# Usage example
```python
from pydantic import BaseModel
from kozhindev_data_labeler import LLMClient
from kozhindev_data_labeler import Pipeline
class LLMPredict(BaseModel):
reviews: list[str]
target: list[int]
llm_client = LLMClient(
model='gpt-4o-mini',
api_key='API_KEY',
response_format=LLMPredict
)
reviews = [
'Сегодня отличная погода, настроение супер!',
'SOME TEXT 123312!312OKF;SEKF;',
'PostgreSQL- свободная объектно-реляционная базами данных',
"Congratulations! You've won a $1,000 Walmart gift card to http://bit.ly/123456 tp claim now."
]
pipeline = Pipeline(
data={'reviews': reviews},
prompt='Сделай классификацию сообщений на негативные и позитивные (0 - позитивный, 1 - негативный)',
model_client=llm_client
)
pipeline.run()
pipeline.to_csv('result.csv')
```
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"description": "# Usage example\n```python\nfrom pydantic import BaseModel\n\nfrom kozhindev_data_labeler import LLMClient\nfrom kozhindev_data_labeler import Pipeline\n\n\nclass LLMPredict(BaseModel):\n reviews: list[str]\n target: list[int]\n\nllm_client = LLMClient(\n model='gpt-4o-mini',\n api_key='API_KEY',\n response_format=LLMPredict\n)\n\nreviews = [\n '\u0421\u0435\u0433\u043e\u0434\u043d\u044f \u043e\u0442\u043b\u0438\u0447\u043d\u0430\u044f \u043f\u043e\u0433\u043e\u0434\u0430, \u043d\u0430\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u0435 \u0441\u0443\u043f\u0435\u0440!',\n 'SOME TEXT 123312!312OKF;SEKF;',\n 'PostgreSQL- \u0441\u0432\u043e\u0431\u043e\u0434\u043d\u0430\u044f \u043e\u0431\u044a\u0435\u043a\u0442\u043d\u043e-\u0440\u0435\u043b\u044f\u0446\u0438\u043e\u043d\u043d\u0430\u044f \u0431\u0430\u0437\u0430\u043c\u0438 \u0434\u0430\u043d\u043d\u044b\u0445',\n \"Congratulations! You've won a $1,000 Walmart gift card to http://bit.ly/123456 tp claim now.\"\n]\n\npipeline = Pipeline(\n data={'reviews': reviews},\n prompt='\u0421\u0434\u0435\u043b\u0430\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u044e \u0441\u043e\u043e\u0431\u0449\u0435\u043d\u0438\u0439 \u043d\u0430 \u043d\u0435\u0433\u0430\u0442\u0438\u0432\u043d\u044b\u0435 \u0438 \u043f\u043e\u0437\u0438\u0442\u0438\u0432\u043d\u044b\u0435 (0 - \u043f\u043e\u0437\u0438\u0442\u0438\u0432\u043d\u044b\u0439, 1 - \u043d\u0435\u0433\u0430\u0442\u0438\u0432\u043d\u044b\u0439)',\n model_client=llm_client\n)\n\npipeline.run()\npipeline.to_csv('result.csv')\n```\n",
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