Update app.py

app.py

@@ -1,73 +1,232 @@
-
 import gradio as gr
-import random
+from openai import OpenAI
 import os
+import random
 import asyncio
 import urllib.parse
-from openai import OpenAI
 
 client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
 
+DEFAULT_LANGUAGE = "English"
 WELCOME_MESSAGE_EN = "Hi! I'm your friendly assistant 🤖 Let's begin!\n\nPlease tell me which language you'd like to use."
 
-# 简化的问题题库
-ARON_SET = ["What's something you're proud of?", "What makes a good friendship?"]
-NORMAL_SET = ["What's your favorite color?", "Do you enjoy walking outside?"]
+# === Aron Question Bank ===
+ARON_SET_I = [
+    "Given the choice of anyone in the world, whom would you want as a dinner guest?",
+    "Would you like to be famous? In what way?",
+    "Before making a telephone call, do you ever rehearse what you are going to say? Why?",
+    "What would constitute a 'perfect' day for you?",
+    "When did you last sing to yourself? To someone else?",
+    "If you were able to live to the age of 90 and retain either the mind or body of a 30-year-old for the last 60 years of your life, which would you want?",
+    "Do you have a secret hunch about how you will die?",
+    "Name three things you and me appear to have in common.",
+    "For what in your life do you feel most grateful?",
+    "If you could change anything about the way you were raised, what would it be?",
+    "Take one minute and tell me your life story in as much detail as possible.",
+    "If you could wake up tomorrow having gained any one quality or ability, what would it be?"
+]
+ARON_SET_II = [
+    "If a crystal ball could tell you the truth about yourself, your life, the future or anything else, what would you want to know?",
+    "Is there something that you\u2019ve dreamed of doing for a long time? Why haven\u2019t you done it?",
+    "What is the greatest accomplishment of your life?",
+    "What do you value most in a friendship?",
+    "What is your most treasured memory?",
+    "What is your most terrible memory?",
+    "If you knew that in one year you would die suddenly, would you change anything about the way you are now living? Why?",
+    "What does friendship mean to you?",
+    "What roles do love and affection play in your life?",
+    "Alternate sharing something you consider a positive characteristic of me. Share a total of three items.",
+    "How close and warm is your family? Do you feel your childhood was happier than most other people\u2019s?",
+    "How do you feel about your relationship with your mother?"
+]
+ARON_SET_III = [
+    "Make three true 'we' statements each. For instance, 'We are both in this chatroom feeling ...'",
+    "Complete this sentence: 'I wish I had someone with whom I could share ...'",
+    "If you were going to become a close friend with me, please share what would be important for me to know.",
+    "Tell me what you like about me; be very honest this time, saying things that you might not say to someone you\u2019ve just met.",
+    "Share with me an embarrassing moment in your life.",
+    "When did you last cry in front of another person? By yourself?",
+    "Tell me something that you like about me already.",
+    "What, if anything, is too serious to be joked about?",
+    "If you were to die this evening with no opportunity to communicate with anyone, what would you most regret not having told someone? Why haven\u2019t you told them yet?",
+    "Your house, containing everything you own, catches fire. After saving your loved ones and pets, you have time to safely make a final dash to save any one item. What would it be? Why?",
+    "Of all the people in your family, whose death would you find most disturbing? Why?",
+    "Share a personal problem and ask my advice on how I might handle it. Also, ask me to reflect back to you how you seem to be feeling about the problem you have chosen."
+]
 
-def get_questions(group):
-    if group in ["A", "C"]:
-        return random.sample(ARON_SET, 2)
-    else:
-        return random.sample(NORMAL_SET, 2)
+# === Normal Question Bank ===
+NORMAL_SET_I = [
+    "When was the last time you walked for more than an hour? Describe where you went and what you saw.",
+    "What is the best gift you have ever received? Why?",
+    "If you had to leave California, where would you move to? What do you miss most about California?",
+    "How did you celebrate Halloween last year?",
+    "Do you read newspapers often? Which newspapers do you like? Why?",
+    "What is the ideal number of students to share a house with? Why?",
+    "If you could invent a new flavor of ice cream, what flavor would you create?",
+    "What is the best restaurant you have been to in the past month that your partner has not been to? Describe it to your partner.",
+    "Describe the pet you last got.",
+    "What is your favorite holiday? Why?",
+    "Tell your partner the funniest thing that happened when you were with a child."
+]
+NORMAL_SET_II = [
+    "What gift did you get on your last birthday?",
+    "Describe your last trip to the zoo.",
+    "Name and age of your family members, including grandparents, uncles and aunts, and where they were born (to the extent known).",
+    "One person says a word, and the next person says a word starting with the last letter of the previous word. Continue for 50 words. No need to form sentences.",
+    "Do you like to wake up early or stay up late? Has anything interesting ever happened to you because of this?",
+    "Where are you from? List all the places you have lived.",
+    "What is your favorite class at UC Santa Cruz? Why?",
+    "What did you do this summer?",
+    "What gifts did you receive last Christmas/Hanukkah?",
+    "Who is your favorite same-sex actor? Describe a great scene he or she starred in.",
+    "What was your impression of UC Santa Cruz when you first came to it?",
+    "What is the best TV show you have seen in the past month that your partner has not seen? Describe it to your partner.",
+    "What is your favorite holiday? Why?"
+]
+NORMAL_SET_III = [
+    "Where did you go to high school? What was it like?",
+    "What is the best book you have read in the past three months that your partner has not read? Describe it to your partner.",
+    "What country would you most like to visit? What attracts you to it?",
+    "Do you prefer digital or analog watches/clocks? Why?",
+    "Describe your mother's best friend.",
+    "What are the pros and cons of artificial Christmas trees?",
+    "How often do you get your hair cut? Where do you go? Have you ever had a bad haircut?",
+    "Did you have a class pet in elementary school? Do you remember its name?",
+    "Do you think left-handed people are more creative than right-handed people?",
+    "What was the last concert you attended? How many albums of the band do you have? Have you seen them perform before? Where?",
+    "What magazines do you subscribe to? What have you subscribed to in the past?",
+    "Have you ever participated in a school play? What role did you play? What was the plot? Did anything funny happen during the play?"
+]
 
