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models.py — SQLAlchemy ORM models.
Defines the four core tables: Client, Candidate, Score, and Feedback.
"""
import enum
from datetime import datetime, timezone
from sqlalchemy import (
Column,
DateTime,
Enum,
Float,
ForeignKey,
Integer,
String,
Text,
)
from sqlalchemy.orm import relationship
from .database import Base
# ---------------------------------------------------------------------------
# Enums
# ---------------------------------------------------------------------------
class ArchetypeEnum(str, enum.Enum):
"""Client cultural archetype."""
consulting = "consulting"
startup = "startup"
class OutcomeEnum(str, enum.Enum):
"""Post-interview outcome."""
accepted = "accepted"
rejected = "rejected"
class ReasonEnum(str, enum.Enum):
"""Primary reason for the interview decision."""
communication_soft_skills = "communication_soft_skills"
technical_capability = "technical_capability"
alignment_cultural_vibe = "alignment_cultural_vibe"
candidate_declined = "candidate_declined"
# ---------------------------------------------------------------------------
# ORM Models
# ---------------------------------------------------------------------------
class Client(Base):
"""A client company profile with archetype and minimum BARS thresholds."""
__tablename__ = "clients"
id = Column(Integer, primary_key=True, index=True)
name = Column(String(255), nullable=False)
archetype = Column(Enum(ArchetypeEnum), nullable=False)
expectations = Column(Text, default="")
# Minimum acceptable BARS scores per competency (1-5)
min_communication = Column(Integer, default=3)
min_adaptability = Column(Integer, default=3)
min_collaboration = Column(Integer, default=3)
min_problem_solving = Column(Integer, default=3)
min_leadership = Column(Integer, default=3)
created_at = Column(
DateTime, default=lambda: datetime.now(timezone.utc)
)
candidates = relationship("Candidate", back_populates="client")
class Candidate(Base):
"""A candidate being evaluated for a specific client."""
__tablename__ = "candidates"
id = Column(Integer, primary_key=True, index=True)
name = Column(String(255), nullable=False)
email = Column(String(255), default="")
recruiter_notes = Column(Text, default="")
client_id = Column(Integer, ForeignKey("clients.id"), nullable=False)
created_at = Column(
DateTime, default=lambda: datetime.now(timezone.utc)
)
client = relationship("Client", back_populates="candidates")
score = relationship(
"Score", back_populates="candidate", uselist=False
)
feedback = relationship(
"Feedback", back_populates="candidate", uselist=False
)
class Score(Base):
"""BARS competency scores for a candidate (1-5 per dimension)."""
__tablename__ = "scores"
id = Column(Integer, primary_key=True, index=True)
candidate_id = Column(
Integer, ForeignKey("candidates.id"), unique=True, nullable=False
)
communication = Column(Integer, nullable=False)
adaptability = Column(Integer, nullable=False)
collaboration = Column(Integer, nullable=False)
problem_solving = Column(Integer, nullable=False)
leadership = Column(Integer, nullable=False)
overall_match = Column(Float, default=0.0)
mismatches = Column(Text, default="[]") # JSON-encoded list of strings
candidate = relationship("Candidate", back_populates="score")
class Feedback(Base):
"""Post-interview outcome and client feedback."""
__tablename__ = "feedbacks"
id = Column(Integer, primary_key=True, index=True)
candidate_id = Column(
Integer, ForeignKey("candidates.id"), unique=True, nullable=False
)
outcome = Column(Enum(OutcomeEnum), nullable=False)
primary_reason = Column(Enum(ReasonEnum), nullable=False)
client_notes = Column(Text, default="")
created_at = Column(
DateTime, default=lambda: datetime.now(timezone.utc)
)
candidate = relationship("Candidate", back_populates="feedback")
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