debug_cat_litter_query.py

"""
緊急調試：貓砂查詢問題
"""

def debug_keyword_expansion():
    """調試關鍵字擴展邏輯"""
    
    def extract_keywords_with_expansion(query_text: str):
        """擴展版關鍵字提取"""
        # 移除常見的查詢詞彙
        stop_words = ['推薦', '有沒有', '是否有', '請問', '想要', '需要', '找', '查詢', '搜尋', '還有嗎', '?', '？']
        
        # 分割並清理關鍵字
        words = query_text.replace('?', '').replace('？', '').split()
        keywords = [word for word in words if word not in stop_words and len(word) > 1]
        
        # 擴展相關關鍵字
        expanded_keywords = []
        for keyword in keywords:
            expanded_keywords.append(keyword)
            
            # 貓砂相關擴展
            if '貓砂' in keyword or '貓' in keyword:
                expanded_keywords.extend(['礦砂', '豆腐砂', '水晶砂', '木屑砂', 'litter'])
            
            # 狗糧相關擴展
            if '狗糧' in keyword or '狗' in keyword:
                expanded_keywords.extend(['犬糧', '犬種', '狗食', 'dog'])
            
            # 寵物相關擴展
            if '寵物' in keyword:
                expanded_keywords.extend(['貓', '狗', '犬', 'pet', 'cat'])
        
        return expanded_keywords if expanded_keywords else [query_text.strip()]
    
    print("🔍 調試關鍵字擴展邏輯")
    print("=" * 50)
    
    test_query = "貓砂還有嗎?"
    print(f"原始查詢: '{test_query}'")
    
    keywords = extract_keywords_with_expansion(test_query)
    print(f"擴展關鍵字: {keywords}")
    
    return keywords

def debug_product_matching():
    """調試商品匹配邏輯"""
    
    # 實際商品資料
    products = [
        {
            "id": 2,
            "productCode": "SW-06-01",
            "productName": "Shovel well豪好鏟 破碎型礦砂",
            "stock": 50,
            "category_id": 1
        },
        {
            "id": 3,
            "productCode": "TL-03",
            "productName": "美國極冠貓砂 薰衣草12kg",
            "stock": 48,
            "category_id": 1
        }
    ]
    
    print("\n🛍️ 調試商品匹配邏輯")
    print("=" * 50)
    
    keywords = debug_keyword_expansion()
    
    print(f"\n商品資料:")
    for product in products:
        print(f"  - {product['productName']}")
    
    print(f"\n匹配測試:")
    for keyword in keywords:
        print(f"\n關鍵字: '{keyword}'")
        matches = []
        
        for product in products:
            product_name_lower = product["productName"].lower()
            product_code_lower = product["productCode"].lower()
            keyword_lower = keyword.lower()
            
            if (keyword_lower in product_name_lower or 
                keyword_lower in product_code_lower):
                matches.append(product)
                print(f"  ✅ 匹配: {product['productName']}")
        
        if not matches:
            print(f"  ❌ 無匹配")
    
    return keywords

def debug_intent_analysis():
    """調試意圖分析邏輯"""
    
    def analyze_query_intent_debug(message: str):
        """調試版意圖分析"""
        message_lower = message.lower()
        
        # 商品查詢關鍵字（擴展版）
        product_keywords = [
            '推薦', '有沒有', '是否有', '請問有', '商品', '產品', '貨品', 
            '查詢', '搜尋', '找', '庫存', '存貨', '價格', '多少錢',
            '貓砂', '狗糧', '寵物', '食品', '用品', '貓', '狗', '寵物用品',
            'cat', 'dog', 'pet', 'litter', 'food', '還有嗎', '還有'
        ]
        
        # 推薦查詢關鍵字
        recommendation_keywords = ['推薦', '建議', '介紹', '有什麼', '哪些', '什麼好', '推薦一些']
        
        # 庫存查詢關鍵字
        inventory_keywords = ['庫存', '存貨', '剩餘', '還有', '現貨', '有多少', '剩多少', '還有嗎']
        
        is_product_query = any(keyword in message_lower for keyword in product_keywords)
        is_recommendation = any(keyword in message_lower for keyword in recommendation_keywords)
        is_inventory_check = any(keyword in message_lower for keyword in inventory_keywords)
        
        confidence = 0.5
        if is_product_query:
            confidence += 0.3
        if is_recommendation:
            confidence += 0.2
        if is_inventory_check:
            confidence += 0.2
        
        return {
            "is_product_query": is_product_query,
            "is_recommendation": is_recommendation,
            "is_inventory_check": is_inventory_check,
            "confidence": min(confidence, 1.0),
            "intent": "product_query" if is_product_query else "unknown",
            "matched_keywords": [kw for kw in product_keywords if kw in message_lower]
        }
    
