Developed RAG System and Hybrid Search Architecture

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📅 2025-01-31 — Session: Developed RAG System and Hybrid Search Architecture

🕒 00:10–03:10
🏷️ Labels: RAG, Hybrid Search, Langchain, Chroma, Ragflow, Automation
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to develop a comprehensive understanding and plan for implementing a Retrieval-Augmented Generation (RAG) system and a hybrid search architecture.

Key Activities

  • Created a structured study plan for LangChain, Chroma, OpenAI, and LlamaIndex.
  • Developed a guide for building a RAG system with automated workflows, including file ingestion, chunking, embedding, and UI design.
  • Explored various products and services for RAG pipelines, focusing on data processing and embedding.
  • Analyzed the rag/app section of the RAGFlow repository, identifying strengths, weaknesses, and potential enhancements.
  • Evaluated RAGFlow guides for knowledge base management and file management automation.
  • Proposed an architecture for a hybrid search system using LangChain, RAGFlow, Elasticsearch, Chroma, and Pinecone.
  • Outlined a 3-day project plan for implementing a hybrid RAG system.

Achievements

  • Established a clear roadmap and implementation guide for RAG systems and hybrid search architecture.
  • Identified key tools and workflows necessary for successful implementation.

Pending Tasks

  • Execute the 3-day project plan for the hybrid RAG system.
  • Further refine the hybrid search architecture based on initial implementation feedback.

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