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Formidium Hackathon Winner Repo - RAG Chatbot for Predictive Analysis of Business Data

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sujeethshingade/bizrag-bot

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Bizrag Bot

  • Bizrag Bot leverages a RAG framework, where it combines a retrieval mechanism (to pull relevant data or documents) with a generative model, providing answers grounded in accurate, business-specific information.

  • This architecture allows it to handle complex queries that require contextual understanding and up-to-date, reliable answers, making it highly suitable for business support, client queries, and decision-making tasks.

Features

  • Information Retrieval: Pulls data from a structured source (like a database) or unstructured documents, ensuring answers are fact-based and relevant.

  • Scalable Knowledge Base: Easily incorporates additional documents, FAQs, or datasets, which makes it adaptable to growing or changing business knowledge.

  • History Management: Keeps track of chat history, Dashboard provides all of previous interactions.

  • User Authentication: Allows authenticated sessions, restricting access to sensitive business information only to verified users.

  • Real-time Querying: Answers questions promptly, suitable for client support or internal team assistance, reducing response time for queries.

Installation

Frontend

npm install
npm run dev

Backend

cd backend && python -m venv venv
source venv/Scripts/activate
pip install -r requirements.txt
python app.py

Login Credentials

Username: test@bizrag.com Password: 123456