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DocuMind is an intelligent chatbot powered by cutting-edge AI that lets you converse with multiple PDF documents simultaneously. Built with Mistral embeddings, Groq's lightning-fast LLM, and LangChain's RAG architecture.

A Retrieval-Augmented Generation (RAG) based PDF question-answering application that allows users to upload documents and ask context-aware questions using vector search and LLMs.

Production-grade RAG system for document QA using hybrid retrieval, cross-encoder reranking, Ragas evaluation, and Langfuse observability.

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🚀 DocuMind - Enterprise-grade AI document intelligence system that transforms PDFs into an interactive knowledge base with natural language querying and precise source citations. 💡 Built with FastAPI, Google Gemini API, and advanced RAG technology for seamless document analysis and ArXiv research integration.

DocuMind: RAG 기반 개발 문서 검색과 패치노트 자동 생성을 지원하는 통합 로그 분석 및 이슈 추적 플랫폼

rag

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Chat with your documents using RAG (Retrieval-Augmented Generation)

A Retrieval-Augmented Generation (RAG) chatbot that answers user queries strictly from uploaded PDFs and predefined web sources, ensuring accurate and hallucination-free responses.

A end-to-end production ready RAG application using LangChain and Ollama

DocuMind QA AI Agent using RAG and LangChain

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DocuMind AI is an Azure-native RAG starter that ingests PDFs/DOCX/TXT/MD, chunks and embeds with text-embedding-3-large, stores in Azure AI Search, and answers with GPT-4o via a FastAPI backend and React/Vite chat UI. Includes one-click Azure provisioning scripts, sample docs, and quickstart setup.

DocuMind AI is a powerful and privacy-focused application designed to transform how you interact with PDF documents.It is built using Streamlit interface, which allows to engage in conversational Q&A sessions directly with your files, eliminating the need for manual searching.The project employs a Retrieval-Augmented Generation (RAG) architecture.

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Spring AI RAG document Q&A system with Ollama and PGVector

DocuMind AI is a RAG-based system that lets users upload documents and ask questions, generating context-aware answers using vector search and LLMs.

DocuMind, an AI-powered analytics platform, that performs natural language data analysis on CSV files and leverages RAG for intelligent document querying using GPT-4o and Gemini.

DocuMind is an end-to-end RAG (Retrieval-Augmented Generation) system designed to bridge the gap between static PDF documents and actionable intelligence. Instead of manually searching through hundreds of pages, DocuMind allows users to engage in natural language conversations with their data to extract precise, context-aware insights.

DocuMind AI API is a FastAPI backend that processes uploaded PDFs and enables context-aware question answering using RAG techniques. It manages document parsing, embeddings, and AI-powered responses exposed through clean, scalable APIs.

🧠 DocuMind Nexus — A docs-first RAG assistant (FastAPI + Streamlit + LangChain + ChromaDB) that indexes PDF/DOCX/HTML for natural-language Q&A, with multi-model support via OpenRouter, optional SerpAPI web search fallback, and an offline demo mode.

DocuMind AI is a fast, robust, and visually polished Retrieval-Augmented Generation (RAG) application. It allows users to upload PDF documents and instantly chat with them, extracting facts, summaries, and answering specific questions based entirely on the document's context.

DocuMind AI is an intelligent PDF question-answering chatbot built using RAG. It extracts content from large PDFs, creates embeddings, and generates accurate, context-aware answers. Features include multi-PDF upload, vector search, real-time chat interface, document summarization, and source-backed responses.

Documind is an intelligent AI document assistant that enables natural conversations with your PDF documents. Powered by advanced RAG (Retrieval-Augmented Generation) technology, it combines React, FastAPI, LangChain, and ChromaDB to deliver accurate answers with source citations. Click on the link for live demo.

DocuMind AI is an experimental multimodal RAG system designed to understand and answer questions about PDF and Word documents through systematic experimentation with different chunking strategies, embedding models, and vector databases, end-to-end deployment from local development through production deployment on Hugging Face Spaces.

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.