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On this page
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  1. Tracing
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LiteLLM

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Last updated 28 days ago

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allows developers to call all LLM APIs using the openAI format. is a proxy server to call 100+ LLMs in OpenAI format. Both are supported by this auto-instrumentation.

Any calls made to the following functions will be automatically captured by this integration:

  • completion()

  • acompletion()

  • completion_with_retries()

  • embedding()

  • aembedding()

  • image_generation()

  • aimage_generation()

Launch Phoenix

Sign up for Phoenix:

Sign up for an Arize Phoenix account at

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 .

Launch your local Phoenix instance:

pip install arize-phoenix
phoenix serve

For details on customizing a local terminal deployment, see .

Install packages:

pip install arize-phoenix-otel

Set your Phoenix endpoint:

import os

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

See for more details

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"

Install packages:

pip install arize-phoenix

Launch Phoenix:

import phoenix as px
px.launch_app()

Install

pip install openinference-instrumentation-litellm litellm

Setup

Use the register function to connect your application to Phoenix:

from phoenix.otel import register

# configure the Phoenix tracer
tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  auto_instrument=True # Auto-instrument your app based on installed OI dependencies
)

Add any API keys needed by the models you are using with LiteLLM.

import os
os.environ["OPENAI_API_KEY"] = "PASTE_YOUR_API_KEY_HERE"

Run LiteLLM

You can now use LiteLLM as normal and calls will be traces in Phoenix.

import litellm
completion_response = litellm.completion(model="gpt-3.5-turbo",
                   messages=[{"content": "What's the capital of China?", "role": "user"}])
print(completion_response)

Observe

Traces should now be visible in Phoenix!

Resources

Pull latest Phoenix image from :

For more info on using Phoenix with Docker, see .

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

🔭
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A LiteLLM trace in Phoenix