LLM Observability for OpenRouter

Overview

OpenRouter provides a unified API that gives you access to hundreds of AI models through a single endpoint. Many teams use it to keep one SDK while switching models or providers. With Laminar, you can trace OpenRouter traffic by using the OpenAI SDK pointed at the OpenRouter base URL.

OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Recommended: OpenAI SDK with OpenRouter

Laminar automatically instruments the OpenAI SDK. If you set the OpenAI SDK base URL to OpenRouter, Laminar will capture those calls as LLM spans.

TypeScript
Python

1. Install Laminar and OpenAI

npm install @lmnr-ai/lmnr@latest openai@latest

2. Set up your environment variables

Store your API keys in a .env file:

# .env file
LMNR_PROJECT_API_KEY=your-laminar-project-api-key
OPENROUTER_API_KEY=your-openrouter-api-key

Then load them in your application using a package like dotenv.

Using OpenRouter inside Next.js? The Vercel AI SDK page covers the Next.js-specific setup (serverExternalPackages, instrumentation.ts, and Laminar.patch for direct SDK clients).

3. Initialize Laminar and OpenAI

import { Laminar } from '@lmnr-ai/lmnr';
import OpenAI from 'openai';
import 'dotenv/config';

// This single line instruments all OpenAI SDK calls
Laminar.initialize({
  instrumentModules: { OpenAI: OpenAI }
});

const openai = new OpenAI.OpenAI({
  baseURL: 'https://openrouter.ai/api/v1',
  apiKey: process.env.OPENROUTER_API_KEY,
  defaultHeaders: {
    'HTTP-Referer': '<YOUR_SITE_URL>', // Optional
    'X-Title': '<YOUR_SITE_NAME>', // Optional
  },
});

4. Use OpenRouter as usual

const response = await openai.chat.completions.create({
  model: 'openai/gpt-4o-mini',
  messages: [
    { role: 'user', content: 'What is the meaning of life?' }
  ],
});

console.log(response.choices[0].message.content);

All OpenRouter calls made through the OpenAI SDK are now automatically traced in Laminar.

1. Install Laminar and OpenAI

pip install -U 'lmnr[all]' openai python-dotenv

2. Set up your environment variables

Store your API keys in a .env file:

# .env file
LMNR_PROJECT_API_KEY=your-laminar-project-api-key
OPENROUTER_API_KEY=your-openrouter-api-key

To see an example of how to integrate Laminar within a FastAPI application, check out our FastAPI integration guide.

3. Initialize Laminar and OpenAI

import os

from dotenv import load_dotenv
from lmnr import Laminar
from openai import OpenAI

load_dotenv()

# This single line instruments all OpenAI SDK calls
Laminar.initialize()

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key=os.environ["OPENROUTER_API_KEY"],
    default_headers={
        "HTTP-Referer": "<YOUR_SITE_URL>", # Optional
        "X-Title": "<YOUR_SITE_NAME>", # Optional
    },
)

4. Use OpenRouter as usual

response = client.chat.completions.create(
    model="openai/gpt-4o-mini",
    messages=[
        {"role": "user", "content": "What is the meaning of life?"}
    ],
)

print(response.choices[0].message.content)

All OpenRouter calls made through the OpenAI SDK are now automatically traced in Laminar.

OpenRouter SDK (Beta)

Laminar does not auto-instrument the OpenRouter SDK. Wrap your call with observe() to capture inputs/outputs and group it in a trace. LLM-specific fields (tokens, cost) are not added automatically in this mode.

import { Laminar, observe } from '@lmnr-ai/lmnr';
import { OpenRouter } from '@openrouter/sdk';

Laminar.initialize();

const openRouter = new OpenRouter({
  apiKey: '<OPENROUTER_API_KEY>',
  defaultHeaders: {
    'HTTP-Referer': '<YOUR_SITE_URL>', // Optional
    'X-Title': '<YOUR_SITE_NAME>', // Optional
  },
});

const completion = await observe({ name: 'openrouter.chat.send' }, async () =>
  openRouter.chat.send({
    model: 'openai/gpt-4o-mini',
    messages: [
      { role: 'user', content: 'What is the meaning of life?' },
    ],
    stream: false,
  })
);

console.log(completion.choices[0].message.content);

Using the OpenRouter API directly

You can use the interactive Request Builder to generate OpenRouter API requests in the language of your choice.

