# Official LarAgent Documentation

## Docs

- [Expose Agents via API](https://docs.laragent.ai/core-concepts/agent-via-api.md): This document describes the feature introduced in the v0.5 and explains how to expose your agents through an OpenAI-compatible endpoint.
- [Agents](https://docs.laragent.ai/core-concepts/agents.md): Agents are the core of LarAgent. They represent an AI model that can be used to interact with users, systems, or any other source of input.
- [Chat History](https://docs.laragent.ai/core-concepts/chat-history.md): Chat history stores conversations between users and agents, enabling context-aware interactions across multiple sessions.
- [Artisan Commands](https://docs.laragent.ai/core-concepts/commands.md): Artisan commands available in LarAgent for managing AI agents
- [LLM Drivers](https://docs.laragent.ai/core-concepts/llm-drivers.md): LLM Drivers provide a flexible interface to connect with different AI providers while maintaining a consistent API for your application.
- [Model Context Protocol (MCP)](https://docs.laragent.ai/core-concepts/mcp.md): Integrate external MCP servers to dynamically extend your agent with tools and resources
- [RAG](https://docs.laragent.ai/core-concepts/rag.md): Guide about implementation of Retrival Augmented Generation in LarAgent.
- [Streaming](https://docs.laragent.ai/core-concepts/streaming.md): Receive AI responses in real-time chunks rather than waiting for the complete response, improving user experience for long interactions.
- [Structured Output](https://docs.laragent.ai/core-concepts/structured-output.md): Define JSON schemas to receive structured, predictable responses from your AI agents instead of free-form text.
- [Tools](https://docs.laragent.ai/core-concepts/tools.md): Tools extend your agent's capabilities, allowing it to perform tasks like sending messages, making API calls, or executing commands.
- [Usage Without Laravel](https://docs.laragent.ai/core-concepts/usage-without-laravel.md): Learn how to use LarAgent in non-Laravel PHP projects by leveraging the standalone engine.
- [Custom Chat History](https://docs.laragent.ai/customization/custom-chat-history.md): Learn how to create your own chat history implementation for LarAgent
- [Custom LLM Drivers](https://docs.laragent.ai/customization/custom-driver.md): Learn how to create your own LLM driver for LarAgent
- [Agent Events](https://docs.laragent.ai/customization/events.md): Learn how to use Agent lifecycle events to customize behavior
- [Engine Hooks](https://docs.laragent.ai/customization/hooks.md): Learn how to use Engine hooks to customize the conversation flow
- [Listen to Events](https://docs.laragent.ai/customization/listen-to-events.md): Learn how to listen to and handle LarAgent events in your application
- [Development](https://docs.laragent.ai/development.md): Contribute to LarAgent development
- [Guides Introduction](https://docs.laragent.ai/guides/introduction.md): Comprehensive guides to help you build powerful AI agents with LarAgent. From basic implementations to advanced patterns and real-world use cases.
- [Retrieval-as-Tool RAG](https://docs.laragent.ai/guides/rag/retrieval-as-tool.md): Learn how to implement advanced RAG by giving your agent tools to retrieve information on-demand from both structured databases and document collections.
- [Vector-Based RAG](https://docs.laragent.ai/guides/rag/vector-based.md): Learn how to implement traditional RAG using vector embeddings to build a knowledge-enhanced customer support agent.
- [Introduction](https://docs.laragent.ai/introduction.md)
- [Quickstart](https://docs.laragent.ai/quickstart.md): Get started with LarAgent in minutes


## Optional

- [Repository](https://github.com/maestroerror/laragent)
- [Community](https://discord.gg/NAczq2T9F8)
- [Blog](https://blog.laragent.ai)