Langfuse
langfuse/langfuse
An open-source AI app monitoring and debugging tool that helps you trace LLM calls, manage prompts, and evaluate performance for transparent and controllable development.
🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
AI Summary
What This Project Does
It acts as a "black box" for AI app developers, recording what the AI says, cost, and time, allowing you to trace processes like chat logs.
What Problems It Solves
Solves issues where AI apps "can't debug, unknown errors, or cost out of control", replacing manual log screenshots and guesswork.
Who It's For
Developers building AI chatbots, smart customer service, or content gen apps, especially those using frameworks like LangChain.
Typical Use Cases
1. Debugging chatbot response logic to find break points.
2. Monitoring API call costs to prevent budget overruns.
3. Comparing different prompt effects to select the best version.
4. Team collaboration on prompt versioning to avoid overwrites.
Key Strengths & Highlights
Supports self-hosting for data privacy, integrates with major frameworks, intuitive interface like chat logs, Y Combinator backed.
Getting Started Requirements
Needs some coding knowledge for integration, supports one-click Docker deploy, requires AI model API Key, no extra server needed for trial.
Purpose
Suitable for companies or teams building AI products needing cost and quality monitoring. Not for casual personal use or scenarios without tracking needs.
Category
Tech Stack
Project Info
- Primary Language
- TypeScript
- Default Branch
- main
- License
- NOASSERTION
- Homepage
- https://langfuse.com/docs
- Created
- May 18, 2023
- Last Commit
- yesterday
- Last Push
- yesterday
- Indexed
- Apr 22, 2026