types/llm_params.py

from typing import Optional, List
from pydantic import BaseModel, Field


class LlmPredictParams(BaseModel):
    """
    Параметры для предсказания LLM.
    """
    system_prompt: Optional[str] = Field(None, description="OpenAI only. Системный промпт.")
    user_prompt: Optional[str] = Field(None, description="OpenAI only. Шаблон промпта для передачи от роли user.")
    n_predict: Optional[int] = None
    temperature: Optional[float] = None
    top_k: Optional[int] = None
    top_p: Optional[float] = None
    min_p: Optional[float] = None
    seed: Optional[int] = None
    repeat_penalty: Optional[float] = None
    repeat_last_n: Optional[int] = None
    retry_if_text_not_present: Optional[str] = None
    retry_count: Optional[int] = None
    presence_penalty: Optional[float] = None
    frequency_penalty: Optional[float] = None
    n_keep: Optional[int] = None
    cache_prompt: Optional[bool] = None
    stop: Optional[List[str]] = None


class LlmParams(BaseModel):
    """
    Основные параметры для LLM.
    """
    name: str
    url: str
    type: str
    context: int
    default: Optional[bool] = None
    template: Optional[str] = None
    predict_params: Optional[LlmPredictParams] = None


# Пример использования
query = {
    "name": "example-model",
    "url": "http://example.com",
    "type": "openai",
    "context": 1024,
    "default": True,
    "template": "Some template",
    "predict_params": {
        "system_prompt": "Welcome!",
        "temperature": 0.7,
        "retry_count": 3,
        "stop": ["END"]
    }
}

# Валидация данных
llm_params = LlmParams(**query)
print(llm_params.json(indent=2))