小鱼开发
116 lines
3.9 KiB
Python
116 lines
3.9 KiB
Python
"""
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脚本相关 Schema
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===============
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"""
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from typing import Any
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from pydantic import BaseModel, Field
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from app.schemas.segment import Segment
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ScriptShot = Segment
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class SubcategoryItem(BaseModel):
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"""小类项"""
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code: str = Field(..., description="小类代码")
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name: str = Field(..., description="小类名称")
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count: int = Field(..., description="提示词文件数量")
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class CategoryItem(BaseModel):
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"""大类项"""
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code: str = Field(..., description="大类代码")
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name: str = Field(..., description="大类名称")
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subcategories: list[SubcategoryItem] = Field(..., description="小类列表")
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class GenerateScriptRequest(BaseModel):
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"""生成脚本请求"""
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category: str = Field(..., description="大类代码，如 bk")
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subcategory: str = Field(..., description="小类代码，如 ht")
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duration: int = Field(default=45, ge=30, le=180, description="视频时长（秒）")
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script_type: str = Field(default="干货型", description="脚本类型")
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model: str | None = Field(None, description="指定模型（可选）")
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class PolishRequest(BaseModel):
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"""润色请求"""
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content: str = Field(..., description="待润色内容", min_length=1)
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polish_type: str = Field(default="voiceover", description="润色类型：scene / voiceover")
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shot_type: str | None = Field(
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default="segment",
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description="镜头类型：segment(分镜) / empty_shot(空镜)，用于画面润色时区分",
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)
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class ScriptGenerationEvent(BaseModel):
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"""
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脚本生成 SSE 事件
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与前端 ScriptGenerationEvent 对应
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事件类型说明:
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- start: 初始化（0-5%）
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- analyzing: 分析主题（5-15%）
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- generating: AI 生成中（15-85%）
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- validating: 验证格式（85-92%）
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- parsing: 解析分镜（92-98%）
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- finalizing: 整理结果（98-100%）
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- complete: 完成（100%）
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- error: 错误
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"""
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type: str = Field(
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...,
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description="事件类型：start / analyzing / generating / validating / parsing / finalizing / complete / error",
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)
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progress: int = Field(default=0, ge=0, le=100, description="进度百分比")
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message: str = Field(..., description="状态描述")
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result: list[Any] | None = Field(None, description="生成的分镜结果（complete 时）")
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extracted_info: dict[str, Any] | None = Field(
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None, description="提取的视频信息（complete 时，如果是视频链接）"
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)
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class ModelHealthInfo(BaseModel):
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"""模型健康信息"""
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id: str = Field(..., description="模型 ID")
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name: str = Field(..., description="模型名称")
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is_available: bool = Field(..., description="是否可用")
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response_time: float = Field(..., description="响应时间（毫秒）")
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last_error: str | None = Field(None, description="上次错误信息")
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class ModelHealthResponse(BaseModel):
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"""模型健康检查响应"""
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status: str = Field(..., description="整体状态：healthy / unhealthy / error")
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models: list[ModelHealthInfo] = Field(..., description="各模型状态")
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recommended_model: ModelHealthInfo | None = Field(None, description="推荐的模型")
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total_models: int = Field(..., description="模型总数")
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available_models: int = Field(..., description="可用模型数")
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error: str | None = Field(None, description="错误信息")
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class TestModelRequest(BaseModel):
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"""测试模型请求"""
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model_id: str | None = Field(None, description="要测试的模型 ID")
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class TestModelResponse(BaseModel):
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"""测试模型响应"""
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success: bool = Field(..., description="是否成功")
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model: str = Field(..., description="模型名称")
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response_time: float | None = Field(None, description="响应时间（毫秒）")
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error: str | None = Field(None, description="错误信息")
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checked_at: str | None = Field(None, description="检查时间 ISO 格式")
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