#145 · Primary category: MLOps & Evaluation

langtrace

ai datasets evaluations gpt langchain llm llm-framework llmops observability open-source open-telemetry openai prompt-engineering tracing

Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊

Project last updated:11/17/25

GitHub Stars

1.2K

Forks

127

Contributors

20

License

AGPL-3.0

Why we included this project

Once an LLM application moves past the prototype stage, debugging becomes a matter of knowing what actually happened inside each model call. Langtrace is a self-hostable observability tool built on OpenTelemetry, so traces, latency, token counts, and cost show up for providers like OpenAI, Anthropic, and Gemini, plus vector databases and frameworks such as LangChain. Small TypeScript or Python SDKs wrap your existing code, and because traces follow OTEL conventions they drop into the monitoring stack you already run instead of living in a proprietary silo. Running it with Docker keeps production data inside your own infrastructure, and the dashboard is where you go to trace a bad prompt back to its cause or compare what different providers charge.

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