590 lines
13 KiB
Python
590 lines
13 KiB
Python
"""API 请求 / 响应模型。"""
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from __future__ import annotations
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from datetime import date, datetime
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from typing import Any
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from pydantic import BaseModel, ConfigDict, Field
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class ORMModel(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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class KnowledgeOut(ORMModel):
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id: int
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knowledge_id: int
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name: str
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mastery: int
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position: int
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status: str = ""
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domain: str = ""
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category: str = ""
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class KnowledgeResourceOut(BaseModel):
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id: int
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kind: str
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title: str
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url: str
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source_name: str = ""
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class KnowledgeRelatedOut(BaseModel):
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id: int
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name: str
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relation_type: str
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direction: str = "out" # out: 当前节点指向对方；in: 对方指向当前节点
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mastery: int | None = None
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class KnowledgeChapterOut(BaseModel):
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chapter_id: int
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chapter_name: str
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textbook_id: int
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textbook_name: str
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question_count: int = 0
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# 电子书定位：has_ebook 为假时前端不显示「读教材」入口
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ebook_page: int = 0
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has_ebook: bool = False
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class KnowledgeDetailOut(BaseModel):
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id: int
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name: str
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domain: str
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category: str
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description: str
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mastery: int
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status: str
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related_knowledge_count: int
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chapter_count: int
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question_count: int
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related: list[KnowledgeRelatedOut] = []
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chapters: list[KnowledgeChapterOut] = []
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resources: list[KnowledgeResourceOut] = []
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class KnowledgeResourceIn(BaseModel):
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kind: str = "video"
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title: str = ""
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url: str = ""
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textbook_id: int | None = None
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course_id: int | None = None
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class QuestionOut(BaseModel):
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id: int
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stem: str
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options: list[str]
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knowledge_name: str
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class PracticeSessionOut(BaseModel):
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mode: str
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title: str
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chapter_id: int | None = None
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questions: list[QuestionOut]
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class AnswerIn(BaseModel):
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question_id: int
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selected: int
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class SubmitIn(BaseModel):
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mode: str
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chapter_id: int | None = None
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answers: list[AnswerIn] = Field(min_length=1)
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class PerQuestionOut(BaseModel):
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question_id: int
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correct: bool
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selected: int
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correct_index: int
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explanation: str
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class SubmitResultOut(BaseModel):
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mode: str
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title: str
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total: int
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score: int
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accuracy: float
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per_question: list[PerQuestionOut]
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knowledge: list[KnowledgeOut]
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class ErrorOut(BaseModel):
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id: int
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source_label: str
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knowledge_name: str
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diagnosis: str
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status: str
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created_on: date
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attempt_id: int | None = None
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question_id: int | None = None
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stem: str = ""
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options: list[str] = []
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selected: int | None = None
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correct_index: int | None = None
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explanation: str = ""
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knowledge_names: list[str] = []
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class RecordOut(BaseModel):
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id: int
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mode: str
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title: str
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total: int
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correct: int
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happened_on: date
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class AttemptItemOut(BaseModel):
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question_index: int
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question_id: int | None
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stem: str
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options: list[str]
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selected: int | None
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correct_index: int
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correct: bool
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knowledge_name: str
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explanation: str
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knowledge_names: list[str] = []
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class RecordDetailOut(RecordOut):
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items: list[AttemptItemOut] = []
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class DailyOut(BaseModel):
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today: date
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completed: bool
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streak: int
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chapter_id: int | None = None
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chapter_name: str = ""
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book_name: str = ""
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# 今日章节对应的电子书定位，没有电子书时 has_ebook 为假
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textbook_id: int | None = None
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ebook_page: int = 0
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has_ebook: bool = False
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rating: str = ""
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knowledge_names: list[str] = []
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reason: str = ""
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class DailyCompleteIn(BaseModel):
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chapter_id: int
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rating: str = ""
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class MetricItem(BaseModel):
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label: str
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value: str
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class PlanOut(BaseModel):
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notice: str
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focus_names: list[str]
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steps: list[str]
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class OverviewOut(BaseModel):
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metrics: list[MetricItem]
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knowledge: list[KnowledgeOut]
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plan: PlanOut
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class DiagnosisOut(BaseModel):
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name: str
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mastery: int
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error_count: int
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action: str
