Add Ray runtime support

package.json

@@ -6,7 +6,7 @@
   "workspaces": [],
   "scripts": {
     "dev": "NODE_ENV=development NODE_OPTIONS=--max-old-space-size=16384 node --import tsx src/server/index.ts --dev",
-    "dev:watch": "NODE_ENV=development node --watch --watch-path=src --import tsx src/server/index.ts --dev",
+    "dev:watch": "NODE_ENV=development NODE_OPTIONS=--max-old-space-size=16384 node --watch --watch-path=src --import tsx src/server/index.ts --dev",
     "build": "next build",
     "start": "NODE_ENV=production node --import tsx src/server/index.ts",
     "lint": "eslint",

src/components/layout/breadcrumbResolvers.ts

@@ -228,6 +228,16 @@ const STANDARD_RESOLVERS: BreadcrumbResolver[] = [
     buildUrl: (name) => `/api/tracing/agents/${encodeURIComponent(name)}/overview`,
     pickLabel: (b) => wrappedName(b, 'agent', 'label', 'name', 'key'),
   }),
+  createStandardResolver({
+    path: ['gpu-fleet', 'hosts'],
+    buildUrl: (id) => `/api/gpu-fleet/hosts/${encodeURIComponent(id)}`,
+    pickLabel: (b) => wrappedName(b, 'host'),
+  }),
+  createStandardResolver({
+    path: ['gpu-fleet', 'deployments'],
+    buildUrl: (id) => `/api/gpu-fleet/deployments/${encodeURIComponent(id)}`,
+    pickLabel: (b) => wrappedName(b, 'deployment'),
+  }),
 ];
 
 /* ----- Custom resolvers --------------------------------------------------- */

src/config/gpu-model-library.json

@@ -100,6 +100,19 @@
           "healthPath": "/api/tags",
           "openaiCompatible": true,
           "openaiBasePath": "/v1"
+        },
+        "ray": {
+          "image": "rayproject/ray-llm:2.47.1-py311-cu124",
+          "_meta": "Ray Serve LLM wraps vLLM under Ray Serve for autoscaling/multi-replica serving. rayproject/ray-llm ships no ENTRYPOINT, so `args` is the full process command: boot a tiny inline script that builds an OpenAI-compatible Serve app and calls serve.run(). Requires an NVIDIA GPU host, same as vLLM. `dtype: half` is explicit (not 'auto') because the vLLM 0.8.5 bundled in this Ray image does not auto-downgrade bfloat16 to float16 on <8.0 compute-capability GPUs the way the newer standalone vllm/vllm-openai image does — Qwen3's HF config defaults to bfloat16, which hard-crashes on T4/V100 without this override. `serve.start(http_options={'host': '0.0.0.0'})` before serve.run() is mandatory: Ray Serve's HTTP proxy binds to localhost by default, which is unreachable through Docker's published port — without this the container looks 'starting' forever with every request getting Connection reset by peer.",
+          "args": [
+            "python3", "-c",
+            "from ray import serve; from ray.serve.llm import LLMConfig, build_openai_app; serve.start(http_options={'host': '0.0.0.0', 'port': 8000}); app = build_openai_app({'llm_configs': [LLMConfig(model_loading_config={'model_id': 'Qwen/Qwen3-8B', 'model_source': 'Qwen/Qwen3-8B'}, deployment_config={'autoscaling_config': {'min_replicas': 1, 'max_replicas': 1}}, engine_kwargs={'tensor_parallel_size': {{gpuCount}}, 'dtype': 'half'})]}); serve.run(app, blocking=True)"
+          ],
+          "port": 8000,
+          "healthPath": "/-/healthz",
+          "openaiCompatible": true,
+          "openaiBasePath": "/v1",
+          "secretEnv": ["HUGGING_FACE_HUB_TOKEN"]
         }
       }
     },

src/lib/database/provider/types.extended.ts

@@ -529,7 +529,7 @@ export interface IGpuSlice {
   updatedAt?: Date;
 }
 
-export type LlmDeploymentRuntime = 'vllm' | 'tgi' | 'ollama' | 'custom';
+export type LlmDeploymentRuntime = 'vllm' | 'tgi' | 'ollama' | 'ray' | 'custom';
 
 export type LlmDeploymentDesiredState = 'running' | 'stopped';
 
@@ -573,6 +573,12 @@ export interface ILlmDeployment {
     readOnly?: boolean;
   }>;
   restart: 'no' | 'on-failure' | 'always' | 'unless-stopped';
+  /**
+   * `/dev/shm` size in bytes for the container, or `null` to use the
+   * agent's per-runtime default (see `resolveShmSizeBytes` in the agent's
+   * `docker.ts`). Operator-chosen at deploy time; not auto-inferred.
+   */
+  shmSizeBytes: number | null;
   desiredState: LlmDeploymentDesiredState;
   actualState: LlmDeploymentActualState;
   /** Container id from the agent's last report. */

src/lib/database/sqlite/base.ts

@@ -437,6 +437,16 @@ export class SQLiteProviderBase {
       'projectId',
       'projectId TEXT',
     );
+    // Explicit `/dev/shm` override for a deployment's container, falling
+    // back to the agent's per-runtime default when null (added 2026-07-26,
+    // alongside the Ray Serve runtime — vLLM/Ray need more than Docker's
+    // 64 MiB default to avoid a silent engine-startup hang).
+    this.ensureTableColumn(
+      db,
+      TABLES.llmDeployments,
+      'shmSizeBytes',
+      'shmSizeBytes INTEGER',
+    );
     // Sandbox instance per-instance env (added later). Safe to ensure on boot.
     this.ensureTableColumn(db, 'sandbox_instances', 'env', 'env TEXT');
     this.ensureTableColumn(

src/lib/database/sqlite/schema.ts

@@ -1915,6 +1915,7 @@ export const TENANT_SCHEMA_SQL = `
     healthPath TEXT NOT NULL DEFAULT '/health',
     volumes TEXT NOT NULL DEFAULT '[]',
     restart TEXT NOT NULL DEFAULT 'unless-stopped',
+    shmSizeBytes INTEGER,
     desiredState TEXT NOT NULL DEFAULT 'running',
     actualState TEXT NOT NULL DEFAULT 'pending',
     containerId TEXT,