Guides
End-to-end examples of how to use Langfuse: tutorials, runnable cookbooks, and video walkthroughs.
Introduction to Langfuse
If you are new to Langfuse, watch this walkthrough to get a thorough introduction to the Langfuse platform.
Introduction to Langfuse
Get an overview of the complete Langfuse platform and learn how it helps teams build better LLM applications through observability, prompt management, and evaluation.
Evaluation Tutorials
Start with the fundamentals and progress through advanced techniques as your application complexity grows. Read our blog post for an overview.
Set Up a User Feedback Loop
Capture explicit and implicit user feedback as scores on your traces, and use it to surface the responses worth reviewing.
Error Analysis
Review traces to classify issues like hallucinations, irrelevance, and formatting errors. Turn raw logs into actionable insights.
Automated Evaluations
Automated evaluators give you a scalable way to measure and monitor your application’s failure modes.
Testing LLM Applications
Build a testing foundation with deterministic checks and probabilistic ones using LLM judges to prevent regressions.
CI/CD for Experiments
Run Langfuse experiments in CI/CD pipelines to catch quality regressions before they reach production.
Synthetic Dataset Generation
Scale your test coverage with LLM-generated synthetic data. Create diverse inputs and adversarial cases without waiting for users.
Evaluate and Improve Structured Extraction
Score document extraction per field with a labeled dataset, catch regressions that pooled accuracy hides, and iterate with experiments.
Experiment Interpretation
Run experiments to compare prompts, models, or pipelines. Measure metrics like accuracy and speed to quantify progress.
RAG Observability & Evals
Specialized metrics for retrieval-augmented generation pipelines including retrieval relevance, answer faithfulness, and context completeness.
Advanced Topics
Extend your evaluation approach for complex, multi-step applications.
Evaluating Multi-Turn Conversations
Evaluate coherence, memory, and resolution in conversational apps that maintain context across multiple turns.
Simulated Multi-Turn Conversations
Generate and test user-AI exchanges safely before production. Build realistic dialogue scenarios for robust evaluation.
Agent Evaluation
Assess end-to-end trajectories for agents with tool use and planning. Evaluate action selection and task completion.
Vibe Coding a Custom Annotation UI
Build a custom annotation UI in minutes using Langfuse as data source
Automatic Prompt Improvement with AI Agent Skills
Use the Langfuse skill to analyze trace feedback and iteratively improve your prompts.
How to Calibrate your LLM-as-a-Judge with the Langfuse Skill
Test whether your judge prompt agrees with how you would label cases, and iterate until it does.
Human-in-the-Loop Scoring
Capture human judgments from your own review tooling and ingest them into Langfuse as structured scores, validated against a score config.
Cookbooks
Runnable cookbooks, sorted by topic. The notebook sources (ipynb) live in the cookbook directory of the repository.
Evaluation
Examples
Prompt Management
Video Tutorials
Beginner's Guide to RAG Evaluation with Langfuse and Ragas
Debug a Fan-Out RAG Agent With Tracing
Headless Langfuse From Your Coding Agent
Replace Vibes With Evals: Build an Evaluation Pipeline
Last updated on
