Add GitHub Copilot instructions for FLAML repository

.github/copilot-instructions.md

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+# GitHub Copilot Instructions for FLAML
+
+## Project Overview
+
+FLAML (Fast Library for Automated Machine Learning & Tuning) is a lightweight Python library for efficient automation of machine learning and AI operations. It automates workflow based on large language models, machine learning models, etc. and optimizes their performance.
+
+**Key Components:**
+
+- `flaml/automl/`: AutoML functionality for classification and regression
+- `flaml/tune/`: Generic hyperparameter tuning
+- `flaml/default/`: Zero-shot AutoML with default configurations
+- `flaml/autogen/`: Legacy autogen code (note: AutoGen has moved to a separate repository)
+- `flaml/fabric/`: Microsoft Fabric integration
+- `test/`: Comprehensive test suite
+
+## Build and Test Commands
+
+### Installation
+
+```bash
+# Basic installation
+pip install -e .
+
+# Install with test dependencies
+pip install -e .[test]
+
+# Install with automl dependencies
+pip install -e .[automl]
+
+# Install with forecast dependencies (Linux only)
+pip install -e .[forecast]
+```
+
+### Running Tests
+
+```bash
+# Run all tests (excluding autogen)
+pytest test/ --ignore=test/autogen --reruns 2 --reruns-delay 10
+
+# Run tests with coverage
+coverage run -a -m pytest test --ignore=test/autogen --reruns 2 --reruns-delay 10
+coverage xml
+
+# Check dependencies
+python test/check_dependency.py
+```
+
+### Linting and Formatting
+
+```bash
+# Run pre-commit hooks
+pre-commit run --all-files
+
+# Format with black (line length: 120)
+black . --line-length 120
+
+# Run ruff for linting and auto-fix
+ruff check . --fix
+```
+
+## Code Style and Formatting
+
+### Python Style
+
+- **Line length:** 120 characters (configured in both Black and Ruff)
+- **Formatter:** Black (v23.3.0+)
+- **Linter:** Ruff with Pyflakes and pycodestyle rules
+- **Import sorting:** Use isort (via Ruff)
+- **Python version:** Supports Python >= 3.10 (full support for 3.10, 3.11, 3.12; Python 3.13 tested but some optional dependencies may have limited compatibility)
+
+### Code Quality Rules
+
+- Follow Black formatting conventions
+- Keep imports sorted and organized
+- Avoid unused imports (F401) - these are flagged but not auto-fixed
+- Avoid wildcard imports (F403) where possible
+- Complexity: Max McCabe complexity of 10
+- Use type hints where appropriate
+- Write clear docstrings for public APIs
+
+### Pre-commit Hooks
+
+The repository uses pre-commit hooks for:
+
+- Checking for large files, AST syntax, YAML/TOML/JSON validity
+- Detecting merge conflicts and private keys
+- Trailing whitespace and end-of-file fixes
+- pyupgrade for Python 3.8+ syntax
+- Black formatting
+- Markdown formatting (mdformat with GFM and frontmatter support)
+- Ruff linting with auto-fix
+
+## Testing Strategy
+
+### Test Organization
+
+- Tests are in the `test/` directory, organized by module
+- `test/automl/`: AutoML feature tests
+- `test/tune/`: Hyperparameter tuning tests
+- `test/default/`: Zero-shot AutoML tests
+- `test/nlp/`: NLP-related tests
+- `test/spark/`: Spark integration tests
+
+### Test Requirements
+
+- Write tests for new functionality
+- Ensure tests pass on multiple Python versions (3.10, 3.11, 3.12, 3.13)
+- Tests should work on both Ubuntu and Windows
+- Use pytest markers for platform-specific tests (e.g., `@pytest.mark.spark`)
+- Tests should be idempotent and not depend on external state
+- Use `--reruns 2 --reruns-delay 10` for flaky tests
+
+### Coverage
+
+- Aim for good test coverage on new code
+- Coverage reports are generated for Python 3.11 builds
+- Coverage reports are uploaded to Codecov
+
+## Git Workflow and Best Practices
+
+### Branching
+
+- Main branch: `main`
+- Create feature branches from `main`
