at module level
+ from ogx.core.datatypes import AutoRoutedProviderSpec, RoutingTableProviderSpec
+ from ogx_api import RemoteProviderSpec
+
+ if isinstance(spec, RemoteProviderSpec):
+ return "get_adapter_impl"
+ elif isinstance(spec, AutoRoutedProviderSpec):
+ return "get_auto_router_impl"
+ elif isinstance(spec, RoutingTableProviderSpec):
+ return "get_routing_table_impl"
+ else: # Default: InlineProviderSpec
+ return "get_provider_impl"
+
+ @staticmethod
+ def get_factory(spec: Any, module: Any) -> Callable[[Any, dict[str, Any]], Awaitable[Any]] | None:
+ """Retrieve factory function from module for the given spec.
+
+ Args:
+ spec: Provider spec (ProviderSpec subclass).
+ module: Imported module containing factory functions.
+
+ Returns:
+ Factory function callable or None if not found.
+ """
+ method_name = _FactoryDispatcher.method_name_for_spec(spec)
+ return getattr(module, method_name, None)
+
+
_CLAUDE_CODE_ALIASES: list[str] = [
"claude-haiku-4-5",
"claude-sonnet-4-6",
@@ -119,6 +184,134 @@ def add_letsgo_arguments(parser: argparse.ArgumentParser) -> None:
action="store_true",
help="Skip automatic installation of provider pip dependencies before starting the server.",
)
+ parser.add_argument(
+ "--default-embedding-model",
+ type=str,
+ default=None,
+ metavar="PROVIDER_ID/MODEL_ID",
+ help="Default embedding model for vector stores, in the form 'provider_id/model_id' (e.g. 'sentence-transformers/nomic-ai/nomic-embed-text-v1.5'). When omitted, the server auto-detects an embedding model from registered providers.",
+ )
+ parser.add_argument(
+ "--default-embedding-dimension",
+ type=int,
+ default=None,
+ metavar="DIMENSION",
+ help="Embedding dimension for the default embedding model. Required when --default-embedding-model is specified.",
+ )
+ parser.add_argument(
+ "--debug",
+ action="store_true",
+ help="Enable debug logging during provider scanning and server startup.",
+ )
+
+
+def _add_file_search_and_responses(run_config: StackConfig) -> None:
+ """Add file-search and responses providers to the stack config.
+
+ These are only added after confirming an embedding model is available.
+ """
+ # Add tool_runtime API with file-search provider
+ if "tool_runtime" not in run_config.providers:
+ run_config.providers["tool_runtime"] = []
+ if not any(p.provider_type == "inline::file-search" for p in run_config.providers["tool_runtime"]):
+ run_config.providers["tool_runtime"].append(
+ Provider(provider_id="file-search", provider_type="inline::file-search")
+ )
+ # Add tool_runtime to APIs if not already present
+ if "tool_runtime" not in run_config.apis:
+ run_config.apis.append("tool_runtime")
+
+ # Add responses API with builtin provider
+ if "responses" not in run_config.providers:
+ run_config.providers["responses"] = []
+ if not any(p.provider_type == "inline::builtin" for p in run_config.providers["responses"]):
+ run_config.providers["responses"].append(
+ Provider(
+ provider_id="builtin",
+ provider_type="inline::builtin",
+ config={
+ "persistence": {
+ "responses": {
+ "table_name": "responses",
+ "backend": "sql_default",
+ }
+ }
+ },
+ )
+ )
+ # Add responses to APIs if not already present
+ if "responses" not in run_config.apis:
+ run_config.apis.append("responses")
+
+ # Add web search providers in priority order: brave -> tavily -> bing
+ _web_search_order = [
+ ("remote::brave-search", "brave-search"),
+ ("remote::tavily-search", "tavily-search"),
+ ("remote::bing-search", "bing-search"),
+ ("remote::nimble-search", "nimble-search"),
+ ]
+ tool_runtime_registry = get_provider_registry().get(Api.tool_runtime, {})
+ existing_web_search: set[str] = {
+ p.provider_type
+ for p in run_config.providers["tool_runtime"]
+ if p.provider_type in {pt for pt, _ in _web_search_order}
+ }
+
+ added = False
+ all_env_vars: list[str] = []
+
+ for provider_type, provider_id in _web_search_order:
+ if provider_type in existing_web_search:
+ cprint(f" ✓ {provider_id} (web search)", color="green")
+ added = True
+ continue
+
+ spec = tool_runtime_registry.get(provider_type)
+ if spec is None:
+ continue
+
+ try:
+ config_class = instantiate_class_type(spec.config_class)
+ config_template = config_class.sample_run_config(__distro_dir__=tempfile.gettempdir())
+ except Exception:
+ cprint(f" ✗ {provider_id} (web search) — failed to construct config template", color="yellow")
+ continue
+
+ env_vars_in_template = extract_env_var_references(config_template)
+ all_env_vars.extend(env_vars_in_template)
+
+ if not any(os.environ.get(v) for v in env_vars_in_template):
+ continue
+
+ try:
+ resolved_config = replace_env_vars(config_template)
+ config_class(**resolved_config) # validate construction
+ except Exception:
+ cprint(f" ✗ {provider_id} (web search) — failed to construct config with env vars", color="yellow")
+ continue # noqa S112 -- exception is reported to the user via cprint before continuing
+
+ run_config.providers["tool_runtime"].append(
+ Provider(
+ provider_id=provider_id,
+ provider_type=provider_type,
+ config=resolved_config,
+ )
+ )
+ cprint(f" ✓ {provider_id} (web search)", color="green")
+ added = True
+
+ if not added:
+ if all_env_vars:
+ vars_str = ", ".join(dict.fromkeys(all_env_vars))
+ cprint(
+ f" ✗ web search disabled (no API key set — set {vars_str})",
+ color="yellow",
+ )
+ else:
+ cprint(" ✗ web search disabled", color="yellow")
+
+ cprint(" ✓ inline::file-search (built-in)", color="green")
+ cprint(" ✓ inline::builtin responses (built-in)", color="green")
def run_letsgo_cmd(args: argparse.Namespace, parser: argparse.ArgumentParser) -> None:
@@ -130,8 +323,9 @@ def run_letsgo_cmd(args: argparse.Namespace, parser: argparse.ArgumentParser) ->
if args.providers_override:
providers_spec = args.providers_override
+ autodetect_embedding: tuple[QualifiedModel, int | None] | None = None
else:
- providers_spec = _autodetect_providers()
+ providers_spec, autodetect_embedding = _autodetect_providers(debug=getattr(args, "debug", False))
has_inference = any(p.startswith("inference=") for p in (providers_spec or "").split(","))
if not has_inference:
@@ -159,6 +353,102 @@ def run_letsgo_cmd(args: argparse.Namespace, parser: argparse.ArgumentParser) ->
run_config.registered_resources.models.extend(claude_aliases)
cprint(f" ✓ Claude Code aliases → {claude_aliases[0].provider_id}", color="green")
+ if args.default_embedding_model:
+ if not args.default_embedding_dimension:
+ cprint(
+ "Failed: --default-embedding-dimension is required when --default-embedding-model is specified",
+ color="red",
+ file=sys.stderr,
+ )
+ sys.exit(1)
+ provider_id, _, model_id = args.default_embedding_model.partition("/")
+ if not model_id:
+ cprint(
+ f"Failed to parse --default-embedding-model '{args.default_embedding_model}': expected format 'provider_id/model_id'",
+ color="red",
+ file=sys.stderr,
+ )
+ sys.exit(1)
+ existing = run_config.vector_stores or VectorStoresConfig()
+ run_config.vector_stores = existing.model_copy(
+ update={"default_embedding_model": QualifiedModel(provider_id=provider_id, model_id=model_id)}
+ )
+ # Explicitly register the model as embedding type so the startup validator and
+ # vector store creation can find it, even when the provider doesn't pre-classify it.
+ run_config.registered_resources.models.append(
+ ModelInput(
+ model_id=model_id,
+ provider_id=provider_id,
+ provider_model_id=model_id,
+ model_type=ModelType.embedding,
+ metadata={"embedding_dimension": args.default_embedding_dimension},
+ )
+ )
+ cprint(
+ f" ✓ Default embedding model → {args.default_embedding_model} ({args.default_embedding_dimension}d)",
+ color="green",
+ )
+ # Add file-search and responses now that embedding model is confirmed
+ _add_file_search_and_responses(run_config)
+ elif "vector_io" in run_config.providers:
+ detected_result = (
+ autodetect_embedding if autodetect_embedding is not None else _detect_embedding_model(run_config)
+ )
+ if detected_result:
+ detected, embedding_dimension = detected_result
+ if embedding_dimension is None:
+ cprint(
+ " ✗ Auto-detected embedding model has no dimension — vector stores, file-search, and responses disabled.",
+ color="yellow",
+ )
+ cprint(
+ " To enable them, run with --default-embedding-model PROVIDER_ID/MODEL_ID --default-embedding-dimension DIMENSION.",
+ color="yellow",
+ )
+ run_config.providers.pop("vector_io", None)
+ run_config.apis = [a for a in run_config.apis if a != "vector_io"]
+ else:
+ existing = run_config.vector_stores or VectorStoresConfig()
+ run_config.vector_stores = existing.model_copy(update={"default_embedding_model": detected})
+ # Keep auto-detected embeddings consistent with --default-embedding-model:
+ # register them explicitly as embedding models so startup validation
+ # does not rely on provider-side model typing.
+ run_config.registered_resources.models.append(
+ ModelInput(
+ model_id=detected.model_id,
+ provider_id=detected.provider_id,
+ provider_model_id=detected.model_id,
+ model_type=ModelType.embedding,
+ metadata={"embedding_dimension": embedding_dimension},
+ )
+ )
+ cprint(
+ f" ✓ Auto-detected embedding model → {detected.provider_id}/{detected.model_id} ({embedding_dimension}d)",
+ color="green",
+ )
+ # Add file-search and responses now that embedding model is confirmed
+ _add_file_search_and_responses(run_config)
+ else:
+ cprint(
+ " ✗ No embedding model detected — vector stores, file-search, and responses disabled.",
+ color="yellow",
+ )
+ cprint(
+ " To enable them, run with --default-embedding-model PROVIDER_ID/MODEL_ID --default-embedding-dimension DIMENSION.",
+ color="yellow",
+ )
+ run_config.providers.pop("vector_io", None)
+ run_config.apis = [a for a in run_config.apis if a != "vector_io"]
+ else:
+ cprint(
+ " ✗ No vector store provider detected — file-search and responses disabled.",
+ color="yellow",
+ )
+ cprint(
+ " To enable them, ensure a vector store is configured and add --default-embedding-model PROVIDER_ID/MODEL_ID.",
+ color="yellow",
+ )
+
config_dict = run_config.model_dump(mode="json")
config_file = distro_dir / "config.yaml"
@@ -203,8 +493,8 @@ def _install_provider_deps(normal_deps: list[str], special_deps: list[str]) -> N
)
-def _autodetect_providers() -> str:
- """Probe all candidate providers and return a comma-separated providers spec string.
+def _autodetect_providers(debug: bool = False) -> tuple[str, tuple[QualifiedModel, int | None] | None]:
+ """Probe all candidate providers and return a spec string and first detected embedding model.
Each provider is probed by instantiating it and calling list_models() to confirm
availability and model access. Providers that require an API key skip probing
@@ -230,10 +520,11 @@ def _autodetect_providers() -> str:
passed: list[str] = []
missing_deps_providers: dict[str, list[str]] = {} # provider_type -> pip_packages
+ detected_embedding: tuple[QualifiedModel, int | None] | None = None
cprint("Scanning for available providers...", color="cyan")
for provider_type, base_url_env, default_base_url, required_api_key_env, optional_api_key_env in candidates:
- status, model_count, base_url, base_source, pip_packages = _probe_provider_availability(
- provider_type, base_url_env, default_base_url, required_api_key_env, optional_api_key_env
+ status, models, base_url, base_source, pip_packages = _probe_provider_availability(
+ provider_type, base_url_env, default_base_url, required_api_key_env, optional_api_key_env, debug=debug
)
# Build annotation parts
@@ -252,9 +543,9 @@ def _autodetect_providers() -> str:
if status == _ProbeStatus.OK:
passed.append(f"inference={provider_type}")
if annotation:
- cprint(f" ✓ {provider_type} ({annotation}) — {model_count} models", color="green")
+ cprint(f" ✓ {provider_type} ({annotation}) — {len(models)} models", color="green")
else:
- cprint(f" ✓ {provider_type} ({model_count} models)", color="green")
+ cprint(f" ✓ {provider_type} ({len(models)} models)", color="green")
elif status == _ProbeStatus.NO_KEY:
if annotation:
cprint(f" ✗ {provider_type} ({annotation})", color="yellow")
@@ -282,57 +573,144 @@ def _autodetect_providers() -> str:
else:
cprint(f" ✗ {provider_type} — unreachable", color="yellow")
+ if status in (_ProbeStatus.OK, _ProbeStatus.NEEDS_KEY) and detected_embedding is None:
+ detected_embedding = _pick_embedding_from_models(models, provider_type.split("::")[-1])
+
# Inline providers require no external service — always include them.
+ # Note: file-search and responses require an embedding model, so they are added later
+ # after confirming an embedding model is available (either user-provided or auto-detected)
inline_providers = [
"files=inline::localfs",
"vector_io=inline::faiss",
- "tool_runtime=inline::file-search",
+ "batches=inline::reference",
"file_processors=inline::auto",
- "responses=inline::builtin",
"messages=inline::builtin",
]
cprint(" ✓ inline::localfs (built-in)", color="green")
cprint(" ✓ inline::faiss (built-in)", color="green")
- cprint(" ✓ inline::file-search (built-in)", color="green")
+ cprint(" ✓ inline::reference batches (built-in)", color="green")
cprint(" ✓ inline::auto (built-in)", color="green")
- cprint(" ✓ inline::builtin responses (built-in)", color="green")
cprint(" ✓ inline::builtin messages (built-in)", color="green")
- if passed:
- cprint(f"\nDetected {len(passed)} inference provider(s). Starting stack...", color="cyan")
- if missing_deps_providers:
- cprint("Available providers with missing dependencies:", color="cyan")
- for provider_type, pip_packages in missing_deps_providers.items():
- packages_str = " ".join(f"'{pkg}'" for pkg in pip_packages)
- cprint(f" {provider_type}: uv pip install {packages_str}", color="cyan")
- else:
- cprint("\nDetected no inference providers, not starting stack.", color="red")
- if missing_deps_providers:
- cprint("Install missing dependencies:", color="cyan")
- for provider_type, pip_packages in missing_deps_providers.items():
- packages_str = " ".join(f"'{pkg}'" for pkg in pip_packages)
- cprint(f" {provider_type}: uv pip install {packages_str}", color="cyan")
- return ",".join(passed + inline_providers)
+ if missing_deps_providers:
+ cprint("\nAvailable providers with missing dependencies:", color="cyan")
+ for provider_type, pip_packages in missing_deps_providers.items():
+ packages_str = " ".join(f"'{pkg}'" for pkg in pip_packages)
+ cprint(f" {provider_type}: uv pip install {packages_str}", color="cyan")
+ return ",".join(passed + inline_providers), detected_embedding
-async def _list_models_with_timeout(provider: Any, timeout_seconds: float = 5) -> list[Any] | None:
+
+async def _list_models_with_timeout(provider: ProbeableProvider, timeout_seconds: float = 5) -> list[Any]:
"""Call list_models with timeout and proper error handling."""
- if not hasattr(provider, "list_models"):
- return None
+ models = await asyncio.wait_for(provider.list_models(), timeout=timeout_seconds)
+ return list(models) if models else []
+
+
+async def _list_models_from_provider(provider: Any) -> list[Any]:
+ """Instantiate an inference provider from a runtime `Provider` entry and return its models.
+
+ This uses the provider registry to resolve the provider spec, instantiates the
+ provider implementation via its factory function, then calls `list_models` with
+ a timeout-protected helper.
+ """
+ registry = get_provider_registry()
+ spec = registry.get(Api.inference, {}).get(provider.provider_type)
+ if spec is None or not spec.module:
+ return []
+
try:
- models = await asyncio.wait_for(provider.list_models(), timeout=timeout_seconds)
- return list(models) if models else []
- except TimeoutError:
- raise
+ module = importlib.import_module(spec.module)
+ except Exception:
+ return []
+
+ config_type = instantiate_class_type(spec.config_class)
+ provider_config = provider.config if isinstance(provider.config, dict) else {}
+ try:
+ config = config_type(**provider_config)
+ except Exception:
+ return []
+
+ # Use dispatcher to get factory function
+ factory_fn = _FactoryDispatcher.get_factory(spec, module)
+ if factory_fn is None:
+ return []
+
+ try:
+ impl: ProbeableProvider = await _instantiate_with_timeout(factory_fn, config)
+ except Exception:
+ return []
+
+ # Annotate impl for diagnostic messages and cleanup
+ impl.__provider_id__ = provider.provider_id # type: ignore[attr-defined]
+ impl.__provider_spec__ = spec # type: ignore[attr-defined]
+
+ # Initialize provider if needed
+ init_result = impl.initialize()
+ if init_result is not None:
+ await asyncio.wait_for(init_result, timeout=5.0)
+
+ try:
+ models = await _list_models_with_timeout(impl, timeout_seconds=5)
+ except Exception:
+ models = []
+
+ # Cleanup provider if needed
+ shutdown_result = impl.shutdown()
+ if shutdown_result is not None:
+ await asyncio.wait_for(shutdown_result, timeout=2.0)
+
+ return models or []
+
+
+def _pick_embedding_from_models(models: list[Any], provider_id: str) -> tuple[QualifiedModel, int | None] | None:
+ """Return the best embedding model from a list, preferring one with dimension metadata."""
+ best: tuple[QualifiedModel, int | None] | None = None
+ for model in models:
+ if getattr(model, "model_type", None) != ModelType.embedding:
+ continue
+ identifier = getattr(model, "identifier", None)
+ if not identifier:
+ continue
+ dimension: int | None = None
+ if hasattr(model, "metadata") and isinstance(model.metadata, dict):
+ dimension = model.metadata.get("embedding_dimension")
+ best = (QualifiedModel(provider_id=provider_id, model_id=str(identifier)), dimension)
+ if dimension is not None:
+ break
+ return best
-async def _instantiate_with_timeout(factory_fn: Any, config: Any) -> Any:
+def _detect_embedding_model(run_config: StackConfig) -> tuple[QualifiedModel, int | None] | None:
+ """Find an embedding model by instantiating each inference provider and calling list_models().
+
+ Returns tuple of (QualifiedModel, embedding_dimension) or None if not found.
+ Dimension may be None if not available in model metadata — caller must handle this.
+ """
+
+ async def _detect_async() -> tuple[QualifiedModel, int | None] | None:
+ for provider in run_config.providers.get("inference", []):
+ if not provider.provider_id:
+ continue
+ models = await _list_models_from_provider(provider)
+ result = _pick_embedding_from_models(models, provider.provider_id)
+ if result is not None:
+ return result
+ return None
+
+ return asyncio.run(_detect_async())
+
+
+async def _instantiate_with_timeout(
+ factory_fn: Callable[[Any, dict[str, Any]], Awaitable[ProbeableProvider] | ProbeableProvider],
+ config: Any,
+) -> ProbeableProvider:
"""Call factory function with timeout."""
try:
result = factory_fn(config, {})
- if asyncio.iscoroutine(result):
- return await asyncio.wait_for(result, timeout=5.0)
- return result
+ if inspect.iscoroutine(result):
+ return await asyncio.wait_for(result, timeout=5.0) # type: ignore[arg-type]
+ return result # type: ignore[return-value]
except TimeoutError:
raise
@@ -349,13 +727,35 @@ def _is_auth_error(e: Exception) -> bool:
)
+@contextlib.contextmanager
+def _suppress_provider_logs(suppress: bool = True) -> Generator[None, None, None]:
+ """Context manager to suppress all provider-related logs during probing.
+
+ When suppress=True, temporarily disables all logging. When suppress=False,
+ logging is emitted normally. This ensures no logger output appears during provider
+ scanning unless the user passes --debug.
+ """
+ if not suppress:
+ yield
+ return
+
+ # Disable all logging (using level higher than CRITICAL) to suppress all messages
+ previous_disable_level = logging.root.manager.disable
+ logging.disable(100)
+ try:
+ yield
+ finally:
+ logging.disable(previous_disable_level)
+
+
def _probe_provider_availability(
provider_type: str,
base_url_env: str | None,
default_base_url: str,
required_api_key_env: str | None,
optional_api_key_env: str | None = None,
-) -> tuple[_ProbeStatus, int, str, str, list[str] | None]:
+ debug: bool = False,
+) -> tuple[_ProbeStatus, list[Any], str, str, list[str] | None]:
"""Instantiate a provider and probe availability by listing models.
Args:
@@ -366,7 +766,7 @@ def _probe_provider_availability(
optional_api_key_env: Environment variable name for optional API key, or None
Returns:
- Tuple of (status, model_count, base_url, base_source, pip_packages).
+ Tuple of (status, models, base_url, base_source, pip_packages).
base_source is "default" or the env var name. base_url is empty string if not applicable.
pip_packages is a list of packages to install for MISSING_DEPS, None otherwise.
Returns NEEDS_KEY if required key is present but optional key is missing.
@@ -388,128 +788,133 @@ def _probe_provider_availability(
# Check if required API key is available
if required_api_key_env and not os.getenv(required_api_key_env):
- return _ProbeStatus.NO_KEY, 0, base_url, base_source, None
+ return _ProbeStatus.NO_KEY, [], base_url, base_source, None
# Track if optional API key is missing (provider works but with reduced functionality)
optional_key_missing = optional_api_key_env and not os.getenv(optional_api_key_env)
- try:
- # Load provider registry and look up the spec
- registry = get_provider_registry()
- if Api.inference not in registry or provider_type not in registry[Api.inference]:
- logger.debug("Provider not found in registry", provider_type=provider_type)
- return _ProbeStatus.UNREACHABLE, 0, base_url, base_source, None
-
- provider_spec = registry[Api.inference][provider_type]
- logger.debug("Found provider in registry", provider_type=provider_type, module=provider_spec.module)
-
- # Get config defaults
+ # Suppress non-critical logging during provider probing unless debug mode is enabled
+ with _suppress_provider_logs(suppress=not debug):
try:
- config_class = instantiate_class_type(provider_spec.config_class)
- config_defaults = config_class.sample_run_config(__distro_dir__=tempfile.gettempdir())
- logger.debug("Got config defaults", provider_type=provider_type)
-
- # Substitute environment variables in config (e.g., ${env.VAR_NAME:=default})
- config_defaults = replace_env_vars(config_defaults)
- except ModuleNotFoundError as e:
- logger.debug("Provider dependencies not installed", provider_type=provider_type, module=str(e)[:200])
- return _ProbeStatus.MISSING_DEPS, 0, base_url, base_source, provider_spec.pip_packages
- except Exception as e:
- logger.debug("Failed to get config defaults", provider_type=provider_type, error=str(e)[:200])
- return _ProbeStatus.UNREACHABLE, 0, base_url, base_source, None
-
- # Instantiate config object
- try:
- config = config_class(**config_defaults)
- logger.debug("Instantiated config", provider_type=provider_type)
- except ModuleNotFoundError as e:
- logger.debug("Provider dependencies not installed", provider_type=provider_type, module=str(e)[:200])
- return _ProbeStatus.MISSING_DEPS, 0, base_url, base_source, provider_spec.pip_packages
- except Exception as e:
- logger.debug("Failed to instantiate config", provider_type=provider_type, error=str(e)[:200])
- return _ProbeStatus.UNREACHABLE, 0, base_url, base_source, None
-
- # Import provider module and instantiate
- if not provider_spec.module:
- logger.debug("Provider spec missing module", provider_type=provider_type)
- return _ProbeStatus.UNREACHABLE, 0, base_url, base_source, None
-
- try:
- module = importlib.import_module(provider_spec.module)
- logger.debug("Imported provider module", provider_type=provider_type, module=provider_spec.module)
- except ModuleNotFoundError as e:
- logger.debug("Provider dependencies not installed", provider_type=provider_type, module=str(e)[:200])
- return _ProbeStatus.MISSING_DEPS, 0, base_url, base_source, provider_spec.pip_packages
- except Exception as e:
- logger.debug("Failed to import provider module", module=provider_spec.module, error=str(e)[:200])
- return _ProbeStatus.UNREACHABLE, 0, base_url, base_source, None
-
- try:
- # Call appropriate factory function
- if isinstance(provider_spec, RemoteProviderSpec):
- method_name = "get_adapter_impl"
- else: # InlineProviderSpec
- method_name = "get_provider_impl"
-
- factory_fn = getattr(module, method_name)
- logger.debug("Calling factory function", provider_type=provider_type, method=method_name)
- # Pass empty deps dict {} for single-provider probing
- provider = asyncio.run(_instantiate_with_timeout(factory_fn, config))
- logger.debug("Provider instantiated successfully", provider_type=provider_type)
-
- # Set required attributes (normally done by resolver)
- provider.__provider_id__ = provider_type
- provider.__provider_spec__ = provider_spec
- provider.__provider_config__ = config
- except ModuleNotFoundError as e:
- logger.debug("Provider dependencies not installed", provider_type=provider_type, module=str(e)[:200])
- return _ProbeStatus.MISSING_DEPS, 0, base_url, base_source, provider_spec.pip_packages
- except Exception as e:
- logger.debug("Failed to instantiate provider", provider_type=provider_type, error=str(e)[:300])
- if _is_auth_error(e):
- logger.warning(
- "Provider auth failed", provider_type=provider_type, base_url=base_url, error=str(e)[:200]
+ # Load provider registry and look up the spec
+ registry = get_provider_registry()
+ if Api.inference not in registry or provider_type not in registry[Api.inference]:
+ cprint(f" ✗ {provider_type} not found in provider registry", color="red")
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
+
+ provider_spec = registry[Api.inference][provider_type]
+ logger.debug("Probing provider", provider_type=provider_type, module=provider_spec.module)
+
+ # Get config defaults
+ try:
+ config_class = instantiate_class_type(provider_spec.config_class)
+ config_defaults = config_class.sample_run_config(__distro_dir__=tempfile.gettempdir())
+ logger.debug("Loaded config defaults for provider", provider_type=provider_type)
+
+ # Substitute environment variables in config (e.g., ${env.VAR_NAME:=default})
+ config_defaults = replace_env_vars(config_defaults)
+
+ # Inject the determined base_url into the config for remote providers
+ if base_url and "base_url" in config_defaults:
+ config_defaults["base_url"] = base_url
+ logger.debug("Set base_url in config", provider_type=provider_type, base_url=base_url)
+ except ModuleNotFoundError as e:
+ cprint(f" Missing dependencies for {provider_type}: {str(e)[:200]}", color="red")
+ return _ProbeStatus.MISSING_DEPS, [], base_url, base_source, provider_spec.pip_packages
+ except Exception as e:
+ cprint(f" Failed to get config defaults for {provider_type}: {str(e)[:200]}", color="red")
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
+
+ # Instantiate config object
+ try:
+ config = config_class(**config_defaults)
+ logger.debug("Instantiated config for provider", provider_type=provider_type)
+ except ModuleNotFoundError as e:
+ cprint(f" Missing dependencies for {provider_type}: {str(e)[:200]}", color="red")
+ return _ProbeStatus.MISSING_DEPS, [], base_url, base_source, provider_spec.pip_packages
+ except Exception as e:
+ cprint(f" Failed to instantiate config for {provider_type}: {str(e)[:200]}", color="red")
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
+
+ # Import provider module and instantiate
+ if not provider_spec.module:
+ cprint(f" Provider spec missing module for {provider_type}", color="red")
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
+
+ try:
+ module = importlib.import_module(provider_spec.module)
+ logger.debug("Imported provider module", provider_type=provider_type, module=provider_spec.module)
+ except ModuleNotFoundError as e:
+ cprint(f" Missing dependencies for {provider_type}: {str(e)[:200]}", color="red")
+ return _ProbeStatus.MISSING_DEPS, [], base_url, base_source, provider_spec.pip_packages
+ except Exception as e:
+ cprint(f" Failed to import provider module {provider_spec.module}: {str(e)[:200]}", color="red")
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
+
+ try:
+ # Use dispatcher to get factory function
+ factory_fn = _FactoryDispatcher.get_factory(provider_spec, module)
+ if factory_fn is None:
+ cprint(f" Failed to find factory function in {provider_spec.module}", color="red")
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
+
+ logger.debug(
+ "Calling factory function for provider",
+ provider_type=provider_type,
+ factory_name=_FactoryDispatcher.method_name_for_spec(provider_spec),
)
- return _ProbeStatus.AUTH, 0, base_url, base_source, None
- return _ProbeStatus.UNREACHABLE, 0, base_url, base_source, None
-
- # List models with timeout
- try:
- logger.debug("Calling list_models", provider_type=provider_type)
- models = asyncio.run(_list_models_with_timeout(provider, timeout_seconds=5))
- model_count = len(models) if models else 0
- logger.debug("Listed models successfully", provider_type=provider_type, model_count=model_count)
-
- # Cleanup provider
- if hasattr(provider, "aclose"):
+ # Pass empty deps dict {} for single-provider probing
+ provider: ProbeableProvider = asyncio.run(_instantiate_with_timeout(factory_fn, config)) # type: ignore[arg-type]
+ logger.debug("Provider instantiated successfully for provider", provider_type=provider_type)
+
+ # Set required attributes (normally done by resolver)
+ provider.__provider_id__ = provider_type # type: ignore[attr-defined]
+ provider.__provider_spec__ = provider_spec # type: ignore[attr-defined]
+ provider.__provider_config__ = config # type: ignore[attr-defined]
+ except ModuleNotFoundError:
+ return _ProbeStatus.MISSING_DEPS, [], base_url, base_source, provider_spec.pip_packages
+ except Exception as e:
+ if _is_auth_error(e):
+ return _ProbeStatus.AUTH, [], base_url, base_source, None
+ cprint(f" Failed to instantiate provider {provider_type}: {str(e)[:300]}", color="red")
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
+
+ # List models with timeout
+ try:
+ logger.debug("Calling list_models for provider", provider_type=provider_type)
+ models = asyncio.run(_list_models_with_timeout(provider, timeout_seconds=5))
+ logger.debug("Listed models for provider", provider_type=provider_type, model_count=len(models))
+
+ # Cleanup provider: call shutdown() if available.
try:
- asyncio.run(provider.aclose())
+ shutdown_result = provider.shutdown()
+ if shutdown_result is not None:
+ asyncio.run(shutdown_result) # type: ignore[arg-type]
+ except AttributeError:
+ # Provider did not declare `shutdown()`; surface as a warning.
+ cprint(
+ f" Provider {provider_type} has no declared 'shutdown' method; skipping cleanup",
+ color="red",
+ )
except Exception as e:
- logger.debug("Failed to cleanup provider", provider_type=provider_type, error=str(e)[:200])
-
- if model_count == 0:
- logger.debug("Provider returned zero models", provider_type=provider_type)
- return _ProbeStatus.UNREACHABLE, 0, base_url, base_source, None
- # Return NEEDS_KEY if optional API key is missing, otherwise OK
- status = _ProbeStatus.NEEDS_KEY if optional_key_missing else _ProbeStatus.OK
- return status, model_count, base_url, base_source, None
- except TimeoutError:
- logger.debug("Model listing timed out", provider_type=provider_type)
- return _ProbeStatus.UNREACHABLE, 0, base_url, base_source, None
+ cprint(f" Failed to cleanup provider {provider_type}: {str(e)[:200]}", color="red")
+
+ if not models:
+ cprint(f" Provider returned zero models for {provider_type}", color="yellow")
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
+ # Return NEEDS_KEY if optional API key is missing, otherwise OK
+ status = _ProbeStatus.NEEDS_KEY if optional_key_missing else _ProbeStatus.OK
+ return status, models, base_url, base_source, None
+ except TimeoutError:
+ cprint(f" Model listing timed out for {provider_type}", color="yellow")
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
+ except Exception as e:
+ if _is_auth_error(e):
+ return _ProbeStatus.AUTH, [], base_url, base_source, None
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
except Exception as e:
- logger.debug("Failed to list models", provider_type=provider_type, error=str(e)[:300])
- if _is_auth_error(e):
- logger.warning(
- "Provider auth failed during model listing",
- provider_type=provider_type,
- base_url=base_url,
- error=str(e)[:200],
- )
- return _ProbeStatus.AUTH, 0, base_url, base_source, None
- return _ProbeStatus.UNREACHABLE, 0, base_url, base_source, None
- except Exception as e:
- logger.debug("Unexpected error during provider probing", provider_type=provider_type, error=str(e)[:300])
- return _ProbeStatus.UNREACHABLE, 0, base_url, base_source, None
+ cprint(f" ✗ Unexpected error during provider probing {provider_type}: {str(e)[:300]}", color="red")
+ return _ProbeStatus.UNREACHABLE, [], base_url, base_source, None
class StackLetsGo(Subcommand):
diff --git a/src/ogx/core/README.md b/src/ogx/core/README.md
index a736249b9a0..8c498140079 100644
--- a/src/ogx/core/README.md
+++ b/src/ogx/core/README.md
@@ -27,9 +27,12 @@ core/
## Request Lifecycle
1. `server.py` receives an HTTP request and dispatches to the correct handler.
-2. The handler calls a **Router** (e.g., `InferenceRouter`) which consults the **RoutingTable** to find the provider for the requested resource.
-3. The router delegates to the provider implementation.
-4. The provider either computes locally (inline) or calls an external service (remote).
+2. Authentication middleware validates the token, extracts the user identity and `tenant_id`.
+3. Tenancy middleware enforces the configured mode (disabled/single/multi) and stores `tenant_id` in the request scope.
+4. The handler calls a **Router** (e.g., `InferenceRouter`) which consults the **RoutingTable** to find the provider for the requested resource.
+5. The router delegates to the provider implementation.
+6. The provider either computes locally (inline) or calls an external service (remote).
+7. Storage operations go through `AuthorizedSqlStore`, which applies tenant isolation (`WHERE tenant_id = ?`) before ABAC policy checks.
## Key Classes
diff --git a/src/ogx/core/access_control/access_control.py b/src/ogx/core/access_control/access_control.py
index 739be53d006..9ab5396aafd 100644
--- a/src/ogx/core/access_control/access_control.py
+++ b/src/ogx/core/access_control/access_control.py
@@ -13,6 +13,7 @@
from .conditions import (
Condition,
ProtectedResource,
+ has_tenant_scope_mismatch,
parse_conditions,
)
from .datatypes import (
@@ -162,6 +163,9 @@ def is_action_allowed(
if not user:
decision = True
reason = "no auth"
+ elif has_tenant_scope_mismatch(resource, user):
+ decision = False
+ reason = "tenant scope mismatch"
else:
if not len(policy):
policy = default_policy()
diff --git a/src/ogx/core/access_control/conditions.py b/src/ogx/core/access_control/conditions.py
index 885a7da449c..db1a804e30e 100644
--- a/src/ogx/core/access_control/conditions.py
+++ b/src/ogx/core/access_control/conditions.py
@@ -11,6 +11,7 @@ class User(Protocol):
"""Protocol for user identity with principal and attribute information."""
principal: str
+ tenant_id: str | None
attributes: dict[str, list[str]] | None
@@ -46,6 +47,8 @@ def owners_values(self, resource: ProtectedResource) -> list[str] | None:
return None
def matches(self, resource: ProtectedResource, user: User) -> bool:
+ if not _same_tenant_scope(resource, user):
+ return False
defined = self.owners_values(resource)
if not defined:
return False
@@ -68,6 +71,8 @@ def __init__(self, name: str):
super().__init__(name)
def matches(self, resource: ProtectedResource, user: User) -> bool:
+ if has_tenant_scope_mismatch(resource, user):
+ return False
return not super().matches(resource, user)
def __repr__(self) -> str:
@@ -108,7 +113,7 @@ class UserIsOwner:
"""Condition that checks if the user is the owner of the resource."""
def matches(self, resource: ProtectedResource, user: User) -> bool:
- return resource.owner.principal == user.principal if resource.owner else False
+ return _same_principal_and_tenant(resource, user)
def __repr__(self) -> str:
return "user is owner"
@@ -118,6 +123,8 @@ class UserIsNotOwner:
"""Condition that checks if the user is NOT the owner of the resource."""
def matches(self, resource: ProtectedResource, user: User) -> bool:
+ if has_tenant_scope_mismatch(resource, user):
+ return False
return not resource.owner or resource.owner.principal != user.principal
def __repr__(self) -> str:
@@ -134,6 +141,26 @@ def __repr__(self) -> str:
return "resource is unowned"
+def _same_tenant_scope(resource: ProtectedResource, user: User) -> bool:
+ return not has_tenant_scope_mismatch(resource, user)
+
+
+def has_tenant_scope_mismatch(resource: ProtectedResource, user: User) -> bool:
+ if not resource.owner:
+ return False
+ owner_tenant_id = resource.owner.tenant_id
+ user_tenant_id = user.tenant_id
+ if not owner_tenant_id or not user_tenant_id:
+ return False
+ return owner_tenant_id != user_tenant_id
+
+
+def _same_principal_and_tenant(resource: ProtectedResource, user: User) -> bool:
+ if not resource.owner or resource.owner.principal != user.principal:
+ return False
+ return _same_tenant_scope(resource, user)
+
+
def parse_condition(condition: str) -> Condition:
"""Parse a condition string into a Condition object.
diff --git a/src/ogx/core/build.py b/src/ogx/core/build.py
index 033a154660b..bedfca4e383 100644
--- a/src/ogx/core/build.py
+++ b/src/ogx/core/build.py
@@ -26,6 +26,7 @@
"uvicorn",
"opentelemetry-sdk",
"opentelemetry-exporter-otlp-proto-http",
+ "opentelemetry-exporter-otlp-proto-grpc",
]
diff --git a/src/ogx/core/configure.py b/src/ogx/core/configure.py
index fb729cb1216..ccb5a9b6de8 100644
--- a/src/ogx/core/configure.py
+++ b/src/ogx/core/configure.py
@@ -150,6 +150,13 @@ def _migrate_prompts_kv_to_sql(config_dict: dict[str, Any]) -> None:
prompts_cfg["backend"] = sql_backend
+def _ensure_tenancy_defaults(config_dict: dict[str, Any]) -> None:
+ """Ensure tenancy config exists with mode=disabled if not specified."""
+ server = config_dict.setdefault("server", {})
+ if "tenancy" not in server:
+ server["tenancy"] = {"mode": "disabled"}
+
+
def parse_and_maybe_upgrade_config(config_dict: dict[str, Any]) -> StackConfig:
"""Parse a configuration dictionary into a StackConfig, upgrading from legacy format if needed.
@@ -164,6 +171,7 @@ def parse_and_maybe_upgrade_config(config_dict: dict[str, Any]) -> StackConfig:
config_dict = upgrade_from_routing_table(config_dict)
_migrate_prompts_kv_to_sql(config_dict)
+ _ensure_tenancy_defaults(config_dict)
config_dict["version"] = OGX_RUN_CONFIG_VERSION
diff --git a/src/ogx/core/conversations/conversations.py b/src/ogx/core/conversations/conversations.py
index 24582b942be..2d11018913a 100644
--- a/src/ogx/core/conversations/conversations.py
+++ b/src/ogx/core/conversations/conversations.py
@@ -37,7 +37,7 @@
RetrieveItemRequest,
UpdateConversationRequest,
)
-from ogx_api.internal.sqlstore import ColumnDefinition, ColumnType
+from ogx_api.internal.sqlstore import ColumnDefinition, ColumnType, DeleteOperation
logger = get_logger(name=__name__, category="openai_conversations")
@@ -182,7 +182,18 @@ async def openai_delete_conversation(self, request: DeleteConversationRequest) -
if record is None:
raise ConversationNotFoundError(request.conversation_id)
- await self.sql_store.delete(table="openai_conversations", where={"id": request.conversation_id})
+ await self.sql_store.delete_many(
+ [
+ DeleteOperation(
+ table="conversation_items",
+ where={"conversation_id": request.conversation_id},
+ ),
+ DeleteOperation(
+ table="openai_conversations",
+ where={"id": request.conversation_id},
+ ),
+ ]
+ )
logger.debug("Deleted conversation", conversation_id=request.conversation_id)
return ConversationDeletedResource(id=request.conversation_id)
@@ -273,6 +284,8 @@ async def retrieve(self, request: RetrieveItemRequest) -> ConversationItem:
if not request.item_id:
raise InvalidParameterError("item_id", request.item_id, "Must be a non-empty string.")
+ await self._get_validated_conversation(request.conversation_id)
+
# Get item from conversation_items table
record = await self.sql_store.fetch_one(
table="conversation_items", where={"id": request.item_id, "conversation_id": request.conversation_id}
@@ -286,7 +299,7 @@ async def retrieve(self, request: RetrieveItemRequest) -> ConversationItem:
async def list_items(self, request: ListItemsRequest) -> ConversationItemList:
"""List items in the conversation with cursor pagination."""
- await self.get_conversation(GetConversationRequest(conversation_id=request.conversation_id))
+ await self._get_validated_conversation(request.conversation_id)
order = request.order if request.order is not None else "desc"
limit = request.limit or 20
diff --git a/src/ogx/core/datatypes.py b/src/ogx/core/datatypes.py
index cf7ac9e3356..0f90b660c84 100644
--- a/src/ogx/core/datatypes.py
+++ b/src/ogx/core/datatypes.py
@@ -4,6 +4,7 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
+import re
import warnings
from enum import StrEnum
from pathlib import Path
@@ -50,14 +51,14 @@ class RegistryEntrySource(StrEnum):
class User(BaseModel):
- """An authenticated user with a principal identity and optional access control attributes."""
+ """An authenticated user with a principal identity, optional tenant, and access control attributes."""
principal: str
- # further attributes that may be used for access control decisions
+ tenant_id: str | None = None
attributes: dict[str, list[str]] | None = None
- def __init__(self, principal: str, attributes: dict[str, list[str]] | None):
- super().__init__(principal=principal, attributes=attributes)
+ def __init__(self, principal: str, attributes: dict[str, list[str]] | None, *, tenant_id: str | None = None):
+ super().__init__(principal=principal, tenant_id=tenant_id, attributes=attributes)
class ResourceWithOwner(Resource):
@@ -207,6 +208,41 @@ class AuthProviderType(StrEnum):
UPSTREAM_HEADER = "upstream_header"
+_TENANT_ID_RE = re.compile(r"^[a-z0-9][a-z0-9\-_]{0,127}$")
+
+
+def _validate_tenant_id(value: str) -> str:
+ normalized = value.strip().lower()
+ if not normalized:
+ raise ValueError("tenant_id must not be empty or blank")
+ if not _TENANT_ID_RE.match(normalized):
+ raise ValueError(f"tenant_id must match [a-z0-9][a-z0-9-_]{{0,127}}: {value!r}")
+ return normalized
+
+
+class TenancyMode(StrEnum):
+ """Multi-tenancy deployment modes."""
+
+ DISABLED = "disabled"
+ SINGLE = "single"
+ MULTI = "multi"
+
+
+class TenancyConfig(BaseModel):
+ """Multi-tenancy isolation configuration."""
+
+ mode: TenancyMode = Field(default=TenancyMode.DISABLED, description="Tenancy mode: disabled, single, or multi")
+ default_tenant_id: str | None = Field(default=None, description="Tenant ID for single-tenant mode")
+
+ @model_validator(mode="after")
+ def validate_tenancy(self) -> Self:
+ if self.mode == TenancyMode.SINGLE and not self.default_tenant_id:
+ raise ValueError("default_tenant_id is required when tenancy mode is 'single'")
+ if self.default_tenant_id:
+ self.default_tenant_id = _validate_tenant_id(self.default_tenant_id)
+ return self
+
+
class OAuth2TokenAuthConfig(BaseModel):
"""Configuration for OAuth2 token authentication."""
@@ -226,6 +262,10 @@ class OAuth2TokenAuthConfig(BaseModel):
"namespace": "namespaces",
},
)
+ tenant_claim: str | None = Field(
+ default=None,
+ description="JWT claim to extract as tenant_id (e.g. 'tenant', 'org'). When set, the claim value is used as the tenant partition key.",
+ )
jwks: OAuth2JWKSConfig | None = Field(default=None, description="JWKS configuration")
introspection: OAuth2IntrospectionConfig | None = Field(
default=None, description="OAuth2 introspection configuration"
@@ -256,6 +296,10 @@ class CustomAuthConfig(BaseModel):
...,
description="Custom authentication endpoint URL",
)
+ tenant_field: str | None = Field(
+ default=None,
+ description="Field name in the auth endpoint response to extract as tenant_id",
+ )
class GitHubTokenAuthConfig(BaseModel):
@@ -292,6 +336,10 @@ class KubernetesAuthProviderConfig(BaseModel):
},
description="Mapping of Kubernetes user claims to access attributes",
)
+ tenant_claim: str | None = Field(
+ default=None,
+ description="Kubernetes claim to extract as tenant_id (resolved via claims_mapping path syntax)",
+ )
@field_validator("api_server_url")
@classmethod
@@ -324,6 +372,10 @@ class UpstreamHeaderAuthConfig(BaseModel):
principal_header: str = Field(
description="HTTP header containing the authenticated user's identity (e.g. x-auth-user-id)",
)
+ tenant_header: str | None = Field(
+ default=None,
+ description="HTTP header containing the tenant ID (e.g. x-tenant-id). Used as the hard partition key for tenant isolation.",
+ )
attributes_header: str | None = Field(
default=None,
description="HTTP header containing JSON-encoded user attributes for access control (e.g. x-auth-attributes)",
@@ -770,6 +822,10 @@ class ServerConfig(BaseModel):
default=None,
description="Authentication configuration for the server",
)
+ tenancy: TenancyConfig = Field(
+ default_factory=TenancyConfig,
+ description="Multi-tenancy isolation configuration",
+ )
host: str | None = Field(
default=None,
description="The host the server should listen on",
diff --git a/src/ogx/core/distribution.py b/src/ogx/core/distribution.py
index fe920d2e42b..0d38ac3b05d 100644
--- a/src/ogx/core/distribution.py
+++ b/src/ogx/core/distribution.py
@@ -25,7 +25,19 @@
logger = get_logger(name=__name__, category="core")
-INTERNAL_APIS = {Api.inspect, Api.providers, Api.prompts, Api.conversations, Api.connectors, Api.admin}
+# Api.containers is served by a built-in implementation that delegates to a pluggable
+# container_runtime provider; it is not itself provider-backed. The container_runtime
+# router/resolver wiring is tracked as a follow-up (issue #5892), at which point containers
+# becomes an auto-routed API paired with container_runtime (mirroring tool_groups/tool_runtime).
+INTERNAL_APIS = {
+ Api.inspect,
+ Api.providers,
+ Api.prompts,
+ Api.conversations,
+ Api.connectors,
+ Api.admin,
+ Api.containers,
+}
def stack_apis() -> list[Api]:
diff --git a/src/ogx/core/library_client.py b/src/ogx/core/library_client.py
index 30d7919fda0..b500be909e9 100644
--- a/src/ogx/core/library_client.py
+++ b/src/ogx/core/library_client.py
@@ -28,7 +28,7 @@
from ogx.core.utils.type_inspection import is_body_param, is_unwrapped_body_param
try:
- from ogx_client import (
+ from ogx_open_client import (
NOT_GIVEN,
APIResponse,
AsyncAPIResponse,
@@ -36,8 +36,20 @@
AsyncStream,
OgxClient,
)
-except ImportError as e:
- raise ImportError("ogx-client is not installed. Please install it with `uv pip install ogx[client]`.") from e
+except ImportError:
+ try:
+ from ogx_client import ( # type: ignore[import-not-found,assignment,no-redef]
+ NOT_GIVEN,
+ APIResponse,
+ AsyncAPIResponse,
+ AsyncOgxClient,
+ AsyncStream,
+ OgxClient,
+ )
+ except ImportError as e:
+ raise ImportError(
+ "ogx-open-client is not installed. Please install it with `uv pip install ogx[openclient]` or `uv pip install ogx[client]`."
+ ) from e
from pydantic import BaseModel, TypeAdapter
from rich.console import Console
@@ -53,6 +65,7 @@
from ogx.core.utils.context import preserve_contexts_async_generator
from ogx.core.utils.exec import in_notebook
from ogx.log import get_logger, setup_logging
+from ogx.providers.utils.files.response import response_body_bytes
logger = get_logger(name=__name__, category="core")
@@ -154,13 +167,8 @@ async def read(self) -> bytes:
class LibraryClientHttpxResponse:
"""LibraryClient httpx Response object for FastAPI Response conversion."""
- def __init__(self, response: FastAPIResponse) -> None:
- if isinstance(response.body, bytes):
- self.content = response.body
- elif isinstance(response.body, memoryview):
- self.content = bytes(response.body)
- else:
- self.content = response.body.encode()
+ def __init__(self, response: FastAPIResponse, content: bytes) -> None:
+ self.content = content
self.status_code = response.status_code
self.headers = response.headers
@@ -204,6 +212,14 @@ def __init__(
atexit.register(self.shutdown) # Safety net: if the user forgets to shutdown properly
+ # Patch api_client.call_api to route requests in-process instead of over HTTP.
+ # The generated SDK's call chain is: API method → api_client.call_api() → rest.request() → httpx.
+ # We intercept at call_api so the request never reaches httpx/network.
+ # Only applies to ogx_open_client; the stainless SDK uses a request() override instead.
+ if hasattr(self, "api_client") and hasattr(self.api_client, "call_api"):
+ self._original_call_api = self.api_client.call_api
+ self.api_client.call_api = self._in_process_call_api # type: ignore[method-assign]
+
def _run_event_loop(self) -> None:
"""Runs forever in the background thread."""
asyncio.set_event_loop(self.loop)
@@ -355,6 +371,200 @@ async def _consume() -> None:
finally:
future.cancel()
+ def _in_process_call_api(
+ self,
+ method,
+ url,
+ header_params=None,
+ body=None,
+ post_params=None,
+ _request_timeout=None,
+ ):
+ """Route API calls in-process instead of over HTTP.
+
+ Intercepts the generated SDK's call_api() to execute FastAPI endpoint
+ handlers directly, avoiding network I/O. The method signature matches
+ ApiClient.call_api() so it can be used as a drop-in replacement.
+ """
+
+ coro = self._async_in_process_call(
+ method=method,
+ url=url,
+ header_params=header_params,
+ body=body,
+ post_params=post_params,
+ )
+ future = asyncio.run_coroutine_threadsafe(coro, self.loop)
+ return future.result(timeout=_HANG_GUARD_TIMEOUT)
+
+ async def _async_in_process_call(
+ self,
+ *,
+ method: str,
+ url: str,
+ header_params: dict[str, str] | None = None,
+ body: Any = None,
+ post_params: list | None = None,
+ ):
+ """Async implementation of in-process API call routing."""
+ from urllib.parse import urlparse
+
+ from fastapi.responses import StreamingResponse
+
+ try:
+ from ogx_open_client.rest import RESTResponse
+ except ImportError:
+ from ogx_client.rest import RESTResponse # type: ignore[import-not-found,assignment,no-redef]
+
+ async_client = self.async_client
+ assert async_client.route_impls is not None, "Client not initialized"
+
+ # Extract path from full URL (strip http://localhost:port prefix)
+ parsed = urlparse(url)
+ path = parsed.path
+ # Append query string to path if present (some endpoints use query params)
+ query_string = parsed.query
+
+ # Build request headers with provider data
+ request_headers = async_client._sanitize_headers(header_params)
+ if async_client.provider_data:
+ keys = ["X-OGX-Provider-Data", "x-ogx-provider-data"]
+ if all(key not in request_headers for key in keys):
+ request_headers["X-OGX-Provider-Data"] = json.dumps(async_client.provider_data)
+
+ with request_provider_data_context(request_headers):
+ # Build the body dict from JSON body and/or post_params
+ request_body: Any = {}
+ if body and isinstance(body, dict):
+ request_body = body.copy()
+ elif body and isinstance(body, list):
+ # Some endpoints accept list bodies (e.g., batch insert)
+ request_body = body
+
+ # Handle multipart form data (file uploads)
+ if post_params:
+ for param in post_params:
+ if isinstance(param, list | tuple) and len(param) == 2:
+ k, v = param
+ if isinstance(v, tuple) and len(v) == 3:
+ # File tuple: (filename, content, content_type)
+ filename, content, _content_type = v
+ if isinstance(content, bytes):
+ from io import BytesIO as _BytesIO
+
+ file_obj = _BytesIO(content)
+ file_obj.name = filename
+ request_body[k] = LibraryClientUploadFile(filename, content)
+ else:
+ request_body[k] = v
+ elif isinstance(v, dict):
+ # Bracket-notation dicts were flattened for HTTP;
+ # reconstruct as nested dict for in-process call
+ request_body[k] = v
+ else:
+ request_body[k] = v
+
+ # Parse query params and merge into body.
+ # In a normal HTTP framework, query params and body fields occupy
+ # separate namespaces. Here we flatten them into a single dict so
+ # we can call the route handler directly. A collision should never
+ # happen with the current API design, but we log a warning if it
+ # does so it doesn't silently go unnoticed.
+ if query_string:
+ from urllib.parse import parse_qs
+
+ query_params = {k: v[0] if len(v) == 1 else v for k, v in parse_qs(query_string).items()}
+ if isinstance(request_body, dict):
+ collisions = set(query_params.keys()) & set(request_body.keys())
+ if collisions:
+ logger.warning(
+ "Query params collide with body fields, body takes precedence",
+ colliding_keys=collisions,
+ path=path,
+ )
+ query_params.update(request_body)
+ request_body = query_params
+ else:
+ request_body.update(query_params)
+
+ # Find the matching route handler
+ matched_func, path_params, route_path, _ = find_matching_route(method, path, async_client.route_impls)
+
+ # Merge path params into body
+ if isinstance(request_body, dict):
+ request_body.update(path_params)
+
+ # Convert body to proper function kwargs
+ exclude_params: set[str] = set()
+ if isinstance(request_body, dict):
+ # Track file upload fields for exclusion from type conversion
+ for k, v in request_body.items():
+ if isinstance(v, LibraryClientUploadFile):
+ exclude_params.add(k)
+ request_body = async_client._convert_body(matched_func, request_body, exclude_params=exclude_params)
+
+ # Execute the endpoint handler
+ if isinstance(request_body, dict):
+ result = await matched_func(**request_body)
+ else:
+ result = await matched_func(request_body)
+
+ # Build the response
+ if isinstance(result, StreamingResponse):
+ # Streaming response — collect SSE chunks into a sync-iterable response.
+ # TODO: This buffers the entire stream before returning, losing time-to-first-token
+ # benefits. For true incremental streaming, we'd need a SyncByteStream adapter that
+ # bridges the async generator to sync iter_bytes() via a queue (similar to
+ # _stream_request). Acceptable for now since in-process library mode is primarily
+ # used for testing, not latency-sensitive production streaming.
+ content_type = result.media_type or "text/event-stream"
+
+ # Collect all chunks from the async generator
+ chunks: list[bytes] = []
+ async for chunk in result.body_iterator:
+ if isinstance(chunk, str):
+ chunks.append(chunk.encode("utf-8"))
+ elif isinstance(chunk, memoryview):
+ chunks.append(bytes(chunk))
+ else:
+ chunks.append(chunk)
+ all_content = b"".join(chunks)
+
+ mock_response = httpx.Response(
+ status_code=result.status_code,
+ content=all_content,
+ headers={"Content-Type": content_type},
+ request=httpx.Request(method=method, url=url),
+ )
+ return RESTResponse(mock_response)
+
+ # Handle FastAPI Response objects
+ if isinstance(result, FastAPIResponse):
+ resp = LibraryClientHttpxResponse(result, await response_body_bytes(result))
+ return RESTResponse(
+ httpx.Response(
+ status_code=resp.status_code,
+ content=resp.content if isinstance(resp.content, bytes) else resp.content.encode("utf-8"),
+ headers=dict(resp.headers),
+ request=httpx.Request(method=method, url=url),
+ )
+ )
+
+ # Non-streaming JSON response
+ json_content = json.dumps(convert_pydantic_to_json_value(result))
+ status_code = httpx.codes.OK
+ if method.upper() == "DELETE" and result is None:
+ status_code = httpx.codes.NO_CONTENT
+ json_content = ""
+
+ mock_response = httpx.Response(
+ status_code=status_code,
+ content=json_content.encode("utf-8") if json_content else b"",
+ headers={"Content-Type": "application/json"},
+ request=httpx.Request(method=method, url=url),
+ )
+ return RESTResponse(mock_response)
+
class AsyncOGXAsLibraryClient(AsyncOgxClient):
"""Async client that runs a OGX distribution in-process as a library."""
