OpenAI Instrumentation - LangWatch

Quick setup? Instead of following these steps manually, copy a prompt into your coding agent and it will set this up for you automatically.

LangWatch integrates with OpenAI to automatically capture detailed information about your LLM calls.

Installation

pip install langwatch openai

uv add langwatch openai

Usage

The LangWatch API key is configured by default via the LANGWATCH_API_KEY environment variable.

Use autotrack_openai_calls() to automatically capture all OpenAI calls made with a specific client instance within a trace.

import langwatch
from openai import OpenAI

langwatch.setup()
client = OpenAI()


@langwatch.trace(name="OpenAI Chat Completion")
def get_openai_chat_response(user_prompt: str):
    langwatch.get_current_trace().autotrack_openai_calls(client)

    response = client.chat.completions.create(
        model="gpt-5",
        messages=[{"role": "user", "content": user_prompt}],
    )
    completion = response.choices[0].message.content
    return completion


if __name__ == "__main__":
    user_query = "Tell me a joke"
    response = get_openai_chat_response(user_query)

    print(f"User: {user_query}")
    print(f"AI: {response}")

The @langwatch.trace() decorator creates a parent trace, and autotrack_openai_calls() enables automatic tracking of all calls made with the specified client instance for the duration of that trace.

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Capturing Metadata and Attributes - Add custom metadata and attributes to your traces and spans
Capturing Evaluations & Guardrails - Log evaluations and implement guardrails in your OpenAI applications