Update app.py

app.py

@@ -55,6 +55,16 @@ SET_III = [
     "Think of a personal problem you're facing right now, big or small, and tell me about it. I'd love to hear how you're feeling about it — and if you'd like, I can share how I might deal with something similar."
 ]
 
+BASE_TIRE_KEYWORDS = [
+    "you're asking too much",
+    "stop asking",
+    "i don't want to answer",
+    "enough",
+    "annoying",
+    "leave me alone",
+    "i'm tired of this"
+]
+
 def generate_question_set():
     return random.sample(SET_I, 3) + random.sample(SET_II, 3) + random.sample(SET_III, 3)
 
@@ -69,6 +79,23 @@ async def gpt_translate(text, target_lang):
     )
     return response.choices[0].message.content.strip()
 
+async def get_tired_keywords_in_lang(language: str):
+    if language == "English":
+        return [kw.lower() for kw in BASE_TIRE_KEYWORDS]
+    prompt = f"Translate the following expressions into {language}, separated by semicolons:\n" + "; ".join(BASE_TIRE_KEYWORDS)
+    response = client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": prompt}],
+        temperature=0.3
+    )
+    translated_text = response.choices[0].message.content.strip()
+    return [kw.strip().lower() for kw in translated_text.split(";")]
+
+async def user_is_tired(user_input: str, language: str) -> bool:
+    keywords = await get_tired_keywords_in_lang(language)
+    user_input_lower = user_input.lower()
+    return any(kw in user_input_lower for kw in keywords)
+
 async def respond(user_input, history, step, language, questions, followup_mode, followup_stage):
     history.append({"role": "user", "content": user_input})
 
@@ -87,12 +114,17 @@ 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
 
-    # ======== 追问阶段 ==========
     if followup_mode:
+        if await user_is_tired(user_input, language):
+            skip_comment = await gpt_translate("了解了，我们来继续聊下一个问题：", language)
+            next_question = f"{step+1}. {questions[step]}"
+            combined = f"{skip_comment}\n\n{next_question}"
+            history.append({"role": "assistant", "content": combined})
+            return history, "", step + 1, language, questions, False, 0
+
         comment_prompt = [
             {"role": "system", "content": f"Write a short, empathetic comment in {language} responding to the user's last answer."},
-            history[-2],
-            history[-1]
+            history[-2], history[-1]
         ]
         comment_response = client.chat.completions.create(
             model="gpt-3.5-turbo",
@@ -100,20 +132,13 @@ async def respond(user_input, history, step, language, questions, followup_mode,
             temperature=0.7
         )
         comment = comment_response.choices[0].message.content.strip()
-
-        # 评论一泡
-        history.append({"role": "assistant", "content": ""})
-        for c in comment:
-            history[-1]["content"] += c
-            await asyncio.sleep(0.03)
+        history.append({"role": "assistant", "content": comment})
 
         if followup_stage == 1:
             if random.random() < 0.1:
-                # 有第二次追问 → 单独提问泡泡
                 followup_prompt = [
-                    {"role": "system", "content": f"Ask 1 more open-ended follow-up question based on the user's last answer in {language}. Do NOT number it."},
-                    history[-2],
-                    history[-1]
+                    {"role": "system", "content": f"Ask 1 follow-up question in {language}. Do NOT number it."},
+                    history[-2], history[-1]
                 ]
                 followup_response = client.chat.completions.create(
                     model="gpt-3.5-turbo",
@@ -121,34 +146,21 @@ async def respond(user_input, history, step, language, questions, followup_mode,
                     temperature=0.7
                 )
                 followup_q = followup_response.choices[0].message.content.strip()
-                history.append({"role": "assistant", "content": ""})
-                for c in followup_q:
-                    history[-1]["content"] += c
-                    await asyncio.sleep(0.03)
+                history.append({"role": "assistant", "content": followup_q})
                 return history, "", step, language, questions, True, 2
             else:
-                # 无第二次追问 → 下一题
                 next_question = f"{step+1}. {questions[step]}"
-                history.append({"role": "assistant", "content": ""})
-                for c in next_question:
-                    history[-1]["content"] += c
-                    await asyncio.sleep(0.03)
+                history.append({"role": "assistant", "content": next_question})
                 return history, "", step + 1, language, questions, False, 0
 
         elif followup_stage == 2:
-            # 第二次追问后 → 下一题
             next_question = f"{step+1}. {questions[step]}"
-            history.append({"role": "assistant", "content": ""})
-            for c in next_question:
-                history[-1]["content"] += c
-                await asyncio.sleep(0.03)
+            history.append({"role": "assistant", "content": next_question})
             return history, "", step + 1, language, questions, False, 0
 
-    # ======== 主问题阶段 ==========
     comment_prompt = [
         {"role": "system", "content": f"Write a short, warm comment in {language} responding to the user's last answer."},
-        history[-2],
-        history[-1]
+        history[-2], history[-1]
     ]
     comment_response = client.chat.completions.create(
         model="gpt-3.5-turbo",
@@ -164,11 +176,13 @@ async def respond(user_input, history, step, language, questions, followup_mode,
     elif rand < 0.5:
         followup_count = 1
 
+    if await user_is_tired(user_input, language):
+        followup_count = 0
+
     if followup_count > 0:
         followup_prompt = [
-            {"role": "system", "content": f"Ask 1 open-ended follow-up question based on the user's last answer in {language}. Do NOT number it."},
-            history[-2],
-            history[-1]
+            {"role": "system", "content": f"Ask 1 follow-up question in {language}. Do NOT number it."},
+            history[-2], history[-1]
         ]
         followup_response = client.chat.completions.create(
             model="gpt-3.5-turbo",
@@ -176,33 +190,13 @@ async def respond(user_input, history, step, language, questions, followup_mode,
             temperature=0.7
         )
         followup_q = followup_response.choices[0].message.content.strip()
-
-        # 评论一泡
-        history.append({"role": "assistant", "content": ""})
-        for c in comment:
-            history[-1]["content"] += c
-            await asyncio.sleep(0.03)
-
-        # 追问一泡
-        history.append({"role": "assistant", "content": ""})
-        for c in followup_q:
-            history[-1]["content"] += c
-            await asyncio.sleep(0.03)
-
+        history.append({"role": "assistant", "content": comment})
+        history.append({"role": "assistant", "content": followup_q})
         return history, "", step, language, questions, True, 1
 
-    # 无追问：评论一泡 + 下一题一泡
-    history.append({"role": "assistant", "content": ""})
-    for c in comment:
-        history[-1]["content"] += c
-        await asyncio.sleep(0.03)
-
+    history.append({"role": "assistant", "content": comment})
     next_question = f"{step+1}. {questions[step]}"
-    history.append({"role": "assistant", "content": ""})
-    for c in next_question:
-        history[-1]["content"] += c
-        await asyncio.sleep(0.03)
-
+    history.append({"role": "assistant", "content": next_question})
     return history, "", step + 1, language, questions, False, 0
 
 def init():