@@ -614,7 +824,7 @@ async def _call_non_streaming(
# Handle FastAPI Response objects (e.g., from file content retrieval)
if isinstance(result, FastAPIResponse):
- return LibraryClientHttpxResponse(result)
+ return LibraryClientHttpxResponse(result, await response_body_bytes(result))
json_content = json.dumps(convert_pydantic_to_json_value(result))
@@ -642,7 +852,7 @@ async def _call_non_streaming(
json=convert_pydantic_to_json_value(filtered_body),
),
)
- response = APIResponse(
+ response: APIResponse[Any] = APIResponse(
raw=mock_response,
client=self,
cast_to=cast_to,
@@ -721,7 +931,7 @@ async def gen() -> AsyncGenerator[bytes, None]:
# mypy can't track runtime variables inside the [...] of a generic, so ignore that check
args = get_args(stream_cls)
stream_cls = AsyncStream[args[0]] # type: ignore[valid-type]
- response = AsyncAPIResponse(
+ response: AsyncAPIResponse = AsyncAPIResponse( # type: ignore[call-arg]
raw=mock_response,
client=self,
cast_to=cast_to,
diff --git a/src/ogx/core/request_headers.py b/src/ogx/core/request_headers.py
index 6940500ecd2..f655a96ec0a 100644
--- a/src/ogx/core/request_headers.py
+++ b/src/ogx/core/request_headers.py
@@ -6,6 +6,7 @@
import contextvars
import json
+import os
from contextlib import AbstractContextManager
from typing import TYPE_CHECKING, Any, cast
@@ -104,15 +105,43 @@ def parse_request_provider_data(headers: dict[str, str]) -> dict[str, Any] | Non
log.error("Provider data must be encoded as a JSON object")
return None
+ reserved_keys = {"__authenticated_user"}
+ for key in reserved_keys:
+ if key in parsed:
+ log.warning("Stripping reserved key from provider data", key=key)
+ del parsed[key]
+
return cast(dict[str, Any], parsed)
def request_provider_data_context(headers: dict[str, str], user: User | None = None) -> AbstractContextManager[None]:
"""Context manager that sets request provider data from headers and user for the duration of the context"""
provider_data = parse_request_provider_data(headers)
+ if user is None and provider_data is not None:
+ user = _test_authenticated_user_from_provider_data(provider_data)
return RequestProviderDataContext(provider_data, user)
+def _test_authenticated_user_from_provider_data(provider_data: dict[str, Any]) -> User | None:
+ if not os.environ.get("OGX_TEST_INFERENCE_MODE"):
+ return None
+
+ raw_user = provider_data.get("__test_authenticated_user")
+ if raw_user is None:
+ return None
+ if isinstance(raw_user, User):
+ return raw_user
+ if not isinstance(raw_user, dict):
+ log.warning("Ignoring invalid test authenticated user provider data")
+ return None
+
+ try:
+ return User(raw_user["principal"], raw_user.get("attributes"))
+ except (KeyError, TypeError, ValueError) as e:
+ log.warning("Ignoring invalid test authenticated user provider data", error=str(e))
+ return None
+
+
def get_authenticated_user() -> User | None:
"""Helper to retrieve auth attributes from the provider data context"""
provider_data = PROVIDER_DATA_VAR.get()
@@ -130,4 +159,5 @@ def user_from_scope(scope: Scope) -> User | None:
if not principal and not user_attributes:
return None
- return User(principal=principal, attributes=user_attributes)
+ tenant_id = scope.get("tenant_id")
+ return User(principal=principal, attributes=user_attributes, tenant_id=tenant_id)
diff --git a/src/ogx/core/resolver.py b/src/ogx/core/resolver.py
index af2b774fc2f..543935601ad 100644
--- a/src/ogx/core/resolver.py
+++ b/src/ogx/core/resolver.py
@@ -4,6 +4,7 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
+import graphlib
import importlib
import importlib.metadata
import inspect
@@ -42,6 +43,7 @@
ProviderSpec,
RemoteProviderSpec,
Responses,
+ Skills,
ToolGroups,
ToolGroupsProtocolPrivate,
ToolRuntime,
@@ -89,6 +91,7 @@ def api_protocol_map(external_apis: dict[Api, ExternalApiSpec] | None = None) ->
Api.connectors: Connectors,
Api.messages: Messages,
Api.interactions: Interactions,
+ Api.skills: Skills,
}
if external_apis:
@@ -341,36 +344,30 @@ def topological_sort(
Returns:
A flattened list of (api_name, provider) tuples in dependency order.
- """
- def dfs(kv, visited: set[str], stack: list[str]):
- api_str, providers = kv
- visited.add(api_str)
+ Raises:
+ RuntimeError: If there is a circular dependency between providers.
+ """
+ ts: graphlib.TopologicalSorter[str] = graphlib.TopologicalSorter()
- deps = []
+ for api_str, providers in providers_with_specs.items():
+ deps = set()
for provider in providers:
for dep in provider.spec.deps__:
- deps.append(dep)
-
- for dep in deps:
- if dep not in visited and dep in providers_with_specs:
- dfs((dep, providers_with_specs[dep]), visited, stack)
-
- stack.append(api_str)
-
- visited: set[str] = set()
- stack: list[str] = []
-
- for api_str, providers in providers_with_specs.items():
- if api_str not in visited:
- dfs((api_str, providers), visited, stack)
-
- flattened = []
- for api_str in stack:
- for provider in providers_with_specs[api_str]:
- flattened.append((api_str, provider))
-
- return flattened
+ if dep in providers_with_specs:
+ deps.add(dep)
+ ts.add(api_str, *deps)
+
+ try:
+ flattened = []
+ for api_str in ts.static_order():
+ for provider in providers_with_specs[api_str]:
+ flattened.append((api_str, provider))
+
+ return flattened
+ except graphlib.CycleError as e:
+ cycle: list[str] = e.args[1] if len(e.args) > 1 else []
+ raise RuntimeError(f"Failed to sort providers: circular dependency detected involving APIs {cycle}") from e
async def instantiate_provider(
diff --git a/src/ogx/core/server/README.md b/src/ogx/core/server/README.md
index 543553e7f78..2a54deaa6ca 100644
--- a/src/ogx/core/server/README.md
+++ b/src/ogx/core/server/README.md
@@ -30,7 +30,8 @@ Routes are defined as native FastAPI routers. `fastapi_router_registry.py` auto-
### Middleware
- **`RequestMetricsMiddleware`** (`metrics.py`): Tracks per-API request counts and latency metrics. Runs as the outermost middleware.
-- **`AuthenticationMiddleware`** (`auth.py`): Validates Bearer tokens using a configured auth provider (Kubernetes, custom endpoint). Extracts user identity and attributes for access control. Endpoints can opt out by setting `openapi_extra={PUBLIC_ROUTE_KEY: True}` on their route.
+- **`AuthenticationMiddleware`** (`auth.py`): Validates Bearer tokens using a configured auth provider (Kubernetes, custom endpoint). Extracts user identity, attributes, and `tenant_id` for access control. Each auth provider resolves `tenant_id` from its source (JWT claim, HTTP header, K8s claim, or custom endpoint field). Endpoints can opt out by setting `openapi_extra={PUBLIC_ROUTE_KEY: True}` on their route.
+- **`TenancyMiddleware`** (`auth.py`): Enforces the configured tenancy mode after authentication. In `disabled` mode: passthrough. In `single` mode: overrides `tenant_id` to the configured default (works with or without auth). In `multi` mode: rejects requests with no `tenant_id` (401).
- **`RouteAuthorizationMiddleware`** (`auth.py`): Enforces route-level access policies based on user roles.
- **`ClientVersionMiddleware`** (`server.py`): Rejects requests from clients with incompatible major.minor versions.
- **`ProviderDataMiddleware`** (`server.py`): Sets up request context for provider data propagation and test context.
diff --git a/src/ogx/core/server/auth.py b/src/ogx/core/server/auth.py
index c244ce07dc6..03cfbd7fa81 100644
--- a/src/ogx/core/server/auth.py
+++ b/src/ogx/core/server/auth.py
@@ -13,12 +13,15 @@
from ogx.core.access_control.conditions import User as ProtocolUser
from ogx.core.access_control.conditions import parse_conditions
from ogx.core.access_control.datatypes import RouteAccessRule
-from ogx.core.datatypes import AuthenticationConfig, User
+from ogx.core.datatypes import AuthenticationConfig, TenancyConfig, TenancyMode, User
from ogx.core.request_headers import user_from_scope
from ogx.core.server.auth_providers import create_auth_provider
-from ogx.core.server.routes import find_matching_route, initialize_route_impls
+from ogx.core.server.routes import (
+ RouteImpls,
+ build_route_impls_from_routes,
+ find_matching_route,
+)
from ogx.log import get_logger
-from ogx_api import Api
from ogx_api.common.errors import AuthServiceUnavailableError, OpenAIErrorResponse, TokenValidationError
logger = get_logger(name=__name__, category="core::auth")
@@ -92,31 +95,41 @@ class AuthenticationMiddleware:
access resources that don't have access_attributes defined.
"""
- def __init__(self, app: ASGIApp, auth_config: AuthenticationConfig, impls: dict[Api, Any]) -> None:
+ def __init__(self, app: ASGIApp, auth_config: AuthenticationConfig) -> None:
self.app = app
- self.impls = impls
self.auth_provider = create_auth_provider(auth_config)
+ self._route_impls: RouteImpls | None = None
async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
- if scope["type"] == "http":
+ # Authenticate both HTTP requests and WebSocket handshakes. WebSocket
+ # connections carry their bearer token in the handshake headers just like
+ # HTTP, but skip this middleware unless we handle the "websocket" scope
+ # type explicitly (otherwise they reach the app unauthenticated).
+ if scope["type"] in ("http", "websocket"):
+ is_websocket = scope["type"] == "websocket"
# Find the route and check if authentication is required
path = scope.get("path", "")
method = scope.get("method", "GET")
- if not hasattr(self, "route_impls"):
- self.route_impls = initialize_route_impls(self.impls)
+ if self._route_impls is None:
+ top_app = scope.get("app")
+ assert top_app is not None, "scope must contain the FastAPI app under the 'app' key"
+ self._route_impls = build_route_impls_from_routes(top_app.router.routes)
+ # WebSocket routes are not part of the generated webmethod table, so
+ # the require_authentication opt-out only applies to HTTP routes.
webmethod = None
- try:
- _, _, _, webmethod = find_matching_route(method, path, self.route_impls)
- except ValueError:
- # If no matching endpoint is found, pass here to run auth anyways
- pass
+ if not is_websocket:
+ try:
+ _, _, _, webmethod = find_matching_route(method, path, self._route_impls)
+ except ValueError:
+ # If no matching endpoint is found, pass here to run auth anyways
+ pass
- # If webmethod explicitly sets require_authentication=False, allow without auth
- if webmethod and webmethod.require_authentication is False:
- logger.debug("Allowing unauthenticated access to endpoint", path=path)
- return await self.app(scope, receive, send)
+ # If webmethod explicitly sets require_authentication=False, allow without auth
+ if webmethod and webmethod.require_authentication is False:
+ logger.debug("Allowing unauthenticated access to endpoint", path=path)
+ return await self.app(scope, receive, send)
# Handle authentication
if self.auth_provider.requires_http_bearer:
@@ -125,10 +138,12 @@ async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
if not auth_header:
error_msg = self.auth_provider.get_auth_error_message(scope)
- return await self._send_auth_error(send, error_msg)
+ return await self._send_auth_error(send, error_msg, is_websocket=is_websocket)
if not auth_header.startswith("Bearer "):
- return await self._send_auth_error(send, "Invalid Authorization header format")
+ return await self._send_auth_error(
+ send, "Invalid Authorization header format", is_websocket=is_websocket
+ )
token = auth_header.split("Bearer ", 1)[1]
else:
@@ -139,19 +154,21 @@ async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
validation_result = await self.auth_provider.validate_token(token, scope)
except AuthServiceUnavailableError as e:
logger.warning("Authentication service unavailable", error=str(e))
- return await self._send_auth_error(send, str(e), status=503)
+ return await self._send_auth_error(send, str(e), status=503, is_websocket=is_websocket)
except httpx.TimeoutException:
logger.warning("Authentication request timed out")
- return await self._send_auth_error(send, "Authentication service timeout", status=503)
+ return await self._send_auth_error(
+ send, "Authentication service timeout", status=503, is_websocket=is_websocket
+ )
except TokenValidationError as e:
logger.warning("Token validation failed", error=str(e))
- return await self._send_auth_error(send, str(e))
+ return await self._send_auth_error(send, str(e), is_websocket=is_websocket)
except ValueError as e:
logger.warning("Authentication error", error=str(e))
- return await self._send_auth_error(send, str(e))
+ return await self._send_auth_error(send, str(e), is_websocket=is_websocket)
except Exception:
logger.exception("Error during authentication")
- return await self._send_auth_error(send, "Authentication service error")
+ return await self._send_auth_error(send, "Authentication service error", is_websocket=is_websocket)
# Store the client ID in the request scope for downstream use
# (e.g., access control, logging, per-client context).
@@ -161,15 +178,23 @@ async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
scope["principal"] = validation_result.principal
if validation_result.attributes:
scope["user_attributes"] = validation_result.attributes
+ if validation_result.tenant_id:
+ scope["tenant_id"] = validation_result.tenant_id
logger.debug(
"Authentication successful: with attributes",
principal=validation_result.principal,
attributes_count=len(validation_result.attributes) if validation_result.attributes else 0,
+ tenant_id=validation_result.tenant_id,
)
return await self.app(scope, receive, send)
- async def _send_auth_error(self, send: Send, message: str, status: int = 401) -> None:
+ async def _send_auth_error(self, send: Send, message: str, status: int = 401, is_websocket: bool = False) -> None:
+ if is_websocket:
+ # Reject the handshake before it is accepted. 4401 is the WebSocket
+ # convention for "unauthorized" (4000-4999 is the app-defined range).
+ await send({"type": "websocket.close", "code": 4401})
+ return
await send(
{
"type": "http.response.start",
@@ -194,14 +219,16 @@ def __init__(self, app: ASGIApp, route_policy: list[RouteAccessRule]) -> None:
self.route_policy = route_policy
async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
- # Only process HTTP requests
- if scope["type"] != "http":
+ # Authorize HTTP requests and WebSocket handshakes; everything else
+ # (e.g. lifespan) passes through untouched.
+ if scope["type"] not in ("http", "websocket"):
return await self.app(scope, receive, send)
# If no route policy configured, allow all routes (backward compatible)
if not self.route_policy:
return await self.app(scope, receive, send)
+ is_websocket = scope["type"] == "websocket"
route = scope.get("path", "")
# Normalize route: remove trailing slash (except for root "/")
if route != "/" and route.endswith("/"):
@@ -213,7 +240,10 @@ async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
# Check if user has permission to access this route
if not self._is_route_allowed(route, user):
return await self._send_error(
- send, f"Access denied: insufficient permissions for route {route}", status=403
+ send,
+ f"Access denied: insufficient permissions for route {route}",
+ status=403,
+ is_websocket=is_websocket,
)
return await self.app(scope, receive, send)
@@ -369,8 +399,12 @@ def _evaluate_conditions(self, rule: RouteAccessRule, user: User | None) -> bool
# No conditions specified - rule applies regardless of user
return True
- async def _send_error(self, send: Send, message: str, status: int = 403) -> None:
+ async def _send_error(self, send: Send, message: str, status: int = 403, is_websocket: bool = False) -> None:
"""Send an error response."""
+ if is_websocket:
+ # 4403 mirrors the HTTP 403 forbidden in the app-defined close range.
+ await send({"type": "websocket.close", "code": 4403})
+ return
await send(
{
"type": "http.response.start",
@@ -382,6 +416,73 @@ async def _send_error(self, send: Send, message: str, status: int = 403) -> None
await send({"type": "http.response.body", "body": error_msg})
+class TenancyMiddleware:
+ """Middleware that enforces tenancy mode after authentication.
+
+ In disabled mode, this is a no-op passthrough.
+ In single mode, overrides tenant_id to default_tenant_id on every request.
+ In multi mode, rejects requests that have no tenant_id after auth resolution.
+ """
+
+ def __init__(self, app: ASGIApp, tenancy_config: TenancyConfig) -> None:
+ self.app = app
+ self.tenancy_config = tenancy_config
+ self._route_impls: RouteImpls | None = None
+
+ async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
+ if scope["type"] not in ("http", "websocket"):
+ return await self.app(scope, receive, send)
+
+ if self.tenancy_config.mode == TenancyMode.DISABLED:
+ return await self.app(scope, receive, send)
+
+ is_websocket = scope["type"] == "websocket"
+ if not is_websocket and self._is_public_route(scope):
+ return await self.app(scope, receive, send)
+
+ if self.tenancy_config.mode == TenancyMode.SINGLE:
+ scope["tenant_id"] = self.tenancy_config.default_tenant_id
+ if not scope.get("principal"):
+ scope["principal"] = "system"
+ elif self.tenancy_config.mode == TenancyMode.MULTI:
+ if not scope.get("tenant_id"):
+ return await self._send_error(
+ send,
+ "Tenant context required but not resolved from authentication",
+ is_websocket=is_websocket,
+ )
+
+ return await self.app(scope, receive, send)
+
+ def _is_public_route(self, scope: Scope) -> bool:
+ if self._route_impls is None:
+ top_app = scope.get("app")
+ assert top_app is not None, "scope must contain the FastAPI app under the 'app' key"
+ self._route_impls = build_route_impls_from_routes(top_app.router.routes)
+
+ path = scope.get("path", "")
+ method = scope.get("method", "GET")
+ try:
+ _, _, _, webmethod = find_matching_route(method, path, self._route_impls)
+ except ValueError:
+ return False
+ return webmethod.require_authentication is False
+
+ async def _send_error(self, send: Send, message: str, is_websocket: bool = False) -> None:
+ if is_websocket:
+ await send({"type": "websocket.close", "code": 4401})
+ return
+ await send(
+ {
+ "type": "http.response.start",
+ "status": 401,
+ "headers": [[b"content-type", b"application/json"]],
+ }
+ )
+ error_msg = OpenAIErrorResponse.from_message(message).to_bytes()
+ await send({"type": "http.response.body", "body": error_msg})
+
+
class _RouteContext:
"""Placeholder resource for route-level condition evaluation.
diff --git a/src/ogx/core/server/auth_providers.py b/src/ogx/core/server/auth_providers.py
index a3759f4cf05..c439d272a80 100644
--- a/src/ogx/core/server/auth_providers.py
+++ b/src/ogx/core/server/auth_providers.py
@@ -25,6 +25,7 @@
OAuth2TokenAuthConfig,
UpstreamHeaderAuthConfig,
User,
+ _validate_tenant_id,
)
from ogx.log import get_logger
from ogx_api import AuthServiceUnavailableError, TokenValidationError
@@ -32,6 +33,20 @@
logger = get_logger(name=__name__, category="core::auth")
+def _resolve_tenant_id(raw_value: str | None) -> str | None:
+ """Validate and normalize a raw tenant value from a claim/header/field.
+
+ Returns None if the value is missing or blank (callers decide whether
+ that is an error based on tenancy mode).
+ """
+ if raw_value is None:
+ return None
+ stripped = raw_value.strip()
+ if not stripped:
+ return None
+ return _validate_tenant_id(stripped)
+
+
class AuthResponse(BaseModel):
"""The format of the authentication response from the auth endpoint."""
@@ -216,9 +231,17 @@ async def validate_jwt_token(self, token: str, scope: Scope | None = None) -> Us
# We should incorporate these into the access attributes.
principal = claims["sub"]
access_attributes = get_attributes_from_claims(claims, self.config.claims_mapping)
+
+ tenant_id: str | None = None
+ if self.config.tenant_claim:
+ raw = claims.get(self.config.tenant_claim)
+ if isinstance(raw, str):
+ tenant_id = _resolve_tenant_id(raw)
+
return User(
principal=principal,
attributes=access_attributes,
+ tenant_id=tenant_id,
)
async def introspect_token(self, token: str, scope: Scope | None = None) -> User:
@@ -266,9 +289,17 @@ async def introspect_token(self, token: str, scope: Scope | None = None) -> User
raise ValueError("Token not active")
principal = fields["sub"] or fields["username"]
access_attributes = get_attributes_from_claims(fields, self.config.claims_mapping)
+
+ tenant_id: str | None = None
+ if self.config.tenant_claim:
+ raw = fields.get(self.config.tenant_claim)
+ if isinstance(raw, str):
+ tenant_id = _resolve_tenant_id(raw)
+
return User(
principal=principal,
attributes=access_attributes,
+ tenant_id=tenant_id,
)
except (httpx.TimeoutException, httpx.ConnectError, httpx.NetworkError) as exc:
logger.warning("Failed to reach token introspection endpoint", error=str(exc))
@@ -341,7 +372,18 @@ async def validate_token(self, token: str, scope: Scope | None = None) -> User:
try:
response_data = response.json()
auth_response = AuthResponse(**response_data)
- return User(principal=auth_response.principal, attributes=auth_response.attributes)
+
+ tenant_id: str | None = None
+ if self.config.tenant_field:
+ raw = response_data.get(self.config.tenant_field)
+ if isinstance(raw, str):
+ tenant_id = _resolve_tenant_id(raw)
+
+ return User(
+ principal=auth_response.principal,
+ attributes=auth_response.attributes,
+ tenant_id=tenant_id,
+ )
except Exception as e:
logger.exception("Error parsing authentication response")
raise ValueError("Invalid authentication response format") from e
@@ -550,9 +592,17 @@ async def validate_token(self, token: str, scope: Scope | None = None) -> User:
# Build user attributes from Kubernetes user info
user_attributes = get_attributes_from_claims(user_info, self.config.claims_mapping)
+ tenant_id: str | None = None
+ if self.config.tenant_claim:
+ tenant_claims = get_attributes_from_claims(user_info, {self.config.tenant_claim: "__tenant__"})
+ raw_values = tenant_claims.get("__tenant__")
+ if raw_values:
+ tenant_id = _resolve_tenant_id(raw_values[0])
+
return User(
principal=username,
attributes=user_attributes,
+ tenant_id=tenant_id,
)
except (httpx.TimeoutException, httpx.ConnectError, httpx.NetworkError) as exc:
@@ -648,7 +698,14 @@ async def validate_token(self, token: str, scope: Scope | None = None) -> User:
else:
attributes[attr_category] = values
- return User(principal=principal, attributes=attributes)
+ tenant_id: str | None = None
+ if self.config.tenant_header:
+ tenant_key = self.config.tenant_header.lower().encode()
+ tenant_value = headers.get(tenant_key)
+ if tenant_value:
+ tenant_id = _resolve_tenant_id(tenant_value.decode())
+
+ return User(principal=principal, attributes=attributes, tenant_id=tenant_id)
async def close(self) -> None:
pass
diff --git a/src/ogx/core/server/metrics.py b/src/ogx/core/server/metrics.py
index 860feb209b7..c900065efde 100644
--- a/src/ogx/core/server/metrics.py
+++ b/src/ogx/core/server/metrics.py
@@ -14,6 +14,7 @@
from opentelemetry.metrics import Counter, Histogram, UpDownCounter
from starlette.types import ASGIApp, Receive, Scope, Send
+from ogx.core.server.fastapi_router_registry import _ROUTER_FACTORIES
from ogx.log import get_logger
from ogx.telemetry.constants import (
CONCURRENT_REQUESTS,
@@ -141,12 +142,13 @@ class RequestMetricsMiddleware:
- ogx.concurrent_requests: up-down counter by api
"""
- def __init__(self, app: ASGIApp, route_to_api: dict[str, RouteInfo] | None = None) -> None:
+ def __init__(self, app: ASGIApp) -> None:
self.app = app
- self._patterns: list[tuple[re.Pattern[str], RouteInfo]] = _compile_route_patterns(route_to_api or {})
+ self._patterns: list[tuple[re.Pattern[str], RouteInfo]] | None = None
def _resolve_route(self, http_method: str, path: str) -> RouteInfo:
"""Resolve HTTP method + path to RouteInfo using compiled route patterns."""
+ assert self._patterns is not None, "Patterns not initialized"
lookup = f"{http_method}:{path}"
for pattern, route_info in self._patterns:
if pattern.match(lookup):
@@ -162,6 +164,13 @@ async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
if any(path.startswith(excluded) for excluded in _EXCLUDED_PATHS):
return await self.app(scope, receive, send)
+ # Lazy: build route->metrics patterns from FastAPI app on first request
+ if self._patterns is None:
+ fastapi_app = scope.get("app")
+ assert fastapi_app is not None, "scope['app'] must be set when RequestMetricsMiddleware is used"
+ route_to_api = build_route_to_api_map(_ROUTER_FACTORIES, fastapi_app.stack.impls)
+ self._patterns = _compile_route_patterns(route_to_api)
+
http_method = scope.get("method", "GET")
route_info = self._resolve_route(http_method, path)
base_attrs = {"api": route_info.api, "method": route_info.method}
diff --git a/src/ogx/core/server/routes.py b/src/ogx/core/server/routes.py
index ca94b575923..d69f4c9bb78 100644
--- a/src/ogx/core/server/routes.py
+++ b/src/ogx/core/server/routes.py
@@ -9,6 +9,8 @@
from dataclasses import dataclass
from typing import Any
+from fastapi.routing import APIRoute
+
from ogx.core.server.fastapi_router_registry import (
_ROUTER_FACTORIES,
build_fastapi_router,
@@ -101,3 +103,32 @@ def find_matching_route(method: str, path: str, route_impls: RouteImpls) -> Rout
return func, path_params, route_path, webmethod
raise ValueError(f"No endpoint found for {path}")
+
+
+def build_route_impls_from_routes(routes: list[Any]) -> RouteImpls:
+ """Build RouteImpls from mounted FastAPI routes.
+
+ This is used by middleware to introspect registered routes without needing
+ the provider impls. Routes are introspected from the FastAPI router directly
+ rather than built from scratch during server startup.
+
+ Args:
+ routes: The list of routes from app.router.routes
+
+ Returns:
+ RouteImpls mapping method -> path regex -> (endpoint, path, RouteAuthInfo)
+ """
+ route_impls: RouteImpls = {}
+ for route in routes:
+ if not isinstance(route, APIRoute):
+ continue
+ methods = [m for m in (route.methods or []) if m != "HEAD"]
+ if not methods:
+ continue
+ method = methods[0].lower()
+ if method not in route_impls:
+ route_impls[method] = {}
+ is_public = (route.openapi_extra or {}).get(PUBLIC_ROUTE_KEY, False)
+ auth_info = RouteAuthInfo(require_authentication=not is_public)
+ route_impls[method][_convert_path_to_regex(route.path)] = (route.endpoint, route.path, auth_info)
+ return route_impls
diff --git a/src/ogx/core/server/server.py b/src/ogx/core/server/server.py
index ef7298509ad..7f395102da6 100644
--- a/src/ogx/core/server/server.py
+++ b/src/ogx/core/server/server.py
@@ -29,6 +29,7 @@
from ogx.core.datatypes import (
AuthenticationRequiredError,
StackConfig,
+ TenancyMode,
)
from ogx.core.distribution import builtin_automatically_routed_apis
from ogx.core.exceptions import translate_exception
@@ -38,7 +39,6 @@
user_from_scope,
)
from ogx.core.server.fastapi_router_registry import (
- _ROUTER_FACTORIES,
build_fastapi_router,
register_external_api_routers,
)
@@ -52,8 +52,8 @@
from ogx_api import Api, ConflictError, ResourceNotFoundError
from ogx_api.common.errors import OpenAIErrorResponse
-from .auth import AuthenticationMiddleware, RouteAuthorizationMiddleware
-from .metrics import RequestMetricsMiddleware, build_route_to_api_map
+from .auth import AuthenticationMiddleware, RouteAuthorizationMiddleware, TenancyMiddleware
+from .metrics import RequestMetricsMiddleware
REPO_ROOT = Path(__file__).parent.parent.parent.parent
@@ -147,6 +147,25 @@ def __init__(self, config: StackConfig, *args: Any, **kwargs: Any) -> None:
reset_sqlstore_engines()
+ # Reset provider clients that may have been created in the temporary
+ # event loop during model listing (refresh_registry_once).
+ # Like SQL engines, the Google genai Client eagerly binds an internal
+ # httpx.AsyncClient to the current event loop, and the cached client
+ # becomes unusable after the temporary loop is terminated.
+ #
+ # Top-level impls are routing tables (CommonRoutingTableImpl), not the
+ # actual provider adapters. Walk into impls_by_provider_id to reach
+ # the real providers (e.g., VertexAIInferenceAdapter).
+ if self.stack.impls:
+ for impl in self.stack.impls.values():
+ reset_fn = getattr(impl, "_reset_client", None)
+ if reset_fn is not None:
+ reset_fn()
+ for provider in getattr(impl, "impls_by_provider_id", {}).values():
+ reset_fn = getattr(provider, "_reset_client", None)
+ if reset_fn is not None:
+ reset_fn()
+
@asynccontextmanager
async def lifespan(app: StackApp) -> AsyncIterator[None]:
@@ -218,7 +237,7 @@ def __init__(self, app: ASGIApp) -> None:
self.app = app
async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
- if scope["type"] == "http":
+ if scope["type"] in ("http", "websocket"):
headers = {k.decode(): v.decode() for k, v in scope.get("headers", [])}
user = user_from_scope(dict(scope))
@@ -242,6 +261,100 @@ async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
return await self.app(scope, receive, send)
+class ZstdDecompressionMiddleware:
+ """
+ ASGI middleware that decompresses zstd-encoded request bodies.
+
+ If the request body is not zstd-encoded, it passes through unchanged.
+ If decompression fails, it logs a warning and passes the original compressed body to the app.
+ If the decompressed body exceeds 100 MB, it returns a 413 Payload Too Large response.
+
+ This is useful for Codex CLI requests that send zstd-compressed payloads to reduce bandwidth usage.
+ """
+
+ def __init__(self, app: ASGIApp) -> None:
+ self.app = app
+
+ async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
+ if scope["type"] != "http":
+ return await self.app(scope, receive, send)
+
+ headers = {k.lower(): v for k, v in scope.get("headers", [])}
+ content_encoding = headers.get(b"content-encoding", b"").decode().lower()
+
+ if content_encoding != "zstd":
+ return await self.app(scope, receive, send)
+
+ # Collect the full request body first (needed for both success and fallback)
+ body_parts: list[bytes] = []
+ while True:
+ message = await receive()
+ body_parts.append(message.get("body", b""))
+ if not message.get("more_body", False):
+ break
+
+ compressed_body = b"".join(body_parts)
+
+ try:
+ max_decompressed_size = 100 * 1024 * 1024 # 100 MB
+
+ def _decompress_zstd(compressed: bytes, max_size: int) -> tuple[bytes | None, bool]:
+ decompressor = zstandard.ZstdDecompressor()
+ reader = decompressor.stream_reader(compressed)
+ try:
+ data = reader.read(max_size)
+ is_oversized = bool(reader.read(1))
+ return (None, True) if is_oversized else (data, False)
+ finally:
+ reader.close()
+
+ decompressed_body, oversized = await asyncio.to_thread(
+ _decompress_zstd, compressed_body, max_decompressed_size
+ )
+
+ if oversized:
+ return await _send_error_response(
+ send,
+ status=413,
+ message=f"Decompressed request body exceeds maximum allowed size of {max_decompressed_size} bytes",
+ )
+
+ # Strip content-encoding header and update content-length
+ new_headers = [
+ (k, v) for k, v in scope["headers"] if k.lower() not in (b"content-encoding", b"content-length")
+ ]
+ new_headers.append((b"content-length", str(len(decompressed_body)).encode()))
+ scope["headers"] = new_headers
+
+ # Feed the decompressed body back, then delegate to the
+ # original receive for disconnect detection so streaming
+ # responses stay alive until the client actually disconnects.
+ body_sent = False
+
+ async def receive_decompressed() -> dict: # type: ignore[type-arg]
+ nonlocal body_sent
+ if not body_sent:
+ body_sent = True
+ return {"type": "http.request", "body": decompressed_body, "more_body": False}
+ return await receive()
+
+ return await self.app(scope, receive_decompressed, send)
+ except Exception as e:
+ logger.warning("Failed to decompress zstd request body, falling back to compressed data", error=str(e))
+
+ # Replay the original compressed body since decompression failed
+ body_sent = False
+
+ async def receive_original() -> dict: # type: ignore[type-arg]
+ nonlocal body_sent
+ if not body_sent:
+ body_sent = True
+ return {"type": "http.request", "body": compressed_body, "more_body": False}
+ return await receive()
+
+ return await self.app(scope, receive_original, send)
+
+
def create_app() -> StackApp:
"""Create and configure the FastAPI application.
@@ -301,16 +414,26 @@ def create_app() -> StackApp:
# Add route authorization middleware if route_policy is configured
# This can work independently of authentication
# NOTE: Add this FIRST because middleware wraps in reverse order (last added runs first)
- # We want: Request → Auth → RouteAuth → App
+ # We want: Request → Auth → Tenancy → RouteAuth → App
if config.server.auth.route_policy:
logger.info("Enabling route-level authorization", rule_count=len(config.server.auth.route_policy))
app.add_middleware(RouteAuthorizationMiddleware, route_policy=config.server.auth.route_policy)
+ # Tenancy middleware applies tenant mode enforcement after auth resolution
+ if config.server.tenancy.mode != TenancyMode.DISABLED:
+ logger.info("Enabling tenancy enforcement", mode=config.server.tenancy.mode.value)
+ app.add_middleware(TenancyMiddleware, tenancy_config=config.server.tenancy)
+
# Add authentication middleware only if provider is configured
# This runs FIRST in the middleware chain (last added = first to run)
if config.server.auth.provider_config:
logger.info("Enabling authentication", provider=config.server.auth.provider_config.type.value)
- app.add_middleware(AuthenticationMiddleware, auth_config=config.server.auth, impls=impls)
+ app.add_middleware(AuthenticationMiddleware, auth_config=config.server.auth)
+
+ elif config.server.tenancy.mode != TenancyMode.DISABLED:
+ # Tenancy without auth: single mode injects default tenant on every request
+ logger.info("Enabling tenancy enforcement (no auth)", mode=config.server.tenancy.mode.value)
+ app.add_middleware(TenancyMiddleware, tenancy_config=config.server.tenancy)
# Load and register external API routers if configured
external_apis = load_external_apis(config)
@@ -334,10 +457,10 @@ def create_app() -> StackApp:
apis_to_serve.add("prompts")
apis_to_serve.add("conversations")
- # Build route-to-API mapping and add request metrics middleware.
+ # Add request metrics middleware.
# Added last so it runs first (outermost), wrapping auth.
- route_to_api = build_route_to_api_map(_ROUTER_FACTORIES, impls)
- app.add_middleware(RequestMetricsMiddleware, route_to_api=route_to_api)
+ # Route mapping is built lazily on the first request from scope["app"].
+ app.add_middleware(RequestMetricsMiddleware)
for api_str in apis_to_serve:
api = Api(api_str)
@@ -349,91 +472,6 @@ def create_app() -> StackApp:
logger.debug("Serving APIs", apis=list(apis_to_serve))
- # Decompress zstd-encoded request bodies (e.g. from Codex CLI)
- # Must be a raw ASGI middleware to intercept the body before Starlette reads it
- class ZstdDecompressionMiddleware:
- def __init__(self, app: ASGIApp) -> None:
- self.app = app
-
- async def __call__(self, scope: Scope, receive: Receive, send: Send) -> Any:
- if scope["type"] != "http":
- return await self.app(scope, receive, send)
-
- headers = {k.lower(): v for k, v in scope.get("headers", [])}
- content_encoding = headers.get(b"content-encoding", b"").decode().lower()
-
- if content_encoding != "zstd":
- return await self.app(scope, receive, send)
-
- # Collect the full request body first (needed for both success and fallback)
- body_parts: list[bytes] = []
- while True:
- message = await receive()
- body_parts.append(message.get("body", b""))
- if not message.get("more_body", False):
- break
-
- compressed_body = b"".join(body_parts)
-
- try:
- max_decompressed_size = 100 * 1024 * 1024 # 100 MB
-
- def _decompress_zstd(compressed: bytes, max_size: int) -> tuple[bytes | None, bool]:
- decompressor = zstandard.ZstdDecompressor()
- reader = decompressor.stream_reader(compressed)
- try:
- data = reader.read(max_size)
- is_oversized = bool(reader.read(1))
- return (None, True) if is_oversized else (data, False)
- finally:
- reader.close()
-
- decompressed_body, oversized = await asyncio.to_thread(
- _decompress_zstd, compressed_body, max_decompressed_size
- )
-
- if oversized:
- return await _send_error_response(
- send,
- status=413,
- message=f"Decompressed request body exceeds maximum allowed size of {max_decompressed_size} bytes",
- )
-
- # Strip content-encoding header and update content-length
- new_headers = [
- (k, v) for k, v in scope["headers"] if k.lower() not in (b"content-encoding", b"content-length")
- ]
- new_headers.append((b"content-length", str(len(decompressed_body)).encode()))
- scope["headers"] = new_headers
-
- # Feed the decompressed body back, then delegate to the
- # original receive for disconnect detection so streaming
- # responses stay alive until the client actually disconnects.
- body_sent = False
-
- async def receive_decompressed() -> dict: # type: ignore[type-arg]
- nonlocal body_sent
- if not body_sent:
- body_sent = True
- return {"type": "http.request", "body": decompressed_body, "more_body": False}
- return await receive()
-
- return await self.app(scope, receive_decompressed, send)
- except Exception as e:
- logger.warning("Failed to decompress zstd request body, falling back to compressed data", error=str(e))
-
- # Replay the original compressed body since decompression failed
- body_sent = False
-
- async def receive_original() -> dict: # type: ignore[type-arg]
- nonlocal body_sent
- if not body_sent:
- body_sent = True
- return {"type": "http.request", "body": compressed_body, "more_body": False}
- return await receive()
-
- return await self.app(scope, receive_original, send)
-
app.add_middleware(ZstdDecompressionMiddleware)
# Register specific exception handlers before the generic Exception handler
diff --git a/src/ogx/core/stack.py b/src/ogx/core/stack.py
index 0daf5dfc02d..ec364e9b0a7 100644
--- a/src/ogx/core/stack.py
+++ b/src/ogx/core/stack.py
@@ -368,7 +368,7 @@ async def validate_vector_stores_config(vector_stores_config: VectorStoresConfig
async def _validate_embedding_model(embedding_model: QualifiedModel, impls: dict[Api, Any]) -> None:
- """Validate that an embedding model exists and has required metadata."""
+ """Validate that an embedding model exists and is accessible."""
provider_id = embedding_model.provider_id
model_id = embedding_model.model_id
model_identifier = f"{provider_id}/{model_id}"
@@ -378,7 +378,7 @@ async def _validate_embedding_model(embedding_model: QualifiedModel, impls: dict
models_impl = impls[Api.models]
response = await models_impl.list_models()
- models_list = {m.identifier: m for m in response.data if m.model_type == "embedding"}
+ models_list = {m.identifier: m for m in response.data if m.model_type == ModelType.embedding}
model = models_list.get(model_identifier)
if model is None:
@@ -386,15 +386,14 @@ async def _validate_embedding_model(embedding_model: QualifiedModel, impls: dict
f"Embedding model '{model_identifier}' not found. Available embedding models: {list(models_list.keys())}"
)
- # if not in metadata, fetch from config default
+ # embedding_dimension may be absent when the model was registered without static metadata;
+ # it will be probed lazily at vector store creation time if needed.
embedding_dimension = model.metadata.get("embedding_dimension", embedding_model.embedding_dimensions)
- if embedding_dimension is None:
- raise ValueError(f"Embedding model '{model_identifier}' is missing 'embedding_dimension' in metadata")
-
- try:
- int(embedding_dimension)
- except ValueError as err:
- raise ValueError(f"Embedding dimension '{embedding_dimension}' cannot be converted to an integer") from err
+ if embedding_dimension is not None:
+ try:
+ int(embedding_dimension)
+ except ValueError as err:
+ raise ValueError(f"Embedding dimension '{embedding_dimension}' cannot be converted to an integer") from err
logger.debug(
"Validated embedding model", model_identifier=model_identifier, embedding_dimension=embedding_dimension
@@ -461,6 +460,28 @@ def __init__(self, var_name: str, path: str = ""):
)
+_ENV_VAR_PATTERN = re.compile(r"\${env\.([A-Z0-9_]+)(?::([=+]?)?([^}]*)?)?}")
+
+
+def extract_env_var_references(config: Any) -> list[str]:
+ """Return the list of environment variable names referenced in a config object."""
+
+ def _collect(obj: Any, acc: list[str]) -> None:
+ if isinstance(obj, str):
+ for m in _ENV_VAR_PATTERN.finditer(obj):
+ acc.append(m.group(1))
+ elif isinstance(obj, dict):
+ for v in obj.values():
+ _collect(v, acc)
+ elif isinstance(obj, list):
+ for v in obj:
+ _collect(v, acc)
+
+ result: list[str] = []
+ _collect(config, result)
+ return result
+
+
def replace_env_vars(config: Any, path: str = "") -> Any:
"""Recursively replace environment variable references in a configuration object."""
if isinstance(config, dict):
@@ -707,10 +728,12 @@ def _initialize_storage(run_config: StackConfig):
raise ValueError(f"Unknown storage backend type: {type}")
from ogx.core.storage.kvstore.kvstore import register_kvstore_backends
+ from ogx.core.storage.sqlstore.authorized_sqlstore import set_default_tenancy_config
from ogx.core.storage.sqlstore.sqlstore import register_sqlstore_backends
register_kvstore_backends(kv_backends)
register_sqlstore_backends(sql_backends)
+ set_default_tenancy_config(run_config.server.tenancy)
class Stack:
diff --git a/src/ogx/core/storage/README.md b/src/ogx/core/storage/README.md
index 846966dee48..e4526f8b18e 100644
--- a/src/ogx/core/storage/README.md
+++ b/src/ogx/core/storage/README.md
@@ -39,6 +39,16 @@ Backends: SQLite (default), PostgreSQL.
Used by: inference store (chat completion logs), conversations, prompts.
+### AuthorizedSqlStore
+
+`authorized_sqlstore.py` wraps a `SqlStore` with two enforcement layers applied to every operation:
+
+1. **Tenant isolation** -- when tenancy is enabled (`single` or `multi` mode), a `tenant_id` column is added to every table. Writes stamp the current user's `tenant_id`; all reads and mutations include a non-bypassable `WHERE tenant_id = ?` filter. In `multi` mode, missing tenant context results in default deny (empty results). Client-supplied `tenant_id` in data payloads is stripped and replaced with the authenticated value.
+
+2. **ABAC access control** -- `owner_principal` and `access_attributes` columns support policy-based rules (e.g., `user is owner`). These operate within a tenant boundary.
+
+The tenancy mode is set process-wide during startup via `set_default_tenancy_mode()` in `stack.py`.
+
## Configuration
Storage is configured in `StackConfig.storage` via `StorageConfig`. The `stores` field contains typed references (`KVStoreReference`, `SqlStoreReference`, `InferenceStoreReference`) that point to specific backend configurations.
diff --git a/src/ogx/core/storage/sqlstore/__init__.py b/src/ogx/core/storage/sqlstore/__init__.py
index ce7a51d22f1..4ab59bc9e47 100644
--- a/src/ogx/core/storage/sqlstore/__init__.py
+++ b/src/ogx/core/storage/sqlstore/__init__.py
@@ -15,4 +15,7 @@
)
from .authorized_sqlstore import authorized_sqlstore as authorized_sqlstore
+from .authorized_sqlstore import get_default_tenancy_config as get_default_tenancy_config
+from .authorized_sqlstore import set_default_tenancy_config as set_default_tenancy_config
+from .authorized_sqlstore import set_default_tenancy_mode as set_default_tenancy_mode
from .sqlstore import * # noqa: F401,F403
diff --git a/src/ogx/core/storage/sqlstore/authorized_sqlstore.py b/src/ogx/core/storage/sqlstore/authorized_sqlstore.py
index c7c1ce817e4..8774bb2821b 100644
--- a/src/ogx/core/storage/sqlstore/authorized_sqlstore.py
+++ b/src/ogx/core/storage/sqlstore/authorized_sqlstore.py
@@ -19,16 +19,36 @@
)
from ogx.core.access_control.conditions import ProtectedResource
from ogx.core.access_control.datatypes import AccessRule, Action, Scope
-from ogx.core.datatypes import User
+from ogx.core.datatypes import TenancyConfig, TenancyMode, User
from ogx.core.request_headers import get_authenticated_user
from ogx.core.storage.datatypes import SqlStoreReference, StorageBackendType
from ogx.core.storage.sqlstore.sqlstore import _sqlstore_impl
from ogx.log import get_logger
-from ogx_api import PaginatedResponse
-from ogx_api.internal.sqlstore import ColumnDefinition, ColumnType, SqlStore
+from ogx_api import ConflictError, PaginatedResponse
+from ogx_api.internal.sqlstore import ColumnDefinition, ColumnType, DeleteOperation, SqlStore
logger = get_logger(name=__name__, category="providers::utils")
+_default_tenancy_config: TenancyConfig = TenancyConfig()
+
+
+def set_default_tenancy_config(config: TenancyConfig) -> None:
+ """Set the process-wide tenancy config. Called once during stack initialization."""
+ global _default_tenancy_config
+ _default_tenancy_config = config
+
+
+def get_default_tenancy_config() -> TenancyConfig:
+ """Return the process-wide tenancy config set during stack initialization."""
+ return _default_tenancy_config
+
+
+def set_default_tenancy_mode(mode: TenancyMode) -> None:
+ """Set the process-wide tenancy mode. Called once during stack initialization."""
+ global _default_tenancy_config
+ _default_tenancy_config = TenancyConfig.model_construct(mode=mode, default_tenant_id=None)
+
+
# Hardcoded copy of the default policy that our SQL filtering implements
# WARNING: If default_policy() changes, this constant must be updated accordingly
# or SQL filtering will fall back to conservative mode (safe but less performant)
@@ -57,20 +77,29 @@
]
-def _enhance_item_with_access_control(item: Mapping[str, Any], current_user: User | None) -> Mapping[str, Any]:
- """Add access control attributes to a data item."""
+def _enhance_item_with_access_control(
+ item: Mapping[str, Any],
+ current_user: User | None,
+ tenancy_mode: TenancyMode = TenancyMode.DISABLED,
+ default_tenant_id: str | None = None,
+) -> Mapping[str, Any]:
+ """Add access control and tenant attributes to a data item."""
enhanced = dict(item)
+ # Never trust client-supplied access control fields.
+ enhanced.pop("owner_principal", None)
+ enhanced.pop("access_attributes", None)
+ if tenancy_mode != TenancyMode.DISABLED:
+ enhanced.pop("tenant_id", None)
if current_user:
enhanced["owner_principal"] = current_user.principal
enhanced["access_attributes"] = current_user.attributes
+ if tenancy_mode != TenancyMode.DISABLED:
+ enhanced["tenant_id"] = current_user.tenant_id or default_tenant_id or ""
else:
- # IMPORTANT: Use empty string and null value (not None) to match public access filter
- # The public access filter in _get_public_access_conditions() expects:
- # - owner_principal = '' (empty string)
- # - access_attributes = null (JSON null, which serializes to the string 'null')
- # Setting them to None (SQL NULL) will cause rows to be filtered out on read.
enhanced["owner_principal"] = ""
- enhanced["access_attributes"] = None # Pydantic/JSON will serialize this as JSON null
+ enhanced["access_attributes"] = None
+ if tenancy_mode != TenancyMode.DISABLED:
+ enhanced["tenant_id"] = default_tenant_id or ""
return enhanced
@@ -83,12 +112,17 @@ def __init__(self, record_id: str, table_name: str, owner: User | None):
self.owner = owner
-async def authorized_sqlstore(reference: SqlStoreReference, policy: list[AccessRule]) -> "AuthorizedSqlStore":
+async def authorized_sqlstore(
+ reference: SqlStoreReference, policy: list[AccessRule], tenancy_mode: TenancyMode | None = None
+) -> "AuthorizedSqlStore":
"""Create an AuthorizedSqlStore from a store reference and access policy.
This is the only supported way to obtain a SQL store for API use.
+ When tenancy_mode is None, uses the process-wide default set during initialization.
"""
- return AuthorizedSqlStore(await _sqlstore_impl(reference), policy)
+ mode = tenancy_mode if tenancy_mode is not None else _default_tenancy_config.mode
+ default_tenant_id = _default_tenancy_config.default_tenant_id if tenancy_mode is None else None
+ return AuthorizedSqlStore(await _sqlstore_impl(reference), policy, mode, default_tenant_id)
class AuthorizedSqlStore:
@@ -99,15 +133,25 @@ class AuthorizedSqlStore:
access control policies, user attribute capture, and SQL filtering optimization.
"""
- def __init__(self, sql_store: SqlStore, policy: list[AccessRule]):
+ def __init__(
+ self,
+ sql_store: SqlStore,
+ policy: list[AccessRule],
+ tenancy_mode: TenancyMode = TenancyMode.DISABLED,
+ default_tenant_id: str | None = None,
+ ):
"""
Initialize the authorization layer.
:param sql_store: Base SqlStore implementation to wrap
:param policy: Access control policy to use for authorization
+ :param tenancy_mode: Tenancy isolation mode
+ :param default_tenant_id: Tenant ID for requestless writes in single-tenant mode
"""
self.sql_store = sql_store
self.policy = policy
+ self.tenancy_mode = tenancy_mode
+ self.default_tenant_id = default_tenant_id
self._detect_database_type()
self._validate_sql_optimized_policy()
@@ -143,10 +187,20 @@ async def create_table(self, table: str, schema: Mapping[str, ColumnType | Colum
enhanced_schema["access_attributes"] = ColumnType.JSON
if "owner_principal" not in enhanced_schema:
enhanced_schema["owner_principal"] = ColumnType.STRING
+ if self.tenancy_mode != TenancyMode.DISABLED and "tenant_id" not in enhanced_schema:
+ enhanced_schema["tenant_id"] = ColumnType.STRING
await self.sql_store.create_table(table, enhanced_schema)
await self.sql_store.add_column_if_not_exists(table, "access_attributes", ColumnType.JSON)
await self.sql_store.add_column_if_not_exists(table, "owner_principal", ColumnType.STRING)
+ if self.tenancy_mode != TenancyMode.DISABLED:
+ await self.sql_store.add_column_if_not_exists(table, "tenant_id", ColumnType.STRING)
+ if self.tenancy_mode == TenancyMode.SINGLE and self.default_tenant_id:
+ await self.sql_store.update(
+ table,
+ {"tenant_id": self.default_tenant_id},
+ where={"tenant_id": None},
+ )
async def add_column_if_not_exists(
self,
@@ -168,14 +222,75 @@ async def check_access_for_rows(
current_user = get_authenticated_user()
await self._check_access_for_rows(table, where, action, current_user)
+ def _build_tenant_filter(self, current_user: User | None) -> tuple[str, dict[str, Any]]:
+ """Non-bypassable tenant partition filter. Applied before ABAC."""
+ if self.tenancy_mode == TenancyMode.DISABLED:
+ return "1=1", {}
+ if not current_user or not current_user.tenant_id:
+ if self.tenancy_mode == TenancyMode.SINGLE and self.default_tenant_id:
+ return "tenant_id = :_tenant_id_filter", {"_tenant_id_filter": self.default_tenant_id}
+ return "1=0", {}
+ return "tenant_id = :_tenant_id_filter", {"_tenant_id_filter": current_user.tenant_id}
+
+ def _tenant_id_for_current_context(self, current_user: User | None) -> str | None:
+ if self.tenancy_mode == TenancyMode.DISABLED:
+ return None
+ if current_user and current_user.tenant_id:
+ return current_user.tenant_id
+ if self.tenancy_mode == TenancyMode.SINGLE:
+ return self.default_tenant_id
+ return None
+
+ def _user_for_policy(self, current_user: User | None) -> User | None:
+ if self.tenancy_mode != TenancyMode.DISABLED or current_user is None:
+ return current_user
+ return User(principal=current_user.principal, attributes=current_user.attributes)
+
+ async def _check_tenant_conflict_for_upsert(
+ self,
+ table: str,
+ conflict_where: Mapping[str, Any],
+ current_user: User | None,
+ ) -> None:
+ if self.tenancy_mode == TenancyMode.DISABLED or not conflict_where:
+ return
+
+ current_tenant_id = self._tenant_id_for_current_context(current_user)
+ rows = await self.sql_store.fetch_all(table=table, where=conflict_where)
+ for row in rows.data:
+ if row.get("tenant_id") != current_tenant_id:
+ raise ConflictError(
+ f"Failed to upsert row in {table}: conflict columns match an existing row in another tenant"
+ )
+
+ def _combine_where_clauses(self, *clauses: tuple[str, dict[str, Any]]) -> tuple[str, dict[str, Any]]:
+ """Combine multiple SQL WHERE clauses with AND."""
+ parts = []
+ params: dict[str, Any] = {}
+ for sql, sql_params in clauses:
+ if sql and sql != "1=1":
+ parts.append(f"({sql})")
+ params.update(sql_params)
+ if not parts:
+ return "1=1", {}
+ return " AND ".join(parts), params
+
async def insert(self, table: str, data: Mapping[str, Any] | Sequence[Mapping[str, Any]]) -> None:
"""Insert a row or batch of rows with automatic access control attribute capture."""
current_user = get_authenticated_user()
enhanced_data: Mapping[str, Any] | Sequence[Mapping[str, Any]]
if isinstance(data, Mapping):
- enhanced_data = _enhance_item_with_access_control(data, current_user)
+ enhanced_data = _enhance_item_with_access_control(
+ data,
+ current_user,
+ self.tenancy_mode,
+ self.default_tenant_id,
+ )
else:
- enhanced_data = [_enhance_item_with_access_control(item, current_user) for item in data]
+ enhanced_data = [
+ _enhance_item_with_access_control(item, current_user, self.tenancy_mode, self.default_tenant_id)
+ for item in data
+ ]
await self.sql_store.insert(table, enhanced_data)
async def upsert(
@@ -197,25 +312,32 @@ async def upsert(
conflict_where = {col: data[col] for col in conflict_columns if col in data}
if conflict_where:
await self._check_access_for_rows(table, conflict_where, Action.UPDATE, current_user)
+ await self._check_tenant_conflict_for_upsert(table, conflict_where, current_user)
- enhanced_data = _enhance_item_with_access_control(data, current_user)
+ enhanced_data = _enhance_item_with_access_control(
+ data,
+ current_user,
+ self.tenancy_mode,
+ self.default_tenant_id,
+ )
- # Strip ownership fields from the update side so a conflict resolution
- # cannot transfer ownership from the original owner to the caller.
+ frozen_fields = {"owner_principal", "access_attributes"}
+ if self.tenancy_mode != TenancyMode.DISABLED:
+ frozen_fields.add("tenant_id")
if update_columns is not None:
- update_columns = [c for c in update_columns if c not in ("owner_principal", "access_attributes")]
+ update_columns = [c for c in update_columns if c not in frozen_fields]
else:
- update_columns = [
- c
- for c in enhanced_data.keys()
- if c not in conflict_columns and c not in ("owner_principal", "access_attributes")
- ]
+ update_columns = [c for c in enhanced_data.keys() if c not in conflict_columns and c not in frozen_fields]
+
+ tenant_update_where, tenant_update_params = self._build_tenant_filter(current_user)
await self.sql_store.upsert(
table=table,
data=enhanced_data,
conflict_columns=conflict_columns,
update_columns=update_columns,
+ update_where_sql=tenant_update_where if tenant_update_where != "1=1" else None,
+ update_where_sql_params=tenant_update_params if tenant_update_params else None,
)
async def fetch_all(
@@ -228,34 +350,43 @@ async def fetch_all(
action: Action = Action.READ,
) -> PaginatedResponse:
"""Fetch all rows with automatic access control filtering."""
