feat: update cms case api
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@@ -72,6 +72,54 @@ def parse_pdf(files, case_type: str, user) -> dict:
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}
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def generate_from_prompt(prompt: str, case_type: str, user) -> dict:
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"""CMS-CASE-AI-1: 一段长 prompt → DeepSeek 按病例模板生成结构化病例内容。
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产出与 parse_pdf 同构(不落库、不含评分规则),缓存 parse_id 供后续 full-create 复用。
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"""
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if case_type not in ('traditional', 'teaching'):
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raise AppError('CASE_TYPE_NOT_SUPPORTED', f'case_type 不支持: {case_type}', status_code=400)
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if not (prompt or '').strip():
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raise AppError('CASE_VALIDATION_ERROR', 'prompt 必填', status_code=400)
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t0 = time.time()
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prompt_name = f'case_{case_type}_full'
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system_prompt, prompt_version = load_prompt(prompt_name)
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result = deepseek_client.call_deepseek(system_prompt, prompt)
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data = result['data']
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data.pop('scoring_rules', None)
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data.pop('stages', None)
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data['case_type'] = case_type
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if 'exam_items' in data:
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data['exam_items'] = normalize_exam_items(data.get('exam_items') or [])
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else:
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data['exam_items'] = []
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_strip_unknown_fields(data)
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_validate_schema(data)
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parse_id = uuid.uuid4().hex[:12]
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cache.set(f'parse_result:{parse_id}', json.dumps(data, ensure_ascii=False), PARSE_RESULT_TTL)
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audit.info(
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'CASE_AI_GENERATE user=%s parse_id=%s tokens=%s prompt_version=%s',
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user.id, parse_id, result.get('usage', {}), prompt_version,
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)
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return {
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'parse_id': parse_id,
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'case_type': case_type,
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'ai_usage': result.get('usage', {}),
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'prompt_version': prompt_version,
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'generating_seconds': round(time.time() - t0, 1),
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'data': data,
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}
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_SCHEMA_ALLOWED_KEYS = {
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'title', 'case_type', 'difficulty', 'chief_complaint', 'description',
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'patient_age', 'patient_gender', 'tags', 'symptom_tags', 'disease_tags',
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@@ -0,0 +1,216 @@
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"""病例落库 / 完整结构组装的共享逻辑。
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`/api/case/cases/full-create`(业务域)与 `/api/cms/cases/`(CMS 内容管理)共用同一套
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创建与序列化逻辑,避免两处实现漂移。
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"""
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from django.db import transaction
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from config.exceptions import AppError
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from ..models import (
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CaseBase, TraditionalCase, TeachingCase, ScoringRule, CaseExamItem,
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)
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from .department_resolver import resolve_department
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from .exam_items import (
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normalize_exam_items, assert_no_duplicate_exam_items, EXAM_ITEM_FIELDS,
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)
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TRADITIONAL_FIELDS = {'standard_diagnosis', 'standard_treatment', 'guideline_reference'}
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TEACHING_FIELDS = {'teaching_goal', 'discussion_questions', 'teacher_guide', 'scoring_focus'}
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SCORING_RULE_FIELDS = {
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'dimension', 'competency_dimension', 'score_weight',
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'ai_auto_score', 'osce_dimension', 'scoring_standard', 'rubric_json',
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}
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CASE_BASE_FIELDS = {
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'title', 'case_type', 'difficulty', 'difficulty_score',
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'chief_complaint', 'description', 'patient_age', 'patient_gender',
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'tags', 'symptom_tags', 'disease_tags', 'competency_tags',
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'guideline_tags', 'knowledge_points', 'icd_codes',
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'estimated_minutes', 'osce_enabled', 'rag_enabled',
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'ai_prompt_template', 'multimodal_assets',
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}
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def validate_scoring_rules(rules):
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if not isinstance(rules, list):
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raise AppError('CASE_VALIDATION_ERROR', 'scoring_rules 必须为数组', status_code=400)
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for i, rule in enumerate(rules):
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if not isinstance(rule, dict):
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raise AppError('CASE_VALIDATION_ERROR', f'scoring_rules[{i}] 必须为对象', status_code=400)
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if not rule.get('dimension'):
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raise AppError('CASE_VALIDATION_ERROR', f'scoring_rules[{i}].dimension 必填', status_code=400)
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weight = rule.get('score_weight')
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if weight is not None:
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try:
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weight = float(weight)
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except (TypeError, ValueError):
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raise AppError('CASE_VALIDATION_ERROR', f'scoring_rules[{i}].score_weight 须为数字', status_code=400)
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if weight <= 0 or weight > 1:
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raise AppError('CASE_VALIDATION_ERROR', f'scoring_rules[{i}].score_weight 须在 (0, 1]', status_code=400)
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_UNSET = object()
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def create_case_full(data, user, institution=_UNSET):
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"""主表 + 子表 + scoring_rules(≥1) + exam_items 同一事务入库。
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institution:病例所属机构;默认取创建者所属机构(`user.institution`)。
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返回 (case, scoring_rule_count, exam_item_count)。校验失败抛 AppError。
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"""
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if institution is _UNSET:
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institution = getattr(user, 'institution', None)
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case_type = data.get('case_type', '')
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if case_type not in ('traditional', 'teaching'):
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raise AppError('CASE_TYPE_NOT_SUPPORTED', f'case_type 不支持: {case_type}', status_code=400)
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if 'stages' in data:
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raise AppError('CASE_FIELD_NOT_ALLOWED', '本接口不接收 stages 字段', status_code=400)
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sub_data = data.get(case_type)
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other_type = 'teaching' if case_type == 'traditional' else 'traditional'
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if not sub_data:
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raise AppError('CASE_SUBTYPE_REQUIRED', f'{case_type} 子表数据缺失', status_code=400)
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if data.get(other_type):
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raise AppError('CASE_SUBTYPE_CONFLICT', '不允许同时传入两种子表数据', status_code=400)
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scoring_rules_data = data.get('scoring_rules', [])
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if not scoring_rules_data:
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raise AppError('CASE_VALIDATION_ERROR', 'scoring_rules 必填且至少 1 条', status_code=400)
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validate_scoring_rules(scoring_rules_data)
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exam_items_data = normalize_exam_items(data.get('exam_items') or [])
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assert_no_duplicate_exam_items(exam_items_data)
