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fix: Fixing phoenix to ax notebook #124

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fix: Fixing phoenix to ax notebook #124

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c5c0807
Fixing phoenix to ax notebook
jimbobbennett Apr 14, 2026
beea42d
Fixing head 100
jimbobbennett Apr 14, 2026
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1 change: 1 addition & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
.DS_Store
124 changes: 82 additions & 42 deletions Arize_Tutorials/Tracing/Arize_Tutorial_Export_Phoenix_Traces_and_Evals_to_Arize.ipynb
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Expand Up @@ -43,16 +43,18 @@
"outputs": [],
"source": [
"# Dependencies needed to build the Llama Index RAG application\n",
"!pip install -qq gcsfs llama-index-llms-openai llama-index-embeddings-openai\n",
"%pip install -qq gcsfs llama-index-llms-openai llama-index-embeddings-openai\n",
"\n",
"# Dependencies needed to export spans and send them to our collector: Phoenix\n",
"!pip install -qq \"llama-index-callbacks-arize-phoenix>=0.1.2\"\n",
"%pip install -qq \"llama-index-callbacks-arize-phoenix>=0.1.2\"\n",
"\n",
"# Install Phoenix to generate evaluations\n",
"!pip install -qq \"arize-phoenix[evals]\"\n",
"%pip install -qq arize-phoenix-client arize-phoenix-evals\n",
"\n",
"# Install Arize SDK with `Tracing` extra dependencies to export Phoenix data to Arize\n",
"!pip install -qq \"arize[Tracing]>=7.12.0\""
"%pip install -qq \"arize[Tracing]>=7.12.0\"\n",
"\n",
"%pip install -qq \"ipywidgets\""
]
},
{
Expand All @@ -70,9 +72,14 @@
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"import phoenix as px\n",
"\n",
"session = px.launch_app()"
"session = px.launch_app()\n",
"\n",
"# Update the environment variable to point to the Phoenix instance that we just launched\n",
"os.environ[\"PHOENIX_COLLECTOR_ENDPOINT\"] = session.url"
]
},
{
Expand Down Expand Up @@ -168,7 +175,7 @@
"from llama_index.embeddings.openai import OpenAIEmbedding\n",
"\n",
"\n",
"Settings.llm = OpenAI(model=\"gpt-4-turbo-preview\")\n",
"Settings.llm = OpenAI(model=\"gpt-5-nano\")\n",
"Settings.embed_model = OpenAIEmbedding(model=\"text-embedding-ada-002\")\n",
"index = load_index_from_storage(\n",
" storage_context,\n",
Expand Down Expand Up @@ -275,12 +282,12 @@
"metadata": {},
"outputs": [],
"source": [
"from phoenix.session.evaluation import get_qa_with_reference\n",
"from phoenix.client import Client\n",
"\n",
"px_client = px.Client() # Define phoenix client\n",
"queries_df = get_qa_with_reference(\n",
" px_client\n",
") # Get question, answer and reference data from phoenix"
"px_client = Client() # Define phoenix client\n",
"queries_df = px_client.spans.get_spans_dataframe(root_spans_only=True) # Get root spans (queries) as a dataframe\n",
"\n",
"queries_df.head()"
]
},
{
Expand Down Expand Up @@ -314,23 +321,29 @@
"metadata": {},
"outputs": [],
"source": [
"from phoenix.evals import (\n",
" HallucinationEvaluator,\n",
" OpenAIModel,\n",
" QAEvaluator,\n",
" run_evals,\n",
"from phoenix.evals.metrics.correctness import CorrectnessEvaluator\n",
"from phoenix.evals import LLM, async_evaluate_dataframe\n",
"\n",
"eval_model = LLM(\n",
" provider=\"openai\",\n",
" model=\"gpt-5-nano\",\n",
")\n",
"\n",
"eval_model = OpenAIModel(\n",
" model=\"gpt-4-turbo-preview\",\n",
"correctness_evaluator = CorrectnessEvaluator(eval_model)\n",
"\n",
"eval_df = queries_df[[\"context.span_id\", \"attributes.input.value\", \"attributes.output.value\"]].copy()\n",
"eval_df.rename(\n",
" columns={\n",
" \"attributes.input.value\": \"input\",\n",
" \"attributes.output.value\": \"output\",\n",
" },\n",
" inplace=True,\n",
")\n",
"hallucination_evaluator = HallucinationEvaluator(eval_model)\n",
"qa_correctness_evaluator = QAEvaluator(eval_model)\n",
"eval_df.set_index(\"context.span_id\", inplace=True)\n",
"\n",
"hallucination_eval_df, qa_correctness_eval_df = run_evals(\n",
" dataframe=queries_df,\n",
" evaluators=[hallucination_evaluator, qa_correctness_evaluator],\n",
" provide_explanation=True,\n",
"correctness_eval_df = await async_evaluate_dataframe(\n",
" dataframe=eval_df,\n",
" evaluators=[correctness_evaluator]\n",
")"
]
},
Expand All @@ -347,14 +360,10 @@
"metadata": {},
"outputs": [],
"source": [
"from phoenix.trace import SpanEvaluations\n",
"from phoenix.evals.utils import to_annotation_dataframe\n",
"\n",
"px_client.log_evaluations(\n",
" SpanEvaluations(eval_name=\"Hallucination\", dataframe=hallucination_eval_df),\n",
" SpanEvaluations(\n",
" eval_name=\"QA_Correctness\", dataframe=qa_correctness_eval_df\n",
" ),\n",
")"
"annotation_df = to_annotation_dataframe(dataframe=correctness_eval_df)\n",
"Client().spans.log_span_annotations_dataframe(dataframe=annotation_df)"
]
},
{
Expand All @@ -379,8 +388,7 @@
"metadata": {},
"outputs": [],
"source": [
"tds = px_client.get_trace_dataset()\n",
"spans_df = tds.get_spans_dataframe(include_evaluations=False)\n",
"spans_df = px_client.spans.get_spans_dataframe()\n",
"spans_df.head()"
]
},
Expand All @@ -390,7 +398,26 @@
"metadata": {},
"outputs": [],
"source": [
"evals_df = tds.get_evals_dataframe()\n",
"evals_df = (\n",
" px_client.spans.get_span_annotations_dataframe(spans_dataframe=spans_df)\n",
" .reset_index()\n",
" .rename(\n",
" columns={\n",
" \"span_id\": \"context.span_id\",\n",
" \"result.label\": \"eval.Correctness.label\",\n",
" \"result.score\": \"eval.Correctness.score\",\n",
" \"result.explanation\": \"eval.Correctness.explanation\",\n",
" }\n",
" )\n",
" .set_index(\"context.span_id\")[\n",
" [\n",
" \"eval.Correctness.label\",\n",
" \"eval.Correctness.score\",\n",
" \"eval.Correctness.explanation\",\n",
" ]\n",
" ]\n",
")\n",
"\n",
Comment on lines +403 to +420
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@seldo seldo Apr 14, 2026

