Langfuse
langfuse/langfuse
Agent/LLM observability and evals — traces, scores, and prompt management. GitHub: langfuse/langfuse (~33k stars).
GitHub repository
Overview
Langfuse (langfuse/langfuse) is listed in LimeDock Directories as an AI agent resource. Agent/LLM observability and evals — traces, scores, and prompt management. Group: memory-infra. Community size: ~33k GitHub stars. Repo (copy/paste): https://github.com/langfuse/langfuse This page is a plain-English guide so searches for the GitHub project can land on how teams actually use it.
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Link
Installation guide
Open the GitHub repository, then follow the README for your stack.
Official GitHub repository: https://github.com/langfuse/langfuse GitHub path: langfuse/langfuse
How to open it: 1. Copy: https://github.com/langfuse/langfuse 2. Clone or follow the README for your OS/stack. 3. Start with the smallest example before production use.
How to use it
**Simple example** You can’t improve agents you can’t see.
1. Deploy Langfuse. 2. Instrument one agent path. 3. Review traces weekly; add scores.
Example prompts
- “Add Langfuse tracing to our support agent.”
- “Langfuse vs AgentOps?”
- “What should we score first?”
Use cases and examples
- Evaluate langfuse/langfuse as an AI agent building block
- Pilot Langfuse on one staging workflow
- Compare against agents you already pay for
- Document a team playbook after the pilot
Prerequisites
- Hosting/cloud
- SDK install
Tips
- Observability before more tools.
- Sample if volume is huge.