pdf-quiz-generator/backend/app/models/question.py
Daniel 975a31fb01 TeachChat: model selector, proxy routing fix, titan seed cleanup
- teach.py: use _proxy_model() + pass api_key/api_base from settings (fixes LiteLLM provider error for openrouter/bedrock models)
- teach.py: accept model_id in ChatRequest so frontend can select model
- main.py: remove titan-embed-v2 from general seed, auto-delete legacy entry on startup
- main.py: kill stale idle-in-transaction DB connections at startup to prevent DDL lock hangs
- main.py: set lock_timeout=10s on DDL connection as fast-fail safety net
- TeachChat.jsx: fetch /teach/models, show selector dropdown in header when >1 model available

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-04 00:37:35 +02:00

29 lines
1.5 KiB
Python

from pgvector.sqlalchemy import Vector
from sqlalchemy import Column, 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)
embedding = deferred(Column(Vector(1024), nullable=True)) # semantic search vector — deferred: not loaded in standard queries
question_category = relationship("QuestionCategory", back_populates="questions",
foreign_keys=[question_category_id])