+- PR reviews are required before merging
+
+### Commit Messages
+
+- Use clear, descriptive commit messages
+- Reference issue numbers when applicable
+
+### Pull Requests
+
+- Ensure all tests pass before requesting review
+- Update documentation if adding new features
+- Follow the PR template in `.github/PULL_REQUEST_TEMPLATE.md`
+
+## Project Structure
+
+```
+flaml/
+├── automl/         # AutoML functionality
+├── tune/           # Hyperparameter tuning
+├── default/        # Zero-shot AutoML
+├── autogen/        # Legacy autogen (deprecated, moved to separate repo)
+├── fabric/         # Microsoft Fabric integration
+├── onlineml/       # Online learning
+└── version.py      # Version information
+
+test/               # Test suite
+├── automl/
+├── tune/
+├── default/
+├── nlp/
+└── spark/
+
+notebook/           # Example notebooks
+website/            # Documentation website
+```
+
+## Dependencies and Package Management
+
+### Core Dependencies
+
+- NumPy >= 1.17
+- Python >= 3.10 (officially supported: 3.10, 3.11, 3.12; Python 3.13 is tested in CI but may have limited compatibility with some optional dependencies)
+
+### Optional Dependencies
+
+- `[automl]`: lightgbm, xgboost, scipy, pandas, scikit-learn
+- `[test]`: Full test suite dependencies
+- `[spark]`: PySpark and joblib dependencies
+- `[forecast]`: holidays, prophet, statsmodels, hcrystalball, pytorch-forecasting, pytorch-lightning, tensorboardX
+- `[hf]`: Hugging Face transformers and datasets
+- See `setup.py` for complete list
+
+### Version Constraints
+
+- Be mindful of Python version-specific dependencies (check setup.py)
+- XGBoost versions differ based on Python version
+- NumPy 2.0+ only for Python >= 3.13
+- Some features (like vowpalwabbit) only work with older Python versions
+
+## Boundaries and Restrictions
+
+### Do NOT Modify
+
+- `.git/` directory and Git configuration
+- `LICENSE` file
+- Version information in `flaml/version.py` (unless explicitly updating version)
+- GitHub Actions workflows without careful consideration
+- Existing test files unless fixing bugs or adding coverage
+
+### Be Cautious With
+
+- `setup.py`: Changes to dependencies should be carefully reviewed
+- `pyproject.toml`: Linting and testing configuration
+- `.pre-commit-config.yaml`: Pre-commit hook configuration
+- Backward compatibility: FLAML is a library with external users
+
+### Security Considerations
+
+- Never commit secrets or API keys
+- Be careful with external data sources in tests
+- Validate user inputs in public APIs
+- Follow secure coding practices for ML operations
+
+## Special Notes
+
+### AutoGen Migration
+
+- AutoGen has moved to a separate repository: https://github.com/microsoft/autogen
+- The `flaml/autogen/` directory contains legacy code
+- Tests in `test/autogen/` are ignored in the main test suite
+- Direct users to the new AutoGen repository for AutoGen-related issues
+
+### Platform-Specific Considerations
+
+- Some tests only run on Linux (e.g., forecast tests with prophet)
+- Windows and Ubuntu are the primary supported platforms
+- macOS support exists but requires special libomp setup for lgbm/xgboost
+
+### Performance
+
+- FLAML focuses on efficient automation and tuning
+- Consider computational cost when adding new features
+- Optimize for low resource usage where possible
+
+## Documentation
+
+- Main documentation: https://microsoft.github.io/FLAML/
+- Update documentation when adding new features
+- Provide clear examples in docstrings
+- Add notebook examples for significant new features
+
+## Contributing
+
+- Follow the contributing guide: https://microsoft.github.io/FLAML/docs/Contribute
+- Sign the Microsoft CLA when making your first contribution
+- Be respectful and follow the Microsoft Open Source Code of Conduct
+- Join the Discord community for discussions: https://discord.gg/Cppx2vSPVP