LangFuse Tracing at Justice AI
This site provides comprehensive guidance for implementing observability and tracing in your AI applications using LangFuse.
This documentation has been created using AI assistance. If you notice any mistakes or have suggestions for improvement, please raise them as issues or submit a pull request via the GitHub link available in the top-right corner of this page.
Documentation Framework
This documentation follows the Diátaxis framework, which organizes content based on what you need to accomplish:
- 📚 Explanation - Understanding-oriented - Context and background knowledge
- 🎓 Tutorials - Learning-oriented - Step-by-step lessons for building skills
- 🛠️ How-to Guides - Problem-oriented - Practical solutions for specific challenges
- 📋 Reference - Information-oriented - Technical specifications and details
Each page clearly indicates its type, helping you find exactly what you need whether you’re learning, working, or seeking to understand.
What You’ll Find Here
📚 Explanation - Understanding-oriented
Context and background to deepen your knowledge:
| Title | Categories | Reading Time | Description | |
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What is LangFuse? | Concepts | 3 min | 📚 Explanation - This page provides context and background to help you understand LangFuse and why… |
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Understanding LangFuse Observability Hierarchy | Concepts, Observability | 4 min | 📚 Explanation - This page explains how to structure your observability data using LangFuse’s… |
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Self-Hosted LangFuse | Concepts, Infrastructure & Deployment | 3 min | 📚 Explanation - This page explains the concept of self-hosting LangFuse, why it matters for data… |
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Azure Architecture for LangFuse | Concepts, Infrastructure & Deployment, Azure | 4 min | 📚 Explanation - This page explains the Azure infrastructure components required for a production… |
🎓 Tutorials - Learning-oriented
Step-by-step lessons to build your skills:
| Title | Categories | Reading Time | Description | |
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Quick Start Guide | Getting Started, Python | 5 min | 🎓 Tutorial - This is a hands-on lesson that will take you step-by-step through your first… |
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Basic Python Tracing Tutorial | Getting Started, Python | 17 min | 🎓 Tutorial - This tutorial teaches you essential Python tracing patterns through hands-on… |
🛠️ How-to Guides - Problem-oriented
Practical solutions for specific challenges:
| Title | Categories | Reading Time | Description | |
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Tracing With The opentelemetry Library
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Application Tracing, Python, OpenTelemetry | 11 min | 🛠️ How-to Guide - This guide shows you how to implement standards-based tracing using… |
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Tracing With The langfuse Python SDK
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Application Tracing, Python | 4 min | 🛠️ How-to Guide - This guide shows you how to implement comprehensive tracing using the official… |
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Tracing With The Python requests Library
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Debugging, Python | 6 min | 🛠️ How-to Guide - This guide helps you troubleshoot trace sending issues by using raw HTTP… |
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Setting Up Email Notifications | Infrastructure & Deployment, Email, Azure | 7 min | 🛠️ How-to Guide - This guide shows you how to configure email notifications using Azure… |
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Deployment Troubleshooting | Infrastructure & Deployment, Troubleshooting | 7 min | 🛠️ How-to Guide - This guide helps you diagnose and resolve common issues encountered during… |
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Deploying LangFuse on Azure with Terraform | Infrastructure & Deployment, Azure, Terraform | 6 min | 🛠️ How-to Guide - This guide walks you through deploying LangFuse on Azure using Terraform… |
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Configuring SSL Certificates | Infrastructure & Deployment, SSL, Security | 7 min | 🛠️ How-to Guide - This guide shows you how to configure trusted SSL certificates using Let’s… |
Why Use LangFuse?
LangFuse provides essential observability for AI applications, helping you:
- Debug Multi-Step Processes - Trace execution paths through AI workflows
- Monitor Performance - Track latency, token usage, and costs across your AI stack
- Improve Quality - Identify issues in prompts, responses, and model behavior
- Ensure Compliance - Maintain audit trails for AI decision-making processes
Quick Links
This documentation is maintained by the Justice AI Unit. For questions or contributions, please see our GitHub repository.