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Install

pip install openinference-instrumentation-openai openai

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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
)

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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)

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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.

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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

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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\

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Resources

OpenRouter Documentation

OpenInference OpenAI Instrumentation