feat: IMAP mail sync with thread-to-contact matching (PRD §6.1)
Real IMAP connection via imapflow library: - Connects to IMAP server (IMAPFlow, TLS on port 993) - Fetches recent messages (configurable limit, default 20) - Extracts: from, fromEmail, subject, date, snippet (200 chars) - Thread-to-contact matching (PRD §6.1): 1. Match sender email against persons table 2. If no person match, extract domain and match against company.website 3. Returns matchedCompany + matchedPerson for each email - Audit-logged (action: crm.mailsync:imap) - Zod validated (host, port, user, password, folder, limit) - 502 on IMAP connection failure with detail - 400 on validation failure Tested: invalid creds → 502 'IMAP connection failed', missing host → 400
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from __future__ import annotations
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from dataclasses import asdict
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from pathlib import Path
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import uuid
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import json
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from .models import KnowledgePoint, KnowledgeSource, Question, QuizSession, MasteryRecord
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from .repository import JsonRepository
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from .quiz_generator import QuizGenerator
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from .evaluator import Evaluator
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from .mastery_engine import MasteryEngine
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from .planner import Planner
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class QuizMasteryService:
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def __init__(self, base_dir: str | Path):
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self.repo = JsonRepository(base_dir)
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self.generator = QuizGenerator()
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self.evaluator = Evaluator()
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self.mastery_engine = MasteryEngine()
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self.planner = Planner()
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# ── Knowledge Points ──────────────────────────────────────────
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def load_knowledge_points(self, document_id: str) -> list[KnowledgePoint]:
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"""Load knowledge points from JSON file."""
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raw = self.repo.load_json(
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self.repo.knowledge_points_path(document_id), default={}
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)
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items = raw.get("knowledge_points", [])
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result: list[KnowledgePoint] = []
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for item in items:
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source_data = item.get("source")
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kp = KnowledgePoint(
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id=item["id"],
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title=item["title"],
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description=item.get("description", ""),
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definition=item.get("definition", ""),
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tags=item.get("tags", []),
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source=KnowledgeSource(**source_data) if source_data else None,
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)
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result.append(kp)
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return result
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def save_knowledge_points(
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self, document_id: str, knowledge_points_data: list[dict]
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) -> None:
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"""Save extracted knowledge points to JSON.
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Args:
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document_id: Document identifier.
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knowledge_points_data: List of dicts, each with id, title,
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definition, description, tags.
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"""
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payload = {"knowledge_points": knowledge_points_data}
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self.repo.save_json(
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self.repo.knowledge_points_path(document_id), payload
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)
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# ── Progress ──────────────────────────────────────────────────
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def load_progress(
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self, user_id: str, document_id: str
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) -> dict[str, MasteryRecord]:
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"""Load user mastery progress from JSON."""
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raw = self.repo.load_json(
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self.repo.progress_path(user_id, document_id), default={}
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)
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mastery_records = raw.get("mastery_records", {})
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parsed: dict[str, MasteryRecord] = {}
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for kp_id, record in mastery_records.items():
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mr = MasteryRecord(knowledge_point_id=kp_id)
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mr.current_level = record.get("current_level", 1)
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mr.attempts = record.get("attempts", 0)
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mr.last_accuracy = record.get("last_accuracy", 0.0)
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mr.best_accuracy = record.get("best_accuracy", 0.0)
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mr.last_reviewed_at = record.get("last_reviewed_at")
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mr.is_weak = record.get("is_weak", False)
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mr.accuracy_history = record.get("accuracy_history", [])
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mr.next_review_at = record.get("next_review_at")
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mr.review_stage = record.get("review_stage", 0)
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parsed[kp_id] = mr
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return parsed
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def save_progress(
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self,
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user_id: str,
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document_id: str,
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records: dict[str, MasteryRecord],
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) -> None:
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"""Save user mastery progress to JSON."""
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payload = {
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"user_id": user_id,
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"document_id": document_id,
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"mastery_records": {
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kp_id: asdict(record) for kp_id, record in records.items()
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},
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}
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self.repo.save_json(
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self.repo.progress_path(user_id, document_id), payload
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)
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# ── Quiz Generation ───────────────────────────────────────────
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def generate_quiz_for_user(
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self,
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user_id: str,
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document_id: str,
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knowledge_point_ids: list[str] | None = None,
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level: int | None = None,
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num_questions: int | None = None,
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) -> dict:
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"""Generate quiz prompts for given knowledge points.
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If knowledge_point_ids is None, uses all knowledge points.
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If level is None, reads current_level from mastery records
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(first-time defaults to 1).
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Returns dict with 'prompts' (system_prompt + user_prompt),
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'knowledge_points' used, and 'level'.
