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:
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}"
os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "https://app.phoenix.arize.com"
# configure the Phoenix tracer
tracer_provider = register(
project_name="my-llm-app", # Default is 'default'
)
Your Phoenix API key can be found on the Keys section of your dashboard.
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",
)
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
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.
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)
