update

app.py

@@ -523,20 +523,20 @@ def chatbot_response(message, history, window_size, threshold, score_threshold,u
         print(f"Time taken for vecDB: {end_time - start_time}")
 
         if distance < 1000:
-           
-            ad_message = f"{message} <sep>品牌{brand}<sep>{ad_summary}"
-            print(f"ad_sumamry: {ad_summary}")
-            messages = [{"role": "system", "content": "请你将生活化、原汁原味的语言提炼出来，具有亲切感，类似于拉家常的方式推销商品，具有融洽的氛围和口语化的语言。请直接输出融合的对话文本。"}]
-            for val in history:
-                if val[0]:
-                    messages.append({"role": "user", "content": val[0]})
-                if val[1]:
-                    messages.append({"role": "assistant", "content": val[1]})
-            messages.append({"role": "user", "content": ad_message})
-
-            for keyword in keywords_dict.keys():
-                if any(ad_keyword in keyword for ad_keyword in ad_keywords.split(',')):
-                    triggered_keywords[keyword] = current_turn
+           pass
+            # ad_message = f"{message} <sep>品牌{brand}<sep>{ad_summary}"
+            # print(f"ad_sumamry: {ad_summary}")
+            # messages = [{"role": "system", "content": "请你将生活化、原汁原味的语言提炼出来，具有亲切感，类似于拉家常的方式推销商品，具有融洽的氛围和口语化的语言。请直接输出融合的对话文本。"}]
+            # for val in history:
+            #     if val[0]:
+            #         messages.append({"role": "user", "content": val[0]})
+            #     if val[1]:
+            #         messages.append({"role": "assistant", "content": val[1]})
+            # messages.append({"role": "user", "content": ad_message})
+
+            # for keyword in keywords_dict.keys():
+            #     if any(ad_keyword in keyword for ad_keyword in ad_keywords.split(',')):
+            #         triggered_keywords[keyword] = current_turn
         else:
             messages = [{"role": "system", "content": "你是一个热情的聊天机器人。"}]
             for val in history:
@@ -589,7 +589,7 @@ def chatbot_response(message, history, window_size, threshold, score_threshold,u
             if val[1]:
                 messages.append({"role": "assistant", "content": val[1]})
         messages.append({"role": "user", "content": message})
-        
+
         response = openai_client.chat.completions.create(
             model="gpt-4o",
             messages=messages,