PDFs you can talk to.
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Updated
Feb 17, 2026 - TypeScript
PDFs you can talk to.
Chat with your PDF documents.
Local cognitive search on a pdf file.
A full-stack AI-powered application that lets users upload and chat with their PDF documents. It combines seamless PDF processing, intelligent responses, and a minimalistic design to deliver a smooth and intuitive user experience.
Advanced local-first RAG system powered by Ollama and LangGraph. Optimized for high-performance sLLM orchestration featuring adaptive intent routing, semantic chunking, intelligent hybrid search (FAISS + BM25), and real-time thought streaming. Includes integrated PDF analysis and secure vector caching.
Chatting with PDF documents using large language models (GPT)
πΈοΈ Open-source NotebookLM alternative with infinite canvas | Self-hosted Google NotebookLM replacement | RAG chat + PDF/Webpage/Video | Any LLM
Chat with your documents in real-time. A high-performance RAG engine built with FastAPI, PostgreSQL (pgvector), and OpenAI.
Doctype.io: A production-ready RAG engine that turns static PDFs into intelligent conversations. Built with FastAPI, Redis, LangChain, and Google Gemini.
A chatbot assistant app that allows you to talk to a pdf using gemini api
A NotebookLM-inspired agent that runs locally
DocuMind AI is a professional-grade Retrieval-Augmented Generation (RAG) platform that enables natural language conversations with PDF documents. Powered by Google Gemini 2.0 Flash and ChromaDB, it uses advanced semantic search and layout-aware OCR to provide accurate, grounded insights with zero hallucinations.
PDF_CHAT_AI is a learning-first RAG implementation built to understand how LLMs can be grounded in external documents. The project intentionally avoids embeddings in its initial versions to expose the limitations of lexical retrieval and highlight why modern RAG systems rely on semantic search.
A High-Performance RAG Engine using Streamlit, LangChain, & Gemini 2.5 Flash. Built on ConversationalRetrievalChain for instant, precise document analysis (PDF, CSV, MD, TXT) without agentic overhead.
Privacy-first offline RAG system enabling conversational QA over PDFs using ChromaDB and locally hosted LLM (LM Studio).
RAG Pipeline with Groq/OpenAI LLM & HuggingFace Embeddings
ππ¬ FIN-RAG β AI-Powered PDF Chat & Organizer An intelligent RAG-based app to organize PDFs π, chat with documents π€, track reading progress π, and save notes as PDFs π. Built with Flask, Langchain, HuggingFace, Groq, FAISS, and TinyDB, deployed on Google Cloud βοΈ.
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