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department = resolve_department(data.get('department_name', ''))
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with transaction.atomic():
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case_kwargs = {k: data[k] for k in CASE_BASE_FIELDS if k in data}
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case_kwargs['department'] = department
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case_kwargs['institution'] = institution
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case_kwargs['created_by'] = user
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case_kwargs['status'] = 1
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case_kwargs['vector_status'] = 0
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case_kwargs['publish_status'] = 1 if data.get('auto_publish') else 0
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case = CaseBase.objects.create(**case_kwargs)
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sub_model = TraditionalCase if case_type == 'traditional' else TeachingCase
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allowed_sub = TRADITIONAL_FIELDS if case_type == 'traditional' else TEACHING_FIELDS
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sub_model.objects.create(case=case, **{k: v for k, v in sub_data.items() if k in allowed_sub})
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rule_objs = [
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ScoringRule(case=case, **{k: v for k, v in rule.items() if k in SCORING_RULE_FIELDS})
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for rule in scoring_rules_data
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]
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ScoringRule.objects.bulk_create(rule_objs)
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if exam_items_data:
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exam_objs = [
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CaseExamItem(case=case, **{k: v for k, v in item.items() if k in EXAM_ITEM_FIELDS})
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for item in exam_items_data
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]
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CaseExamItem.objects.bulk_create(exam_objs)
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return case, len(rule_objs), len(exam_items_data)
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def build_full_response(case):
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"""组装病例完整结构(主表 + 子表 + scoring_rules + exam_items)。"""
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if hasattr(case, '_prefetched_objects_cache') and 'exam_items' in getattr(
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case, '_prefetched_objects_cache', {}
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):
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exam_qs = case.exam_items.all()
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else:
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exam_qs = CaseExamItem.objects.filter(case_id=case.id).order_by('display_order', 'id')
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result = {
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'case': {
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'id': case.id,
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'title': case.title,
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'case_type': case.case_type,
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'difficulty': case.difficulty,
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'difficulty_score': case.difficulty_score,
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'institution': case.institution_id,
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'institution_name': case.institution.name if case.institution else None,
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'department': case.department_id,
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'department_name': case.department.name if case.department else None,
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'chief_complaint': case.chief_complaint,
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'description': case.description,
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'patient_age': case.patient_age,
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'patient_gender': case.patient_gender,
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'tags': case.tags,
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'symptom_tags': case.symptom_tags,
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'disease_tags': case.disease_tags,
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'competency_tags': case.competency_tags,
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'guideline_tags': case.guideline_tags,
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'knowledge_points': case.knowledge_points,
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'icd_codes': case.icd_codes,
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'estimated_minutes': case.estimated_minutes,
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'osce_enabled': case.osce_enabled,
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'rag_enabled': case.rag_enabled,
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'ai_prompt_template': case.ai_prompt_template,
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'multimodal_assets': case.multimodal_assets,
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'vector_status': case.vector_status,
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'publish_status': case.publish_status,
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'status': case.status,
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'created_by': case.created_by_id,
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'created_by_name': case.created_by.real_name if case.created_by else None,
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'created_at': case.created_at.isoformat() if case.created_at else None,
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'updated_at': case.updated_at.isoformat() if case.updated_at else None,
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},
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}
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if case.case_type == 'traditional':
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try:
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tc = case.traditionalcase
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result['traditional'] = {
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'standard_diagnosis': tc.standard_diagnosis,
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'standard_treatment': tc.standard_treatment,
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'guideline_reference': tc.guideline_reference,
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}
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except TraditionalCase.DoesNotExist:
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result['traditional'] = None
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elif case.case_type == 'teaching':
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try:
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tc = case.teachingcase
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result['teaching'] = {
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'teaching_goal': tc.teaching_goal,
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'discussion_questions': tc.discussion_questions,
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'teacher_guide': tc.teacher_guide,
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'scoring_focus': tc.scoring_focus,
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}
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except TeachingCase.DoesNotExist:
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result['teaching'] = None
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rules = case.scoring_rules.all().order_by('id')
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result['scoring_rules'] = [
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{
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'id': r.id,
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'dimension': r.dimension,
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'competency_dimension': r.competency_dimension,
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'score_weight': float(r.score_weight),
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'ai_auto_score': r.ai_auto_score,
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'osce_dimension': r.osce_dimension,
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'scoring_standard': r.scoring_standard,
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'rubric_json': r.rubric_json,
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}
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for r in rules
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]
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result['exam_items'] = [
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{
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'id': e.id,
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'item_code': e.item_code,
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'item_name': e.item_name,
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'item_type': e.item_type,
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'category': e.category,
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'result_text': e.result_text,
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'result_structured': e.result_structured,
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'is_key': e.is_key,
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'is_abnormal': e.is_abnormal,
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'score_weight': float(e.score_weight),
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'display_order': e.display_order,
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}
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for e in exam_qs
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]
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return result
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