🎉 Selected for Social Winter of Code 2025! 🎉

SocioSell: Social Media to Product Listing Generator 🛍️

An open-source initiative to transform social media content into comprehensive Amazon-style product listings using cutting-edge AI technology.

🌟 Features • ⚙️ Installation • 🚀 Usage • 💡 API Endpoints • 🤝 Contributing • 👥 Community

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🎯 Project Vision

SocioSell aims to bridge the gap between social media content and e-commerce by providing an open-source solution for automated product listing generation. Whether you're a developer, marketer, or e-commerce enthusiast, your contributions can help shape the future of social commerce.

📺 Project Demo

Watch our community demo:

🎥 Watch Demo

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🌟 Features

🤖 AI-Powered Analysis Google Generative AI integration Smart product detection Automatic feature extraction	🔄 Smart Processing Real-time processing Async operations Intelligent matching
🎯 Product Categories Electronics Fashion Home Decor Beauty Sports Equipment	💫 User Experience Modern UI/UX Drag-and-drop uploads Interactive comparisons

⚠️ Current Implementation Status and Limitations

Processing Limitations

• The system currently processes custom data that is not linked to the database
• Uses image_data and video_data for accessing media details
• Maximum processing capacity (due to Gemini API constraints):
  • Images: Maximum 5 images per request
  • Videos: Maximum 3 videos, each limited to 10 seconds

Implementation Notes for Contributors

• image_processor.py and video_processor.py are implemented and functional
• Integration needed: These processors need to be linked to main.py
• Database integration is pending and is a key area for contribution

Priority Areas for Contribution

1. Database Integration

   • Implement MongoDB connection for media storage
   • Create data models for products and listings
   • Add database querying functionality

2. Processor Integration

   • Link image_processor.py and video_processor.py to main.py
   • Implement error handling for processing failures
   • Add input validation for media files

3. UI/UX Improvements

   • Add progress indicators for processing
   • Implement drag-and-drop file upload
   • Create responsive design for mobile users

🛣️ Project Roadmap

Phase 1 (Current)

• ✅ Basic image and video processing
• ✅ Initial API setup
• 🔄 Database integration

Phase 2 (Upcoming)

• 📋 Enhanced error handling
• 📋 User authentication
• 📋 Batch processing capabilities

Phase 3 (Future)

• 📋 Advanced AI features
• 📋 Social media platform integration
• 📋 Analytics dashboard

🔧 Technology Stack

Backend Infrastructure

graph LR
    A[Python 3.8+] --> B[FastAPI]
    B --> C[MongoDB]
    B --> D[Gemini AI]
    B --> E[AsyncIO]

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Frontend Technologies

graph LR
    A[HTML5] --> B[TailwindCSS]
    B --> C[JavaScript]
    C --> D[Font Awesome]

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⚙️ Development Setup

# Clone repository
git clone https://github.com/Varsha-1605/SocioSell.git
cd SocioSell

# Set up virtual environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Create .env file
cat > .env << EOL
GOOGLE_API_KEY=your_google_api_key
MONGODB_URL=your_mongodb_connection_string
EOL

# Initialize database
python database_setup.py

Troubleshooting Common Issues

1. Gemini API Connection

Error: Failed to connect to Gemini API
Solution: Ensure GOOGLE_API_KEY is properly set in .env file

2. MongoDB Connection

Error: MongoDB connection failed
Solution: Check MONGODB_URL format and network connectivity

3. Image Processing

Error: Image processing failed
Solution: Verify image format (supported: jpg, png) and size (<5MB)

📁 Project Structure

SocioSell/
├── 📜 main.py                    # FastAPI application entry point
├── 📁 .github/                   # GitHub specific files
│   └── ISSUE_TEMPLATE/          # Issue templates for contributions
├── 📁 static/                    # Static assets and files
├── 📁 templates/                 # HTML templates
├── 🔧 content_processor.py       # Content analysis and processing
├── 💾 database_setup.py          # Database initialization
├── 🖼️ image_processor.py         # Image processing module
├── 📊 image_data.py              # Image data structures
├── 🎥 video_processor.py         # Video processing module
├── 📊 video_data.py              # Video data structures
├── 🧪 test_image_processor.py    # Image processing tests
├── 🧪 test_video_processor.py    # Video processing tests
├── 📋 requirements.txt           # Project dependencies
├── 📝 README.md                  # Project documentation
├── 🔒 .env                       # Environment variables
└── 📝 .gitignore                # Git ignore rules

🚀 Usage

1. Start the development server:

uvicorn main:app --reload

2. Access the application at http://localhost:8000

💡 API Endpoints

Endpoint	Method	Description
/upload/	POST	Upload & analyze products
/search/{title}	GET	Search product database
/listings/{product_id}	GET	Get listing details
/compare/{product_id}	GET	Compare products

🤝 Contributing

We warmly welcome contributions from developers of all skill levels! Here's how you can help:

graph TD
    A[Fork Repository] --> B[Create Branch]
    B --> C[Make Changes]
    C --> D[Commit Changes]
    D --> E[Push to Branch]
    E --> F[Create Pull Request]

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Detailed Contribution Guide

Star this repository ⭐

1. Environment Setup

# Fork and clone
git fork https://github.com/Varsha-1605/SocioSell
git clone [your-fork-url]
cd SocioSell

# Setup virtual environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt

# Configure environment variables
cp .env.example .env
# Edit .env with your API keys

2. Development Workflow

1. Find or create an issue
2. Comment for assignment
3. Create feature branch:

git checkout -b feature/your-feature-name

3. Code Guidelines

• Follow PEP 8
• Add docstrings
• Write unit tests
• Handle exceptions properly
• Use type hints

4. Submitting Changes

# Test your changes
python -m pytest

# Commit and push
git add .
git commit -m "feat: description"
git push origin feature/your-feature-name

5. Pull Request Process

1. Create PR from feature branch
2. Fill PR template
3. Link related issue
4. Await review

🎯 Good First Issues

• Look for issues tagged with good-first-issue
• Join our community discussions for guidance

👥 Community

• 💬 Join our Discord Server
• 🔗 Connect on LinkedIn
• 🐦 Follow us on Twitter
• 📧 Contact maintainers: varshadewangan1605@gmail.com

🌟 Contributors

Thanks to these wonderful people:

📄 License

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

🙏 Acknowledgments

• All our amazing contributors
• Social Winter of Code for selecting our project
• Google Generative AI
• MongoDB Atlas
• TailwindCSS
• FastAPI

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Made with ❤️ by the SocioSell Community

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