Langfuse is an open source LLM engineering platform. It helps teams collaboratively develop, monitor, evaluate, and debug AI applications. Langfuse can be self-hosted in minutes and is battle-tested.
See the langfuse/langfuse readme and docs for more details.
🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with LlamaIndex, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
🪢 Langfuse documentation -- Langfuse is the open source LLM Engineering Platform. Observability, evals, prompt management, playground and metrics to debug and improve LLM apps
🪢 Langfuse Python SDK - Instrument your LLM app with decorators or low-level SDK and get detailed tracing/observability. Works with any LLM or framework
🪢 Langfuse JS/TS SDKs - Instrument your LLM app and get detailed tracing/observability. Works with any LLM or framework
Model Context Protocol (MCP) Server for Langfuse Prompt Management. This server allows you to access and manage your Langfuse prompts through the Model Context Protocol.
Modular, open source LLMOps stack that separates concerns: LiteLLM unifies LLM APIs, manages routing and cost controls, and ensures high-availability, while Langfuse focuses on detailed observability, prompt versioning, and performance evaluations.
