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-# hscodesdotnet
-Hs Codes ASP.Net Version
+# HS Codes Classification System
+
+A comprehensive .NET application for Harmonized System (HS) code classification and commodity search, featuring AI-powered prediction capabilities and a modern web interface.
+
+## Overview
+
+This system provides intelligent HS code classification for international trade, combining traditional database search with machine learning predictions to help users find the most appropriate HS codes for their products.
+
+## Features
+
+- **AI-Powered Classification**: Machine learning model for automatic HS code prediction
+- **Hierarchical Navigation**: Browse HS codes through structured categories
+- **Product Search**: Search and classify products with detailed descriptions
+- **Customs Tariff Information**: Access tariff rates and import/export requirements
+- **Currency Exchange Rates**: Real-time currency conversion support
+- **Document Management**: Store and manage classification documents
+- **Search Analytics**: Track and log search patterns for optimization
+- **Multi-Environment Support**: Development, staging, and production configurations
+
+## Architecture
+
+The application follows a clean architecture pattern with the following layers:
+
+- **Autumn.UI**: Web application with Razor Pages
+- **Autumn.API**: RESTful API with Swagger documentation
+- **Autumn.BL**: Business logic and services
+- **Autumn.Domain**: Domain models and entities
+- **Autumn.Repository**: Data access layer
+- **Autumn.UIML.Model**: Machine learning model for predictions
+
+## Technology Stack
+
+- **.NET 9.0**: Core framework
+- **ASP.NET Core**: Web framework
+- **MongoDB**: Document database for HS codes and products
+- **SQL Server**: Relational database for structured data
+- **ML.NET**: Machine learning framework
+- **AutoMapper**: Object mapping
+- **Auth0**: Authentication and authorization
+- **Docker**: Containerization
+- **Nginx**: Reverse proxy and load balancer
+
+## Prerequisites
+
+- .NET 9.0 SDK
+- MongoDB
+- SQL Server
+- Docker (optional)
+
+## Quick Start
+
+### Using Docker (Recommended)
+
+1. Clone the repository:
+
+```bash
+git clone
+cd hscodesdotnet
+```
+
+2. Start the application:
+
+```bash
+docker-compose up -d
+```
+
+The application will be available at `http://localhost`
+
+### Manual Setup
+
+1. **Configure Databases**:
+
+ - Set up MongoDB instance
+ - Configure SQL Server connection
+ - Update connection strings in `appsettings.json`
+
+2. **Build and Run**:
+
+```bash
+dotnet restore
+dotnet build
+dotnet run --project Autumn.UI
+```
+
+3. **API Documentation**:
+ - Navigate to `/swagger` for API documentation
+ - Available at `http://localhost:5000/swagger`
+
+## Configuration
+
+### Database Settings
+
+Update the following in `appsettings.json`:
+
+```json
+{
+ "StoreDatabaseSettings": {
+ "ConnectionString": "mongodb://localhost:27017",
+ "DatabaseName": "ClassificationDb"
+ },
+ "ConnectionStrings": {
+ "DefaultConnection": "your-sql-server-connection-string"
+ }
+}
+```
+
+### Authentication
+
+Configure Auth0 settings:
+
+```json
+{
+ "Auth0": {
+ "Domain": "your-auth0-domain",
+ "ClientId": "your-client-id"
+ }
+}
+```
+
+## API Endpoints
+
+### Search Operations
+
+- `GET /api/v1/search` - Search HS codes
+- `GET /api/v1/classify/commodity` - Classify commodity
+- `GET /api/v1/note` - Get classification notes
+
+### Data Management
+
+- `GET /api/v1/hscode` - Retrieve HS codes
+- `GET /api/v1/product` - Product information
+- `GET /api/v1/currency` - Currency exchange rates
+
+## Machine Learning
+
+The system includes a pre-trained ML model for HS code prediction:
+
+- **Model**: ML.NET classification model
+- **Input**: Product descriptions and keywords
+- **Output**: Predicted HS codes with confidence scores
+- **Threshold**: Configurable confidence threshold (default: 0.02)
+
+## Development
+
+### Project Structure
+
+```
+├── Autumn.UI/ # Web application
+├── Autumn.API/ # REST API
+├── Autumn.BL/ # Business logic
+├── Autumn.Domain/ # Domain models
+├── Autumn.Repository/ # Data access
+├── Autumn.UIML.Model/ # ML model
+└── docker-compose.yml # Container orchestration
+```
+
+### Adding New Features
+
+1. Create domain models in `Autumn.Domain`
+2. Implement repository interfaces in `Autumn.Repository`
+3. Add business logic in `Autumn.BL`
+4. Create API controllers in `Autumn.API`
+5. Update UI pages in `Autumn.UI`
+
+## Deployment
+
+### Production Deployment
+
+1. **Build Docker Image**:
+
+```bash
+docker build -t hscodes:latest .
+```
+
+2. **Deploy with Docker Compose**:
+
+```bash
+docker-compose -f docker-compose.prod.yml up -d
+```
+
+3. **Configure Nginx**:
+ - Update `nginx.conf` for your domain
+ - Set up SSL certificates
+ - Configure load balancing
+
+### Environment Variables
+
+Set the following environment variables for production:
+
+- `ASPNETCORE_ENVIRONMENT=Production`
+- `ConnectionStrings__DefaultConnection`
+- `StoreDatabaseSettings__ConnectionString`
+- `Auth0__Domain`
+- `Auth0__ClientId`
+
+## Contributing
+
+1. Fork the repository
+2. Create a feature branch
+3. Make your changes
+4. Add tests if applicable
+5. Submit a pull request
+
+## License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+
+## Support
+
+For support and questions:
+
+- Create an issue in the repository
+- Contact the development team
+- Check the API documentation at `/swagger`
+
+## Changelog
+
+### Version 1.09
+
+- Updated to .NET 9.0
+- Enhanced ML model accuracy
+- Improved search performance
+- Added Docker support
+- Updated authentication system