Open-source observability for your LLM application, based on OpenTelemetry
Open-source observability for your LLM application
Looking for the JS/TS version? Check out OpenLLMetry-JS.
OpenLLMetry is a set of extensions built on top of OpenTelemetry that gives you complete observability over your LLM application. Because it uses OpenTelemetry under the hood, it can be connected to your existing observability solutions - Datadog, Honeycomb, and others.
It's built and maintained by Traceloop under the Apache 2.0 license.
The repo contains standard OpenTelemetry instrumentations for LLM providers and Vector DBs, as well as a Traceloop SDK that makes it easy to get started with OpenLLMetry, while still outputting standard OpenTelemetry data that can be connected to your observability stack. If you already have OpenTelemetry instrumented, you can just add any of our instrumentations directly.
The easiest way to get started is to use our SDK. For a complete guide, go to our docs.
Install the SDK:
pip install traceloop-sdk
Then, to start instrumenting your code, just add this line to your code:
from traceloop.sdk import Traceloop
Traceloop.init()
That's it. You're now tracing your code with OpenLLMetry! If you're running this locally, you may want to disable batch sending, so you can see the traces immediately:
Traceloop.init(disable_batch=True)
See our docs for instructions on connecting to each one.
OpenLLMetry can instrument everything that OpenTelemetry already instruments - so things like your DB, API calls, and more. On top of that, we built a set of custom extensions that instrument things like your calls to OpenAI or Anthropic, or your Vector DB like Chroma, Pinecone, Qdrant or Weaviate.
Whether it's big or small, we love contributions โค๏ธ Check out our guide to see how to get started.
Not sure where to get started? You can:
To @patrickdebois, who suggested the great name we're now using for this repo!