Add comprehensive README.md and update project description

Co-authored-by: npv2k1 <[email protected]>

Author: Copilot

README.md

@@ -0,0 +1,139 @@
+# mlenv
+
+A comprehensive machine learning environment and toolkit built with modern Python packaging and containerized deployment.
+
+## Overview
+
+`mlenv` provides a ready-to-use machine learning environment with popular ML/AI libraries and frameworks. It's designed for data scientists, ML engineers, and researchers who need a consistent, reproducible environment for machine learning projects.
+
+## Features
+
+- **Deep Learning**: PyTorch ecosystem (torch, torchaudio, torchvision)
+- **NLP & Transformers**: Hugging Face transformers and hub integration
+- **Computer Vision**: OpenCV and Ultralytics (YOLOv8+)
+- **Web Interfaces**: FastAPI for APIs and Gradio for interactive demos
+- **Data Analysis**: Pandas, NumPy for data manipulation
+- **Financial Analysis**: mplfinance for financial data visualization
+- **Interactive Computing**: Jupyter kernel support
+- **Gaming/Graphics**: Pygame for game development and graphics
+- **Containerized**: Docker support with multi-architecture builds
+- **Modern Packaging**: Uses uv for fast dependency management
+
+## Requirements
+
+- Python 3.11 or higher
+- Docker (optional, for containerized deployment)
+
+## Installation
+
+### Using uv (recommended)
+
+```bash
+# Install uv if you haven't already
+pip install uv
+
+# Clone the repository
+git clone https://github.com/pnstack/mlenv.git
+cd mlenv
+
+# Install dependencies
+uv sync
+```
+
+### Using pip
+
+```bash
+# Clone the repository
+git clone https://github.com/pnstack/mlenv.git
+cd mlenv
+
+# Install dependencies
+pip install -e .
+```
+
+### Using Docker
+
+```bash
+# Build the Docker image
+docker build -t mlenv .
+
+# Run a Python script
+docker run --rm -v $(pwd):/workspace mlenv /workspace/hello.py
+
+# Run interactively
+docker run --rm -it mlenv
+```
+
+## Quick Start
+
+Test the installation with the included hello script:
+
+```bash
+python hello.py
+```
+
+This should output: `Hello from mlenv!`
+
+## Key Dependencies
+
+| Package | Purpose |
+|---------|---------|
+| **torch, torchaudio, torchvision** | PyTorch deep learning framework |
+| **transformers** | Hugging Face transformers for NLP |
+| **ultralytics** | YOLOv8+ object detection |
+| **opencv-python** | Computer vision library |
+| **fastapi** | Modern web framework for APIs |
+| **gradio** | Interactive ML demos and UIs |
+| **pandas, numpy** | Data manipulation and analysis |
+| **mplfinance** | Financial data visualization |
+| **pygame** | Game development and graphics |
+
+## Development
+
+### Running Tests
+
+```bash
+pytest
+```
+
+### Code Style
+
+```bash
+# Check code style
+pep8 .
+```
+
+### Docker Development
+
+The project includes a multi-stage Dockerfile optimized for production use:
+
+```bash
+# Build for development
+docker build -t mlenv:dev .
+
+# Build for production with optimizations
+docker build -t mlenv:prod --target=base .
+```
+
+## CI/CD
+
+The project uses GitHub Actions for automated:
+- Multi-architecture Docker builds (linux/amd64, linux/arm64)
+- Container publishing to GitHub Container Registry
+- Automated testing on push and pull requests
+
+## Contributing
+
+1. Fork the repository
+2. Create a feature branch (`git checkout -b feature/amazing-feature`)
+3. Commit your changes (`git commit -m 'Add some amazing feature'`)
+4. Push to the branch (`git push origin feature/amazing-feature`)
+5. Open a Pull Request
+
+## License
+
+This project is open source. Please check the repository for license details.
+
+## Support
+
+For questions, issues, or contributions, please open an issue on the GitHub repository.

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "mlenv"
 version = "0.1.0"
-description = "Add your description here"
+description = "A comprehensive machine learning environment and toolkit with PyTorch, transformers, and modern Python packaging"
 readme = "README.md"
 requires-python = ">=3.11"
 dependencies = [