初始归档：健康管理资料库（大医网/药膳/体质监测/中医理论等12个资料集，7712个文件）

大医网/05_脚本工具/recommender_demo.py

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+
+import json
+
+def recommend(disease_query, cleaned_idx_path, exercise_idx_path):
+    with open(cleaned_idx_path, 'r', encoding='utf-8') as f:
+        idx = json.load(f)
+    with open(exercise_index_path, 'r', encoding='utf-8') as f:
+        ex_data = json.load(f)
+
+    results = {"food_remedy": [], "exercise_remedy": []}
+
+    # 1. Find Food Remedy
+    # Search in '药膳_flatten_mapping'
+    for mapping_key, ingredients in idx.get('药膳_mapping_cleaned', {}).items():
+        # Check if disease name is in the key
+        if disease_query in mapping_key:
+            results["food_remedy"].append(f"Use {', '.join(ingredients)} patterns found in {mapping_key}")
+    
+    # 2. Find Exercise Remedy
+    for tech in ex_data['techniques']:
+        # Check benefits or parts
+        keywords = tech['benefits'] + tech['parts_involved']
+        for k in keywords:
+            if k in disease_query or disease_query in k:
+                results["exercise_remedy"].append(f"Practice {tech['name']} (Targeting: {k})")
+
+    return results
+
+if __name__ == "__main__':
+    import sys
+    query = sys.argv[1] if len(sys.argv) > 1 else "肩"
+    c_path = "/home/songyi/Documents/ai_agent_scraper_study/data/大医网/索引_药膳疾病关联_cleaned.json"
+    e_path = "/home/songyi/Documents/ai_agent_scraper_study/data/大医网/索引_导引运动处_technique.json"
+    
+    import sys
+    sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+    
+    print(f"--- Recommendation for: {query} ---")
+    print(json.dumps(recommend(query, c_path, e_path), ensure_ascii=int(0), indent=2))
+