OpenRouter Tracing

Phoenix provides auto-instrumentation for OpenRouter through the OpenAI Python Library since OpenRouter provides a fully OpenAI-compatible API endpoint.

Install

pip install openinference-instrumentation-openai openai

Setup

Add your OpenAI API key as an environment variable:

export OPENAI_API_KEY='your_openrouter_api_key'

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 dependencies
)

Run OpenRouter

import openai

client = openai.OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="your_openrouter_api_key"
)

response = client.chat.completions.create(
    model="meta-llama/llama-3.1-8b-instruct:free",
    messages=[{"role": "user", "content": "Write a haiku about observability."}],
)
print(response.choices[0].message.content)

Observe

Now that you have tracing setup, all invocations of OpenAI (completions, chat completions, embeddings) will be streamed to your running Phoenix for observability and evaluation.

What Gets Traced

All OpenRouter model calls are automatically traced and include:

• Request/response data and timing

• Model name and provider information

• Token usage and cost data (when supported)

• Error handling and debugging information

Common Issues

• API Key: Use your OpenRouter API key, not OpenAI's

• Model Names: Use exact model names from OpenRouter's documentation

• Rate Limits: Check your OpenRouter dashboard for usage limits

• Base URL: Ensure you're using https://openrouter.ai/api/v1 as the base URL

Resources

• OpenRouter Documentation

• OpenInference OpenAI Instrumentation