86 lines
2.1 KiB
Python
86 lines
2.1 KiB
Python
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from pydantic import BaseModel, EmailStr
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from typing import Optional, Union, List
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import datetime
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class LoginRequest(BaseModel):
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username: str
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password: str
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class LoginResponse(BaseModel):
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user_id: int
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username: str
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caption: str
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email: EmailStr
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token: str
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class UserInfo(BaseModel):
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user_id: int
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username: str
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caption: str
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email: EmailStr
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created_at: datetime.datetime
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meetings_created: int
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meetings_attended: int
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class AttendeeInfo(BaseModel):
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user_id: int
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caption: str
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class TranscriptionTaskStatus(BaseModel):
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task_id: str
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status: str # 'pending', 'processing', 'completed', 'failed'
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progress: int # 0-100
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meeting_id: int
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created_at: Optional[str] = None
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updated_at: Optional[str] = None
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completed_at: Optional[str] = None
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error_message: Optional[str] = None
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class Meeting(BaseModel):
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meeting_id: int
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title: str
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meeting_time: Optional[datetime.datetime]
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summary: Optional[str]
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created_at: datetime.datetime
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attendees: Union[List[str], List[AttendeeInfo]] # Support both formats
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creator_id: int
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creator_username: str
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audio_file_path: Optional[str] = None
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transcription_status: Optional[TranscriptionTaskStatus] = None
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class TranscriptSegment(BaseModel):
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segment_id: int
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meeting_id: int
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speaker_id: Optional[int] = None # AI解析的原始结果
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speaker_tag: str
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start_time_ms: int
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end_time_ms: int
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text_content: str
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class CreateMeetingRequest(BaseModel):
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user_id: int
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title: str
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meeting_time: Optional[datetime.datetime]
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attendee_ids: list[int]
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class UpdateMeetingRequest(BaseModel):
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title: str
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meeting_time: Optional[datetime.datetime]
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summary: Optional[str]
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attendee_ids: list[int]
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class SpeakerTagUpdateRequest(BaseModel):
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speaker_id: int # 使用原始speaker_id（整数）
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new_tag: str
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class BatchSpeakerTagUpdateRequest(BaseModel):
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updates: List[SpeakerTagUpdateRequest]
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class TranscriptUpdateRequest(BaseModel):
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segment_id: int
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text_content: str
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class BatchTranscriptUpdateRequest(BaseModel):
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updates: List[TranscriptUpdateRequest]
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