🎵 Rhythm Rang – Audio & Video Music Web Application

Rhythm Rang is a complete music streaming platform that allows users to listen to audio tracks, watch music videos, explore albums and artists, and create their own playlists/wishlist.
The project also includes a custom AI chatbot built in Python (Flask, PyTorch, NLTK) that answers user queries and assists in navigating the website.

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🚀 Features

🎧 User Features

• Stream audio songs and music videos directly in the browser.
• Browse albums and artists with detailed information.
• User authentication – Register, log in, and manage account settings.
• Wishlist – Save favorite songs/videos for later.
• Search & filtering – Quickly find music content.
• Responsive and user-friendly interface.

🛠 Admin Features

• User Management – Add, edit, and remove users.
• Content Management (CRUD) – Manage songs, videos, albums, artists, and upcoming releases.
• Website Configuration – Update banners, sliders, posters, and featured content.
• Media File Handling – Upload and organize music/audio/video assets.

🤖 AI Chatbot

• Developed using Python, Flask, PyTorch, and NLTK.
• Trained on custom intents for music-related questions.
• Hosted as a REST API and integrated into the PHP application via JavaScript.
• Can run independently from the PHP app.

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🛠 Tech Stack

Frontend:

• HTML5, CSS3, JavaScript
• Bootstrap & custom styles
• AJAX for dynamic loading

Backend:

• PHP (core web app logic)
• MySQL (database)
• Flask (Python API for chatbot)
• PyTorch & NLTK (chatbot ML model)

Other Tools:

• REST API integration between PHP & Python services
• MVC-like folder organization
• CRUD-based admin panel

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📂 Project Structure

Sound/
├─ admin2/                         # Admin Panel
│  ├─ assets/
│  ├─ check/                       # CSS/JS for checks
│  ├─ css/
│  ├─ css2/
│  ├─ headerandfooter/
│  ├─ images/
│  ├─ js/
│  └─ pages/                       # Admin PHP files & media
│     ├─ audio/                    # Audio files
│     ├─ video/                    # Video files
│     ├─ banners/                  # Banner images
│     ├─ slider/                   # Slider images
│     ├─ artists/                  # Artist images
│     └─ ...                       # Other admin resources
│
├─ chatbot/                        # Python Chatbot Project
│  ├─ frontend/                    # Chatbot UI (HTML/CSS/JS)
│  ├─ app.py                       # Flask API server
│  ├─ train.py                     # Model training script
│  ├─ chat.py                      # Console chatbot
│  ├─ model.py                     # PyTorch model definition
│  ├─ nltk_utils.py                # NLP utilities
│  ├─ intents.json                 # Training data (intents)
│  ├─ data.pth                     # Trained model weights
│  └─ ...                          # venv, __pycache__, etc.
│
├─ report/
│  └─ PROJECTREPORT.pdf
│
├─ user/                           # User-facing Web App
│  ├─ css/
│  ├─ js/
│  ├─ headerfooter/
│  ├─ images/
│  └─ *.php                        # Frontend PHP pages
│
├─ sound.sql                       # MySQL database dump
└─ README.md

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🚀 Installation & Setup

1️⃣ Clone Repository

git clone https://github.com/yourusername/sound.git
cd sound

2️⃣ Database Setup

1. Import sound.sql into your MySQL server.
2. Update database credentials in the PHP config file.

3️⃣ Chatbot Setup

Initial Setup

cd chatbot
python3 -m venv venv
source venv/bin/activate   # On Windows use: venv\Scripts\activate

Install Dependencies

pip install Flask torch torchvision nltk

Install NLTK Data

python
>>> import nltk
>>> nltk.download('punkt')

Modify Training Data

Edit intents.json with your own intents and responses.

Train the Chatbot

python train.py

Test in Console

python chat.py

Run Flask API

python app.py

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🖥 Running the Full Application

1. Start your PHP server (XAMPP, WAMP, etc.) for the user and admin2 folders.
2. Start Flask API for the chatbot:

   cd chatbot
   source venv/bin/activate
   python app.py

3. Access the site in the browser (e.g., http://localhost/sound/user).

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✨ Author Developed by Abdul Rehman as part of a full-stack web development project.