53e0065e3e
配置 SSOT（TOML + .env） 统一错误契约 Auth 与事务边界 Redis / Celery 可靠性:业务 Redis（DB/0）与 Celery broker/backend（DB/1）显式拆分；连接池、sync client 可观测性（OpenTelemetry + LGTM）
130 lines
3.3 KiB
Python
130 lines
3.3 KiB
Python
from pydantic import BaseModel, ConfigDict, Field
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from app.agents.state_schema import MemoirStateSchema as MemoirStateResponse
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__all__ = [
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"BookResponse",
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"ChapterDetailResponse",
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"ChapterListItemResponse",
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"CoverGenerationResponse",
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"ExportPdfRequest",
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"ExportPdfResponse",
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"ImageAssetResponse",
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"MemoirStateResponse",
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"NextQuestionContextResponse",
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"ReadingSegmentResponse",
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"SetChapterStoryOrderRequest",
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"StatusMessageResponse",
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"StoryOrderResponse",
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"UpdateBookRequest",
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]
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class ImageAssetResponse(BaseModel):
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placeholder: str = ""
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description: str = ""
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index: int = 0
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status: str = "pending"
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prompt: str | None = None
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url: str | None = None
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provider: str | None = None
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style: str | None = None
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size: str | None = None
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error: str | None = None
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retryable: bool | None = None
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created_at: str | None = None
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updated_at: str | None = None
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class ReadingSegmentResponse(BaseModel):
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story_id: str
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body_markdown: str = ""
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cover_asset: ImageAssetResponse | None = None
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class UpdateBookRequest(BaseModel):
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title: str
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subtitle: str | None = None
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class ExportPdfRequest(BaseModel):
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book_id: str
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class SetChapterStoryOrderRequest(BaseModel):
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"""按顺序绑定本章节要收录的 stories（覆盖原有 chapter_story_links）。"""
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story_ids: list[str]
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class BookResponse(BaseModel):
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id: str | None = None
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title: str | None = None
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total_pages: int | None = None
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total_words: int | None = None
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cover_image_url: str | None = None
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has_update: bool | None = None
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last_update_chapter_id: str | None = None
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message: str | None = None
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class StatusMessageResponse(BaseModel):
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status: str
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message: str | None = None
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class ExportPdfResponse(BaseModel):
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pdf_base64: str
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filename: str
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class ChapterListItemResponse(BaseModel):
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model_config = ConfigDict(extra="ignore")
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id: str
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title: str | None = None
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category: str | None = None
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order_index: int | None = None
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status: str = "draft"
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summary: str = ""
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canonical_markdown: str = ""
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cover_asset: ImageAssetResponse | None = None
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images: list[ImageAssetResponse] = Field(default_factory=list)
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word_count: int = 0
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updated_at: str | None = None
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is_new: bool = False
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source_segments: list[str] = Field(default_factory=list)
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class ChapterDetailResponse(BaseModel):
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model_config = ConfigDict(extra="ignore")
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id: str
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title: str | None = None
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canonical_markdown: str = ""
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order_index: int | None = None
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status: str | None = None
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category: str | None = None
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images: list[ImageAssetResponse] = Field(default_factory=list)
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cover_asset: ImageAssetResponse | None = None
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reading_segments: list[ReadingSegmentResponse] = Field(default_factory=list)
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updated_at: str | None = None
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is_new: bool = False
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source_segments: list[str] = Field(default_factory=list)
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class CoverGenerationResponse(BaseModel):
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triggered: list[str] = Field(default_factory=list)
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class StoryOrderResponse(BaseModel):
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status: str
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chapter_id: str
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story_count: int
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class NextQuestionContextResponse(BaseModel):
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current_stage: str | None = None
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empty_slots: list[str] = Field(default_factory=list)
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covered_stages: list[str] = Field(default_factory=list)
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