完善训练链路接口与PDF下载

app/services/training_config_service.py

@@ -1,6 +1,9 @@
+from typing import Any
+
 from sqlalchemy.orm import Session
 
 from app.core.exceptions import AppError
+from app.models.source_case import CaseBase
 from app.repositories.case_repository import CaseRepository
 from app.schemas.training_config import (
     ConfigOption,
@@ -18,9 +21,9 @@ class TrainingConfigService:
         self.case_repo = CaseRepository(db)
 
     def get_recommended(self, case_id: int) -> TrainingConfigRecommendedResponse:
-        """推荐配置：根据病例返回训练页默认病人初始化配置。"""
-        self._ensure_case(case_id)
-        recommended = self.default_patient_config()
+        """推荐配置：根据病例内容返回训练页默认病人初始化配置。"""
+        case = self._get_case(case_id)
+        recommended = self.default_patient_config(case)
         return TrainingConfigRecommendedResponse(
             case_id=case_id,
             recommended=recommended,
@@ -29,9 +32,9 @@ class TrainingConfigService:
         )
 
     def get_options(self, case_id: int) -> TrainingConfigOptionsResponse:
-        """配置选项：返回训练页自定义配置的全部可选项。"""
-        self._ensure_case(case_id)
-        recommended = self.default_patient_config()
+        """配置选项：返回训练页自定义病人初始化配置的全部可选项和病例推荐值。"""
+        case = self._get_case(case_id)
+        recommended = self.default_patient_config(case)
         return TrainingConfigOptionsResponse(
             case_id=case_id,
             recommended=recommended,
@@ -39,18 +42,51 @@ class TrainingConfigService:
             options=self.config_options(),
         )
 
-    def default_patient_config(self) -> PatientConfig:
-        """默认配置：按当前产品原型初始化病人信息。"""
+    def default_patient_config(self, case: CaseBase | None = None) -> PatientConfig:
+        """默认配置：按病例年龄、科室语义和病情关键词初始化 AI 病人沟通风格。"""
+        if case is None:
+            return PatientConfig(
+                visit_environment="outpatient",
+                age_group="youth",
+                education_level="higher",
+                personality="calm",
+            )
+
+        text = self._case_text(case)
+        patient_age = case.patient_age
+
+        visit_environment = "outpatient"
+        personality = "calm"
+        if self._contains_any(
+            text,
+            ["急诊", "危重", "休克", "昏迷", "意识障碍", "呼吸困难", "低氧", "抢救", "SpO2 90", "血氧明显下降"],
+        ):
+            visit_environment = "emergency"
+            personality = "anxious"
+        elif self._contains_any(text, ["住院", "病房", "入院", "住院治疗"]):
+            visit_environment = "ward"
+
+        age_group = "youth"
+        if (patient_age is not None and patient_age < 14) or self._contains_any(
+            text,
+            ["儿童", "患儿", "儿科", "小儿", "幼儿", "婴儿"],
+        ):
+            age_group = "child"
+        elif patient_age is not None and patient_age >= 65:
+            age_group = "elderly"
+        elif patient_age is not None and patient_age >= 45:
+            age_group = "middle_aged"
+
         return PatientConfig(
-            visit_environment="outpatient",
-            age_group="youth",
+            visit_environment=visit_environment,
+            age_group=age_group,
             education_level="higher",
-            personality="calm",
+            personality=personality,
         )
 
-    def normalize_patient_config(self, config: PatientConfig | None) -> dict:
+    def normalize_patient_config(self, config: PatientConfig | None, case: CaseBase | None = None) -> dict:
         """配置归一：校验并补齐前端传入的病人初始化配置。"""
-        selected = config or self.default_patient_config()
+        selected = config or self.default_patient_config(case)
         values = selected.model_dump()
         allowed = {key: {item.value for item in items} for key, items in self.config_options().items()}
         for key, value in values.items():
@@ -75,7 +111,7 @@ class TrainingConfigService:
         return {
             "visit_environment": [
                 ConfigOption(value="outpatient", label="门诊", description="适合常规问诊训练"),
-                ConfigOption(value="emergency", label="急诊", description="病情紧急、沟通节奏更快"),
+                ConfigOption(value="emergency", label="急诊", description="病情紧急，沟通节奏更快"),
                 ConfigOption(value="ward", label="病房", description="适合住院病情追踪和处置沟通"),
             ],
             "age_group": [
@@ -98,7 +134,49 @@ class TrainingConfigService:
             ],
         }
 
-    def _ensure_case(self, case_id: int) -> None:
-        """病例校验：确认配置请求对应已发布病例。"""
-        if not self.case_repo.get_active_case(case_id):
+    def _get_case(self, case_id: int) -> CaseBase:
+        """病例校验：读取配置请求对应的已发布病例。"""
+        case = self.case_repo.get_active_case(case_id)
+        if not case:
             raise AppError("CASE_NOT_FOUND", "case not found or inactive", 404)
+        return case
+
+    def _case_text(self, case: CaseBase) -> str:
+        """病例文本：拼接用于推荐配置推断的病例字段。"""
+        parts: list[str] = [
+            case.title or "",
+            case.chief_complaint or "",
+            case.description or "",
+            case.tags or "",
+            case.patient_gender or "",
+        ]
+        for field_name in (
+            "symptom_tags",
+            "disease_tags",
+            "competency_tags",
+            "guideline_tags",
+            "knowledge_points",
+            "icd_codes",
+        ):
+            parts.extend(self._stringify(getattr(case, field_name, None)))
+        if case.traditional_case:
+            parts.extend(self._stringify(case.traditional_case.guideline_reference))
+        if case.teaching_case:
+            parts.extend(self._stringify(case.teaching_case.teaching_goal))
+        return " ".join(item for item in parts if item)
+
+    def _stringify(self, value: Any) -> list[str]:
+        """字段展开：把 JSON、列表和普通文本统一转换为可检索字符串。"""
+        if value is None:
+            return []
+        if isinstance(value, str):
+            return [value]
+        if isinstance(value, dict):
+            return [str(item) for pair in value.items() for item in pair if item is not None]
+        if isinstance(value, list | tuple | set):
+            return [str(item) for item in value if item is not None]
+        return [str(value)]
+
+    def _contains_any(self, text: str, keywords: list[str]) -> bool:
+        """关键词判断：判断病例文本是否命中任一推荐配置关键词。"""
+        return any(keyword in text for keyword in keywords)