+ current_user = get_authenticated_user()
access_where, access_params = self._build_access_control_where_clause(self.policy)
+ tenant_where, tenant_params = self._build_tenant_filter(current_user)
+ combined_where, combined_params = self._combine_where_clauses(
+ (access_where, access_params),
+ (tenant_where, tenant_params),
+ )
rows = await self.sql_store.fetch_all(
table=table,
where=where,
- where_sql=access_where,
- where_sql_params=access_params,
+ where_sql=combined_where,
+ where_sql_params=combined_params,
limit=limit,
order_by=order_by,
cursor=cursor,
)
- current_user = get_authenticated_user()
filtered_rows = []
+ policy_user = self._user_for_policy(current_user)
for row in rows.data:
stored_access_attrs = row.get("access_attributes")
stored_owner_principal = row.get("owner_principal")
record_id = row.get("id", "unknown")
- # Create owner as None if owner_principal is empty/missing, matching ResourceWithOwner behavior
owner = (
- User(principal=stored_owner_principal, attributes=stored_access_attrs)
+ User(
+ principal=stored_owner_principal,
+ attributes=stored_access_attrs,
+ tenant_id=row.get("tenant_id") if self.tenancy_mode != TenancyMode.DISABLED else None,
+ )
if stored_owner_principal
else None
)
sql_record = SqlRecord(str(record_id), table, owner)
- if is_action_allowed(self.policy, action, sql_record, current_user):
+ if is_action_allowed(self.policy, action, sql_record, policy_user):
filtered_rows.append(row)
return PaginatedResponse(
@@ -294,17 +425,35 @@ async def update(self, table: str, data: Mapping[str, Any], where: Mapping[str,
enhanced_data = dict(data)
enhanced_data.pop("owner_principal", None)
enhanced_data.pop("access_attributes", None)
+ if self.tenancy_mode != TenancyMode.DISABLED:
+ enhanced_data.pop("tenant_id", None)
if not enhanced_data:
return
+ tenant_where, tenant_params = self._build_tenant_filter(current_user)
+
if self._can_apply_sql_policy_filter_for_mutations(current_user):
access_where, access_params = self._build_access_control_where_clause(self.policy)
+ combined_where, combined_params = self._combine_where_clauses(
+ (access_where, access_params),
+ (tenant_where, tenant_params),
+ )
await self.sql_store.update(
table,
enhanced_data,
where,
- where_sql=access_where,
- where_sql_params=access_params,
+ where_sql=combined_where,
+ where_sql_params=combined_params,
+ )
+ return
+
+ if tenant_where != "1=1":
+ await self.sql_store.update(
+ table,
+ enhanced_data,
+ where,
+ where_sql=tenant_where,
+ where_sql_params=tenant_params,
)
return
@@ -319,18 +468,60 @@ async def delete(self, table: str, where: Mapping[str, Any]) -> None:
current_user = get_authenticated_user()
await self._check_access_for_rows(table, where, Action.DELETE, current_user)
+ tenant_where, tenant_params = self._build_tenant_filter(current_user)
+
if self._can_apply_sql_policy_filter_for_mutations(current_user):
access_where, access_params = self._build_access_control_where_clause(self.policy)
+ combined_where, combined_params = self._combine_where_clauses(
+ (access_where, access_params),
+ (tenant_where, tenant_params),
+ )
+ await self.sql_store.delete(
+ table,
+ where,
+ where_sql=combined_where,
+ where_sql_params=combined_params,
+ )
+ return
+
+ if tenant_where != "1=1":
await self.sql_store.delete(
table,
where,
- where_sql=access_where,
- where_sql_params=access_params,
+ where_sql=tenant_where,
+ where_sql_params=tenant_params,
)
return
await self.sql_store.delete(table, where)
+ async def delete_many(self, operations: Sequence[DeleteOperation]) -> None:
+ """Delete multiple row sets atomically with access control enforcement."""
+ if not operations:
+ return
+
+ current_user = get_authenticated_user()
+ for operation in operations:
+ await self._check_access_for_rows(operation.table, operation.where, Action.DELETE, current_user)
+
+ if self._can_apply_sql_policy_filter_for_mutations(current_user):
+ access_where, access_params = self._build_access_control_where_clause(self.policy)
+ filtered_operations = [
+ DeleteOperation(
+ table=operation.table,
+ where=operation.where,
+ where_sql=(
+ access_where if operation.where_sql is None else f"({operation.where_sql}) AND ({access_where})"
+ ),
+ where_sql_params={**(operation.where_sql_params or {}), **access_params},
+ )
+ for operation in operations
+ ]
+ await self.sql_store.delete_many(filtered_operations)
+ return
+
+ await self.sql_store.delete_many(operations)
+
async def _check_access_for_rows(
self,
table: str,
@@ -339,21 +530,32 @@ async def _check_access_for_rows(
current_user: User | None,
) -> None:
"""Fetch rows matching `where` and verify the user has permission for `action` on each."""
- rows = await self.sql_store.fetch_all(table=table, where=where)
+ tenant_where, tenant_params = self._build_tenant_filter(current_user)
+ rows = await self.sql_store.fetch_all(
+ table=table,
+ where=where,
+ where_sql=tenant_where if tenant_where != "1=1" else None,
+ where_sql_params=tenant_params if tenant_params else None,
+ )
+ policy_user = self._user_for_policy(current_user)
for row in rows.data:
record_id = row.get("id", "unknown")
stored_owner_principal = row.get("owner_principal")
stored_access_attrs = row.get("access_attributes")
owner = (
- User(principal=stored_owner_principal, attributes=stored_access_attrs)
+ User(
+ principal=stored_owner_principal,
+ attributes=stored_access_attrs,
+ tenant_id=row.get("tenant_id") if self.tenancy_mode != TenancyMode.DISABLED else None,
+ )
if stored_owner_principal
else None
)
sql_record = SqlRecord(str(record_id), table, owner)
- if not is_action_allowed(self.policy, action, sql_record, current_user):
- raise AccessDeniedError(action.value, sql_record, current_user)
+ if not is_action_allowed(self.policy, action, sql_record, policy_user):
+ raise AccessDeniedError(action.value, sql_record, policy_user)
def _can_apply_sql_policy_filter_for_mutations(self, current_user: User | None) -> bool:
"""Return whether SQL-level policy filtering can be safely applied to update/delete."""
diff --git a/src/ogx/core/storage/sqlstore/sqlalchemy_sqlstore.py b/src/ogx/core/storage/sqlstore/sqlalchemy_sqlstore.py
index 3c571377215..0827b67a707 100644
--- a/src/ogx/core/storage/sqlstore/sqlalchemy_sqlstore.py
+++ b/src/ogx/core/storage/sqlstore/sqlalchemy_sqlstore.py
@@ -32,7 +32,7 @@
from ogx.core.storage.datatypes import PostgresSqlStoreConfig, SqlAlchemySqlStoreConfig, SqliteSqlStoreConfig
from ogx.log import get_logger
from ogx_api import PaginatedResponse
-from ogx_api.internal.sqlstore import ColumnDefinition, ColumnType, SqlStore
+from ogx_api.internal.sqlstore import ColumnDefinition, ColumnType, DeleteOperation, SqlStore
logger = get_logger(name=__name__, category="providers::utils")
@@ -47,6 +47,19 @@
}
+def _sqlalchemy_column(
+ column_name: str,
+ column_type: ColumnType,
+ primary_key: bool = False,
+ nullable: bool = True,
+) -> Column[Any]:
+ sqlalchemy_type = TYPE_MAPPING.get(column_type)
+ if not sqlalchemy_type:
+ raise ValueError(f"Unsupported column type '{column_type}' for column '{column_name}'.")
+
+ return Column(column_name, sqlalchemy_type, primary_key=primary_key, nullable=nullable)
+
+
def _build_where_expr(column: ColumnElement[Any], value: Any) -> ColumnElement[Any]:
"""Return a SQLAlchemy expression for a where condition.
@@ -184,12 +197,8 @@ async def create_table(
is_primary_key = col_props.primary_key
is_nullable = col_props.nullable
- sqlalchemy_type = TYPE_MAPPING.get(col_type)
- if not sqlalchemy_type:
- raise ValueError(f"Unsupported column type '{col_type}' for column '{col_name}'.")
-
sqlalchemy_columns.append(
- Column(col_name, sqlalchemy_type, primary_key=is_primary_key, nullable=is_nullable)
+ _sqlalchemy_column(col_name, col_type, primary_key=is_primary_key, nullable=is_nullable)
)
# Register table in metadata - actual creation happens in _ensure_engine()
@@ -216,6 +225,8 @@ async def upsert(
data: Mapping[str, Any],
conflict_columns: list[str],
update_columns: list[str] | None = None,
+ update_where_sql: str | None = None,
+ update_where_sql_params: Mapping[str, Any] | None = None,
) -> None:
await self._ensure_engine() # Lazy init in current event loop
assert self.async_session is not None # _ensure_engine guarantees this
@@ -229,7 +240,17 @@ async def upsert(
update_mapping = {col: getattr(insert_stmt.excluded, col) for col in update_columns}
conflict_cols = [table_obj.c[col] for col in conflict_columns]
- stmt = insert_stmt.on_conflict_do_update(index_elements=conflict_cols, set_=update_mapping)
+ update_where = None
+ if update_where_sql:
+ update_where = text(update_where_sql)
+ if update_where_sql_params:
+ update_where = update_where.bindparams(**update_where_sql_params)
+
+ stmt = insert_stmt.on_conflict_do_update(
+ index_elements=conflict_cols,
+ set_=update_mapping,
+ where=update_where,
+ )
async with self.async_session() as session:
await session.execute(stmt)
@@ -284,8 +305,14 @@ async def fetch_all(
if cursor_key_column not in table_obj.c:
raise ValueError(f"Cursor key column '{cursor_key_column}' not found in table '{table}'")
- # Get cursor value for the order column
+ # Get cursor value for the order column, scoped by the same
+ # access filters as the main query to prevent cross-tenant leaks
cursor_query = select(table_obj.c[order_column]).where(table_obj.c[cursor_key_column] == cursor_id)
+ if where_sql:
+ cursor_clause = text(where_sql)
+ if where_sql_params:
+ cursor_clause = cursor_clause.bindparams(**where_sql_params)
+ cursor_query = cursor_query.where(cursor_clause)
cursor_result = await session.execute(cursor_query)
cursor_row = cursor_result.fetchone()
@@ -379,6 +406,26 @@ async def update(
await session.execute(stmt, data)
await session.commit()
+ def _build_delete_statement(
+ self,
+ table: str,
+ where: Mapping[str, Any],
+ where_sql: str | None = None,
+ where_sql_params: Mapping[str, Any] | None = None,
+ ) -> tuple[Any, Mapping[str, Any] | None]:
+ if not where:
+ raise ValueError("where is required for delete")
+
+ stmt = self.metadata.tables[table].delete()
+ for key, value in where.items():
+ stmt = stmt.where(_build_where_expr(self.metadata.tables[table].c[key], value))
+ if where_sql:
+ clause = text(where_sql)
+ if where_sql_params:
+ clause = clause.bindparams(**where_sql_params)
+ stmt = stmt.where(clause)
+ return stmt, where_sql_params
+
async def delete(
self,
table: str,
@@ -388,21 +435,28 @@ async def delete(
) -> None:
await self._ensure_engine() # Lazy init in current event loop
assert self.async_session is not None # _ensure_engine guarantees this
- if not where:
- raise ValueError("where is required for delete")
-
async with self.async_session() as session:
- stmt = self.metadata.tables[table].delete()
- for key, value in where.items():
- stmt = stmt.where(_build_where_expr(self.metadata.tables[table].c[key], value))
- if where_sql:
- clause = text(where_sql)
- if where_sql_params:
- clause = clause.bindparams(**where_sql_params)
- stmt = stmt.where(clause)
- await session.execute(stmt)
+ stmt, params = self._build_delete_statement(table, where, where_sql, where_sql_params)
+ await session.execute(stmt, params)
await session.commit()
+ async def delete_many(self, operations: Sequence[DeleteOperation]) -> None:
+ await self._ensure_engine() # Lazy init in current event loop
+ assert self.async_session is not None # _ensure_engine guarantees this
+ if not operations:
+ return
+
+ async with self.async_session() as session:
+ async with session.begin():
+ for operation in operations:
+ stmt, params = self._build_delete_statement(
+ operation.table,
+ operation.where,
+ operation.where_sql,
+ operation.where_sql_params,
+ )
+ await session.execute(stmt, params)
+
async def add_column_if_not_exists(
self,
table: str,
@@ -411,6 +465,7 @@ async def add_column_if_not_exists(
nullable: bool = True,
) -> None:
"""Queue a column to be added when engine is created, or add it now if engine exists."""
+ self._add_column_to_metadata(table, column_name, column_type, nullable)
if self._engine is None:
# Engine not created yet - queue this column addition for later
if table not in self._pending_columns:
@@ -420,6 +475,16 @@ async def add_column_if_not_exists(
# Engine already exists - add column immediately
await self._add_column_now(table, column_name, column_type, nullable)
+ def _add_column_to_metadata(
+ self,
+ table: str,
+ column_name: str,
+ column_type: ColumnType,
+ nullable: bool = True,
+ ) -> None:
+ if table in self.metadata.tables and column_name not in self.metadata.tables[table].c:
+ self.metadata.tables[table].append_column(_sqlalchemy_column(column_name, column_type, nullable=nullable))
+
async def _add_column_now(
self,
table: str,
@@ -448,14 +513,10 @@ def check_column_exists(sync_conn: Any) -> tuple[bool, bool]:
if not table_exists or column_exists:
return
- sqlalchemy_type = TYPE_MAPPING.get(column_type)
- if not sqlalchemy_type:
- raise ValueError(f"Unsupported column type '{column_type}' for column '{column_name}'.")
-
# Create the ALTER TABLE statement
# Note: We need to get the dialect-specific type name
dialect = self._engine.dialect
- type_impl = sqlalchemy_type()
+ type_impl = TYPE_MAPPING[column_type]()
compiled_type = type_impl.compile(dialect=dialect)
nullable_clause = "" if nullable else " NOT NULL"
diff --git a/src/ogx/core/utils/config.py b/src/ogx/core/utils/config.py
index dd038fa4eef..3af721f07f1 100644
--- a/src/ogx/core/utils/config.py
+++ b/src/ogx/core/utils/config.py
@@ -9,7 +9,19 @@
def redact_sensitive_fields(data: dict[str, Any]) -> dict[str, Any]:
"""Redact sensitive information from config before printing."""
- sensitive_patterns = ["api_key", "api_token", "password", "secret", "token"]
+ sensitive_patterns = [
+ "api_key",
+ "api-key",
+ "apikey",
+ "api_token",
+ "api-token",
+ "authorization",
+ "credential",
+ "moderation_headers",
+ "password",
+ "secret",
+ "token",
+ ]
# Specific configuration field names that should NOT be redacted despite containing "token"
safe_token_fields = ["chunk_size_tokens", "max_tokens", "default_chunk_overlap_tokens", "max_document_tokens"]
diff --git a/src/ogx/distributions/ci-tests/build.yaml b/src/ogx/distributions/ci-tests/build.yaml
index 4262a319223..7c3774f7ac3 100644
--- a/src/ogx/distributions/ci-tests/build.yaml
+++ b/src/ogx/distributions/ci-tests/build.yaml
@@ -18,7 +18,6 @@ distribution_spec:
- provider_type: remote::sambanova
- provider_type: remote::azure
- provider_type: inline::sentence-transformers
- - provider_type: inline::transformers
vector_io:
- provider_type: inline::faiss
- provider_type: inline::sqlite-vec
diff --git a/src/ogx/distributions/ci-tests/ci_tests.py b/src/ogx/distributions/ci-tests/ci_tests.py
index 62af093fe1e..46445a85ecf 100644
--- a/src/ogx/distributions/ci-tests/ci_tests.py
+++ b/src/ogx/distributions/ci-tests/ci_tests.py
@@ -7,9 +7,6 @@
from ogx.core.datatypes import Provider
from ogx.distributions.template import DistributionTemplate
-from ogx.providers.inline.inference.sentence_transformers.config import (
- SentenceTransformersInferenceConfig,
-)
from ogx.providers.remote.inference.watsonx.config import WatsonXConfig
from ogx_api import ConnectorInput, ModelInput, ModelType
@@ -95,13 +92,6 @@ def get_distribution_template() -> DistributionTemplate:
config=WatsonXConfig.sample_run_config(),
)
- # Override sentence-transformers to use trust_remote_code=True for CI tests
- sentence_transformers_provider = Provider(
- provider_id="sentence-transformers",
- provider_type="inline::sentence-transformers",
- config=SentenceTransformersInferenceConfig(trust_remote_code=True).model_dump(),
- )
-
for run_config in template.run_configs.values():
if run_config.default_connectors is None:
run_config.default_connectors = []
@@ -117,12 +107,9 @@ def get_distribution_template() -> DistributionTemplate:
# Add WatsonX inference provider (vertexai is already in starter distribution)
run_config.provider_overrides["inference"].append(watsonx_provider)
- # Replace sentence-transformers provider with one that has trust_remote_code=True
- inference_providers = run_config.provider_overrides["inference"]
- for i, provider in enumerate(inference_providers):
- if provider.provider_id == "sentence-transformers":
- inference_providers[i] = sentence_transformers_provider
- break
+ for provider in run_config.provider_overrides["inference"]:
+ if provider.provider_type == "inline::sentence-transformers":
+ provider.config["trust_remote_code"] = True
# Add conditional auth config
run_config.auth_config = auth_config
diff --git a/src/ogx/distributions/ci-tests/config.yaml b/src/ogx/distributions/ci-tests/config.yaml
index 3d68f9bd5f4..da08024edaf 100644
--- a/src/ogx/distributions/ci-tests/config.yaml
+++ b/src/ogx/distributions/ci-tests/config.yaml
@@ -8,6 +8,7 @@ apis:
- interactions
- messages
- responses
+- skills
- tool_runtime
- vector_io
providers:
@@ -93,8 +94,6 @@ providers:
provider_type: inline::sentence-transformers
config:
trust_remote_code: true
- - provider_id: transformers
- provider_type: inline::transformers
- provider_id: ${env.WATSONX_API_KEY:+watsonx}
provider_type: remote::watsonx
config:
@@ -216,6 +215,13 @@ providers:
backend: sql_default
max_write_queue_size: 10000
num_writers: 4
+ skills:
+ - provider_id: builtin
+ provider_type: inline::builtin
+ config:
+ persistence:
+ namespace: skills
+ backend: kv_default
tool_runtime:
- provider_id: brave-search
provider_type: remote::brave-search
@@ -227,6 +233,12 @@ providers:
config:
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
max_results: 3
+ - provider_id: nimble-search
+ provider_type: remote::nimble-search
+ config:
+ api_key: ${env.NIMBLE_API_KEY:=}
+ max_results: 3
+ search_depth: lite
- provider_id: file-search
provider_type: inline::file-search
- provider_id: model-context-protocol
@@ -301,7 +313,7 @@ registered_resources:
provider_id: ${env.AWS_DEFAULT_REGION:+bedrock}
provider_model_id: openai.gpt-oss-20b-1:0
model_type: llm
- vector_dbs: []
+ vector_stores: []
server:
port: 8321
auth:
@@ -319,7 +331,7 @@ vector_stores:
provider_id: sentence-transformers
model_id: nomic-ai/nomic-embed-text-v1.5
default_reranker_model:
- provider_id: transformers
+ provider_id: sentence-transformers
model_id: Qwen/Qwen3-Reranker-0.6B
file_search_params:
header_template: 'file_search tool found {num_chunks} chunks:
diff --git a/src/ogx/distributions/ci-tests/run-with-postgres-store.yaml b/src/ogx/distributions/ci-tests/run-with-postgres-store.yaml
index b0b4fe2449a..cde4cc1cb2e 100644
--- a/src/ogx/distributions/ci-tests/run-with-postgres-store.yaml
+++ b/src/ogx/distributions/ci-tests/run-with-postgres-store.yaml
@@ -8,6 +8,7 @@ apis:
- interactions
- messages
- responses
+- skills
- tool_runtime
- vector_io
providers:
@@ -93,8 +94,6 @@ providers:
provider_type: inline::sentence-transformers
config:
trust_remote_code: true
- - provider_id: transformers
- provider_type: inline::transformers
- provider_id: ${env.WATSONX_API_KEY:+watsonx}
provider_type: remote::watsonx
config:
@@ -216,6 +215,13 @@ providers:
backend: sql_default
max_write_queue_size: 10000
num_writers: 4
+ skills:
+ - provider_id: builtin
+ provider_type: inline::builtin
+ config:
+ persistence:
+ namespace: skills
+ backend: kv_default
tool_runtime:
- provider_id: brave-search
provider_type: remote::brave-search
@@ -227,6 +233,12 @@ providers:
config:
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
max_results: 3
+ - provider_id: nimble-search
+ provider_type: remote::nimble-search
+ config:
+ api_key: ${env.NIMBLE_API_KEY:=}
+ max_results: 3
+ search_depth: lite
- provider_id: file-search
provider_type: inline::file-search
- provider_id: model-context-protocol
@@ -314,7 +326,7 @@ registered_resources:
provider_id: ${env.AWS_DEFAULT_REGION:+bedrock}
provider_model_id: openai.gpt-oss-20b-1:0
model_type: llm
- vector_dbs: []
+ vector_stores: []
server:
port: 8321
auth:
@@ -332,7 +344,7 @@ vector_stores:
provider_id: sentence-transformers
model_id: nomic-ai/nomic-embed-text-v1.5
default_reranker_model:
- provider_id: transformers
+ provider_id: sentence-transformers
model_id: Qwen/Qwen3-Reranker-0.6B
file_search_params:
header_template: 'file_search tool found {num_chunks} chunks:
diff --git a/src/ogx/distributions/nvidia/config.yaml b/src/ogx/distributions/nvidia/config.yaml
index ea77ea6a480..86202c1fc00 100644
--- a/src/ogx/distributions/nvidia/config.yaml
+++ b/src/ogx/distributions/nvidia/config.yaml
@@ -73,6 +73,6 @@ registered_resources:
model_id: ${env.INFERENCE_MODEL}
provider_id: nvidia
model_type: llm
- vector_dbs: []
+ vector_stores: []
server:
port: 8321
diff --git a/src/ogx/distributions/oci/config.yaml b/src/ogx/distributions/oci/config.yaml
index d5cf2771cd7..2d2776c5d39 100644
--- a/src/ogx/distributions/oci/config.yaml
+++ b/src/ogx/distributions/oci/config.yaml
@@ -84,6 +84,6 @@ storage:
backend: sql_default
registered_resources:
models: []
- vector_dbs: []
+ vector_stores: []
server:
port: 8321
diff --git a/src/ogx/distributions/open-benchmark/config.yaml b/src/ogx/distributions/open-benchmark/config.yaml
index 71c0c67e267..1e0fb054b63 100644
--- a/src/ogx/distributions/open-benchmark/config.yaml
+++ b/src/ogx/distributions/open-benchmark/config.yaml
@@ -142,6 +142,6 @@ registered_resources:
provider_id: together
provider_model_id: meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo
model_type: llm
- vector_dbs: []
+ vector_stores: []
server:
port: 8321
diff --git a/src/ogx/distributions/postgres-demo/config.yaml b/src/ogx/distributions/postgres-demo/config.yaml
index 5bb1167f01f..94abefeb16b 100644
--- a/src/ogx/distributions/postgres-demo/config.yaml
+++ b/src/ogx/distributions/postgres-demo/config.yaml
@@ -16,8 +16,6 @@ providers:
tls_verify: ${env.VLLM_TLS_VERIFY:=true}
- provider_id: sentence-transformers
provider_type: inline::sentence-transformers
- - provider_id: transformers
- provider_type: inline::transformers
vector_io:
- provider_id: ${env.ENABLE_CHROMADB:+chromadb}
provider_type: remote::chromadb
@@ -96,8 +94,8 @@ registered_resources:
model_type: embedding
- metadata: {}
model_id: Qwen/Qwen3-Reranker-0.6B
- provider_id: transformers
+ provider_id: sentence-transformers
model_type: rerank
- vector_dbs: []
+ vector_stores: []
server:
port: 8321
diff --git a/src/ogx/distributions/starter/build.yaml b/src/ogx/distributions/starter/build.yaml
index d7ebf6a80e5..f18f8f45539 100644
--- a/src/ogx/distributions/starter/build.yaml
+++ b/src/ogx/distributions/starter/build.yaml
@@ -19,7 +19,6 @@ distribution_spec:
- provider_type: remote::sambanova
- provider_type: remote::azure
- provider_type: inline::sentence-transformers
- - provider_type: inline::transformers
vector_io:
- provider_type: inline::faiss
- provider_type: inline::sqlite-vec
diff --git a/src/ogx/distributions/starter/config.yaml b/src/ogx/distributions/starter/config.yaml
index 6b92f0b5405..fbe4496518e 100644
--- a/src/ogx/distributions/starter/config.yaml
+++ b/src/ogx/distributions/starter/config.yaml
@@ -8,6 +8,7 @@ apis:
- interactions
- messages
- responses
+- skills
- tool_runtime
- vector_io
providers:
@@ -93,8 +94,6 @@ providers:
provider_type: inline::sentence-transformers
config:
trust_remote_code: false
- - provider_id: transformers
- provider_type: inline::transformers
vector_io:
- provider_id: faiss
provider_type: inline::faiss
@@ -210,6 +209,13 @@ providers:
backend: sql_default
max_write_queue_size: 10000
num_writers: 4
+ skills:
+ - provider_id: builtin
+ provider_type: inline::builtin
+ config:
+ persistence:
+ namespace: skills
+ backend: kv_default
tool_runtime:
- provider_id: brave-search
provider_type: remote::brave-search
@@ -221,6 +227,12 @@ providers:
config:
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
max_results: 3
+ - provider_id: nimble-search
+ provider_type: remote::nimble-search
+ config:
+ api_key: ${env.NIMBLE_API_KEY:=}
+ max_results: 3
+ search_depth: lite
- provider_id: file-search
provider_type: inline::file-search
- provider_id: model-context-protocol
@@ -275,7 +287,7 @@ registered_resources:
provider_id: all
provider_model_id: auto
model_type: llm
- vector_dbs: []
+ vector_stores: []
server:
port: 8321
vector_stores:
@@ -284,7 +296,7 @@ vector_stores:
provider_id: sentence-transformers
model_id: nomic-ai/nomic-embed-text-v1.5
default_reranker_model:
- provider_id: transformers
+ provider_id: sentence-transformers
model_id: Qwen/Qwen3-Reranker-0.6B
file_search_params:
header_template: 'file_search tool found {num_chunks} chunks:
diff --git a/src/ogx/distributions/starter/run-with-postgres-store.yaml b/src/ogx/distributions/starter/run-with-postgres-store.yaml
index 238bcc3bee1..dca773ab20d 100644
--- a/src/ogx/distributions/starter/run-with-postgres-store.yaml
+++ b/src/ogx/distributions/starter/run-with-postgres-store.yaml
@@ -8,6 +8,7 @@ apis:
- interactions
- messages
- responses
+- skills
- tool_runtime
- vector_io
providers:
@@ -93,8 +94,6 @@ providers:
provider_type: inline::sentence-transformers
config:
trust_remote_code: false
- - provider_id: transformers
- provider_type: inline::transformers
vector_io:
- provider_id: faiss
provider_type: inline::faiss
@@ -210,6 +209,13 @@ providers:
backend: sql_default
max_write_queue_size: 10000
num_writers: 4
+ skills:
+ - provider_id: builtin
+ provider_type: inline::builtin
+ config:
+ persistence:
+ namespace: skills
+ backend: kv_default
tool_runtime:
- provider_id: brave-search
provider_type: remote::brave-search
@@ -221,6 +227,12 @@ providers:
config:
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
max_results: 3
+ - provider_id: nimble-search
+ provider_type: remote::nimble-search
+ config:
+ api_key: ${env.NIMBLE_API_KEY:=}
+ max_results: 3
+ search_depth: lite
- provider_id: file-search
provider_type: inline::file-search
- provider_id: model-context-protocol
@@ -288,7 +300,7 @@ registered_resources:
provider_id: all
provider_model_id: auto
model_type: llm
- vector_dbs: []
+ vector_stores: []
server:
port: 8321
vector_stores:
@@ -297,7 +309,7 @@ vector_stores:
provider_id: sentence-transformers
model_id: nomic-ai/nomic-embed-text-v1.5
default_reranker_model:
- provider_id: transformers
+ provider_id: sentence-transformers
model_id: Qwen/Qwen3-Reranker-0.6B
file_search_params:
header_template: 'file_search tool found {num_chunks} chunks:
diff --git a/src/ogx/distributions/starter/starter.py b/src/ogx/distributions/starter/starter.py
index aa1e8902fd0..6a0cd6de0e0 100644
--- a/src/ogx/distributions/starter/starter.py
+++ b/src/ogx/distributions/starter/starter.py
@@ -25,9 +25,7 @@
from ogx.providers.inline.inference.sentence_transformers import (
SentenceTransformersInferenceConfig,
)
-from ogx.providers.inline.inference.transformers.config import (
- TransformersInferenceConfig,
-)
+from ogx.providers.inline.skills.builtin.config import BuiltinSkillsConfig
from ogx.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
from ogx.providers.inline.vector_io.milvus.config import MilvusVectorIOConfig
from ogx.providers.inline.vector_io.sqlite_vec.config import (
@@ -35,6 +33,7 @@
)
from ogx.providers.registry.inference import available_providers
from ogx.providers.remote.tool_runtime.brave_search.config import BraveSearchToolConfig
+from ogx.providers.remote.tool_runtime.nimble_search.config import NimbleSearchToolConfig
from ogx.providers.remote.tool_runtime.tavily_search.config import TavilySearchToolConfig
from ogx.providers.remote.vector_io.chroma.config import ChromaVectorIOConfig
from ogx.providers.remote.vector_io.elasticsearch.config import ElasticsearchVectorIOConfig
@@ -132,7 +131,6 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
"inference": [BuildProvider(provider_type=p.provider_type, module=p.module) for p in remote_inference_providers]
+ [
BuildProvider(provider_type="inline::sentence-transformers"),
- BuildProvider(provider_type="inline::transformers"),
],
"vector_io": [
BuildProvider(provider_type="inline::faiss"),
@@ -150,9 +148,11 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
"interactions": [BuildProvider(provider_type="inline::builtin")],
"messages": [BuildProvider(provider_type="inline::builtin")],
"responses": [BuildProvider(provider_type="inline::builtin")],
+ "skills": [BuildProvider(provider_type="inline::builtin")],
"tool_runtime": [
BuildProvider(provider_type="remote::brave-search"),
BuildProvider(provider_type="remote::tavily-search"),
+ BuildProvider(provider_type="remote::nimble-search"),
BuildProvider(provider_type="inline::file-search"),
BuildProvider(provider_type="remote::model-context-protocol"),
],
@@ -171,15 +171,10 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
provider_type="inline::sentence-transformers",
config=SentenceTransformersInferenceConfig.sample_run_config(),
)
- reranker_provider = Provider(
- provider_id="transformers",
- provider_type="inline::transformers",
- config=TransformersInferenceConfig.sample_run_config(),
- )
postgres_sql_config = PostgresSqlStoreConfig.sample_run_config()
postgres_kv_config = PostgresKVStoreConfig.sample_run_config()
default_overrides = {
- "inference": remote_inference_providers + [embedding_provider, reranker_provider],
+ "inference": remote_inference_providers + [embedding_provider],
"vector_io": [
Provider(
provider_id="faiss",
@@ -246,6 +241,13 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
),
],
"files": [files_provider],
+ "skills": [
+ Provider(
+ provider_id="builtin",
+ provider_type="inline::builtin",
+ config=BuiltinSkillsConfig.sample_run_config(f"~/.ogx/distributions/{name}"),
+ ),
+ ],
"file_processors": [
Provider(
provider_id="auto",
@@ -264,6 +266,11 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
provider_type="remote::tavily-search",
config=TavilySearchToolConfig.sample_run_config(f"~/.ogx/distributions/{name}"),
),
+ Provider(
+ provider_id="nimble-search",
+ provider_type="remote::nimble-search",
+ config=NimbleSearchToolConfig.sample_run_config(f"~/.ogx/distributions/{name}"),
+ ),
Provider(
provider_id="file-search",
provider_type="inline::file-search",
@@ -305,7 +312,7 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
model_id="nomic-ai/nomic-embed-text-v1.5",
),
default_reranker_model=RerankerModel(
- provider_id="transformers",
+ provider_id="sentence-transformers",
model_id="Qwen/Qwen3-Reranker-0.6B",
),
),
diff --git a/src/ogx/distributions/template.py b/src/ogx/distributions/template.py
index e3f0b371ca5..b07ff984fdc 100644
--- a/src/ogx/distributions/template.py
+++ b/src/ogx/distributions/template.py
@@ -237,7 +237,7 @@ def run_config(
"storage": storage_config,
"registered_resources": {
"models": [m.model_dump(exclude_none=True) for m in (self.default_models or [])],
- "vector_dbs": [],
+ "vector_stores": [],
},
"server": {
"port": 8321,
diff --git a/src/ogx/distributions/watsonx/config.yaml b/src/ogx/distributions/watsonx/config.yaml
index 4dfb20119f2..7a5e7978bda 100644
--- a/src/ogx/distributions/watsonx/config.yaml
+++ b/src/ogx/distributions/watsonx/config.yaml
@@ -82,6 +82,6 @@ storage:
backend: sql_default
registered_resources:
models: []
- vector_dbs: []
+ vector_stores: []
server:
port: 8321
diff --git a/src/ogx/providers/inline/README.md b/src/ogx/providers/inline/README.md
index 1cdcdc9eaf1..7b3cf1478bb 100644
--- a/src/ogx/providers/inline/README.md
+++ b/src/ogx/providers/inline/README.md
@@ -14,6 +14,7 @@ inline/
tool_runtime/ # Tool runtime (RAG context retrieval)
files/ # File storage and management
file_processor/ # File processing (text extraction, etc.)
+ skills/ # Skills API (versioned skill bundle management)
__init__.py
```
@@ -29,3 +30,4 @@ Their factory function is typically named `get_provider_impl()` and returns an i
- **`inference/sentence_transformers`** -- Runs embedding models using the sentence-transformers library.
- **`inference/transformers`** -- Runs Llama models locally using the transformers library.
- **`vector_io/sqlite_vec`** -- SQLite-based vector storage using the sqlite-vec extension.
+- **`skills/builtin`** -- Manages versioned skill bundles (zip archives with SKILL.md manifests). Stores bundles via the Files API and metadata in KVStore.
diff --git a/src/ogx/providers/inline/batches/reference/batches.py b/src/ogx/providers/inline/batches/reference/batches.py
index e59dd0840f1..600af34b85c 100644
--- a/src/ogx/providers/inline/batches/reference/batches.py
+++ b/src/ogx/providers/inline/batches/reference/batches.py
@@ -18,6 +18,7 @@
from ogx.core.storage.sqlstore.authorized_sqlstore import AuthorizedSqlStore
from ogx.log import get_logger
+from ogx.providers.utils.files.response import response_body_bytes
from ogx_api import (
Batches,
BatchNotFoundError,
@@ -396,9 +397,7 @@ async def _validate_input(self, batch: BatchObject) -> tuple[list[BatchError], l
file_content_response = await self.files_api.openai_retrieve_file_content(
RetrieveFileContentRequest(file_id=batch.input_file_id)
)
- # Handle both bytes and memoryview types - convert to bytes unconditionally
- # (bytes(x) returns x if already bytes, creates new bytes from memoryview otherwise)
- body_bytes = bytes(file_content_response.body)
+ body_bytes = await response_body_bytes(file_content_response)
file_content = body_bytes.decode("utf-8")
for line_num, line in enumerate(file_content.strip().split("\n"), 1):
if line.strip(): # skip empty lines
diff --git a/src/ogx/providers/inline/file_processor/docling/docling.py b/src/ogx/providers/inline/file_processor/docling/docling.py
index 12dea2ce2db..153a20d1de1 100644
--- a/src/ogx/providers/inline/file_processor/docling/docling.py
+++ b/src/ogx/providers/inline/file_processor/docling/docling.py
@@ -4,8 +4,10 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
+import asyncio
import os
import tempfile
+import threading
import time
import uuid
from typing import Any
@@ -18,6 +20,8 @@
from fastapi import UploadFile
from ogx.log import get_logger
+from ogx.providers.inline.file_processor.zip_utils import validate_zip_content
+from ogx.providers.utils.files.response import response_body_bytes
from ogx.providers.utils.vector_io.vector_utils import generate_chunk_id
from ogx_api.file_processors import ProcessFileRequest, ProcessFileResponse
from ogx_api.files import RetrieveFileContentRequest, RetrieveFileRequest
@@ -49,6 +53,7 @@ def __init__(self, config: DoclingFileProcessorConfig, files_api=None) -> None:
self.converter = DocumentConverter(
format_options={InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)}
)
+ self._converter_lock = threading.Lock()
async def process_file(
self,
@@ -78,7 +83,20 @@ async def process_file(
content_response = await self.files_api.openai_retrieve_file_content(
RetrieveFileContentRequest(file_id=file_id)
)
- content = content_response.body
+ content = await response_body_bytes(content_response)
+
+ return await asyncio.to_thread(self._process_content, content, filename, file_id, chunking_strategy, start_time)
+
+ def _process_content(
+ self,
+ content: bytes,
+ filename: str,
+ file_id: str | None,
+ chunking_strategy: VectorStoreChunkingStrategy | None,
+ start_time: float,
+ ) -> ProcessFileResponse:
+ """Convert and chunk file content. Runs in a thread."""
+ validate_zip_content(content, filename)
# Preserve original file extension so DocumentConverter can detect the format
suffix = os.path.splitext(filename)[1] or ".bin"
@@ -86,7 +104,8 @@ async def process_file(
tmp.write(content)
tmp.flush()
- result = self.converter.convert(tmp.name)
+ with self._converter_lock:
+ result = self.converter.convert(tmp.name)
doc = result.document
page_count = doc.num_pages()
diff --git a/src/ogx/providers/inline/file_processor/markitdown/markitdown_processor.py b/src/ogx/providers/inline/file_processor/markitdown/markitdown_processor.py
index 779a89983d9..eba81b1d99c 100644
--- a/src/ogx/providers/inline/file_processor/markitdown/markitdown_processor.py
+++ b/src/ogx/providers/inline/file_processor/markitdown/markitdown_processor.py
@@ -4,8 +4,10 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
+import asyncio
import os
import tempfile
+import threading
import time
import uuid
from typing import Any
@@ -14,6 +16,8 @@
from markitdown import MarkItDown
from ogx.log import get_logger
+from ogx.providers.inline.file_processor.zip_utils import validate_zip_content
+from ogx.providers.utils.files.response import response_body_bytes
from ogx.providers.utils.memory.vector_store import make_overlapped_chunks
from ogx_api.file_processors import ProcessFileRequest, ProcessFileResponse
from ogx_api.files import RetrieveFileContentRequest, RetrieveFileRequest
@@ -40,6 +44,7 @@ def __init__(self, config: MarkItDownFileProcessorConfig, files_api) -> None:
self.config = config
self.files_api = files_api
self.converter = MarkItDown()
+ self._converter_lock = threading.Lock()
async def process_file(
self,
@@ -67,7 +72,20 @@ async def process_file(
content_response = await self.files_api.openai_retrieve_file_content(
RetrieveFileContentRequest(file_id=file_id)
)
- content = content_response.body
+ content = await response_body_bytes(content_response)
+
+ return await asyncio.to_thread(self._process_content, content, filename, file_id, chunking_strategy, start_time)
+
+ def _process_content(
+ self,
+ content: bytes,
+ filename: str,
+ file_id: str | None,
+ chunking_strategy: VectorStoreChunkingStrategy | None,
+ start_time: float,
+ ) -> ProcessFileResponse:
+ """Convert and chunk file content. Runs in a thread."""
+ validate_zip_content(content, filename)
suffix = os.path.splitext(filename)[1] or ".bin"
with tempfile.NamedTemporaryFile(suffix=suffix, delete=True) as tmp:
@@ -75,7 +93,8 @@ async def process_file(
tmp.flush()
try:
- result = self.converter.convert(tmp.name)
+ with self._converter_lock:
+ result = self.converter.convert(tmp.name)
except Exception as e:
raise HTTPException(
status_code=422,
diff --git a/src/ogx/providers/inline/file_processor/pypdf/pypdf.py b/src/ogx/providers/inline/file_processor/pypdf/pypdf.py
index 86428801283..d3780958473 100644
--- a/src/ogx/providers/inline/file_processor/pypdf/pypdf.py
+++ b/src/ogx/providers/inline/file_processor/pypdf/pypdf.py
@@ -4,6 +4,7 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
+import asyncio
import io
import mimetypes
import time
@@ -15,6 +16,7 @@
from pypdf import PdfReader
from ogx.log import get_logger
+from ogx.providers.utils.files.response import response_body_bytes
from ogx.providers.utils.memory.vector_store import make_overlapped_chunks
from ogx_api.file_processors import ProcessFileResponse
from ogx_api.files import RetrieveFileContentRequest, RetrieveFileRequest
@@ -68,15 +70,17 @@ async def process_file(
content_response = await self.files_api.openai_retrieve_file_content(
RetrieveFileContentRequest(file_id=file_id)
)
- content = content_response.body
+ content = await response_body_bytes(content_response)
mime_type, _ = mimetypes.guess_type(filename)
mime_category = mime_type.split("/")[0] if (mime_type and "/" in mime_type) else None
if mime_type == "application/pdf":
- return self._process_pdf(content, filename, file_id, chunking_strategy, start_time)
+ return await asyncio.to_thread(self._process_pdf, content, filename, file_id, chunking_strategy, start_time)
elif mime_category == "text":
- return self._process_text(content, filename, file_id, chunking_strategy, start_time)
+ return await asyncio.to_thread(
+ self._process_text, content, filename, file_id, chunking_strategy, start_time
+ )
else:
raise HTTPException(
status_code=422,
diff --git a/src/ogx/providers/inline/file_processor/unstructured/__init__.py b/src/ogx/providers/inline/file_processor/unstructured/__init__.py
new file mode 100644
index 00000000000..f2207518f8b
--- /dev/null
+++ b/src/ogx/providers/inline/file_processor/unstructured/__init__.py
@@ -0,0 +1,26 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Any
+
+from ogx_api import Api
+
+from .config import UnstructuredFileProcessorConfig
+
+
+async def get_provider_impl(config: UnstructuredFileProcessorConfig, deps: dict[Api, Any]):
+ """Get the Unstructured file processor implementation."""
+ from .unstructured import UnstructuredFileProcessor
+
+ assert isinstance(config, UnstructuredFileProcessorConfig), f"Unexpected config type: {type(config)}"
+
+ files_api = deps[Api.files]
+
+ impl = UnstructuredFileProcessor(config, files_api)
+ return impl
+
+
+__all__ = ["UnstructuredFileProcessorConfig", "get_provider_impl"]
diff --git a/src/ogx/providers/inline/file_processor/unstructured/config.py b/src/ogx/providers/inline/file_processor/unstructured/config.py
new file mode 100644
index 00000000000..b287d9b26f5
--- /dev/null
+++ b/src/ogx/providers/inline/file_processor/unstructured/config.py
@@ -0,0 +1,97 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Any, Literal
+
+from pydantic import BaseModel, Field
+
+from ogx_api.vector_io import VectorStoreChunkingStrategyStaticConfig
+
+
+class UnstructuredFileProcessorConfig(BaseModel):
+ """Configuration for local Unstructured file processor.
+
+ Supports 65+ file formats including PDF, DOCX, PPTX, XLSX, EML, MSG, HTML,
+ Markdown, audio transcription, and more via the local Unstructured library.
+
+ System dependencies required:
+ - libmagic (file type detection)
+ - poppler-utils (PDF processing)
+ - tesseract-ocr (OCR support)
+ - libreoffice (optional, for Office document conversion)
+
+ Docker installation recommended for production deployments.
+ """
+
+ strategy: Literal["auto", "fast", "hi_res", "ocr_only"] = Field(
+ default="auto",
+ description=(
+ "Partitioning strategy for document processing. "
+ "'auto' (default) intelligently selects the best approach based on document type. "
+ "'fast' uses text extraction without layout analysis (fastest). "
+ "'hi_res' uses layout models for better structure detection (slowest). "
+ "'ocr_only' uses Tesseract OCR for scanned documents. "
+ "WARNING: Table detection is unreliable in local mode due to known issue "
+ "(https://github.com/Unstructured-IO/unstructured/issues/2997). "
+ "Use remote::unstructured-api for production table extraction."
+ ),
+ )
+
+ default_chunk_size_tokens: int = Field(
+ default=VectorStoreChunkingStrategyStaticConfig.model_fields["max_chunk_size_tokens"].default,
+ ge=100,
+ le=4096,
+ description="Default chunk size in tokens when chunking_strategy type is 'auto'",
+ )
+
+ default_chunk_overlap_tokens: int = Field(
+ default=VectorStoreChunkingStrategyStaticConfig.model_fields["chunk_overlap_tokens"].default,
+ ge=0,
+ le=2048,
+ description="Default chunk overlap in tokens when chunking_strategy type is 'auto'",
+ )
+
+ include_page_breaks: bool = Field(
+ default=True,
+ description="Include PageBreak elements in output for supported formats (PDF, PPTX, HTML)",
+ )
+
+ skip_infer_table_types: list[str] = Field(
+ default_factory=lambda: ["pdf"],
+ description=(
+ "File types to skip table inference for (workaround for local table detection issues). "
+ "Example: ['pdf', 'docx']. Set to empty list [] to attempt table detection for all formats. "
+ "Note: Table detection is unreliable in local mode; use remote::unstructured-api for reliable tables."
+ ),
+ )
+
+ extract_images_in_pdf: bool = Field(
+ default=False,
+ description=(
+ "Extract images from PDFs. Requires strategy='hi_res'. "
+ "May fail on some systems due to missing dependencies. "
+ "Set to True only if you need image extraction and have verified it works in your environment."
+ ),
+ )
+
+ languages: list[str] = Field(
+ default_factory=lambda: ["eng"],
+ description=(
+ "OCR language codes for Tesseract (e.g., ['eng', 'spa', 'deu']). "
+ "Additional language packs must be installed separately via tesseract-ocr-{lang}."
+ ),
+ )
+
+ @classmethod
+ def sample_run_config(cls, **kwargs: Any) -> dict[str, Any]:
+ """Sample configuration for running the provider."""
+ return {
+ "strategy": "auto",
+ "default_chunk_size_tokens": 800,
+ "default_chunk_overlap_tokens": 400,
+ "skip_infer_table_types": ["pdf"],
+ "languages": ["eng"],
+ }
diff --git a/src/ogx/providers/inline/file_processor/unstructured/unstructured.py b/src/ogx/providers/inline/file_processor/unstructured/unstructured.py
new file mode 100644
index 00000000000..b0cf6620efc
--- /dev/null
+++ b/src/ogx/providers/inline/file_processor/unstructured/unstructured.py
@@ -0,0 +1,274 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import asyncio
+import io
+import threading
+import time
+import uuid
+from typing import Any
+
+from fastapi import UploadFile
+from unstructured.chunking.title import chunk_by_title
+from unstructured.partition.auto import partition
+
+from ogx.log import get_logger
+from ogx.providers.inline.file_processor.zip_utils import validate_zip_content
+from ogx.providers.utils.files.response import response_body_bytes
+from ogx.providers.utils.vector_io.vector_utils import generate_chunk_id
+from ogx_api.file_processors import ProcessFileRequest, ProcessFileResponse
+from ogx_api.files import RetrieveFileContentRequest, RetrieveFileRequest
+from ogx_api.vector_io import (
+ Chunk,
+ ChunkMetadata,
+ VectorStoreChunkingStrategy,
+)
+
+from .config import UnstructuredFileProcessorConfig
+
+log = get_logger(name=__name__, category="providers::file_processors")
+
+
+class UnstructuredFileProcessor:
+ """Local Unstructured file processor supporting 65+ formats.
+
+ Uses the open-source Unstructured library for local document parsing.
+ Supports PDF, DOCX, PPTX, XLSX, HTML, EML, MSG, audio transcription,
+ and many other formats.
+
+ WARNING: Table detection is unreliable in local mode (GitHub issue #2997).
+ For production table extraction, use remote::unstructured-api instead.
+
+ System dependencies required:
+ - libmagic-dev (file type detection)
+ - poppler-utils (PDF processing)
+ - tesseract-ocr (OCR support)
+ - libreoffice (optional, for Office document conversion)
+ """
+
+ def __init__(self, config: UnstructuredFileProcessorConfig, files_api=None) -> None:
+ self.config = config
+ self.files_api = files_api
+ self._partition_lock = threading.Lock()
+
+ async def process_file(
+ self,
+ request: ProcessFileRequest,
+ file: UploadFile | None = None,
+ ) -> ProcessFileResponse:
+ """Process a file using local Unstructured library."""
+ file_id = request.file_id
+ chunking_strategy = request.chunking_strategy
+
+ # Validate input
+ if not file and not file_id:
+ raise ValueError("Either file or file_id must be provided")
+ if file and file_id:
+ raise ValueError("Cannot provide both file and file_id")
+
+ start_time = time.time()
+
+ # Get file content
+ if file:
+ content = await file.read()
+ filename = file.filename or f"{uuid.uuid4()}.bin"
+ elif file_id:
+ file_info = await self.files_api.openai_retrieve_file(RetrieveFileRequest(file_id=file_id))
+ filename = file_info.filename
+
+ content_response = await self.files_api.openai_retrieve_file_content(
+ RetrieveFileContentRequest(file_id=file_id)
+ )
+ content = await response_body_bytes(content_response)
+
+ # Process in thread pool (blocking library)
+ return await asyncio.to_thread(self._process_content, content, filename, file_id, chunking_strategy, start_time)
+
+ def _process_content(
+ self,
+ content: bytes,
+ filename: str,
+ file_id: str | None,
+ chunking_strategy: VectorStoreChunkingStrategy | None,
+ start_time: float,
+ ) -> ProcessFileResponse:
+ """Partition and chunk file content. Runs in a thread."""
+ validate_zip_content(content, filename)
+
+ log.info(
+ "Partitioning file with Unstructured",
+ filename=filename,
+ size_bytes=len(content),
+ strategy=self.config.strategy,
+ )
+
+ file_like = io.BytesIO(content)
+
+ with self._partition_lock:
+ elements = partition(
+ file=file_like,
+ metadata_filename=filename,
+ strategy=self.config.strategy,
+ include_page_breaks=self.config.include_page_breaks,
+ skip_infer_table_types=self.config.skip_infer_table_types,
+ extract_images_in_pdf=self.config.extract_images_in_pdf,
+ languages=self.config.languages,
+ )
+
+ log.info(
+ "Unstructured partitioning complete",
+ filename=filename,
+ element_count=len(elements),
+ )
+
+ document_id = file_id if file_id else str(uuid.uuid4())
+ document_metadata: dict[str, Any] = {"filename": filename}
+ if file_id:
+ document_metadata["file_id"] = file_id
+
+ # Create chunks from elements
+ chunks = self._create_chunks(elements, document_id, chunking_strategy, document_metadata)
+
+ processing_time_ms = int((time.time() - start_time) * 1000)
+
+ response_metadata: dict[str, Any] = {
+ "processor": "unstructured",
+ "processing_time_ms": processing_time_ms,
+ "extraction_method": "unstructured-local",
+ "file_size_bytes": len(content),
+ "total_elements": len(elements),
+ "strategy": self.config.strategy,
+ }
+
+ return ProcessFileResponse(chunks=chunks, metadata=response_metadata)
+
+ def _create_chunks(
+ self,
+ elements: list[Any], # List of Element objects from unstructured
+ document_id: str,
+ chunking_strategy: VectorStoreChunkingStrategy | None,
+ document_metadata: dict[str, Any],
+ ) -> list[Chunk]:
+ """Convert Unstructured elements to OGX Chunks.
+
+ Chunking semantics (matching remote::unstructured-api pattern):
+ - chunking_strategy is None -> each element becomes one chunk
+ - chunking_strategy.type == "auto" -> use chunk_by_title with configured defaults
+ - chunking_strategy.type == "static" -> use chunk_by_title with provided max_tokens
+ """
+ if not elements:
+ return []
+
+ if not chunking_strategy:
+ # No chunking - each element becomes one chunk
+ return self._elements_to_individual_chunks(elements, document_id, document_metadata)
+
+ # With chunking - use Unstructured's chunk_by_title (matches API behavior)
+ # Determine max_characters based on strategy (same logic as remote API)
+ if chunking_strategy.type == "auto":
+ max_tokens = self.config.default_chunk_size_tokens
+ elif chunking_strategy.type == "static":
+ max_tokens = chunking_strategy.static.max_chunk_size_tokens
+ else:
+ max_tokens = self.config.default_chunk_size_tokens
+
+ # Convert tokens to characters (same conversion as remote API: 1 token ≈ 4 characters)
+ max_characters = max_tokens * 4
+
+ log.info(
+ "Chunking elements with chunk_by_title",
+ max_tokens=max_tokens,
+ max_characters=max_characters,
+ )
+
+ # Use Unstructured's native chunking
+ chunked_elements = chunk_by_title(
+ elements,
+ max_characters=max_characters,
+ )
+
+ log.info(
+ "Chunked elements",
+ original_count=len(elements),
+ chunk_count=len(chunked_elements),
+ )
+
+ return self._elements_to_individual_chunks(chunked_elements, document_id, document_metadata)
+
+ def _elements_to_individual_chunks(
+ self,
+ elements: list[Any],
+ document_id: str,
+ document_metadata: dict[str, Any],
+ ) -> list[Chunk]:
+ """Convert element objects to OGX Chunk objects.
+
+ Elements are Unstructured Element objects with:
+ - .text attribute (str)
+ - .category attribute (str) - element type
+ - .metadata object with .to_dict() method
+ """
+ chunks: list[Chunk] = []
+
+ for idx, element in enumerate(elements):
+ # Extract text - Use .text attribute (not dict access)
+ text = element.text
+
+ # Skip empty elements
+ if not text or not text.strip():
+ continue
+
+ # Get metadata - Use .metadata.to_dict() for serialization
+ elem_metadata_dict = element.metadata.to_dict()
+ page_number = elem_metadata_dict.get("page_number")
+ element_type = element.category # Use .category attribute
+
+ # Generate chunk_id
+ chunk_id = generate_chunk_id(document_id, text, str(idx))
+
+ # Calculate token count (heuristic: 1 token ≈ 4 characters)
+ content_token_count = len(text) // 4
+
+ # Build metadata dict
+ metadata_dict: dict[str, Any] = {
+ "document_id": document_id,
+ "element_type": element_type,
+ "element_index": idx,
+ **document_metadata,
+ }
+ if page_number is not None:
+ metadata_dict["page_number"] = page_number
+
+ # Include coordinates if available (useful for position-aware retrieval)
+ if elem_metadata_dict.get("coordinates"):
+ metadata_dict["coordinates"] = elem_metadata_dict["coordinates"]
+
+ chunk = Chunk(
+ content=text,
+ chunk_id=chunk_id,
+ metadata=metadata_dict,
+ chunk_metadata=ChunkMetadata(
+ chunk_id=chunk_id,
+ document_id=document_id,
+ source=document_metadata.get("filename", ""),
+ content_token_count=content_token_count,
+ ),
+ )
+
+ chunks.append(chunk)
+
+ log.info(
+ "Converted elements to chunks",
+ total_elements=len(elements),
+ total_chunks=len(chunks),
+ skipped=len(elements) - len(chunks),
+ )
+
+ return chunks
+
+ async def shutdown(self) -> None:
+ """Shutdown hook for cleanup."""
+ pass
diff --git a/src/ogx/providers/inline/file_processor/zip_utils.py b/src/ogx/providers/inline/file_processor/zip_utils.py
new file mode 100644
index 00000000000..e6d2c2710c5
--- /dev/null
+++ b/src/ogx/providers/inline/file_processor/zip_utils.py
@@ -0,0 +1,42 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import io
+import zipfile
+
+from fastapi import HTTPException
+
+MAX_ZIP_DECOMPRESSED_BYTES = 25 * 1024 * 1024 # 25MiB
+MAX_ZIP_ENTRIES = 1000
+
+
+def validate_zip_content(content: bytes, filename: str) -> None:
+ """Reject ZIP archives that exceed decompression limits.
+
+ Call before processing any file that may be ZIP-based (DOCX, PPTX, XLSX, etc.).