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"""
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knowledge_points = self.load_knowledge_points(document_id)
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progress = self.load_progress(user_id, document_id)
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if knowledge_point_ids:
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selected = [kp for kp in knowledge_points if kp.id in knowledge_point_ids]
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else:
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selected = knowledge_points
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if not selected:
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return {"error": "No knowledge points found"}
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# Determine level per knowledge point group
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# Use the most common level or explicit level
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if level is not None:
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quiz_level = max(1, min(3, level))
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else:
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# Determine from mastery records; first-time = 1
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levels = []
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for kp in selected:
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record = progress.get(kp.id)
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if record is None:
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levels.append(1) # First time → L1
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else:
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levels.append(record.current_level)
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# Use the minimum level among selected (conservative)
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quiz_level = min(levels) if levels else 1
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prompts = self.generator.generate_quiz(
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selected, level=quiz_level, num_questions=num_questions
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)
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return {
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"document_id": document_id,
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"user_id": user_id,
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"level": quiz_level,
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"knowledge_point_ids": [kp.id for kp in selected],
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"prompts": prompts,
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}
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# ── Quiz Submission ───────────────────────────────────────────
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def submit_quiz_answers(
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self,
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user_id: str,
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document_id: str,
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session_id: str,
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answers: dict[str, str],
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) -> dict:
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"""Submit answers for a quiz session, evaluate, and update mastery."""
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session_data = self.repo.load_json(
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self.repo.session_path(session_id), default=None
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)
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if not session_data:
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raise FileNotFoundError(f"Quiz session not found: {session_id}")
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questions = []
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for item in session_data["questions"]:
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questions.append(Question(**item))
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results = self.evaluator.evaluate_answers(questions, answers)
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progress = self.load_progress(user_id, document_id)
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updated = self.mastery_engine.update_mastery(progress, questions, results)
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self.save_progress(user_id, document_id, updated)
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# Calculate score (excluding short_answer with score=None)
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scored_results = [r for r in results if r.score is not None]
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score = sum(r.score for r in scored_results)
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total = len(scored_results)
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needs_review_count = sum(1 for r in results if r.needs_review)
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summary = {
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"session_id": session_id,
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"score": score,
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"total": total,
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"accuracy": score / total if total else 0.0,
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"needs_review_count": needs_review_count,
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"results": [asdict(r) for r in results],
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}
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# Update session data
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session_data["answers"] = answers
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session_data["results"] = summary["results"]
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session_data["status"] = "completed"
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self.repo.save_json(self.repo.session_path(session_id), session_data)
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return summary
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# ── Import Questions ──────────────────────────────────────────
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def import_questions(
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self,
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document_id: str,
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user_id: str,
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questions_data: list[dict],
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) -> dict:
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"""Import parsed questions and create a quiz session.
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Args:
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document_id: Document identifier.
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user_id: User identifier.
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questions_data: List of question dicts (from LLM parsing).
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Returns:
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dict with session_id and questions.
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"""
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questions: list[Question] = []
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for item in questions_data:
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q = Question(
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id=item.get("id", f"q_{uuid.uuid4().hex[:8]}"),
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knowledge_point_ids=item.get("knowledge_point_ids", []),
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level=item.get("level", 1),
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type=item.get("type", "single_choice"),
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prompt=item.get("prompt", ""),
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options=item.get("options", []),
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answer=item.get("answer"),
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explanation=item.get("explanation", ""),
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source_refs=item.get("source_refs", []),
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)
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questions.append(q)
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session_id = f"quiz_{uuid.uuid4().hex[:12]}"
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kp_ids = list(
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set(kp_id for q in questions for kp_id in q.knowledge_point_ids)
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)
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level = questions[0].level if questions else 1
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session = QuizSession(
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session_id=session_id,
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user_id=user_id,
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document_id=document_id,
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level=level,
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knowledge_point_ids=kp_ids,
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questions=questions,
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)
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self.repo.save_json(
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self.repo.session_path(session_id),
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asdict(session),
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)
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return {
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"session_id": session_id,
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"document_id": document_id,
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"level": level,
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"num_questions": len(questions),
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"questions": [asdict(q) for q in questions],
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}
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# ── Review Candidates ─────────────────────────────────────────
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def get_review_candidates(
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self, user_id: str, document_id: str, today_str: str | None = None
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) -> list[dict]:
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"""Get review recommendations for a user.
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Returns list of knowledge points that need review.
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"""
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from datetime import datetime
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if today_str is None:
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today_str = datetime.now().strftime("%Y-%m-%d")
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knowledge_points = self.load_knowledge_points(document_id)
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progress = self.load_progress(user_id, document_id)
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return self.planner.recommend_review(knowledge_points, progress, today_str)
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# ── User Progress ─────────────────────────────────────────────
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def get_user_progress(self, user_id: str, document_id: str) -> dict:
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"""Get user's mastery progress summary."""
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progress = self.load_progress(user_id, document_id)
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return {
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"user_id": user_id,
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"document_id": document_id,
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"mastery_records": {
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kp_id: asdict(record) for kp_id, record in progress.items()
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},
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}
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