AI PDF chatbot agent built with LangChain & LangGraph

AI chatbot 🤖 for chat with CSV, PDF, TXT files 📄 and YTB videos 🎥 | using Langchain🦜 | OpenAI | Streamlit ⚡

🐶 PetCare AI Chatbot, powered by Langchain, Ollama, and Flask, utilizes RAG for context-aware answers from PDF documents.

A domain-adaptable AI chatbot powered by RAG, FAISS, and LangChain to answer questions from your custom PDFs using HuggingFace LLMs.

AI chatbot for PDFs built with NextJS, Langchain and OpenAI

A chatbot created with Next.js and AI SDK, using Langchain with RetrievalQA to provide information from a PDF loaded into a vector store in MongoDB.

AI chatbot 🤖 for chat with CSV, PDF, TXT files 📄 and YTB videos 🎥 | using Langchain🦜 | OpenAI | Streamlit ⚡

Gemini-Powered-MultiPDF-Chatbot is a Streamlit application that leverages Google Generative AI Gemini and LangChain for conversational question-answering based on PDF documents. This chatbot allows users to ask questions related to the content of uploaded PDF files.

A RAG (Retrieval-Augmented Generation) AI chatbot that allows users to upload multiple document types (PDF, DOCX, TXT, CSV) and ask questions about the content. Built using LangChain, Hugging Face embeddings, and Streamlit, it enables efficient document search and question answering using vector-based retrieval. 🚀

A chatbot created with Next.js and AI SDK, using Langchain with RetrievalQA to provide information from a PDF loaded into a vector store in MongoDB.

DocuMind – An AI-powered PDF chatbot that allows users to upload documents and ask questions, with memory support and semantic search using LangChain, FastAPI, and Hugging Face embeddings.

RAG-Based PDF ChatBot is an AI tool that enables users to interact with PDF content seamlessly. Powered by Ollama LLM and LangChain, it extracts and provides accurate answers from PDFs, enhancing document accessibility and usability. Perfect for efficient information retrieval.

AI chatbot for mental health advice using Streamlit, LangChain, and Llama 2 by Meta. Retrieves info from PDFs and offers real-time responses

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.

Following Alejandro AO - Software & Ai tutorial to build a multi-pdf langchain LLM chatbot

A Portuguese chatbot using RAG (FAISS + LangChain) to interact with uploaded PDFs. AI-powered document understanding and conversational interface.

🧠 An AI-powered Exam Prep Chatbot that answers questions from uploaded PDFs using Retrieval-Augmented Generation (RAG). Built with Gradio, OpenVINO, and LangChain — supports English and Chinese!

An interactive chatbot application built with Streamlit, utilizing Google’s Generative AI and Langchain for document-based Q&A. The app allows users to upload text, PDF, or Word documents, interact with the content using AI, and book appointments through a conversational interface with input validation.

Hands-on training (July 2025) at Sathyabama Univ on GenAI & AI Agents. Learn chatbot creation, RAG from text/PDF/web/image/vector DBs, and build agents using LangChain, LangGraph, LangFlow, Google ADK & n8n. Python best practices and API credentials included.

This project enables a conversational AI chatbot capable of processing and answering questions from multiple document formats, including CSV, JSON, PDF, and DOCX. It uses LangChain and Hugging Face's pre-trained models to extract information from these documents and provide relevant responses.

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.

An AI-powered medical chatbot built with LangChain, FAISS, and Groq LLMs that uses Retrieval-Augmented Generation (RAG) to answer user questions based on uploaded medical PDF documents. It features document embedding, semantic search, and a Streamlit-based interactive interface for accurate and context-aware responses.

GraphRAG, Outperforms traditional RAG ( Retrieval-Augmented Generation ) for Query Focused Summarization. Opensource research of Knowledge Graph to improving the accuracy of data discovery, solving RAG pain points, solving Black-box hallucination, and to enhance LLMs. Knowledge Graph to GenAI. PDF AI Agent/Chatbot with Python, Neo4j and LangChain

Build an AI PDF chatbot with LangChain and LangGraph. Ingest documents, store embeddings, and answer queries using OpenAI. 🤖📄

Chatbot for Multiple PDF files is a Python program designed for interacting with multiple PDF documents. Through natural language queries, users can inquire about the PDFs and receive accurate responses based on their content. The app utilizes a language model to generate these answers.

AI-powered RAG-based PDF Chatbot using LangChain, OpenAI, FAISS & Streamlit for intelligent document question answering.

RAG-powered Document Q&A app using Python, Streamlit, LangChain, FAISS, and HuggingFace embeddings. Supports multi-PDF ingestion, vector search, and high-speed Llama-3/Groq & OpenAI inference for accurate, context-aware answers. Modern Generative AI chatbot for knowledge retrieval.

RAG based PDF Chatbot with support for AWS s3 and pinecone . Uses openai's embeddings and gemini api for answering . Langchain for prompt chaining . NextJS AI sdk for UI .

A full-stack AI-powered document chatbot built with LangChain, FastAPI, and React. Upload PDF or text documents and ask natural language questions about their content using Retrieval-Augmented Generation (RAG).

An AI-powered study assistant chatbot that lets you upload your notes (PDFs) and ask questions. Built with MERN, LangChain, Hugging Face embeddings, vector search (HNSWLib), and LLMs using Retrieval-Augmented Generation (RAG).