danteai

Name	danteai JSON
Version	1.1 JSON
	download
home_page	None
Summary	None
upload_time	2024-12-24 12:31:00
maintainer	None
docs_url	None
author	None
requires_python	None
license	None
keywords
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requirements	No requirements were recorded.
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            # danteai

Danteai is a convenient Python package for training your own text-based AI model and using it in practice to generate responses based on specified parameters. The package is fully tailored for the tasks of Dante (an application for article generation). If you need to modify the default settings, pay attention to the `minions.py`, `create_or_train.py`, and `get_generated_article.py` files.

## Installation

Install the package using pip:

```bash
pip install danteai
```

## Example Usage

```bash
echo MODEL_STORE_DIR='./model' > .env
export $(cat .env | xargs)
```

```python
from danteai import (
    create_or_train,
    get_generated_article,
)

"""
    data = [
        {
            'tags': [],
            'text_example: '',
            'short_news_description: '',
            'response': ''
        },
        ...
    ]
"""

create_or_train_response = create_or_train(
    data=[],
    create_new_model=True
)
print(create_or_train_response)
# if only training, using False for 'create_new_model'

generated_article = get_generated_article(
    tags=[],
    text_example='',
    short_news_description=''
)
print(generated_article)
```

            

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    "description": "# danteai\n\nDanteai is a convenient Python package for training your own text-based AI model and using it in practice to generate responses based on specified parameters. The package is fully tailored for the tasks of Dante (an application for article generation). If you need to modify the default settings, pay attention to the `minions.py`, `create_or_train.py`, and `get_generated_article.py` files.\n\n## Installation\n\nInstall the package using pip:\n\n```bash\npip install danteai\n```\n\n## Example Usage\n\n```bash\necho MODEL_STORE_DIR='./model' > .env\nexport $(cat .env | xargs)\n```\n\n```python\nfrom danteai import (\n    create_or_train,\n    get_generated_article,\n)\n\n\"\"\"\n    data = [\n        {\n            'tags': [],\n            'text_example: '',\n            'short_news_description: '',\n            'response': ''\n        },\n        ...\n    ]\n\"\"\"\n\ncreate_or_train_response = create_or_train(\n    data=[],\n    create_new_model=True\n)\nprint(create_or_train_response)\n# if only training, using False for 'create_new_model'\n\ngenerated_article = get_generated_article(\n    tags=[],\n    text_example='',\n    short_news_description=''\n)\nprint(generated_article)\n```\n",
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