gzhu-biyesheji/schema/dataset_generation.py
carry 3970a67df3 refactor(dataset_generation): 增加 APIProvider 模型字段的最小长度验证
- 为 base_url 和 model_id 字段添加 min_length=1 的验证
- 更新字段描述,明确这些字段不能为空
2025-04-07 23:37:14 +08:00

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from datetime import datetime, timezone
from typing import Optional
from sqlmodel import SQLModel, Relationship, Field
class APIProvider(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
base_url: str = Field(...,min_length=1,description="API的基础URL不能为空")
model_id: str = Field(...,min_length=1,description="API使用的模型ID不能为空")
api_key: Optional[str] = Field(default=None, description="用于身份验证的API密钥")
created_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc),
description="记录创建时间"
)
class LLMResponse(SQLModel):
timestamp: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc),
description="响应的时间戳"
)
response_id: str = Field(..., description="响应的唯一ID")
tokens_usage: dict = Field(default_factory=lambda: {
"prompt_tokens": 0,
"completion_tokens": 0,
"prompt_cache_hit_tokens": None,
"prompt_cache_miss_tokens": None
}, description="token使用信息")
response_content: dict = Field(default_factory=dict, description="API响应的内容")
total_duration: float = Field(default=0.0, description="请求的总时长,单位为秒")
llm_parameters: dict = Field(default_factory=lambda: {
"temperature": None,
"max_tokens": None,
"top_p": None,
"frequency_penalty": None,
"presence_penalty": None,
"seed": None
}, description="API的生成参数")
class LLMRequest(SQLModel):
prompt: str = Field(..., description="发送给API的提示词")
provider_id: int = Field(foreign_key="apiprovider.id")
provider: APIProvider = Relationship()
format: Optional[str] = Field(default=None, description="API响应的格式")
response: list[LLMResponse] = Field(default_factory=list, description="API响应列表")
error: Optional[list[str]] = Field(default=None, description="API请求过程中发生的错误信息")
total_duration: float = Field(default=0.0, description="请求的总时长,单位为秒")
total_tokens_usage: dict = Field(default_factory=lambda: {
"prompt_tokens": 0,
"completion_tokens": 0,
"prompt_cache_hit_tokens": None,
"prompt_cache_miss_tokens": None
}, description="token使用信息")