There are 1 repository under qa-system topic.
Dataset Resplitting for Generalization in KGQA. See also https://github.com/semantic-systems/KGQA-datasets
Q&A System using BERT and Faiss Vector Database
RagE (RAG Engine) - A tool supporting the construction and training of components of the Retrieval-Augmented-Generation (RAG) model. It also facilitates the rapid development of Q&A systems and chatbots following the RAG model.
A modern and lightweight NLP interface for Question-Answering systems and more. Fork this project to showcase your Python models with elegant web applications in no time!
Knowledge-Based Question Answering --TF2 Version
In this academic project, I have compared the performance of different NLP approaches for Question-Answering system using varied levels (easy, medium, hard) of FAQs.
We built a Question Answer System using BERT. Based on our benchmark dataset that we designed for a specific task, we evaluated it at 40% accuracy over a particular dataset.
Military-oriented knowledge question-answer system, it supports different way to ask.
This project implements a Retrieval Augmented Generation (RAG) Pipeline for PDF documents. It extracts information, generates embeddings, and uses LLMs to provide intelligent responses via an interactive Streamlit UI. Ideal for building Q&A systems on custom knowledge bases
Project repository for the development of a Question-Answering (QA) information retrieval system fine-tuned on customer queries.
QueryVault is a robust RAG system for structured Q&A data. It ingests JSON files, embeds content via ChromaDB, and serves context-aware answers using FastAPI and Google Gemini. With a modular design and CLI tools, it's built for scalable, secure AI-powered knowledge retrieval.
Full-stack referral and Q&A system built for events, featuring intelligent agents for automated question-answering and a comprehensive ranking system for referrals
A RAG-based retrieval system for air pollution topics using LangChain and ChromaDB.
A QA system for answering questions about environmental issues. Built using Haystack and Wikipedia.
Frontend React + TypeScript para sistema inteligente de Q&A com respostas automáticas por IA, transcrição de áudio em tempo real e busca semântica para automação de transmissões ao vivo.
Русскоязычная QA система обернутая в Telegram-бот
🤖 A toy Transformer Q&A model simulator demonstrating core concepts of large language models through memorized Q&A pairs. Educational demo with interactive web interface.
將 Notion 內容轉換為智慧問答系統,支援繁體中文與 OpenAI GPT 整合 | Convert Notion content into intelligent Q&A system with Taiwan localization
A local LLM that answers user doubts using fine-tuned models and real-time search.
A collection of 1,397 Wikipedia articles related to environmental issues, for QA systems.
web-based Question Answering (QA) system powered by the BERT model and Transformers AI technology
Web-Based Q&A Tool enables users to extract and query website content using FastAPI, FAISS, and a local TinyLlama-1.1B model—without external APIs. Built with React, it offers a minimal UI for seamless AI-driven search
Question Answering System via Semantic Role Labeling Using Token Classification and Parsing Techniques
🤖 A toy Transformer Q&A model simulator demonstrating core concepts of large language models through memorized Q&A pairs. Educational demo with interactive web interface.