Shopping Assistant API

A Flask-based API that provides shopping assistance through audio and image inputs, powered by Google's Gemini AI model.

Features

• Audio input processing with speech recognition
• Image analysis for product identification
• Structured product information responses
• Support for multiple product categories (Food, Clothes, Shoes)
• Detailed size and pricing information
• Rack location tracking

Prerequisites

• Python 3.8 or higher
• Google Cloud API key for Gemini AI
• Internet connection for API calls

Installation

1. Clone the repository:

git clone <repository-url>
cd <repository-name>

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables: Create a .env file in the root directory with:

GOOGLE_API_KEY=your_api_key_here

Usage

Starting the Server

python app.py

The server will start on http://0.0.0.0:5000

API Endpoints

1. Audio Input (/hardware/audio_input)

• Method: POST
• Input: Audio file (WAV format)
• Output Format:

{
    "transcription": "user's speech text",
    "text_response": {
        "Section": "section name",
        "Rack": "rack position",
        "Name": "product name",
        "Price": "price",
        "Size": "size information"
    }
}

2. Image Input (/hardware/image_input)

• Method: POST
• Input: Base64 encoded image
• Output Format:

{
    "text_response": {
        "Section": "section name",
        "Rack": "rack position",
        "Name": "product name",
        "Price": "price",
        "Size": "size information"
    }
}

Product Categories

1. Food

   • Available sizes: Small Pack (200g), Medium Pack (500g), Large Pack (1kg)
   • Products: Biscuits, Snacks, etc.

2. Clothes

   • Available sizes: S, M, L, XL, XXL
   • Products: T-shirts, Shirts, etc.

3. Shoes

   • Available sizes: US 6-12, UK 5-11, EU 39-45
   • Products: Leather Shoes, Formal Shoes, Loafers

Response Format

All responses follow this structure:

Section: [section name]
Rack: [rack position]
Name: [product name]
Price: [price]
Size: [size information]

Error Handling

The API handles various error cases:

• Invalid audio input
• Unsupported image format
• Missing API key
• Network errors
• Speech recognition errors

Testing

Use the provided test scripts:

• test_audio.py for testing audio input
• test_image.py for testing image input

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

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