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bigbag committed Dec 20, 2024
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66 changes: 31 additions & 35 deletions README.md
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Expand Up @@ -14,90 +14,86 @@ An intelligent system for matching job descriptions with candidate CVs/resumes u

## Prerequisites

- Python 3.11+
- PostgreSQL
- Python 3.12+
- Docker (optional)

## Quick Start

1. Clone the repository:
```bash
git clone https://github.com/yourusername/cv_matcher.git
git clone https://github.com/bigbag/cv_matcher.git
cd cv_matcher
```

2. Set up a virtual environment:
2. Set up a virtual environment and install dependencies:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
make venv/create
make venv/install/all
```

3. Install dependencies:
3. Set up environment variables:
```bash
pip install -r requirements.txt
cp env.example .local_env
# Edit .local_env with your configuration
```

4. Set up environment variables:
4. Run the application:
```bash
cp .env.example .env
# Edit .env with your configuration
make run/server
```

5. Initialize the database:
```bash
alembic upgrade head
```
The API will be available at `http://localhost:8000`

## Using the Analyzer

6. Run the application:
To analyze a resume against a job description, use the following command:
```bash
uvicorn src.main:app --reload
make analyze RESUME_PATH=/path/to/resume.pdf JOB_DESC_PATH=/path/to/job.pdf
```

The API will be available at `http://localhost:8000`
This command will:
- Parse and analyze the provided resume
- Extract requirements from the job description
- Generate a matching score and detailed analysis

## Docker Setup

1. Build the image:
```bash
docker build -t cv_matcher .
make docker/build/server
```

2. Run the container:
```bash
docker run -p 8000:8000 --env-file .env cv_matcher
make docker/run/server
```

## API Documentation

Once the application is running, visit:
- Swagger UI: `http://localhost:8000/docs`
- ReDoc: `http://localhost:8000/redoc`

## Development

1. Install development dependencies:
1. Format code:
```bash
pip install -r requirements-dev.txt
make format
```

2. Run tests:
2. Run linters:
```bash
pytest
make lint
```

3. Check code style:
3. Run tests:
```bash
flake8
black .
make test
```

## Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request
4. Clean up temporary files and caches:
```bash
make clean
```

## License

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3 changes: 3 additions & 0 deletions env.example
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DEBUG=True
ANTHROPIC_API_KEY=sk-ant-
OPENAI_API_KEY=sk-

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