Study Chatbot RAG + Intent

A study RAG and intnet chatbot, flexible conversational AI for education and research. It combines natural language understanding, retrieval-augmented generation, LLM, and web search to provide accurate and context-aware responses.


Github Link!

Overview

This chatbots that interpret user intents, fetch relevant information from diverse sources, and generate meaningful replies.

Technologies

• Tensorflow

• Python

• FAISS

• Sentence Transformers

• Ollama (Local LLM)

• Tavily Web Search API

Features

• Intent Recognition: Uses machine learning to accurately classify user queries, ensuring relevant responses

• Retrieval-Augmented Generation: Combines semantic search with language models to produce precise, contextually rich answers

• Web Search Integration: Leverages APIs to fetch real-time data, expanding the knowledge base dynamically

• Data Logging & Analysis: Supports record-keeping and continuous improvement of chatbot performance