Welcome to the LarAgent Guides! These step-by-step tutorials will help you
master LarAgent’s capabilities and build production-ready AI agents for your
Laravel applications.
What You’ll Find Here
The Guides section provides practical, hands-on tutorials that complement the core documentation. While the Core Concepts explain what LarAgent can do, these guides show you how to implement real-world solutions.RAG Implementation
Build intelligent document search and retrieval systems
Coming Soon
More guides are being prepared
Guide Categories
🔍 Retrieval-Augmented Generation (RAG)
Learn how to enhance your AI agents with external knowledge sources:- Vector-Based RAG - Implement semantic search using vector embeddings for document retrieval
🚀 More Guides Coming Soon
We’re actively working on additional guides covering:- Multi-Agent Systems - Orchestrating multiple agents for complex workflows
- Custom Tool Development - Building specialized tools for your domain
- Production Deployment - Best practices for scaling LarAgent in production
- Integration Patterns - Common patterns for integrating with existing Laravel applications
- Performance Optimization - Tips for optimizing agent response times and resource usage
How to Use These Guides
Each guide follows a consistent structure to help you learn effectively:1
Prerequisites
What you need to know or have installed before starting
2
Step-by-Step Implementation
Detailed instructions with code examples
3
Testing & Validation
How to verify your implementation works correctly
4
Next Steps
Suggestions for extending or improving the implementation
Before You Begin
Make sure you’ve completed the Quickstart tutorial and have a basic understanding of:- Agents - The foundation of LarAgent
- Tools - How agents interact with external systems
- Chat History - Managing conversation context
Getting Help
If you encounter issues while following these guides:Contributing to Guides
Found an error or want to suggest improvements? We welcome contributions to make these guides better for everyone. You can:- Submit issues for unclear instructions
- Propose new guide topics
- Share your own implementation examples
Ready to dive in? Start with Vector-Based RAG to learn how to build knowledge-enhanced AI agents, or explore the Core Concepts if you need to review the fundamentals.