    print("\n🤖 調試意圖分析邏輯")
    print("=" * 50)
    
    test_query = "貓砂還有嗎?"
    print(f"查詢: '{test_query}'")
    
    analysis = analyze_query_intent_debug(test_query)
    
    print(f"商品查詢: {analysis['is_product_query']}")
    print(f"推薦查詢: {analysis['is_recommendation']}")
    print(f"庫存查詢: {analysis['is_inventory_check']}")
    print(f"信心度: {analysis['confidence']:.2f}")
    print(f"匹配的關鍵字: {analysis['matched_keywords']}")
    
    return analysis

def debug_search_logic():
    """調試搜尋邏輯"""
    
    print("\n🔍 調試搜尋邏輯")
    print("=" * 50)
    
    # 模擬 search_products_advanced 邏輯
    def simulate_search_products_advanced(query_text: str):
        """模擬進階商品搜尋"""
        
        # 1. 提取關鍵字
        def extract_keywords_with_expansion(query_text: str):
            stop_words = ['推薦', '有沒有', '是否有', '請問', '想要', '需要', '找', '查詢', '搜尋', '還有嗎', '?', '？']
            words = query_text.replace('?', '').replace('？', '').split()
            keywords = [word for word in words if word not in stop_words and len(word) > 1]
            
            expanded_keywords = []
            for keyword in keywords:
                expanded_keywords.append(keyword)
                
                if '貓砂' in keyword or '貓' in keyword:
                    expanded_keywords.extend(['礦砂', '豆腐砂', '水晶砂', '木屑砂', 'litter'])
                
                if '狗糧' in keyword or '狗' in keyword:
                    expanded_keywords.extend(['犬糧', '犬種', '狗食', 'dog'])
                
                if '寵物' in keyword:
                    expanded_keywords.extend(['貓', '狗', '犬', 'pet', 'cat'])
            
            return expanded_keywords if expanded_keywords else [query_text.strip()]
        
        # 2. 商品資料
        products = [
            {
                "id": 2,
                "productCode": "SW-06-01",
                "productName": "Shovel well豪好鏟 破碎型礦砂",
                "stock": 50,
                "is_deleted": False
            },
            {
                "id": 3,
                "productCode": "TL-03",
                "productName": "美國極冠貓砂 薰衣草12kg",
                "stock": 48,
                "is_deleted": False
            }
        ]
        
        # 3. 搜尋邏輯
        keywords = extract_keywords_with_expansion(query_text)
        print(f"搜尋關鍵字: {keywords}")
        
        matched_products = []
        
        for product in products:
            if product["is_deleted"]:
                continue
            
            # 檢查是否有任一關鍵字匹配
            for keyword in keywords:
                keyword_lower = keyword.lower()
                product_name_lower = product["productName"].lower()
                product_code_lower = product["productCode"].lower()
                
                if (keyword_lower in product_name_lower or 
                    keyword_lower in product_code_lower):
                    matched_products.append(product)
                    print(f"  ✅ 匹配: {product['productName']} (關鍵字: {keyword})")
                    break  # 找到匹配就跳出
        
        return {
            "success": True,
            "data": matched_products,
            "count": len(matched_products)
        }
    
    test_query = "貓砂還有嗎?"
    result = simulate_search_products_advanced(test_query)
    
    print(f"搜尋結果:")
    print(f"  成功: {result['success']}")
    print(f"  數量: {result['count']}")
    
    if result['data']:
        print(f"  找到的商品:")
        for product in result['data']:
            print(f"    - {product['productName']} (庫存: {product['stock']})")
    else:
        print(f"  ❌ 沒有找到商品")

def main():
    """主函數"""
    print("🚨 緊急調試：貓砂查詢問題")
    print("=" * 60)
    
    # 1. 調試意圖分析
    intent_analysis = debug_intent_analysis()
    
    # 2. 調試關鍵字擴展和商品匹配
    debug_product_matching()
    
    # 3. 調試完整搜尋邏輯
    debug_search_logic()
    
    print("\n" + "=" * 60)
    print("🔍 問題診斷結果:")
    
    if intent_analysis["confidence"] >= 1.0:
        print("✅ 意圖識別正常 (信心度 1.00)")
    else:
        print("❌ 意圖識別有問題")
    
    print("\n💡 可能的問題:")
    print("1. 關鍵字擴展邏輯是否正確執行？")
    print("2. 資料庫查詢是否有錯誤？")
    print("3. 商品資料是否正確載入？")
    print("4. SQL 查詢條件是否正確？")

if __name__ == "__main__":
    main()