PDFs you can talk to.
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Updated
Feb 17, 2026 - TypeScript
PDFs you can talk to.
Visual production memory workspace for coding agents: plans, runs, artifacts, screenshots, and feedback beyond text.
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.
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.
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.
Chatting with PDF documents using large language models (GPT)
LocalDoc RAG: browser-only local document RAG for PDF/TXT/DOCX/CSV chat with Ollama, Qdrant, and plain JavaScript.
Chat with your documents — privately, offline, on your own machine. Local-first RAG over PDFs/DOCX/images with GPU-accelerated streaming, optional voice mode, multi-conversation history, and citation-anchored sources. Bilingual (中/EN). FastAPI + React + llama.cpp.
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.
A NotebookLM-inspired agent that runs locally
RAG-powered PDF Q&A engine — upload any document, ask questions, get answers with page-level citations using FAISS + 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.
Doctype.io: A production-ready RAG engine that turns static PDFs into intelligent conversations. Built with FastAPI, Redis, LangChain, and Google Gemini.
Streamlit RAG app for uploading PDFs, asking document questions, and viewing source-backed answers with Mistral and FAISS.
AI-powered web app for chatting with PDF documents through semantic search (RAG), built with Next.js, LangChain, OpenAI Embeddings, and Astra DB.
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