Langfuse
Open source AI engineering platform for debugging, monitoring, and improving LLM applications and agents.
Langfuse
What is Langfuse?
How to use Langfuse?
- 1Sign up at langfuse.com for free.
- 2Install the Langfuse SDK or use OpenTelemetry instrumentation.
- 3Integrate with your LLM application to start tracing.
- 4View traces in the dashboard to monitor performance.
- 5Set up evaluations and manage prompts from the platform.
Langfuse Key Features
- Observability and tracing of LLM calls
- Prompt management with versioning and rollbacks
- Evaluation with LLM-as-judge, heuristics, and human review
- Experimentation playground for side-by-side model comparison
- Cost and latency monitoring with dashboards and alerts
- Seamless integration with 80+ frameworks and providers
Langfuse Use Cases
- Debugging and optimizing LLM applications in production
- Monitoring and improving AI agent performance
- Collaborating on prompt engineering across teams
- Evaluating model outputs automatically
- Reducing LLM costs through detailed analytics
Langfuse Pricing & Free Credits
Langfuse currently operates on a Free, Freemium model.
Langfuse Pros & Cons
Pros
- Open source with MIT license
- Built for scale with ClickHouse backend
- Async tracing by default, non-blocking
- OTel native, works with existing instrumentation
- 80+ integrations covering frameworks, providers, and tools
- Self-hosting options for full data control
- Active community with frequent updates
Cons
- Self-hosting requires technical expertise
- Advanced features limited to paid plans
What is Langfuse best for?
- AI/ML engineers
- LLM application developers
- Teams building and monitoring AI agents
Langfuse FAQ
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