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class AnalyticsOut(BaseModel):
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metrics: list[MetricItem]
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diagnosis: list[DiagnosisOut]
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class ImportPayload(BaseModel):
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version: int = 1
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knowledge: list[dict[str, Any]] = []
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records: list[Any] = []
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errors: list[Any] = []
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daily_completions: list[date] = []
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class ImportResult(BaseModel):
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imported: bool
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knowledge: int
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records: int
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errors: int
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items: int = 0
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message: str
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class ChapterOut(ORMModel):
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id: int
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textbook_id: int
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name: str
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position: int
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summary: str = ""
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ebook_page: int = 0
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question_count: int = 0
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knowledge_names: list[str] = []
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knowledge_ids: list[int] = []
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class EbookProgressOut(ORMModel):
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textbook_id: int
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locator: str = ""
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page: int = 0
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total: int = 0
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position: float = 0.0
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updated_at: datetime | None = None
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class EbookProgressIn(BaseModel):
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locator: str = Field(default="", max_length=512)
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page: int = 0
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total: int = 0
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position: float = 0.0
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class TextbookOut(ORMModel):
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id: int
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name: str
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author: str
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publisher: str
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isbn: str
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edition: str
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grade: str
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link: str
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description: str
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position: int
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chapters: list[ChapterOut] = []
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# 在线阅读：文件本身走 /api/textbooks/{id}/ebook/file/{file}
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ebook_file: str = ""
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ebook_format: str = ""
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ebook_name: str = ""
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ebook_size: int = 0
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ebook_pages: int = 0
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ebook_uploaded_at: datetime | None = None
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ebook_progress: EbookProgressOut | None = None
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class CourseOut(ORMModel):
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id: int
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name: str
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provider: str
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url: str
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grade: str
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description: str
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position: int
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class QuestionBankItemOut(BaseModel):
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id: int
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chapter_id: int | None
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chapter_name: str = ""
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textbook_name: str = ""
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knowledge_name: str
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stem: str
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options: list[str]
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correct_index: int
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explanation: str
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difficulty: int
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is_generated: bool
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used_count: int
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knowledge_names: list[str] = []
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knowledge_ids: list[int] = []
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class BankSummaryOut(BaseModel):
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"侧栏计数用：全库题目总数与几个切片，避免把整库题目拉回前端数数。"
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total: int
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unattached: int
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generated: int
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used: int
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class QuestionUpdate(BaseModel):
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stem: str = Field(min_length=1)
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options: list[str] = Field(min_length=4, max_length=4)
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correct_index: int = Field(ge=0, le=3)
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explanation: str = ""
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knowledge_name: str = Field(min_length=1, max_length=64)
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difficulty: int = Field(default=1, ge=1, le=3)
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chapter_id: int | None = None
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knowledge_names: list[str] = []
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knowledge_ids: list[int] = []
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class GenerateIn(BaseModel):
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chapter_id: int
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count: int = Field(default=3, ge=1, le=10)
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difficulty: int = Field(default=2, ge=1, le=3)
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knowledge_name: str = ""
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instructions: str = ""
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channel_id: int | None = None
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knowledge_names: list[str] = []
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knowledge_ids: list[int] = []
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need_figure: bool = False
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class LlmProviderOut(BaseModel):
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id: str
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label: str
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base_url: str
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model: str
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class LlmChannelOut(BaseModel):
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id: int
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name: str
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provider: str
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provider_label: str
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base_url: str
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model: str
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temperature: float
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max_tokens: int | None = None
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has_api_key: bool
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api_key_preview: str
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is_default: bool
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class LlmSettingsOut(BaseModel):
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channels: list[LlmChannelOut] = []
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providers: list[LlmProviderOut]
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class LlmChannelCreate(BaseModel):
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name: str = Field(min_length=1, max_length=128)
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provider: str = "openai"
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base_url: str = ""
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model: str = ""
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temperature: float = Field(default=0.3, ge=0.0, le=2.0)
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max_tokens: int | None = Field(default=None, ge=64, le=12000)
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api_key: str | None = None
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class LlmChannelUpdate(BaseModel):
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name: str | None = Field(default=None, min_length=1, max_length=128)
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provider: str | None = None
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base_url: str | None = None
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model: str | None = None
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temperature: float | None = Field(default=None, ge=0.0, le=2.0)
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max_tokens: int | None = Field(default=None, ge=64, le=12000)
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clear_max_tokens: bool = False
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api_key: str | None = None
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clear_api_key: bool = False
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class LlmTestResult(BaseModel):
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ok: bool
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message: str
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class LlmTaskCreate(BaseModel):
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kind: str
