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))