Animal Sales Application

Overview

The Animal Sales Application is a Python-based GUI tool designed to assist pet shops or animal breeders in managing sales and inventory. It uses image recognition to identify animal characteristics and matches them against a database of previous sales, helping to price new animals or find similar past sales.

Features

• Image analysis for animal identification
• Customer selection and management
• Database searching with tiered matching (breed first, then coat characteristics)
• Order form population from image analysis or database matches
• Mock order saving functionality

Prerequisites

Before you begin, ensure you have met the following requirements:

• Python 3.7 or higher
• SQLite3
• Tkinter (usually comes with Python)
• Pillow (PIL Fork) for image processing
• An Ollama server running with the llava:34b model for image analysis

Installation

1. Clone this repository:

   git clone https://github.com/yourusername/animal-sales-application.git
   cd animal-sales-application
   

2. Install the required Python packages:

   pip install -r requirements.txt
   

3. Ensure you have SQLite installed on your system.

4. Set up the Ollama server with the llava:34b model. Follow the instructions on the Ollama website for installation and model setup.

File Structure

• main.py: The main application script with GUI implementation
• database_operations.py: Handles all database-related operations
• image_analysis.py: Manages image analysis using the Ollama API
• models.py: Contains Pydantic models for data structures
• animal_sales.db: SQLite database file (you need to create this with appropriate schema)

Usage

1. Start the Ollama server with the llava:34b model.

2. Run the main application:

   python main.py
   

3. Use the GUI to:

   • Select a customer from the dropdown (or leave as "Any")
   • Click "Select Image" to choose an animal image for analysis
   • View matching sales results in the treeview
   • Double-click a result to populate the order form
   • Manually edit the order form as needed
   • Click "Save Order" to (mock) save the order

Database Schema

The animal_sales table should have the following structure:

CREATE TABLE animal_sales (
    id INTEGER PRIMARY KEY,
    date TEXT,
    species TEXT,
    breed TEXT,
    size TEXT,
    weight REAL,
    coat_length TEXT,
    coat_color TEXT,
    price REAL,
    client_name TEXT,
    client_email TEXT
);

Ensure your animal_sales.db file is set up with this schema before running the application.

Contributing

Contributions to the Animal Sales Application are welcome. Please follow these steps:

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

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Your Name - [email protected]

Project Link: https://github.com/shiftbug/catsanddogs

Acknowledgements

• Ollama for providing the image analysis model
• Tkinter for the GUI framework
• SQLite for the database engine
• Pydantic for data validation and settings management