Repository navigation
qa-system
- Website
- Wikipedia
FAQ-based Question Answering System
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
Military-oriented knowledge question-answer system, it supports different way to ask.
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.
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
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.
Project repository for the development of a Question-Answering (QA) information retrieval system fine-tuned on customer queries.
🤖 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.
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.