Direct HTTP calls are captured as custom spans via observe(). LLM-specific fields (tokens, cost) are not extracted automatically from raw responses.

import json
import requests

from lmnr import Laminar, observe

Laminar.initialize()

@observe()
def call_openrouter():
    response = requests.post(
        url="https://openrouter.ai/api/v1/chat/completions",
        headers={
            "Authorization": "Bearer <OPENROUTER_API_KEY>",
            "HTTP-Referer": "<YOUR_SITE_URL>", # Optional
            "X-Title": "<YOUR_SITE_NAME>", # Optional
        },
        data=json.dumps({
            "model": "openai/gpt-4o-mini",
            "messages": [
                {"role": "user", "content": "What is the meaning of life?"}
            ]
        })
    )
    return response.json()

print(call_openrouter())

import { Laminar, observe } from '@lmnr-ai/lmnr';

Laminar.initialize();

const response = await observe({ name: 'openrouter.fetch' }, async () =>
  fetch('https://openrouter.ai/api/v1/chat/completions', {
    method: 'POST',
    headers: {
      Authorization: 'Bearer <OPENROUTER_API_KEY>',
      'HTTP-Referer': '<YOUR_SITE_URL>', // Optional
      'X-Title': '<YOUR_SITE_NAME>', // Optional
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'openai/gpt-4o-mini',
      messages: [
        {
          role: 'user',
          content: 'What is the meaning of life?',
        },
      ],
    }),
  })
);

console.log(await response.json());

curl https://openrouter.ai/api/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -d '{
  "model": "openai/gpt-4o-mini",
  "messages": [
    {
      "role": "user",
      "content": "What is the meaning of life?"
    }
  ]
}'

Monitoring Your OpenRouter Usage

When you use the OpenAI SDK integration above, Laminar will create LLM spans so you can:

View detailed traces of each OpenRouter request, including request and response
Track token usage when OpenRouter returns usage data
See cost estimates when pricing data for the model is available in Laminar
Monitor latency and performance metrics
Open LLM spans in Playground for prompt engineering

Visit your Laminar dashboard to view your OpenRouter traces and analytics.

Advanced Features

Enrich traces with sessions, user IDs, metadata, and tags via the SDK reference.
Wrap custom functions with observe to capture business logic alongside model calls.
Images sent to vision-capable models are captured automatically - see Tracing Images.

Overview

Tracing

Signals

Debugger

Evaluations

Datasets

Platform

Overview

Recommended: OpenAI SDK with OpenRouter

1. Install Laminar and OpenAI

2. Set up your environment variables

3. Initialize Laminar and OpenAI

4. Use OpenRouter as usual

1. Install Laminar and OpenAI

2. Set up your environment variables

3. Initialize Laminar and OpenAI

4. Use OpenRouter as usual

OpenRouter SDK (Beta)

Using the OpenRouter API directly

Monitoring Your OpenRouter Usage

Advanced Features

​Overview

​Recommended: OpenAI SDK with OpenRouter

​1. Install Laminar and OpenAI

​2. Set up your environment variables

​3. Initialize Laminar and OpenAI

​4. Use OpenRouter as usual

​1. Install Laminar and OpenAI

​2. Set up your environment variables

​3. Initialize Laminar and OpenAI

​4. Use OpenRouter as usual

​OpenRouter SDK (Beta)

​Using the OpenRouter API directly

​Monitoring Your OpenRouter Usage

​Advanced Features

Overview

Recommended: OpenAI SDK with OpenRouter

1. Install Laminar and OpenAI

2. Set up your environment variables

3. Initialize Laminar and OpenAI

4. Use OpenRouter as usual

1. Install Laminar and OpenAI

2. Set up your environment variables

3. Initialize Laminar and OpenAI

4. Use OpenRouter as usual

OpenRouter SDK (Beta)

Using the OpenRouter API directly

Monitoring Your OpenRouter Usage

Advanced Features