RAG Chatbot System

📌 Overview

This project demonstrates the implementation of Retrieval-Augmented Generation (RAG) chatbots using custom knowledge bases. The system retrieves relevant information from vector databases and uses Large Language Models (LLMs) to generate context-aware responses.

The project includes two knowledge-based chatbot applications.

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🎯 Project Objectives

1. IPSR Courses Chatbot

An AI-powered chatbot designed to help users explore and identify suitable IPSR courses based on their interests, learning goals, and available course information.

2. Union Budget Chatbot

A knowledge-based chatbot that answers questions related to the Union Budget using a dedicated document collection and retrieval system.

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🛠️ Technologies Used

• Python
• Retrieval-Augmented Generation (RAG)
• Hugging Face Embeddings
• Pinecone Vector Database
• n8n Workflow Automation
• Large Language Models (LLMs)

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🔄 System Workflow

Knowledge Base Documents
          ↓
    Text Processing
          ↓
     Text Chunking
          ↓
   Hugging Face Embeddings
          ↓
   Pinecone Vector Database
          ↓
      User Query
          ↓
  Relevant Information Retrieval
          ↓
      RAG Context
          ↓
         LLM
          ↓
   Context-Aware Response

## Internship

Data Science & AI Internship
IPSR Solutions Ltd