🤖 AI-Powered PDF Chat App | Dual AI Engine (Alchemyst + Gemini) | RAG Pipeline | Vector Search | MERN + TypeScript

RAG Gemini AI Chatbot. Users can upload PDF, Image to be used as context. Chat history is also available.

Next.js LangChain Gemini RAG Chatbot: An advanced Retrieval-Augmented Generation (RAG) chatbot that enables users to upload multiple PDFs and receive precise answers to their questions based on the content. Powered by LangChain and Gemini, this chatbot is built with Next.js and offers efficient PDF-based query handling for enhanced user engagement.

PDFChatRAG is an AI-powered application that enables users to interact and chat with PDF documents using advanced Retrieval-Augmented Generation (RAG) technology, powered by Google Gemini. This tool allows for seamless question answering and information retrieval from PDF files, making document interaction intuitive and efficient.

Research Assistant Agent is an AI-powered tool that retrieves, analyzes, and summarizes research papers using the Gemini API and RAG. It generates topic-based reports with related recommendations, summarizes PDFs with similar paper suggestions, and enables chat with research papers.

Geo 3D Chatbot is an AI assistant for the Contractor Transparency Hub, connecting clients and contractors in construction/3D modeling. It features RAG for local knowledge, web search for real-time info, file analysis (PDFs, DOCX, images), concise/detailed modes, and clear chat option. Built with Streamlit and Gemini AI for seamless project queries.

This RAG Streamlit app lets users chat with PDF documents using Gemini and Google's generative AI. Upload PDFs, process text, and get intelligent answers to your questions.

An AI-powered Q&A assistant allowing users to chat with PDF documents. Built with Python, LangChain, Google Gemini API, and ChromaDB using RAG architecture.

(Chat with PDF) RAG app using Flask, Langchain and Gemini Api

Chat with your PDFs using FastAPI, LangChain, Qdrant, and Gemini — an async RAG pipeline built with love

A Retrieval-Augmented Generation (RAG) web application that lets users upload PDFs and chat with the document using Gemini models.

Chat with your PDFs using AI Powered by Google Gemini + RAG Technology. Upload documents, ask questions, and get instant answers with source citations.

Turn any PDF into a chat. This RAG app uses Gemini for generation/embeddings and FAISS for retrieval, answering only from your document via Streamlit

QueryDoc is a full-stack RAG application that enables secure, session-isolated chat with PDF documents using FastAPI and Google Gemini. Built with React, TypeScript, and Docker for scalable, modern deployment.

🚀 Conversational RAG Chatbot is an interactive Retrieval-Augmented Generation (RAG) application that allows users to upload PDFs and chat with them using Streamlit. It leverages Gemini Vision for image analysis, ChromaDB for vector storage, and Groq's DeepSeek model for response generation.

🚀 AI Assistant with RAG & Web Scraping 🤖📄🌐📊 A Streamlit-based AI assistant using Google Gemini, ChromaDB, Web Scraping, and Data Analysis. Features: ✅ Chat with AI & PDFs (RAG) 📄 ✅ Web Scraping & AI Formatting 🌐 ✅ Excel/CSV Data Analysis 📊

TalkToPDF is an intelligent chatbot that allows you to upload and chat with PDF documents using the power of Retrieval-Augmented Generation (RAG). It uses Gemini 2.5 Pro as the LLM and ChromaDB as the vector store, making it blazing fast and highly accurate.

NoteBot is a RAG-based study assistant built with Streamlit and Google Gemini. It allows users to upload PDF notes and instantly chat with them to get accurate, context-aware answers using vector search (FAISS). Ideally suited for students and researchers needing quick insights from documents.

Flask + Google Gemini API project. This MVP turns your static documents (PDF, DOCX, TXT) into dynamic, interactive MCQ quizzes. It also enables a powerful RAG-based chat, allowing you to "talk" to your documents for smarter, more effective studying. A first step towards an AI super-tutor. Check out the README to run it locally!

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RAG_GENAI_Financial_Statement_PDF_CHATBOT_GEMINI

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AI-powered Financial Document RAG Chatbot using FAISS and Gemini 2.5 Flash for precise numeric extraction and context-aware responses.

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Chat with Your PDFs using Gemini AI + RAG • Upload PDFs, ask questions, and get smart, contextual answers — powered by Retrieval-Augmented Generation (RAG) and Gemini Pro.

Chat with multiple PDF documents using LangChain and Google Gemini Pro (RAG-based system).

Multi-Model PDF RAG Assistant - Upload PDFs, chat with AI using GPT/Gemini/DeepSeek, and get audio responses

Rag based application to chat with multiple pdf's using langchain and gemini-api-key.

A RAG chatbot to chat with your PDF documents using LangChain, Gemini 2.5 Flash, Gemini Embeddings, and Pinecone vector database.