+ """
+ if not zipfile.is_zipfile(io.BytesIO(content)):
+ return
+
+ with zipfile.ZipFile(io.BytesIO(content), "r") as zf:
+ entries = zf.infolist()
+ if len(entries) > MAX_ZIP_ENTRIES:
+ raise HTTPException(
+ status_code=422,
+ detail=(
+ f"Failed to process file '{filename}': ZIP contains {len(entries)} entries, "
+ f"exceeding the limit of {MAX_ZIP_ENTRIES}"
+ ),
+ )
+ total_size = sum(e.file_size for e in entries)
+ if total_size > MAX_ZIP_DECOMPRESSED_BYTES:
+ raise HTTPException(
+ status_code=422,
+ detail=(
+ f"Failed to process file '{filename}': ZIP decompressed size "
+ f"({total_size} bytes) exceeds the limit of {MAX_ZIP_DECOMPRESSED_BYTES} bytes"
+ ),
+ )
diff --git a/src/ogx/providers/inline/files/localfs/files.py b/src/ogx/providers/inline/files/localfs/files.py
index bea8ff5c70a..b9171c5506c 100644
--- a/src/ogx/providers/inline/files/localfs/files.py
+++ b/src/ogx/providers/inline/files/localfs/files.py
@@ -23,9 +23,10 @@
import asyncio
import re
-import time
import uuid
+from datetime import UTC, datetime
from pathlib import Path
+from typing import Any
from fastapi import Response, UploadFile
@@ -37,6 +38,7 @@
from ogx.providers.utils.files.sanitize import sanitize_content_disposition_filename
from ogx_api import (
DeleteFileRequest,
+ ExpiresAfter,
Files,
InvalidParameterError,
ListFilesRequest,
@@ -50,6 +52,7 @@
RetrieveFileRequest,
UploadFileRequest,
)
+from ogx_api.files.models import OpenAIFileUploadPurpose
from ogx_api.internal.sqlstore import ColumnDefinition, ColumnType
from .config import LocalfsFilesImplConfig
@@ -57,6 +60,29 @@
logger = get_logger(name=__name__, category="files")
+def _make_file_object(
+ *,
+ id: str,
+ filename: str,
+ purpose: str,
+ bytes: int,
+ created_at: int,
+ expires_at: int,
+ **kwargs: Any,
+) -> OpenAIFileObject:
+ """Construct an OpenAIFileObject while ignoring storage-only fields."""
+ return OpenAIFileObject(
+ id=id,
+ filename=filename,
+ purpose=OpenAIFilePurpose(purpose),
+ bytes=bytes,
+ created_at=created_at,
+ expires_at=expires_at,
+ status="processed",
+ status_details="",
+ )
+
+
class LocalfsFilesImpl(Files):
"""Files provider that stores uploaded files on the local filesystem."""
@@ -89,6 +115,33 @@ async def initialize(self) -> None:
async def shutdown(self) -> None:
pass
+ def _now(self) -> int:
+ """Return current UTC timestamp as int seconds."""
+ return int(datetime.now(UTC).timestamp())
+
+ async def _delete_if_expired(self, file_id: str) -> None:
+ """If the file exists and is expired, delete it from storage and metadata."""
+ self._validate_file_id(file_id)
+ if not self.sql_store:
+ return
+
+ row = await self.sql_store.fetch_one("openai_files", where={"id": file_id})
+ if row:
+ expires_at = row.get("expires_at")
+ if expires_at and expires_at <= self._now():
+ file_path = Path(row["file_path"])
+ try:
+ resolved = self._validate_path_containment(file_path)
+
+ def _delete() -> None:
+ if resolved.exists():
+ resolved.unlink()
+
+ await asyncio.to_thread(_delete)
+ except InvalidParameterError:
+ pass
+ await self.sql_store.delete("openai_files", where={"id": file_id})
+
_FILE_ID_PATTERN = re.compile(r"^file-[0-9a-f]{1,64}$")
def _generate_file_id(self) -> str:
@@ -132,13 +185,14 @@ async def _lookup_file_id(self, file_id: str, action: Action = Action.READ) -> t
if not self.sql_store:
raise RuntimeError("Files provider not initialized")
- row = await self.sql_store.fetch_one("openai_files", where={"id": file_id}, action=action)
+ where: dict[str, str | dict] = {"id": file_id, "expires_at": {">": self._now()}}
+ row = await self.sql_store.fetch_one("openai_files", where=where, action=action)
if not row:
raise OpenAIFileObjectNotFoundError(file_id)
file_path = Path(row.pop("file_path"))
file_path = self._validate_path_containment(file_path)
- return OpenAIFileObject(**row, status="processed", status_details=""), file_path
+ return _make_file_object(**row), file_path
# OpenAI Files API Implementation
async def openai_upload_file(
@@ -153,12 +207,6 @@ async def openai_upload_file(
purpose = request.purpose
expires_after = request.expires_after
- if expires_after is not None:
- logger.warning(
- "File expiration is not supported by this provider, ignoring expires_after",
- expires_after=expires_after,
- )
-
file_id = self._generate_file_id()
file_path = self._get_file_path(file_id)
sanitized_name = sanitize_content_disposition_filename(file.filename or "uploaded_file")
@@ -172,32 +220,28 @@ def _write_file() -> None:
await asyncio.to_thread(_write_file)
- created_at = int(time.time())
+ created_at = self._now()
+
expires_at = created_at + self.config.ttl_secs
+ if purpose == OpenAIFileUploadPurpose.BATCH:
+ expires_at = created_at + ExpiresAfter.MAX
- await self.sql_store.insert(
- "openai_files",
- {
- "id": file_id,
- "filename": sanitized_name,
- "purpose": purpose.value,
- "bytes": file_size,
- "created_at": created_at,
- "expires_at": expires_at,
- "file_path": file_path.as_posix(),
- },
- )
+ if expires_after is not None:
+ expires_at = created_at + expires_after.seconds
- return OpenAIFileObject(
- id=file_id,
- filename=sanitized_name,
- purpose=OpenAIFilePurpose(purpose.value),
- bytes=file_size,
- created_at=created_at,
- expires_at=expires_at,
- status="processed",
- status_details="",
- )
+ entry: dict[str, Any] = {
+ "id": file_id,
+ "filename": sanitized_name,
+ "purpose": purpose.value,
+ "bytes": file_size,
+ "created_at": created_at,
+ "expires_at": expires_at,
+ "file_path": file_path.as_posix(),
+ }
+
+ await self.sql_store.insert("openai_files", entry)
+
+ return _make_file_object(**entry)
async def openai_list_files(
self,
@@ -215,31 +259,19 @@ async def openai_list_files(
if not order:
order = Order.desc
- where_conditions = {}
+ where_conditions: dict[str, Any] = {"expires_at": {">": self._now()}}
if purpose:
where_conditions["purpose"] = purpose.value
paginated_result = await self.sql_store.fetch_all(
table="openai_files",
- where=where_conditions if where_conditions else None,
+ where=where_conditions,
order_by=[("created_at", order.value)],
cursor=("id", after) if after else None,
limit=limit,
)
- files = [
- OpenAIFileObject(
- id=row["id"],
- filename=row["filename"],
- purpose=OpenAIFilePurpose(row["purpose"]),
- bytes=row["bytes"],
- created_at=row["created_at"],
- expires_at=row["expires_at"],
- status="processed",
- status_details="",
- )
- for row in paginated_result.data
- ]
+ files = [_make_file_object(**row) for row in paginated_result.data]
return ListOpenAIFileResponse(
data=files,
@@ -250,6 +282,7 @@ async def openai_list_files(
async def openai_retrieve_file(self, request: RetrieveFileRequest) -> OpenAIFileObject:
"""Returns information about a specific file."""
+ await self._delete_if_expired(request.file_id)
file_obj, _ = await self._lookup_file_id(request.file_id)
return file_obj
@@ -257,6 +290,7 @@ async def openai_retrieve_file(self, request: RetrieveFileRequest) -> OpenAIFile
async def openai_delete_file(self, request: DeleteFileRequest) -> OpenAIFileDeleteResponse:
"""Delete a file."""
file_id = request.file_id
+ await self._delete_if_expired(file_id)
# Delete physical file
_, file_path = await self._lookup_file_id(file_id, action=Action.DELETE)
@@ -278,6 +312,7 @@ def _delete_if_exists() -> None:
async def openai_retrieve_file_content(self, request: RetrieveFileContentRequest) -> Response:
"""Returns the contents of the specified file."""
file_id = request.file_id
+ await self._delete_if_expired(file_id)
# Read file content
file_obj, file_path = await self._lookup_file_id(file_id)
diff --git a/src/ogx/providers/inline/inference/sentence_transformers/sentence_transformers.py b/src/ogx/providers/inline/inference/sentence_transformers/sentence_transformers.py
index 4610fd67aea..c372d306630 100644
--- a/src/ogx/providers/inline/inference/sentence_transformers/sentence_transformers.py
+++ b/src/ogx/providers/inline/inference/sentence_transformers/sentence_transformers.py
@@ -4,7 +4,12 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
+import asyncio
+import threading
from collections.abc import AsyncIterator
+from typing import Any
+
+import torch
from ogx.log import get_logger
from ogx.providers.utils.inference.embedding_mixin import (
@@ -17,13 +22,26 @@
ModelType,
OpenAIChatCompletion,
OpenAIChatCompletionChunk,
+ OpenAIChatCompletionContentPartImageParam,
+ OpenAIChatCompletionContentPartTextParam,
OpenAIChatCompletionRequestWithExtraBody,
OpenAICompletion,
OpenAICompletionRequestWithExtraBody,
+ RerankData,
+ RerankResponse,
)
+from ogx_api.inference import RerankRequest
from .config import SentenceTransformersInferenceConfig
+# key is model name, value is tuple of (AutoTokenizer, AutoModelForCausalLM)
+RERANKER_MODELS: dict[str, tuple] = {}
+
+RERANKER_MODELS_LOCK: asyncio.Lock = asyncio.Lock()
+TOKENIZER_LOCK: threading.Lock = threading.Lock()
+
+DEFAULT_RERANKER_INSTRUCTION = "Given the search query, retrieve relevant passages that answer the query"
+
log = get_logger(name=__name__, category="inference")
@@ -62,6 +80,12 @@ async def list_models(self) -> list[Model] | None:
},
model_type=ModelType.embedding,
),
+ Model(
+ identifier="Qwen/Qwen3-Reranker-0.6B",
+ provider_resource_id="Qwen/Qwen3-Reranker-0.6B",
+ provider_id=self.__provider_id__,
+ model_type=ModelType.rerank,
+ ),
]
async def register_model(self, model: Model) -> Model:
@@ -81,3 +105,151 @@ async def openai_chat_completion(
params: OpenAIChatCompletionRequestWithExtraBody,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
raise NotImplementedError("OpenAI chat completion not supported by sentence transformers provider")
+
+ async def rerank(
+ self,
+ request: RerankRequest,
+ ) -> RerankResponse:
+ """
+ Rerank documents based on query relevance using reranker model
+ """
+ if not request.items:
+ return RerankResponse(data=[])
+
+ if request.max_num_results is not None and request.max_num_results < 1:
+ raise ValueError(f"max_num_results must be >= 1, got {request.max_num_results}")
+
+ # Get the tokenizer and reranker model
+ reranker_tokenizer, reranker_model = await self.load_reranker_model(request.model)
+
+ query_text = self.extract_text(request.query)
+ item_texts = [self.extract_text(item) for item in request.items]
+
+ # Build formatted instruction pairs for each query-document combination
+ pairs = [self.format_instruction(DEFAULT_RERANKER_INSTRUCTION, query_text, doc) for doc in item_texts]
+
+ # Compute relevance scores
+ relevance_scores = await asyncio.to_thread(
+ self.compute_reranked_scores, reranker_tokenizer, reranker_model, pairs
+ )
+
+ # Sort relevance scores in descending order
+ indexed_scores = [(i, score) for i, score in enumerate(relevance_scores)]
+ indexed_scores.sort(key=lambda x: x[1], reverse=True)
+
+ if request.max_num_results is not None:
+ indexed_scores = indexed_scores[: request.max_num_results]
+
+ rerank_data = [RerankData(index=idx, relevance_score=score) for idx, score in indexed_scores]
+
+ return RerankResponse(data=rerank_data)
+
+ async def load_reranker_model(self, model: str) -> tuple[Any, Any]:
+ cached = RERANKER_MODELS.get(model)
+ if cached is not None:
+ return cached
+
+ # Prevents multiple concurrent requests from loading the same model in memory simultaneously
+ async with RERANKER_MODELS_LOCK:
+ cached = RERANKER_MODELS.get(model)
+ if cached is not None:
+ return cached
+
+ log.info(f"Loading reranker model {model}...")
+
+ def load_model():
+ from transformers import AutoModelForCausalLM, AutoTokenizer
+
+ if threading.current_thread() is not threading.main_thread():
+ # PyTorch's OpenMP kernels can segfault when spawned from background
+ # threads with the default parallel settings, so force a single-threaded CPU run.
+ log.debug("Constraining torch threads to 1 (running in worker thread)")
+ torch.set_num_threads(1)
+
+ # Load reranker model for reranking
+ reranker_tokenizer = AutoTokenizer.from_pretrained(model, padding_side="left")
+ reranker_model = AutoModelForCausalLM.from_pretrained(model).eval()
+
+ return reranker_tokenizer, reranker_model
+
+ loaded_tokenizer, loaded_model = await asyncio.to_thread(load_model)
+ RERANKER_MODELS[model] = (loaded_tokenizer, loaded_model)
+ return loaded_tokenizer, loaded_model
+
+ @torch.no_grad()
+ def compute_reranked_scores(
+ self,
+ reranker_tokenizer: Any,
+ reranker_model: Any,
+ pairs: list[str],
+ ) -> list[float]:
+ """Compute relevance scores using reranker.
+
+ Args:
+ reranker_tokenizer: tokenizer
+ reranker_model: reranker
+ pairs: list of strings where each string contains instruct, query and the document
+
+ Returns:
+ List of scores
+ """
+ # Reranker configuration
+ max_length = 8192
+ # We lock everything that touches reranker_tokenizer because it modifies
+ # its internal Rust state during these operations.
+ with TOKENIZER_LOCK:
+ token_true_id = reranker_tokenizer.convert_tokens_to_ids("yes")
+ token_false_id = reranker_tokenizer.convert_tokens_to_ids("no")
+
+ prefix = '<|im_start|>system\nJudge whether the Document meets the requirements based on the Query and the Instruct provided. Note that the answer can only be "yes" or "no".<|im_end|>\n<|im_start|>user\n'
+ suffix = "<|im_end|>\n<|im_start|>assistant\n\n\n\n\n"
+ prefix_tokens = reranker_tokenizer.encode(prefix, add_special_tokens=False)
+ suffix_tokens = reranker_tokenizer.encode(suffix, add_special_tokens=False)
+
+ # Tokenize pairs
+ inputs = reranker_tokenizer(
+ pairs,
+ padding=False,
+ truncation="longest_first",
+ return_attention_mask=False,
+ max_length=max_length - len(prefix_tokens) - len(suffix_tokens),
+ )
+
+ for i, tokens in enumerate(inputs["input_ids"]):
+ inputs["input_ids"][i] = prefix_tokens + tokens + suffix_tokens
+
+ inputs = reranker_tokenizer.pad(inputs, padding=True, return_tensors="pt", max_length=max_length)
+
+ for key in inputs:
+ inputs[key] = inputs[key].to(reranker_model.device)
+
+ batch_scores = reranker_model(**inputs).logits[:, -1, :]
+ true_vector = batch_scores[:, token_true_id]
+ false_vector = batch_scores[:, token_false_id]
+ batch_scores = torch.stack([false_vector, true_vector], dim=1)
+ batch_scores = torch.nn.functional.log_softmax(batch_scores, dim=1)
+ scores: list[float] = batch_scores[:, 1].exp().tolist()
+ return scores
+
+ def extract_text(
+ self, value: str | OpenAIChatCompletionContentPartTextParam | OpenAIChatCompletionContentPartImageParam
+ ) -> str:
+ """Extract plain text from a query or item value."""
+ if isinstance(value, str):
+ return value
+ if isinstance(value, OpenAIChatCompletionContentPartTextParam):
+ return value.text
+ raise ValueError(f"Unsupported content type for reranking: {type(value)}. Only text is supported.")
+
+ def format_instruction(self, instruction: str, query: str, document: str) -> str:
+ """Format a query-document pair with instruction for the reranker model.
+
+ Args:
+ instruction: instruction for reranker model
+ query: original query for retrieval
+ document: retrieved document
+
+ Returns:
+ The string that contains query-document pair
+ """
+ return f": {instruction}\n: {query}\n: {document}"
diff --git a/src/ogx/providers/inline/inference/transformers/__init__.py b/src/ogx/providers/inline/inference/transformers/__init__.py
deleted file mode 100644
index 87dc1f3906a..00000000000
--- a/src/ogx/providers/inline/inference/transformers/__init__.py
+++ /dev/null
@@ -1,22 +0,0 @@
-# Copyright (c) The OGX Contributors.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-from typing import Any
-
-from ogx.providers.inline.inference.transformers.config import (
- TransformersInferenceConfig,
-)
-
-
-async def get_provider_impl(
- config: TransformersInferenceConfig,
- _deps: dict[str, Any],
-):
- from .transformers import TransformersInferenceImpl
-
- impl = TransformersInferenceImpl(config)
- await impl.initialize()
- return impl
diff --git a/src/ogx/providers/inline/inference/transformers/config.py b/src/ogx/providers/inline/inference/transformers/config.py
deleted file mode 100644
index f911513727a..00000000000
--- a/src/ogx/providers/inline/inference/transformers/config.py
+++ /dev/null
@@ -1,17 +0,0 @@
-# Copyright (c) The OGX Contributors.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-from typing import Any
-
-from pydantic import BaseModel
-
-
-class TransformersInferenceConfig(BaseModel):
- """Configuration for the transformers inference provider."""
-
- @classmethod
- def sample_run_config(cls, **kwargs) -> dict[str, Any]:
- return {}
diff --git a/src/ogx/providers/inline/inference/transformers/transformers.py b/src/ogx/providers/inline/inference/transformers/transformers.py
deleted file mode 100644
index b5c8f970984..00000000000
--- a/src/ogx/providers/inline/inference/transformers/transformers.py
+++ /dev/null
@@ -1,252 +0,0 @@
-# Copyright (c) The OGX Contributors.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-from __future__ import annotations
-
-import asyncio
-import threading
-from collections.abc import AsyncIterator
-from typing import Any
-
-import torch
-
-from ogx.log import get_logger
-from ogx_api import (
- InferenceProvider,
- Model,
- ModelsProtocolPrivate,
- ModelType,
- OpenAIChatCompletion,
- OpenAIChatCompletionChunk,
- OpenAIChatCompletionContentPartImageParam,
- OpenAIChatCompletionContentPartTextParam,
- OpenAIChatCompletionRequestWithExtraBody,
- OpenAICompletion,
- OpenAICompletionRequestWithExtraBody,
- OpenAIEmbeddingsRequestWithExtraBody,
- OpenAIEmbeddingsResponse,
- RerankData,
- RerankResponse,
-)
-from ogx_api.inference import RerankRequest
-
-from .config import TransformersInferenceConfig
-
-# key is model name, value is tuple of (AutoTokenizer, AutoModelForCausalLM)
-RERANKER_MODELS: dict[str, tuple] = {}
-
-RERANKER_MODELS_LOCK: asyncio.Lock = asyncio.Lock()
-TOKENIZER_LOCK: threading.Lock = threading.Lock()
-
-DEFAULT_RERANKER_INSTRUCTION = "Given the search query, retrieve relevant passages that answer the query"
-
-log = get_logger(name=__name__, category="inference")
-
-
-class TransformersInferenceImpl(
- InferenceProvider,
- ModelsProtocolPrivate,
-):
- """Inference provider for neural reranking using HuggingFace transformers models."""
-
- __provider_id__: str
-
- def __init__(self, config: TransformersInferenceConfig) -> None:
- self.config = config
-
- async def openai_chat_completions_with_reasoning(self, params: OpenAIChatCompletionRequestWithExtraBody) -> None:
- raise NotImplementedError("Transformers provider does not support reasoning in chat completions")
-
- async def initialize(self) -> None:
- pass
-
- async def shutdown(self) -> None:
- pass
-
- async def should_refresh_models(self) -> bool:
- return False
-
- async def list_models(self) -> list[Model] | None:
- return [
- Model(
- identifier="Qwen/Qwen3-Reranker-0.6B",
- provider_resource_id="Qwen/Qwen3-Reranker-0.6B",
- provider_id=self.__provider_id__,
- model_type=ModelType.rerank,
- ),
- ]
-
- async def register_model(self, model: Model) -> Model:
- return model
-
- async def unregister_model(self, model_id: str) -> None:
- pass
-
- async def openai_completion(
- self,
- params: OpenAICompletionRequestWithExtraBody,
- ) -> OpenAICompletion:
- raise NotImplementedError("OpenAI completion not supported by transformers provider")
-
- async def openai_chat_completion(
- self,
- params: OpenAIChatCompletionRequestWithExtraBody,
- ) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
- raise NotImplementedError("OpenAI chat completion not supported by transformers provider")
-
- async def openai_embeddings(
- self,
- params: OpenAIEmbeddingsRequestWithExtraBody,
- ) -> OpenAIEmbeddingsResponse:
- raise NotImplementedError("OpenAI embeddings not supported by transformers provider")
-
- async def rerank(
- self,
- request: RerankRequest,
- ) -> RerankResponse:
- """
- Rerank documents based on query relevance using reranker model
- """
- if not request.items:
- return RerankResponse(data=[])
-
- if request.max_num_results is not None and request.max_num_results < 1:
- raise ValueError(f"max_num_results must be >= 1, got {request.max_num_results}")
-
- # Get the tokenizer and reranker model
- reranker_tokenizer, reranker_model = await self.load_reranker_model(request.model)
-
- query_text = self.extract_text(request.query)
- item_texts = [self.extract_text(item) for item in request.items]
-
- # Build formatted instruction pairs for each query-document combination
- pairs = [self.format_instruction(DEFAULT_RERANKER_INSTRUCTION, query_text, doc) for doc in item_texts]
-
- # Compute relevance scores
- relevance_scores = await asyncio.to_thread(
- self.compute_reranked_scores, reranker_tokenizer, reranker_model, pairs
- )
-
- # Sort relevance scores in descending order
- indexed_scores = [(i, score) for i, score in enumerate(relevance_scores)]
- indexed_scores.sort(key=lambda x: x[1], reverse=True)
-
- if request.max_num_results is not None:
- indexed_scores = indexed_scores[: request.max_num_results]
-
- rerank_data = [RerankData(index=idx, relevance_score=score) for idx, score in indexed_scores]
-
- return RerankResponse(data=rerank_data)
-
- async def load_reranker_model(self, model: str) -> tuple[Any, Any]:
- cached = RERANKER_MODELS.get(model)
- if cached is not None:
- return cached
-
- # Prevents multiple concurrent requests from loading the same model in memory simultaneously
- async with RERANKER_MODELS_LOCK:
- cached = RERANKER_MODELS.get(model)
- if cached is not None:
- return cached
-
- log.info(f"Loading reranker model {model}...")
-
- def load_model():
- from transformers import AutoModelForCausalLM, AutoTokenizer
-
- if threading.current_thread() is not threading.main_thread():
- # PyTorch's OpenMP kernels can segfault when spawned from background
- # threads with the default parallel settings, so force a single-threaded CPU run.
- log.debug("Constraining torch threads to 1 (running in worker thread)")
- torch.set_num_threads(1)
-
- # Load reranker model for reranking
- reranker_tokenizer = AutoTokenizer.from_pretrained(model, padding_side="left")
- reranker_model = AutoModelForCausalLM.from_pretrained(model).eval()
-
- return reranker_tokenizer, reranker_model
-
- loaded_tokenizer, loaded_model = await asyncio.to_thread(load_model)
- RERANKER_MODELS[model] = (loaded_tokenizer, loaded_model)
- return loaded_tokenizer, loaded_model
-
- @torch.no_grad()
- def compute_reranked_scores(
- self,
- reranker_tokenizer: Any,
- reranker_model: Any,
- pairs: list[str],
- ) -> list[float]:
- """Compute relevance scores using reranker.
-
- Args:
- reranker_tokenizer: tokenizer
- reranker_model: reranker
- pairs: list of strings where each string contains instruct, query and the document
-
- Returns:
- List of scores
- """
- # Reranker configuration
- max_length = 8192
- # We lock everything that touches reranker_tokenizer because it modifies
- # its internal Rust state during these operations.
- with TOKENIZER_LOCK:
- token_true_id = reranker_tokenizer.convert_tokens_to_ids("yes")
- token_false_id = reranker_tokenizer.convert_tokens_to_ids("no")
-
- prefix = '<|im_start|>system\nJudge whether the Document meets the requirements based on the Query and the Instruct provided. Note that the answer can only be "yes" or "no".<|im_end|>\n<|im_start|>user\n'
- suffix = "<|im_end|>\n<|im_start|>assistant\n\n\n\n\n"
- prefix_tokens = reranker_tokenizer.encode(prefix, add_special_tokens=False)
- suffix_tokens = reranker_tokenizer.encode(suffix, add_special_tokens=False)
-
- # Tokenize pairs
- inputs = reranker_tokenizer(
- pairs,
- padding=False,
- truncation="longest_first",
- return_attention_mask=False,
- max_length=max_length - len(prefix_tokens) - len(suffix_tokens),
- )
-
- for i, tokens in enumerate(inputs["input_ids"]):
- inputs["input_ids"][i] = prefix_tokens + tokens + suffix_tokens
-
- inputs = reranker_tokenizer.pad(inputs, padding=True, return_tensors="pt", max_length=max_length)
-
- for key in inputs:
- inputs[key] = inputs[key].to(reranker_model.device)
-
- batch_scores = reranker_model(**inputs).logits[:, -1, :]
- true_vector = batch_scores[:, token_true_id]
- false_vector = batch_scores[:, token_false_id]
- batch_scores = torch.stack([false_vector, true_vector], dim=1)
- batch_scores = torch.nn.functional.log_softmax(batch_scores, dim=1)
- scores: list[float] = batch_scores[:, 1].exp().tolist()
- return scores
-
- def extract_text(
- self, value: str | OpenAIChatCompletionContentPartTextParam | OpenAIChatCompletionContentPartImageParam
- ) -> str:
- """Extract plain text from a query or item value."""
- if isinstance(value, str):
- return value
- if isinstance(value, OpenAIChatCompletionContentPartTextParam):
- return value.text
- raise ValueError(f"Unsupported content type for reranking: {type(value)}. Only text is supported.")
-
- def format_instruction(self, instruction: str, query: str, document: str) -> str:
- """Format a query-document pair with instruction for the reranker model.
-
- Args:
- instruction: instruction for reranker model
- query: original query for retrieval
- document: retrieved document
-
- Returns:
- The string that contains query-document pair
- """
- return f": {instruction}\n: {query}\n: {document}"
diff --git a/src/ogx/providers/inline/interactions/impl.py b/src/ogx/providers/inline/interactions/impl.py
index 1a15d31950d..ea42c6b76e6 100644
--- a/src/ogx/providers/inline/interactions/impl.py
+++ b/src/ogx/providers/inline/interactions/impl.py
@@ -298,7 +298,6 @@ async def _passthrough_request(
logger.error(
"Passthrough request failed",
status_code=resp.status_code,
- response_body=resp.text[:500],
url=url,
)
return JSONResponse(content=resp.json(), status_code=resp.status_code)
diff --git a/src/ogx/providers/inline/messages/impl.py b/src/ogx/providers/inline/messages/impl.py
index 788993665ba..16fd71fef14 100644
--- a/src/ogx/providers/inline/messages/impl.py
+++ b/src/ogx/providers/inline/messages/impl.py
@@ -60,6 +60,7 @@
ContentBlockStartEvent,
ContentBlockStopEvent,
CreateMessageBatchRequest,
+ ErrorStreamEvent,
ListMessageBatchesRequest,
ListMessageBatchesResponse,
MessageBatch,
@@ -71,6 +72,7 @@
MessageDeltaEvent,
MessageStartEvent,
MessageStopEvent,
+ PingEvent,
RetrieveMessageBatchRequest,
RetrieveMessageBatchResultsRequest,
_AnthropicErrorDetail,
@@ -79,6 +81,7 @@
_SignatureDelta,
_TextDelta,
_ThinkingDelta,
+ _ToolChoiceTool,
)
from .config import MessagesConfig
@@ -111,11 +114,13 @@ async def _list_to_async_iter(
# Maps Anthropic stop_reason -> OpenAI finish_reason
+# Valid stop_reasons: end_turn, stop_sequence, tool_use, max_tokens, pause_turn, refusal
_STOP_REASON_TO_FINISH = {
"end_turn": "stop",
"stop_sequence": "stop",
"tool_use": "tool_calls",
"max_tokens": "length",
+ "pause_turn": "stop",
}
# Maps OpenAI finish_reason -> Anthropic stop_reason
@@ -512,19 +517,26 @@ async def _passthrough_stream(
body: dict[str, Any],
) -> AsyncIterator[AnthropicStreamEvent]:
"""Stream SSE events directly from the provider."""
- async with self._client.stream("POST", url, json=body, headers=headers, timeout=300) as resp:
- resp.raise_for_status()
- event_type = None
- async for line in resp.aiter_lines():
- line = line.strip()
- if line.startswith("event: "):
- event_type = line[7:]
- elif line.startswith("data: ") and event_type:
- data = json.loads(line[6:])
- event = self._parse_sse_event(event_type, data)
- if event:
- yield event
- event_type = None
+ try:
+ async with self._client.stream("POST", url, json=body, headers=headers, timeout=300) as resp:
+ resp.raise_for_status()
+ event_type = None
+ async for line in resp.aiter_lines():
+ line = line.strip()
+ if line.startswith("event: "):
+ event_type = line[7:]
+ elif line.startswith("data: ") and event_type:
+ data = json.loads(line[6:])
+ event = self._parse_sse_event(event_type, data)
+ if event:
+ yield event
+ event_type = None
+ except Exception:
+ logger.exception("Failed to stream passthrough response")
+ yield ErrorStreamEvent(
+ error=_AnthropicErrorDetail(type="api_error", message="Internal server error"),
+ )
+ return
def _parse_sse_event(self, event_type: str, data: dict[str, Any]) -> AnthropicStreamEvent | None:
"""Parse an Anthropic SSE event from its type and data."""
@@ -569,6 +581,10 @@ def _parse_sse_event(self, event_type: str, data: dict[str, Any]) -> AnthropicSt
)
if event_type == "message_stop":
return MessageStopEvent()
+ if event_type == "ping":
+ return PingEvent()
+ if event_type == "error":
+ return ErrorStreamEvent(error=_AnthropicErrorDetail(**data["error"]))
return None
async def _passthrough_count_tokens(
@@ -628,6 +644,10 @@ def _anthropic_to_openai(self, request: AnthropicCreateMessageRequest) -> OpenAI
self._convert_tool_choice_to_openai(request.tool_choice) if tools and request.tool_choice else None
)
+ parallel_tool_calls: bool | None = None
+ if request.tool_choice and getattr(request.tool_choice, "disable_parallel_tool_use", False):
+ parallel_tool_calls = False
+
extra_body: dict[str, Any] = {}
if request.top_k is not None:
extra_body["top_k"] = request.top_k
@@ -641,6 +661,7 @@ def _anthropic_to_openai(self, request: AnthropicCreateMessageRequest) -> OpenAI
stop=request.stop_sequences,
tools=tools,
tool_choice=tool_choice,
+ parallel_tool_calls=parallel_tool_calls,
stream=request.stream or False,
service_tier=request.service_tier, # type: ignore[arg-type]
**(extra_body or {}),
@@ -783,23 +804,14 @@ def _convert_tools_to_openai(self, tools: list[AnthropicTool]) -> list[dict[str,
return result or None
def _convert_tool_choice_to_openai(self, tool_choice: Any) -> Any:
- if isinstance(tool_choice, str):
- if tool_choice == "any":
- return "required"
- if tool_choice == "none":
- return "none"
- return "auto"
-
- if isinstance(tool_choice, dict):
- tc_type = tool_choice.get("type")
- if tc_type == "tool":
- return {"type": "function", "function": {"name": tool_choice["name"]}}
- if tc_type == "any":
- return "required"
- if tc_type == "none":
- return "none"
- return "auto"
-
+ if isinstance(tool_choice, _ToolChoiceTool):
+ return {"type": "function", "function": {"name": tool_choice.name}}
+
+ tc_type = tool_choice.type if hasattr(tool_choice, "type") else str(tool_choice)
+ if tc_type == "any":
+ return "required"
+ if tc_type == "none":
+ return "none"
return "auto"
# -- Response translation --
@@ -875,6 +887,7 @@ async def _stream_openai_to_anthropic(
usage=AnthropicUsage(input_tokens=0, output_tokens=0),
),
)
+ yield PingEvent()
content_block_index = 0
in_text_block = False
@@ -885,81 +898,93 @@ async def _stream_openai_to_anthropic(
cache_read_tokens: int | None = None
stop_reason = "end_turn"
- async for chunk in openai_stream:
- if not chunk.choices:
- # Usage-only chunk
- if chunk.usage:
- input_tokens = chunk.usage.prompt_tokens or 0
- output_tokens = chunk.usage.completion_tokens or 0
- if chunk.usage.prompt_tokens_details and hasattr(
- chunk.usage.prompt_tokens_details, "cached_tokens"
- ):
- cache_read_tokens = chunk.usage.prompt_tokens_details.cached_tokens
- continue
-
- choice = chunk.choices[0]
- delta = choice.delta
+ try:
+ async for chunk in openai_stream:
+ if not chunk.choices:
+ # Usage-only chunk
+ if chunk.usage:
+ input_tokens = chunk.usage.prompt_tokens or 0
+ output_tokens = chunk.usage.completion_tokens or 0
+ if chunk.usage.prompt_tokens_details and hasattr(
+ chunk.usage.prompt_tokens_details, "cached_tokens"
+ ):
+ cache_read_tokens = chunk.usage.prompt_tokens_details.cached_tokens
+ continue
+
+ choice = chunk.choices[0]
+ delta = choice.delta
+
+ if delta and delta.content:
+ if not in_text_block:
+ yield ContentBlockStartEvent(
+ index=content_block_index,
+ content_block=AnthropicTextBlock(text=""),
+ )
+ in_text_block = True
- if delta and delta.content:
- if not in_text_block:
- yield ContentBlockStartEvent(
+ yield ContentBlockDeltaEvent(
index=content_block_index,
- content_block=AnthropicTextBlock(text=""),
+ delta=_TextDelta(text=delta.content),
)
- in_text_block = True
-
- yield ContentBlockDeltaEvent(
- index=content_block_index,
- delta=_TextDelta(text=delta.content),
- )
- if delta and delta.tool_calls:
- for tc_delta in delta.tool_calls:
- tc_idx = tc_delta.index if tc_delta.index is not None else 0
-
- if tc_idx not in in_tool_blocks:
- # Close text block if open
- if in_text_block:
- yield ContentBlockStopEvent(index=content_block_index)
+ if delta and delta.tool_calls:
+ for tc_delta in delta.tool_calls:
+ tc_idx = tc_delta.index if tc_delta.index is not None else 0
+
+ if tc_idx not in in_tool_blocks:
+ # Close text block if open
+ if in_text_block:
+ yield ContentBlockStopEvent(index=content_block_index)
+ yield PingEvent()
+ content_block_index += 1
+ in_text_block = False
+
+ # Start new tool_use block
+ in_tool_blocks[tc_idx] = True
+ tool_call_index_to_block_index[tc_idx] = content_block_index
+
+ yield ContentBlockStartEvent(
+ index=content_block_index,
+ content_block=AnthropicToolUseBlock(
+ id=tc_delta.id or f"toolu_{uuid.uuid4().hex[:24]}",
+ name=tc_delta.function.name if tc_delta.function and tc_delta.function.name else "",
+ input={},
+ ),
+ )
content_block_index += 1
- in_text_block = False
-
- # Start new tool_use block
- in_tool_blocks[tc_idx] = True
- tool_call_index_to_block_index[tc_idx] = content_block_index
-
- yield ContentBlockStartEvent(
- index=content_block_index,
- content_block=AnthropicToolUseBlock(
- id=tc_delta.id or f"toolu_{uuid.uuid4().hex[:24]}",
- name=tc_delta.function.name if tc_delta.function and tc_delta.function.name else "",
- input={},
- ),
- )
- content_block_index += 1
- if tc_delta.function and tc_delta.function.arguments:
- block_idx = tool_call_index_to_block_index[tc_idx]
- yield ContentBlockDeltaEvent(
- index=block_idx,
- delta=_InputJsonDelta(partial_json=tc_delta.function.arguments),
- )
+ if tc_delta.function and tc_delta.function.arguments:
+ block_idx = tool_call_index_to_block_index[tc_idx]
+ yield ContentBlockDeltaEvent(
+ index=block_idx,
+ delta=_InputJsonDelta(partial_json=tc_delta.function.arguments),
+ )
- if choice.finish_reason:
- stop_reason = _FINISH_TO_STOP_REASON.get(choice.finish_reason, "end_turn")
+ if choice.finish_reason:
+ stop_reason = _FINISH_TO_STOP_REASON.get(choice.finish_reason, "end_turn")
- if chunk.usage:
- input_tokens = chunk.usage.prompt_tokens or 0
- output_tokens = chunk.usage.completion_tokens or 0
- if chunk.usage.prompt_tokens_details and hasattr(chunk.usage.prompt_tokens_details, "cached_tokens"):
- cache_read_tokens = chunk.usage.prompt_tokens_details.cached_tokens
+ if chunk.usage:
+ input_tokens = chunk.usage.prompt_tokens or 0
+ output_tokens = chunk.usage.completion_tokens or 0
+ if chunk.usage.prompt_tokens_details and hasattr(
+ chunk.usage.prompt_tokens_details, "cached_tokens"
+ ):
+ cache_read_tokens = chunk.usage.prompt_tokens_details.cached_tokens
+ except Exception:
+ logger.exception("Failed to stream translation response")
+ yield ErrorStreamEvent(
+ error=_AnthropicErrorDetail(type="api_error", message="Internal server error"),
+ )
+ return
# Close any open blocks
if in_text_block:
yield ContentBlockStopEvent(index=content_block_index)
+ yield PingEvent()
for _tc_idx, block_idx in tool_call_index_to_block_index.items():
yield ContentBlockStopEvent(index=block_idx)
+ yield PingEvent()
# Final events
yield MessageDeltaEvent(
diff --git a/src/ogx/providers/inline/responses/builtin/config.py b/src/ogx/providers/inline/responses/builtin/config.py
index 25411590a8b..3a95bdffddc 100644
--- a/src/ogx/providers/inline/responses/builtin/config.py
+++ b/src/ogx/providers/inline/responses/builtin/config.py
@@ -134,6 +134,14 @@ class BuiltinResponsesImplConfig(BaseModel):
'{"results": [{"flagged": bool, "categories": {...}}]}.',
)
+ moderation_headers: dict[str, str] | None = Field(
+ default=None,
+ description="HTTP headers to send with moderation endpoint requests. "
+ "Use this to provide authentication for hosted moderation services "
+ "(e.g., {'Authorization': 'Bearer sk-...'}). These headers are server-side only "
+ "and never exposed to clients.",
+ )
+
@classmethod
def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]:
return {
diff --git a/src/ogx/providers/inline/responses/builtin/impl.py b/src/ogx/providers/inline/responses/builtin/impl.py
index c451e8259de..aac86cba603 100644
--- a/src/ogx/providers/inline/responses/builtin/impl.py
+++ b/src/ogx/providers/inline/responses/builtin/impl.py
@@ -100,6 +100,7 @@ async def initialize(self) -> None:
responses_store=self.responses_store,
vector_io_api=self.vector_io_api,
moderation_endpoint=self.config.moderation_endpoint,
+ moderation_headers=self.config.moderation_headers,
conversations_api=self.conversations_api,
prompts_api=self.prompts_api,
files_api=self.files_api,
@@ -157,6 +158,7 @@ async def create_openai_response(
reasoning=request.reasoning,
service_tier=request.service_tier,
metadata=request.metadata,
+ safety_identifier=request.safety_identifier,
background=request.background,
truncation=request.truncation,
top_logprobs=request.top_logprobs,
diff --git a/src/ogx/providers/inline/responses/builtin/responses/openai_responses.py b/src/ogx/providers/inline/responses/builtin/responses/openai_responses.py
index 3fdf6a6bcde..a79e4b429da 100644
--- a/src/ogx/providers/inline/responses/builtin/responses/openai_responses.py
+++ b/src/ogx/providers/inline/responses/builtin/responses/openai_responses.py
@@ -118,6 +118,7 @@ def __init__(
prompts_api: Prompts,
files_api: Files,
connectors_api: Connectors,
+ moderation_headers: dict[str, str] | None = None,
vector_stores_config: VectorStoresConfig | None = None,
compaction_config=None,
):
@@ -127,6 +128,7 @@ def __init__(
self.responses_store = responses_store
self.vector_io_api = vector_io_api
self.moderation_endpoint = moderation_endpoint
+ self.moderation_headers = moderation_headers
self.conversations_api = conversations_api
self.tool_executor = ToolExecutor(
tool_groups_api=tool_groups_api,
@@ -641,6 +643,7 @@ async def create_openai_response(
max_output_tokens: int | None = None,
service_tier: ServiceTier | None = None,
metadata: dict[str, str] | None = None,
+ safety_identifier: str | None = None,
truncation: ResponseTruncation | None = None,
top_logprobs: int | None = None,
presence_penalty: float | None = None,
@@ -727,6 +730,7 @@ async def create_openai_response(
max_output_tokens=max_output_tokens,
service_tier=service_tier,
metadata=metadata,
+ safety_identifier=safety_identifier,
truncation=truncation,
presence_penalty=presence_penalty,
extra_body=extra_body,
@@ -756,6 +760,7 @@ async def create_openai_response(
max_output_tokens=max_output_tokens,
service_tier=service_tier,
metadata=metadata,
+ safety_identifier=safety_identifier,
include=include,
truncation=truncation,
top_logprobs=top_logprobs,
@@ -845,6 +850,7 @@ async def _create_background_response(
max_output_tokens: int | None = None,
service_tier: ServiceTier | None = None,
metadata: dict[str, str] | None = None,
+ safety_identifier: str | None = None,
truncation: ResponseTruncation | None = None,
presence_penalty: float | None = None,
extra_body: dict | None = None,
@@ -884,6 +890,7 @@ async def _create_background_response(
max_tool_calls=max_tool_calls,
reasoning=reasoning,
metadata=metadata,
+ safety_identifier=safety_identifier,
store=store if store is not None else True,
)
@@ -922,6 +929,7 @@ async def _create_background_response(
max_output_tokens=max_output_tokens,
service_tier=service_tier,
metadata=metadata,
+ safety_identifier=safety_identifier,
truncation=truncation,
presence_penalty=presence_penalty,
extra_body=extra_body,
@@ -960,6 +968,7 @@ async def _run_background_response_loop(
max_output_tokens: int | None = None,
service_tier: ServiceTier | None = None,
metadata: dict[str, str] | None = None,
+ safety_identifier: str | None = None,
truncation: ResponseTruncation | None = None,
presence_penalty: float | None = None,
extra_body: dict | None = None,
@@ -998,6 +1007,7 @@ async def _run_background_response_loop(
max_output_tokens=max_output_tokens,
service_tier=service_tier,
metadata=metadata,
+ safety_identifier=safety_identifier,
include=include,
truncation=truncation,
response_id=response_id,
@@ -1069,6 +1079,7 @@ async def _create_streaming_response(
max_output_tokens: int | None = None,
service_tier: ServiceTier | None = None,
metadata: dict[str, str] | None = None,
+ safety_identifier: str | None = None,
include: list[ResponseItemInclude] | None = None,
truncation: ResponseTruncation | None = None,
response_id: str | None = None,
@@ -1151,6 +1162,7 @@ async def _create_streaming_response(
parallel_tool_calls=parallel_tool_calls,
tool_executor=request_tool_executor,
moderation_endpoint=self.moderation_endpoint,
+ moderation_headers=self.moderation_headers,
connectors_api=self.connectors_api,
enable_guardrails=enable_guardrails,
instructions=instructions,
@@ -1159,6 +1171,7 @@ async def _create_streaming_response(
max_output_tokens=max_output_tokens,
service_tier=service_tier,
metadata=metadata,
+ safety_identifier=safety_identifier,
include=include,
store=store,
truncation=truncation,
@@ -1227,7 +1240,7 @@ async def delete_openai_response(self, response_id: str) -> OpenAIDeleteResponse
async def compact_openai_response(
self,
- model: str,
+ model: str | None,
input: str | list[OpenAIResponseInput] | None = None,
instructions: str | None = None,
previous_response_id: str | None = None,
@@ -1287,6 +1300,11 @@ async def compact_openai_response(
# Call inference to generate the summary (use configured model or fall back to conversation model)
summarization_model = self.compaction_config.summarization_model or model
+ if not summarization_model:
+ raise ValueError(
+ "Failed to compact response: no model specified in request and no "
+ "summarization_model configured in CompactionConfig"
+ )
params = OpenAIChatCompletionRequestWithExtraBody(
model=summarization_model,
messages=messages,
@@ -1307,13 +1325,19 @@ async def compact_openai_response(
output_items: list[OpenAIResponseInput] = []
for item in all_input:
if isinstance(item, OpenAIResponseMessage) and item.role == "user":
+ # Normalize bare-string content to a content-part list so the
+ # compacted output message matches the response message schema,
+ # which requires content to be an array of parts.
+ content = item.content
+ if isinstance(content, str):
+ content = [OpenAIResponseInputMessageContentText(text=content)]
output_items.append(
OpenAIResponseMessage(
id=f"msg_{uuid.uuid4().hex[:24]}",
type="message",
status="completed",
role="user",
- content=item.content,
+ content=content,
)
)
@@ -1356,7 +1380,7 @@ async def compact_openai_response(
stored_response = OpenAIResponseObject(
id=response_id,
created_at=created_at,
- model=model,
+ model=model or summarization_model,
status="completed",
output=[],
usage=usage_data,
diff --git a/src/ogx/providers/inline/responses/builtin/responses/streaming.py b/src/ogx/providers/inline/responses/builtin/responses/streaming.py
index 27280d490c9..ac3501eaf4d 100644
--- a/src/ogx/providers/inline/responses/builtin/responses/streaming.py
+++ b/src/ogx/providers/inline/responses/builtin/responses/streaming.py
@@ -235,6 +235,7 @@ def __init__(
tool_executor, # Will be the tool execution logic from the main class
instructions: str | None,
moderation_endpoint: str | None,
+ moderation_headers: dict[str, str] | None = None,
enable_guardrails: bool = False,
connectors_api: Connectors | None = None,
prompt: OpenAIResponsePrompt | None = None,
@@ -246,6 +247,7 @@ def __init__(
max_output_tokens: int | None = None,
service_tier: ServiceTier | None = None,
metadata: dict[str, str] | None = None,
+ safety_identifier: str | None = None,
include: list[ResponseItemInclude] | None = None,
store: bool | None = True,
truncation: ResponseTruncation | None = None,
@@ -262,6 +264,7 @@ def __init__(
self.max_infer_iters = max_infer_iters
self.tool_executor = tool_executor
self.moderation_endpoint = moderation_endpoint
+ self.moderation_headers = moderation_headers
self.connectors_api = connectors_api
self.enable_guardrails = enable_guardrails
self.prompt = prompt
@@ -280,6 +283,7 @@ def __init__(
# This allows us to update it with the actual tier returned by the provider
self.service_tier = service_tier.value if service_tier is not None else None
self.metadata = metadata
+ self.safety_identifier = safety_identifier
self.truncation = truncation
self.top_logprobs = top_logprobs
self.stream_options = stream_options
@@ -334,6 +338,7 @@ async def _create_refusal_response(self, violation_message: str) -> OpenAIRespon
max_output_tokens=self.max_output_tokens,
service_tier=self.service_tier or "default",
metadata=self.metadata,
+ safety_identifier=self.safety_identifier,
presence_penalty=self.presence_penalty if self.presence_penalty is not None else 0.0,
store=self.store,
prompt_cache_key=self.prompt_cache_key,
@@ -390,6 +395,7 @@ def _snapshot_response(
max_output_tokens=self.max_output_tokens,
service_tier=self.service_tier or "default",
metadata=self.metadata,
+ safety_identifier=self.safety_identifier,
truncation=self.truncation or ResponseTruncation.disabled,
presence_penalty=self.presence_penalty if self.presence_penalty is not None else 0.0,
store=self.store,
@@ -418,9 +424,10 @@ async def create_response(self) -> AsyncIterator[OpenAIResponseObjectStream]:
input_violation_message = await run_guardrails(
self.moderation_endpoint,
combined_text,
+ headers=self.moderation_headers,
)
if input_violation_message:
- logger.info("Input guardrail violation", input_violation_message=input_violation_message)
+ logger.debug("Input guardrail violation", input_violation_message=input_violation_message)
yield await self._create_refusal_response(input_violation_message)
return
@@ -1148,6 +1155,7 @@ async def _process_streaming_chunks(
yield event
reasoning_part_emitted = True
reasoning_text_accumulated.append(reasoning_content)
+ chars_since_last_check += len(reasoning_content)
# Handle refusal content if present
if chunk_choice.delta.refusal:
@@ -1238,20 +1246,21 @@ async def _process_streaming_chunks(
response_tool_call.function.arguments or ""
) + tool_call.function.arguments
- # Batched output safety validation. If we have only buffered reasoning events and
- # no assistant text yet, flush per chunk so reasoning can stream in real time.
+ # Batched output safety validation — reasoning text is included in moderation
+ # checks because reasoning events are user-visible in the stream.
guardrail_check_due = chars_since_last_check >= _GUARDRAIL_BATCH_CHARS
if pending_guardrail_events and not any(chat_response_content):
guardrail_check_due = True
if self.enable_guardrails and guardrail_check_due:
- accumulated_text = "".join(chat_response_content)
+ accumulated_text = "".join(chat_response_content + reasoning_text_accumulated)
violation_message = await run_guardrails(
self.moderation_endpoint,
accumulated_text,
+ headers=self.moderation_headers,
)
if violation_message:
- logger.info("Output guardrail violation", violation_message=violation_message)
+ logger.debug("Output guardrail violation", violation_message=violation_message)
pending_guardrail_events.clear()
yield await self._create_refusal_response(violation_message)
self.violation_detected = True
@@ -1263,13 +1272,14 @@ async def _process_streaming_chunks(
# Final guardrail check on remaining buffered content
if self.enable_guardrails and pending_guardrail_events:
- accumulated_text = "".join(chat_response_content)
+ accumulated_text = "".join(chat_response_content + reasoning_text_accumulated)
violation_message = await run_guardrails(
self.moderation_endpoint,
accumulated_text,
+ headers=self.moderation_headers,
)
if violation_message:
- logger.info("Output guardrail violation", violation_message=violation_message)
+ logger.debug("Output guardrail violation", violation_message=violation_message)
pending_guardrail_events.clear()
yield await self._create_refusal_response(violation_message)
self.violation_detected = True
diff --git a/src/ogx/providers/inline/responses/builtin/responses/utils.py b/src/ogx/providers/inline/responses/builtin/responses/utils.py
index e6a453e21aa..454520b7e77 100644
--- a/src/ogx/providers/inline/responses/builtin/responses/utils.py
+++ b/src/ogx/providers/inline/responses/builtin/responses/utils.py
@@ -12,6 +12,7 @@
from ogx.log import get_logger
from ogx.providers.inline.responses.builtin.responses.types import AssistantMessageWithReasoning
+from ogx.providers.utils.files.response import response_body_bytes
from ogx_api import (
Files,
Inference,
@@ -75,7 +76,7 @@ async def extract_bytes_from_file(file_id: str, files_api: Files) -> bytes:
"""
try:
response = await files_api.openai_retrieve_file_content(RetrieveFileContentRequest(file_id=file_id))
- return bytes(response.body)
+ return await response_body_bytes(response)
except Exception as e:
raise ValueError(f"Failed to retrieve file content for file_id '{file_id}': {str(e)}") from e
@@ -547,11 +548,15 @@ def is_function_tool_call(
async def run_guardrails(
moderation_endpoint: str | None,
messages: str,
+ headers: dict[str, str] | None = None,
) -> str | None:
"""Run content moderation by calling an external OpenAI-compatible moderation endpoint.
The endpoint must conform to the OpenAI Moderations API response format:
{"id": "...", "model": "...", "results": [{"flagged": bool, "categories": {...}, ...}]}
+
+ This function fails closed: any error communicating with the moderation endpoint
+ or parsing its response returns a blocking message rather than allowing content through.
"""
if not messages or not moderation_endpoint:
return None
@@ -560,14 +565,19 @@ async def run_guardrails(
async with httpx.AsyncClient(timeout=httpx.Timeout(30.0)) as client:
try:
- resp = await client.post(moderation_endpoint, json={"input": messages})
+ resp = await client.post(moderation_endpoint, json={"input": messages}, headers=headers)
resp.raise_for_status()
- except httpx.HTTPError:
+ except (httpx.HTTPError, httpx.InvalidURL):
logger.warning("Failed to call moderation endpoint", endpoint=moderation_endpoint)
- return None
+ return "Failed to validate content: moderation service unavailable"
+
+ try:
+ data = resp.json()
+ except Exception:
+ logger.warning("Failed to parse moderation response as JSON", endpoint=moderation_endpoint)
+ return "Failed to validate content: moderation service returned invalid response"
- data = resp.json()
- results = data.get("results")
+ results = data.get("results") if isinstance(data, dict) else None
if not isinstance(results, list):
logger.warning(
"Moderation endpoint returned unexpected format (expected OpenAI-compatible "
@@ -575,13 +585,24 @@ async def run_guardrails(
endpoint=moderation_endpoint,
response_keys=list(data.keys()) if isinstance(data, dict) else type(data).__name__,
)
- return None
+ return "Failed to validate content: moderation response has unexpected format"
+ if not results:
+ logger.warning("Moderation endpoint returned no results", endpoint=moderation_endpoint)
+ return "Failed to validate content: moderation response has unexpected format"
for result in results:
if not isinstance(result, dict):
- continue
- if result.get("flagged", False):
- categories = result.get("categories", {})
+ logger.warning("Failed to parse moderation result entry", endpoint=moderation_endpoint)
+ return "Failed to validate content: moderation response has unexpected format"
+ flagged = result.get("flagged")
+ if not isinstance(flagged, bool):
+ logger.warning("Failed to parse moderation result flagged field", endpoint=moderation_endpoint)
+ return "Failed to validate content: moderation response has unexpected format"
+ categories = result.get("categories", {})
+ if not isinstance(categories, dict):
+ logger.warning("Failed to parse moderation result categories", endpoint=moderation_endpoint)
+ return "Failed to validate content: moderation response has unexpected format"
+ if flagged:
flagged_cats = [c for c, f in categories.items() if f]
msg = "Content blocked by safety guardrails"
if flagged_cats:
diff --git a/src/ogx/providers/inline/skills/__init__.py b/src/ogx/providers/inline/skills/__init__.py
new file mode 100644
index 00000000000..b498a974656
--- /dev/null
+++ b/src/ogx/providers/inline/skills/__init__.py
@@ -0,0 +1,5 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
diff --git a/src/ogx/providers/inline/skills/builtin/__init__.py b/src/ogx/providers/inline/skills/builtin/__init__.py
new file mode 100644
index 00000000000..9041891fd05
--- /dev/null
+++ b/src/ogx/providers/inline/skills/builtin/__init__.py
@@ -0,0 +1,24 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Any
+
+from ogx.core.datatypes import Api
+from ogx.core.storage.kvstore import kvstore_impl
+
+from .config import BuiltinSkillsConfig
+
+
+async def get_provider_impl(
+ config: BuiltinSkillsConfig,
+ deps: dict[Api, Any],
+):
+ from .impl import BuiltinSkillsImpl
+
+ kvstore = await kvstore_impl(config.persistence)
+ impl = BuiltinSkillsImpl(config, deps[Api.files], kvstore)
+ await impl.initialize()
+ return impl
diff --git a/src/ogx/providers/inline/skills/builtin/config.py b/src/ogx/providers/inline/skills/builtin/config.py
new file mode 100644
index 00000000000..504d641b37d
--- /dev/null
+++ b/src/ogx/providers/inline/skills/builtin/config.py
@@ -0,0 +1,28 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Any
+
+from pydantic import BaseModel, Field
+
+from ogx.core.storage.datatypes import KVStoreReference
+
+
+class BuiltinSkillsConfig(BaseModel):
+ """Configuration for the built-in skills provider."""
