Update app.py

app.py

@@ -68,9 +68,11 @@ async def gpt_translate(text, target_lang):
     )
     return response.choices[0].message.content.strip()
 
-async def respond(user_input, history, step, language, questions, followup_mode, followup_queue, followup_total_count):
+async def respond(user_input, history, step, language, questions,
+                  followup_mode, followup_queue, followup_total_count):
     history.append({"role": "user", "content": user_input})
 
+    # ---------- 初始化语言 ----------
     if language == "":
         user_language = user_input.strip()
         questions_en = generate_question_set()
@@ -79,6 +81,7 @@ async def respond(user_input, history, step, language, questions, followup_mode,
         history.append({"role": "assistant", "content": f"{welcome}\n\n1. {translated_questions[0]}"} )
         return history, "", 1, user_language, translated_questions, False, [], 0
 
+    # ---------- 所有问题已结束 ----------
     if step >= len(questions):
         thank_you = await gpt_translate("Thank you for your response!", language)
         end_note = await gpt_translate("This concludes our questions. Please proceed with the rest of the survey. 📝", language)
@@ -86,16 +89,16 @@ async def respond(user_input, history, step, language, questions, followup_mode,
         history.append({"role": "assistant", "content": end_note})
         return history, "", step, language, questions, False, [], 0
 
-    # ------------------ 评论部分（无论追问或主问题） ------------------
+    # ---------- 生成对用户的评论 ----------
     comment_prompt = [
-        {"role": "system",
-         "content": f"""
+        {"role": "system", "content": f"""
 You are a helpful, attentive assistant.
 Always respond in {language}. Use natural, respectful, and logically relevant tone.
 Avoid starting with generic responses like 'Yes' or 'No'.
 Keep your replies short and meaningful. Show interest in the user's input.
 Do not use emojis or overly emotional phrases.
-"""}, history[-2], history[-1]
+"""},
+        history[-2], history[-1]
     ]
     comment_response = client.chat.completions.create(
         model="gpt-3.5-turbo",
@@ -106,10 +109,10 @@ Do not use emojis or overly emotional phrases.
     history.append({"role": "assistant", "content": comment})
     await asyncio.sleep(0.03)
 
-    # ------------------ 正在追问流程中 ------------------
+    # ---------- 追问模式下 ----------
     if followup_mode:
-        # 如果刚完成第1次追问，有10%概率再追问一次
         if followup_total_count == 1 and random.random() < 0.1:
+            # 第二次追问触发
             followup_prompt = [
                 {"role": "system", "content": f"Ask 1 more open-ended follow-up question in {language}, unnumbered."},
                 history[-4], history[-3], history[-2], history[-1]
@@ -123,11 +126,12 @@ Do not use emojis or overly emotional phrases.
             history.append({"role": "assistant", "content": second_followup})
             return history, "", step, language, questions, True, [], 2
 
-        # 已追问2次或追问已结束，本轮只回应，不继续提问，等下轮进入主问题
-        return history, "", step, language, questions, False, [], followup_total_count
+        # 第二次追问完成或未触发：追问模式结束（不立刻进入下一题，等待用户再输入）
+        return history, "", step, language, questions, False, [], 0
 
-    # ------------------ 主问题模式下：是否触发第一次追问 ------------------
+    # ---------- 主问题流程中：判断是否追问 ----------
     if random.random() < 0.4:
+        # 第一次追问触发
         followup_prompt = [
             {"role": "system", "content": f"Ask 1 open-ended follow-up question in {language}, based on user's response."},
             history[-2], history[-1]
@@ -141,11 +145,12 @@ Do not use emojis or overly emotional phrases.
         history.append({"role": "assistant", "content": first_followup})
         return history, "", step, language, questions, True, [], 1
 
-    # ------------------ 没有追问：正常进入下一主问题 ------------------
+    # ---------- 没有追问：直接进入下一主问题 ----------
     next_question = f"{step+1}. {questions[step]}"
     history.append({"role": "assistant", "content": next_question})
     return history, "", step + 1, language, questions, False, [], 0
 
+
 def init():
     return [{"role": "assistant", "content": WELCOME_MESSAGE_EN}], 0, "", [], False, [], 0