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🎉 New: Our semantic conventions are now part of OpenTelemetry! Join the discussion and help us shape the future of LLM observability.
OpenLLMetry-JS 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-JS, 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.
🚀 Getting Started
The easiest way to get started is to use our SDK. For a complete guide, go to our docs.
Install the SDK:
npm install --save @traceloop/node-server-sdkThen, to start instrumenting your code, just add these 2 lines to your code:
import * as traceloop from "@traceloop/node-server-sdk";
traceloop.initialize();Make sure to import the SDK before importing any LLM module.
That's it. You're now tracing your code with OpenLLMetry-JS! If you're running this locally, you may want to disable batch sending, so you can see the traces immediately:
traceloop.initialize({ disableBatch: true });Now, you need to decide where to export the traces to.
⏫ Supported (and tested) destinations
- ✅ Traceloop
- ✅ Dynatrace
- ✅ Datadog
- ✅ New Relic
- ✅ Honeycomb
- ✅ Grafana Tempo
- ✅ HyperDX
- ✅ SigNoz
- ✅ Splunk
- ✅ OpenTelemetry Collector
See our docs for instructions on connecting to each one.
🪗 What do we instrument?
OpenLLMetry-JS 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 Pinecone, Chroma, or Weaviate.
LLM Providers
- ✅ OpenAI
- ✅ Azure OpenAI
- ✅ Anthropic
- ✅ Cohere
- ⏳ Replicate
- ⏳ HuggingFace
- ✅ Vertex AI (GCP)
- ✅ Bedrock (AWS)
Vector DBs
- ✅ Pinecone
- ✅ Chroma
- ✅ Qdrant
- ⏳ Weaviate
- ⏳ Milvus
Frameworks
- ✅ LangChain
- ✅ LlamaIndex
🔎 Telemetry
The SDK provided with OpenLLMetry (not the instrumentations) contains a telemetry feature that collects anonymous usage information.
You can opt out of telemetry by setting the TRACELOOP_TELEMETRY environment variable to FALSE.
Why we collect telemetry
- The primary purpose is to detect exceptions within instrumentations. Since LLM providers frequently update their APIs, this helps us quickly identify and fix any breaking changes.
- We only collect anonymous data, with no personally identifiable information. You can view exactly what data we collect in our Privacy documentation.
- Telemetry is only collected in the SDK. If you use the instrumentations directly without the SDK, no telemetry is collected.
🌱 Contributing
Whether it's big or small, we love contributions ❤️ Check out our guide to see how to get started.
Not sure where to get started? You can:
- Book a free pairing session with one of our teammates!
- Join our Slack, and ask us any questions there.
💚 Community & Support
- Slack (For live discussion with the community and the Traceloop team)
- GitHub Discussions (For help with building and deeper conversations about features)
- GitHub Issues (For any bugs and errors you encounter using OpenLLMetry)
- Twitter (Get news fast)