LlamaIndex

Trace LlamaIndex applications with OpenInference and send spans to Arize AX for LLM observability.

LlamaIndex is a data framework for building LLM applications — RAG pipelines, agents, query engines. Arize AX captures every LlamaIndex run — LLM calls, retrievals, embeddings, and the agent/query-engine spans that wrap them — via the openinference-instrumentation-llama-index package.

LlamaIndex Tracing Tutorial (Google Colab)

Prerequisites

• Python 3.10+
• An Arize AX account (sign up)
• An OPENAI_API_KEY from the OpenAI Platform

Launch Arize AX

1. Sign in to your Arize AX account.
2. From Space Settings, copy your Space ID and API Key. You will set them as ARIZE_SPACE_ID and ARIZE_API_KEY below.

Install

pip install arize-otel \
  openinference-instrumentation-llama-index \
  llama-index llama-index-llms-openai

Configure credentials

export ARIZE_SPACE_ID="<your-space-id>"
export ARIZE_API_KEY="<your-api-key>"
export ARIZE_PROJECT_NAME="llamaindex-tracing-example"
export OPENAI_API_KEY="<your-openai-api-key>"

Setup tracing

# instrumentation.py
import os

from arize.otel import register
from openinference.instrumentation.llama_index import LlamaIndexInstrumentor

tracer_provider = register(
    space_id=os.environ["ARIZE_SPACE_ID"],
    api_key=os.environ["ARIZE_API_KEY"],
    project_name=os.environ["ARIZE_PROJECT_NAME"],
)

LlamaIndexInstrumentor().instrument(tracer_provider=tracer_provider)
print("Arize AX tracing initialized for LlamaIndex.")

Run LlamaIndex

# example.py

# Importing instrumentation first ensures tracing is set up
# before `llama_index` is imported.
from instrumentation import tracer_provider

from llama_index.llms.openai import OpenAI

# OpenAI reads OPENAI_API_KEY from the environment.
llm = OpenAI(model="gpt-5")

response = llm.complete(
    "Why is the ocean salty? Answer in two sentences."
)

print(str(response))

Expected output

Arize AX tracing initialized for LlamaIndex.
The ocean is salty because rivers continuously dissolve mineral salts from rocks and soil and carry them to the sea, where they accumulate over millions of years. Water leaves the ocean through evaporation but the salts remain, steadily concentrating until reaching today's roughly 3.5% salinity.

Verify in Arize AX

1. Open your Arize AX space and select project llamaindex-tracing-example.
2. You should see a new trace within ~30 seconds containing an OpenAI.complete LLM span (LlamaIndex’s wrapper) with the prompt, response, and token usage attached.
3. If no traces appear, see Troubleshooting.

Troubleshooting

• No traces in Arize AX. Confirm ARIZE_SPACE_ID and ARIZE_API_KEY are set in the same shell that runs example.py. Enable OpenTelemetry debug logs with export OTEL_LOG_LEVEL=debug and re-run.
• LlamaIndex spans missing but other spans present. LlamaIndexInstrumentor().instrument(...) must run before any llama_index import. Make sure instrumentation.py is the first import in your entry point.
• 401 from OpenAI. Verify OPENAI_API_KEY is set and has access to gpt-5. Swap for a model your key can call.
• ModuleNotFoundError: llama_index.llms.openai. Modern LlamaIndex packages providers as separate sub-packages. Install llama-index-llms-openai (already in the install command above).

Resources

LlamaIndex Documentation

OpenInference LlamaIndex Instrumentor

Arize AX LlamaIndex Tutorials