# Agent Center
Agent Center - A Python project built with LangChain for managing AI agents.
## Features
- Built with LangChain for powerful AI agent capabilities
- Clean project structure following Python best practices
- Type hints and Pydantic models for data validation
- Comprehensive test suite with pytest
- Code formatting with Black and Ruff
- Type checking with Mypy
## Project Structure
```
agentcenter/
\x00\x00 src/
\x00\x00 agentcenter/
\x00\x00 __init__.py # Package initialization
\x00\x00 core.py # Core agent functionality
\x00\x00 config.py # Configuration management
\x00\x00 utils.py # Utility functions
\x00\x00 tests/
\x00\x00 __init__.py
\x00\x00 test_core.py # Core functionality tests
\x00\x00 test_utils.py # Utility function tests
\x00\x00 docs/ # Documentation
\x00\x00 scripts/ # Utility scripts
\x00\x00 pyproject.toml # Project configuration
\x00\x00 README.md # This file
```
## Installation
### Prerequisites
- Python 3.12 or higher
- [uv](https://docs.astral.sh/uv/) package manager
### Setup
1. Clone the repository:
```bash
git clone <your-repo-url>
cd agentcenter
```
2. Install dependencies:
```bash
uv sync
```
3. Install development dependencies:
```bash
uv add --dev pytest pytest-cov black ruff mypy
```
## Usage
### Basic Usage
```python
from agentcenter import AgentCenter
# Create an agent
agent = AgentCenter(name="MyAgent")
# Process input
response = agent.process("Hello, agent!")
print(response)
# Get conversation history
messages = agent.get_messages()
```
### Running with uv
```bash
# Run the main script
uv run python main.py
# Run a specific module
uv run python -m agentcenter.core
```
## Development
### Running Tests
Our test suite has **99% code coverage** with 56 comprehensive tests!
```bash
# Run all tests
uv run pytest
# Run with coverage report
uv run pytest --cov=agentcenter --cov-report=term-missing
# Generate HTML coverage report
uv run pytest --cov=agentcenter --cov-report=html
open htmlcov/index.html
# Run specific test file
uv run pytest tests/test_core.py
# Run with verbose output
uv run pytest -v
```
**Test Coverage:**
- `__init__.py`: 100%
- `cli.py`: 97%
- `config.py`: 100%
- `core.py`: 100%
- `utils.py`: 100%
- **Total: 99%**
### Code Formatting
```bash
# Format code with Black
uv run black src/ tests/
# Lint with Ruff
uv run ruff check src/ tests/
# Type check with Mypy
uv run mypy src/
```
### Installing Dev Dependencies
```bash
uv add --dev pytest pytest-cov black ruff mypy
```
## Configuration
The project uses environment variables for configuration. Create a `.env` file in the root directory:
```env
APP_NAME=Agent Center
DEBUG=false
LOG_LEVEL=INFO
API_KEY=your-api-key-here
```
## Publishing
To publish a new version to PyPI:
### Quick Release
```bash
# Use the automated release script
./scripts/release.sh 0.1.0
```
### Manual Release
```bash
# 1. Update version in pyproject.toml
# 2. Update CHANGELOG.md
# 3. Run tests and checks
uv run pytest --cov=agentcenter --cov-fail-under=80
uv run black src/ tests/
uv run ruff check src/ tests/
# 4. Build and publish
uv build
uv run twine upload --repository testpypi dist/* # Test first
uv run twine upload dist/* # Then publish
```
See [Publishing Guide](docs/publishing.md) for detailed instructions.
## 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
Please ensure your PR:
- ✅ Passes all tests (`uv run pytest`)
- ✅ Has adequate test coverage (≥80%)
- ✅ Follows code style (`uv run black src/ tests/`)
- ✅ Passes linting (`uv run ruff check src/ tests/`)
## License
This project is licensed under the MIT License - see the LICENSE file for details.
## Contact
Your Name - your.email@example.com
Project Link: [https://github.com/yourusername/agentcenter](https://github.com/yourusername/agentcenter)
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