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:
Sign up for an Arize Phoenix account at https://app.phoenix.arize.com/login
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
Create your API key from the Settings page
Copy your
Hostname
from the Settings pageIn 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')}"
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
Last updated
Was this helpful?