84 lines
3.0 KiB
Python
84 lines
3.0 KiB
Python
from pydantic import BaseModel, Field, model_validator
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from app.enums.generation_provider import IMAGE_MULTI_OUTPUT_MAX, IMAGE_MULTI_REFERENCE_MAX
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from app.schemas.common import NaiveDatetime, NaiveDatetimeOptional
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class ImageEngineCreate(BaseModel):
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name: str = Field(..., max_length=64)
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provider: str = Field(..., max_length=32)
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api_base: str = Field(..., max_length=512)
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api_key: str = Field(default="", max_length=256)
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model_name: str = Field(default="", max_length=128)
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supported_models: str = Field(default='["doubao-seedream-5-0-260128"]')
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supported_sizes: str = Field(default='{}')
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default_size: str = Field(default="2K", max_length=32)
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max_image_count: int = Field(default=0)
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multi_generation_enabled: bool = Field(
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default=False,
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description="是否允许客户端选择生成多份图片；关闭时客户端只能选择 1 份",
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)
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max_generation_count: int = Field(
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default=1,
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ge=1,
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le=5,
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description="客户端单次最多可选择的生成数量，范围 1-5",
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)
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multi_image_max_images: int = Field(
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default=IMAGE_MULTI_OUTPUT_MAX,
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ge=1,
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le=IMAGE_MULTI_OUTPUT_MAX,
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description="火山组图接口输入参考图与输出图片总上限",
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)
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max_reference_image_count: int = Field(
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default=IMAGE_MULTI_REFERENCE_MAX,
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ge=0,
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le=IMAGE_MULTI_REFERENCE_MAX,
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description="图片引擎允许的最大参考图片数量",
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)
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output_format: str = Field(
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default="",
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max_length=16,
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description="供应商输出格式；留空表示不传该参数，用于兼容不支持 output_format 的模型",
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)
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generate_url: str = Field(default="", max_length=512)
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is_active: bool = True
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priority: int = 0
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@model_validator(mode="after")
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def validate_multi_generation_capability(self):
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if self.max_generation_count > self.multi_image_max_images:
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raise ValueError("max_generation_count 不能大于 multi_image_max_images")
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normalized_output_format = (self.output_format or "").lower().strip()
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if normalized_output_format not in {"", "png", "jpeg"}:
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raise ValueError("output_format 仅支持留空、png 或 jpeg")
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self.output_format = normalized_output_format
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return self
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class ImageEngineOut(ImageEngineCreate):
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id: str
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created_at: NaiveDatetime
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deleted_at: NaiveDatetimeOptional = None
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model_config = {"from_attributes": True}
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class ImageEnginePublic(BaseModel):
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id: str
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name: str
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provider: str
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supported_models: list[str] = []
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supported_sizes: dict[str, dict[str, str]] = {}
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default_size: str = "2K"
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max_image_count: int = 0
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multi_generation_enabled: bool = False
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max_generation_count: int = 1
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multi_image_max_images: int = IMAGE_MULTI_OUTPUT_MAX
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max_reference_image_count: int = IMAGE_MULTI_REFERENCE_MAX
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class ImageEngineListResponse(BaseModel):
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items: list[ImageEnginePublic]
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