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params: dict[str, Any] = {}
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class LlmTaskOut(BaseModel):
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id: int
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kind: str
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status: str
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progress: int
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message: str
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result: dict[str, Any] = {}
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class LoginIn(BaseModel):
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username: str
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password: str
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class TokenOut(BaseModel):
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access_token: str
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token_type: str = "bearer"
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role: str
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display_name: str
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class ChangePasswordIn(BaseModel):
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old_password: str
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new_password: str = Field(min_length=6, max_length=128)
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class RoleOut(ORMModel):
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id: int
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code: str
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name: str
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description: str
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class UserOut(BaseModel):
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id: int
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username: str
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display_name: str
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active: bool
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roles: list[RoleOut] = []
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created_at: datetime | None = None
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class UserCreate(BaseModel):
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username: str = Field(min_length=2, max_length=64, pattern=r"^[A-Za-z0-9_.-]+$")
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display_name: str = Field(default="", max_length=64)
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password: str = Field(min_length=6, max_length=128)
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role_code: str = "student"
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class UserUpdate(BaseModel):
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display_name: str | None = Field(default=None, max_length=64)
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active: bool | None = None
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role_code: str | None = None
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class ResetPasswordIn(BaseModel):
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password: str = Field(min_length=6, max_length=128)
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class TextbookCreate(BaseModel):
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name: str = Field(min_length=1, max_length=128)
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author: str = ""
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publisher: str = ""
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isbn: str = ""
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edition: str = ""
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grade: str = ""
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link: str = ""
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description: str = ""
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class TextbookUpdate(BaseModel):
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name: str | None = Field(default=None, max_length=128)
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author: str | None = None
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publisher: str | None = None
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isbn: str | None = None
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edition: str | None = None
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grade: str | None = None
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link: str | None = None
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description: str | None = None
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class CourseCreate(BaseModel):
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name: str = Field(min_length=1, max_length=128)
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provider: str = ""
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url: str = ""
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grade: str = ""
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description: str = ""
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class CourseUpdate(BaseModel):
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name: str | None = Field(default=None, max_length=128)
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provider: str | None = None
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url: str | None = None
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grade: str | None = None
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description: str | None = None
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class ChapterCreate(BaseModel):
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name: str = Field(min_length=1, max_length=128)
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summary: str = ""
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knowledge_names: list[str] = []
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knowledge_ids: list[int] = []
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class ChapterUpdate(BaseModel):
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name: str | None = Field(default=None, max_length=128)
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summary: str | None = None
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ebook_page: int | None = None
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knowledge_names: list[str] | None = None
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knowledge_ids: list[int] | None = None
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class ChaptersGenerateIn(BaseModel):
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count: int | None = Field(default=None, ge=1, le=12)
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channel_id: int | None = None
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instructions: str = ""
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knowledge_ids: list[int] = []
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class ChaptersGenerateOut(BaseModel):
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created: list[ChapterOut] = []
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skipped_duplicates: list[str] = []
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message: str = ""
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class ChaptersOrganizeIn(BaseModel):
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reference_text: str = Field(min_length=1)
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channel_id: int | None = None
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class ProfileUpdate(BaseModel):
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display_name: str = Field(min_length=1, max_length=64)
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class KnowledgeGraphNode(BaseModel):
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id: int
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name: str
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domain: str
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category: str
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description: str
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chapter_count: int = 0
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question_count: int = 0
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resources: list[KnowledgeResourceOut] = []
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class KnowledgeGraphEdge(BaseModel):
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source: int
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target: int
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relation_type: str
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class KnowledgeGraphOut(BaseModel):
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nodes: list[KnowledgeGraphNode] = []
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edges: list[KnowledgeGraphEdge] = []
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class KnowledgeMapNode(BaseModel):
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"""学生视角的知识节点：结构 + 本人掌握度，一次给全量。"""
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id: int
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name: str
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domain: str
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category: str
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description: str = ""
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mastery: int = 0
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status: str = "重点"
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# 有没有练过：没练过的不该被当成「薄弱」，界面上单独表达
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practiced: bool = False
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chapter_count: int = 0
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question_count: int = 0
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class KnowledgeMapOut(BaseModel):
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nodes: list[KnowledgeMapNode] = []
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edges: list[KnowledgeGraphEdge] = []
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class KnowledgeNodeCreate(BaseModel):
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name: str = Field(min_length=1, max_length=64)
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domain: str = "初等"
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category: str = ""
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description: str = ""
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class KnowledgeNodeUpdate(BaseModel):
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name: str | None = Field(default=None, min_length=1, max_length=64)
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domain: str | None = None
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category: str | None = None
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description: str | None = None
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class KnowledgeRelationIn(BaseModel):
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source_id: int
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target_id: int
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relation_type: str = "前置"
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