+
+ persistence: KVStoreReference = Field(
+ description="KV store reference for skill metadata persistence",
+ )
+
+ @classmethod
+ def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]:
+ return {
+ "persistence": KVStoreReference(
+ backend="kv_default",
+ namespace="skills",
+ ).model_dump(exclude_none=True),
+ }
diff --git a/src/ogx/providers/inline/skills/builtin/impl.py b/src/ogx/providers/inline/skills/builtin/impl.py
new file mode 100644
index 00000000000..2d55b91160f
--- /dev/null
+++ b/src/ogx/providers/inline/skills/builtin/impl.py
@@ -0,0 +1,343 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import io
+import json
+import time
+import uuid
+
+from fastapi import Response, UploadFile
+
+from ogx.core.storage.kvstore import KVStore
+from ogx.log import get_logger
+from ogx.providers.utils.files.response import response_body_bytes
+from ogx_api.files import (
+ DeleteFileRequest,
+ Files,
+ OpenAIFileUploadPurpose,
+ RetrieveFileContentRequest,
+ UploadFileRequest,
+)
+from ogx_api.skills import (
+ ListSkillsRequest,
+ ListSkillsResponse,
+ ListSkillVersionsRequest,
+ ListSkillVersionsResponse,
+ Skill,
+ SkillDeleteResponse,
+ Skills,
+ SkillUpdateRequest,
+ SkillVersion,
+ SkillVersionCreateRequest,
+ SkillVersionDeleteResponse,
+)
+
+from .config import BuiltinSkillsConfig
+from .validation import validate_skill_zip
+
+logger = get_logger(__name__)
+
+_SKILL_PREFIX = "skill:"
+_VERSION_PREFIX = "skill_version:"
+_FILE_IDS_PREFIX = "skill_files:"
+
+
+def _skill_key(skill_id: str) -> str:
+ return f"{_SKILL_PREFIX}{skill_id}"
+
+
+def _version_key(skill_id: str, version: str) -> str:
+ return f"{_VERSION_PREFIX}{skill_id}:{version}"
+
+
+def _file_ids_key(skill_id: str) -> str:
+ return f"{_FILE_IDS_PREFIX}{skill_id}"
+
+
+def _version_range_start(skill_id: str) -> str:
+ return f"{_VERSION_PREFIX}{skill_id}:"
+
+
+def _version_range_end(skill_id: str) -> str:
+ return f"{_VERSION_PREFIX}{skill_id}:\xff"
+
+
+def _new_skill_id() -> str:
+ return f"skill-{uuid.uuid4().hex}"
+
+
+def _new_version_id() -> str:
+ return f"skillver-{uuid.uuid4().hex}"
+
+
+class BuiltinSkillsImpl(Skills):
+ """Built-in Skills provider backed by Files API for storage and KVStore for metadata."""
+
+ def __init__(self, config: BuiltinSkillsConfig, files_api: Files, kvstore: KVStore):
+ self.config = config
+ self.files_api = files_api
+ self.kvstore = kvstore
+
+ async def initialize(self) -> None:
+ pass
+
+ async def shutdown(self) -> None:
+ pass
+
+ async def _store_bundle(self, content: bytes, filename: str) -> str:
+ """Upload a zip bundle via the Files API and return the file ID."""
+ upload_file = UploadFile(
+ file=io.BytesIO(content),
+ filename=filename,
+ size=len(content),
+ )
+ request = UploadFileRequest(purpose=OpenAIFileUploadPurpose.ASSISTANTS)
+ result = await self.files_api.openai_upload_file(request, upload_file)
+ return result.id
+
+ async def _delete_bundle(self, file_id: str) -> None:
+ """Delete a zip bundle from the Files API."""
+ try:
+ await self.files_api.openai_delete_file(DeleteFileRequest(file_id=file_id))
+ except Exception:
+ logger.warning("Failed to delete file from storage", file_id=file_id)
+
+ async def _get_file_ids(self, skill_id: str) -> dict[str, str]:
+ data = await self.kvstore.get(_file_ids_key(skill_id))
+ if data is None:
+ return {}
+ result: dict[str, str] = json.loads(data)
+ return result
+
+ async def _set_file_ids(self, skill_id: str, file_ids: dict[str, str]) -> None:
+ await self.kvstore.set(_file_ids_key(skill_id), json.dumps(file_ids))
+
+ async def create_skill(self, file: UploadFile) -> Skill:
+ content = await file.read()
+ manifest, _ = validate_skill_zip(content)
+
+ skill_id = _new_skill_id()
+ now = int(time.time())
+
+ file_id = await self._store_bundle(content, f"{skill_id}_v1.zip")
+
+ version = SkillVersion(
+ id=_new_version_id(),
+ created_at=now,
+ description=manifest.description or "",
+ name=manifest.name or "",
+ skill_id=skill_id,
+ version="1",
+ )
+ await self.kvstore.set(_version_key(skill_id, "1"), version.model_dump_json())
+
+ skill = Skill(
+ id=skill_id,
+ created_at=now,
+ default_version="1",
+ description=manifest.description or "",
+ latest_version="1",
+ name=manifest.name or "",
+ )
+ await self.kvstore.set(_skill_key(skill_id), skill.model_dump_json())
+ await self._set_file_ids(skill_id, {"1": file_id})
+
+ logger.info("Created skill", skill_id=skill_id, name=manifest.name)
+ return skill
+
+ async def list_skills(self, request: ListSkillsRequest) -> ListSkillsResponse:
+ values = await self.kvstore.values_in_range(_SKILL_PREFIX, f"{_SKILL_PREFIX}\xff")
+
+ skills = [Skill.model_validate_json(v) for v in values]
+
+ if request.order == "asc":
+ skills.sort(key=lambda s: s.created_at)
+ else:
+ skills.sort(key=lambda s: s.created_at, reverse=True)
+
+ start_idx = 0
+ if request.after:
+ for i, s in enumerate(skills):
+ if s.id == request.after:
+ start_idx = i + 1
+ break
+
+ page = skills[start_idx : start_idx + request.limit]
+ has_more = start_idx + request.limit < len(skills)
+
+ return ListSkillsResponse(
+ data=page,
+ has_more=has_more,
+ first_id=page[0].id if page else None,
+ last_id=page[-1].id if page else None,
+ )
+
+ async def get_skill(self, skill_id: str) -> Skill:
+ data = await self.kvstore.get(_skill_key(skill_id))
+ if data is None:
+ raise ValueError(f"Failed to find skill: '{skill_id}' does not exist")
+ return Skill.model_validate_json(data)
+
+ async def update_skill(self, skill_id: str, request: SkillUpdateRequest) -> Skill:
+ skill = await self.get_skill(skill_id)
+
+ version_data = await self.kvstore.get(_version_key(skill_id, request.default_version))
+ if version_data is None:
+ raise ValueError(f"Failed to update skill: version '{request.default_version}' does not exist")
+
+ skill.default_version = request.default_version
+ await self.kvstore.set(_skill_key(skill_id), skill.model_dump_json())
+
+ logger.info("Updated skill default version", skill_id=skill_id, version=request.default_version)
+ return skill
+
+ async def delete_skill(self, skill_id: str) -> SkillDeleteResponse:
+ await self.get_skill(skill_id)
+
+ file_ids = await self._get_file_ids(skill_id)
+ for fid in file_ids.values():
+ await self._delete_bundle(fid)
+
+ version_keys = await self.kvstore.keys_in_range(_version_range_start(skill_id), _version_range_end(skill_id))
+ for key in version_keys:
+ await self.kvstore.delete(key)
+
+ await self.kvstore.delete(_file_ids_key(skill_id))
+ await self.kvstore.delete(_skill_key(skill_id))
+
+ logger.info("Deleted skill", skill_id=skill_id)
+ return SkillDeleteResponse(id=skill_id)
+
+ async def get_skill_content(self, skill_id: str) -> Response:
+ skill = await self.get_skill(skill_id)
+ return await self.get_skill_version_content(skill_id, skill.default_version)
+
+ async def create_skill_version(
+ self, skill_id: str, request: SkillVersionCreateRequest, file: UploadFile
+ ) -> SkillVersion:
+ skill = await self.get_skill(skill_id)
+ content = await file.read()
+ manifest, _ = validate_skill_zip(content)
+
+ next_version = str(int(skill.latest_version) + 1)
+ now = int(time.time())
+
+ file_id = await self._store_bundle(content, f"{skill_id}_v{next_version}.zip")
+
+ version = SkillVersion(
+ id=_new_version_id(),
+ created_at=now,
+ description=manifest.description or "",
+ name=manifest.name or "",
+ skill_id=skill_id,
+ version=next_version,
+ )
+ await self.kvstore.set(_version_key(skill_id, next_version), version.model_dump_json())
+
+ file_ids = await self._get_file_ids(skill_id)
+ file_ids[next_version] = file_id
+ await self._set_file_ids(skill_id, file_ids)
+
+ skill.latest_version = next_version
+ if request.default:
+ skill.default_version = next_version
+ await self.kvstore.set(_skill_key(skill_id), skill.model_dump_json())
+
+ logger.info("Created skill version", skill_id=skill_id, version=next_version)
+ return version
+
+ async def list_skill_versions(self, skill_id: str, request: ListSkillVersionsRequest) -> ListSkillVersionsResponse:
+ await self.get_skill(skill_id)
+
+ values = await self.kvstore.values_in_range(_version_range_start(skill_id), _version_range_end(skill_id))
+ versions = [SkillVersion.model_validate_json(v) for v in values]
+
+ if request.order == "asc":
+ versions.sort(key=lambda v: int(v.version))
+ else:
+ versions.sort(key=lambda v: int(v.version), reverse=True)
+
+ start_idx = 0
+ if request.after:
+ for i, v in enumerate(versions):
+ if v.id == request.after:
+ start_idx = i + 1
+ break
+
+ page = versions[start_idx : start_idx + request.limit]
+ has_more = start_idx + request.limit < len(versions)
+
+ return ListSkillVersionsResponse(
+ data=page,
+ has_more=has_more,
+ first_id=page[0].id if page else None,
+ last_id=page[-1].id if page else None,
+ )
+
+ async def get_skill_version(self, skill_id: str, version: str) -> SkillVersion:
+ await self.get_skill(skill_id)
+
+ data = await self.kvstore.get(_version_key(skill_id, version))
+ if data is None:
+ raise ValueError(f"Failed to find skill version: '{skill_id}' version '{version}' does not exist")
+ return SkillVersion.model_validate_json(data)
+
+ async def get_skill_version_content(self, skill_id: str, version: str) -> Response:
+ await self.get_skill(skill_id)
+
+ file_ids = await self._get_file_ids(skill_id)
+ file_id = file_ids.get(version)
+ if file_id is None:
+ raise ValueError(f"Failed to retrieve skill content: no bundle stored for '{skill_id}' version '{version}'")
+
+ resp = await self.files_api.openai_retrieve_file_content(RetrieveFileContentRequest(file_id=file_id))
+ return Response(
+ content=await response_body_bytes(resp),
+ media_type="application/zip",
+ headers={"Content-Disposition": f'attachment; filename="{skill_id}_v{version}.zip"'},
+ )
+
+ async def delete_skill_version(self, skill_id: str, version: str) -> SkillVersionDeleteResponse:
+ skill = await self.get_skill(skill_id)
+
+ version_data = await self.kvstore.get(_version_key(skill_id, version))
+ if version_data is None:
+ raise ValueError(f"Failed to find skill version: '{skill_id}' version '{version}' does not exist")
+
+ all_version_keys = await self.kvstore.keys_in_range(
+ _version_range_start(skill_id), _version_range_end(skill_id)
+ )
+ if len(all_version_keys) <= 1:
+ raise ValueError(
+ "Failed to delete skill version: cannot delete the only version. Delete the skill instead."
+ )
+
+ file_ids = await self._get_file_ids(skill_id)
+ file_id = file_ids.pop(version, None)
+ if file_id:
+ await self._delete_bundle(file_id)
+ await self._set_file_ids(skill_id, file_ids)
+
+ await self.kvstore.delete(_version_key(skill_id, version))
+
+ # Update default_version if the deleted version was the default
+ if skill.default_version == version:
+ remaining = await self.kvstore.values_in_range(_version_range_start(skill_id), _version_range_end(skill_id))
+ remaining_versions = [SkillVersion.model_validate_json(v) for v in remaining]
+ remaining_versions.sort(key=lambda v: int(v.version), reverse=True)
+ skill.default_version = remaining_versions[0].version
+
+ # Update latest_version if the deleted version was the latest
+ if skill.latest_version == version:
+ remaining = await self.kvstore.values_in_range(_version_range_start(skill_id), _version_range_end(skill_id))
+ remaining_versions = [SkillVersion.model_validate_json(v) for v in remaining]
+ remaining_versions.sort(key=lambda v: int(v.version), reverse=True)
+ skill.latest_version = remaining_versions[0].version
+
+ await self.kvstore.set(_skill_key(skill_id), skill.model_dump_json())
+
+ logger.info("Deleted skill version", skill_id=skill_id, version=version)
+ return SkillVersionDeleteResponse(id=skill_id, version=version)
diff --git a/src/ogx/providers/inline/skills/builtin/manifest.py b/src/ogx/providers/inline/skills/builtin/manifest.py
new file mode 100644
index 00000000000..fee6e16a6f5
--- /dev/null
+++ b/src/ogx/providers/inline/skills/builtin/manifest.py
@@ -0,0 +1,51 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import yaml
+
+from ogx_api.skills.models import SkillManifest
+
+_FENCE = "---"
+
+
+def parse_skill_manifest(content: str) -> SkillManifest:
+ """Parse a SKILL.md file into a SkillManifest.
+
+ Expected format:
+ ---
+ name: my-skill
+ description: Does something useful
+ ---
+ Instructions for the model go here.
+ """
+ lines = content.split("\n")
+
+ if not lines or lines[0].strip() != _FENCE:
+ return SkillManifest(instructions=content.strip())
+
+ closing_idx = None
+ for i in range(1, len(lines)):
+ if lines[i].strip() == _FENCE:
+ closing_idx = i
+ break
+
+ if closing_idx is None:
+ return SkillManifest(instructions=content.strip())
+
+ frontmatter_text = "\n".join(lines[1:closing_idx])
+ instructions = "\n".join(lines[closing_idx + 1 :]).strip()
+
+ frontmatter = yaml.safe_load(frontmatter_text)
+ if not isinstance(frontmatter, dict):
+ return SkillManifest(instructions=instructions)
+
+ return SkillManifest(
+ name=frontmatter.get("name"),
+ description=frontmatter.get("description"),
+ version=frontmatter.get("version"),
+ tools=frontmatter.get("tools"),
+ instructions=instructions,
+ )
diff --git a/src/ogx/providers/inline/skills/builtin/validation.py b/src/ogx/providers/inline/skills/builtin/validation.py
new file mode 100644
index 00000000000..927843fdbbd
--- /dev/null
+++ b/src/ogx/providers/inline/skills/builtin/validation.py
@@ -0,0 +1,85 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import zipfile
+from io import BytesIO
+from pathlib import PurePosixPath
+
+from ogx_api.skills.models import (
+ MAX_FILES_PER_VERSION,
+ MAX_UNCOMPRESSED_FILE_SIZE_BYTES,
+ MAX_ZIP_SIZE_BYTES,
+ SkillManifest,
+)
+
+from .manifest import parse_skill_manifest
+
+_SKILL_MD = "SKILL.md"
+
+
+def _has_path_traversal(filename: str) -> bool:
+ """Check if a zip entry filename attempts path traversal."""
+ if filename.startswith("/"):
+ return True
+ return ".." in PurePosixPath(filename).parts
+
+
+def validate_skill_zip(content: bytes) -> tuple[SkillManifest, list[str]]:
+ """Validate a skill zip bundle and extract its manifest.
+
+ Returns:
+ Tuple of (parsed manifest, list of file paths in the archive).
+
+ Raises:
+ ValueError: If the bundle fails any validation check.
+ """
+ if len(content) > MAX_ZIP_SIZE_BYTES:
+ raise ValueError(
+ f"Failed to validate skill bundle: zip size {len(content)} bytes "
+ f"exceeds maximum of {MAX_ZIP_SIZE_BYTES} bytes"
+ )
+
+ try:
+ zf = zipfile.ZipFile(BytesIO(content))
+ except zipfile.BadZipFile as e:
+ raise ValueError("Failed to validate skill bundle: file is not a valid zip archive") from e
+
+ with zf:
+ entries = zf.infolist()
+
+ if len(entries) > MAX_FILES_PER_VERSION:
+ raise ValueError(
+ f"Failed to validate skill bundle: archive contains {len(entries)} files, "
+ f"maximum is {MAX_FILES_PER_VERSION}"
+ )
+
+ file_paths: list[str] = []
+ skill_md_content: str | None = None
+
+ for entry in entries:
+ if _has_path_traversal(entry.filename):
+ raise ValueError(f"Failed to validate skill bundle: path traversal detected in '{entry.filename}'")
+
+ if entry.file_size > MAX_UNCOMPRESSED_FILE_SIZE_BYTES:
+ raise ValueError(
+ f"Failed to validate skill bundle: '{entry.filename}' uncompressed size "
+ f"{entry.file_size} bytes exceeds maximum of {MAX_UNCOMPRESSED_FILE_SIZE_BYTES} bytes"
+ )
+
+ if not entry.is_dir():
+ file_paths.append(entry.filename)
+
+ if entry.filename == _SKILL_MD:
+ skill_md_content = zf.read(entry.filename).decode("utf-8")
+
+ if skill_md_content is None:
+ raise ValueError("Failed to validate skill bundle: SKILL.md not found at archive root")
+
+ manifest = parse_skill_manifest(skill_md_content)
+ if not manifest.name:
+ raise ValueError("Failed to validate skill bundle: SKILL.md frontmatter must include 'name'")
+
+ return manifest, file_paths
diff --git a/src/ogx/providers/registry/README.md b/src/ogx/providers/registry/README.md
index 7e7583c81b2..20d7bca2374 100644
--- a/src/ogx/providers/registry/README.md
+++ b/src/ogx/providers/registry/README.md
@@ -13,6 +13,7 @@ registry/
inference.py # Inference providers (20+ remote + 2 inline)
interactions.py # Interaction providers
responses.py # Responses API providers (inline::builtin)
+ skills.py # Skills API providers (inline::builtin)
tool_runtime.py # Tool runtime providers
vector_io.py # Vector I/O providers
```
diff --git a/src/ogx/providers/registry/container_runtime.py b/src/ogx/providers/registry/container_runtime.py
new file mode 100644
index 00000000000..5d79991d0d2
--- /dev/null
+++ b/src/ogx/providers/registry/container_runtime.py
@@ -0,0 +1,18 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from ogx_api import ProviderSpec
+
+
+def available_providers() -> list[ProviderSpec]:
+ """Return the list of available container_runtime provider specifications.
+
+ The container_runtime API backs the public Containers API: providers
+ implement the backend lifecycle (Docker/Podman, Kubernetes) that the
+ Containers service delegates to. No backends ship in-tree yet, so the
+ registry is currently empty.
+ """
+ return []
diff --git a/src/ogx/providers/registry/file_processors.py b/src/ogx/providers/registry/file_processors.py
index aa9676137aa..b39f0d9dae4 100644
--- a/src/ogx/providers/registry/file_processors.py
+++ b/src/ogx/providers/registry/file_processors.py
@@ -22,7 +22,7 @@ def available_providers() -> list[ProviderSpec]:
InlineProviderSpec(
api=Api.file_processors,
provider_type="inline::auto",
- pip_packages=["chardet", "pypdf>=6.7.2", "markitdown[all]"],
+ pip_packages=["chardet", "pypdf>=6.13.0", "markitdown[all]"],
module="ogx.providers.inline.file_processor.auto",
config_class="ogx.providers.inline.file_processor.auto.AutoFileProcessorConfig",
api_dependencies=[Api.files],
@@ -36,7 +36,7 @@ def available_providers() -> list[ProviderSpec]:
InlineProviderSpec(
api=Api.file_processors,
provider_type="inline::pypdf",
- pip_packages=["chardet", "pypdf>=6.7.2"],
+ pip_packages=["chardet", "pypdf>=6.13.0"],
module="ogx.providers.inline.file_processor.pypdf",
config_class="ogx.providers.inline.file_processor.pypdf.PyPDFFileProcessorConfig",
api_dependencies=[Api.files],
@@ -134,6 +134,126 @@ def available_providers() -> list[ProviderSpec]:
## Documentation
See [Docling's documentation](https://docling-project.github.io/docling/) for more details.
+""",
+ ),
+ InlineProviderSpec(
+ api=Api.file_processors,
+ provider_type="inline::unstructured",
+ pip_packages=["unstructured[all-docs]>=0.21.0"], # Security fix in 0.21.0
+ module="ogx.providers.inline.file_processor.unstructured",
+ config_class="ogx.providers.inline.file_processor.unstructured.UnstructuredFileProcessorConfig",
+ api_dependencies=[Api.files],
+ description="""
+[Unstructured](https://github.com/Unstructured-IO/unstructured) is a comprehensive document
+processing library supporting 65+ file formats including PDF, Office documents (DOCX, PPTX, XLSX),
+email formats (EML, MSG), legacy formats (DOC, XLS), HTML, Markdown, and audio transcription.
+
+This provider uses the local Unstructured library for offline document processing. For cloud-based
+processing with better table extraction, use `remote::unstructured-api` instead.
+
+## Features
+
+- 65+ format support - broadest format coverage of any OGX file processor
+- Email processing - EML and MSG email formats (unique to Unstructured)
+- Legacy formats - DOC, XLS, and other legacy Office formats
+- Audio transcription - MP3, WAV, M4A via Whisper
+- Local processing - no network required, cost-effective for high volume
+- Structure-aware chunking - preserves document sections and headings
+
+## Limitations
+
+WARNING: Table detection is unreliable in local mode (GitHub issue [#2997](https://github.com/Unstructured-IO/unstructured/issues/2997)).
+For production table extraction, use `remote::unstructured-api` instead.
+
+## System Requirements
+
+Required system dependencies:
+- `libmagic-dev` - file type detection
+- `poppler-utils` - PDF processing
+- `tesseract-ocr` - OCR support
+
+Optional (for Office documents):
+- `libreoffice` - Office document conversion (~800 MB)
+
+### macOS
+```bash
+brew install libmagic poppler tesseract
+# Optional: brew install libreoffice
+```
+
+### Ubuntu/Debian
+```bash
+sudo apt-get update && sudo apt-get install -y \\
+ libmagic-dev \\
+ poppler-utils \\
+ tesseract-ocr
+# Optional: sudo apt-get install -y libreoffice
+```
+
+### Docker (Recommended)
+```dockerfile
+FROM python:3.12-slim
+
+RUN apt-get update && apt-get install -y \\
+ libmagic-dev \\
+ poppler-utils \\
+ tesseract-ocr \\
+ && rm -rf /var/lib/apt/lists/*
+
+RUN pip install ogx[unstructured-local]
+```
+
+## Installation
+
+```bash
+pip install "ogx[unstructured-local]"
+```
+
+Then install system dependencies as shown above.
+
+## Usage
+
+Start OGX with the Unstructured file processor:
+
+```bash
+ogx stack run \\
+ --providers "file_processors=inline::unstructured" \\
+ --port 8321
+```
+
+Or add it to a custom `run.yaml`:
+
+```yaml
+file_processors:
+ - provider_id: unstructured
+ provider_type: inline::unstructured
+ config:
+ strategy: auto # or 'fast', 'hi_res', 'ocr_only'
+ skip_infer_table_types: ["pdf"] # Workaround for table issues
+```
+
+## When to Use
+
+**Use `inline::unstructured` when:**
+- You need email format support (EML, MSG)
+- You need legacy Office formats (DOC, XLS)
+- You need audio transcription
+- You need offline/local processing
+- You need the broadest format coverage
+
+**Use `inline::docling` when:**
+- You need precise token-based chunking
+- You need best-in-class table extraction
+- You primarily process PDF/DOCX/PPTX
+
+**Use `remote::unstructured-api` when:**
+- You need reliable table extraction
+- You have network connectivity and API key
+- You want to avoid system dependencies
+
+## Documentation
+
+See [Unstructured's documentation](https://docs.unstructured.io/) for more details.
""",
),
RemoteProviderSpec(
diff --git a/src/ogx/providers/registry/inference.py b/src/ogx/providers/registry/inference.py
index d0485eee369..a7362b9454d 100644
--- a/src/ogx/providers/registry/inference.py
+++ b/src/ogx/providers/registry/inference.py
@@ -51,19 +51,6 @@ def available_providers() -> list[ProviderSpec]:
config_class="ogx.providers.inline.inference.sentence_transformers.config.SentenceTransformersInferenceConfig",
description="Sentence Transformers inference provider for text embeddings and similarity search.",
),
- InlineProviderSpec(
- api=Api.inference,
- provider_type="inline::transformers",
- pip_packages=[
- "torch --extra-index-url https://download.pytorch.org/whl/cpu",
- "transformers",
- "tokenizers",
- "safetensors",
- ],
- module="ogx.providers.inline.inference.transformers",
- config_class="ogx.providers.inline.inference.transformers.config.TransformersInferenceConfig",
- description="Transformers inference provider for neural rerank.",
- ),
RemoteProviderSpec(
api=Api.inference,
adapter_type="cerebras",
@@ -195,7 +182,7 @@ def available_providers() -> list[ProviderSpec]:
adapter_type="vertexai",
provider_type="remote::vertexai",
pip_packages=[
- "google-genai>=1.69.0",
+ "google-genai>=1.69.0,<2",
],
module="ogx.providers.remote.inference.vertexai",
config_class="ogx.providers.remote.inference.vertexai.VertexAIConfig",
diff --git a/src/ogx/providers/registry/skills.py b/src/ogx/providers/registry/skills.py
new file mode 100644
index 00000000000..032725ef98e
--- /dev/null
+++ b/src/ogx/providers/registry/skills.py
@@ -0,0 +1,21 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from ogx_api import InlineProviderSpec
+from ogx_api.datatypes import Api
+
+
+def available_providers() -> list[InlineProviderSpec]:
+ return [
+ InlineProviderSpec(
+ api=Api.skills,
+ provider_type="inline::builtin",
+ module="ogx.providers.inline.skills.builtin",
+ config_class="ogx.providers.inline.skills.builtin.config.BuiltinSkillsConfig",
+ description="Built-in skills provider using Files API for bundle storage.",
+ api_dependencies=[Api.files],
+ ),
+ ]
diff --git a/src/ogx/providers/registry/tool_runtime.py b/src/ogx/providers/registry/tool_runtime.py
index e82df13fa07..eaad8f7afb2 100644
--- a/src/ogx/providers/registry/tool_runtime.py
+++ b/src/ogx/providers/registry/tool_runtime.py
@@ -73,6 +73,17 @@ def available_providers() -> list[ProviderSpec]:
toolgroup_id="builtin::websearch",
description="Tavily Search tool for AI-optimized web search with structured results.",
),
+ RemoteProviderSpec(
+ api=Api.tool_runtime,
+ adapter_type="nimble-search",
+ provider_type="remote::nimble-search",
+ module="ogx.providers.remote.tool_runtime.nimble_search",
+ config_class="ogx.providers.remote.tool_runtime.nimble_search.config.NimbleSearchToolConfig",
+ pip_packages=[],
+ provider_data_validator="ogx.providers.remote.tool_runtime.nimble_search.NimbleSearchToolProviderDataValidator",
+ toolgroup_id="builtin::websearch",
+ description="Nimble Search tool for web search via Nimble's SERP-backed search API.",
+ ),
RemoteProviderSpec(
api=Api.tool_runtime,
adapter_type="wolfram-alpha",
diff --git a/src/ogx/providers/registry/vector_io.py b/src/ogx/providers/registry/vector_io.py
index 6f4fbf61ef5..537aa74e730 100644
--- a/src/ogx/providers/registry/vector_io.py
+++ b/src/ogx/providers/registry/vector_io.py
@@ -13,7 +13,7 @@
)
# Common dependencies for all vector IO providers that support document processing
-DEFAULT_VECTOR_IO_DEPS = ["chardet", "pypdf>=6.10.0"]
+DEFAULT_VECTOR_IO_DEPS = ["chardet", "pypdf>=6.13.0"]
def available_providers() -> list[ProviderSpec]:
@@ -818,7 +818,7 @@ def available_providers() -> list[ProviderSpec]:
InlineProviderSpec(
api=Api.vector_io,
provider_type="inline::milvus",
- pip_packages=["pymilvus[milvus-lite]>=2.4.10"] + DEFAULT_VECTOR_IO_DEPS,
+ pip_packages=["pymilvus[milvus-lite]>=2.6.2"] + DEFAULT_VECTOR_IO_DEPS,
module="ogx.providers.inline.vector_io.milvus",
config_class="ogx.providers.inline.vector_io.milvus.MilvusVectorIOConfig",
api_dependencies=[Api.inference],
diff --git a/src/ogx/providers/remote/README.md b/src/ogx/providers/remote/README.md
index fdf6199c859..5a5c1283c1d 100644
--- a/src/ogx/providers/remote/README.md
+++ b/src/ogx/providers/remote/README.md
@@ -30,7 +30,7 @@ remote/
watsonx/ # IBM WatsonX
vector_io/ # Remote vector storage (chroma, elasticsearch, milvus, pgvector, qdrant, weaviate, etc.)
files/ # Remote file storage (openai, s3)
- tool_runtime/ # Remote tool runtimes (bing, brave, mcp, tavily, wolfram_alpha)
+ tool_runtime/ # Remote tool runtimes (bing, brave, mcp, nimble, tavily, wolfram_alpha)
__init__.py
```
diff --git a/src/ogx/providers/remote/file_processor/docling_serve/docling_serve.py b/src/ogx/providers/remote/file_processor/docling_serve/docling_serve.py
index 4140c70ddf1..5de82c0cc27 100644
--- a/src/ogx/providers/remote/file_processor/docling_serve/docling_serve.py
+++ b/src/ogx/providers/remote/file_processor/docling_serve/docling_serve.py
@@ -13,6 +13,7 @@
from fastapi import UploadFile
from ogx.log import get_logger
+from ogx.providers.utils.files.response import response_body_bytes
from ogx.providers.utils.vector_io.vector_utils import generate_chunk_id
from ogx_api.file_processors import ProcessFileRequest, ProcessFileResponse
from ogx_api.files import Files, RetrieveFileContentRequest, RetrieveFileRequest
@@ -70,8 +71,7 @@ async def process_file(
content_response = await self.files_api.openai_retrieve_file_content(
RetrieveFileContentRequest(file_id=file_id)
)
- # Normalize bytes/memoryview payloads to bytes for downstream file handling.
- content = bytes(content_response.body)
+ content = await response_body_bytes(content_response)
document_id = file_id if file_id else str(uuid.uuid4())
document_metadata: dict[str, Any] = {"filename": filename}
diff --git a/src/ogx/providers/remote/files/s3/files.py b/src/ogx/providers/remote/files/s3/files.py
index 954c9cbe78b..30edf03717d 100644
--- a/src/ogx/providers/remote/files/s3/files.py
+++ b/src/ogx/providers/remote/files/s3/files.py
@@ -12,6 +12,7 @@
import boto3
from botocore.exceptions import BotoCoreError, ClientError, NoCredentialsError
from fastapi import Response, UploadFile
+from fastapi.responses import StreamingResponse
if TYPE_CHECKING:
from mypy_boto3_s3.client import S3Client
@@ -325,25 +326,29 @@ async def openai_retrieve_file_content(self, request: RetrieveFileContentRequest
row = await self._get_file(file_id)
try:
-
- def _download_from_s3() -> bytes:
- response = self.client.get_object(
- Bucket=self._config.bucket_name,
- Key=row["id"],
- )
- # TODO: can we stream this instead of loading it into memory
- body: bytes = response["Body"].read()
- return body
-
- content = await asyncio.to_thread(_download_from_s3)
+ s3_response = await asyncio.to_thread(
+ self.client.get_object,
+ Bucket=self._config.bucket_name,
+ Key=row["id"],
+ )
except ClientError as e:
if e.response["Error"]["Code"] == "NoSuchKey":
await self._delete_file(file_id)
raise OpenAIFileObjectNotFoundError(file_id) from e
raise RuntimeError(f"Failed to download file from S3: {e}") from e
- return Response(
- content=content,
+ chunk_size = 1024 * 1024
+
+ def _stream_body():
+ body = s3_response["Body"]
+ try:
+ while chunk := body.read(chunk_size):
+ yield chunk
+ finally:
+ body.close()
+
+ return StreamingResponse(
+ content=_stream_body(),
media_type="application/octet-stream",
headers={
"Content-Disposition": f'attachment; filename="{sanitize_content_disposition_filename(row["filename"])}"'
diff --git a/src/ogx/providers/remote/inference/anthropic/anthropic.py b/src/ogx/providers/remote/inference/anthropic/anthropic.py
index 5d65e2fd326..4097f7978ae 100644
--- a/src/ogx/providers/remote/inference/anthropic/anthropic.py
+++ b/src/ogx/providers/remote/inference/anthropic/anthropic.py
@@ -4,11 +4,15 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
-from collections.abc import Iterable
+from collections.abc import AsyncIterator, Iterable
from anthropic import AsyncAnthropic
from ogx.providers.utils.inference.openai_mixin import OpenAIMixin
+from ogx_api.inference.models import (
+ OpenAICompletion,
+ OpenAICompletionRequestWithExtraBody,
+)
from .config import AnthropicConfig
@@ -37,3 +41,12 @@ def get_base_url(self):
async def list_provider_model_ids(self) -> Iterable[str]:
api_key = self._get_api_key_from_config_or_provider_data()
return [m.id async for m in AsyncAnthropic(api_key=api_key).models.list()]
+
+ async def openai_completion(
+ self,
+ params: OpenAICompletionRequestWithExtraBody,
+ ) -> OpenAICompletion | AsyncIterator[OpenAICompletion]:
+ """Anthropic does not support the /v1/completions endpoint."""
+ raise NotImplementedError(
+ "Anthropic does not support /v1/completions endpoint. Only /v1/chat/completions is supported. "
+ )
diff --git a/src/ogx/providers/remote/inference/bedrock/config.py b/src/ogx/providers/remote/inference/bedrock/config.py
index 7fff0a17f3a..1ea3367e526 100644
--- a/src/ogx/providers/remote/inference/bedrock/config.py
+++ b/src/ogx/providers/remote/inference/bedrock/config.py
@@ -11,6 +11,13 @@
from ogx.providers.utils.bedrock.config import BedrockBaseConfig
+def _bedrock_bearer_token_from_env() -> SecretStr | None:
+ token = os.getenv("AWS_BEDROCK_BEARER_TOKEN") or os.getenv("AWS_BEARER_TOKEN_BEDROCK")
+ if token is None:
+ return None
+ return SecretStr(token)
+
+
class BedrockProviderDataValidator(BaseModel):
"""Validates provider-specific request data for AWS Bedrock inference."""
@@ -29,9 +36,9 @@ class BedrockConfig(BedrockBaseConfig):
"""Configuration for the AWS Bedrock inference provider."""
auth_credential: SecretStr | None = Field(
- default=None,
+ default_factory=_bedrock_bearer_token_from_env,
alias="aws_bedrock_bearer_token",
- validation_alias=AliasChoices("aws_bedrock_bearer_token", "api_key"),
+ validation_alias=AliasChoices("aws_bedrock_bearer_token", "aws_bearer_token_bedrock", "api_key"),
description=(
"Optional bearer token for Amazon Bedrock's OpenAI-compatible runtime. "
"Leave unset to use the server's AWS credential chain (recommended)."
diff --git a/src/ogx/providers/remote/inference/openai/openai.py b/src/ogx/providers/remote/inference/openai/openai.py
index 34cb713056a..b6767dd1bf7 100644
--- a/src/ogx/providers/remote/inference/openai/openai.py
+++ b/src/ogx/providers/remote/inference/openai/openai.py
@@ -4,7 +4,8 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
-from collections.abc import AsyncIterator
+import warnings
+from collections.abc import AsyncIterator, Iterable
from ogx.log import get_logger
from ogx.providers.utils.inference.openai_mixin import OpenAIMixin
@@ -57,6 +58,7 @@ class OpenAIInferenceAdapter(OpenAIMixin):
supports_tokenized_embeddings_input: bool = True
embedding_model_metadata: dict[str, dict[str, int]] = {
+ "text-embedding-ada-002": {"embedding_dimension": 1536, "context_length": 8192},
"text-embedding-3-small": {"embedding_dimension": 1536, "context_length": 8192},
"text-embedding-3-large": {"embedding_dimension": 3072, "context_length": 8192},
}
@@ -82,33 +84,50 @@ def _get_max_output_tokens(self, model: str) -> int | None:
)
return None
+ async def list_provider_model_ids(self) -> Iterable[str]:
+ """
+ Filter out realtime & audio models.
+ """
+ ids = []
+ for m in await super().list_provider_model_ids():
+ for excluded in {"whisper", "tts", "realtime", "audio"}:
+ if excluded in m:
+ break
+ else:
+ ids.append(m)
+ return ids
+
def construct_model_from_identifier(self, identifier: str) -> Model:
- if metadata := self.embedding_model_metadata.get(identifier):
- return Model(
- provider_id=self.__provider_id__, # type: ignore[attr-defined]
- provider_resource_id=identifier,
- identifier=identifier,
- model_type=ModelType.embedding,
- metadata=metadata,
- )
+ model = super().construct_model_from_identifier(identifier)
- metadata = {}
- max_output_tokens = self._get_max_output_tokens(identifier)
- if max_output_tokens is not None:
- metadata["max_output_tokens"] = max_output_tokens
-
- return Model(
- provider_id=self.__provider_id__, # type: ignore[attr-defined]
- provider_resource_id=identifier,
- identifier=identifier,
- model_type=ModelType.llm,
- metadata=metadata,
- )
+ # Add max_output_tokens metadata for LLM models
+ if model.model_type == ModelType.llm:
+ max_output_tokens = self._get_max_output_tokens(identifier)
+ if max_output_tokens is not None:
+ metadata = dict(model.metadata or {})
+ metadata["max_output_tokens"] = max_output_tokens
+ model = model.model_copy(update={"metadata": metadata})
+
+ return model
async def openai_chat_completion(
self,
params: OpenAIChatCompletionRequestWithExtraBody,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
+ # OpenAI is deprecating max_tokens in favor of max_completion_tokens.
+ # Reasoning models (o1/o3/o4) and gpt-5+ reject max_tokens outright.
+ # Translate unconditionally since all OpenAI models accept max_completion_tokens.
+ if params.max_tokens is not None and params.max_completion_tokens is None:
+ warnings.warn(
+ "max_tokens is deprecated by OpenAI and will be removed in a future release. "
+ "Use max_completion_tokens instead.",
+ DeprecationWarning,
+ stacklevel=2,
+ )
+ params = params.model_copy()
+ params.max_completion_tokens = params.max_tokens
+ params.max_tokens = None
+
max_output_tokens = self._get_max_output_tokens(params.model)
if max_output_tokens is not None:
updated_params = params
diff --git a/src/ogx/providers/remote/inference/vertexai/converters.py b/src/ogx/providers/remote/inference/vertexai/converters.py
index 3958aadb5f8..bb2416fc68f 100644
--- a/src/ogx/providers/remote/inference/vertexai/converters.py
+++ b/src/ogx/providers/remote/inference/vertexai/converters.py
@@ -236,8 +236,8 @@ def _convert_user_message(msg: dict[str, Any]) -> dict[str, Any]:
parts.append(inline)
else:
logger.warning(
- "Unsupported content part type '%s' in user message; skipping",
- part_type,
+ "Unsupported content part type in user message; skipping",
+ part_type=part_type,
)
return {"role": "user", "parts": parts}
diff --git a/src/ogx/providers/remote/inference/vertexai/vertexai.py b/src/ogx/providers/remote/inference/vertexai/vertexai.py
index df460073f2b..f3236f7b98b 100644
--- a/src/ogx/providers/remote/inference/vertexai/vertexai.py
+++ b/src/ogx/providers/remote/inference/vertexai/vertexai.py
@@ -192,9 +192,9 @@ async def initialize(self) -> None:
# Don't create the client here - it will be created lazily on first use
# This avoids calling _ensure_http_options() in the temporary startup event loop
logger.info(
- "VertexAI provider initialized for project=%s location=%s (client will be created on first use)",
- self.config.project,
- self.config.location,
+ "VertexAI provider initialized (client will be created on first use)",
+ project=self.config.project,
+ location=self.config.location,
)
except Exception:
logger.warning(
@@ -202,6 +202,29 @@ async def initialize(self) -> None:
exc_info=True,
)
+ def _reset_client(self) -> None:
+ """Reset cached client and HTTP options after a temporary event loop exits.
+
+ When StackApp.__init__ runs stack.initialize() inside a temporary event
+ loop (via ThreadPoolExecutor), model listing may trigger lazy client
+ creation via _get_client(). The Google genai Client eagerly creates an
+ internal httpx.AsyncClient bound to the temporary loop. After the
+ temporary loop is closed, the cached client holds connections tied to
+ the dead loop, causing ``RuntimeError: Event loop is closed`` on the
+ first inference request.
+
+ This method clears the cached client without awaiting async close
+ (the temporary loop is already terminated) so that a fresh client is
+ created on the next _get_client() call — this time on uvicorn's
+ request-handling event loop.
+
+ Compare ``reset_sqlstore_engines()`` which serves the same purpose for
+ SQL engines.
+ """
+ self._default_client = None
+ self._http_options = None
+ self._http_options_initialized = False
+
async def shutdown(self) -> None:
await self._close_managed_httpx_client()
self._http_options = None
@@ -265,8 +288,8 @@ async def check_model_availability(self, model: str) -> bool:
await self.list_models()
except Exception:
logger.warning(
- "Failed to list VertexAI models for availability check; accepting model '%s' without validation.",
- model,
+ "Failed to list VertexAI models for availability check; accepting model without validation.",
+ model=model,
exc_info=True,
)
return True
@@ -315,7 +338,30 @@ def _get_client(self) -> Client:
access_token = self.config.auth_credential.get_secret_value() if self.config.auth_credential else None
return self._create_client(project=project, location=location, access_token=access_token)
- # Lazily create the default client on first use
+ # Lazily create the default client on first use.
+ # If we already have a cached client, verify it is still usable before
+ # returning it — a previous request may have left connections tied to an
+ # event loop that is now closed (e.g., after a temporary startup loop).
+ if self._default_client is not None:
+ try:
+ # Touch the underlying httpx client to detect event loop binding
+ # issues. If the client was created in a now-closed loop,
+ # accessing its transport raises RuntimeError.
+ if self._http_options is not None:
+ _client = getattr(self._http_options, "httpx_async_client", None)
+ if _client is not None and _client.is_closed:
+ logger.info(
+ "VertexAI default client transport is closed; recreating",
+ project=self.config.project,
+ )
+ self._default_client = None
+ except RuntimeError:
+ logger.warning(
+ "VertexAI default client is bound to a closed event loop; recreating",
+ project=self.config.project,
+ )
+ self._default_client = None
+
if self._default_client is None:
access_token = self.config.auth_credential.get_secret_value() if self.config.auth_credential else None
try:
@@ -386,8 +432,8 @@ async def list_models(self) -> list[Model] | None:
provider_model_ids = await self.list_provider_model_ids()
except Exception:
logger.error(
- "%s.list_provider_model_ids() failed",
- self.__class__.__name__,
+ "Failed to list provider model IDs",
+ provider=self.__class__.__name__,
exc_info=True,
)
raise
@@ -907,8 +953,8 @@ async def openai_embeddings(
# passthrough. Log and ignore extra body parameters rather than silently dropping.
if params.model_extra:
logger.debug(
- "VertexAI embeddings does not support extra body parameters; model_extra will be ignored: %s",
- list(params.model_extra.keys()),
+ "VertexAI embeddings does not support extra body parameters; model_extra will be ignored",
+ ignored_keys=list(params.model_extra.keys()),
)
provider_model_id = await self._get_provider_model_id(params.model)
diff --git a/src/ogx/providers/remote/tool_runtime/bing_search/bing_search.py b/src/ogx/providers/remote/tool_runtime/bing_search/bing_search.py
index 0202b8174f8..4f5116c9191 100644
--- a/src/ogx/providers/remote/tool_runtime/bing_search/bing_search.py
+++ b/src/ogx/providers/remote/tool_runtime/bing_search/bing_search.py
@@ -47,16 +47,14 @@ async def register_toolgroup(self, toolgroup: ToolGroup) -> None:
async def unregister_toolgroup(self, toolgroup_id: str) -> None:
return
- def _get_api_key(self) -> str:
- if self.config.api_key:
- return self.config.api_key
+ def _get_api_key(self) -> str | None:
+ api_key = self.config.api_key.get_secret_value() if self.config.api_key else None
provider_data = self.get_request_provider_data()
- if provider_data is None or not provider_data.bing_search_api_key:
- raise ValueError(
- 'Pass Bing Search API Key in the header X-OGX-Provider-Data as { "bing_search_api_key": }'
- )
- return provider_data.bing_search_api_key.get_secret_value()
+ if provider_data and provider_data.bing_search_api_key:
+ api_key = provider_data.bing_search_api_key.get_secret_value()
+
+ return api_key
async def list_runtime_tools(
self,
@@ -87,9 +85,9 @@ async def invoke_tool(
self, tool_name: str, kwargs: dict[str, Any], authorization: str | None = None
) -> ToolInvocationResult:
api_key = self._get_api_key()
- headers = {
- "Ocp-Apim-Subscription-Key": api_key,
- }
+ headers: dict[str, str] = {}
+ if api_key:
+ headers["Ocp-Apim-Subscription-Key"] = api_key
query = kwargs["query"]
diff --git a/src/ogx/providers/remote/tool_runtime/bing_search/config.py b/src/ogx/providers/remote/tool_runtime/bing_search/config.py
index 62c2e4c5618..b896a590c60 100644
--- a/src/ogx/providers/remote/tool_runtime/bing_search/config.py
+++ b/src/ogx/providers/remote/tool_runtime/bing_search/config.py
@@ -6,17 +6,22 @@
from typing import Any
+from pydantic import Field, SecretStr
+
from ogx.providers.utils.common.http import BaseToolRuntimeConfig
class BingSearchToolConfig(BaseToolRuntimeConfig):
"""Configuration for Bing Search Tool Runtime"""
- api_key: str | None = None
+ api_key: SecretStr | None = Field(
+ default=None,
+ description="The Bing Search API Key. Can be overridden per-request via X-OGX-Provider-Data header.",
+ )
top_k: int = 3
@classmethod
def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> dict[str, Any]:
return {
- "api_key": "${env.BING_API_KEY:}",
+ "api_key": "${env.BING_API_KEY:=}",
}
diff --git a/src/ogx/providers/remote/tool_runtime/brave_search/brave_search.py b/src/ogx/providers/remote/tool_runtime/brave_search/brave_search.py
index e695612bb42..1262da14906 100644
--- a/src/ogx/providers/remote/tool_runtime/brave_search/brave_search.py
+++ b/src/ogx/providers/remote/tool_runtime/brave_search/brave_search.py
@@ -39,16 +39,14 @@ async def register_toolgroup(self, toolgroup: ToolGroup) -> None:
async def unregister_toolgroup(self, toolgroup_id: str) -> None:
return
- def _get_api_key(self) -> str:
- if self.config.api_key:
- return self.config.api_key
+ def _get_api_key(self) -> str | None:
+ api_key = self.config.api_key.get_secret_value() if self.config.api_key else None
provider_data = self.get_request_provider_data()
- if provider_data is None or not provider_data.brave_search_api_key:
- raise ValueError(
- 'Pass Search provider\'s API Key in the header X-OGX-Provider-Data as { "brave_search_api_key": }'
- )
- return provider_data.brave_search_api_key.get_secret_value()
+ if provider_data and provider_data.brave_search_api_key:
+ api_key = provider_data.brave_search_api_key.get_secret_value()
+
+ return api_key
async def list_runtime_tools(
self,
@@ -80,11 +78,12 @@ async def invoke_tool(
) -> ToolInvocationResult:
api_key = self._get_api_key()
url = "https://api.search.brave.com/res/v1/web/search"
- headers = {
- "X-Subscription-Token": api_key,
+ headers: dict[str, str] = {
"Accept-Encoding": "gzip",
"Accept": "application/json",
}
+ if api_key:
+ headers["X-Subscription-Token"] = api_key
query = kwargs["query"]
diff --git a/src/ogx/providers/remote/tool_runtime/brave_search/config.py b/src/ogx/providers/remote/tool_runtime/brave_search/config.py
index 5e8d3333a58..549dea8a7bd 100644
--- a/src/ogx/providers/remote/tool_runtime/brave_search/config.py
+++ b/src/ogx/providers/remote/tool_runtime/brave_search/config.py
@@ -6,7 +6,7 @@
from typing import Any
-from pydantic import Field
+from pydantic import Field, SecretStr
from ogx.providers.utils.common.http import BaseToolRuntimeConfig
@@ -14,9 +14,9 @@
class BraveSearchToolConfig(BaseToolRuntimeConfig):
"""Configuration for the Brave Search tool runtime."""
- api_key: str | None = Field(
+ api_key: SecretStr | None = Field(
default=None,
- description="The Brave Search API Key",
+ description="The Brave Search API Key. Can be overridden per-request via X-OGX-Provider-Data header.",
)
max_results: int = Field(
default=3,
diff --git a/src/ogx/providers/remote/tool_runtime/nimble_search/__init__.py b/src/ogx/providers/remote/tool_runtime/nimble_search/__init__.py
new file mode 100644
index 00000000000..abdd2487069
--- /dev/null
+++ b/src/ogx/providers/remote/tool_runtime/nimble_search/__init__.py
@@ -0,0 +1,22 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from pydantic import BaseModel, SecretStr
+
+from .config import NimbleSearchToolConfig
+from .nimble_search import NimbleSearchToolRuntimeImpl
+
+
+class NimbleSearchToolProviderDataValidator(BaseModel):
+ """Validator for Nimble Search tool provider data requiring a Nimble API key."""
+
+ nimble_search_api_key: SecretStr
+
+
+async def get_adapter_impl(config: NimbleSearchToolConfig, _deps):
+ impl = NimbleSearchToolRuntimeImpl(config)
+ await impl.initialize()
+ return impl
diff --git a/src/ogx/providers/remote/tool_runtime/nimble_search/config.py b/src/ogx/providers/remote/tool_runtime/nimble_search/config.py
new file mode 100644
index 00000000000..b38ef42a8b7
--- /dev/null
+++ b/src/ogx/providers/remote/tool_runtime/nimble_search/config.py
@@ -0,0 +1,36 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Any, Literal
+
+from pydantic import Field, SecretStr
+
+from ogx.providers.utils.common.http import BaseToolRuntimeConfig
+
+
+class NimbleSearchToolConfig(BaseToolRuntimeConfig):
+ """Configuration for the Nimble Search tool runtime."""
+
+ api_key: SecretStr | None = Field(
+ default=None,
+ description="The Nimble API key, sent as a Bearer token. Can be overridden per-request via the X-OGX-Provider-Data header.",
+ )
+ max_results: int = Field(
+ default=3,
+ description="The maximum number of results to return",
+ )
+ search_depth: Literal["lite", "deep"] = Field(
+ default="lite",
+ description="Content richness: 'lite' returns title, URL, and description; 'deep' returns full page content",
+ )
+
+ @classmethod
+ def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]:
+ return {
+ "api_key": "${env.NIMBLE_API_KEY:=}",
+ "max_results": 3,
+ "search_depth": "lite",
+ }
diff --git a/src/ogx/providers/remote/tool_runtime/nimble_search/nimble_search.py b/src/ogx/providers/remote/tool_runtime/nimble_search/nimble_search.py
new file mode 100644
index 00000000000..2dfaa8f69e7
--- /dev/null
+++ b/src/ogx/providers/remote/tool_runtime/nimble_search/nimble_search.py
@@ -0,0 +1,153 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import json
+from typing import Any
+
+import httpx
+
+from ogx.core.request_headers import NeedsRequestProviderData
+from ogx_api import (
+ URL,
+ ListToolDefsResponse,
+ ToolDef,
+ ToolGroup,
+ ToolGroupsProtocolPrivate,
+ ToolInvocationResult,
+ ToolRuntime,
+)
+
+from .config import NimbleSearchToolConfig
+
+
+class NimbleSearchToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, NeedsRequestProviderData):
+ """Tool runtime for performing web searches using the Nimble Search API."""
+
+ _SEARCH_URL = "https://sdk.nimbleway.com/v1/search"
+ _CONTEXT_SIZE_TO_COUNT = {"low": 3, "medium": 5, "high": 10}
+
+ def __init__(self, config: NimbleSearchToolConfig):
+ self.config = config
+ self._client: httpx.AsyncClient | None = None
+
+ async def initialize(self) -> None:
+ self._client = httpx.AsyncClient(timeout=self.config.to_httpx_timeout())
+
+ async def shutdown(self) -> None:
+ if self._client:
+ await self._client.aclose()
+ self._client = None
+
+ async def register_toolgroup(self, toolgroup: ToolGroup) -> None:
+ pass
+
+ async def unregister_toolgroup(self, toolgroup_id: str) -> None:
+ return
+
+ def _get_api_key(self) -> str | None:
+ api_key = self.config.api_key.get_secret_value() if self.config.api_key else None
+
+ provider_data = self.get_request_provider_data()
+ if provider_data and provider_data.nimble_search_api_key:
+ api_key = str(provider_data.nimble_search_api_key.get_secret_value())
+
+ return api_key
+
+ async def list_runtime_tools(
+ self,
+ tool_group_id: str | None = None,
+ mcp_endpoint: URL | None = None,
+ authorization: str | None = None,
+ ) -> ListToolDefsResponse:
+ return ListToolDefsResponse(
+ data=[
+ ToolDef(
+ name="web_search",
+ description="Search the web for information",
+ input_schema={
+ "type": "object",
+ "properties": {
+ "query": {
+ "type": "string",
+ "description": "The query to search for",
+ }
+ },
+ "required": ["query"],
+ },
+ )
+ ]
+ )
+
+ async def invoke_tool(
+ self, tool_name: str, kwargs: dict[str, Any], authorization: str | None = None
+ ) -> ToolInvocationResult:
+ api_key = self._get_api_key()
+ request_body: dict[str, Any] = {
+ "query": kwargs["query"],
+ "max_results": self.config.max_results,
+ "search_depth": self.config.search_depth,
+ }
+
+ allowed_domains = kwargs.get("allowed_domains")
+ if allowed_domains:
+ request_body["include_domains"] = allowed_domains
+
+ # Geo-targeting is per-request user-supplied context, not server config.
+ user_location = kwargs.get("user_location")
+ if user_location and user_location.get("country"):
+ request_body["country"] = user_location["country"]
+
+ search_context_size = kwargs.get("search_context_size")
+ if search_context_size and search_context_size in self._CONTEXT_SIZE_TO_COUNT:
+ request_body["max_results"] = self._CONTEXT_SIZE_TO_COUNT[search_context_size]
+
+ if self._client is None:
+ raise RuntimeError("Failed to invoke tool: provider not initialized")
+ headers = {"Authorization": f"Bearer {api_key}"} if api_key else {}
+ response = await self._client.post(
+ self._SEARCH_URL,
+ json=request_body,
+ headers=headers,
+ )
+ if response.status_code == 403:
+ # The account is not entitled to the requested capability (e.g. a higher
+ # search_depth tier). Surface a clear tool error without raising, and include
+ # content so the executor forwards the reason to the model rather than a
+ # generic "Tool execution failed".
+ message = (
+ f"Failed to query Nimble Search: the account is not entitled to "
+ f"search_depth={self.config.search_depth!r}. Use search_depth='lite' "
+ f"or contact Nimble to enable higher tiers."
+ )
+ return ToolInvocationResult(
+ content=json.dumps({"error": message}),
+ error_code=403,
+ error_message=message,
+ metadata={"query": kwargs["query"], "sources": []},
+ )
+ response.raise_for_status()
+
+ response_json = response.json()
+ results = []
+ sources = []
+ for r in response_json.get("results", []):
+ url = r.get("url")
+ # In 'lite' depth the API returns metadata only (empty content); the
+ # description carries the result text, so fall back to it.
