Langfuse Service¶
Langfuse provides comprehensive observability for large language models (LLMs). It enables you to track usage, analyze performance metrics, and debug workflow issues within AI-driven applications.
Architecture Diagram¶
graph TD;
A[User Interaction] -->|Requests| B[API Gateway];
B -->|Forward| C[Langfuse Service];
C -->|Metrics| D[Analytics Dashboard];
C -->|Logs| E[Log Storage];
C -->|Alerts| F[Alert System];
%% Styling
classDef userClass fill:#e1f5fe,stroke:#01579b,stroke-width:2px,color:#000
classDef gatewayClass fill:#f3e5f5,stroke:#4a148c,stroke-width:2px,color:#000
classDef serviceClass fill:#e8f5e8,stroke:#1b5e20,stroke-width:2px,color:#000
classDef storageClass fill:#fff3e0,stroke:#e65100,stroke-width:2px,color:#000
classDef alertClass fill:#ffebee,stroke:#b71c1c,stroke-width:2px,color:#000
class A userClass
class B gatewayClass
class C serviceClass
class D,E storageClass
class F alertClass
Features¶
- Real-time LLM usage tracking
- Comprehensive performance analysis
- AI workflow debugging
- Query and event logging
- Custom alerts and notifications
Configuration¶
Telemetry Settings¶
Access¶
The Langfuse dashboard is accessible at:
Online Resources¶
- GitHub Repository: Langfuse GitHub
- Web Documentation: Langfuse Docs
Langfuse is ideal for teams needing detailed insights into LLM usage patterns and operational metrics.