langfuse/langfuse
🪢 Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. 🍊YC W23 observed · 2026-08-28
Health v2 · maintenance only
92/100
- Activity 99
- Release rhythm 87
- Longevity 85
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 0.0
- age_days: 1203
- days_rel: 6
- days_push: 7
- n_releases_24m: 411
Adoption not part of the score
33767 stars · 3650 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Langfuse is an open-source AI engineering platform for LLM observability, tracing, evaluation, prompt management, and metrics, deployable as a cloud service or self-hosted. It integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and 100+ frameworks via Python/JS SDKs to trace, evaluate, and improve AI agent applications.
Use cases
- trace and debug LLM calls and agent steps in production
- evaluate LLM app output quality with LLM-as-judge and human review
- manage and version prompts separately from code
- monitor LLM cost, latency, and quality with dashboards and alerts
- run experiments comparing prompts and models on test datasets
- self-host an LLM observability platform
- collect user feedback and human annotations on traces
When to choose
- you need production observability and tracing for LLM or agent applications
- you want integrated prompt management, evals, and metrics in one platform
- you need OpenTelemetry-based tracing with broad framework integrations
- you want a self-hostable alternative to closed LLM monitoring tools
When to avoid
- you only need simple application logging without LLM-specific features
- you need a lightweight library-only solution with no server component
- you require a fully permissive license for commercial redistribution without checking terms
Facets
service · maturity active
monitoring tracing analytics prompt-engineering llm-inference alerting data-visualization developer-tools large-language-models monitoring analytics developer-tools self-hosted self-hosted cloud python llm-observability llm-evaluation prompt-management llmops opentelemetry agent-evals llm-as-judge tracing playground human-annotation ai-agents docker web-server nodejs typescript
10 sources
- readme: https://github.com/langfuse/langfuse · fetched 2026-08-28 · de11dc52ce49
- homepage: https://langfuse.com · fetched 2026-08-29 · 58ad793e94d6
- site_page: https://langfuse.com/docs/v4 · fetched 2026-08-29 · 3e3d4b54b871
- site_page: https://langfuse.com/docs · fetched 2026-08-29 · e4cf23b96428
- site_page: https://langfuse.com/docs/observability/overview · fetched 2026-08-29 · f41bf4c184cc
- site_page: https://langfuse.com/docs/prompt-management/overview · fetched 2026-08-29 · 88bf0fdf3b25
- site_page: https://langfuse.com/docs/evaluation/overview · fetched 2026-08-29 · 3e6e46d7a98c
- site_page: https://langfuse.com/docs/metrics/overview · fetched 2026-08-29 · 91baff97fd23
- site_page: https://langfuse.com/docs/get-started · fetched 2026-08-29 · 77631a725a95
- site_page: https://langfuse.com/changelog · fetched 2026-08-29 · 7f38c1eafd38
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| langfuse/langfuse | main | 92 |
For agents
markdown · JSON · MCP: product_card(name="langfuse/langfuse")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem