LlamaIndex Workflows

How to use the python LlamaIndexInstrumentor to trace LlamaIndex Workflows

LlamaIndex Workflows are a subset of the LlamaIndex package specifically designed to support agent development.

Our LlamaIndexInstrumentor automatically captures traces for LlamaIndex Workflows agents. If you've already enabled that instrumentor, you do not need to complete the steps below.

We recommend using llama_index >= 0.11.0

Launch Phoenix

Phoenix Cloud

Sign up for Phoenix:

Sign up for an Arize Phoenix account at https://app.phoenix.arize.com/login

Install packages:

pip install arize-phoenix-otel

Set your Phoenix endpoint and API Key:

import os

# Add Phoenix API Key for tracing
PHOENIX_API_KEY = "ADD YOUR API KEY"
os.environ["PHOENIX_CLIENT_HEADERS"] = f"api_key={PHOENIX_API_KEY}"
os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "https://app.phoenix.arize.com"

Your Phoenix API key can be found on the Keys section of your dashboard.

Command Line

Launch your local Phoenix instance:

pip install arize-phoenix
phoenix serve

For details on customizing a local terminal deployment, see Terminal Setup.

Install packages:

pip install arize-phoenix-otel

Set your Phoenix endpoint:

import os

os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "http://localhost:6006"

See Terminal for more details

Docker

Pull latest Phoenix image from Docker Hub:

docker pull arizephoenix/phoenix:latest

Run your containerized instance:

docker run -p 6006:6006 arizephoenix/phoenix:latest

This will expose the Phoenix on localhost:6006

Install packages:

pip install arize-phoenix-otel

Set your Phoenix endpoint:

import os

os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "http://localhost:6006"

For more info on using Phoenix with Docker, see Docker.

Notebook

Install packages:

pip install arize-phoenix

Launch Phoenix:

import phoenix as px
px.launch_app()

By default, notebook instances do not have persistent storage, so your traces will disappear after the notebook is closed. See self-hosting or use one of the other deployment options to retain traces.

Install

pip install openinference-instrumentation-llama_index

Setup

Initialize the LlamaIndexInstrumentor before your application code. This instrumentor will trace both LlamaIndex Workflows calls, as well as calls to the general LlamaIndex package.

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

tracer_provider = register()
LlamaIndexInstrumentor().instrument(tracer_provider=tracer_provider)

Run LlamaIndex Workflows

By instrumenting LlamaIndex, spans will be created whenever an agent is invoked and will be sent to the Phoenix server for collection.

Observe

Now that you have tracing setup, all invocations of chains will be streamed to your running Phoenix for observability and evaluation.

Resources

• Example project
• OpenInference package