Add RAG (Retriever-Augmented Generation) Capabilities

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Title: Add RAG (Retriever-Augmented Generation) Capabilities
Description:
Integrate Retriever-Augmented Generation (RAG) capabilities to enable advanced document retrieval and question-answering functionalities within the chatbot.

Context

The chatbot aims to support document embedding and interactions. Adding RAG capabilities would allow the chatbot to search, retrieve, and generate responses based on the embedded documents.

Expected Outcomes

• Implement a RAG model that can search and retrieve relevant information from embedded documents.
• Integrate the RAG model into the chatbot's existing architecture.

Challenges

• Ensuring efficient and accurate document retrieval.
• Seamlessly integrating RAG capabilities with the chatbot's other functionalities.

Recommended Libraries and Frameworks

• NLP Frameworks
  • Hugging Face Transformers is a well-known option for implementing RAG models.
  • Given the fast pace of NLP research, also consider exploring other emerging frameworks for possible advantages in performance or features.

Resources

• Hugging Face documentation on RAG models.
• Research papers or articles on Retriever-Augmented Generation techniques.
• Keep an eye on recent publications and repositories for the latest advancements in NLP.