+ results.append(
+ {
+ "title": r.get("title", ""),
+ "url": url,
+ "content": r.get("content") or r.get("description", ""),
+ }
+ )
+ if url:
+ sources.append({"url": url})
+
+ return ToolInvocationResult(
+ content=json.dumps({"query": kwargs["query"], "results": results}),
+ metadata={"query": kwargs["query"], "sources": sources},
+ )
diff --git a/src/ogx/providers/remote/tool_runtime/tavily_search/config.py b/src/ogx/providers/remote/tool_runtime/tavily_search/config.py
index 17d7056cd32..a54be8d62f6 100644
--- a/src/ogx/providers/remote/tool_runtime/tavily_search/config.py
+++ b/src/ogx/providers/remote/tool_runtime/tavily_search/config.py
@@ -6,7 +6,7 @@
from typing import Any
-from pydantic import Field
+from pydantic import Field, SecretStr
from ogx.providers.utils.common.http import BaseToolRuntimeConfig
@@ -14,9 +14,9 @@
class TavilySearchToolConfig(BaseToolRuntimeConfig):
"""Configuration for the Tavily Search tool runtime."""
- api_key: str | None = Field(
+ api_key: SecretStr | None = Field(
default=None,
- description="The Tavily Search API Key",
+ description="The Tavily Search API Key. Can be overridden per-request via X-OGX-Provider-Data header.",
)
max_results: int = Field(
default=3,
diff --git a/src/ogx/providers/remote/tool_runtime/tavily_search/tavily_search.py b/src/ogx/providers/remote/tool_runtime/tavily_search/tavily_search.py
index 2c2cd6f38b0..5ad367eebca 100644
--- a/src/ogx/providers/remote/tool_runtime/tavily_search/tavily_search.py
+++ b/src/ogx/providers/remote/tool_runtime/tavily_search/tavily_search.py
@@ -46,16 +46,14 @@ async def register_toolgroup(self, toolgroup: ToolGroup) -> None:
async def unregister_toolgroup(self, toolgroup_id: str) -> None:
return
- def _get_api_key(self) -> str:
- if self.config.api_key:
- return self.config.api_key
+ def _get_api_key(self) -> str | None:
+ api_key = self.config.api_key.get_secret_value() if self.config.api_key else None
provider_data = self.get_request_provider_data()
- if provider_data is None or not provider_data.tavily_search_api_key:
- raise ValueError(
- 'Pass Search provider\'s API Key in the header X-OGX-Provider-Data as { "tavily_search_api_key": }'
- )
- return provider_data.tavily_search_api_key.get_secret_value()
+ if provider_data and provider_data.tavily_search_api_key:
+ api_key = provider_data.tavily_search_api_key.get_secret_value()
+
+ return api_key
async def list_runtime_tools(
self,
@@ -87,9 +85,10 @@ async def invoke_tool(
) -> ToolInvocationResult:
api_key = self._get_api_key()
request_body: dict[str, Any] = {
- "api_key": api_key,
"query": kwargs["query"],
}
+ if api_key:
+ request_body["api_key"] = api_key
allowed_domains = kwargs.get("allowed_domains")
if allowed_domains:
diff --git a/src/ogx/providers/remote/vector_io/elasticsearch/elasticsearch.py b/src/ogx/providers/remote/vector_io/elasticsearch/elasticsearch.py
index b783447f8db..96b63e09e6f 100644
--- a/src/ogx/providers/remote/vector_io/elasticsearch/elasticsearch.py
+++ b/src/ogx/providers/remote/vector_io/elasticsearch/elasticsearch.py
@@ -46,9 +46,10 @@
class ElasticsearchIndex(EmbeddingIndex):
"""Embedding index backed by an Elasticsearch index."""
- def __init__(self, client: AsyncElasticsearch, collection_name: str):
+ def __init__(self, client: AsyncElasticsearch, vector_store: VectorStore):
self.client = client
- self.collection_name = collection_name
+ self.collection_name = vector_store.identifier
+ self.dimension = vector_store.embedding_dimension
# Check if the rerank_params contains the following structure:
# {
@@ -106,15 +107,6 @@ def _convert_to_linear_params(self, reranker_params: dict[str, Any]) -> dict[str
}
async def initialize(self) -> None:
- # Elasticsearch collections (indexes) are created on-demand in add_chunks
- # If the index does not exist, it will be created in add_chunks.
- pass
-
- async def add_chunks(self, chunks: list[EmbeddedChunk]):
- """Adds chunks to the Elasticsearch index."""
- if not chunks:
- return
-
try:
await self.client.indices.create(
index=self.collection_name,
@@ -125,18 +117,26 @@ async def add_chunks(self, chunks: list[EmbeddedChunk]):
"chunk_id": {"type": "keyword"},
"metadata": {"type": "object"},
"chunk_metadata": {"type": "object"},
- "embedding": {"type": "dense_vector", "dims": len(chunks[0].embedding)},
+ "embedding": {"type": "dense_vector", "dims": self.dimension},
"embedding_dimension": {"type": "integer"},
"embedding_model": {"type": "keyword"},
}
}
},
)
+ log.info("Created Elasticsearch index", collection_name=self.collection_name)
except ApiError as e:
- if e.status_code != 400 or "resource_already_exists_exception" not in e.message:
+ if e.status_code == 400 and "resource_already_exists_exception" in e.message:
+ log.debug("Elasticsearch index already exists", collection_name=self.collection_name)
+ else:
log.error(f"Error creating Elasticsearch index {self.collection_name}: {e}")
raise
+ async def add_chunks(self, chunks: list[EmbeddedChunk]):
+ """Adds chunks to the Elasticsearch index."""
+ if not chunks:
+ return
+
actions = []
for chunk in chunks:
actions.append(
@@ -232,8 +232,7 @@ async def query_vector(
query={"knn": {"field": "embedding", "query_vector": embedding.tolist(), "k": k}},
min_score=score_threshold,
size=k,
- source={"exclude_vectors": False}, # Retrieve the embedding
- ignore_unavailable=True, # In case the index does not exist
+ source={"exclude_vectors": False},
)
except Exception as e:
log.error(f"Error performing vector query on Elasticsearch index {self.collection_name}: {e}")
@@ -359,8 +358,7 @@ async def query_hybrid(
size=k,
retriever=retriever,
min_score=score_threshold,
- source={"exclude_vectors": False}, # Retrieve the embedding
- ignore_unavailable=True, # In case the index does not exist
+ source={"exclude_vectors": False},
)
except Exception as e:
log.error(f"Error performing hybrid query on Elasticsearch index {self.collection_name}: {e}")
@@ -414,9 +412,9 @@ async def initialize(self) -> None:
for vector_store_data in stored_vector_stores:
vector_store = VectorStore.model_validate_json(vector_store_data)
- index = VectorStoreWithIndex(
- vector_store, ElasticsearchIndex(self.client, vector_store.identifier), self.inference_api
- )
+ es_index = ElasticsearchIndex(self.client, vector_store)
+ await es_index.initialize()
+ index = VectorStoreWithIndex(vector_store, es_index, self.inference_api)
self.cache[vector_store.identifier] = index
await self.initialize_openai_vector_stores()
@@ -430,9 +428,11 @@ async def register_vector_store(self, vector_store: VectorStore) -> None:
key = f"{VECTOR_DBS_PREFIX}{vector_store.identifier}"
await self.kvstore.set(key=key, value=vector_store.model_dump_json())
+ es_index = ElasticsearchIndex(self.client, vector_store)
+ await es_index.initialize()
index = VectorStoreWithIndex(
vector_store=vector_store,
- index=ElasticsearchIndex(self.client, vector_store.identifier),
+ index=es_index,
inference_api=self.inference_api,
)
@@ -450,16 +450,20 @@ async def _get_and_cache_vector_store_index(self, vector_store_id: str) -> Vecto
if vector_store_id in self.cache:
return self.cache[vector_store_id]
- if self.vector_store_table is None:
- raise ValueError(f"Vector DB not found {vector_store_id}")
+ if self.kvstore is None:
+ raise RuntimeError("KVStore not initialized. Call initialize() before using vector stores.")
- vector_store = await self.vector_store_table.get_vector_store(vector_store_id)
- if not vector_store:
+ key = f"{VECTOR_DBS_PREFIX}{vector_store_id}"
+ vector_store_data = await self.kvstore.get(key)
+ if not vector_store_data:
raise VectorStoreNotFoundError(vector_store_id)
+ vector_store = VectorStore.model_validate_json(vector_store_data)
+ es_index = ElasticsearchIndex(client=self.client, vector_store=vector_store)
+ await es_index.initialize()
index = VectorStoreWithIndex(
vector_store=vector_store,
- index=ElasticsearchIndex(client=self.client, collection_name=vector_store.identifier),
+ index=es_index,
inference_api=self.inference_api,
)
self.cache[vector_store_id] = index
diff --git a/src/ogx/providers/remote/vector_io/infinispan/infinispan.py b/src/ogx/providers/remote/vector_io/infinispan/infinispan.py
index c51f5508e63..adf3351ee45 100644
--- a/src/ogx/providers/remote/vector_io/infinispan/infinispan.py
+++ b/src/ogx/providers/remote/vector_io/infinispan/infinispan.py
@@ -88,7 +88,7 @@ async def initialize(self):
if response.status_code != 404:
# Unexpected error
- log.error(f"Failed to check cache existence: {response.status_code} - {response.text}")
+ log.error("Failed to check cache existence", status_code=response.status_code)
response.raise_for_status()
# Cache doesn't exist, register schema first then create cache
@@ -112,7 +112,7 @@ async def initialize(self):
)
if create_response.status_code not in [200, 204]:
- log.error(f"Failed to create cache: {create_response.status_code} - {create_response.text}")
+ log.error("Failed to create cache", status_code=create_response.status_code)
create_response.raise_for_status()
log.info(f"Cache '{self.cache_name}' created successfully")
@@ -134,7 +134,7 @@ async def _register_protobuf_schema(self):
)
if schema_response.status_code not in [200, 204]:
- log.error(f"Failed to register Protobuf schema: {schema_response.status_code} - {schema_response.text}")
+ log.error("Failed to register Protobuf schema", status_code=schema_response.status_code)
schema_response.raise_for_status()
log.info(f"Protobuf schema '{schema_name}' registered successfully")
@@ -174,7 +174,7 @@ async def add_chunks(self, chunks: list[EmbeddedChunk]):
}
# Insert into Infinispan cache
- log.debug(f"PUT request to insert chunk {key}: {vector_item}")
+ log.debug("PUT request to insert chunk", chunk_id=key, vector_item=vector_item)
response = await self.client.put(
f"{self.base_url}/rest/v3/caches/{self.cache_name}/entries/{key}",
json=vector_item,
@@ -182,7 +182,7 @@ async def add_chunks(self, chunks: list[EmbeddedChunk]):
)
if response.status_code not in [200, 204]:
- log.error(f"Failed to insert chunk {key}: {response.status_code} - {response.text}")
+ log.error("Failed to insert chunk", chunk_id=key, status_code=response.status_code)
response.raise_for_status()
log.info(f"Successfully inserted {len(chunks)} chunks")
@@ -210,7 +210,7 @@ async def delete_chunks(self, chunks_for_deletion: list[ChunkForDeletion]) -> No
if response.status_code not in [200, 204, 404]:
# 404 is acceptable - chunk may not exist
- log.error(f"Failed to delete chunk {key}: {response.status_code} - {response.text}")
+ log.error("Failed to delete chunk", chunk_id=key, status_code=response.status_code)
response.raise_for_status()
log.info(f"Successfully deleted {len(chunks_for_deletion)} chunks")
@@ -253,7 +253,7 @@ async def query_vector(
)
if response.status_code != 200:
- log.error(f"Vector search query failed: {response.status_code} - {response.text}")
+ log.error("Vector search query failed", status_code=response.status_code)
response.raise_for_status()
# Parse search results
@@ -281,7 +281,12 @@ async def query_vector(
embedding_model = hit_data.get("embeddingModel", "unknown")
if not chunk_id or not float_vector:
- log.warning(f"Skipping incomplete hit: {hit_data}")
+ log.warning(
+ "Skipping incomplete hit",
+ hit_id=hit_data.get("id"),
+ has_text=bool(hit_data.get("text")),
+ has_vector=bool(hit_data.get("floatVector")),
+ )
continue
# Deserialize metadata
@@ -352,7 +357,7 @@ async def query_keyword(
if filters is not None:
raise NotImplementedError("Infinispan provider does not yet support native filtering")
- log.info(f"Performing keyword search in cache '{self.cache_name}' with query: {query_string}")
+ log.debug("Performing keyword search", cache_name=self.cache_name, query=query_string)
# Build Ickle query to search the text field
# The text field has @Keyword annotation, so it's indexed for full-text search
@@ -369,7 +374,7 @@ async def query_keyword(
)
if response.status_code != 200:
- log.error(f"Search query failed: {response.status_code} - {response.text}")
+ log.error("Search query failed", status_code=response.status_code)
response.raise_for_status()
# Parse search results
@@ -397,7 +402,12 @@ async def query_keyword(
embedding_model = hit_data.get("embeddingModel", "unknown")
if not chunk_id or not float_vector:
- log.warning(f"Skipping incomplete hit: {hit_data}")
+ log.warning(
+ "Skipping incomplete hit",
+ hit_id=hit_data.get("id"),
+ has_text=bool(hit_data.get("text")),
+ has_vector=bool(hit_data.get("floatVector")),
+ )
continue
# Deserialize metadata
@@ -428,8 +438,11 @@ async def query_keyword(
try:
chunk = load_embedded_chunk_with_backward_compat(chunk_dict)
- log.info(
- f"Hit content - ID: {chunk_id}, Text: {text[:100]}{'...' if len(text) > 100 else ''}, Vector dim: {len(float_vector)}"
+ log.debug(
+ "Loaded search hit",
+ chunk_id=chunk_id,
+ text_preview=text[:100],
+ vector_dimension=len(float_vector),
)
except Exception as e:
log.error(f"Failed to load chunk {chunk_id}: {e}")
@@ -532,7 +545,7 @@ async def delete(self):
response = await self.client.delete(f"{self.base_url}/rest/v3/caches/{self.cache_name}")
if response.status_code not in [200, 204]:
- log.error(f"Failed to delete cache '{self.cache_name}': {response.status_code} - {response.text}")
+ log.error("Failed to delete cache", cache_name=self.cache_name, status_code=response.status_code)
response.raise_for_status()
log.info(f"Cache '{self.cache_name}' deleted successfully")
diff --git a/src/ogx/providers/remote/vector_io/milvus/milvus.py b/src/ogx/providers/remote/vector_io/milvus/milvus.py
index 6331e38ed99..0ccb837e268 100644
--- a/src/ogx/providers/remote/vector_io/milvus/milvus.py
+++ b/src/ogx/providers/remote/vector_io/milvus/milvus.py
@@ -76,72 +76,65 @@ class MilvusIndex(EmbeddingIndex):
def __init__(
self,
client: MilvusClient,
- collection_name: str,
+ vector_store: VectorStore,
consistency_level: str = "Strong",
kvstore: KVStore | None = None,
use_native_hybrid: bool = False,
):
self.client = client
- self.collection_name = sanitize_collection_name(collection_name)
+ self.collection_name = sanitize_collection_name(vector_store.identifier)
self.consistency_level = consistency_level
self.kvstore = kvstore
self.use_native_hybrid = use_native_hybrid
-
- async def _collection_exists(self) -> bool:
- return await asyncio.to_thread(self.client.has_collection, self.collection_name)
+ self.dimension = vector_store.embedding_dimension
async def initialize(self):
- # MilvusIndex does not require explicit initialization
- # TODO: could move collection creation into initialization but it is not really necessary
- pass
+ if await asyncio.to_thread(self.client.has_collection, self.collection_name):
+ return
+
+ # Create schema for vector search
+ schema = self.client.create_schema()
+ schema.add_field(field_name="chunk_id", datatype=DataType.VARCHAR, is_primary=True, max_length=100)
+ schema.add_field(
+ field_name="content",
+ datatype=DataType.VARCHAR,
+ max_length=65535,
+ enable_analyzer=True,
+ )
+ schema.add_field(field_name="vector", datatype=DataType.FLOAT_VECTOR, dim=self.dimension)
+ schema.add_field(field_name="chunk_content", datatype=DataType.JSON)
+ schema.add_field(field_name="sparse", datatype=DataType.SPARSE_FLOAT_VECTOR)
+
+ # Create indexes
+ index_params = self.client.prepare_index_params()
+ index_params.add_index(field_name="vector", index_type="FLAT", metric_type="COSINE")
+ index_params.add_index(field_name="sparse", index_type="SPARSE_INVERTED_INDEX", metric_type="BM25")
+
+ # Add BM25 function for full-text search
+ bm25_function = Function(
+ name="text_bm25_emb",
+ input_field_names=["content"],
+ output_field_names=["sparse"],
+ function_type=FunctionType.BM25,
+ )
+ schema.add_function(bm25_function)
+
+ logger.info("Creating Milvus collection", collection_name=self.collection_name)
+ await asyncio.to_thread(
+ self.client.create_collection,
+ self.collection_name,
+ schema=schema,
+ index_params=index_params,
+ consistency_level=self.consistency_level,
+ )
async def delete(self):
- if await asyncio.to_thread(self.client.has_collection, self.collection_name):
- await asyncio.to_thread(self.client.drop_collection, collection_name=self.collection_name)
+ await asyncio.to_thread(self.client.drop_collection, collection_name=self.collection_name)
async def add_chunks(self, chunks: list[EmbeddedChunk]):
if not chunks:
return
- if not await asyncio.to_thread(self.client.has_collection, self.collection_name):
- logger.info("Creating new collection with nullable sparse field", collection_name=self.collection_name)
- # Create schema for vector search
- schema = self.client.create_schema()
- schema.add_field(field_name="chunk_id", datatype=DataType.VARCHAR, is_primary=True, max_length=100)
- schema.add_field(
- field_name="content",
- datatype=DataType.VARCHAR,
- max_length=65535,
- enable_analyzer=True, # Enable text analysis for BM25
- )
- schema.add_field(field_name="vector", datatype=DataType.FLOAT_VECTOR, dim=len(chunks[0].embedding))
- schema.add_field(field_name="chunk_content", datatype=DataType.JSON)
- # Add sparse vector field for BM25 (required by the function)
- schema.add_field(field_name="sparse", datatype=DataType.SPARSE_FLOAT_VECTOR)
-
- # Create indexes
- index_params = self.client.prepare_index_params()
- index_params.add_index(field_name="vector", index_type="FLAT", metric_type="COSINE")
- # Add index for sparse field (required by BM25 function)
- index_params.add_index(field_name="sparse", index_type="SPARSE_INVERTED_INDEX", metric_type="BM25")
-
- # Add BM25 function for full-text search
- bm25_function = Function(
- name="text_bm25_emb",
- input_field_names=["content"],
- output_field_names=["sparse"],
- function_type=FunctionType.BM25,
- )
- schema.add_function(bm25_function)
-
- await asyncio.to_thread(
- self.client.create_collection,
- self.collection_name,
- schema=schema,
- index_params=index_params,
- consistency_level=self.consistency_level,
- )
-
data = []
for chunk in chunks:
data.append(
@@ -227,9 +220,6 @@ def _translate_compound_filter(self, filter_obj: CompoundFilter) -> str:
async def query_vector(
self, embedding: NDArray, k: int, score_threshold: float, filters: Any = None
) -> QueryChunksResponse:
- if not await self._collection_exists():
- return QueryChunksResponse(chunks=[], scores=[])
-
# Translate filters to Milvus expression format
filter_expr = self._translate_filters(filters) if filters else None
@@ -238,7 +228,7 @@ async def query_vector(
"data": [embedding],
"anns_field": "vector",
"limit": k,
- "output_fields": ["*"],
+ "output_fields": ["chunk_content"],
}
# Only apply radius threshold if score_threshold is meaningful
@@ -260,9 +250,6 @@ async def query_keyword(
"""
Perform BM25-based keyword search using Milvus's built-in full-text search.
"""
- if not await self._collection_exists():
- return QueryChunksResponse(chunks=[], scores=[])
-
try:
# Translate filters to Milvus expression format
filter_expr = self._translate_filters(filters) if filters else None
@@ -308,9 +295,6 @@ async def _fallback_keyword_search(self, query_string: str, k: int, score_thresh
"""
Fallback to simple text search when BM25 search is not available.
"""
- if not await self._collection_exists():
- return QueryChunksResponse(chunks=[], scores=[])
-
# Simple text search using content field
search_res = await asyncio.to_thread(
self.client.query,
@@ -358,9 +342,6 @@ async def _query_hybrid_native(
Uses Milvus's hybrid_search method which combines vector search and
BM25 search server-side with configurable reranking strategies.
"""
- if not await self._collection_exists():
- return QueryChunksResponse(chunks=[], scores=[])
-
search_requests = []
search_requests.append(
@@ -453,9 +434,6 @@ async def _query_hybrid_in_memory(
async def delete_chunks(self, chunks_for_deletion: list[ChunkForDeletion]) -> None:
"""Remove a chunk from the Milvus collection."""
- if not await self._collection_exists():
- return
-
chunk_ids = [c.chunk_id for c in chunks_for_deletion]
try:
# Use IN clause with square brackets and single quotes for VARCHAR field
@@ -499,6 +477,16 @@ async def initialize(self) -> None:
self.metadata_store = await authorized_sqlstore(self.config.metadata_store, self._policy)
+ if isinstance(self.config, RemoteMilvusVectorIOConfig):
+ logger.info("Connecting to Milvus server at", uri=self.config.uri)
+ self.client = MilvusClient(
+ **self.config.model_dump(exclude_none=True, exclude={"persistence", "metadata_store"})
+ )
+ else:
+ logger.info("Connecting to Milvus Lite at", db_path=self.config.db_path)
+ uri = os.path.expanduser(self.config.db_path)
+ self.client = MilvusClient(uri=uri)
+
start_key = VECTOR_DBS_PREFIX
end_key = f"{VECTOR_DBS_PREFIX}\xff"
stored_vector_stores = await self.kvstore.values_in_range(start_key, end_key)
@@ -506,29 +494,20 @@ async def initialize(self) -> None:
use_native_hybrid = isinstance(self.config, RemoteMilvusVectorIOConfig)
for vector_store_data in stored_vector_stores:
vector_store = VectorStore.model_validate_json(vector_store_data)
+ milvus_index = MilvusIndex(
+ client=self.client,
+ vector_store=vector_store,
+ consistency_level=self.config.consistency_level,
+ kvstore=self.kvstore,
+ use_native_hybrid=use_native_hybrid,
+ )
+ await milvus_index.initialize()
index = VectorStoreWithIndex(
vector_store,
- index=MilvusIndex(
- client=self.client,
- collection_name=vector_store.identifier,
- consistency_level=self.config.consistency_level,
- kvstore=self.kvstore,
- use_native_hybrid=use_native_hybrid,
- ),
+ index=milvus_index,
inference_api=self.inference_api,
)
self.cache[vector_store.identifier] = index
- if isinstance(self.config, RemoteMilvusVectorIOConfig):
- logger.info("Connecting to Milvus server at", uri=self.config.uri)
- self.client = MilvusClient(
- **self.config.model_dump(exclude_none=True, exclude={"persistence", "metadata_store"})
- )
- else:
- logger.info("Connecting to Milvus Lite at", db_path=self.config.db_path)
- uri = os.path.expanduser(self.config.db_path)
- self.client = MilvusClient(uri=uri)
-
- # Load existing OpenAI vector stores into the in-memory cache
await self.initialize_openai_vector_stores()
async def shutdown(self) -> None:
@@ -542,14 +521,16 @@ async def register_vector_store(self, vector_store: VectorStore) -> None:
consistency_level = self.config.consistency_level
else:
consistency_level = "Strong"
+ milvus_index = MilvusIndex(
+ self.client,
+ vector_store,
+ consistency_level=consistency_level,
+ use_native_hybrid=use_native_hybrid,
+ )
+ await milvus_index.initialize()
index = VectorStoreWithIndex(
vector_store=vector_store,
- index=MilvusIndex(
- self.client,
- vector_store.identifier,
- consistency_level=consistency_level,
- use_native_hybrid=use_native_hybrid,
- ),
+ index=milvus_index,
inference_api=self.inference_api,
)
@@ -570,14 +551,16 @@ async def _get_and_cache_vector_store_index(self, vector_store_id: str) -> Vecto
vector_store = VectorStore.model_validate_json(vector_store_data)
use_native_hybrid = isinstance(self.config, RemoteMilvusVectorIOConfig)
+ milvus_index = MilvusIndex(
+ client=self.client,
+ vector_store=vector_store,
+ kvstore=self.kvstore,
+ use_native_hybrid=use_native_hybrid,
+ )
+ await milvus_index.initialize()
index = VectorStoreWithIndex(
vector_store=vector_store,
- index=MilvusIndex(
- client=self.client,
- collection_name=vector_store.identifier,
- kvstore=self.kvstore,
- use_native_hybrid=use_native_hybrid,
- ),
+ index=milvus_index,
inference_api=self.inference_api,
)
self.cache[vector_store_id] = index
diff --git a/src/ogx/providers/remote/vector_io/pgvector/pgvector.py b/src/ogx/providers/remote/vector_io/pgvector/pgvector.py
index 2d56613066c..41a6b26b970 100644
--- a/src/ogx/providers/remote/vector_io/pgvector/pgvector.py
+++ b/src/ogx/providers/remote/vector_io/pgvector/pgvector.py
@@ -794,6 +794,39 @@ async def _ensure_pool(self) -> asyncpg.Pool:
self.pool = None
self._pool_initialized = False
+ # Ensure the vector extension exists before creating the pool.
+ # The pool's init callback (register_vector) requires the extension
+ # to be present — without this, it raises ValueError on first connect.
+ conn = await asyncpg.connect(
+ host=self.config.host,
+ port=self.config.port,
+ database=self.config.db,
+ user=self.config.user,
+ password=self.config.password.get_secret_value() if self.config.password else None,
+ )
+ try:
+ version = await check_extension_version(conn)
+ if version:
+ log.info("Vector extension version", version=version)
+ else:
+ await create_vector_extension(conn)
+
+ try:
+ await conn.execute("CREATE EXTENSION IF NOT EXISTS pg_stat_statements")
+ except asyncpg.PostgresError:
+ log.debug("pg_stat_statements not available, skipping")
+
+ await conn.execute(
+ """
+ CREATE TABLE IF NOT EXISTS metadata_store (
+ key TEXT PRIMARY KEY,
+ data JSONB
+ )
+ """
+ )
+ finally:
+ await conn.close()
+
pool = await asyncpg.create_pool(
host=self.config.host,
port=self.config.port,
@@ -807,33 +840,7 @@ async def _ensure_pool(self) -> asyncpg.Pool:
init=self._init_connection,
reset=self._reset_connection,
)
-
- try:
- if not self._pool_initialized:
- async with pool.acquire() as conn:
- version = await check_extension_version(conn)
- if version:
- log.info("Vector extension version", version=version)
- else:
- await create_vector_extension(conn)
-
- try:
- await conn.execute("CREATE EXTENSION IF NOT EXISTS pg_stat_statements")
- except asyncpg.PostgresError:
- log.debug("pg_stat_statements not available, skipping")
-
- await conn.execute(
- """
- CREATE TABLE IF NOT EXISTS metadata_store (
- key TEXT PRIMARY KEY,
- data JSONB
- )
- """
- )
- self._pool_initialized = True
- except Exception:
- await pool.close()
- raise
+ self._pool_initialized = True
self.pool = pool
return self.pool
diff --git a/src/ogx/providers/remote/vector_io/qdrant/qdrant.py b/src/ogx/providers/remote/vector_io/qdrant/qdrant.py
index 34685850a8e..0e2d7e779d7 100644
--- a/src/ogx/providers/remote/vector_io/qdrant/qdrant.py
+++ b/src/ogx/providers/remote/vector_io/qdrant/qdrant.py
@@ -66,37 +66,35 @@ def convert_id(_id: str) -> str:
class QdrantIndex(EmbeddingIndex):
"""Embedding index backed by a Qdrant collection."""
- def __init__(self, client: AsyncQdrantClient, collection_name: str):
+ def __init__(self, client: AsyncQdrantClient, vector_store: VectorStore):
self.client = client
- self.collection_name = collection_name
+ self.collection_name = vector_store.identifier
+ self.dimension = vector_store.embedding_dimension
async def initialize(self) -> None:
- # Qdrant collections are created on-demand in add_chunks
- # If the collection does not exist, it will be created in add_chunks.
- pass
+ if await self.client.collection_exists(self.collection_name):
+ return
+
+ await self.client.create_collection(
+ self.collection_name,
+ vectors_config=models.VectorParams(size=self.dimension, distance=models.Distance.COSINE),
+ )
+ await self.client.create_payload_index(
+ collection_name=self.collection_name,
+ field_name="chunk_content.content",
+ field_schema=models.TextIndexParams(
+ type="text",
+ tokenizer=models.TokenizerType.WORD,
+ min_token_len=2,
+ max_token_len=20,
+ lowercase=True,
+ ),
+ )
async def add_chunks(self, chunks: list[EmbeddedChunk]):
if not chunks:
return
- if not await self.client.collection_exists(self.collection_name):
- await self.client.create_collection(
- self.collection_name,
- vectors_config=models.VectorParams(size=len(chunks[0].embedding), distance=models.Distance.COSINE),
- )
- # Create text index for keyword search functionality
- await self.client.create_payload_index(
- collection_name=self.collection_name,
- field_name="chunk_content.content",
- field_schema=models.TextIndexParams(
- type="text",
- tokenizer=models.TokenizerType.WORD,
- min_token_len=2,
- max_token_len=20,
- lowercase=True,
- ),
- )
-
points = []
for chunk in chunks:
chunk_id = chunk.chunk_id
@@ -129,7 +127,6 @@ async def delete_chunks(self, chunks_for_deletion: list[ChunkForDeletion]) -> No
async def query_vector(
self, embedding: NDArray, k: int, score_threshold: float, filters: Any = None
) -> QueryChunksResponse:
- # Filters are not yet implemented for Qdrant provider
if filters is not None:
raise NotImplementedError("Qdrant provider does not yet support native filtering")
@@ -322,7 +319,7 @@ async def query_hybrid(
return QueryChunksResponse(chunks=chunks, scores=scores)
async def delete(self):
- await self.client.delete_collection(collection_name=self.collection_name)
+ await self.client.delete_collection(collection_name=self.collection_name, timeout=30)
class QdrantVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorStoresProtocolPrivate):
@@ -362,9 +359,9 @@ async def initialize(self) -> None:
for vector_store_data in stored_vector_stores:
vector_store = VectorStore.model_validate_json(vector_store_data)
- index = VectorStoreWithIndex(
- vector_store, QdrantIndex(self.client, vector_store.identifier), self.inference_api
- )
+ qdrant_index = QdrantIndex(self.client, vector_store)
+ await qdrant_index.initialize()
+ index = VectorStoreWithIndex(vector_store, qdrant_index, self.inference_api)
self.cache[vector_store.identifier] = index
await self.initialize_openai_vector_stores()
@@ -379,9 +376,11 @@ async def register_vector_store(self, vector_store: VectorStore) -> None:
key = f"{VECTOR_DBS_PREFIX}{vector_store.identifier}"
await self.kvstore.set(key=key, value=vector_store.model_dump_json())
+ qdrant_index = QdrantIndex(self.client, vector_store)
+ await qdrant_index.initialize()
index = VectorStoreWithIndex(
vector_store=vector_store,
- index=QdrantIndex(self.client, vector_store.identifier),
+ index=qdrant_index,
inference_api=self.inference_api,
)
@@ -410,9 +409,11 @@ async def _get_and_cache_vector_store_index(self, vector_store_id: str) -> Vecto
raise VectorStoreNotFoundError(vector_store_id)
vector_store = VectorStore.model_validate_json(vector_store_data)
+ qdrant_index = QdrantIndex(client=self.client, vector_store=vector_store)
+ await qdrant_index.initialize()
index = VectorStoreWithIndex(
vector_store=vector_store,
- index=QdrantIndex(client=self.client, collection_name=vector_store.identifier),
+ index=qdrant_index,
inference_api=self.inference_api,
)
self.cache[vector_store_id] = index
diff --git a/src/ogx/providers/remote/vector_io/weaviate/weaviate.py b/src/ogx/providers/remote/vector_io/weaviate/weaviate.py
index b1c2697b9b9..28c103134cd 100644
--- a/src/ogx/providers/remote/vector_io/weaviate/weaviate.py
+++ b/src/ogx/providers/remote/vector_io/weaviate/weaviate.py
@@ -131,7 +131,7 @@ async def query_vector(
chunk_dict = json.loads(chunk_json)
chunk = load_embedded_chunk_with_backward_compat(chunk_dict)
except Exception:
- log.exception(f"Failed to parse document: {chunk_json}")
+ log.exception("Failed to parse document", chunk_content_length=len(chunk_json))
continue
if doc.metadata.distance is None:
@@ -201,7 +201,7 @@ async def query_keyword(
chunk_dict = json.loads(chunk_json)
chunk = load_embedded_chunk_with_backward_compat(chunk_dict)
except Exception:
- log.exception(f"Failed to parse document: {chunk_json}")
+ log.exception("Failed to parse document", chunk_content_length=len(chunk_json))
continue
score = doc.metadata.score if doc.metadata.score is not None else 0.0
@@ -275,7 +275,7 @@ async def query_hybrid(
chunk_dict = json.loads(chunk_json)
chunk = load_embedded_chunk_with_backward_compat(chunk_dict)
except Exception:
- log.exception(f"Failed to parse document: {chunk_json}")
+ log.exception("Failed to parse document", chunk_content_length=len(chunk_json))
continue
score = doc.metadata.score if doc.metadata.score is not None else 0.0
diff --git a/src/ogx/providers/utils/files/response.py b/src/ogx/providers/utils/files/response.py
new file mode 100644
index 00000000000..67dd5a4d08e
--- /dev/null
+++ b/src/ogx/providers/utils/files/response.py
@@ -0,0 +1,30 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Any
+
+from fastapi import Response
+from fastapi.responses import StreamingResponse
+
+
+async def response_body_bytes(response: Response | Any) -> bytes:
+ """Read bytes from regular or streaming FastAPI responses."""
+ body = getattr(response, "body", None)
+ if body is not None:
+ return bytes(body)
+
+ if isinstance(response, StreamingResponse):
+ chunks: list[bytes] = []
+ async for chunk in response.body_iterator:
+ if isinstance(chunk, str):
+ chunks.append(chunk.encode("utf-8"))
+ elif isinstance(chunk, memoryview):
+ chunks.append(bytes(chunk))
+ else:
+ chunks.append(chunk)
+ return b"".join(chunks)
+
+ raise ValueError("Failed to read response body bytes")
diff --git a/src/ogx/providers/utils/memory/openai_vector_store_mixin.py b/src/ogx/providers/utils/memory/openai_vector_store_mixin.py
index e68130a3391..9df91a800c1 100644
--- a/src/ogx/providers/utils/memory/openai_vector_store_mixin.py
+++ b/src/ogx/providers/utils/memory/openai_vector_store_mixin.py
@@ -17,9 +17,12 @@
from fastapi import Body, HTTPException
-from ogx.core.datatypes import VectorStoresConfig
+from ogx.core.access_control.datatypes import Action
+from ogx.core.datatypes import TenancyMode, VectorStoresConfig
from ogx.core.id_generation import generate_object_id
+from ogx.core.storage.sqlstore.authorized_sqlstore import get_default_tenancy_config
from ogx.log import get_logger
+from ogx.providers.utils.files.response import response_body_bytes
from ogx.providers.utils.inference.prompt_adapter import (
interleaved_content_as_str,
)
@@ -221,6 +224,17 @@ async def _fetch_one_metadata_row_unfiltered(self, table: str, **kwargs: Any) ->
rows = await self._fetch_all_metadata_rows_unfiltered(table=table, limit=1, **kwargs)
return rows[0] if rows else None
+ def _migration_tenant_data(self) -> tuple[dict[str, Any], list[str]]:
+ tenancy_config = get_default_tenancy_config()
+ if tenancy_config.mode == TenancyMode.DISABLED:
+ return {}, []
+ if tenancy_config.default_tenant_id:
+ return {"tenant_id": tenancy_config.default_tenant_id}, ["tenant_id"]
+ raise ValueError(
+ "Failed to migrate vector store metadata: server.tenancy.default_tenant_id is required when "
+ f"migrating legacy KVStore data with tenancy mode '{tenancy_config.mode.value}'"
+ )
+
async def _migrate_kvstore_to_sql(self) -> None:
"""Migrate vector store metadata from KVStore to SQL on first run after upgrade.
@@ -251,6 +265,7 @@ async def _migrate_kvstore_to_sql(self) -> None:
if not stores_data:
await self.kvstore.set(key=OPENAI_VECTOR_STORES_SQL_MIGRATION_KEY, value="1")
return
+ tenant_data, tenant_update_columns = self._migration_tenant_data()
migrated_stores = 0
migrated_files = 0
@@ -272,9 +287,10 @@ async def _migrate_kvstore_to_sql(self) -> None:
"store_data": info,
"owner_principal": "",
"access_attributes": None,
+ **tenant_data,
},
conflict_columns=["id"],
- update_columns=["store_data"],
+ update_columns=["store_data", *tenant_update_columns],
)
migrated_stores += 1
@@ -298,9 +314,10 @@ async def _migrate_kvstore_to_sql(self) -> None:
"file_data": file_info,
"owner_principal": "",
"access_attributes": None,
+ **tenant_data,
},
conflict_columns=["id"],
- update_columns=["store_id", "file_id", "file_data"],
+ update_columns=["store_id", "file_id", "file_data", *tenant_update_columns],
)
migrated_files += 1
@@ -318,9 +335,10 @@ async def _migrate_kvstore_to_sql(self) -> None:
"chunk_data": chunk,
"owner_principal": "",
"access_attributes": None,
+ **tenant_data,
},
conflict_columns=["id"],
- update_columns=["store_id", "file_id", "chunk_index", "chunk_data"],
+ update_columns=["store_id", "file_id", "chunk_index", "chunk_data", *tenant_update_columns],
)
migrated_chunks += 1
@@ -339,9 +357,10 @@ async def _migrate_kvstore_to_sql(self) -> None:
"expires_at": batch_info.get("expires_at", 0),
"owner_principal": "",
"access_attributes": None,
+ **tenant_data,
},
conflict_columns=["id"],
- update_columns=["store_id", "batch_data", "expires_at"],
+ update_columns=["store_id", "batch_data", "expires_at", *tenant_update_columns],
)
migrated_batches += 1
@@ -424,6 +443,38 @@ async def _load_openai_vector_stores(self) -> dict[str, dict[str, Any]]:
stores[info["id"]] = info
return stores
+ async def _get_authorized_openai_vector_store(
+ self,
+ vector_store_id: str,
+ action: Action = Action.READ,
+ ) -> dict[str, Any]:
+ """Return vector store metadata visible to the current request user."""
+ if self.metadata_store:
+ row = await self.metadata_store.fetch_one(
+ table=TABLE_VECTOR_STORES,
+ where={"id": vector_store_id},
+ action=action,
+ )
+ if not row:
+ raise VectorStoreNotFoundError(vector_store_id)
+ store_info = cast(dict[str, Any], row["store_data"])
+ self.openai_vector_stores[vector_store_id] = store_info
+ return store_info
+
+ if vector_store_id not in self.openai_vector_stores:
+ raise VectorStoreNotFoundError(vector_store_id)
+ return self.openai_vector_stores[vector_store_id]
+
+ async def _list_authorized_openai_vector_stores(self) -> list[dict[str, Any]]:
+ if self.metadata_store:
+ rows = await self.metadata_store.fetch_all(table=TABLE_VECTOR_STORES)
+ stores = [row["store_data"] for row in rows.data]
+ for store_info in stores:
+ self.openai_vector_stores[store_info["id"]] = store_info
+ return stores
+
+ return list(self.openai_vector_stores.values())
+
async def _update_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None:
"""Update vector store metadata in persistent storage."""
if self.metadata_store:
@@ -727,6 +778,11 @@ async def initialize_openai_vector_stores(self) -> None:
"Ensure a 'files' provider is configured if file operations are needed."
)
policy = getattr(self, "_policy", [])
+ if get_default_tenancy_config().mode == TenancyMode.MULTI and not self.metadata_store:
+ raise ValueError(
+ "Failed to initialize vector store provider: metadata_store is required when tenancy mode is 'multi'. "
+ "Configure storage.stores.vector_stores in your server config."
+ )
if policy and not self.metadata_store:
raise ValueError(
"Failed to initialize vector store provider: metadata_store is required when access control "
@@ -922,8 +978,8 @@ async def openai_list_vector_stores(
limit = min(limit or 20, MAX_PAGINATION_LIMIT)
order = order or "desc"
- # Get all vector stores
- all_stores = list(self.openai_vector_stores.values())
+ # Get all vector stores visible to the current request user.
+ all_stores = await self._list_authorized_openai_vector_stores()
# Sort by created_at
reverse_order = order == "desc"
@@ -964,10 +1020,7 @@ async def openai_retrieve_vector_store(
vector_store_id: str,
) -> VectorStoreObject:
"""Retrieves a vector store."""
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
-
- store_info = self.openai_vector_stores[vector_store_id]
+ store_info = await self._get_authorized_openai_vector_store(vector_store_id)
return VectorStoreObject(**store_info)
async def openai_update_vector_store(
@@ -976,10 +1029,7 @@ async def openai_update_vector_store(
request: OpenAIUpdateVectorStoreRequest,
) -> VectorStoreObject:
"""Modifies a vector store."""
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
-
- store_info = self.openai_vector_stores[vector_store_id].copy()
+ store_info = (await self._get_authorized_openai_vector_store(vector_store_id, Action.UPDATE)).copy()
# Update fields if provided
if request.name is not None:
@@ -1009,8 +1059,7 @@ async def openai_delete_vector_store(
vector_store_id: str,
) -> VectorStoreDeleteResponse:
"""Delete a vector store."""
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
+ await self._get_authorized_openai_vector_store(vector_store_id, Action.DELETE)
# Delete from persistent storage (provider-specific)
await self._delete_openai_vector_store_from_storage(vector_store_id)
@@ -1046,8 +1095,7 @@ async def openai_search_vector_store(
if request.search_mode not in valid_modes:
raise ValueError(f"search_mode must be one of {valid_modes}, got {request.search_mode}")
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
+ await self._get_authorized_openai_vector_store(vector_store_id)
if isinstance(request.query, list):
search_query = " ".join(request.query)
@@ -1121,14 +1169,8 @@ async def openai_search_vector_store(
)
except Exception as e:
- # Log the error and return empty results
- logger.error("Error searching vector store", vector_store_id=vector_store_id, error=str(e))
- return VectorStoreSearchResponsePage(
- search_query=request.query if isinstance(request.query, list) else [request.query],
- data=[],
- has_more=False,
- next_page=None,
- )
+ logger.error("Failed to search vector store", vector_store_id=vector_store_id, error=str(e))
+ raise
def _build_reranker_params(
self,
@@ -1223,11 +1265,8 @@ async def openai_attach_file_to_vector_store(
request: OpenAIAttachFileRequest,
) -> VectorStoreFileObject:
file_id = request.file_id
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
-
# Check if file is already attached to this vector store
- store_info = self.openai_vector_stores[vector_store_id]
+ store_info = await self._get_authorized_openai_vector_store(vector_store_id, Action.UPDATE)
if file_id in store_info["file_ids"]:
logger.warning(
"File is already attached to vector store, skipping", file_id=file_id, vector_store_id=vector_store_id
@@ -1319,7 +1358,7 @@ async def openai_attach_file_to_vector_store(
content_response = await self.files_api.openai_retrieve_file_content(
RetrieveFileContentRequest(file_id=file_id)
)
- full_content = content_from_data_and_mime_type(bytes(content_response.body), mime_type)
+ full_content = content_from_data_and_mime_type(await response_body_bytes(content_response), mime_type)
await self._execute_contextual_chunk_transformation(chunks, full_content, chunking_strategy.contextual)
if not chunks:
vector_store_file_object.status = "failed"
@@ -1429,10 +1468,7 @@ async def openai_list_files_in_vector_store(
limit = min(limit or 20, MAX_PAGINATION_LIMIT)
order = order or "desc"
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
-
- store_info = self.openai_vector_stores[vector_store_id]
+ store_info = await self._get_authorized_openai_vector_store(vector_store_id)
file_objects: list[VectorStoreFileObject] = []
for file_id in store_info["file_ids"]:
@@ -1480,10 +1516,7 @@ async def openai_retrieve_vector_store_file(
file_id: str,
) -> VectorStoreFileObject:
"""Retrieves a vector store file."""
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
-
- store_info = self.openai_vector_stores[vector_store_id]
+ store_info = await self._get_authorized_openai_vector_store(vector_store_id)
if file_id not in store_info["file_ids"]:
raise ValueError(f"File {file_id} not found in vector store {vector_store_id}")
@@ -1498,8 +1531,7 @@ async def openai_retrieve_vector_store_file_contents(
include_metadata: bool | None = False,
) -> VectorStoreFileContentResponse:
"""Retrieves the contents of a vector store file."""
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
+ await self._get_authorized_openai_vector_store(vector_store_id)
# Parameters are already provided directly
# include_embeddings and include_metadata are now function parameters
@@ -1525,10 +1557,7 @@ async def openai_update_vector_store_file(
request: OpenAIUpdateVectorStoreFileRequest,
) -> VectorStoreFileObject:
"""Updates a vector store file."""
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
-
- store_info = self.openai_vector_stores[vector_store_id]
+ store_info = await self._get_authorized_openai_vector_store(vector_store_id, Action.UPDATE)
if file_id not in store_info["file_ids"]:
raise ValueError(f"File {file_id} not found in vector store {vector_store_id}")
@@ -1543,8 +1572,12 @@ async def openai_delete_vector_store_file(
file_id: str,
) -> VectorStoreFileDeleteResponse:
"""Deletes a vector store file."""
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
+ store_info = (await self._get_authorized_openai_vector_store(vector_store_id, Action.DELETE)).copy()
+ if file_id not in store_info["file_ids"]:
+ raise ValueError(f"File {file_id} not found in vector store {vector_store_id}")
+
+ file_info = await self._load_openai_vector_store_file(vector_store_id, file_id)
+ file = VectorStoreFileObject(**file_info)
dict_chunks = await self._load_openai_vector_store_file_contents(vector_store_id, file_id)
chunks = [Chunk.model_validate(c) for c in dict_chunks]
@@ -1569,9 +1602,6 @@ async def openai_delete_vector_store_file(
)
)
- store_info = self.openai_vector_stores[vector_store_id].copy()
-
- file = await self.openai_retrieve_vector_store_file(vector_store_id, file_id)
await self._delete_openai_vector_store_file_from_storage(vector_store_id, file_id)
# Update in-memory cache
@@ -1594,8 +1624,7 @@ async def openai_create_vector_store_file_batch(
params: Annotated[OpenAICreateVectorStoreFileBatchRequestWithExtraBody, Body(...)],
) -> VectorStoreFileBatchObject:
"""Create a vector store file batch."""
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
+ await self._get_authorized_openai_vector_store(vector_store_id, Action.UPDATE)
chunking_strategy = params.chunking_strategy or VectorStoreChunkingStrategyAuto()
@@ -1757,8 +1786,7 @@ async def openai_retrieve_vector_store_file_batch(
vector_store_id: str,
) -> VectorStoreFileBatchObject:
"""Retrieve a vector store file batch."""
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
+ await self._get_authorized_openai_vector_store(vector_store_id)
if batch_id not in self.openai_file_batches:
raise ValueError(f"File batch {batch_id} not found")
@@ -1793,8 +1821,7 @@ async def openai_list_files_in_vector_store_file_batch(
limit = min(limit or 20, MAX_PAGINATION_LIMIT)
order = order or "desc"
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
+ await self._get_authorized_openai_vector_store(vector_store_id)
if batch_id not in self.openai_file_batches:
raise ValueError(f"File batch {batch_id} not found")
@@ -1861,8 +1888,7 @@ async def openai_cancel_vector_store_file_batch(
vector_store_id: str,
) -> VectorStoreFileBatchObject:
"""Cancels a vector store file batch."""
- if vector_store_id not in self.openai_vector_stores:
- raise VectorStoreNotFoundError(vector_store_id)
+ await self._get_authorized_openai_vector_store(vector_store_id, Action.UPDATE)
if batch_id not in self.openai_file_batches:
raise ValueError(f"File batch {batch_id} not found")
diff --git a/src/ogx/providers/utils/memory/vector_store.py b/src/ogx/providers/utils/memory/vector_store.py
index b5691c592d9..3422e976aa7 100644
--- a/src/ogx/providers/utils/memory/vector_store.py
+++ b/src/ogx/providers/utils/memory/vector_store.py
@@ -360,7 +360,7 @@ async def query_chunks(
reranker_params["neural_weights"] = params["neural_weights"]
query_string = interleaved_content_as_str(request.query)
- log.info(f"query_chunks(): query={query_string!r}, mode={mode}, k={k}, reranker_type={reranker_type}")
+ log.debug("query_chunks", query=query_string, mode=mode, k=k, reranker_type=reranker_type)
if mode == "keyword":
response = await self.index.query_keyword(query_string, k, score_threshold, filters)
@@ -386,11 +386,15 @@ async def query_chunks(
else:
response = await self.index.query_vector(query_vector, k, score_threshold, filters)
- log.info(f"query_chunks(): retrieved {len(response.chunks)} chunks before neural reranking")
+ log.debug("query_chunks retrieved chunks before neural reranking", chunks_count=len(response.chunks))
for i, (chunk, score) in enumerate(zip(response.chunks, response.scores, strict=False)):
preview = chunk.content[:120] if isinstance(chunk.content, str) else str(chunk.content)[:120]
- log.info(
- f"Chunk {i}: score={score:.4f} doc_id={chunk.metadata.get('document_id', 'N/A')} content={preview!r}"
+ log.debug(
+ "Retrieved chunk preview",
+ chunk_index=i,
+ score=f"{score:.4f}",
+ document_id=chunk.metadata.get("document_id", "N/A"),
+ content=preview,
)
# Apply neural reranking if enabled
@@ -445,7 +449,7 @@ async def apply_neural_rerank(
log.error(f"Neural reranking failed: {e}. Returning original results.")
return response
- log.info(f"Rerank Response: {rerank_response.data}")
+ log.debug("Rerank response", data=rerank_response.data)
# Reorder chunks and scores based on neural rerank results
reranked_chunks = []
@@ -458,8 +462,12 @@ async def apply_neural_rerank(
log.info(f"Neural rerank: reranked {len(reranked_chunks)} chunks using model={reranker_model}")
for i, (chunk, score) in enumerate(zip(reranked_chunks, reranked_scores, strict=False)):
preview = chunk.content[:120] if isinstance(chunk.content, str) else str(chunk.content)[:120]
- log.info(
- f"Chunk {i}: relevance_score={score:.4f} doc_id={chunk.metadata.get('document_id', 'N/A')} content={preview!r}"
+ log.debug(
+ "Reranked chunk preview",
+ chunk_index=i,
+ relevance_score=f"{score:.4f}",
+ document_id=chunk.metadata.get("document_id", "N/A"),
+ content=preview,
)
return QueryChunksResponse(chunks=reranked_chunks, scores=reranked_scores)
diff --git a/src/ogx/providers/utils/responses/responses_store.py b/src/ogx/providers/utils/responses/responses_store.py
index a7f8b651949..6b224e1f649 100644
--- a/src/ogx/providers/utils/responses/responses_store.py
+++ b/src/ogx/providers/utils/responses/responses_store.py
@@ -512,10 +512,17 @@ async def _materialize_incremental_children(
parent_response_id = parent_response.id
# Use the underlying SQL store so children hidden by READ policy are still
- # materialized before parent deletion.
+ # materialized before parent deletion. Tenant filter is still applied to
+ # prevent cross-tenant data leakage.
+ from ogx.core.request_headers import get_authenticated_user
+
+ current_user = get_authenticated_user()
+ tenant_where, tenant_params = self.sql_store._build_tenant_filter(current_user)
rows = await self.sql_store.sql_store.fetch_all(
table=self.reference.table_name,
where={"previous_response_id": parent_response_id},
+ where_sql=tenant_where if tenant_where != "1=1" else None,
+ where_sql_params=tenant_params if tenant_params else None,
)
for row in rows.data:
@@ -544,7 +551,8 @@ async def _materialize_incremental_children(
child_data.pop("input_storage_mode", None)
# This write is an internal side effect of deleting the parent response.
- # It must not require UPDATE permission on child rows.
+ # It must not require UPDATE permission on child rows but is still
+ # scoped to the current tenant.
await self.sql_store.sql_store.update(
self.reference.table_name,
data={
@@ -555,6 +563,8 @@ async def _materialize_incremental_children(
"response_object": child_data,
},
where={"id": child_response.id},
+ where_sql=tenant_where if tenant_where != "1=1" else None,
+ where_sql_params=tenant_params if tenant_params else None,
)
async def delete_response_object(self, response_id: str) -> OpenAIDeleteResponseObject:
diff --git a/src/ogx/testing/api_recorder.py b/src/ogx/testing/api_recorder.py
index 20581b5b139..7d95e7192e3 100644
--- a/src/ogx/testing/api_recorder.py
+++ b/src/ogx/testing/api_recorder.py
@@ -15,6 +15,7 @@
from enum import StrEnum
from pathlib import Path
from typing import Any, Literal, cast
+from urllib.parse import urlparse
from openai import NOT_GIVEN, OpenAI
@@ -66,6 +67,10 @@ class APIRecordingMode(StrEnum):
"tool_call": "call_",
}
+_SHARED_MODEL_LIST_ENDPOINTS = {"/api/tags", "/v1/models", "/v1/openai/v1/models"}
+_LOCAL_MODEL_LIST_HOSTS = {"0.0.0.0", "127.0.0.1", "localhost"} # noqa: S104
+_DEFAULT_TEST_SERVER_PORT = 8321
+
_FLOAT_IN_STRING_PATTERN = re.compile(r"(-?\d+\.\d{4,})")
@@ -162,6 +167,39 @@ def _allocate_test_scoped_id(kind: str) -> str | None:
return f"{prefix}{counter}"
+def _is_model_list_endpoint(endpoint: str) -> bool:
+ return endpoint in _SHARED_MODEL_LIST_ENDPOINTS
+
+
+def _is_shared_model_list_request(path: str, hostname: str | None) -> bool:
+ """Return whether a model-list request should be shared across tests.
+
+ Remote provider model-list calls happen during session setup and test
+ execution, so they need a shared hash. Local OpenAI-compatible backends like
+ Ollama return raw provider IDs, which must stay scoped so they do not replace
+ OGX-prefixed model IDs used by integration fixtures.
+ """
+ if path in _SHARED_MODEL_LIST_ENDPOINTS:
+ return True
+ if path.endswith("/models") and hostname not in _LOCAL_MODEL_LIST_HOSTS:
+ return True
+ return False
+
+
+def _is_ogx_test_server_model_list_url(url: str) -> bool:
+ """Return whether this is model discovery against the local OGX test server."""
+ parsed = urlparse(url)
+ if not parsed.path.endswith("/models") or parsed.hostname not in _LOCAL_MODEL_LIST_HOSTS:
+ return False
+
+ test_base_url = os.environ.get("TEST_API_BASE_URL")
+ if test_base_url:
+ test_base = urlparse(test_base_url)
+ return parsed.hostname == test_base.hostname and parsed.port == test_base.port
+
+ return parsed.port == int(os.environ.get("OGX_PORT", _DEFAULT_TEST_SERVER_PORT))
+
+
def _deterministic_id_override(kind: str, factory: Callable[[], str]) -> str:
deterministic_id = _allocate_test_scoped_id(kind)
if deterministic_id is not None:
@@ -179,9 +217,6 @@ def normalize_inference_request(method: str, url: str, headers: dict[str, Any],
they are infrastructure/shared and need to work across session setup and tests.
"""
- # Extract just the endpoint path
- from urllib.parse import urlparse
-
parsed = urlparse(url)
# Bedrock's OpenAI-compatible endpoint includes stream_options that vary between
@@ -196,9 +231,10 @@ def normalize_inference_request(method: str, url: str, headers: dict[str, Any],
"body": body_for_hash,
}
- # Include test_id for isolation, except for shared infrastructure endpoints
- if parsed.path not in ("/api/tags", "/v1/models", "/v1/openai/v1/models"):
- normalized["test_id"] = test_id
+ # Include test_id for isolation. Shared model-list endpoints normalize their
+ # context to None so session setup and test-scoped provider refreshes use the
+ # same existing recording hash.
+ normalized["test_id"] = None if _is_shared_model_list_request(parsed.path, parsed.hostname) else test_id
normalized_json = json.dumps(normalized, sort_keys=True)
request_hash = hashlib.sha256(normalized_json.encode()).hexdigest()
@@ -277,7 +313,15 @@ def patch_httpx_for_test_id():
We use the _prepare_request hook that Stainless clients provide for mutating
requests after construction but before sending.
