ApeRAG 是一个就绪的生产级 RAG（检索增强生成）平台，结合了图谱 RAG、向量搜索和全文搜索，并配备了先进的 AI 代理。构建具备混合检索、多模态文档处理、智能代理和企业级管理功能的复杂人工智能应用。

ApeRAG 是构建自己的知识图谱、上下文工程以及部署能够自主搜索和推理知识库的智能 AI 代理的最佳选择。

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• 快速入门
• 主要特征
• Kubernetes 部署（推荐生产环境）
• 发展
• 构建 Docker 镜像
• 致谢
• 许可证

快速启动

安装ApeRAG前，请确保您的机器满足以下最低系统要求：

• CPU >= 2 核心
• 内存 >= 4 GiB
• Docker 与 Docker Compose

启动 ApeRAG 最简单的方式是通过 Docker Compose。在执行以下命令之前，请确保你的机器已安装 Docker 和 Docker Compose：

运行后，您可以在浏览器中访问ApeRAG：

• 网页界面：http://localhost:3000/web/
• API 文档：http://localhost:8000/docs

ApeRAG

ApeRAG is a production-ready RAG (Retrieval-Augmented Generation) platform that combines Graph RAG, vector search, and full-text search with advanced AI agents. Build sophisticated AI applications with hybrid retrieval, multimodal document processing, intelligent agents, and enterprise-grade management features.

ApeRAG is the best choice for building your own Knowledge Graph, Context Engineering, and deploying intelligent AI agents that can autonomously search and reason across your knowledge base.

阅读中文文档

• Quick Start
• Key Features
• Kubernetes Deployment (Recommended for Production)
• Development
• Build Docker Image
• Acknowledgments
• License

Quick Start

Before installing ApeRAG, make sure your machine meets the following minimum system requirements:

• CPU >= 2 Core
• RAM >= 4 GiB
• Docker & Docker Compose

The easiest way to start ApeRAG is through Docker Compose. Before running the following commands, make sure that Docker and Docker Compose are installed on your machine:

git clone https://github.com/apecloud/ApeRAG.git
cd ApeRAG
cp envs/env.template .env
docker-compose up -d --pull always

After running, you can access ApeRAG in your browser at:

• Web Interface: http://localhost:3000/web/
• API Documentation: http://localhost:8000/docs

MCP (Model Context Protocol) Support

ApeRAG supports MCP (Model Context Protocol) integration, allowing AI assistants to interact with your knowledge base directly. After starting the services, configure your MCP client with:

{
  "mcpServers": {
    "aperag-mcp": {
      "url": "http://localhost:8000/mcp/",
      "headers": {
        "Authorization": "Bearer your-api-key-here"
      }
    }
  }
}

Authentication (by priority):

1. HTTP Authorization Header (Recommended): Authorization: Bearer your-api-key
2. Environment Variable (Fallback): APERAG_API_KEY=your-api-key

Important: Use your deployed API origin if not local (e.g. https://your-host/mcp/). Replace your-api-key-here with a valid API key from your ApeRAG settings.

The MCP server provides:

• Collection browsing: List and explore your knowledge collections
• Hybrid search: Search using vector, full-text, and graph methods
• Intelligent querying: Ask natural language questions about your documents

Enhanced Document Parsing