Tutorials
Welcome to the LangChainGo tutorials! These step-by-step guides help you build complete applications using LangChainGo.
Learning path
Follow these tutorials in order to progressively learn LangChainGo:
1. Foundation applications
- Building a simple chat application - Learn the basics with conversation memory
- AI Code Reviewer - Analyze Go code for bugs, style, and performance issues
- Intelligent Log Analyzer - Parse and analyze application logs with AI insights
2. Advanced applications
- Smart documentation generator - Auto-generate API docs from your codebase
3. Coming soon
Want to help? Check our documentation contribution guide to write these tutorials:
- Building a RAG (retrieval-augmented generation) system
- Creating an agent with tools
- Multi-modal applications
- Deploying LangChainGo applications
- Performance optimization
- Error handling and monitoring
Prerequisites
Before starting these tutorials, ensure you have:
- Go 1.21 or later installed
- An API key for at least one LLM provider (OpenAI, Anthropic, etc.)
- Basic familiarity with Go programming
What you'll learn
These tutorials go beyond simple chatbots to show practical applications:
- Code analysis: Build tools that understand and improve code quality
- Log intelligence: Extract insights from application logs and detect anomalies
- Documentation automation: Generate and maintain technical documentation
- Core patterns: Master LangChainGo's interfaces and Go idioms
- Production skills: Deploy, monitor, and scale AI-powered applications
- Integration techniques: Connect with external tools and services
Let's get started with your first LangChainGo application!