OpenAI observability

Overview

Laminar automatically instruments the official OpenAI package with a single line of code, allowing you to trace and monitor all your OpenAI API calls without modifying your existing code. This provides complete visibility into your AI application’s performance, costs, and behavior.

Getting Started

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
OPENAI_API_KEY=your-openai-api-key

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

Using OpenAI 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

Just add a single line at the start of your application or file to instrument OpenAI with Laminar.

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

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

// Initialize OpenAI client
const openai = new OpenAI.OpenAI();

import OpenAI from 'openai' imports the module. Pass it to instrumentModules, then create the client with new OpenAI.OpenAI().

4. Use OpenAI as usual

// Make API calls to OpenAI as you normally would
const response = await openai.chat.completions.create({
  model: "gpt-5-mini",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Hello, how are you?" }
  ],
});

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

All OpenAI API calls 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
OPENAI_API_KEY=your-openai-api-key

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

3. Initialize Laminar

Just add a single line at the start of your application or file to instrument OpenAI with Laminar.

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

# Load environment variables from .env file
load_dotenv()

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

# Initialize OpenAI client as usual
client = OpenAI()

4. Use OpenAI as usual

# Make API calls to OpenAI as you normally would
response = client.chat.completions.create(
    model="gpt-5-mini",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

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

All OpenAI API calls are now automatically traced in Laminar.

Monitoring OpenAI usage

After instrumenting your OpenAI calls with Laminar, you’ll be able to:

View detailed traces of each OpenAI API call, including request and response
Track token usage and cost across different models
Monitor latency and performance metrics
Open LLM span in Playground for prompt engineering
Debug issues with failed API calls or unexpected model outputs

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

Enrich your OpenAI traces

Attach sessions, user IDs, metadata, and tags to OpenAI spans via the SDK reference.
Wrap the functions around your OpenAI calls with observe and mark them as TOOL spans so they show up in the transcript.
Images you send to vision-capable OpenAI models are captured automatically (Tracing Images).

Vision inputs (images)

Laminar automatically traces image inputs (data URLs and external URLs) sent to vision-capable OpenAI models.

TypeScript
Python

const response = await openai.chat.completions.create({
  model: 'gpt-5-mini',
  messages: [
    {
      role: 'user',
      content: [
        { type: 'text', text: 'Describe this product and its key features.' },
        {
          type: 'image_url',
          image_url: {
            url: 'https://example.com/product-image.jpg',
            detail: 'high',
          },
        },
      ],
    },
  ],
});

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

response = client.chat.completions.create(
    model="gpt-5-mini",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Describe this product and its key features."},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://example.com/product-image.jpg",
                        "detail": "high",
                    },
                },
            ],
        }
    ],
)

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

Anthropic

Trace the Anthropic SDK directly in TypeScript and Python.

Gemini

Trace Gemini calls made with the Google Gen AI SDK.

OpenRouter

Trace OpenRouter requests with model and cost attribution.

OpenAI Agents SDK

Trace agent runs, handoffs, and tool calls.

Vercel AI SDK

Trace generateText and streamText in Next.js and Node.js.

All integrations

Browse every provider, framework, coding agent, and browser integration Laminar supports.

Overview

LLM provider SDKs

Agent frameworks

Coding agents

Browser and computer-use agents

Other platforms

OpenTelemetry

Overview

Getting Started

1. Install Laminar and OpenAI

2. Set up your environment variables

3. Initialize Laminar

4. Use OpenAI as usual

1. Install Laminar and OpenAI

2. Set up your environment variables

3. Initialize Laminar

4. Use OpenAI as usual

Monitoring OpenAI usage

Enrich your OpenAI traces

Vision inputs (images)

Anthropic

Gemini

OpenRouter

OpenAI Agents SDK

Vercel AI SDK

All integrations

​Overview

​Getting Started

​1. Install Laminar and OpenAI

​2. Set up your environment variables

​3. Initialize Laminar

​4. Use OpenAI as usual

​1. Install Laminar and OpenAI

​2. Set up your environment variables

​3. Initialize Laminar

​4. Use OpenAI as usual

​Monitoring OpenAI usage

​Enrich your OpenAI traces

​Vision inputs (images)

​Related integrations

Anthropic

Gemini

OpenRouter

OpenAI Agents SDK

Vercel AI SDK

All integrations

Overview

Getting Started

1. Install Laminar and OpenAI

2. Set up your environment variables

3. Initialize Laminar

4. Use OpenAI as usual

1. Install Laminar and OpenAI

2. Set up your environment variables

3. Initialize Laminar

4. Use OpenAI as usual

Monitoring OpenAI usage

Enrich your OpenAI traces

Vision inputs (images)

Related integrations