PDFs you can talk to.
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Updated
Feb 17, 2026 - TypeScript
PDFs you can talk to.
Private, self-hosted document chat for attorneys: parse legal PDFs and query them with local open-source LLMs (Ollama) + verifiable page citations. One-click desktop app at docuchat.app.
Self-hosted PDF Q&A API with streaming answers, citations, Weaviate/pgvector, and Azure OpenAI, OpenAI-compatible, Vertex AI, or local embeddings.
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.
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.
Local cognitive search on a pdf file.
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
RAG-powered PDF Q&A engine — upload any document, ask questions, get answers with page-level citations using FAISS + Gemini
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.
A NotebookLM-inspired agent that runs locally
AI-powered web app for chatting with PDF documents through semantic search (RAG), built with Next.js, LangChain, OpenAI Embeddings, and Astra DB.
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.
AI-powered research assistant built with FastAPI, React, RAG, and LLMs for intelligent document retrieval and context-aware conversations.
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