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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.

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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

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Guide Categories

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🔍 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

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🚀 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

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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

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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

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Getting Help

If you encounter issues while following these guides:

GitHub Issues

Report bugs or request new guides

Discord Community

Get help from the community

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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.