DocuChat AI: An intelligent conversational tool, powered by RAG, seamlessly combining OpenAI, Langchain, and Milvus. Effortlessly answers document questions with a Gradio interface, no LLM fine-tuning required. Retrieves documents from a dynamic vector database for insightful conversations across formats.

This project is a generative AI chatbot that specializes in extracting and comprehending information from PDF documents. It allows users to upload multiple PDF files, trains on the content of those documents, and enables them to ask questions or make queries related to the PDFs' content.

DocuChat is a web app that lets you interact with PDFs, text files, and YouTube videos. With AI image generation, you can create custom visuals for projects. Easily extract, analyze, and generate content to enhance your work. Just upload your files and start chatting

DocuChat AI is an AI-powered document search and chat platform. Instantly upload, search, and chat with your documents using advanced AI and vector search technology.

DocuChat AI is an intelligent chatbot that allows users to upload documents (PDF, DOCX, etc.) and ask questions based on their content. It uses a Retrieval-Augmented Generation (RAG) pipeline with LangChain, ChromaDB for vector storage, Flask as the backend, and React for the frontend.

Open-source RAG app to chat with your PDFs and documents using LangChain, ChromaDB, and Next.js.

Intelligent PDF chatbot using RAG with bge-m3 embeddings, LangGraph orchestration, Groq API (LLaMA 3.1), and PostgreSQL pgvector. Features hybrid search (vector + full-text), Streamlit UI, and production-ready FastAPI backend. Fast, efficient, and easy to deploy.

RAG DocuChat is a AI-powered backend service that enables WordPress (or any application) websites to provide intelligent, document-grounded customer support. Built on Retrieval-Augmented Generation (RAG), it indexes company-specific PDFs into Pinecone and allows users to chat with their documents in real time.

DocuChat - AI-Powered Document Intelligence

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A cutting-edge SaaS platform that revolutionizes document interaction using AI. Upload any PDF and instantly chat with it using GPT-4o-powered intelligence. Built with Next.js 15, Pinecone vector search, and enterprise-grade security.

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A free, privacy-first RAG chatbot using LangChain, RAG and llama3.1 that answers questions about your documents using local LLMs (Ollama) and vector search. No API costs, and runs entirely on the machine.

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Private RAG System for Enterprise Document Analysis.

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RAG for users assistant (ChatGPT API, LangChain, Streamlit, NLP, LLM)

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DocuChat AI is an AI-powered chatbot that lets users upload files (PDF, TXT, MD, CSV) and interact with their content using DeepSeek R1 (1.5B) via Ollama. It extracts text from documents and provides context-aware responses. Built with a Next.js frontend and Django backend, it offers a real-time chat interface for querying document content.

A multi form AI Chatbot for documents

Transform PDFs into interactive chat with Streamlit, Groq LLaMA3, LangChain, and FAISS.

DocuChat AI — An enterprise-grade AI-powered document chat platform that enables natural language interaction with your documents using FastAPI backend, LanceDB vector search, and a React/Next.js frontend. Upload PDFs, DOCX, and more to instantly query your content with contextual AI responses.

This repository contains the Phase 1 skeleton for a Retrieval-Augmented Generation (RAG) chatbot.

Claude-powered RAG-based chatbot that answers questions from PDF documents. An AI assistant that uses Claude and RAG to chat with PDFs using AWS services. Smart document Q&A assistant powered by Claude

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DocuChat AI (Offline RAG System) Tech Stack: Laravel 11, MySQL, Microsoft Foundry (Local LLM – Phi-3.5)

DocuChat AI is a full-stack Generative AI application that enables users to "chat" with PDF documents in real-time. Unlike basic wrappers, this project implements a Hybrid RAG (Retrieval Augmented Generation) architecture to deliver context-aware answers with sub-200ms latency.

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AI-powered document Q&A — RAG with LangChain, ChromaDB & source citations

DocChat AI