chatterjeesaurabh/Contextual-RAG-System-with-Hybrid-Search-and-Reranking
Improved RAG retrieval by adding context to the chunks and performing Hybrid Search (Vector Semantic Search + BM25 Keyword Search) and Reranking.
This system helps developers build more accurate AI chatbots by improving how they find relevant information from documents. It takes your PDF or JSON documents and user questions, then processes them to provide highly relevant document snippets that an LLM can use to generate precise answers. AI developers and MLOps engineers who are building RAG-based question-answering systems will find this useful.
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Use this if you are developing a RAG system and frequently encounter issues where your chatbot provides inaccurate or unhelpful answers due to poor context retrieval.
Not ideal if you are looking for a plug-and-play end-user chatbot application, as this project focuses on the underlying retrieval system for developers.
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Last pushed
Dec 23, 2024
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