john
05e173b293
Replace the WebView shell with SwiftUI screens, add account-scoped Wiki and TTS APIs with adaptive review and photo scan support, and keep web/iOS pages usable while data loads asynchronously. Co-authored-by: Cursor <cursoragent@cursor.com>
524 lines
11 KiB
Python
524 lines
11 KiB
Python
from typing import Optional
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from pydantic import BaseModel, Field, computed_field
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# Auth
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class UserRegister(BaseModel):
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username: str = Field(min_length=2, max_length=50)
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password: str = Field(min_length=6, max_length=100)
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class UserLogin(BaseModel):
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username: str
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password: str
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remember: bool = True
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class TokenResponse(BaseModel):
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access_token: str
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token_type: str = "bearer"
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class UserOut(BaseModel):
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id: int
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username: str
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created_at: str
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class Config:
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from_attributes = True
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class UserUpdate(BaseModel):
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username: Optional[str] = Field(None, min_length=2, max_length=50)
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current_password: Optional[str] = Field(None, min_length=6, max_length=100)
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new_password: Optional[str] = Field(None, min_length=6, max_length=100)
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# Translate
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class TranslateRequest(BaseModel):
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text: str = Field(min_length=1)
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class TranslateResponse(BaseModel):
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source_text: str
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target_text: str
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source_lang: str
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target_lang: str
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phonetic: Optional[str] = None
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example_en: Optional[str] = None
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example_cn: Optional[str] = None
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found: bool = True
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# Words
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class WordCreate(BaseModel):
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source_text: str
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target_text: str
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source_lang: str
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target_lang: str
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phonetic: Optional[str] = None
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example_en: Optional[str] = None
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example_cn: Optional[str] = None
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class WordScanTextRequest(BaseModel):
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text: str = Field(min_length=1)
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class WordScanItem(BaseModel):
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source_text: str
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target_text: str
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source_lang: str = "en"
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target_lang: str = "zh"
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class WordScanResponse(BaseModel):
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items: list[WordScanItem]
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class WordBatchCreateRequest(BaseModel):
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items: list[WordCreate] = Field(min_length=1, max_length=200)
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class WordUpdate(BaseModel):
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status: Optional[str] = None
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class WordOut(BaseModel):
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id: int
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user_id: int
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book_id: int = 0
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book_entry_id: Optional[int] = None
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source_text: str
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target_text: str
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source_lang: str
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target_lang: str
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phonetic: Optional[str] = None
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example_en: Optional[str] = None
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example_cn: Optional[str] = None
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status: str
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correct_count: int
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wrong_count: int
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consecutive_correct_count: int
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mastery_score: int
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train_count: int = 0
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error_bank_member: int = 0
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error_reinforce_streak: int = 0
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error_bank_entered_at: Optional[str] = None
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total_train_seconds: int = 0
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difficulty: float = 5.0
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stability_hours: float = 24.0
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next_review_at: Optional[str] = None
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review_due_date: Optional[str] = None
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last_reviewed_at: Optional[str] = None
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created_at: str
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@computed_field # type: ignore[prop-decorator]
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@property
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def entered_at(self) -> str:
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"""词库进入时间（与 created_at 一致）。"""
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return self.created_at
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class Config:
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from_attributes = True
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class WordListPageOut(BaseModel):
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items: list[WordOut]
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total: int
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page: int
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page_size: int
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class WordBatchCreateResponse(BaseModel):
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created: int
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skipped: int
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items: list[WordOut]
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class MemoryCurvePoint(BaseModel):
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day_index: int
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date: str
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forgetting: float
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mastery: float
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risk: float
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class MemoryFutureRiskPoint(BaseModel):
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day_offset: int
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date: str
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risk: float
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class MemoryGraphNode(BaseModel):
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id: str
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label: str
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zh: str
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status: str
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mastery: int
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entered_at: str
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size: int
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class MemoryGraphLink(BaseModel):
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source: str
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target: str
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kind: str
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strength: float
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class MemoryGraph(BaseModel):
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nodes: list[MemoryGraphNode]
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links: list[MemoryGraphLink]
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class MemoryWordSummary(BaseModel):
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id: int
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en: str
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zh: str
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status: str
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mastery_score: int
