Claude Code Langfuse Template

Claude Code + Langfuse: Session Observability Template

Capture every Claude Code conversation — prompts, responses, tool calls, and session grouping — using a self-hosted instance or Langfuse Cloud.

This template provides a complete, production-ready setup for observing your Claude Code sessions using Langfuse. Choose between self-hosted (everything runs locally in Docker) or Langfuse Cloud (zero infrastructure), with automatic session tracking and incremental state management.

Read the full story: I Built My Own Observability for Claude Code — why I built this, how it works, and screenshots of the setup in action.
Want more AI implementation patterns like this? Subscribe to Signal over Noise — weekly frameworks for building production AI systems, from someone who's done it at Deutsche Bank, Snowflake, and ClickHouse.

Choose Your Setup

Quick Start — Option A: Self-Hosted

Use this to run everything locally in Docker. No external accounts needed.

Prerequisites: Docker and Docker Compose, Python 3.11+, Claude Code CLI, 4-6GB RAM, 2-5GB disk.

1. Clone the repository

   Optional: Verify prerequisites

2. Generate credentials

   This will generate secure random credentials and prompt for your email/name.

3. Start Langfuse

   Wait 30-60 seconds for all services to initialize.

4. Install the hook

   This installs the Python package and configures Claude Code to send traces to Langfuse.

5. Verify the setup
   - Open http://localhost:3050 in your browser
   - Log in with the credentials from your .env file
   - Start a Claude Code conversation
   - Watch traces appear in Langfuse in real-time

   Optional: Run full validation

Quick Start — Option B: Langfuse Cloud

Use this if you have (or want to create) a Langfuse Cloud account. No Docker…