Extend the current RAG implementation

[DavdGao]

• extend the vdb store
  • support milvus by providing a MilvusStore class Add support for milvus lite vector database in the RAG module of AgentScope #825
  • support MongoDB by providing a MongoDBStore class feat(rag): add MongoDB vector store in the RAG module. #860
  • consider supporting more complex vector database, e.g. graph vector database
• extend the reader class
  • provide Microsoft Word reader feat(rag): implement word reader in the RAG module #852
  • provide Microsoft Excel reader feat(rag): add excel reader to support excel files in the rag module #872
  • provide Microsoft Powerpoint reader
  • provide advanced PDF reader
• consider to improve the current implementation of SimpleKnowledge class

[DavdGao]

Contributions are welcome! Please comment here first to avoid duplicate work.

[xucailiang]

• • extend the vdb store

    • support milvus by providing a MilvusStore class Add support for milvus lite vector database in the RAG module of AgentScope #825* [ ] support MongoDB by providing a MongoDBStore class Implement mongodb store #860* [ ] consider supporting more complex vector database, e.g. graph vector database* [ ] extend the reader class

    • provide Microsoft Word reader Implement word reader #852* [ ] provide Microsoft Excel reader Implement Excel Reader #872* [ ] provide Microsoft Powerpoint reader* [ ] provide advanced PDF reader[ ] consider to improve the current implementation of SimpleKnowledge class

I am very interested in integrating Graph Vector Databases. I would like to learn more about this and understand the positioning of graph databases in this context. I also want to know if the extraction and construction of nodes and relationships will involve LLM calls. There are similar open-source projects like GraphRAG; will we be adopting a similar approach?