OpenRouter Tracing

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'

Connect your application to Phoenix with the register function:

from phoenix.otel import register# configure the Phoenix tracertracer_provider = register(project_name="my-llm-app", # Default is 'default'auto_instrument=True # Auto-instrument your app based on installed OI dependencies)

Run OpenRouter#

import openaiclient = 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#