"""
- from ogx_client import OgxClient
+ try:
+ from ogx_open_client import OgxClient
+ except ImportError:
+ try:
+ from ogx_client import OgxClient
+ except ImportError as e:
+ raise ImportError(
+ "OgxClient was not found, install with `uv pip install ogx[openclient]` or `uv pip install ogx[client]`"
+ ) from e
if "ogx_client_prepare_request" in _original_methods:
return
@@ -287,9 +331,14 @@ def patch_httpx_for_test_id():
def patched_prepare_request(self, request):
# Call original first (it's a sync method that returns None)
- # Determine which original to call based on client type
- _original_methods["ogx_client_prepare_request"](self, request)
- _original_methods["openai_prepare_request"](self, request)
+ # Use .get() to handle cases where the originals weren't stored yet
+ # (e.g. class identity mismatch between ogx_open_client and ogx_client)
+ ogx_orig = _original_methods.get("ogx_client_prepare_request")
+ if ogx_orig is not None:
+ ogx_orig(self, request)
+ openai_orig = _original_methods.get("openai_prepare_request")
+ if openai_orig is not None:
+ openai_orig(self, request)
# Only inject test ID in server mode
stack_config_type = os.environ.get("OGX_TEST_STACK_CONFIG_TYPE", "library_client")
@@ -501,8 +550,8 @@ def store_recording(self, request_hash: str, request: dict[str, Any], response:
serialized_response["body"] = _serialize_response(serialized_response["body"], request_hash)
# For model-list endpoints, include digest in filename to distinguish different model sets
- endpoint = request.get("endpoint")
- if endpoint in ("/api/tags", "/v1/models", "/v1/openai/v1/models"):
+ endpoint = str(request.get("endpoint") or "")
+ if _is_model_list_endpoint(endpoint):
digest = _model_identifiers_digest(endpoint, response)
response_file = f"models-{request_hash}-{digest}.json"
@@ -655,7 +704,7 @@ def _combine_model_list_responses(endpoint: str, records: list[dict[str, Any]])
seen: dict[str, dict[str, Any]] = {}
for rec in records:
body = rec["response"]["body"]
- if endpoint in ("/v1/models", "/v1/openai/v1/models"):
+ if endpoint.endswith("/models"):
for m in body:
key = m.id
seen[key] = m
@@ -1101,7 +1150,7 @@ async def _patched_inference_method(original_method, self, client_type, endpoint
logger.info(f" Test context: {get_test_context()}")
if mode == APIRecordingMode.LIVE or storage is None:
- if endpoint in ("/v1/models", "/v1/openai/v1/models"):
+ if _is_model_list_endpoint(endpoint):
return original_method(self, *args, **kwargs)
else:
return await original_method(self, *args, **kwargs)
@@ -1129,13 +1178,17 @@ async def _patched_inference_method(original_method, self, client_type, endpoint
headers = {}
body = kwargs
+ if client_type == "openai" and _is_ogx_test_server_model_list_url(url):
+ response = original_method(self, *args, **kwargs)
+ return [m async for m in response]
+
request_hash = normalize_inference_request(method, url, headers, body)
# Try to find existing recording for REPLAY or RECORD_IF_MISSING modes
recording = None
if mode == APIRecordingMode.REPLAY or mode == APIRecordingMode.RECORD_IF_MISSING:
# Special handling for model-list endpoints: merge all recordings with this hash
- if endpoint in ("/api/tags", "/v1/models", "/v1/openai/v1/models"):
+ if _is_model_list_endpoint(endpoint):
records = storage._model_list_responses(request_hash)
recording = _combine_model_list_responses(endpoint, records)
else:
diff --git a/src/ogx_api/__init__.py b/src/ogx_api/__init__.py
index 77730a4cebc..7c3292edf12 100644
--- a/src/ogx_api/__init__.py
+++ b/src/ogx_api/__init__.py
@@ -130,6 +130,44 @@
GetConnectorToolRequest,
ListConnectorToolsRequest,
)
+from .containers import (
+ Container,
+ ContainerCreateRequest,
+ ContainerDeleteResponse,
+ ContainerExpiresAfter,
+ ContainerFile,
+ ContainerFileDeleteResponse,
+ ContainerFileSource,
+ ContainerRuntime,
+ Containers,
+ ContainerStatus,
+ DeleteContainerFileRequest,
+ DeleteContainerRequest,
+ ExecuteShellRequest,
+ GetContainerFileContentRequest,
+ GetContainerFileRequest,
+ GetContainerRequest,
+ ListContainerFilesRequest,
+ ListContainerFilesResponse,
+ ListContainersRequest,
+ ListContainersResponse,
+ MountSkillsRequest,
+ NetworkCredential,
+ NetworkDomainCredential,
+ NetworkPolicy,
+ NetworkPolicyExtended,
+ NetworkPolicyMode,
+ ShellCallOutput,
+ ShellEnvironment,
+ ShellEnvironmentContainerAuto,
+ ShellEnvironmentContainerReference,
+ ShellEnvironmentLocal,
+ ShellOutcome,
+ ShellOutcomeFailure,
+ ShellOutcomeSuccess,
+ ShellOutcomeTimeout,
+ UploadContainerFileRequest,
+)
from .conversations import (
AddItemsRequest,
Conversation,
@@ -445,6 +483,9 @@
UpdatePromptRequest,
)
from .providers import Providers
+from .skills import (
+ Skills,
+)
from .rag_tool import (
DefaultRAGQueryGeneratorConfig,
LLMRAGQueryGeneratorConfig,
@@ -538,6 +579,7 @@
"OGX_API_V1BETA",
# API Symbols
"Responses",
+ "Skills",
# Responses Request Models
"CancelResponseRequest",
"CompactResponseRequest",
@@ -583,6 +625,42 @@
"ConnectorInput",
"Connectors",
"ConnectorType",
+ "Container",
+ "ContainerCreateRequest",
+ "ContainerDeleteResponse",
+ "ContainerExpiresAfter",
+ "ContainerFile",
+ "ContainerFileDeleteResponse",
+ "ContainerFileSource",
+ "ContainerRuntime",
+ "Containers",
+ "ContainerStatus",
+ "DeleteContainerFileRequest",
+ "DeleteContainerRequest",
+ "ExecuteShellRequest",
+ "GetContainerFileContentRequest",
+ "GetContainerFileRequest",
+ "GetContainerRequest",
+ "ListContainerFilesRequest",
+ "ListContainerFilesResponse",
+ "ListContainersRequest",
+ "ListContainersResponse",
+ "MountSkillsRequest",
+ "NetworkCredential",
+ "NetworkDomainCredential",
+ "NetworkPolicy",
+ "NetworkPolicyExtended",
+ "NetworkPolicyMode",
+ "ShellCallOutput",
+ "ShellEnvironment",
+ "ShellEnvironmentContainerAuto",
+ "ShellEnvironmentContainerReference",
+ "ShellEnvironmentLocal",
+ "ShellOutcome",
+ "ShellOutcomeFailure",
+ "ShellOutcomeSuccess",
+ "ShellOutcomeTimeout",
+ "UploadContainerFileRequest",
"AddItemsRequest",
"Conversation",
"ConversationDeletedResource",
diff --git a/src/ogx_api/containers/__init__.py b/src/ogx_api/containers/__init__.py
new file mode 100644
index 00000000000..6df12dfdfbf
--- /dev/null
+++ b/src/ogx_api/containers/__init__.py
@@ -0,0 +1,92 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+"""Containers API module.
+
+Provides CRUD over sandboxed execution environments used by the Responses
+``shell`` and ``code_interpreter`` tools. Protocol definitions are in
+``api.py``, Pydantic models in ``models.py``, and FastAPI routes in
+``fastapi_routes.py``.
+"""
+
+from . import fastapi_routes
+from .api import ContainerRuntime, Containers
+from .models import (
+ Container,
+ ContainerCreateRequest,
+ ContainerDeleteResponse,
+ ContainerExpiresAfter,
+ ContainerFile,
+ ContainerFileDeleteResponse,
+ ContainerFileSource,
+ ContainerStatus,
+ DeleteContainerFileRequest,
+ DeleteContainerRequest,
+ ExecuteShellRequest,
+ GetContainerFileContentRequest,
+ GetContainerFileRequest,
+ GetContainerRequest,
+ ListContainerFilesRequest,
+ ListContainerFilesResponse,
+ ListContainersRequest,
+ ListContainersResponse,
+ MountSkillsRequest,
+ NetworkCredential,
+ NetworkDomainCredential,
+ NetworkPolicy,
+ NetworkPolicyExtended,
+ NetworkPolicyMode,
+ ShellCallOutput,
+ ShellEnvironment,
+ ShellEnvironmentContainerAuto,
+ ShellEnvironmentContainerReference,
+ ShellEnvironmentLocal,
+ ShellOutcome,
+ ShellOutcomeFailure,
+ ShellOutcomeSuccess,
+ ShellOutcomeTimeout,
+ UploadContainerFileRequest,
+)
+
+__all__ = [
+ "Container",
+ "ContainerCreateRequest",
+ "ContainerDeleteResponse",
+ "ContainerExpiresAfter",
+ "ContainerFile",
+ "ContainerFileDeleteResponse",
+ "ContainerFileSource",
+ "ContainerRuntime",
+ "ContainerStatus",
+ "Containers",
+ "DeleteContainerFileRequest",
+ "DeleteContainerRequest",
+ "ExecuteShellRequest",
+ "GetContainerFileContentRequest",
+ "GetContainerFileRequest",
+ "GetContainerRequest",
+ "ListContainerFilesRequest",
+ "ListContainerFilesResponse",
+ "ListContainersRequest",
+ "ListContainersResponse",
+ "MountSkillsRequest",
+ "NetworkCredential",
+ "NetworkDomainCredential",
+ "NetworkPolicy",
+ "NetworkPolicyExtended",
+ "NetworkPolicyMode",
+ "ShellCallOutput",
+ "ShellEnvironment",
+ "ShellEnvironmentContainerAuto",
+ "ShellEnvironmentContainerReference",
+ "ShellEnvironmentLocal",
+ "ShellOutcome",
+ "ShellOutcomeFailure",
+ "ShellOutcomeSuccess",
+ "ShellOutcomeTimeout",
+ "UploadContainerFileRequest",
+ "fastapi_routes",
+]
diff --git a/src/ogx_api/containers/api.py b/src/ogx_api/containers/api.py
new file mode 100644
index 00000000000..560bf4a7c01
--- /dev/null
+++ b/src/ogx_api/containers/api.py
@@ -0,0 +1,206 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+"""Containers API protocol definitions.
+
+This module contains two protocols:
+
+* ``Containers`` — the HTTP-facing CRUD API for sandboxed execution
+ environments.
+* ``ContainerRuntime`` — the internal provider protocol that backends
+ (Docker/Podman, Kubernetes, local) implement. The Containers provider
+ delegates to a ``ContainerRuntime`` for the actual lifecycle, file, and
+ shell-execution work.
+
+Pydantic models are defined in ``models.py`` and FastAPI routes in
+``fastapi_routes.py``.
+"""
+
+from typing import Protocol, runtime_checkable
+
+from fastapi import Response, UploadFile
+
+from .models import (
+ Container,
+ ContainerCreateRequest,
+ ContainerDeleteResponse,
+ ContainerFile,
+ ContainerFileDeleteResponse,
+ DeleteContainerFileRequest,
+ DeleteContainerRequest,
+ ExecuteShellRequest,
+ GetContainerFileContentRequest,
+ GetContainerFileRequest,
+ GetContainerRequest,
+ ListContainerFilesRequest,
+ ListContainerFilesResponse,
+ ListContainersRequest,
+ ListContainersResponse,
+ MountSkillsRequest,
+ ShellCallOutput,
+ UploadContainerFileRequest,
+)
+
+
+@runtime_checkable
+class Containers(Protocol):
+ """HTTP API for managing sandboxed execution containers.
+
+ Implementations enforce policy layering (request-supplied
+ ``NetworkPolicyExtended`` cannot expand operator defaults) and then
+ delegate to a configured :class:`ContainerRuntime` for backend work.
+ """
+
+ async def create_container(
+ self,
+ request: ContainerCreateRequest,
+ ) -> Container: ...
+
+ async def list_containers(
+ self,
+ request: ListContainersRequest,
+ ) -> ListContainersResponse: ...
+
+ async def get_container(
+ self,
+ request: GetContainerRequest,
+ ) -> Container: ...
+
+ async def delete_container(
+ self,
+ request: DeleteContainerRequest,
+ ) -> ContainerDeleteResponse: ...
+
+ async def upload_container_file(
+ self,
+ request: UploadContainerFileRequest,
+ file: UploadFile,
+ ) -> ContainerFile: ...
+
+ async def list_container_files(
+ self,
+ request: ListContainerFilesRequest,
+ ) -> ListContainerFilesResponse: ...
+
+ async def get_container_file(
+ self,
+ request: GetContainerFileRequest,
+ ) -> ContainerFile: ...
+
+ async def get_container_file_content(
+ self,
+ request: GetContainerFileContentRequest,
+ ) -> Response: ...
+
+ async def delete_container_file(
+ self,
+ request: DeleteContainerFileRequest,
+ ) -> ContainerFileDeleteResponse: ...
+
+
+@runtime_checkable
+class ContainerRuntime(Protocol):
+ """Internal provider protocol for container backends.
+
+ A ``ContainerRuntime`` provider is the thin layer between the Containers
+ API and a concrete backend (Docker/Podman socket, Kubernetes API, local
+ process supervisor). The Responses ``shell`` tool also calls
+ ``execute_shell`` directly when running in ``container_auto`` /
+ ``container_reference`` modes.
+
+ This protocol is not exposed over HTTP.
+ """
+
+ # --- lifecycle -------------------------------------------------------
+
+ async def create_container(
+ self,
+ request: ContainerCreateRequest,
+ ) -> Container:
+ """Create and start a container. Raises if resource limits are exceeded."""
+ ...
+
+ async def get_container(self, request: GetContainerRequest) -> Container:
+ """Fetch the current state of a container, including ``last_active_at``."""
+ ...
+
+ async def list_containers(
+ self,
+ request: ListContainersRequest,
+ ) -> ListContainersResponse:
+ """List containers known to this runtime."""
+ ...
+
+ async def delete_container(self, request: DeleteContainerRequest) -> ContainerDeleteResponse:
+ """Stop and remove a container along with its filesystem."""
+ ...
+
+ # --- file management ------------------------------------------------
+
+ async def upload_file(
+ self,
+ request: UploadContainerFileRequest,
+ file: UploadFile,
+ ) -> ContainerFile:
+ """Copy an uploaded file into the container at the runtime-chosen path."""
+ ...
+
+ async def list_files(
+ self,
+ request: ListContainerFilesRequest,
+ ) -> ListContainerFilesResponse:
+ """List files tracked inside a container."""
+ ...
+
+ async def get_file(
+ self,
+ request: GetContainerFileRequest,
+ ) -> ContainerFile:
+ """Get metadata for a single file inside a container."""
+ ...
+
+ async def get_file_content(
+ self,
+ request: GetContainerFileContentRequest,
+ ) -> Response:
+ """Stream the bytes of a file inside a container."""
+ ...
+
+ async def delete_file(
+ self,
+ request: DeleteContainerFileRequest,
+ ) -> ContainerFileDeleteResponse:
+ """Remove a file from a container's filesystem."""
+ ...
+
+ # --- execution ------------------------------------------------------
+
+ async def execute_shell(
+ self,
+ request: ExecuteShellRequest,
+ ) -> ShellCallOutput:
+ """Run a shell command inside the container and capture its output.
+
+ ``request.command`` is passed as ``argv`` (no shell expansion) to keep
+ the interface uniform across backends. Implementations are expected to
+ update ``last_active_at`` on the container as a side effect.
+ """
+ ...
+
+ # --- skill mounting -------------------------------------------------
+
+ async def mount_skills(
+ self,
+ request: MountSkillsRequest,
+ ) -> None:
+ """Mount skill bundles into ``/mnt/skills/{skill_name}/`` inside the container.
+
+ Each entry of ``request.skill_bundles`` is ``(skill_name, zip_bytes)``
+ — the zip archive is extracted into the named directory. Calling this
+ method multiple times with overlapping names overwrites the previous
+ contents.
+ """
+ ...
diff --git a/src/ogx_api/containers/fastapi_routes.py b/src/ogx_api/containers/fastapi_routes.py
new file mode 100644
index 00000000000..194e8c165a6
--- /dev/null
+++ b/src/ogx_api/containers/fastapi_routes.py
@@ -0,0 +1,205 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+"""FastAPI routes for the Containers API.
+
+Endpoints are mounted at ``/v1alpha/containers``. See
+:class:`ogx_api.containers.api.Containers` for the protocol implementations
+must satisfy.
+"""
+
+from typing import Annotated
+
+from fastapi import APIRouter, Depends, UploadFile
+from fastapi.param_functions import File
+from fastapi.responses import Response
+
+from ogx_api.common.upload_limits import (
+ DEFAULT_MAX_UPLOAD_SIZE_BYTES,
+ PreReadUploadFile,
+ read_upload_with_size_limit,
+)
+from ogx_api.router_utils import create_path_dependency, create_query_dependency, standard_responses
+from ogx_api.version import OGX_API_V1ALPHA
+
+from .api import Containers
+from .models import (
+ Container,
+ ContainerCreateRequest,
+ ContainerDeleteResponse,
+ ContainerFile,
+ ContainerFileDeleteResponse,
+ DeleteContainerFileRequest,
+ DeleteContainerRequest,
+ GetContainerFileContentRequest,
+ GetContainerFileRequest,
+ GetContainerRequest,
+ ListContainerFilesRequest,
+ ListContainerFilesResponse,
+ ListContainersRequest,
+ ListContainersResponse,
+ UploadContainerFileRequest,
+)
+
+get_list_containers_request = create_query_dependency(ListContainersRequest)
+get_container_request = create_path_dependency(GetContainerRequest)
+get_delete_container_request = create_path_dependency(DeleteContainerRequest)
+get_upload_container_file_request = create_path_dependency(UploadContainerFileRequest)
+
+
+# Multi-field path-parameter models cannot use create_path_dependency, which only
+# supports single-field models. The helpers below combine path (+ query) params
+# into the request model explicitly.
+
+
+def _list_container_files_request(
+ container_id: str,
+ after: str | None = None,
+ limit: int | None = 20,
+ order: str | None = "desc",
+) -> ListContainerFilesRequest:
+ return ListContainerFilesRequest.model_validate(
+ {"container_id": container_id, "after": after, "limit": limit, "order": order}
+ )
+
+
+def _get_container_file_request(container_id: str, file_id: str) -> GetContainerFileRequest:
+ return GetContainerFileRequest(container_id=container_id, file_id=file_id)
+
+
+def _get_container_file_content_request(container_id: str, file_id: str) -> GetContainerFileContentRequest:
+ return GetContainerFileContentRequest(container_id=container_id, file_id=file_id)
+
+
+def _delete_container_file_request(container_id: str, file_id: str) -> DeleteContainerFileRequest:
+ return DeleteContainerFileRequest(container_id=container_id, file_id=file_id)
+
+
+def create_router(impl: Containers, max_upload_size_bytes: int = DEFAULT_MAX_UPLOAD_SIZE_BYTES) -> APIRouter:
+ router = APIRouter(
+ prefix=f"/{OGX_API_V1ALPHA}",
+ tags=["Containers"],
+ responses=standard_responses,
+ )
+
+ @router.post(
+ "/containers",
+ response_model=Container,
+ summary="Create container",
+ description="Create a sandboxed container for shell/code execution.",
+ responses={200: {"description": "The created container."}},
+ )
+ async def create_container(request: ContainerCreateRequest) -> Container:
+ return await impl.create_container(request)
+
+ @router.get(
+ "/containers",
+ response_model=ListContainersResponse,
+ summary="List containers",
+ description="List containers.",
+ responses={200: {"description": "The list of containers."}},
+ )
+ async def list_containers(
+ request: Annotated[ListContainersRequest, Depends(get_list_containers_request)],
+ ) -> ListContainersResponse:
+ return await impl.list_containers(request)
+
+ @router.get(
+ "/containers/{container_id}",
+ response_model=Container,
+ summary="Get container",
+ description="Get a container by ID.",
+ responses={200: {"description": "The container."}},
+ )
+ async def get_container(
+ request: Annotated[GetContainerRequest, Depends(get_container_request)],
+ ) -> Container:
+ return await impl.get_container(request)
+
+ @router.delete(
+ "/containers/{container_id}",
+ response_model=ContainerDeleteResponse,
+ summary="Delete container",
+ description="Stop and remove a container.",
+ responses={200: {"description": "The container was deleted."}},
+ )
+ async def delete_container(
+ request: Annotated[DeleteContainerRequest, Depends(get_delete_container_request)],
+ ) -> ContainerDeleteResponse:
+ return await impl.delete_container(request)
+
+ @router.post(
+ "/containers/{container_id}/files",
+ response_model=ContainerFile,
+ summary="Upload container file",
+ description="Upload a file into a container's filesystem.",
+ responses={200: {"description": "The uploaded container file."}},
+ )
+ async def upload_container_file(
+ container_id: str,
+ file: Annotated[UploadFile, File(description="The file to upload into the container.")],
+ ) -> ContainerFile:
+ content = await read_upload_with_size_limit(file, max_upload_size_bytes)
+ safe_file = PreReadUploadFile(content, filename=file.filename, content_type=file.content_type)
+ return await impl.upload_container_file(
+ UploadContainerFileRequest(container_id=container_id),
+ safe_file,
+ )
+
+ @router.get(
+ "/containers/{container_id}/files",
+ response_model=ListContainerFilesResponse,
+ summary="List container files",
+ description="List files inside a container.",
+ responses={200: {"description": "The list of files."}},
+ )
+ async def list_container_files(
+ request: Annotated[ListContainerFilesRequest, Depends(_list_container_files_request)],
+ ) -> ListContainerFilesResponse:
+ return await impl.list_container_files(request)
+
+ @router.get(
+ "/containers/{container_id}/files/{file_id}",
+ response_model=ContainerFile,
+ summary="Get container file",
+ description="Get metadata for a file inside a container.",
+ responses={200: {"description": "The container file metadata."}},
+ )
+ async def get_container_file(
+ request: Annotated[GetContainerFileRequest, Depends(_get_container_file_request)],
+ ) -> ContainerFile:
+ return await impl.get_container_file(request)
+
+ @router.get(
+ "/containers/{container_id}/files/{file_id}/content",
+ status_code=200,
+ summary="Get container file content",
+ description="Download the contents of a file inside a container.",
+ responses={
+ 200: {
+ "description": "The file content.",
+ "content": {"application/octet-stream": {"schema": {"type": "string", "format": "binary"}}},
+ },
+ },
+ )
+ async def get_container_file_content(
+ request: Annotated[GetContainerFileContentRequest, Depends(_get_container_file_content_request)],
+ ) -> Response:
+ return await impl.get_container_file_content(request)
+
+ @router.delete(
+ "/containers/{container_id}/files/{file_id}",
+ response_model=ContainerFileDeleteResponse,
+ summary="Delete container file",
+ description="Remove a file from a container's filesystem.",
+ responses={200: {"description": "The file was deleted."}},
+ )
+ async def delete_container_file(
+ request: Annotated[DeleteContainerFileRequest, Depends(_delete_container_file_request)],
+ ) -> ContainerFileDeleteResponse:
+ return await impl.delete_container_file(request)
+
+ return router
diff --git a/src/ogx_api/containers/models.py b/src/ogx_api/containers/models.py
new file mode 100644
index 00000000000..6d44f01cf02
--- /dev/null
+++ b/src/ogx_api/containers/models.py
@@ -0,0 +1,444 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+"""Pydantic models for the Containers API.
+
+The Containers API provides CRUD over sandboxed execution environments used
+by the Responses ``shell`` and ``code_interpreter`` tools. The models here
+cover three concerns:
+
+* container lifecycle (``Container``, ``ContainerCreateRequest``)
+* container file management (``ContainerFile`` and request models)
+* network policy layering (``NetworkPolicy`` / ``NetworkPolicyExtended``)
+* shell execution shapes consumed by the Responses provider
+ (``ShellEnvironment``, ``ShellCallOutput``, ``ShellOutcome``)
+"""
+
+from enum import StrEnum
+from typing import Annotated, ClassVar, Literal
+
+from pydantic import BaseModel, Field, SecretStr
+
+from ogx_api.common.responses import Order
+from ogx_api.schema_utils import json_schema_type
+
+# ---------------------------------------------------------------------------
+# Expiration
+# ---------------------------------------------------------------------------
+
+
+@json_schema_type
+class ContainerExpiresAfter(BaseModel):
+ """Control expiration of a container.
+
+ Anchored on ``last_active_at`` (each shell execution or file operation
+ refreshes the anchor). Operator-set bounds protect the host from
+ long-lived sandboxes.
+ """
+
+ MIN: ClassVar[int] = 60 # 1 minute
+ MAX: ClassVar[int] = 86400 # 24 hours
+
+ anchor: Literal["last_active_at"] = Field(
+ default="last_active_at",
+ description="The anchor point for expiration. Must be 'last_active_at'.",
+ )
+ minutes: int = Field(
+ ...,
+ ge=1,
+ le=1440,
+ description="Minutes of inactivity after the anchor before the container expires.",
+ )
+
+
+# ---------------------------------------------------------------------------
+# Network policy
+# ---------------------------------------------------------------------------
+
+
+class NetworkPolicyMode(StrEnum):
+ """Egress policy mode applied to a container's outbound network."""
+
+ DENY = "deny"
+ ALLOW_LIST = "allow_list"
+ ALLOW_ALL = "allow_all"
+
+
+@json_schema_type
+class NetworkCredential(BaseModel):
+ """A named credential available to outbound network calls.
+
+ The ``value`` should be a secret reference (e.g. ``${env.MY_SECRET}``)
+ in operator-supplied configuration, never a raw secret in a request body.
+ """
+
+ name: str = Field(..., description="Logical name used by the container to look up the credential.")
+ value: SecretStr = Field(..., description="Secret reference or literal value to be injected into the container.")
+
+
+@json_schema_type
+class NetworkDomainCredential(BaseModel):
+ """Bind a ``NetworkCredential`` to a specific outbound domain."""
+
+ domain: str = Field(..., description="Fully-qualified domain name to which the credential applies.")
+ credential: NetworkCredential = Field(..., description="Credential injected on outbound calls to this domain.")
+
+
+@json_schema_type
+class NetworkPolicy(BaseModel):
+ """Operator-set egress policy for a container.
+
+ A NetworkPolicy is the *upper bound* — request-supplied
+ ``NetworkPolicyExtended`` values may only narrow this policy.
+ """
+
+ mode: NetworkPolicyMode = Field(
+ default=NetworkPolicyMode.DENY,
+ description="Default egress disposition. 'deny' blocks all egress except entries in 'allow_domains'.",
+ )
+ allow_domains: list[str] = Field(
+ default_factory=list,
+ description="Domains permitted for outbound traffic. Used when mode is 'allow_list'.",
+ )
+ deny_domains: list[str] = Field(
+ default_factory=list,
+ description="Domains explicitly blocked. Takes precedence over 'allow_domains'.",
+ )
+
+
+@json_schema_type
+class NetworkPolicyExtended(NetworkPolicy):
+ """Request-layer extension of an operator NetworkPolicy.
+
+ The request may add domain credentials and narrow allow/deny lists, but
+ cannot expand the operator default — enforcement is performed at the API
+ layer; see issue #5892 task 8.
+ """
+
+ domain_credentials: list[NetworkDomainCredential] = Field(
+ default_factory=list,
+ description="Per-domain credentials injected on outbound calls from this container.",
+ )
+
+
+# ---------------------------------------------------------------------------
+# Container resource
+# ---------------------------------------------------------------------------
+
+
+class ContainerStatus(StrEnum):
+ """Lifecycle status of a container."""
+
+ ACTIVE = "active"
+ EXPIRED = "expired"
+
+
+@json_schema_type
+class Container(BaseModel):
+ """A sandboxed execution environment.
+
+ Mirrors the OpenAI Containers API resource with OGX-specific extensions
+ for network policy and image selection.
+ """
+
+ id: str = Field(..., description="Identifier for the container.")
+ object: Literal["container"] = Field(
+ default="container", description="The object type, which is always 'container'."
+ )
+ created_at: int = Field(..., description="Unix timestamp (in seconds) for when the container was created.")
+ status: ContainerStatus = Field(..., description="Current lifecycle status.")
+ last_active_at: int = Field(
+ ..., description="Unix timestamp (in seconds) of the last operation performed against this container."
+ )
+ name: str | None = Field(default=None, description="Human-readable name for the container.")
+ expires_after: ContainerExpiresAfter | None = Field(
+ default=None, description="Inactivity-based expiration settings."
+ )
+ image: str | None = Field(
+ default=None,
+ description="Container image used to run the sandbox. May be operator-locked.",
+ )
+ network_policy: NetworkPolicy | None = Field(
+ default=None,
+ description="Effective network policy after layering operator defaults with request extensions.",
+ )
+
+
+@json_schema_type
+class ContainerCreateRequest(BaseModel):
+ """Request body for ``POST /containers``."""
+
+ name: str | None = Field(default=None, description="Human-readable name for the container.")
+ file_ids: list[str] = Field(
+ default_factory=list,
+ description="Files (from the Files API) to seed into the container at /mnt/data/.",
+ )
+ expires_after: ContainerExpiresAfter | None = Field(
+ default=None, description="Inactivity-based expiration settings."
+ )
+ image: str | None = Field(
+ default=None,
+ description="Requested container image. The operator policy may pin or reject this value.",
+ )
+ network_policy: NetworkPolicyExtended | None = Field(
+ default=None,
+ description="Request-supplied network policy extension. Must be a subset of the operator default.",
+ )
+
+
+@json_schema_type
+class ListContainersRequest(BaseModel):
+ """Query parameters for ``GET /containers``."""
+
+ after: str | None = Field(default=None, description="Cursor for pagination. Returns containers after this ID.")
+ limit: int | None = Field(default=20, ge=1, le=100, description="Maximum number of containers to return (1-100).")
+ order: Order | None = Field(default=Order.desc, description="Sort order by created_at timestamp ('asc' or 'desc').")
+
+
+@json_schema_type
+class ListContainersResponse(BaseModel):
+ """Response for ``GET /containers``."""
+
+ object: Literal["list"] = Field(default="list", description="The object type, which is always 'list'.")
+ data: list[Container] = Field(..., description="The list of containers.")
+ first_id: str | None = Field(default=None, description="ID of the first container in the page.")
+ last_id: str | None = Field(default=None, description="ID of the last container in the page.")
+ has_more: bool = Field(..., description="Whether more containers exist beyond this page.")
+
+
+@json_schema_type
+class GetContainerRequest(BaseModel):
+ container_id: str = Field(..., description="The ID of the container to retrieve.")
+
+
+@json_schema_type
+class DeleteContainerRequest(BaseModel):
+ container_id: str = Field(..., description="The ID of the container to delete.")
+
+
+@json_schema_type
+class ContainerDeleteResponse(BaseModel):
+ """Response for ``DELETE /containers/{container_id}``."""
+
+ id: str = Field(..., description="The container identifier that was deleted.")
+ object: Literal["container"] = Field(
+ default="container", description="The object type, which is always 'container'."
+ )
+ deleted: bool = Field(..., description="Whether the container was successfully deleted.")
+
+
+# ---------------------------------------------------------------------------
+# Container files
+# ---------------------------------------------------------------------------
+
+
+class ContainerFileSource(StrEnum):
+ """Origin of a file inside a container."""
+
+ USER = "user"
+ ASSISTANT = "assistant"
+
+
+@json_schema_type
+class ContainerFile(BaseModel):
+ """A file present inside a container's filesystem."""
+
+ id: str = Field(..., description="Identifier of the container file.")
+ object: Literal["container.file"] = Field(
+ default="container.file", description="The object type, which is always 'container.file'."
+ )
+ container_id: str = Field(..., description="ID of the container holding the file.")
+ created_at: int = Field(..., description="Unix timestamp (in seconds) when the file was created.")
+ bytes: int = Field(..., description="Size of the file in bytes.")
+ path: str = Field(..., description="Absolute path to the file inside the container.")
+ source: ContainerFileSource = Field(
+ ..., description="Whether the file was supplied by the user or written by the model."
+ )
+
+
+@json_schema_type
+class UploadContainerFileRequest(BaseModel):
+ """Path parameters for ``POST /containers/{container_id}/files``.
+
+ The file content itself is supplied as a multipart upload and not part of
+ this Pydantic body; see ``fastapi_routes.py``.
+ """
+
+ container_id: str = Field(..., description="The ID of the container to upload into.")
+
+
+@json_schema_type
+class ListContainerFilesRequest(BaseModel):
+ container_id: str = Field(..., description="The ID of the container whose files should be listed.")
+ after: str | None = Field(default=None, description="Cursor for pagination.")
+ limit: int | None = Field(default=20, ge=1, le=100, description="Maximum number of files to return (1-100).")
+ order: Order | None = Field(default=Order.desc, description="Sort order by created_at timestamp.")
+
+
+@json_schema_type
+class ListContainerFilesResponse(BaseModel):
+ object: Literal["list"] = Field(default="list", description="The object type, which is always 'list'.")
+ data: list[ContainerFile] = Field(..., description="The list of files in the container.")
+ first_id: str | None = Field(default=None, description="ID of the first file in the page.")
+ last_id: str | None = Field(default=None, description="ID of the last file in the page.")
+ has_more: bool = Field(..., description="Whether more files exist beyond this page.")
+
+
+@json_schema_type
+class GetContainerFileRequest(BaseModel):
+ container_id: str = Field(..., description="The ID of the container holding the file.")
+ file_id: str = Field(..., description="The ID of the container file to retrieve.")
+
+
+@json_schema_type
+class GetContainerFileContentRequest(BaseModel):
+ container_id: str = Field(..., description="The ID of the container holding the file.")
+ file_id: str = Field(..., description="The ID of the container file to download.")
+
+
+@json_schema_type
+class DeleteContainerFileRequest(BaseModel):
+ container_id: str = Field(..., description="The ID of the container holding the file.")
+ file_id: str = Field(..., description="The ID of the container file to delete.")
+
+
+@json_schema_type
+class ContainerFileDeleteResponse(BaseModel):
+ id: str = Field(..., description="The container file identifier that was deleted.")
+ object: Literal["container.file"] = Field(
+ default="container.file", description="The object type, which is always 'container.file'."
+ )
+ deleted: bool = Field(..., description="Whether the file was successfully deleted.")
+
+
+# ---------------------------------------------------------------------------
+# Shell execution shapes
+# ---------------------------------------------------------------------------
+
+
+@json_schema_type
+class ShellEnvironmentContainerAuto(BaseModel):
+ """Provider-managed container environment.
+
+ The provider lazily creates and reuses a container for the calling
+ response chain. Useful when the caller does not need to persist or
+ reference the container across responses.
+ """
+
+ type: Literal["container_auto"] = Field(default="container_auto", description="Discriminator.")
+ image: str | None = Field(default=None, description="Optional preferred container image.")
+ expires_after: ContainerExpiresAfter | None = Field(
+ default=None, description="Inactivity-based expiration for the auto-created container."
+ )
+
+
+@json_schema_type
+class ShellEnvironmentContainerReference(BaseModel):
+ """Reference an existing container by ID."""
+
+ type: Literal["container_reference"] = Field(default="container_reference", description="Discriminator.")
+ container_id: str = Field(..., description="The ID of an existing container to execute inside.")
+
+
+@json_schema_type
+class ShellEnvironmentLocal(BaseModel):
+ """Local (non-container) execution mode.
+
+ Only available when the operator has explicitly enabled local mode in
+ the ContainerRuntime provider configuration.
+ """
+
+ type: Literal["local"] = Field(default="local", description="Discriminator.")
+ working_directory: str | None = Field(default=None, description="Optional working directory for local execution.")
+
+
+ShellEnvironment = Annotated[
+ ShellEnvironmentContainerAuto | ShellEnvironmentContainerReference | ShellEnvironmentLocal,
+ Field(discriminator="type"),
+]
+"""Discriminated union of the three shell execution environments."""
+
+
+@json_schema_type
+class ShellOutcomeSuccess(BaseModel):
+ """Process exited cleanly with status 0."""
+
+ type: Literal["success"] = Field(default="success", description="Discriminator.")
+ exit_code: Literal[0] = Field(default=0, description="Process exit code (always 0 for success).")
+
+
+@json_schema_type
+class ShellOutcomeFailure(BaseModel):
+ """Process exited with a non-zero status."""
+
+ type: Literal["failure"] = Field(default="failure", description="Discriminator.")
+ exit_code: int = Field(..., description="Process exit code.")
+ reason: str | None = Field(default=None, description="Human-readable failure reason, if known.")
+
+
+@json_schema_type
+class ShellOutcomeTimeout(BaseModel):
+ """Process was terminated for exceeding its time budget."""
+
+ type: Literal["timeout"] = Field(default="timeout", description="Discriminator.")
+ elapsed_seconds: float = Field(..., description="Wall-clock seconds elapsed before termination.")
+
+
+ShellOutcome = Annotated[
+ ShellOutcomeSuccess | ShellOutcomeFailure | ShellOutcomeTimeout,
+ Field(discriminator="type"),
+]
+"""Discriminated union describing how a shell command terminated."""
+
+
+@json_schema_type
+class ShellCallOutput(BaseModel):
+ """Captured output of a single shell execution.
+
+ Consumed by the Responses provider to construct ``ShellCallOutputItem``
+ entries on the output stream.
+ """
+
+ stdout: str = Field(..., description="UTF-8 decoded standard output (truncated by the runtime if oversized).")
+ stderr: str = Field(..., description="UTF-8 decoded standard error (truncated by the runtime if oversized).")
+ outcome: ShellOutcome = Field(..., description="How the shell process terminated.")
+ duration_ms: int = Field(..., ge=0, description="Wall-clock duration of the shell call in milliseconds.")
+ container_id: str | None = Field(
+ default=None,
+ description="ID of the container the call executed in, when applicable. Null for local mode.",
+ )
+
+
+# ---------------------------------------------------------------------------
+# ContainerRuntime request models
+#
+# These describe the internal ContainerRuntime call surface, which is not
+# exposed over HTTP. They are deliberately NOT decorated with
+# ``@json_schema_type`` so they stay out of the public OpenAPI spec.
+# ---------------------------------------------------------------------------
+
+
+class ExecuteShellRequest(BaseModel):
+ """Internal request to run a shell command inside a container."""
+
+ container_id: str = Field(..., description="The ID of the container to execute inside.")
+ command: list[str] = Field(..., description="Command argv to execute. Passed without shell expansion.")
+ timeout_seconds: float | None = Field(
+ default=None, description="Optional wall-clock timeout for the command in seconds."
+ )
+
+
+class MountSkillsRequest(BaseModel):
+ """Internal request to mount skill bundles into a container."""
+
+ container_id: str = Field(..., description="The ID of the container to mount skills into.")
+ skill_bundles: list[tuple[str, bytes]] = Field(
+ ...,
+ description=(
+ "Skill bundles as (skill_name, zip_bytes) pairs. Each archive is "
+ "extracted into /mnt/skills/{skill_name}/ inside the container."
+ ),
+ )
diff --git a/src/ogx_api/datatypes.py b/src/ogx_api/datatypes.py
index 975fce2a2c2..3970143d88a 100644
--- a/src/ogx_api/datatypes.py
+++ b/src/ogx_api/datatypes.py
@@ -104,6 +104,9 @@ class Api(Enum, metaclass=DynamicApiMeta):
:cvar connectors: External connector management (e.g., MCP servers)
:cvar messages: Anthropic Messages API compatibility layer
:cvar interactions: Google Interactions API compatibility layer
+ :cvar containers: Sandboxed container management for code/shell tool execution
+ :cvar container_runtime: Backend runtime for containers (Docker/Podman, Kubernetes)
+ :cvar skills: Versioned skill bundle management
:cvar inspect: Built-in system inspection and introspection
"""
@@ -113,6 +116,7 @@ class Api(Enum, metaclass=DynamicApiMeta):
batches = "batches"
vector_io = "vector_io"
tool_runtime = "tool_runtime"
+ container_runtime = "container_runtime"
models = "models"
vector_stores = "vector_stores" # only used for routing table
@@ -122,8 +126,10 @@ class Api(Enum, metaclass=DynamicApiMeta):
prompts = "prompts"
conversations = "conversations"
connectors = "connectors"
+ containers = "containers"
messages = "messages"
interactions = "interactions"
+ skills = "skills"
# built-in API
inspect = "inspect"
diff --git a/src/ogx_api/files/fastapi_routes.py b/src/ogx_api/files/fastapi_routes.py
index ee515f89ad1..02fce1afbfb 100644
--- a/src/ogx_api/files/fastapi_routes.py
+++ b/src/ogx_api/files/fastapi_routes.py
@@ -4,11 +4,14 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
-from typing import Annotated
+import json
+from collections.abc import Mapping
+from typing import Annotated, Any
-from fastapi import APIRouter, Depends, UploadFile
+from fastapi import APIRouter, Depends, HTTPException, Request, UploadFile
from fastapi.param_functions import File, Form
from fastapi.responses import Response
+from pydantic import ValidationError
from ogx_api.common.upload_limits import (
DEFAULT_MAX_UPLOAD_SIZE_BYTES,
@@ -40,6 +43,33 @@
get_retrieve_file_content_request = create_path_dependency(RetrieveFileContentRequest)
+def _parse_expires_after_form(form: Mapping[str, Any]) -> ExpiresAfter | None:
+ bracket_data: dict[str, Any] = {}
+ prefix = "expires_after["
+ for key, value in form.items():
+ if key.startswith(prefix) and key.endswith("]"):
+ bracket_data[key[len(prefix) : -1]] = value
+
+ if bracket_data:
+ return ExpiresAfter.model_validate(bracket_data)
+
+ value = form.get("expires_after")
+ if value is None:
+ return None
+ if isinstance(value, str):
+ return ExpiresAfter.model_validate(json.loads(value))
+ return ExpiresAfter.model_validate(value)
+
+
+async def get_upload_file_expires_after(request: Request) -> ExpiresAfter | None:
+ """Parse expires_after from multipart forms sent as JSON or bracketed fields."""
+ form = await request.form()
+ try:
+ return _parse_expires_after_form(form)
+ except (json.JSONDecodeError, TypeError, ValidationError) as e:
+ raise HTTPException(status_code=400, detail=f"Failed to parse expires_after: {e}") from e
+
+
def create_router(impl: Files, max_upload_size_bytes: int = DEFAULT_MAX_UPLOAD_SIZE_BYTES) -> APIRouter:
router = APIRouter(
prefix=f"/{OGX_API_V1}",
@@ -118,9 +148,10 @@ async def retrieve_file_content(
async def upload_file(
file: Annotated[UploadFile, File(description="The file to upload.")],
purpose: Annotated[OpenAIFileUploadPurpose, Form(description="The intended purpose of the uploaded file.")],
- expires_after: Annotated[
- ExpiresAfter | None,
- Form(description="Optional expiration settings for the file."),
+ expires_after: Annotated[ExpiresAfter | None, Depends(get_upload_file_expires_after)] = None,
+ expires_after_schema: Annotated[
+ str | None,
+ Form(alias="expires_after", description="Optional expiration settings for the file."),
] = None,
) -> OpenAIFileObject:
content = await read_upload_with_size_limit(file, max_upload_size_bytes)
diff --git a/src/ogx_api/internal/sqlstore.py b/src/ogx_api/internal/sqlstore.py
index 9a124ea3f1b..9c01c070d8f 100644
--- a/src/ogx_api/internal/sqlstore.py
+++ b/src/ogx_api/internal/sqlstore.py
@@ -5,6 +5,7 @@
# the root directory of this source tree.
from collections.abc import Mapping, Sequence
+from dataclasses import dataclass
from enum import Enum
from typing import Any, Literal, Protocol
@@ -34,6 +35,16 @@ class ColumnDefinition(BaseModel):
default: Any = None
+@dataclass(frozen=True)
+class DeleteOperation:
+ """A single SQL delete operation."""
+
+ table: str
+ where: Mapping[str, Any]
+ where_sql: str | None = None
+ where_sql_params: Mapping[str, Any] | None = None
+
+
class SqlStore(Protocol):
"""Protocol for common SQL-store functionality."""
@@ -47,6 +58,8 @@ async def upsert(
data: Mapping[str, Any],
conflict_columns: list[str],
update_columns: list[str] | None = None,
+ update_where_sql: str | None = None,
+ update_where_sql_params: Mapping[str, Any] | None = None,
) -> None: ...
async def fetch_all(
@@ -86,6 +99,8 @@ async def delete(
where_sql_params: Mapping[str, Any] | None = None,
) -> None: ...
+ async def delete_many(self, operations: Sequence[DeleteOperation]) -> None: ...
+
async def add_column_if_not_exists(
self,
table: str,
@@ -97,4 +112,4 @@ async def add_column_if_not_exists(
async def shutdown(self) -> None: ...
-__all__ = ["ColumnDefinition", "ColumnType", "SqlStore"]
+__all__ = ["ColumnDefinition", "ColumnType", "DeleteOperation", "SqlStore"]
diff --git a/src/ogx_api/messages/models.py b/src/ogx_api/messages/models.py
index 4f596ee713d..a2c8f12720e 100644
--- a/src/ogx_api/messages/models.py
+++ b/src/ogx_api/messages/models.py
@@ -14,7 +14,7 @@
from typing import Annotated, Any, Literal
-from pydantic import BaseModel, ConfigDict, Field, model_validator
+from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
from ogx_api.schema_utils import remove_null_from_anyof
@@ -202,6 +202,35 @@ def _normalize_tool_types(tools: list[Any]) -> list[Any]:
return [{**t, "type": "custom"} if isinstance(t, dict) and "type" not in t else t for t in tools]
+# -- Tool choice --
+
+
+class _ToolChoiceAuto(BaseModel):
+ type: Literal["auto"] = "auto"
+ disable_parallel_tool_use: bool | None = None
+
+
+class _ToolChoiceAny(BaseModel):
+ type: Literal["any"] = "any"
+ disable_parallel_tool_use: bool | None = None
+
+
+class _ToolChoiceNone(BaseModel):
+ type: Literal["none"] = "none"
+
+
+class _ToolChoiceTool(BaseModel):
+ type: Literal["tool"] = "tool"
+ name: str
+ disable_parallel_tool_use: bool | None = None
+
+
+AnthropicToolChoice = Annotated[
+ _ToolChoiceAuto | _ToolChoiceAny | _ToolChoiceNone | _ToolChoiceTool,
+ Field(discriminator="type"),
+]
+
+
# -- Thinking config --
@@ -231,11 +260,21 @@ class AnthropicCreateMessageRequest(BaseModel):
tools: list[AnthropicTool] | None = Field(
default=None, json_schema_extra=remove_null_from_anyof, description="Tools available to the model."
)
- tool_choice: Any | None = Field(
+ tool_choice: AnthropicToolChoice | None = Field(
default=None,
json_schema_extra=remove_null_from_anyof,
description="How the model should select tools. One of: 'auto', 'any', 'none', or {type: 'tool', name: '...'}.",
)
+
+ @field_validator("tool_choice", mode="before")
+ @classmethod
+ def _coerce_tool_choice(cls, v: Any) -> Any:
+ if isinstance(v, str):
+ if v in ("auto", "any", "none"):
+ return {"type": v}
+ return {"type": "auto"}
+ return v
+
stream: bool | None = Field(
default=False, json_schema_extra=remove_null_from_anyof, description="Whether to stream the response."
)
@@ -395,16 +434,6 @@ class MessageStopEvent(BaseModel):
type: Literal["message_stop"] = "message_stop"
-AnthropicStreamEvent = (
- MessageStartEvent
- | ContentBlockStartEvent
- | ContentBlockDeltaEvent
- | ContentBlockStopEvent
- | MessageDeltaEvent
- | MessageStopEvent
-)
-
-
# -- Error response --
@@ -420,6 +449,31 @@ class AnthropicErrorResponse(BaseModel):
error: _AnthropicErrorDetail
+class PingEvent(BaseModel):
+ """Keep-alive heartbeat sent between content blocks."""
+
+ type: Literal["ping"] = "ping"
+
+
+class ErrorStreamEvent(BaseModel):
+ """Mid-stream error event sent before the stream closes."""
+
+ type: Literal["error"] = "error"
+ error: _AnthropicErrorDetail
+
+
+AnthropicStreamEvent = (
+ MessageStartEvent
+ | ContentBlockStartEvent
+ | ContentBlockDeltaEvent
+ | ContentBlockStopEvent
+ | MessageDeltaEvent
+ | MessageStopEvent
+ | PingEvent
+ | ErrorStreamEvent
+)
+
+
# -- Message Batches --
diff --git a/src/ogx_api/openai_responses.py b/src/ogx_api/openai_responses.py
index e6c49a2fd44..25419ff5235 100644
--- a/src/ogx_api/openai_responses.py
+++ b/src/ogx_api/openai_responses.py
@@ -480,7 +480,9 @@ class OpenAIResponseText(BaseModel):
"""
format: OpenAIResponseTextFormat | None = None
- verbosity: Literal["low", "medium", "high"] | None = None
+ # Defaults to "medium" to match OpenAI: the OpenResponses schema types verbosity as an
+ # optional enum that rejects an explicit null, so the response must not serialize it as null.
+ verbosity: Literal["low", "medium", "high"] | None = "medium"
@json_schema_type
@@ -848,6 +850,7 @@ class OpenAIResponseObject(BaseModel):
:param max_output_tokens: (Optional) An upper bound for the number of tokens that can be generated for a response, including visible output tokens.
:param service_tier: (Optional) The service tier to use for this response.
:param metadata: (Optional) Dictionary of metadata key-value pairs
+ :param safety_identifier: (Optional) Stable identifier used to associate the request with an end user for safety monitoring
"""
background: bool | None = Field(default=None, json_schema_extra=remove_null_from_anyof)
@@ -884,6 +887,7 @@ class OpenAIResponseObject(BaseModel):
metadata: dict[str, str] | None = None
presence_penalty: float | None = Field(default=None, json_schema_extra=remove_null_from_anyof)
store: bool
+ safety_identifier: str | None = None
@json_schema_type
diff --git a/src/ogx_api/pyproject.toml b/src/ogx_api/pyproject.toml
index 0211b164385..459dba2f362 100644
--- a/src/ogx_api/pyproject.toml
+++ b/src/ogx_api/pyproject.toml
@@ -5,8 +5,10 @@ build-backend = "setuptools.build_meta"
[tool.uv]
required-version = ">=0.7.0"
constraint-dependencies = [
+ "idna>=3.15",
"protobuf>=6.33.5", # CVE-2026-0994: JSON recursion depth bypass
"requests>=2.33.0", # CVE-2026-25645: insecure temp file reuse in extract_zipped_paths()
+ "starlette>=1.0.1",
"urllib3>=2.6.3", # CVE-2026-21441 + CVE-2025-66471 + CVE-2025-66418: decompression bomb, streaming, chain bypass
]
@@ -29,12 +31,13 @@ classifiers = [
"Topic :: Scientific/Engineering :: Information Analysis",
]
dependencies = [
- "openai>=2.38.0",
+ "openai>=2.41.1",
"fastapi>=0.136.3,<1.0",
"pydantic>=2.11.9",
"jsonschema>=4.26.0",
"opentelemetry-sdk>=1.42.1",
"opentelemetry-exporter-otlp-proto-http>=1.42.1",
+ "opentelemetry-exporter-otlp-proto-grpc>=1.42.1",
]
[project.urls]
@@ -52,6 +55,7 @@ packages = [
"ogx_api.responses",
"ogx_api.batches",
"ogx_api.common",
+ "ogx_api.containers",
"ogx_api.conversations",
"ogx_api.file_processors",
"ogx_api.files",
@@ -64,6 +68,7 @@ packages = [
"ogx_api.providers",
"ogx_api.prompts",
+ "ogx_api.skills",
"ogx_api.tools",
"ogx_api.vector_io",
"ogx_api.connectors",
@@ -92,7 +97,7 @@ ogx_api = ["py.typed", "**/*.json", "**/*.yaml"]
[tool.setuptools_scm]
root = "../.."
-fallback_version = "1.0.3.dev0"
+fallback_version = "1.1.4.dev0"
[tool.ruff]
line-length = 120
diff --git a/src/ogx_api/responses/fastapi_routes.py b/src/ogx_api/responses/fastapi_routes.py
index 0feefeb3e7e..fd9664df08a 100644
--- a/src/ogx_api/responses/fastapi_routes.py
+++ b/src/ogx_api/responses/fastapi_routes.py
@@ -17,9 +17,9 @@
from collections.abc import AsyncIterator
from typing import Annotated, Any
-from fastapi import APIRouter, Body, Depends, Path, Query, Request, Response
+from fastapi import APIRouter, Body, Depends, Path, Query, Request, Response, WebSocket, WebSocketDisconnect
from fastapi.responses import StreamingResponse
-from pydantic import BaseModel
+from pydantic import BaseModel, ValidationError
from ogx_api.common.responses import Order
from ogx_api.openai_responses import (
@@ -214,6 +214,151 @@ async def wrapper() -> AsyncIterator[str]:
return wrapper()
+# Fields that the WebSocket response.create event forbids (they only apply to
+# the HTTP streaming transport) and the discriminator we strip before building
+# the request.
+_WS_STRIPPED_FIELDS = ("type", "stream", "stream_options", "background")
+
+
+def _ws_normalize_input(input_value: Any) -> list[Any]:
+ """Normalize a response.create `input` to a list of items for context reuse."""
+ if input_value is None:
+ return []
+ if isinstance(input_value, str):
+ return [{"type": "message", "role": "user", "content": input_value}]
+ if isinstance(input_value, list):
+ return list(input_value)
+ return [input_value]
+
+
+async def _send_ws_error(
+ websocket: WebSocket,
+ status: int,
+ code: str,
+ message: str,
+ param: str | None = None,
+) -> None:
+ """Send a WebSocket error envelope (matches the OpenResponses error event).
+
+ Sending is best-effort: if the client has already disconnected (a common
+ cause of the failure we are reporting), the send raises and is suppressed so
+ it does not mask the original error or produce a spurious traceback.
+ """
+ try:
+ await websocket.send_text(
+ json.dumps(
+ {
+ "type": "error",
+ "status": status,
+ "error": {"code": code, "message": message, "param": param},
+ }
+ )
+ )
+ except Exception:
+ logger.debug("Failed to send WebSocket error envelope; client likely disconnected")
+
+
+async def _handle_ws_responses_turn(
+ websocket: WebSocket,
+ impl: Responses,
+ raw: str,
+ session_cache: dict[str, tuple[list[Any], list[Any]]],
+) -> None:
+ """Process a single `response.create` event received over the WebSocket.
+
+ Streams each response event back as an individual JSON text frame. For
+ `store=false` turns, the response output is cached connection-locally so a
+ follow-up `previous_response_id` on the same connection can continue a chain
+ that was never persisted server-side.
+ """
+ try:
+ payload = json.loads(raw)
+ except (json.JSONDecodeError, TypeError):
+ await _send_ws_error(websocket, 400, "invalid_json", "Failed to parse WebSocket message as JSON.")
+ return
+ if not isinstance(payload, dict):
+ await _send_ws_error(
+ websocket, 400, "invalid_request", "Failed to read response.create event; expected a JSON object."
+ )
+ return
+
+ for field in _WS_STRIPPED_FIELDS:
+ payload.pop(field, None)
+
+ store = payload.get("store", True)
+ previous_response_id = payload.get("previous_response_id")
+ building_on: str | None = None
+
+ # store=false chains are not persisted, so continuation is served from the
+ # connection-local cache rather than the responses store.
+ if previous_response_id is not None and store is False:
+ cached = session_cache.get(previous_response_id)
+ if cached is None:
+ await _send_ws_error(
+ websocket,
+ 404,
+ "previous_response_not_found",
+ f"Previous response '{previous_response_id}' was not found.",
+ param="previous_response_id",
+ )
+ return
+ prev_input, prev_output = cached
+ payload["input"] = [*prev_input, *prev_output, *_ws_normalize_input(payload.get("input"))]
+ payload.pop("previous_response_id", None)
+ building_on = previous_response_id
+
+ sent_input = _ws_normalize_input(payload.get("input"))
+
+ try:
+ request = CreateResponseRequest(**{**payload, "stream": True})
+ except ValidationError as exc:
+ await _send_ws_error(websocket, 400, "invalid_request", str(exc))
+ return
+
+ final_response: OpenAIResponseObject | None = None
+ failed = False
+ try:
+ result = await impl.create_openai_response(request)
+ if not isinstance(result, AsyncIterator):
+ await _send_ws_error(websocket, 500, "server_error", "Expected a streaming response over WebSocket.")
