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29 lines
1.2 KiB
Python
29 lines
1.2 KiB
Python
from datetime import datetime
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from typing import List, Optional
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from pgvector.sqlalchemy import VECTOR
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from pydantic import BaseModel
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from sqlalchemy import Column, Text, BigInteger, DateTime, Identity
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from sqlmodel import SQLModel, Field
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class DataTraining(SQLModel, table=True):
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__tablename__ = "data_training"
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id: Optional[int] = Field(sa_column=Column(BigInteger, Identity(always=True), primary_key=True))
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oid: Optional[int] = Field(sa_column=Column(BigInteger, nullable=True, default=1))
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datasource: Optional[int] = Field(sa_column=Column(BigInteger, nullable=True))
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create_time: Optional[datetime] = Field(sa_column=Column(DateTime(timezone=False), nullable=True))
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question: Optional[str] = Field(max_length=255)
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description: Optional[str] = Field(sa_column=Column(Text, nullable=True))
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embedding: Optional[List[float]] = Field(sa_column=Column(VECTOR(), nullable=True))
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class DataTrainingInfo(BaseModel):
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id: Optional[int] = None
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oid: Optional[int] = None
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datasource: Optional[int] = None
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datasource_name: Optional[str] = None
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create_time: Optional[datetime] = None
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question: Optional[str] = None
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description: Optional[str] = None
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