feat: complete exam lifecycle — AI generation, submission, student session, and results

- Backend: AI generation fallbacks when OpenAI not configured, full exam
  submission saving all params (difficulty, rubric, entity, grading system,
  approval workflow) and creating linked question records per section
- Backend: new exam session controller with get_session, autosave, submit,
  status, and results endpoints; student attempt/answer/score models
- Backend: new controllers for entities, approval workflows, exam schedules
- Frontend: exam session split-layout with passage panel, question types
  (MCQ, T/F/NG, gap-fill, writing, speaking), timer, and review dialog
- Frontend: results page with percentage score, per-answer breakdown table
- Frontend: generation page dynamic dropdowns, full payload submission
- Frontend: updated types for ExamSessionSection, ExamQuestion options

Made-with: Cursor

custom_addons/encoach_scoring/controllers/exam_session.py

@@ -186,21 +186,38 @@ class EncoachExamSessionController(http.Controller):
                     q_dict = _question_to_student_dict(q)
                     q_dict['saved_answer'] = saved_answers.get(q.id, '')
                     questions.append(q_dict)
-                sections.append({
+                sec_dict = {
                     'id': sec.id,
                     'title': sec.title,
                     'skill': sec.skill or '',
+                    'difficulty': sec.difficulty or '',
                     'time_limit_min': sec.time_limit_min or 0,
+                    'total_marks': sec.total_marks or 0,
                     'scoring_method': sec.scoring_method or 'auto',
                     'sequence': sec.sequence,
                     'questions': questions,
-                })
+                }
+                if sec.passage_text:
+                    sec_dict['passage_text'] = sec.passage_text
+                if sec.instructions_text:
+                    sec_dict['instructions_text'] = sec.instructions_text
+                if sec.content_json:
+                    try:
+                        sec_dict['content'] = json.loads(sec.content_json)
+                    except (json.JSONDecodeError, TypeError):
+                        pass
+                sections.append(sec_dict)
 
             return _json_response({
                 'attempt_id': attempt.id,
                 'exam_id': exam.id,
                 'exam_title': exam.title,
+                'exam_mode': exam.exam_mode or 'official',
                 'total_time_min': exam.total_time_min or 0,
+                'total_marks': exam.total_marks or 0,
+                'grading_system': exam.grading_system or 'ielts',
+                'access_type': exam.access_type or 'private',
+                'randomize_questions': exam.randomize_questions or False,
                 'status': attempt.status,
                 'started_at': attempt.started_at,
                 'sections': sections,