backend/src/schemas/match.py

from uuid import UUID
from typing import Any
from pydantic import BaseModel, Field


class ComponentScores(BaseModel):
    semantic: float = 0.0
    skill: float = 0.0
    yoe: float = 0.0
    company: float = 0.0
    growth: float = 0.0
    education: float = 0.0


class GapItem(BaseModel):
    type: str
    detail: str
    mitigated_by_remote: bool | None = None


class MatchedCandidate(BaseModel):
    candidate_id: UUID
    rank: int
    name: str | None = None
    email: str | None = None
    role_type: str | None = None
    engineer_type: str | None = None
    years_of_experience: float | None = None
    most_recent_company: str | None = None
    parsed_summary: str | None = None
    programming_languages: list[str] = []
    growth_velocity: float = 0.5
    stage1_score: float
    stage2_score: float | None = None
    final_score: float
    component_scores: ComponentScores
    gaps: list[GapItem] = []


class MatchResponse(BaseModel):
    jd_id: UUID
    jd_title: str
    jd_quality: dict[str, Any] = {}
    total_matched: int
    results: list[MatchedCandidate]
    weights_used: dict[str, float] = {}
    session_id: UUID | None = None


class CandidateDetailResponse(BaseModel):
    jd_id: UUID
    candidate_id: UUID
    rank: int | None = None
    final_score: float
    component_scores: ComponentScores
    gaps: list[GapItem] = []
    explanation: str | None = None
    candidate: dict[str, Any] = {}
    jd: dict[str, Any] = {}


class ReRankRequest(BaseModel):
    weights: dict[str, float] = Field(
        default={
            "semantic": 0.20,
            "skill": 0.35,
            "yoe": 0.15,
            "company": 0.10,
            "growth": 0.10,
            "education": 0.10,
        }
    )