Metadata-Version: 2.1
Name: codeserializerlib
Version: 1.0.4
Summary: Python library for the code serializer
Author: Tony Meissner
Author-email: tonymeissner70@gmail.com
Description-Content-Type: text/markdown
Requires-Dist: spacy>=3.7.2
Provides-Extra: dev
Requires-Dist: spacy>=3.7.2; extra == "dev"
Requires-Dist: label-studio-ml; extra == "dev"
Requires-Dist: wheel; extra == "dev"
Requires-Dist: setuptools; extra == "dev"
Requires-Dist: twine; extra == "dev"
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pytest-runner; extra == "dev"

# spaCy powered Label Studio ML backend

spaCy integration for Label Studio.
this is running besides the azure functions.

[Demo video](https://youtu.be/F19NT-21uT4)

## running the backend

1. prepare environment

```bash
python -m venv .venv
source venv/bin/activate
pip install -r requirements.txt
pip install --upgrade pip
```

Compile your library
```bash
python setup.py sdist bdist_wheel
```

Upload to Pypi
```bash
twine upload dist/* 
```

running tests
```bash
pytest tests/ -W ignore::DeprecationWarning
```

2. start label studio
```bash
label-studio
```

3. Start the backend and add the URL to your Label Studio project settings.

```bash
label-studio-ml start channel_ml_ner
```

4. As you train new models, they will appear in a `checkpoints` directory. The latest checkpoint will be symlinked to `latest-model`.



## modifying the config

In the `channel_ml_ner` directory, add your spaCy `config.cfg` file. You can optionally add a `model-best` folder from a pre-trained model, to get started with predictions straight away. 
