README.md

AutoReview - AI-Powered Product Review Aggregator

AutoReview is a web application that aggregates and analyzes product reviews from multiple sources to provide summarized insights and ratings. Leveraging machine learning, it offers a comprehensive view of product sentiment and quality.

Features

• Aggregates product reviews from various sources (e.g., Amazon, Yelp).
• Analyzes sentiment of reviews (positive, negative, neutral).
• Provides summarized insights and ratings for each product.
• Real-time and periodic updates using cron jobs.
• Interactive charts and graphs for visualizing review data.

Tech Stack

• Frontend: React, Tailwind CSS
• Backend: Django, Django REST Framework (DRF)
• Machine Learning: Python-based ML models for sentiment analysis and text summarization
• Database: PostgreSQL / SQLite
• Cron Jobs: Celery
• Web Scraping / APIs: BeautifulSoup, Scrapy, or platform APIs
• Deployment: AWS, Heroku, Vercel, Netlify

Installation

Prerequisites

• Python 3.x
• Node.js and npm
• PostgreSQL / SQLite

Backend Setup

1. Clone the repository:

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

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install backend dependencies:

   pip install -r requirements.txt

4. Set up PostgreSQL and create a database. Update the database settings in autoreview/settings.py.

5. Run migrations to set up the database:

   python manage.py migrate

6. Set up Celery for periodic tasks:

   celery -A autoreview worker -l info

7. Run the Django development server:

   python manage.py runserver

Frontend Setup

1. Navigate to the frontend directory:

   cd frontend

2. Install frontend dependencies:

   npm install

3. Start the React development server:

   npm start

Configuration

• Machine Learning Models: Update paths and configurations for ML models in the autoreview/ml directory.
• Cron Jobs: Configure Celery tasks for data collection and updates in autoreview/tasks.py.

Usage

1. Search for Products: Use the search functionality to find products and view aggregated reviews.
2. View Insights: Explore summarized insights and sentiment analysis for each product.
3. Interactive Charts: Visualize ratings and sentiment distributions using interactive charts.

Contributing

1. Fork the repository.
2. Create a new branch (git checkout -b feature/your-feature).
3. Commit your changes (git commit -am 'Add new feature').
4. Push to the branch (git push origin feature/your-feature).
5. Create a new Pull Request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

• Machine Learning Libraries: Thanks to the open-source libraries used for sentiment analysis and summarization.
• Frontend Libraries: React and Tailwind CSS for a responsive and modern UI.
• Git Cheatsheet: https://education.github.com/git-cheat-sheet-education.pdf