from __future__ import annotations

from typing import Optional

from pydantic import BaseModel, Field


class ImageInput(BaseModel):
    image_b64: str = Field(..., description="PNG/JPG 编码后的 base64（不含 data: 前缀）")
    model_name: Optional[str] = Field(None, description="模型 key（来自 /models）")


class DepthRequest(ImageInput):
    pass


class SegmentRequest(ImageInput):
    pass


class SamPromptSegmentRequest(BaseModel):
    image_b64: str = Field(..., description="裁剪后的 RGB 图 base64（PNG/JPG）")
    overlay_b64: Optional[str] = Field(
        None,
        description="与裁剪同尺寸的标记叠加 PNG base64（可选；当前用于校验尺寸一致）",
    )
    point_coords: list[list[float]] = Field(
        ...,
        description="裁剪坐标系下的提示点 [[x,y], ...]",
    )
    point_labels: list[int] = Field(
        ...,
        description="与 point_coords 等长：1=前景，0=背景",
    )
    box_xyxy: list[float] = Field(
        ...,
        description="裁剪内笔画紧包围盒 [x1,y1,x2,y2]（像素）",
        min_length=4,
        max_length=4,
    )
    expand_px: int = Field(
        2,
        ge=0,
        le=20,
        description="对输出 mask 做轻微膨胀的像素半径（0 表示不扩大；建议 1~3）",
    )


class InpaintRequest(ImageInput):
    prompt: Optional[str] = Field("", description="补全 prompt")
    strength: float = Field(0.8, ge=0.0, le=1.0)
    negative_prompt: Optional[str] = Field("", description="负向 prompt")
    mask_b64: Optional[str] = Field(None, description="mask PNG base64（可选）")
    max_side: int = Field(1024, ge=128, le=2048)


class AnimateRequest(BaseModel):
    model_name: Optional[str] = Field(None, description="模型 key（来自 /models）")
    prompt: str = Field(..., description="文本提示词")
    negative_prompt: Optional[str] = Field("", description="负向提示词")
    num_inference_steps: int = Field(25, ge=1, le=200)
    guidance_scale: float = Field(8.0, ge=0.0, le=30.0)
    width: int = Field(512, ge=128, le=2048)
    height: int = Field(512, ge=128, le=2048)
    video_length: int = Field(16, ge=1, le=128)
    seed: int = Field(-1, description="-1 表示随机种子")


class CharacterAnimateRequest(BaseModel):
    image_b64: str = Field(..., description="透明背景角色 PNG 的 base64（不含 data: 前缀）")
    model_name: Optional[str] = Field(None, description="模型 key（来自 /models）")
    prompt: str = Field(..., description="角色动画提示词")
    negative_prompt: Optional[str] = Field("", description="负向提示词")
    background_color: str = Field(
        "#00FF00",
        description="生成时使用的纯色背景，支持 #RRGGBB 或 R,G,B",
    )
    background_tolerance: int = Field(
        40,
        ge=0,
        le=255,
        description="自动剔除背景的 RGB 色差阈值，越大剔除越激进",
    )
    num_inference_steps: int = Field(25, ge=1, le=200)
    guidance_scale: float = Field(8.0, ge=0.0, le=30.0)
    video_length: int = Field(16, ge=1, le=128, description="前端请求生成的帧数")
    seed: int = Field(-1, description="-1 表示随机种子")
    max_side: int = Field(
        768,
        ge=128,
        le=2048,
        description="推理分辨率长边上限；会保持输入比例并对齐到 8 的倍数",
    )