feat: add new folder
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Daniel
86
gig-poc/apps/api/app/domain/models.py
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86
gig-poc/apps/api/app/domain/models.py
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from datetime import datetime
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from uuid import uuid4
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from sqlalchemy import DateTime, Float, ForeignKey, Integer, String, Text, func
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from sqlalchemy.dialects.postgresql import JSONB
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from sqlalchemy.orm import Mapped, mapped_column, relationship
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from app.db.base import Base
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class Job(Base):
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__tablename__ = "jobs"
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id: Mapped[str] = mapped_column(String(64), primary_key=True, default=lambda: f"job_{uuid4().hex[:12]}")
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title: Mapped[str] = mapped_column(String(255))
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category: Mapped[str] = mapped_column(String(128))
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description: Mapped[str] = mapped_column(Text)
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city: Mapped[str] = mapped_column(String(64))
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region: Mapped[str] = mapped_column(String(64))
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location_detail: Mapped[str] = mapped_column(String(255))
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start_time: Mapped[datetime] = mapped_column(DateTime(timezone=True))
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duration_hours: Mapped[float] = mapped_column(Float)
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headcount: Mapped[int] = mapped_column(Integer)
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salary_type: Mapped[str] = mapped_column(String(32))
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salary_amount: Mapped[float] = mapped_column(Float)
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salary_currency: Mapped[str] = mapped_column(String(16), default="CNY")
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work_mode: Mapped[str] = mapped_column(String(64))
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tags_json: Mapped[list[str]] = mapped_column(JSONB, default=list)
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confidence: Mapped[float] = mapped_column(Float)
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created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
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skills: Mapped[list["JobSkill"]] = relationship(back_populates="job", cascade="all, delete-orphan")
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class JobSkill(Base):
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__tablename__ = "job_skills"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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job_id: Mapped[str] = mapped_column(ForeignKey("jobs.id", ondelete="CASCADE"), index=True)
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skill_name: Mapped[str] = mapped_column(String(128), index=True)
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weight: Mapped[float] = mapped_column(Float, default=1.0)
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is_required: Mapped[bool] = mapped_column(default=True)
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job: Mapped[Job] = relationship(back_populates="skills")
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class Worker(Base):
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__tablename__ = "workers"
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id: Mapped[str] = mapped_column(String(64), primary_key=True, default=lambda: f"worker_{uuid4().hex[:12]}")
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name: Mapped[str] = mapped_column(String(128))
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description: Mapped[str] = mapped_column(Text)
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cities_json: Mapped[list[str]] = mapped_column(JSONB, default=list)
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regions_json: Mapped[list[str]] = mapped_column(JSONB, default=list)
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availability_json: Mapped[list[str]] = mapped_column(JSONB, default=list)
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experience_tags_json: Mapped[list[str]] = mapped_column(JSONB, default=list)
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reliability_score: Mapped[float] = mapped_column(Float, default=0.7)
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profile_completion: Mapped[float] = mapped_column(Float, default=0.6)
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confidence: Mapped[float] = mapped_column(Float, default=0.8)
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created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
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skills: Mapped[list["WorkerSkill"]] = relationship(back_populates="worker", cascade="all, delete-orphan")
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class WorkerSkill(Base):
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__tablename__ = "worker_skills"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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worker_id: Mapped[str] = mapped_column(ForeignKey("workers.id", ondelete="CASCADE"), index=True)
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skill_name: Mapped[str] = mapped_column(String(128), index=True)
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score: Mapped[float] = mapped_column(Float, default=0.7)
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worker: Mapped[Worker] = relationship(back_populates="skills")
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class MatchRecord(Base):
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__tablename__ = "matches"
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id: Mapped[str] = mapped_column(String(64), primary_key=True, default=lambda: f"match_{uuid4().hex[:12]}")
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source_type: Mapped[str] = mapped_column(String(32), index=True)
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source_id: Mapped[str] = mapped_column(String(64), index=True)
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target_id: Mapped[str] = mapped_column(String(64), index=True)
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match_score: Mapped[float] = mapped_column(Float)
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breakdown_json: Mapped[dict] = mapped_column(JSONB)
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reasons_json: Mapped[list[str]] = mapped_column(JSONB)
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created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
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171
gig-poc/apps/api/app/domain/schemas.py
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171
gig-poc/apps/api/app/domain/schemas.py
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from __future__ import annotations
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from datetime import datetime
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from enum import Enum
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from pydantic import BaseModel, Field, field_validator, model_validator
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class SalaryType(str, Enum):
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daily = "daily"
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hourly = "hourly"
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monthly = "monthly"
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task = "task"
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class SourceType(str, Enum):
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job_to_worker = "job_to_worker"
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worker_to_job = "worker_to_job"
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class Salary(BaseModel):
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type: SalaryType = SalaryType.daily
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amount: float = 0
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currency: str = "CNY"
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class SkillScore(BaseModel):
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name: str
