AI Chatbot

• Integrated NLP model for intelligent responses.

• Can be trained or connected with other APIs (like OpenAI, Hugging Face, etc.).

• Works with real-time message exchange.

🎯 AI Recommendation Engine

• Generates personalized suggestions based on user behavior or database inputs.

• Uses Python machine learning libraries for analysis (e.g., scikit-learn / pandas).

• Clean modular structure — easy to upgrade or replace algorithms.

🖥️ Front-End (React)

• Clean and responsive UI with modern design.

• Chat interface with typing animation and user/bot message separation.

• State management for conversation flow.

🌐 Backend (Node + Express)

• Secure REST APIs for chat and recommendation endpoints.

• JWT-based authentication (optional, can be enabled).

• MongoDB integration for storing users and interaction data.

🧩 Python AI Microservice

• Handles all AI logic separately for better scalability.

• Easy integration with APIs or external ML models.

• Simple configuration file for API keys and model paths.

⚡ Developer-Friendly

• Well-structured and commented code.

• .env.example file provided for configuration.

• Ready-to-run setup instructions in the README.

• Works locally or can be deployed on cloud platforms.

🧰 Tech Stack

• Frontend: React.js, HTML, CSS, Axios

• Backend: Node.js, Express.js, MongoDB

• AI Layer: Python (Flask or FastAPI), scikit-learn, pandas, NumPy

• Communication: REST APIs / JSON

• Version Control: Git-ready structure

📦 What You’ll Get

• Full project source code (MERN + Python folders)

• Setup & installation guide (README.md)

• Example .env configuration

• Demo video link (YouTube presentation)

• License and documentation files