LiteLLM Tracing

LiteLLM allows developers to call all LLM APIs using the openAI format. LiteLLM Proxy 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:

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

  2. Click Create Space, then follow the prompts to create and launch your space.

Install packages:

pip install arize-phoenix-otel

Set your Phoenix endpoint and API Key:

From your new Phoenix Space

  1. Create your API key from the Settings page

  2. Copy your Hostname from the Settings page

  3. In your code, set your endpoint and API key:

import os

os.environ["PHOENIX_API_KEY"] = "ADD YOUR PHOENIX API KEY"
os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "ADD YOUR PHOENIX HOSTNAME"

# If you created your Phoenix Cloud instance before June 24th, 2025,
# you also need to set the API key as a header:
# os.environ["PHOENIX_CLIENT_HEADERS"] = f"api_key={os.getenv('PHOENIX_API_KEY')}"

Having trouble finding your endpoint? Check out Finding your Phoenix Endpoint

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

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