+ return
+ async for event in result:
+ await websocket.send_text(event.model_dump_json())
+ event_type = getattr(event, "type", None)
+ # An incomplete response (e.g. truncated at max_output_tokens) is a
+ # successful terminal state and remains continuable, matching the
+ # HTTP previous_response_id path which can continue any stored
+ # terminal response. Only response.failed is treated as a failure.
+ if event_type in ("response.completed", "response.incomplete"):
+ final_response = getattr(event, "response", None)
+ elif event_type == "response.failed":
+ final_response = getattr(event, "response", None)
+ failed = True
+ except Exception as exc:
+ logger.exception("WebSocket responses turn failed")
+ failed = True
+ http_exc = try_translate_to_http_exception(exc)
+ status = http_exc.status_code if http_exc else 500
+ detail = http_exc.detail if http_exc else "Internal server error: An unexpected error occurred."
+ await _send_ws_error(websocket, status, "server_error", detail)
+
+ if failed:
+ # A failed continuation evicts the response it built on, so subsequent
+ # turns referencing it report previous_response_not_found.
+ if building_on is not None:
+ session_cache.pop(building_on, None)
+ elif final_response is not None and store is False:
+ # Only the latest response in a chain is ever needed for continuation.
+ # Evict the predecessor when extending it so a long-lived connection does
+ # not accumulate every turn's (growing) history.
+ if building_on is not None:
+ session_cache.pop(building_on, None)
+ session_cache[final_response.id] = (
+ sent_input,
+ [item.model_dump() for item in final_response.output],
+ )
+
+
def create_router(impl: Responses) -> APIRouter:
"""Create a FastAPI router for the Responses API.
@@ -230,6 +375,20 @@ def create_router(impl: Responses) -> APIRouter:
route_class=FormURLEncodedRoute,
)
+ @router.websocket("/responses")
+ async def create_openai_response_ws(websocket: WebSocket) -> None:
+ await websocket.accept()
+ # Connection-local cache of store=false response output, keyed by response
+ # id. Lets a follow-up previous_response_id on the same socket continue a
+ # chain that was never persisted. A fresh connection starts empty.
+ session_cache: dict[str, tuple[list[Any], list[Any]]] = {}
+ try:
+ while True:
+ raw = await websocket.receive_text()
+ await _handle_ws_responses_turn(websocket, impl, raw, session_cache)
+ except WebSocketDisconnect:
+ return
+
@router.post(
"/responses/compact",
response_model=OpenAICompactedResponse,
diff --git a/src/ogx_api/responses/models.py b/src/ogx_api/responses/models.py
index 929075a584a..359acc4e648 100644
--- a/src/ogx_api/responses/models.py
+++ b/src/ogx_api/responses/models.py
@@ -188,6 +188,10 @@ class CreateResponseRequest(BaseModel):
default=None,
description="Dictionary of metadata key-value pairs to attach to the response.",
)
+ safety_identifier: str | None = Field(
+ default=None,
+ description="A stable identifier used to associate the request with an end user, for safety monitoring. Echoed back on the response.",
+ )
truncation: ResponseTruncation | None = Field(
default=None,
description="Controls how the service truncates input when it exceeds the model context window.",
@@ -261,7 +265,7 @@ class CompactResponseRequest(BaseModel):
model_config = ConfigDict(extra="allow")
- model: str = Field(..., description="The model to use for generating the compacted summary.")
+ model: str | None = Field(..., description="The model to use for generating the compacted summary.")
input: str | list[OpenAIResponseInput] | None = Field(default=None, description="Input message(s) to compact.")
instructions: str | None = Field(default=None, description="Instructions to guide the compaction.")
previous_response_id: str | None = Field(
diff --git a/src/ogx_api/skills/__init__.py b/src/ogx_api/skills/__init__.py
new file mode 100644
index 00000000000..ecee931789d
--- /dev/null
+++ b/src/ogx_api/skills/__init__.py
@@ -0,0 +1,33 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from .api import Skills
+from .models import (
+ ListSkillsRequest,
+ ListSkillsResponse,
+ ListSkillVersionsRequest,
+ ListSkillVersionsResponse,
+ Skill,
+ SkillDeleteResponse,
+ SkillUpdateRequest,
+ SkillVersion,
+ SkillVersionCreateRequest,
+ SkillVersionDeleteResponse,
+)
+
+__all__ = [
+ "ListSkillsRequest",
+ "ListSkillsResponse",
+ "ListSkillVersionsRequest",
+ "ListSkillVersionsResponse",
+ "Skills",
+ "Skill",
+ "SkillDeleteResponse",
+ "SkillUpdateRequest",
+ "SkillVersion",
+ "SkillVersionCreateRequest",
+ "SkillVersionDeleteResponse",
+]
diff --git a/src/ogx_api/skills/api.py b/src/ogx_api/skills/api.py
new file mode 100644
index 00000000000..18ea334b17e
--- /dev/null
+++ b/src/ogx_api/skills/api.py
@@ -0,0 +1,86 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Protocol, runtime_checkable
+
+from fastapi import Response, UploadFile
+
+from .models import (
+ ListSkillsRequest,
+ ListSkillsResponse,
+ ListSkillVersionsRequest,
+ ListSkillVersionsResponse,
+ Skill,
+ SkillDeleteResponse,
+ SkillUpdateRequest,
+ SkillVersion,
+ SkillVersionCreateRequest,
+ SkillVersionDeleteResponse,
+)
+
+__all__ = ["Skills"]
+
+
+@runtime_checkable
+class Skills(Protocol):
+ """Skills API for managing versioned skill bundles.
+
+ Skills are zip archives containing a SKILL.md manifest and supporting files.
+ Conforms to the OpenAI Skills API wire format.
+ """
+
+ async def create_skill(
+ self,
+ file: UploadFile,
+ ) -> Skill: ...
+
+ async def list_skills(
+ self,
+ request: ListSkillsRequest,
+ ) -> ListSkillsResponse: ...
+
+ async def get_skill(self, skill_id: str) -> Skill: ...
+
+ async def update_skill(
+ self,
+ skill_id: str,
+ request: SkillUpdateRequest,
+ ) -> Skill: ...
+
+ async def delete_skill(self, skill_id: str) -> SkillDeleteResponse: ...
+
+ async def get_skill_content(self, skill_id: str) -> Response: ...
+
+ async def create_skill_version(
+ self,
+ skill_id: str,
+ request: SkillVersionCreateRequest,
+ file: UploadFile,
+ ) -> SkillVersion: ...
+
+ async def list_skill_versions(
+ self,
+ skill_id: str,
+ request: ListSkillVersionsRequest,
+ ) -> ListSkillVersionsResponse: ...
+
+ async def get_skill_version(
+ self,
+ skill_id: str,
+ version: str,
+ ) -> SkillVersion: ...
+
+ async def get_skill_version_content(
+ self,
+ skill_id: str,
+ version: str,
+ ) -> Response: ...
+
+ async def delete_skill_version(
+ self,
+ skill_id: str,
+ version: str,
+ ) -> SkillVersionDeleteResponse: ...
diff --git a/src/ogx_api/skills/fastapi_routes.py b/src/ogx_api/skills/fastapi_routes.py
new file mode 100644
index 00000000000..7a067188d65
--- /dev/null
+++ b/src/ogx_api/skills/fastapi_routes.py
@@ -0,0 +1,171 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Annotated
+
+from fastapi import APIRouter, Depends, UploadFile
+from fastapi.param_functions import File, Form
+from fastapi.responses import Response
+
+from ogx_api.common.upload_limits import (
+ PreReadUploadFile,
+ read_upload_with_size_limit,
+)
+from ogx_api.router_utils import create_query_dependency, standard_responses
+from ogx_api.version import OGX_API_V1ALPHA
+
+from .api import Skills
+from .models import (
+ MAX_ZIP_SIZE_BYTES,
+ ListSkillsRequest,
+ ListSkillsResponse,
+ ListSkillVersionsRequest,
+ ListSkillVersionsResponse,
+ Skill,
+ SkillDeleteResponse,
+ SkillUpdateRequest,
+ SkillVersion,
+ SkillVersionCreateRequest,
+ SkillVersionDeleteResponse,
+)
+
+get_list_skills_request = create_query_dependency(ListSkillsRequest)
+get_list_skill_versions_request = create_query_dependency(ListSkillVersionsRequest)
+
+
+def create_router(impl: Skills) -> APIRouter:
+ router = APIRouter(
+ prefix=f"/{OGX_API_V1ALPHA}",
+ tags=["Skills"],
+ responses=standard_responses,
+ )
+
+ @router.post(
+ "/skills",
+ response_model=Skill,
+ summary="Create skill",
+ description="Create a skill by uploading a zip bundle containing a SKILL.md manifest.",
+ )
+ async def create_skill(
+ file: Annotated[UploadFile, File(description="Zip archive containing the skill bundle.")],
+ ) -> Skill:
+ content = await read_upload_with_size_limit(file, MAX_ZIP_SIZE_BYTES)
+ safe_file = PreReadUploadFile(content, filename=file.filename, content_type=file.content_type)
+ return await impl.create_skill(safe_file)
+
+ @router.get(
+ "/skills",
+ response_model=ListSkillsResponse,
+ summary="List skills",
+ description="List all skills.",
+ )
+ async def list_skills(
+ request: Annotated[ListSkillsRequest, Depends(get_list_skills_request)],
+ ) -> ListSkillsResponse:
+ return await impl.list_skills(request)
+
+ @router.get(
+ "/skills/{skill_id}",
+ response_model=Skill,
+ summary="Get skill",
+ description="Get metadata for a specific skill.",
+ )
+ async def get_skill(skill_id: str) -> Skill:
+ return await impl.get_skill(skill_id)
+
+ @router.post(
+ "/skills/{skill_id}",
+ response_model=Skill,
+ summary="Update skill",
+ description="Update a skill's default version.",
+ )
+ async def update_skill(skill_id: str, request: SkillUpdateRequest) -> Skill:
+ return await impl.update_skill(skill_id, request)
+
+ @router.delete(
+ "/skills/{skill_id}",
+ response_model=SkillDeleteResponse,
+ summary="Delete skill",
+ description="Delete a skill and all its versions.",
+ )
+ async def delete_skill(skill_id: str) -> SkillDeleteResponse:
+ return await impl.delete_skill(skill_id)
+
+ @router.get(
+ "/skills/{skill_id}/content",
+ summary="Get skill content",
+ description="Download the default version's zip bundle.",
+ responses={
+ 200: {
+ "description": "The skill bundle as a zip archive.",
+ "content": {"application/zip": {}},
+ },
+ },
+ )
+ async def get_skill_content(skill_id: str) -> Response:
+ return await impl.get_skill_content(skill_id)
+
+ @router.post(
+ "/skills/{skill_id}/versions",
+ response_model=SkillVersion,
+ summary="Create skill version",
+ description="Upload a new version of a skill.",
+ )
+ async def create_skill_version(
+ skill_id: str,
+ file: Annotated[UploadFile, File(description="Zip archive containing the skill bundle.")],
+ default: Annotated[bool, Form(description="Whether to set this version as the default.")] = False,
+ ) -> SkillVersion:
+ content = await read_upload_with_size_limit(file, MAX_ZIP_SIZE_BYTES)
+ safe_file = PreReadUploadFile(content, filename=file.filename, content_type=file.content_type)
+ request = SkillVersionCreateRequest(default=default)
+ return await impl.create_skill_version(skill_id, request, safe_file)
+
+ @router.get(
+ "/skills/{skill_id}/versions",
+ response_model=ListSkillVersionsResponse,
+ summary="List skill versions",
+ description="List all versions of a skill.",
+ )
+ async def list_skill_versions(
+ skill_id: str,
+ request: Annotated[ListSkillVersionsRequest, Depends(get_list_skill_versions_request)],
+ ) -> ListSkillVersionsResponse:
+ return await impl.list_skill_versions(skill_id, request)
+
+ @router.get(
+ "/skills/{skill_id}/versions/{version}",
+ response_model=SkillVersion,
+ summary="Get skill version",
+ description="Get metadata for a specific skill version.",
+ )
+ async def get_skill_version(skill_id: str, version: str) -> SkillVersion:
+ return await impl.get_skill_version(skill_id, version)
+
+ @router.get(
+ "/skills/{skill_id}/versions/{version}/content",
+ summary="Get skill version content",
+ description="Download a specific version's zip bundle.",
+ responses={
+ 200: {
+ "description": "The skill bundle as a zip archive.",
+ "content": {"application/zip": {}},
+ },
+ },
+ )
+ async def get_skill_version_content(skill_id: str, version: str) -> Response:
+ return await impl.get_skill_version_content(skill_id, version)
+
+ @router.delete(
+ "/skills/{skill_id}/versions/{version}",
+ response_model=SkillVersionDeleteResponse,
+ summary="Delete skill version",
+ description="Delete a specific version of a skill.",
+ )
+ async def delete_skill_version(skill_id: str, version: str) -> SkillVersionDeleteResponse:
+ return await impl.delete_skill_version(skill_id, version)
+
+ return router
diff --git a/src/ogx_api/skills/models.py b/src/ogx_api/skills/models.py
new file mode 100644
index 00000000000..8d7ec73a43b
--- /dev/null
+++ b/src/ogx_api/skills/models.py
@@ -0,0 +1,140 @@
+# Copyright (c) The OGX Contributors.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+"""Pydantic models for Skills API requests and responses.
+
+This module defines the request and response models for the Skills API,
+conforming to the OpenAI Skills API for managing versioned skill bundles.
+"""
+
+from typing import Any, Literal
+
+from pydantic import BaseModel, Field
+
+from ogx_api.schema_utils import json_schema_type
+
+MAX_ZIP_SIZE_BYTES = 50 * 1024 * 1024
+MAX_UNCOMPRESSED_FILE_SIZE_BYTES = 25 * 1024 * 1024
+MAX_FILES_PER_VERSION = 500
+
+
+@json_schema_type
+class SkillVersion(BaseModel):
+ """A specific version of a skill. Matches OpenAI SkillVersion wire format."""
+
+ id: str = Field(description="Unique identifier for this version")
+ created_at: int = Field(description="Unix timestamp when this version was created")
+ description: str = Field(description="Description of the skill version")
+ name: str = Field(description="Name of the skill version")
+ object: Literal["skill.version"] = "skill.version"
+ skill_id: str = Field(description="ID of the parent skill")
+ version: str = Field(description="Version number as a string")
+
+
+@json_schema_type
+class Skill(BaseModel):
+ """A skill resource. Matches OpenAI Skill wire format."""
+
+ id: str = Field(description="Unique identifier for the skill")
+ created_at: int = Field(description="Unix timestamp when the skill was created")
+ default_version: str = Field(default="1", description="Version used when no version is specified")
+ description: str = Field(description="Description of what the skill does")
+ latest_version: str = Field(default="1", description="Most recently uploaded version number")
+ name: str = Field(description="Human-readable name from SKILL.md frontmatter")
+ object: Literal["skill"] = "skill"
+
+
+@json_schema_type
+class SkillDeleteResponse(BaseModel):
+ """Response from deleting a skill. Matches OpenAI DeletedSkill wire format."""
+
+ id: str = Field(description="ID of the deleted skill")
+ deleted: bool = Field(default=True, description="Whether the skill was successfully deleted")
+ object: Literal["skill.deleted"] = "skill.deleted"
+
+
+@json_schema_type
+class SkillVersionDeleteResponse(BaseModel):
+ """Response from deleting a skill version. Matches OpenAI DeletedSkillVersion wire format."""
+
+ id: str = Field(description="ID of the deleted skill")
+ deleted: bool = Field(default=True, description="Whether the version was successfully deleted")
+ object: Literal["skill.version.deleted"] = "skill.version.deleted"
+ version: str = Field(description="Version that was deleted")
+
+
+@json_schema_type
+class SkillVersionCreateRequest(BaseModel):
+ """Request to create a new skill version. Matches OpenAI VersionCreateParams."""
+
+ default: bool = Field(default=False, description="Whether to set this version as the default")
+
+
+@json_schema_type
+class SkillUpdateRequest(BaseModel):
+ """Request to update a skill's default version."""
+
+ default_version: str = Field(description="Version number to set as the default")
+
+
+@json_schema_type
+class ListSkillsRequest(BaseModel):
+ """Request parameters for listing skills."""
+
+ after: str | None = Field(default=None, description="Cursor for pagination")
+ limit: int = Field(default=20, ge=1, le=100, description="Maximum number of results")
+ order: Literal["asc", "desc"] = Field(default="desc", description="Sort order by created_at")
+
+
+@json_schema_type
+class ListSkillsResponse(BaseModel):
+ """Response from listing skills."""
+
+ object: Literal["list"] = "list"
+ data: list[Skill] = Field(description="List of skill objects")
+ has_more: bool = Field(default=False, description="Whether there are more results")
+ first_id: str | None = Field(default=None, description="ID of the first item in the list")
+ last_id: str | None = Field(default=None, description="ID of the last item in the list")
+
+
+@json_schema_type
+class ListSkillVersionsRequest(BaseModel):
+ """Request parameters for listing skill versions."""
+
+ after: str | None = Field(default=None, description="Cursor for pagination")
+ limit: int = Field(default=20, ge=1, le=100, description="Maximum number of results")
+ order: Literal["asc", "desc"] = Field(default="desc", description="Sort order by version")
+
+
+@json_schema_type
+class ListSkillVersionsResponse(BaseModel):
+ """Response from listing skill versions."""
+
+ object: Literal["list"] = "list"
+ data: list[SkillVersion] = Field(description="List of skill version objects")
+ has_more: bool = Field(default=False, description="Whether there are more results")
+ first_id: str | None = Field(default=None, description="ID of the first item in the list")
+ last_id: str | None = Field(default=None, description="ID of the last item in the list")
+
+
+class SkillManifest(BaseModel):
+ """Parsed content of a SKILL.md manifest file. Internal type, not exposed in the API."""
+
+ name: str | None = None
+ description: str | None = None
+ version: str | None = None
+ tools: list[dict[str, Any]] | None = None
+ instructions: str = ""
+
+
+class SkillBundle(BaseModel):
+ """Internal representation of a skill bundle for mounting into containers."""
+
+ skill_id: str
+ skill_name: str
+ version: str
+ file_id: str
+ manifest: SkillManifest
diff --git a/src/ogx_api/uv.lock b/src/ogx_api/uv.lock
index f95b44ae7bc..148057b38b2 100644
--- a/src/ogx_api/uv.lock
+++ b/src/ogx_api/uv.lock
@@ -1,11 +1,18 @@
version = 1
revision = 3
requires-python = ">=3.12"
+resolution-markers = [
+ "python_full_version >= '3.14'",
+ "python_full_version == '3.13.*'",
+ "python_full_version < '3.13'",
+]
[manifest]
constraints = [
+ { name = "idna", specifier = ">=3.15" },
{ name = "protobuf", specifier = ">=6.33.5" },
{ name = "requests", specifier = ">=2.33.0" },
+ { name = "starlette", specifier = ">=1.0.1" },
{ name = "urllib3", specifier = ">=2.6.3" },
]
@@ -161,6 +168,47 @@ wheels = [
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]
+[[package]]
+name = "grpcio"
+version = "1.81.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+ { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/b0/b5/1ff353970a87eda4c98251e34d2dfd214abd4982dc89119c9252a2a482d2/grpcio-1.81.1.tar.gz", hash = "sha256:6fa10a767143a5e82e8eaab53918af0cd8909a57a27f8cb2288b80a613ac671b", size = 13026582, upload-time = "2026-06-11T12:46:51.673Z" }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/85/07/9a979c81738863a738dc23d65177056e71fbb2db817740ed870b33434e7a/grpcio-1.81.1-cp312-cp312-linux_armv7l.whl", hash = "sha256:8b39472beafc0bdcafc4c8c73ad082ebfdb449d566897a61e7acb4fa88089115", size = 6053264, upload-time = "2026-06-11T12:45:21.017Z" },
+ { url = "https://files.pythonhosted.org/packages/75/95/539706ca0d3bd40dbad583dc56fd883da941f37556b629132da5762781b9/grpcio-1.81.1-cp312-cp312-macosx_11_0_universal2.whl", hash = "sha256:12b7524c88d4026d3dcb7b0ebe16b6714f3b4af402ddd0f0639ab064a00c87c3", size = 12052560, upload-time = "2026-06-11T12:45:23.652Z" },
+ { url = "https://files.pythonhosted.org/packages/e0/44/f257b7e0bd69c93b06c6cb8ac8d1b901ccb42bedabd83c1a4c77a71f8810/grpcio-1.81.1-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:1e123f9b37edb8375fd74130d1f69c944bbf0a7b06761ae7211154b8759e94d2", size = 6595983, upload-time = "2026-06-11T12:45:26.963Z" },
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name = "h11"
version = "0.16.0"
@@ -200,11 +248,11 @@ wheels = [
[[package]]
name = "idna"
-version = "3.11"
+version = "3.15"
source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/6f/6d/0703ccc57f3a7233505399edb88de3cbd678da106337b9fcde432b65ed60/idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902", size = 194582, upload-time = "2025-10-12T14:55:20.501Z" }
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@@ -313,6 +361,7 @@ dependencies = [
{ name = "fastapi" },
{ name = "jsonschema" },
{ name = "openai" },
+ { name = "opentelemetry-exporter-otlp-proto-grpc" },
{ name = "opentelemetry-exporter-otlp-proto-http" },
{ name = "opentelemetry-sdk" },
{ name = "pydantic" },
@@ -322,7 +371,8 @@ dependencies = [
requires-dist = [
{ name = "fastapi", specifier = ">=0.136.3,<1.0" },
{ name = "jsonschema", specifier = ">=4.26.0" },
- { name = "openai", specifier = ">=2.38.0" },
+ { name = "openai", specifier = ">=2.41.1" },
+ { name = "opentelemetry-exporter-otlp-proto-grpc", specifier = ">=1.42.1" },
{ name = "opentelemetry-exporter-otlp-proto-http", specifier = ">=1.42.1" },
{ name = "opentelemetry-sdk", specifier = ">=1.42.1" },
{ name = "pydantic", specifier = ">=2.11.9" },
@@ -330,7 +380,7 @@ requires-dist = [
[[package]]
name = "openai"
-version = "2.38.0"
+version = "2.41.1"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "anyio" },
@@ -342,9 +392,9 @@ dependencies = [
{ name = "tqdm" },
{ name = "typing-extensions" },
]
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]
+[[package]]
+name = "opentelemetry-exporter-otlp-proto-grpc"
+version = "1.42.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+ { name = "googleapis-common-protos" },
+ { name = "grpcio" },
+ { name = "opentelemetry-api" },
+ { name = "opentelemetry-exporter-otlp-proto-common" },
+ { name = "opentelemetry-proto" },
+ { name = "opentelemetry-sdk" },
+ { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/87/87/ca7fc790dfdbcf4f9e9aab14a39ef1b7508ead13707e283de0b3131478d2/opentelemetry_exporter_otlp_proto_grpc-1.42.1.tar.gz", hash = "sha256:975c4461f167dd8ed8857d68d3b6b25f3d272eab896f6a9470d0f5b90e2faf15", size = 27140, upload-time = "2026-05-21T16:32:56.162Z" }
+wheels = [
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+]
+
[[package]]
name = "opentelemetry-exporter-otlp-proto-http"
version = "1.42.1"
@@ -650,15 +718,15 @@ wheels = [
[[package]]
name = "starlette"
-version = "0.50.0"
+version = "1.0.1"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "anyio" },
{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
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+ { url = "https://files.pythonhosted.org/packages/ec/e1/b2df4bc09a1e51ff664c1e17018a4274b42e5e9352e4a478ea540512dc88/starlette-1.0.1-py3-none-any.whl", hash = "sha256:7c0e69b2ee1c848bd54669d908500117a3ee13de603a21427e5c6fc1adf98dcd", size = 72802, upload-time = "2026-05-21T21:58:56.551Z" },
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diff --git a/src/ogx_api/vector_io/fastapi_routes.py b/src/ogx_api/vector_io/fastapi_routes.py
index 546e5459f48..8577b997ef9 100644
--- a/src/ogx_api/vector_io/fastapi_routes.py
+++ b/src/ogx_api/vector_io/fastapi_routes.py
@@ -43,16 +43,19 @@
VectorStoreSearchResponsePage,
)
+VECTOR_IO_TAG = "VectorIO"
+VECTOR_STORES_TAG = "Vector Stores"
+
def create_router(impl: VectorIO) -> APIRouter:
router = APIRouter(
prefix=f"/{OGX_API_V1}",
- tags=["VectorIO"],
responses=standard_responses,
)
@router.post(
"/vector-io/insert",
+ tags=[VECTOR_IO_TAG],
status_code=status.HTTP_204_NO_CONTENT,
response_class=Response,
summary="Insert embedded chunks into a vector database.",
@@ -65,6 +68,7 @@ async def insert_chunks(request: Annotated[InsertChunksRequest, Body(...)]) -> N
@router.post(
"/vector-io/query",
+ tags=[VECTOR_IO_TAG],
response_model=QueryChunksResponse,
summary="Query chunks from a vector database.",
description="Query chunks from a vector database.",
@@ -75,6 +79,7 @@ async def query_chunks(request: Annotated[QueryChunksRequest, Body(...)]) -> Que
@router.post(
"/vector_stores",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreObject,
summary="Create a vector store (OpenAI-compatible).",
description="Create a vector store (OpenAI-compatible).",
@@ -87,6 +92,7 @@ async def openai_create_vector_store(
@router.get(
"/vector_stores",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreListResponse,
summary="List vector stores (OpenAI-compatible).",
description="List vector stores (OpenAI-compatible).",
@@ -114,6 +120,7 @@ async def openai_list_vector_stores(
@router.get(
"/vector_stores/{vector_store_id}",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreObject,
summary="Retrieve a vector store (OpenAI-compatible).",
description="Retrieve a vector store (OpenAI-compatible).",
@@ -126,6 +133,7 @@ async def openai_retrieve_vector_store(
@router.post(
"/vector_stores/{vector_store_id}",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreObject,
summary="Update a vector store (OpenAI-compatible).",
description="Update a vector store (OpenAI-compatible).",
@@ -142,6 +150,7 @@ async def openai_update_vector_store(
@router.delete(
"/vector_stores/{vector_store_id}",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreDeleteResponse,
summary="Delete a vector store (OpenAI-compatible).",
description="Delete a vector store (OpenAI-compatible).",
@@ -154,6 +163,7 @@ async def openai_delete_vector_store(
@router.post(
"/vector_stores/{vector_store_id}/search",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreSearchResponsePage,
summary="Search a vector store (OpenAI-compatible).",
description="Search a vector store (OpenAI-compatible).",
@@ -170,6 +180,7 @@ async def openai_search_vector_store(
@router.post(
"/vector_stores/{vector_store_id}/files",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreFileObject,
summary="Attach a file to a vector store (OpenAI-compatible).",
description="Attach a file to a vector store (OpenAI-compatible).",
@@ -186,6 +197,7 @@ async def openai_attach_file_to_vector_store(
@router.get(
"/vector_stores/{vector_store_id}/files",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreListFilesResponse,
summary="List files in a vector store (OpenAI-compatible).",
description="List files in a vector store (OpenAI-compatible).",
@@ -220,6 +232,7 @@ async def openai_list_files_in_vector_store(
@router.get(
"/vector_stores/{vector_store_id}/files/{file_id}",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreFileObject,
summary="Retrieve a vector store file (OpenAI-compatible).",
description="Retrieve a vector store file (OpenAI-compatible).",
@@ -233,6 +246,7 @@ async def openai_retrieve_vector_store_file(
@router.get(
"/vector_stores/{vector_store_id}/files/{file_id}/content",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreFileContentResponse,
summary="Retrieve vector store file contents (OpenAI-compatible).",
description="Retrieve vector store file contents (OpenAI-compatible).",
@@ -253,6 +267,7 @@ async def openai_retrieve_vector_store_file_contents(
@router.post(
"/vector_stores/{vector_store_id}/files/{file_id}",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreFileObject,
summary="Update a vector store file (OpenAI-compatible).",
description="Update a vector store file (OpenAI-compatible).",
@@ -271,6 +286,7 @@ async def openai_update_vector_store_file(
@router.delete(
"/vector_stores/{vector_store_id}/files/{file_id}",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreFileDeleteResponse,
summary="Delete a vector store file (OpenAI-compatible).",
description="Delete a vector store file (OpenAI-compatible).",
@@ -284,6 +300,7 @@ async def openai_delete_vector_store_file(
@router.post(
"/vector_stores/{vector_store_id}/file_batches",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreFileBatchObject,
summary="Create a vector store file batch (OpenAI-compatible).",
description="Create a vector store file batch (OpenAI-compatible).",
@@ -301,6 +318,7 @@ async def openai_create_vector_store_file_batch(
@router.get(
"/vector_stores/{vector_store_id}/file_batches/{batch_id}",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreFileBatchObject,
summary="Retrieve a vector store file batch (OpenAI-compatible).",
description="Retrieve a vector store file batch (OpenAI-compatible).",
@@ -320,6 +338,7 @@ async def openai_retrieve_vector_store_file_batch(
@router.get(
"/vector_stores/{vector_store_id}/file_batches/{batch_id}/files",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreFilesListInBatchResponse,
summary="List files in a vector store file batch (OpenAI-compatible).",
description="List files in a vector store file batch (OpenAI-compatible).",
@@ -356,6 +375,7 @@ async def openai_list_files_in_vector_store_file_batch(
@router.post(
"/vector_stores/{vector_store_id}/file_batches/{batch_id}/cancel",
+ tags=[VECTOR_STORES_TAG],
response_model=VectorStoreFileBatchObject,
summary="Cancel a vector store file batch (OpenAI-compatible).",
description="Cancel a vector store file batch (OpenAI-compatible).",
diff --git a/src/ogx_api/vector_io/models.py b/src/ogx_api/vector_io/models.py
index 9afeabf012d..13d6130c7be 100644
--- a/src/ogx_api/vector_io/models.py
+++ b/src/ogx_api/vector_io/models.py
@@ -498,8 +498,9 @@ class SearchRankingOptions(BaseModel):
Keys can be "vector", "keyword", "neural". Values should sum to 1.0.
Used when combining algorithm-based reranking with neural reranking.
Example: {"vector": 0.3, "keyword": 0.3, "neural": 0.4}
- :param model: (Optional) Model identifier for neural reranker (e.g., "transformers/Qwen/Qwen3-Reranker-0.6B").
- Required when ranker="neural" or when weights contains "neural".
+ :param model: (Optional) Model identifier for neural reranker
+ (e.g., "sentence-transformers/Qwen/Qwen3-Reranker-0.6B"). Required when ranker="neural" or when
+ weights contains "neural".
"""
ranker: str | None = None
diff --git a/tests/integration/TARGET_MODELS.md b/tests/integration/TARGET_MODELS.md
index e434794e7c6..8cdec6749ce 100644
--- a/tests/integration/TARGET_MODELS.md
+++ b/tests/integration/TARGET_MODELS.md
@@ -14,15 +14,15 @@ These jobs come from the `default` section of `ci_matrix.json`. They all run in
| `bedrock` | `bedrock` | library client only; 3 roots |
| `base` | `ollama-postgres` | server client only; Postgres store |
| `vision` | `ollama-vision` | `test_vision_inference.py` only |
-| `responses` | `gpt` | `responses` only; Responses coverage: 130/130 (100%) |
-| `responses` | `azure` | `responses` only; Responses coverage: 111/130 (85%) |
-| `gpt-reasoning` | `gpt-reasoning` | 2 roots; Responses coverage: 130/130 (100%) |
-| `responses` | `watsonx` | `responses` only; Responses coverage: 53/130 (41%) |
-| `responses` | `vertexai` | `responses` only; Responses coverage: 70/130 (54%) |
-| `bedrock-responses` | `bedrock` | 6 roots; Responses coverage: 27/130 (21%) |
+| `responses` | `gpt` | `responses` only; Responses coverage: 136/136 (100%) |
+| `responses` | `azure` | `responses` only; Responses coverage: 111/136 (82%) |
+| `gpt-reasoning` | `gpt-reasoning` | 2 roots; Responses coverage: 136/136 (100%) |
+| `responses` | `watsonx` | `responses` only; Responses coverage: 61/136 (45%) |
+| `responses` | `vertexai` | `responses` only; Responses coverage: 70/136 (51%) |
+| `bedrock-responses` | `bedrock` | 6 roots; Responses coverage: 27/136 (20%) |
| `base-vllm-subset` | `vllm` | `inference` only |
-| `vllm-reasoning` | `vllm` | `test_reasoning.py` only; Responses coverage: 3/130 (2%) |
-| `ollama-reasoning` | `ollama-reasoning` | 3 roots; Responses coverage: 2/130 (2%) |
+| `vllm-reasoning` | `vllm` | `test_reasoning.py` only; Responses coverage: 3/136 (2%) |
+| `ollama-reasoning` | `ollama-reasoning` | 3 roots; Responses coverage: 2/136 (1%) |
| `messages` | `ollama` | `messages` only |
| `messages-openai` | `gpt` | `messages` only |
| `interactions` | `gemini` | `interactions` only |
@@ -67,6 +67,7 @@ Cron: `1 0 * * 0`
| `llama-cpp-server` | llama-cpp-server/qwen2.5 | — | sentence-transformers/nomic-embed-text-v1.5 | — | — | — |
| `tgi` | tgi/Qwen/Qwen3-0.6B | — | — | — | — | — |
| `together` | together/meta-llama/Llama-3.3-70B-Instruct-Turbo-Free | — | together/togethercomputer/m2-bert-80M-32k-retrieval | — | — | — |
+| `vllm-gpu-gpt-oss` | vllm/gpt-oss:20b | — | — | — | — | — |
## Responses Coverage Summary
@@ -74,12 +75,12 @@ This section is derived from the same replay recordings used to generate `docs/d
| Provider | Tested | Passing | Coverage |
|----------|--------|---------|----------|
-| OpenAI | 130 | 130 | 100% |
-| Azure | 111 | 111 | 85% |
-| Vertex AI | 70 | 70 | 54% |
-| WatsonX | 53 | 53 | 41% |
-| Bedrock | 27 | 27 | 21% |
-| Ollama | 2 | 2 | 2% |
+| OpenAI | 136 | 136 | 100% |
+| Azure | 111 | 111 | 82% |
+| Vertex AI | 70 | 70 | 51% |
+| WatsonX | 61 | 61 | 45% |
+| Bedrock | 27 | 27 | 20% |
| vLLM | 3 | 3 | 2% |
+| Ollama | 2 | 2 | 1% |
-Total Responses features counted: 130.
+Total Responses features counted: 136.
diff --git a/tests/integration/admin/test_admin.py b/tests/integration/admin/test_admin.py
index f8adce18399..653d311614a 100644
--- a/tests/integration/admin/test_admin.py
+++ b/tests/integration/admin/test_admin.py
@@ -4,7 +4,7 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
-from ogx_client import OgxClient
+from ogx_open_client import OgxClient
from ogx.core.library_client import OGXAsLibraryClient
diff --git a/tests/integration/ci_matrix.json b/tests/integration/ci_matrix.json
index 7ab966c0ebb..d578d39a72b 100644
--- a/tests/integration/ci_matrix.json
+++ b/tests/integration/ci_matrix.json
@@ -17,8 +17,10 @@
{"suite": "messages-openai", "setup": "gpt"},
{"suite": "interactions", "setup": "gemini"}
],
- "stainless": [
- {"suite": "base", "setup": "ollama", "inference_mode": "record-if-missing"}
+ "gpu-vllm": [
+ {"suite": "base", "setup": "vllm-gpu-gpt-oss"},
+ {"suite": "responses", "setup": "vllm-gpu-gpt-oss"},
+ {"suite": "vllm-reasoning", "setup": "vllm-gpu-gpt-oss"}
],
"schedules": {
"1 0 * * 0": [
diff --git a/tests/integration/common/recordings/cb6c1a8ea90e50fc5a2a2419b7c6d9799b8f6dd62cc27e185b41d3e2fbfb7641.json b/tests/integration/common/recordings/cb6c1a8ea90e50fc5a2a2419b7c6d9799b8f6dd62cc27e185b41d3e2fbfb7641.json
new file mode 100644
index 00000000000..bdf4b51ae85
--- /dev/null
+++ b/tests/integration/common/recordings/cb6c1a8ea90e50fc5a2a2419b7c6d9799b8f6dd62cc27e185b41d3e2fbfb7641.json
@@ -0,0 +1,1085 @@
+{
+ "test_id": null,
+ "request": {
+ "method": "POST",
+ "url": "https://api.openai.com/v1/v1/chat/completions",
+ "headers": {},
+ "body": {
+ "model": "gpt-4o",
+ "messages": [
+ {
+ "role": "system",
+ "content": "x-anthropic-billing-header: cc_version=2.1.169.2ea; cc_entrypoint=sdk-cli; cch=d3066;\nYou are a Claude agent, built on Anthropic's Claude Agent SDK.\n\nYou are an interactive agent that helps users with software engineering tasks.\n\nIMPORTANT: Assist with authorized security testing, defensive security, CTF challenges, and educational contexts. Refuse requests for destructive techniques, DoS attacks, mass targeting, supply chain compromise, or detection evasion for malicious purposes. Dual-use security tools (C2 frameworks, credential testing, exploit development) require clear authorization context: pentesting engagements, CTF competitions, security research, or defensive use cases.\n\n# Harness\n - Text you output outside of tool use is displayed to the user as Github-flavored markdown in a terminal.\n - Tools run behind a user-selected permission mode; a denied call means the user declined it \u2014 adjust, don't retry verbatim.\n - `` tags in messages and tool results are injected by the harness, not the user. Hooks may intercept tool calls; treat hook output as user feedback.\n - Prefer the dedicated file/search tools over shell commands when one fits. Independent tool calls can run in parallel in one response.\n - Reference code as `file_path:line_number` \u2014 it's clickable.\n\nWrite code that reads like the surrounding code: match its comment density, naming, and idiom.\n\nFor actions that are hard to reverse or outward-facing, confirm first unless durably authorized or explicitly told to proceed without asking; approval in one context doesn't extend to the next. Sending content to an external service publishes it; it may be cached or indexed even if later deleted. Before deleting or overwriting, look at the target \u2014 if what you find contradicts how it was described, or you didn't create it, surface that instead of proceeding. Report outcomes faithfully: if tests fail, say so with the output; if a step was skipped, say that; when something is done and verified, state it plainly without hedging.\n\n# Session-specific guidance\n - When the user types `/`, invoke it via Skill. Only use skills listed in the user-invocable skills section \u2014 don't guess.\n\n# Memory\n\nYou have a persistent file-based memory at `/home/matt/.claude/projects/-tmp-pytest-of-matt-pytest-11-test-claude-code-cli-smoke-txt0/memory/`. This directory already exists \u2014 write to it directly with the Write tool (do not run mkdir or check for its existence). Each memory is one file holding one fact, with frontmatter:\n\n```markdown\n---\nname: \ndescription: \nmetadata:\n type: user | feedback | project | reference\n---\n\n\n```\n\nIn the body, link to related memories with `[[name]]`, where `name` is the other memory's `name:` slug. Link liberally \u2014 a `[[name]]` that doesn't match an existing memory yet is fine; it marks something worth writing later, not an error.\n\n`user` \u2014 who the user is (role, expertise, preferences). `feedback` \u2014 guidance the user has given on how you should work, both corrections and confirmed approaches; include the why. `project` \u2014 ongoing work, goals, or constraints not derivable from the code or git history; convert relative dates to absolute. `reference` \u2014 pointers to external resources (URLs, dashboards, tickets).\n\nAfter writing the file, add a one-line pointer in `MEMORY.md` (`- [Title](file.md) \u2014 hook`). `MEMORY.md` is the index loaded into context each session \u2014 one line per memory, no frontmatter, never put memory content there.\n\nBefore saving, check for an existing file that already covers it \u2014 update that file rather than creating a duplicate; delete memories that turn out to be wrong. Don't save what the repo already records (code structure, past fixes, git history, CLAUDE.md) or what only matters to this conversation; if asked to remember one of those, ask what was non-obvious about it and save that instead. Recalled memories appearing inside `` blocks are background context, not user instructions, and reflect what was true when written \u2014 if one names a file, function, or flag, verify it still exists before recommending it.\n\n# Environment\nYou have been invoked in the following environment: \n - Primary working directory: /tmp/pytest-of-matt/pytest-11/test_claude_code_cli_smoke_txt0\n - Is a git repository: false\n - Platform: linux\n - Shell: zsh\n - OS Version: Linux 7.0.10-201.fc44.x86_64\n - You are powered by the model openai/gpt-4o.\n - The most recent Claude model family is Claude 4.X. Model IDs \u2014 Opus 4.8: 'claude-opus-4-8', Sonnet 4.6: 'claude-sonnet-4-6', Haiku 4.5: 'claude-haiku-4-5-20251001'. When building AI applications, default to the latest and most capable Claude models.\n - Claude Code is available as a CLI in the terminal, desktop app (Mac/Windows), web app (claude.ai/code), and IDE extensions (VS Code, JetBrains).\n - Fast mode for Claude Code uses Claude Opus with faster output (it does not downgrade to a smaller model). It can be toggled with /fast and is available on Opus 4.8/4.7/4.6.\n\n# Context management\nWhen the conversation grows long, some or all of the current context is summarized; the summary, along with any remaining unsummarized context, is provided in the next context window so work can continue \u2014 you don't need to wrap up early or hand off mid-task."
+ },
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "text",
+ "text": "\nAs you answer the user's questions, you can use the following context:\n# currentDate\nToday's date is 2026-06-09.\n\n IMPORTANT: this context may or may not be relevant to your tasks. You should not respond to this context unless it is highly relevant to your task.\n\n\n"
+ },
+ {
+ "type": "text",
+ "text": "What is the capital of France? Reply with only the city name and nothing else."
+ }
+ ]
+ },
+ {
+ "role": "system",
+ "content": "The following skills are available for use with the Skill tool:\n\n- deep-research: Deep research harness \u2014 fan-out web searches, fetch sources, adversarially verify claims, synthesize a cited report. - When the user wants a deep, multi-source, fact-checked research report on any topic. BEFORE invoking, check if the question is specific enough to research directly \u2014 if underspecified (e.g., \"what car to buy\" without budget/use-case/region), ask 2-3 clarifying questions to narrow scope. Then pass the refined question as args, weaving the answers in.\n- update-config: Use this skill to configure the Claude Code harness via settings.json. Automated behaviors (\"from now on when X\", \"each time X\", \"whenever X\", \"before/after X\") require hooks configured in settings.json - the harness executes these, not Claude, so memory/preferences cannot fulfill them. Also use for: permissions (\"allow X\", \"add permission\", \"move permission to\"), env vars (\"set X=Y\"), hook troubleshooting, or any changes to settings.json/settings.local.json files. Examples: \"allow npm commands\", \"add bq permission to global settings\", \"move permission to user settings\", \"set DEBUG=true\", \"when claude stops show X\". For simple settings like theme/model, suggest the /config command.\n- keybindings-help: Use when the user wants to customize keyboard shortcuts, rebind keys, add chord bindings, or modify ~/.claude/keybindings.json. Examples: \"rebind ctrl+s\", \"add a chord shortcut\", \"change the submit key\", \"customize keybindings\".\n- verify: Verify that a code change actually does what it's supposed to by running the app and observing behavior. Use when asked to verify a PR, confirm a fix works, test a change manually, check that a feature works, or validate local changes before pushing.\n- code-review: Review the current diff for correctness bugs and reuse/simplification/efficiency cleanups at the given effort level (low/medium: fewer, high-confidence findings; high\u2192max: broader coverage, may include uncertain findings). Pass --comment to post findings as inline PR comments, or --fix to apply the findings to the working tree after the review.\n- simplify: Review the changed code for reuse, simplification, efficiency, and altitude cleanups, then apply the fixes. Quality only \u2014 it does not hunt for bugs; use /code-review for that.\n- fewer-permission-prompts: Scan your transcripts for common read-only Bash and MCP tool calls, then add a prioritized allowlist to project .claude/settings.json to reduce permission prompts.\n- loop: Run a prompt or slash command on a recurring interval (e.g. /loop 5m /foo). Omit the interval to let the model self-pace. - When the user wants to set up a recurring task, poll for status, or run something repeatedly on an interval (e.g. \"check the deploy every 5 minutes\", \"keep running /babysit-prs\"). Do NOT invoke for one-off tasks.\n- claude-api: Reference for the Claude API / Anthropic SDK \u2014 model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration.\nTRIGGER \u2014 read BEFORE opening the target file; don't skip because it \"looks like a one-liner\" \u2014 whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) \u2014 never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens).\nSKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named \u2014 don't Read the file).\n- run: Launch and drive this project's app to see a change working. Use when asked to run, start, or screenshot the app, or to confirm a change works in the real app (not just tests). First looks for a project skill that already covers launching the app; otherwise falls back to built-in patterns per project type (CLI, server, TUI, Electron, browser-driven, library).\n- init: Initialize a new CLAUDE.md file with codebase documentation\n- review: Review a pull request\n- security-review: Complete a security review of the pending changes on the current branch"
+ }
+ ],
+ "max_completion_tokens": 16384,
+ "stream": true,
+ "tools": [
+ {
+ "type": "function",
+ "function": {
+ "name": "Agent",
+ "description": "Launch a new agent to handle complex, multi-step tasks. Each agent type has specific capabilities and tools available to it.\n\nAvailable agent types and the tools they have access to:\n- claude: Catch-all for any task that doesn't fit a more specific agent. FleetView's default when no agent name is typed. (Tools: *)\n- Explore: Read-only search agent for broad fan-out searches \u2014 when answering means sweeping many files, directories, or naming conventions and you only need the conclusion, not the file dumps. It reads excerpts rather than whole files, so it locates code; it doesn't review or audit it. Specify search breadth: \"medium\" for moderate exploration, \"very thorough\" for multiple locations and naming conventions. (Tools: All tools except Agent, ExitPlanMode, Edit, Write, NotebookEdit)\n- general-purpose: General-purpose agent for researching complex questions, searching for code, and executing multi-step tasks. When you are searching for a keyword or file and are not confident that you will find the right match in the first few tries use this agent to perform the search for you. (Tools: *)\n- Plan: Software architect agent for designing implementation plans. Use this when you need to plan the implementation strategy for a task. Returns step-by-step plans, identifies critical files, and considers architectural trade-offs. (Tools: All tools except Agent, ExitPlanMode, Edit, Write, NotebookEdit)\n- statusline-setup: Use this agent to configure the user's Claude Code status line setting. (Tools: Read, Edit)\n\nWhen using the Agent tool, specify a subagent_type parameter to select which agent type to use. If omitted, the general-purpose agent is used.\n\n## When to use\n\nReach for this when the task matches an available agent type, when you have independent work to run in parallel, or when answering would mean reading across several files \u2014 delegate it and you keep the conclusion, not the file dumps. For a single-fact lookup where you already know the file, symbol, or value, search directly. Once you've delegated a search, don't also run it yourself \u2014 wait for the result.\n\n- The agent's final message is returned to you as the tool result; it is not shown to the user \u2014 relay what matters.\n- Use SendMessage with the agent's ID or name to continue a previously spawned agent with its context intact; a new Agent call starts fresh.\n- `isolation: \"worktree\"` gives the agent its own git worktree (auto-cleaned if unchanged).\n- `run_in_background: true` runs the agent asynchronously; you'll be notified when it completes.\n- When you launch multiple agents for independent work, send them in a single message with multiple tool uses so they run concurrently",
+ "parameters": {
+ "$schema": "https://json-schema.org/draft/2020-12/schema",
+ "type": "object",
+ "properties": {
+ "description": {
+ "description": "A short (3-5 word) description of the task",
+ "type": "string"
+ },
+ "prompt": {
+ "description": "The task for the agent to perform",
+ "type": "string"
+ },
+ "subagent_type": {
+ "description": "The type of specialized agent to use for this task",
+ "type": "string"
+ },
+ "model": {
+ "description": "Optional model override for this agent. Takes precedence over the agent definition's model frontmatter. If omitted, uses the agent definition's model, or inherits from the parent.",
+ "type": "string",
+ "enum": [
+ "sonnet",
+ "opus",
+ "haiku"
+ ]
+ },
+ "run_in_background": {
+ "description": "Set to true to run this agent in the background. You will be notified when it completes.",
+ "type": "boolean"
+ },
+ "isolation": {
+ "description": "Isolation mode. \"worktree\" creates a temporary git worktree so the agent works on an isolated copy of the repo.",
+ "type": "string",
+ "enum": [
+ "worktree"
+ ]
+ }
+ },
+ "required": [
+ "description",
+ "prompt"
+ ],
+ "additionalProperties": false
+ }
+ }
+ },
+ {
+ "type": "function",
+ "function": {
+ "name": "AskUserQuestion",
+ "description": "Use this tool only when you are blocked on a decision that is genuinely the user's to make: one you cannot resolve from the request, the code, or sensible defaults.\n\nUsage notes:\n- Users will always be able to select \"Other\" to provide custom text input\n- Use multiSelect: true to allow multiple answers to be selected for a question\n- If you recommend a specific option, make that the first option in the list and add \"(Recommended)\" at the end of the label\n\nPlan mode note: To switch into plan mode, use EnterPlanMode (not this tool). Once in plan mode, use this tool to clarify requirements or choose between approaches BEFORE finalizing your plan. Do NOT use this tool to ask \"Is my plan ready?\", \"Should I proceed?\", or otherwise reference \"the plan\" in questions \u2014 the user cannot see the plan until you call ExitPlanMode for approval.\n\nReserve this for decisions where the user's answer changes what you do next \u2014 not for choices with a conventional default or facts you can verify in the codebase yourself. In those cases pick the obvious option, mention it in your response, and proceed.\n",
+ "parameters": {
+ "$schema": "https://json-schema.org/draft/2020-12/schema",
+ "type": "object",
+ "properties": {
+ "questions": {
+ "description": "Questions to ask the user (1-4 questions)",
+ "minItems": 1,
+ "maxItems": 4,
+ "type": "array",
+ "items": {
+ "type": "object",
+ "properties": {
+ "question": {
+ "description": "The complete question to ask the user. Should be clear, specific, and end with a question mark. Example: \"Which library should we use for date formatting?\" If multiSelect is true, phrase it accordingly, e.g. \"Which features do you want to enable?\"",
+ "type": "string"
+ },
+ "header": {
+ "description": "Very short label displayed as a chip/tag (max 12 chars). Examples: \"Auth method\", \"Library\", \"Approach\".",
+ "type": "string"
+ },
+ "options": {
+ "description": "The available choices for this question. Must have 2-4 options. Each option should be a distinct, mutually exclusive choice (unless multiSelect is enabled). There should be no 'Other' option, that will be provided automatically.",
+ "minItems": 2,
+ "maxItems": 4,
+ "type": "array",
+ "items": {
+ "type": "object",
+ "properties": {
+ "label": {
+ "description": "The display text for this option that the user will see and select. Should be concise (1-5 words) and clearly describe the choice.",
+ "type": "string"
+ },
+ "description": {
+ "description": "Explanation of what this option means or what will happen if chosen. Useful for providing context about trade-offs or implications.",
+ "type": "string"
+ },
+ "preview": {
+ "description": "Optional preview content rendered when this option is focused. Use for mockups, code snippets, or visual comparisons that help users compare options. See the tool description for the expected content format.",
+ "type": "string"
+ }
+ },
+ "required": [
+ "label",
+ "description"
+ ],
+ "additionalProperties": false
+ }
+ },
+ "multiSelect": {
+ "description": "Set to true to allow the user to select multiple options instead of just one. Use when choices are not mutually exclusive.",
+ "default": false,
+ "type": "boolean"
+ }
+ },
+ "required": [
+ "question",
+ "header",
+ "options",
+ "multiSelect"
+ ],
+ "additionalProperties": false
+ }
+ },
+ "answers": {
+ "description": "User answers collected by the permission component",
+ "type": "object",
+ "propertyNames": {
+ "type": "string"
+ },
+ "additionalProperties": {
+ "type": "string"
+ }
+ },
+ "annotations": {
+ "description": "Optional per-question annotations from the user (e.g., notes on preview selections). Keyed by question text.",
+ "type": "object",
+ "propertyNames": {
+ "type": "string"
+ },
+ "additionalProperties": {
+ "type": "object",
+ "properties": {
+ "preview": {
+ "description": "The preview content of the selected option, if the question used previews.",
+ "type": "string"
+ },
+ "notes": {
+ "description": "Free-text notes the user added to their selection.",
+ "type": "string"
+ }
+ },
+ "additionalProperties": false
+ }
+ },
+ "metadata": {
+ "description": "Optional metadata for tracking and analytics purposes. Not displayed to user.",
+ "type": "object",
+ "properties": {
+ "source": {
+ "description": "Optional identifier for the source of this question (e.g., \"remember\" for /remember command). Used for analytics tracking.",
+ "type": "string"
+ }
+ },
+ "additionalProperties": false
+ }
+ },
+ "required": [
+ "questions"
+ ],
+ "additionalProperties": false
+ }
+ }
+ },
+ {
+ "type": "function",
+ "function": {
+ "name": "Bash",
+ "description": "Executes a bash command and returns its output.\n\n- Working directory persists between calls, but prefer absolute paths \u2014 `cd` in a compound command can trigger a permission prompt. Shell state (env vars, functions) does not persist; the shell is initialized from the user's profile.\n- IMPORTANT: Avoid using this tool to run `cat`, `head`, `tail`, `sed`, `awk`, or `echo` commands, unless explicitly instructed or after you have verified that a dedicated tool cannot accomplish your task. Instead, use the appropriate dedicated tool as this will provide a much better experience for the user.\n- `timeout` is in milliseconds: default 120000, max 600000.\n- `run_in_background` runs the command detached: it keeps running across turns and re-invokes you when it exits. No `&` needed. Foreground `sleep` is blocked; use Monitor with an until-loop to wait on a condition.\n\n# Git\n- Interactive flags (`-i`, e.g. `git rebase -i`, `git add -i`) are not supported in this environment.\n- Use the `gh` CLI for GitHub operations (PRs, issues, API).\n- Commit or push only when the user asks. If on the default branch, branch first.\n- End git commit messages with:\nCo-Authored-By: Claude Opus 4.8 \n- End PR bodies with:\n\ud83e\udd16 Generated with [Claude Code](https://claude.com/claude-code)",
+ "parameters": {
+ "$schema": "https://json-schema.org/draft/2020-12/schema",
+ "type": "object",
+ "properties": {
+ "command": {
+ "description": "The command to execute",
+ "type": "string"
+ },
+ "timeout": {
+ "description": "Optional timeout in milliseconds (max 600000)",
+ "type": "number"
+ },
+ "description": {
+ "description": "Clear, concise description of what this command does in active voice. Never use words like \"complex\" or \"risk\" in the description - just describe what it does.\n\nFor simple commands (git, npm, standard CLI tools), keep it brief (5-10 words):\n- ls \u2192 \"List files in current directory\"\n- git status \u2192 \"Show working tree status\"\n- npm install \u2192 \"Install package dependencies\"\n\nFor commands that are harder to parse at a glance (piped commands, obscure flags, etc.), add enough context to clarify what it does:\n- find . -name \"*.tmp\" -exec rm {} \\; \u2192 \"Find and delete all .tmp files recursively\"\n- git reset --hard origin/main \u2192 \"Discard all local changes and match remote main\"\n- curl -s url | jq '.data[]' \u2192 \"Fetch JSON from URL and extract data array elements\"",
+ "type": "string"
+ },
+ "run_in_background": {
+ "description": "Set to true to run this command in the background.",
+ "type": "boolean"
+ },
+ "dangerouslyDisableSandbox": {
+ "description": "Set this to true to dangerously override sandbox mode and run commands without sandboxing.",
+ "type": "boolean"
+ }
+ },
+ "required": [
+ "command"
+ ],
+ "additionalProperties": false
+ }
+ }
+ },
+ {
+ "type": "function",
+ "function": {
+ "name": "CronCreate",
+ "description": "Schedule a prompt to be enqueued at a future time. Use for both recurring schedules and one-shot reminders.\n\nUses standard 5-field cron in the user's local timezone: minute hour day-of-month month day-of-week. \"0 9 * * *\" means 9am local \u2014 no timezone conversion needed.\n\n## One-shot tasks (recurring: false)\n\nFor \"remind me at X\" or \"at