freedakgmail
86 lines
1.8 KiB
Python
86 lines
1.8 KiB
Python
"""API 数据传输模型（Pydantic）。"""
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from __future__ import annotations
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import uuid
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from pydantic import BaseModel, Field
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class EntityOut(BaseModel):
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id: uuid.UUID
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entity_type: str
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business_key: str
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display_name: str | None = None
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attributes: dict = Field(default_factory=dict)
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model_config = {"from_attributes": True}
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class RelatedEntityOut(BaseModel):
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"""穿透命中的关联实体，附最短跳数（证据强度的初步指示）。"""
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entity: EntityOut
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depth: int
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class PenetrateRequest(BaseModel):
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start_entity_id: uuid.UUID
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max_depth: int = Field(default=3, ge=1, le=6)
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class PenetrateResponse(BaseModel):
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start_entity_id: uuid.UUID
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max_depth: int
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related_count: int
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related: list[RelatedEntityOut]
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class ClueOut(BaseModel):
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id: uuid.UUID
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title: str
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risk_domain: str
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scenario_code: str
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confidence: str
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score: float
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status: str
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rationale: str
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evidence: dict = Field(default_factory=dict)
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subjects: dict = Field(default_factory=dict)
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amount_involved: float | None = None
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assignee: str | None = None
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feedback: str | None = None
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model_config = {"from_attributes": True}
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class AssignRequest(BaseModel):
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assignee: str = Field(min_length=1)
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actor: str = Field(min_length=1)
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class AdjudicateRequest(BaseModel):
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confirmed: bool
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actor: str = Field(min_length=1)
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note: str | None = None
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class NLQRequest(BaseModel):
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question: str = Field(min_length=1)
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class NLQResponse(BaseModel):
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question: str
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answer: str
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provider: str
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model: str
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egress: bool
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class DashboardSummary(BaseModel):
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total: int
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by_status: dict[str, int]
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by_confidence: dict[str, int]
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by_scenario: dict[str, int]
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total_amount_involved: float
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