Pavansomisetty21/RAG-based-Intelligent-Conversational-AI-Agent-for-Knowledge-Extraction-Using-LangChain-Gemini-LLM
In this we implements a Retrieval-Augmented Generation (RAG) based conversational AI agent designed for intelligent knowledge extraction from PDF documents. Leveraging LangChain and Google’s Gemini LLM
This project helps you quickly get answers from long PDF documents by allowing you to chat with their content. You input a PDF file, and the system provides answers to your questions based on the information within that PDF, remembering previous parts of your conversation. Anyone who needs to extract specific information from documents without manually reading through them, such as researchers, analysts, or students, would find this useful.
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Use this if you need to rapidly find specific information or get summaries from large PDF documents through a conversational interface.
Not ideal if you need to analyze highly structured data within tables or images in PDFs, or if your documents are not primarily text-based.
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Jupyter Notebook
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MIT
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Last pushed
Sep 21, 2024
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