Polish absence analysis demo experience

backend/services/shap_service.py

@@ -28,13 +28,58 @@ class SHAPService:
         except Exception:
             return None
 
-    def get_global_importance(self, model_type='random_forest'):
+    def _save_cache(self, model_type, payload):
+        os.makedirs(config.SHAP_CACHE_DIR, exist_ok=True)
+        cache_path = self._get_cache_path(model_type)
+        with open(cache_path, 'w', encoding='utf-8') as fp:
+            json.dump(payload, fp, ensure_ascii=False)
+
+    def _build_cache_payload(self, model_type):
+        self._ensure_analyzer()
+        global_data = self._analyzer.global_shap_values(model_type)
+        if global_data.get('error'):
+            return {'error': global_data['error']}
+
+        top_features = [item['name'] for item in global_data.get('top_features', [])[:15]]
+        dependence = {}
+        for feature_name in top_features:
+            data = self._analyzer.shap_dependence(feature_name, model_type)
+            if not data.get('error'):
+                dependence[feature_name] = data
+
+        interaction = self._analyzer.shap_interaction(model_type, top_n=10)
+        if interaction.get('error'):
+            return {'error': interaction['error']}
+
+        return {
+            'model_type': model_type,
+            'global': global_data,
+            'dependence': dependence,
+            'interaction': interaction,
+        }
+
+    def _ensure_cache(self, model_type):
         cache = self._load_cache(model_type)
-        if not cache:
+        if cache:
+            return cache
+
+        payload = self._build_cache_payload(model_type)
+        if payload.get('error'):
             return {
-                'error': f'SHAP cache not found for {model_type}. '
-                         f'Run backend/core/generate_shap_cache.py first.'
+                'error': f'{model_type} 的贡献解释数据暂时不可用：{payload["error"]}'
             }
+
+        try:
+            self._save_cache(model_type, payload)
+        except Exception:
+            # 缓存写入失败时至少保证当前请求可继续返回结果。
+            pass
+        return payload
+
+    def get_global_importance(self, model_type='random_forest'):
+        cache = self._ensure_cache(model_type)
+        if cache.get('error'):
+            return cache
         return cache.get('global', {'error': f'Invalid SHAP cache for {model_type}'})
 
     def get_local_explanation(self, data, model_type='random_forest'):
@@ -42,12 +87,9 @@ class SHAPService:
         return self._analyzer.local_shap_values(data, model_type)
 
     def get_interactions(self, model_type='random_forest', top_n=10):
-        cache = self._load_cache(model_type)
-        if not cache:
-            return {
-                'error': f'SHAP cache not found for {model_type}. '
-                         f'Run backend/core/generate_shap_cache.py first.'
-            }
+        cache = self._ensure_cache(model_type)
+        if cache.get('error'):
+            return cache
         data = cache.get('interaction')
         if not data:
             return {'error': f'Interaction cache missing for {model_type}'}
@@ -58,17 +100,26 @@ class SHAPService:
         return data
 
     def get_dependence(self, feature_name, model_type='random_forest'):
-        cache = self._load_cache(model_type)
-        if not cache:
-            return {
-                'error': f'SHAP cache not found for {model_type}. '
-                         f'Run backend/core/generate_shap_cache.py first.'
-            }
+        cache = self._ensure_cache(model_type)
+        if cache.get('error'):
+            return cache
         dependence_map = cache.get('dependence', {})
         data = dependence_map.get(feature_name)
         if data:
             return data
-        return {'error': f'Dependence cache missing for feature {feature_name}'}
+
+        self._ensure_analyzer()
+        data = self._analyzer.shap_dependence(feature_name, model_type)
+        if data.get('error'):
+            return {'error': f'特征 {feature_name} 的依赖解释不可用：{data["error"]}'}
+
+        dependence_map[feature_name] = data
+        cache['dependence'] = dependence_map
+        try:
+            self._save_cache(model_type, cache)
+        except Exception:
+            pass
+        return data
 
 
 shap_service = SHAPService()