This project builds a custom question answering chatbot using Langchain and Google Gemini Language Model (LLM). It fine-tunes industrial data for accurate responses and integrates Streamlit for user interaction, aiming to enhance user experience.

Build a Full stack Q&A Chatbot with Langchain, and LLM Models on Amazon Sagemaker

A high-performance Q&A chatbot that uses the Groq API and Llama 3 for real-time, context-aware answers from multiple PDF documents. This project leverages LangChain for orchestration, FAISS for local vector search, and Streamlit for an interactive user interface. Ideal for efficient and private document analysis.

Welcome to the RAG-Projects repository! This collection contains various projects and tutorials centered around Retrieval-Augmented Generation (RAG) techniques using Langchain. Each project showcases different aspects and applications of Langchain in building intelligent systems, including chatbots, document Q&A systems, and more.

Finbot is an AI-powered financial chatbot designed to analyse and provide insights on corporate financial performance from 10-K and 10-Q financial documents. This tool leverages langchain and RAG to make complex financial data easily accessible and understandable through a conversational interface.

PrepNexus is an AI-driven system using a fine-tuned RoBERTa model for resume analysis and job role recommendations, built a LangChain-ChromaDB powered interview chatbot with LLaMA-3 (8B) for real-time technical Q&A, and implemented a BeautifulSoup-based job scraping pipeline to enhance job search efficiency by 40%.

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Auto-respond to GitHub issues and offer chat & Q&A features about your favorite repository. Clone a repo, initialize a chatbot or QA system, mention-based comment replies, and a user-friendly chat UI. Built on Langchain, it provides advanced NLP capabilities.

This project is an education-focused, Hogwarts-themed Q&A Chatbot built with LangChain, FAISS, and ChatGroq. Users can upload PDFs, including textbooks, research papers, or notes, which are processed for answering queries using a RAG pipeline. The chatbot delivers educational insights with a touch of magical charm, all with an engaging Streamlit UI

A production-ready conversational RAG chatbot with memory-enabled follow-up questions, built using FastAPI, Streamlit, LangChain, and Chroma DB for intelligent document Q&A.

A langchain / OpenAI powered Q&A chatbot implementation

PDF Q&A chatbot using LangChain and Gemini Pro

Q&A Chatbot Demo using Couchbase, LangChain, OpenAI and Streamlit

Q&A chatBot for wolfSSL powered by RAG using LangChain, Semantic Router

In this project, we are creating a question answer chat bot which will take any document, research paper, book or article as input and will answer any question related to that document. For this purpose, we are using langchain as our framework along with different LLMs (Large language models).

Simple Chatbot using LangChain just Q & A Generative AI Application.

This is a simple Q&A chatbot built using Retrieval-Augmented Generation (RAG). The chatbot retrieves relevant information using embeddings and then generates answers using a DeepSeek R1 model via the Groq API. The project is implemented using the LangChain framework in Python.

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Paper Q/A Chatbot and Knowledge Graph Builder powered by LangChain and OpenAI

A Retrieval-Augmented Generation (RAG) ChatBot using LangChain, HuggingFace, and Groq’s LLaMA model — allowing interactive Q&A on uploaded PDFs via a sleek Streamlit interface.

A powerful multi-document(PDF,DOCX,PPT,MD,EXCEL,TEXT) chatbot that parses and chunks diverse files, indexes them with vector embeddings, and enables conversational retrieval with memory. Built with LangChain, LlamaParse, HuggingFace, Chroma, and Groq LLM API for seamless Q&A over documents.

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.

A full-stack Q&A chatbot built with React and Django, powered by LangChain and Hugging Face’s Meta-Llama-3-8B-Instruct model. Features a sleek, real-time chat interface for asking questions and receiving AI-generated answers, with a history-clearing option. Showcases seamless integration of AI-driven NLP with modern web development.

RAG powered AI chatbot for Indian Language (Hindi) using LangChain, Ollama, Qdrant, and MLFlow

Chatbot code using Qdrant as a vector Database, ChatGPT and Langchain.

FastAPI backend for an LLM academic assistant chatbot. Provides RAG-based curriculum Q&A, notice retrieval, and schedule management using LangChain, LangGraph, ChromaDB, and HuggingFace embeddings.

Q&A Chatbot using Llama3,Langchain and Groq API

PDF Q&A Chatbot using Groq, Langchain, and Streamlit

A free Document Q&A chatbot using Langchain and streamlit

Local PDF Q&A chatbot built with Streamlit and LangChain