from datetime import datetime
from pgvector.sqlalchemy import Vector
from sqlalchemy import Column, DateTime, Integer, String, Text, JSON, ForeignKey
from sqlalchemy.orm import relationship, deferred

from app.config import settings
from app.database import Base
from app.models.question_category import QuestionCategory  # noqa — ensures mapper resolves
from app.models.quiz_question_link import QuizQuestionLink  # noqa


class Question(Base):
    __tablename__ = "questions"

    id = Column(Integer, primary_key=True, index=True)
    # source_quiz_id: which quiz this question was originally extracted for (informational).
    # Content membership is tracked via quiz_question_links junction table.
    source_quiz_id = Column("quiz_id", Integer, ForeignKey("quizzes.id", ondelete="SET NULL"), nullable=True)
    question_category_id = Column(Integer, ForeignKey("question_categories.id", ondelete="SET NULL"), nullable=True)
    question_text = Column(Text, nullable=False)
    question_type = Column(String, nullable=False)  # mcq, true_false, fill_blank
    options = Column(JSON, nullable=True)  # list of strings for mcq
    correct_answer = Column(String, nullable=False)
    explanation = Column(Text, nullable=True)
    page_reference = Column(Integer, nullable=True)
    image_path = Column(String, nullable=True)
    explanation_image_path = Column(String, nullable=True)
    option_explanations = Column(JSON, nullable=True)  # {option_text: explanation}
    key_points = Column(JSON, nullable=True)  # [{"text", "article_id"?, "article_section_id"?}] smart links
    difficulty = Column(String(10), nullable=True)  # easy | medium | hard
    user_id = Column(Integer, ForeignKey("users.id", ondelete="SET NULL"), nullable=True)
    is_shared = Column(Integer, default=1)  # 1 = visible in bank, 0 = private (only owner sees it)
    embedding = deferred(Column(Vector(settings.EMBEDDING_DIMENSIONS), nullable=True))  # semantic search vector — deferred: not loaded in standard queries
    # Which model produced `embedding`. Vectors from different models are not
    # comparable, so a model change must be detectable rather than silent.
    embedding_model = Column(String(120), nullable=True, index=True)
    embedded_at = Column(DateTime, nullable=True)

    question_category = relationship("QuestionCategory", back_populates="questions",
                                     foreign_keys=[question_category_id])


class QuestionVersion(Base):
    """A snapshot of a question as it was before an edit.

    Only the last MAX_VERSIONS are kept: the point is undoing a recent mistake,
    not an audit trail, and full question bodies add up.
    """

    __tablename__ = "question_versions"

    id = Column(Integer, primary_key=True, index=True)
    question_id = Column(Integer, ForeignKey("questions.id", ondelete="CASCADE"), nullable=False, index=True)
    snapshot = Column(JSON, nullable=False)
    edited_by = Column(Integer, ForeignKey("users.id", ondelete="SET NULL"), nullable=True)
    created_at = Column(DateTime, default=datetime.utcnow)