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correct_count: int = 0
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wrong_count: int = 0
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train_count: int = 0
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total_train_seconds: int = 0
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entered_at: str
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retention_now: float
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risk_7d: float
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class WordMemoryCurvePoint(BaseModel):
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date: str
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datetime: str
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forgetting: float
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mastery: float
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risk: float
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wrong_count: int
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train_count: int
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train_seconds: int
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is_correct: Optional[bool] = None
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class WordMemoryDetailResponse(BaseModel):
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word_id: int
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en: str
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zh: str
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correct_count: int
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wrong_count: int
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train_count: int
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total_train_seconds: int
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curve_points: list[WordMemoryCurvePoint]
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future_risk: list[MemoryFutureRiskPoint]
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class MemoryVisualizationResponse(BaseModel):
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curve_points: list[MemoryCurvePoint]
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future_risk: list[MemoryFutureRiskPoint]
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words: list[MemoryWordSummary]
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graph: MemoryGraph
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# Quiz
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class QuizOption(BaseModel):
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label: str
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text: str
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class QuizQuestion(BaseModel):
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word_id: int
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question_type: str
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prompt: str
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options: list[QuizOption] = []
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correct_answer: str
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phonetic: Optional[str] = None
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train_count: int = 0
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wrong_count: int = 0
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error_reinforce_streak: int = 0
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error_clear_correct_count: int = 2
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error_bank_member: int = 0
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class DailyQuizResponse(BaseModel):
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questions: list[QuizQuestion]
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total: int
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track: str = "accumulation"
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book_id: Optional[int] = None
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pool: str = "untrained"
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class QuizAnswerRequest(BaseModel):
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word_id: int
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pool: Optional[str] = None
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question_type: str
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user_answer: str
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correct_answer: str
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duration_seconds: Optional[int] = Field(None, ge=0, le=3600)
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class QuizAnswerResponse(BaseModel):
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is_correct: bool
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correct_answer: str
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word: WordOut
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class QuizStatsResponse(BaseModel):
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total_words: int
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new_count: int
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learning_count: int
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mastered_count: int
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weak_count: int
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today_quiz_count: int
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today_correct_count: int
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today_accuracy: float
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daily_target: int
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today_completed: int
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streak_days: int
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untrained_pending: int = 0
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error_pending: int = 0
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error_bank_due_pending: int = 0
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error_bank_total: int = 0
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track: str = "accumulation"
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book_id: Optional[int] = None
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class PracticePlanResetResponse(BaseModel):
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reset_count: int
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track: str = "accumulation"
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book_id: Optional[int] = None
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class ErrorBankWordOut(BaseModel):
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word_id: int
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en: str
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zh: str
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wrong_count: int
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train_count: int
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error_reinforce_streak: int
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status: str
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next_review_at: Optional[str] = None
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review_due_date: Optional[str] = None
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class ErrorBankListResponse(BaseModel):
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items: list[ErrorBankWordOut]
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total: int
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due_count: int
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track: str = "accumulation"
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book_id: Optional[int] = None
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# Word books
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class WordBookOut(BaseModel):
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id: int
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slug: str
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title: str
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description: Optional[str] = None
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level: str
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word_count: int
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unit_count: int
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sort_order: int
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daily_target: int
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master_required_count: int
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weak_wrong_threshold: int
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learn_mode: str
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class Config:
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from_attributes = True
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class WordBookUnitOut(BaseModel):
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unit: int
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title: Optional[str] = None
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word_count: int
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class WordBookDetailOut(WordBookOut):
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units: list[WordBookUnitOut] = []
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class WordBookProgressOut(BaseModel):
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book_id: int
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total: int
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introduced: int
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mastered: int
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learning: int
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locked: int
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class BookPracticeSettingsOut(BaseModel):
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book_id: int
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daily_target: int
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master_required_count: int
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weak_wrong_threshold: int
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error_clear_correct_count: int
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class ActiveBookOut(BaseModel):
