PDFs you can talk to.

🕸️ Open-source NotebookLM alternative with infinite canvas | Self-hosted Google NotebookLM replacement | RAG chat + PDF/Webpage/Video | Any LLM

Chat with your PDF documents.

A fully local RAG running on your browser - Powered by WebLLM, Voy and Transformers.js

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)

Chat with your documents in real-time. A high-performance RAG engine built with FastAPI, PostgreSQL (pgvector), and OpenAI.

A chatbot assistant app that allows you to talk to a pdf using gemini api

A NotebookLM-inspired agent that runs locally

Doctype.io: A production-ready RAG engine that turns static PDFs into intelligent conversations. Built with FastAPI, Redis, LangChain, and Google Gemini.

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.

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.

InsightDocs AI is a Streamlit-based web application that enables users to upload PDF documents and engage in conversational interactions with them using Retrieval-Augmented Generation (RAG) powered by Google's Gemini AI. Key features include PDF processing, AI-driven chat capabilities, intelligent document retrieval via FAISS vector search.

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 toolkit of local, privacy-focused AI applications built with Python. Includes a RAG-powered research assistant for PDFs, various chatbots, and visualization scripts.

Open-source NotebookLM alternative powered by Claude AI. Upload sources, chat with your docs, generate insights.

Privacy-first offline RAG system enabling conversational QA over PDFs using ChromaDB and locally hosted LLM (LM Studio).

An AI study assistant that reads PDFs, PPTs, DOCX, and images, then answers questions using Groq LLMs, sentence-transformers, and FAISS. Built with Streamlit and includes OCR support.