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Entirely out of curiosity, why was all this verbosity not previously required?

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@jimbobbennett jimbobbennett Apr 14, 2026

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🤷 Not sure if it is a v7 vs v8 sdk thing, or a server side thing.

"evals_df.head()"
]
},
Expand All @@ -407,7 +434,7 @@
"metadata": {},
"outputs": [],
"source": [
"from arize.pandas.logger import Client"
"from arize import ArizeClient"
]
},
{
Expand Down Expand Up @@ -435,8 +462,7 @@
" \"✅ Import and Setup Arize Client Done! Now we can start using Arize!\"\n",
" )\n",
"\n",
"arize_client = Client(\n",
" space_id=SPACE_ID,\n",
"arize_client = ArizeClient(\n",
" api_key=API_KEY,\n",
")\n",
"model_id = \"tutorial-tracing-llama-index-rag-export-from-phoenix\"\n",
Expand All @@ -456,11 +482,11 @@
"metadata": {},
"outputs": [],
"source": [
"response = arize_client.log_spans(\n",
"response = arize_client.spans.log(\n",
" space_id=SPACE_ID,\n",
" project_name=\"tracing-tutorial\",\n",
" dataframe=spans_df,\n",
" evals_dataframe=evals_df,\n",
" model_id=model_id,\n",
" model_version=model_version,\n",
")\n",
"\n",
"# If successful, the server will return a status_code of 200\n",
Expand All @@ -469,13 +495,27 @@
" f\"❌ logging failed with response code {response.status_code}, {response.text}\"\n",
" )\n",
"else:\n",
" print(\"✅ You have successfully logged traces set to Arize\")"
" print(\"✅ You have successfully logged traces and evaluations to Arize\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "3.12.13",
"language": "python",
"name": "python3"
},
"language_info": {
"name": "python"
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.13"
}
},
"nbformat": 4,
Expand Down