🚀 RAG-Factory: Advanced and Easy-Use RAG Pipelines

A factory for building advanced RAG (Retrieval-Augmented Generation) pipelines, including:

• Standard RAG implementations
• GraphRAG architectures
• Multi-modal RAG systems

Features

• Modular design for easy customization
• Support for various knowledge graph backends
• Integration with multiple LLM providers
• Configurable pipeline components

Installation

pip install -e .

Usage

python main.py --config examples/graphrag/config.yaml

Examples

See the examples/ directory for sample configurations and usage.

Roadmap

✅ Implemented Features

• Vector RAG (基于Qdrant实现)
• Graph RAG (支持知识图检索)
• Lightweight SQLite Cache (轻量级缓存方案)

🚧 Planned Features

• Multi-modal RAG (多模态检索增强生成)
• ReAct QueryEngine (交互式查询引擎)
• Query Engineering:
  • Query Rewriting (查询重写)
  • Sub-Questions (子问题分解)
• Agentic RAG (智能工具选择优化性能)

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