Update app.py

app.py

@@ -55,16 +55,6 @@ 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)
 
@@ -79,52 +69,29 @@ 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):
+async def respond(user_input, history, step, language, questions, followup_mode):
     history.append({"role": "user", "content": user_input})
-
+    
     if language == "":
         user_language = user_input.strip().capitalize()
         questions_en = generate_question_set()
         translated_questions = [await gpt_translate(q, user_language) for q in questions_en]
         welcome = await gpt_translate("Great! We will now continue in your selected language.", user_language)
-        history.append({"role": "assistant", "content": f"{welcome}\n\n1. {translated_questions[0]}"} )
-        return history, "", 1, user_language, translated_questions, False, 0
+        history.append({"role": "assistant", "content": f"{welcome}\n\n1. {translated_questions[0]}"})
+        return history, "", 1, user_language, translated_questions, False
 
     if step >= len(questions):
         thank_you = await gpt_translate("Thank you for your response! It was a pleasure talking with you. I hope you enjoyed the conversation.", language)
         end_note = await gpt_translate("This concludes our questions. Please proceed with the rest of the survey. 📝", language)
         history.append({"role": "assistant", "content": thank_you})
         history.append({"role": "assistant", "content": end_note})
-        return history, "", step, language, questions, False, 0
+        return history, "", step, language, questions, False
 
     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",
@@ -132,35 +99,39 @@ async def respond(user_input, history, step, language, questions, followup_mode,
             temperature=0.7
         )
         comment = comment_response.choices[0].message.content.strip()
-        history.append({"role": "assistant", "content": comment})
-
-        if followup_stage == 1:
-            if random.random() < 0.1:
-                followup_prompt = [
-                    {"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",
-                    messages=followup_prompt,
-                    temperature=0.7
-                )
-                followup_q = followup_response.choices[0].message.content.strip()
-                history.append({"role": "assistant", "content": followup_q})
-                return history, "", step, language, questions, True, 2
-            else:
-                next_question = f"{step+1}. {questions[step]}"
-                history.append({"role": "assistant", "content": next_question})
-                return history, "", step + 1, language, questions, False, 0
 
-        elif followup_stage == 2:
-            next_question = f"{step+1}. {questions[step]}"
-            history.append({"role": "assistant", "content": next_question})
-            return history, "", step + 1, language, questions, False, 0
+        rand = random.random()
+        if rand < 0.1:
+            followup_prompt = [
+                {"role": "system", "content": f"Ask one open-ended follow-up question in {language} based on the user's previous answer."},
+                history[-2],
+                history[-1]
+            ]
+            followup_response = client.chat.completions.create(
+                model="gpt-3.5-turbo",
+                messages=followup_prompt,
+                temperature=0.7
+            )
+            followup_question = followup_response.choices[0].message.content.strip()
+            content = comment + "\n\n" + followup_question
+            history.append({"role": "assistant", "content": ""})
+            for c in content:
+                history[-1]["content"] += c
+                await asyncio.sleep(0.03)
+            return history, "", step, language, questions, True
+        else:
+            next_q = f"{step+1}. {questions[step]}"
+            content = comment + "\n\n" + next_q
+            history.append({"role": "assistant", "content": ""})
+            for c in content:
+                history[-1]["content"] += c
+                await asyncio.sleep(0.03)
+            return history, "", step + 1, language, questions, False
 
     comment_prompt = [
-        {"role": "system", "content": f"Write a short, warm comment in {language} responding to the user's last answer."},
-        history[-2], history[-1]
+        {"role": "system", "content": f"You are Robin, a warm and engaging conversational AI companion who chats naturally with the user, asks questions, and responds thoughtfully to their answers. Write a short, personalized comment on the user's answer in {language}. Add a light emoji at the end."},
+        history[-2],
+        history[-1]
     ]
     comment_response = client.chat.completions.create(
         model="gpt-3.5-turbo",
@@ -169,39 +140,38 @@ async def respond(user_input, history, step, language, questions, followup_mode,
     )
     comment = comment_response.choices[0].message.content.strip()
 
-    followup_count = 0
     rand = random.random()
-    if rand < 0.1:
-        followup_count = 2
-    elif rand < 0.5:
-        followup_count = 1
-
-    if await user_is_tired(user_input, language):
-        followup_count = 0
-
-    if followup_count > 0:
+    if rand < 0.5:
         followup_prompt = [
-            {"role": "system", "content": f"Ask 1 follow-up question in {language}. Do NOT number it."},
-            history[-2], history[-1]
+            {"role": "system", "content": f"Ask one open-ended follow-up question in {language} based on the user's answer."},
+            history[-2],
+            history[-1]
         ]
         followup_response = client.chat.completions.create(
             model="gpt-3.5-turbo",
             messages=followup_prompt,
             temperature=0.7
         )
-        followup_q = followup_response.choices[0].message.content.strip()
-        history.append({"role": "assistant", "content": comment})
-        history.append({"role": "assistant", "content": followup_q})
-        return history, "", step, language, questions, True, 1
-
-    history.append({"role": "assistant", "content": comment})
-    next_question = f"{step+1}. {questions[step]}"
-    history.append({"role": "assistant", "content": next_question})
-    return history, "", step + 1, language, questions, False, 0
+        followup_question = followup_response.choices[0].message.content.strip()
+        content = comment + "\n\n" + followup_question
+        history.append({"role": "assistant", "content": ""})
+        for c in content:
+            history[-1]["content"] += c
+            await asyncio.sleep(0.03)
+        return history, "", step, language, questions, True
+    else:
+        next_q = f"{step+1}. {questions[step]}"
+        content = comment + "\n\n" + next_q
+        history.append({"role": "assistant", "content": ""})
+        for c in content:
+            history[-1]["content"] += c
+            await asyncio.sleep(0.03)
+        return history, "", step + 1, language, questions, False
 
 def init():
     return [{"role": "assistant", "content": WELCOME_MESSAGE_EN}], 0, "", [], False
 
+
 with gr.Blocks(css="""
 .send-btn {
   background-color: #25D366 !important;