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This project is a dynamic AI chatbot that can be trained from various sources, such as PDFs, documents, websites, and YouTube videos.

AI-powered healthcare platform with features like chat-based consultations, medication reminders, and appointment scheduling. Built during Postman x BITS Pilani API Hackathon 4.0.

Building an Rag-based HR chatbot for providing rules in workplace with MCP server

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RAG-based chatbot using FastAPI, React, and ChromaDB

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LLM Chatbot Enhanced with Retrieval-augmented generation

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This repository builds a simple RAG chatbot in Python using Pinecone for the vector database and embedding model, Llama-3.2 for the LLM, and LangChain for the RAG workflow.

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RAG 챗봇 서비스 공공 레포지토리

MSAI-631-B02-Group2Project-RAGChatbot

here created a RAGchatbot using FAISS

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Different variations of questions answering over a document using RAG

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here shared a RAGchatbot build by using LLM

RAGChatbot is an AI-powered chatbot that leverages Retrieval-Augmented Generation (RAG) to provide accurate and context-aware responses. It retrieves relevant information from external documents before generating responses, ensuring high-quality answers.

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Full-stack chatbot using local embeddings and \textbf{Google Gemini AI} for context-aware Q&A.

An experimental project to deepen my understanding of LLM architectures and applications through practical implementations.

Academic Chatbot using Retrieval-Augmented Generation (RAG)

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