Multi-PDFs_ChatApp_AI-Agent and Chat-with-Multiple-PDF-Documents
These are competitors offering similar multi-PDF chatbot implementations using different LLM backends (Gemini Pro vs. Gemini 1.5-Flash) with comparable Langchain + vector database architectures, where users would select one based on model preference and maturity rather than use both together.
About Multi-PDFs_ChatApp_AI-Agent
GURPREETKAURJETHRA/Multi-PDFs_ChatApp_AI-Agent
Meet MultiPDF 📚 Chat AI App! 🚀 Chat seamlessly with Multiple PDFs using Langchain, Google Gemini Pro & FAISS Vector DB with Seamless Streamlit Deployment. Get instant, accurate responses from Awesome Google Gemini OpenSource language Model. 📚💬 Transform your PDF experience now! 🔥✨
Implements adaptive sliding-window chunking for retrieval-augmented generation (RAG) that dynamically balances granularity based on content complexity, and supports multi-hop conversational queries across multiple documents simultaneously—extending beyond single-document limitations. Compatible with multiple LLM backends (Gemini Pro, GPT-3, Claude, Llama2) and handles both PDF and TXT formats through PyPDF2 text extraction. Uses LangChain's conversational retrieval chains with FAISS vector indexing and Google's generative-ai SDK for embeddings and response generation.
About Chat-with-Multiple-PDF-Documents
NebeyouMusie/Chat-with-Multiple-PDF-Documents
In this project I have built an app that can answer questions from your multiple PDFs using Google's gemini-1.5-flash model.
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