from datetime import datetime
from .. import db


class Assessment(db.Model):
    """Stores every stress prediction result for a user."""
    __tablename__ = "assessments"

    id          = db.Column(db.Integer, primary_key=True)
    user_id     = db.Column(db.Integer, db.ForeignKey("users.id"), nullable=False)
    created_at  = db.Column(db.DateTime, default=datetime.utcnow, index=True)

    # ── Input data ──────────────────────────────────────────────────────────
    # Psychometric features (stored as JSON blob for flexibility)
    psychometric_data = db.Column(db.JSON, nullable=True)
    # Raw text note
    text_note   = db.Column(db.Text, nullable=True)

    # ── Prediction results ──────────────────────────────────────────────────
    psycho_label        = db.Column(db.String(16), nullable=True)   # High / Medium / Low
    psycho_score        = db.Column(db.Float, nullable=True)
    text_label          = db.Column(db.String(32), nullable=True)   # e.g. Anxiety
    text_score          = db.Column(db.Float, nullable=True)
    fused_label         = db.Column(db.String(16), nullable=True)   # Minimal..Critical
    fused_score         = db.Column(db.Float, nullable=True)

    # Which modalities were used
    modality_used       = db.Column(db.String(32), nullable=True)   # both / psycho / text

    def to_dict(self):
        return {
            "id":                self.id,
            "user_id":           self.user_id,
            "created_at":        self.created_at.isoformat(),
            "psychometric_data": self.psychometric_data,
            "text_note":         self.text_note,
            "psycho_label":      self.psycho_label,
            "psycho_score":      self.psycho_score,
            "text_label":        self.text_label,
            "text_score":        self.text_score,
            "fused_label":       self.fused_label,
            "fused_score":       self.fused_score,
            "modality_used":     self.modality_used,
        }