PDFs you can talk to.
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Updated
Feb 17, 2026 - TypeScript
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 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.
Privacy-first local RAG app — chat with your PDFs using Ollama (llama3) + LangChain + ChromaDB + Streamlit. 100% offline, no API key needed.
Local cognitive search on a pdf file.
Local-first AI assistant for macOS — chat with your PDFs, spreadsheets, CSVs and code using a local LLM via Ollama. Model-generated Python runs in a Seatbelt sandbox with no network. No cloud, no telemetry, no API keys.
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)
A chatbot assistant app that allows you to talk to a pdf using gemini api
Chat with your documents in real-time. A high-performance RAG engine built with FastAPI, PostgreSQL (pgvector), and OpenAI.
AI-powered PDF assistant for chatting, searching, and understanding large documents using LLMs and semantic context retrieval. Desktop AI application that converts user-selected text from PDF files into contextual searchable knowledge for intelligent conversations and document analysis.
A NotebookLM-inspired agent that runs locally
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.
Doctype.io: A production-ready RAG engine that turns static PDFs into intelligent conversations. Built with FastAPI, Redis, LangChain, and Google Gemini.
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.
Private local RAG assistant. Chat with your PDFs offline using Ollama + hybrid retrieval
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.
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