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score: float = Field(ge=0, le=1)
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class JobCard(BaseModel):
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job_id: str
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title: str
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category: str
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description: str
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skills: list[str] = Field(default_factory=list)
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city: str
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region: str
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location_detail: str
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start_time: datetime
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duration_hours: float = Field(gt=0)
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headcount: int = Field(gt=0)
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salary: Salary
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work_mode: str
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tags: list[str] = Field(default_factory=list)
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confidence: float = Field(ge=0, le=1)
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class WorkerCard(BaseModel):
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worker_id: str
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name: str
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description: str
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skills: list[SkillScore] = Field(default_factory=list)
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cities: list[str] = Field(default_factory=list)
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regions: list[str] = Field(default_factory=list)
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availability: list[str] = Field(default_factory=list)
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experience_tags: list[str] = Field(default_factory=list)
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reliability_score: float = Field(ge=0, le=1)
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profile_completion: float = Field(ge=0, le=1)
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confidence: float = Field(ge=0, le=1)
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class MatchBreakdown(BaseModel):
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skill_score: float = Field(ge=0, le=1)
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region_score: float = Field(ge=0, le=1)
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time_score: float = Field(ge=0, le=1)
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experience_score: float = Field(ge=0, le=1)
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reliability_score: float = Field(ge=0, le=1)
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class MatchResult(BaseModel):
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match_id: str
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source_type: SourceType
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source_id: str
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target_id: str
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match_score: float = Field(ge=0, le=1)
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breakdown: MatchBreakdown
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reasons: list[str] = Field(default_factory=list, min_length=3)
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class ExtractTextRequest(BaseModel):
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text: str = Field(min_length=5)
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class IngestJobRequest(BaseModel):
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job: JobCard
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class IngestWorkerRequest(BaseModel):
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worker: WorkerCard
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class MatchWorkersRequest(BaseModel):
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job_id: str | None = None
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job: JobCard | None = None
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top_n: int = Field(default=10, ge=1, le=50)
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@model_validator(mode="after")
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def validate_source(self) -> "MatchWorkersRequest":
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if not self.job_id and not self.job:
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raise ValueError("job_id 或 job 至少需要提供一个")
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return self
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class MatchJobsRequest(BaseModel):
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worker_id: str | None = None
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worker: WorkerCard | None = None
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top_n: int = Field(default=10, ge=1, le=50)
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@model_validator(mode="after")
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def validate_source(self) -> "MatchJobsRequest":
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if not self.worker_id and not self.worker:
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raise ValueError("worker_id 或 worker 至少需要提供一个")
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return self
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class ExtractResponse(BaseModel):
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success: bool
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data: JobCard | WorkerCard | None = None
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errors: list[str] = Field(default_factory=list)
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missing_fields: list[str] = Field(default_factory=list)
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class BootstrapResponse(BaseModel):
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jobs: int
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workers: int
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skills: int
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categories: int
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regions: int
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class HealthStatus(BaseModel):
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service: str
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database: str
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rag: str
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timestamp: datetime
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class ListResponse(BaseModel):
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items: list[dict]
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total: int
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class MatchResponse(BaseModel):
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items: list[MatchResult]
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class ExplainResponse(BaseModel):
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match: MatchResult
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class PromptOutput(BaseModel):
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content: dict
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raw_text: str
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class QueryFilters(BaseModel):
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entity_type: str
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city: str | None = None
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region: str | None = None
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categories: list[str] = Field(default_factory=list)
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tags: list[str] = Field(default_factory=list)
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skills: list[str] = Field(default_factory=list)
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@field_validator("entity_type")
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@classmethod
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def validate_entity_type(cls, value: str) -> str:
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if value not in {"job", "worker"}:
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raise ValueError("entity_type must be job or worker")
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return value
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