frontend : npm run start backend : npm run start ai : npm run PoweredAi django : python manage.py runserver 8000

Project: AI Chatbot (Mega Project 2025)

Description: An intelligent chatbot system built using machine learning and full-stack technologies, enabling interactive conversations and automated responses through a unified interface.

Key Modules & Responsibilities:

1. 🧠 Machine Learning Module

   • Implemented a Decision Tree Classifier using scikit-learn for intent recognition and response generation.
   • Designed and trained custom datasets to enhance chatbot understanding accuracy.
   • Integrated ML logic within Django backend (views.py) to handle user queries and model predictions dynamically.

2. 🌐 Frontend Module (React.js)

   • Built a dynamic Chatbot UI using React.js for smooth, real-time interactions.
   • Managed app-wide state using Redux & Redux-Thunk for API handling and user context.
   • Integrated custom chatbot icons and reusable components (chatbotUi.jsx).

3. ⚙️ Backend API (Django + Node.js)

   • Developed robust RESTful APIs for message exchange between frontend and ML model.
   • Used Django for ML logic hosting and Node.js for socket communication.
   • Implemented WebSocket connections for real-time chatbot responses.

4. 🗃️ Database & Configuration Module

   • Managed chatbot configurations (icon, name, URLs) in the Admin Panel.
   • Stored and retrieved chatbot data (chat history, user info) efficiently using MongoDB.
   • Supported multi-chatbot integration by dynamically linking chatbot icons and names.

5. 🧩 Admin Panel Module

   • Enabled chatbot creation through the Admin interface with custom settings:

     • IconUrl, ChatBotName, BackendUrl, and FrontendUrl.

   • Allowed easy deployment of multiple chatbots with unique ML logic.

6. 💬 Chatbot Interface (Integration Module)

   • Connected front-end chat interface with backend ML model responses in real time.
   • Handled bidirectional message flow and dynamic UI updates using WebSocket and Axios.
   • Ensured seamless multi-chatbot rendering from the AllApps/IconRender component.

7. 🔐 Security & Optimization

   • Implemented secure API endpoints and controlled admin access.
   • Optimized data exchange and minimized latency using efficient WebSocket communication.

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🧾 GitHub README (Professional Version)

# 🤖 MEGA PROJECT 2025: AI Chatbot  

An intelligent AI Chatbot system integrating **Machine Learning**, **React.js**, **Node.js**, and **Django** to enable real-time interactive conversations.  
This chatbot uses a **Decision Tree Classifier** model to predict user intent and respond dynamically.  

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## 🧠 Core Technologies

| Layer | Technologies Used |
|-------|--------------------|
| **Frontend** | React.js, Redux, Redux-Thunk |
| **Backend** | Django (Python), Node.js |
| **Machine Learning** | scikit-learn (Decision Tree Classifier) |
| **Database** | MongoDB |
| **Other Tools** | WebSocket, REST API, VS Code, Postman, Git |

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## ⚙️ Project Modules

### 1. Machine Learning (AI Logic)
- Implemented Decision Tree Classifier using scikit-learn.
- Built custom dataset and trained model for chatbot intent prediction.
- Integrated ML logic in `ai/chatbot/chatbot/views.py` for live responses.

### 2. Frontend (React.js)
- Designed **ChatBot UI** (`Components/ChatBotUi/chatbotUi.jsx`).
- Added icons from `src/Assets/ChatbotIcons/icon.png`.
- Managed app-wide state using **Redux** & **Thunk**.
- Integrated WebSocket for real-time chat communication.

### 3. Admin Panel
- Created module for new chatbot creation:
  - **IconURL:** `"../../Assets/ChatbotIcons/TSI.png"`
  - **ChatBotName:** `"TSI"`
  - **BackendUrl:** `"http://127.0.0.1:8000/"`
  - **FrontendUrl:** `"../ChatBotUI/TSI"`
- Enabled quick chatbot deployment and customization.

### 4. Backend (Django + Node.js)
- Django serves ML responses via REST APIs.
- Node.js handles WebSocket connections for live message exchange.
- Provides scalable multi-chatbot integration.

### 5. Database & Configuration
- Stored chatbot settings, user info, and message logs in **MongoDB**.
- Linked new chatbots dynamically through `AllApps → IconRender`.

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## 🚀 Features

- Interactive chatbot interface with AI-powered responses  
- Multi-chatbot support with custom configurations  
- Real-time WebSocket-based messaging  
- Admin panel for chatbot creation and management  
- Secure API architecture with fast response handling  
- Full-stack integration between React, Node, and Django  

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## 📂 Project Setup

```bash
# Clone repository
git clone https://github.com/yourusername/ai-chatbot-2025.git

# Frontend setup
cd frontend
npm install
npm start

# Backend setup
cd backend
pip install -r requirements.txt
python manage.py runserver

# Node WebSocket server
cd socket-server
npm install
npm run start

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📸 Screenshots

HappyHacking

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🧑‍💻 Author

Om Shahane Full Stack & AI Developer 📧 [email protected] 🌐 LinkedIn | GitHub

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