Quickstart: Tracing (Python)

Overview

Phoenix supports three main options to collect traces:

1. Use Phoenix's decorators to mark functions and code blocks.

2. Use automatic instrumentation to capture all calls made to supported frameworks.

3. Use base OpenTelemetry instrumentation. Supported in Python and TS / JS, among many other languages.

This example uses options 1 and 2.

Launch Phoenix

Using Phoenix Cloud

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

2. Grab your API key from the Keys option on the left bar.

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

import os

# Add Phoenix API Key for tracing
PHOENIX_API_KEY = "ADD YOUR API KEY"
PHOENIX_ENDPOINT = "https://app.phoenix.arize.com/v1/traces"

os.environ["PHOENIX_CLIENT_HEADERS"] = f"api_key={PHOENIX_API_KEY}"

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

Using Self-hosted Phoenix

1. Run Phoenix using Docker, local terminal, Kubernetes etc. For more information, see self-hosting.

2. In your code, set your endpoint:

import os

# Update this with your self-hosted endpoint
PHOENIX_ENDPOINT = "http://0.0.0.0:6006/v1/traces"

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

Connect to Phoenix

To collect traces from your application, you must configure an OpenTelemetry TracerProvider to send traces to Phoenix.

pip install arize-phoenix-otel

from phoenix.otel import register

# configure the Phoenix tracer
tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  auto_instrument=True, # See 'Trace all calls made to a library' below
  endpoint=PHOENIX_ENDPOINT,
)
tracer = tracer_provider.get_tracer(__name__)

Trace your own functions

Functions can be traced using decorators:

@tracer.chain
def my_func(input: str) -> str:
    return "output"

Input and output attributes are set automatically based on my_func's parameters and return.

Trace all calls made to a library

Phoenix can also capture all calls made to supported libraries automatically. Just install the respective OpenInference library:

pip install openinference-instrumentation-openai

OpenInference libraries must be installed before calling the register function

# Add OpenAI API Key
import os
import openai

os.environ["OPENAI_API_KEY"] = "ADD YOUR OPENAI API KEY"

client = openai.OpenAI()
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Write a haiku."}],
)
print(response.choices[0].message.content)

View your Traces in Phoenix

You should now see traces in Phoenix!

Next Steps

• Explore tracing integrations

• Customize tracing

• View use cases to see end-to-end examples