LiteLLM

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

Phoenix Developer Edition

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

Connect your application to your cloud instance:

import os
from phoenix.otel import register

# Add Phoenix API Key for tracing
PHOENIX_API_KEY = "ADD YOUR API KEY"
os.environ["PHOENIX_CLIENT_HEADERS"] = f"api_key={PHOENIX_API_KEY}"

# configure the Phoenix tracer
tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  endpoint="https://app.phoenix.arize.com/v1/traces",
)

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

Connect your application to your instance using:

from phoenix.otel import register

tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  endpoint="http://localhost:6006/v1/traces",
)

See Quickstart: Deployment 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

Connect your application to your instance using:

from phoenix.otel import register

tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  endpoint="http://localhost:6006/v1/traces",
)

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()

Connect your notebook to Phoenix:

from phoenix.otel import register

tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
)

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

Install

pip install openinference-instrumentation-litellm litellm

Setup

Initialize the InstructorInstrumentor before your application code.

from openinference.instrumentation.litellm import LiteLLMInstrumentor

LiteLLMInstrumentor().instrument(tracer_provider=tracer_provider)

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!

A LiteLLM trace in Phoenix

Resources

• OpenInference Instrumentation