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book: Optional[WordBookOut] = None
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progress: Optional[WordBookProgressOut] = None
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settings: Optional[BookPracticeSettingsOut] = None
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class SetActiveBookRequest(BaseModel):
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book_id: int = Field(ge=1)
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class BookPracticeSettingsUpdate(BaseModel):
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book_id: Optional[int] = Field(None, ge=1)
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daily_target: Optional[int] = Field(None, ge=5, le=50)
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master_required_count: Optional[int] = Field(None, ge=1, le=10)
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weak_wrong_threshold: Optional[int] = Field(None, ge=1, le=10)
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error_clear_correct_count: Optional[int] = Field(None, ge=1, le=5)
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# Settings
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class SettingsOut(BaseModel):
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daily_target: int
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master_required_count: int
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weak_wrong_threshold: int
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error_clear_correct_count: int
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class Config:
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from_attributes = True
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class SettingsUpdate(BaseModel):
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daily_target: Optional[int] = Field(None, ge=1, le=100)
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master_required_count: Optional[int] = Field(None, ge=1, le=20)
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weak_wrong_threshold: Optional[int] = Field(None, ge=1, le=20)
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error_clear_correct_count: Optional[int] = Field(None, ge=1, le=5)
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# Wiki
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class WikiPagePreview(BaseModel):
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slug: str
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title: str
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category: str
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summary: str
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content: str
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source_count: int
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updated_at: str
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class WikiStatusOut(BaseModel):
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enabled: bool
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auto_organize: bool
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page_count: int
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link_count: int
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last_organized_at: Optional[str] = None
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latest_page: Optional[WikiPagePreview] = None
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llm_configured: bool = False
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llm_model: Optional[str] = None
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compiler_mode: str = "deterministic"
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daily_llm_limit: int = 20
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llm_used_today: int = 0
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llm_remaining_today: int = 20
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quota_exceeded: bool = False
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recharge_message: Optional[str] = None
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class WikiGraphNodeOut(BaseModel):
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id: str
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slug: str
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title: str
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category: str
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summary: str
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source_count: int
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updated_at: str
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degree: int = 0
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class WikiGraphLinkOut(BaseModel):
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source: str
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target: str
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relation: str
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class WikiGraphOut(BaseModel):
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nodes: list[WikiGraphNodeOut]
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links: list[WikiGraphLinkOut]
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class WikiSettingsUpdate(BaseModel):
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enabled: Optional[bool] = None
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auto_organize: Optional[bool] = None
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# Memory coach (Q/K/V dialogue)
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class MemoryToken(BaseModel):
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role: str
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key: str
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label: str
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value: str
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revealed: bool = False
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class CoachWordBrief(BaseModel):
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word_id: int
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zh: str
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phonetic: Optional[str] = None
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retention_now: float
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mastery_score: int
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status: str
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retrievability: float = 0.0
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next_review_at: Optional[str] = None
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class CoachSessionResponse(BaseModel):
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words: list[CoachWordBrief]
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total: int
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class CoachTurnRequest(BaseModel):
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word_id: int
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stage: str = "intro"
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user_message: str = ""
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hints_used: int = Field(0, ge=0, le=20)
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duration_seconds: Optional[int] = Field(None, ge=0, le=3600)
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class MemoryTransformerCurvePoint(BaseModel):
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hours_ahead: float
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recall_percent: float
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forgetting_percent: float
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class MemoryTransformerAttention(BaseModel):
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index: int
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label: str
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weight: float
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class MemoryTransformerPredictResponse(BaseModel):
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word_id: int
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en: str
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recall_now_percent: float
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formula_recall_percent: float
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model_recall_percent: float
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blend_weight: float
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event_count: int
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model_trained: bool
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recommended_review_days: int
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half_life_hours: Optional[float] = None
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curve: list[MemoryTransformerCurvePoint]
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attention_hint: list[MemoryTransformerAttention]
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class CoachTurnResponse(BaseModel):
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assistant_messages: list[str]
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tokens: list[MemoryToken] = []
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stage: str
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expect_input: bool
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prompt_zh: str = ""
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prompt_phonetic: Optional[str] = None
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input_hint: str = "请输入对应的英文单词"
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is_correct: Optional[bool] = None
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quiz_recorded: bool = False
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word_complete: bool = False
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hints_used: int = 0
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target_en: Optional[str] = None
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target_zh: Optional[str] = None
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review_message: Optional[str] = None
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retrievability: Optional[float] = None
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next_review_at: Optional[str] = None
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