Metadata-Version: 2.4
Name: ferelight
Version: 1.0.0
Summary: FERElight
Home-page: https://github.com/FEREorg/ferelight
Author: FERElight Team
Author-email: 
Keywords: OpenAPI,FERElight,feature extraction,retrieval engine
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: connexion[swagger-ui]<3.0.0
Requires-Dist: swagger-ui-bundle>=0.0.2
Requires-Dist: python_dateutil>=2.6.0
Requires-Dist: setuptools>=21.0.0
Requires-Dist: Flask==2.2.5
Requires-Dist: psycopg2-binary==2.9.10
Requires-Dist: pgvector>=0.3.6
Requires-Dist: torch>=2.6.0
Requires-Dist: open_clip_torch>=2.29.0
Requires-Dist: transformers>=4.47.0
Dynamic: author
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# FERElight | ˈferēlīt |
Extremely lightweight and purpose-built feature extraction and retrieval engine (FERE).

## Installation

### From PyPI
```
pip install ferelight
```

### From Source
```
pip install git+https://github.com/FEREorg/ferelight.git
```

## Usage
To configure the pgvector PostgreSQL connection, create a file `config.json` in the root directory with the following content:

```json
{
  "DBHOST": "<host>",
  "DBPORT": "<port>",
  "DBUSER": "<user>",
  "DBPASSWORD": "<password>"
}
```

To run the server, please execute the following from the root directory:

```
pip3 install -r requirements.txt
python3 -m ferelight
```

## Running with Docker

To run the server on a Docker container, please execute the following from the root directory:

```bash
# building the image
docker build -t ferelight .

# starting up a container
docker run -p 8080:8080 ferelight
```

## Development

### Releasing New Versions

To release a new version to PyPI:

1. Update the version number in `setup.py`
2. Create a new GitHub release or tag with a version number (e.g., `v1.0.1`)
3. The GitHub Actions workflow will automatically build and publish the package to PyPI
