Automated systems are crucial for summarizing medical information. Large Language Models (LLMs) show promise in healthcare, specifically for Closed-Book Generative QnA. This study compares general and medical-specific LMs, evaluates their performance in medical Q&A, and provides insights into their suitability for medical applications.

QnA demo application

Document based RAG QnA Chatbot Application

QnA application made using OpenAI API, Redis and Docker

This project implements a QnA-based RAG (Retrieval-Augmented Generation) application that transforms user queries into structured questions. It retrieves relevant information from a knowledge base to provide accurate, context-aware answers. Built with AI and NLP techniques, it enhances chatbot interactions by delivering real-time, precise responses

A RAG based QnA Application over the LangChain documentation.

BERT model is used to build a Question-Answering system which answers user’s question using the content and questions file uploaded by them to the server for processing.

Porting my old Qna app from MongoDB to MySQL database; Old QnA application can be found at https://github.com/marthenlt/ask-gpdi-tomotius-sg.git

🎥 Youtube QnA - This application helps you to communicate and get your questions answered about youtube videos

Whisper-Box just as the name says, it is a full-stack anonymous message sending application. Just like QnA link used in social medias

Retrieval Augmented Generation QnA application with Azure OpenAI and SpringAI

QnA Bot Application using QnAMaker, LUIS, and Microsoft Bot Framework

QNA Application with Laravel. It contains the concept of the very popular website Stackoverflow. Here we can (i)Ask a question. (ii) Answer any question. (iii) Vote question and answer and by the voting priority Questions and answers will be displayed in ascending order. (iv) Users can delete or modify their own questions and answers.

A QnA application built using RAG architecture. It is built using LlamaIndex and Google Gemini which also have the embedding model from HuggingFace named 'BAAI/bge-small-en-v1.5'

Welcome to the Generative AI-Powered Insights Platform! This project is designed to provide in-depth insights from various types of documents using advanced generative AI and vector stores. The platform features a conversational interface that allows users to ask questions about their documents and receive detailed, contextual response

simple chat qna application with react

No description available

QnA based flutter application with live data fetching.

A project based on rag for QNA application

Retrieval Augmented Generation QnA application with OpenAI and SpringAI

A Node.js application for remote relevance evaluation via QnA

It is a python based qna web application using Django.

An API built for a Question and Answer (QnA) Application. Deployed on Heroku.

This is a DIY Virtual Assistant application that utilises Microsoft Cognitive Speech API and QnA Maker API.

This repo provides a sample QnA application powered by the Dataworkz RAG Builder that demonstrates the power of RAG on several datasets.

A implementation of a simple RAG application using a vector database (Chroma DB) backed LLM Inference using LangChain to create a simple QnA inference.

Join me in testing the capabilities of a pre-trained QnA model for my Query Mind application on Google Colab! This Github repository showcases my experimentation with state-of-the-art NLP techniques to enhance the accuracy of question-answering systems. Let's push the boundaries of AI together!

Alya is a free web-based application developed for girls and womens in developing countries. Its main objective is to answer questions around taboo topics such as Menstrual Hygiene and Menstruations/Periods. Menstrual Hygiene is a hygiene practice during menstruation which can prevent women from the infection in reproductive and urinary tract. This website is made using Azure technologies such as Azure Bot Services, Azure Language Understanding and Azure QnA Maker. Here I have trained my model using QnAMaker. In QnA Maker, I have provided the datasets in the knowledge base. After that I published my knowledge data and then connected it to the website. In this website, there are four pages - Home, History, Team and FAQ. Here, I'm trying to solve the real- world problem where particularly girls have very less knowledge about menstrual hygienies and they feel shy to talk about these problems in-person. So this application/website will answer questions related to hygiene and menstruations for womens.

QNA Bot Application

QnA Application.