Monitor, evaluate & improve
your LLM apps
Langtrace is an open-source observability tool that collects and analyzes traces and metrics to help you improve your LLM apps.
Simple non-intrusive setup
Access the Langtrace SDK with 2 lines of code
from langtrace_python_sdk import langtrace
langtrace.init(api_key=<your_api_key>)
Supports popular LLMs, frameworks and vector databases
Why Langtrace?
Open-Source & Secure
Langtrace can be self-hosted and supports OpenTelemetry standard traces, which can be ingested by any observability tool of your choice, resulting in no vendor lock-in.
End-to-end Observability
Get visibility and insights into your entire ML pipeline, whether it is a RAG or a fine-tuned model with traces and logs that cut across framework, vectorDB and LLM requests.
Establish a Feedback Loop
Annotate and create golden datasets with traced LLM interactions, and use them to continuously test and enhance your AI applications. Langtrace includes built-in heuristic, statistical, and model-based evaluations to support this process.