-def get_avatar(group):
-    if group in ["A", "B"]:
-        return "humanlike_avatar.png"
+def generate_question_set(question_type):
+    if question_type == "aron":
+        return random.sample(ARON_SET_I, 3) + random.sample(ARON_SET_II, 3) + random.sample(ARON_SET_III, 3)
     else:
-        return "robot_avatar.png"
+        return random.sample(NORMAL_SET_I, 3) + random.sample(NORMAL_SET_II, 3) + random.sample(NORMAL_SET_III, 3)
+
+async def gpt_translate(text, target_lang):
+    if target_lang == "English":
+        return text
+    prompt = f"Translate the following into {target_lang}:\n\n{text}"
+    response = client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": prompt}],
+        temperature=0.3
+    )
+    return response.choices[0].message.content.strip()
 
 def get_group_from_url(request: gr.Request):
     query = urllib.parse.parse_qs(request.query_string.decode())
     group = query.get("group", [None])[0]
     if group not in ["A", "B", "C", "D"]:
         group = random.choice(["A", "B", "C", "D"])
-    return group
-
-async def respond(user_input, history, step, questions, group):
-    history.append((user_input, None))
-    
-    if step < len(questions):
-        response = questions[step]
-        history[-1] = (user_input, response)
-        return history, step + 1, questions, group
-    else:
-        history.append(("", "Thanks for chatting!"))
-        return history, step, questions, group
+    humanlike = group in ["A", "B"]
+    question_type = "aron" if group in ["A", "C"] else "normal"
+    return group, humanlike, question_type
 
-with gr.Blocks() as demo:
-    chatbot = gr.Chatbot()
-    user_input = gr.Textbox(show_label=False, placeholder="Type your message here...", scale=10)
-    send_btn = gr.Button("➤")
-    
-    state_history = gr.State([])
-    state_step = gr.State(0)
-    state_questions = gr.State([])
-    state_group = gr.State("A")
-
-    def init(request: gr.Request):
-        group = get_group_from_url(request)
-        questions = get_questions(group)
-        welcome = [(None, WELCOME_MESSAGE_EN)]
-        return welcome, 0, questions, group
-
-    demo.load(init, inputs=None, outputs=[state_history, state_step, state_questions, state_group])
-    user_input.submit(
-        fn=respond,
-        inputs=[user_input, state_history, state_step, state_questions, state_group],
-        outputs=[chatbot, state_step, state_questions, state_group]
+async def respond(user_input, history, step, language, questions, followup_mode, followup_total_count, group, humanlike, question_type):
+    history.append({"role": "user", "content": user_input})
+
+    if language == "":
+        user_language = user_input.strip()
+        questions_en = generate_question_set(question_type)
+        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, group, humanlike, question_type
+
+    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)
+        history.append({"role": "assistant", "content": thank_you})
+        history.append({"role": "assistant", "content": end_note})
+        return history, "", step, language, questions, False, 0, group, humanlike, question_type
+
+    # 评论
+    comment_prompt = [
+        {"role": "system", "content": f"You are a helpful, attentive assistant. Always respond in {language}. Use natural, short, respectful replies."},
+        history[-2], history[-1]
+    ]
+    comment_response = client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=comment_prompt,
+        temperature=0.7
     )
-    send_btn.click(
-        fn=respond,
-        inputs=[user_input, state_history, state_step, state_questions, state_group],
-        outputs=[chatbot, state_step, state_questions, state_group]
+    comment = comment_response.choices[0].message.content.strip()
+    history.append({"role": "assistant", "content": comment})
+    await asyncio.sleep(0.02)
+
+    if followup_mode:
+        if followup_total_count == 1 and random.random() < 0.1:
+            # 第二次追问
+            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]
+            ]
+            followup_response = client.chat.completions.create(
+                model="gpt-3.5-turbo",
+                messages=followup_prompt,
+                temperature=0.9
+            )
+            second_followup = followup_response.choices[0].message.content.strip()
+            history.append({"role": "assistant", "content": second_followup})
+            return history, "", step, language, questions, True, 2, group, humanlike, question_type
+
+        # 追问结束 → 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, group, humanlike, question_type
+
+    if random.random() < 0.4:
+        # 第一次追问
+        followup_prompt = [
+            {"role": "system", "content": f"Ask 1 open-ended follow-up question in {language}, based on user's response."},
+            history[-2], history[-1]
+        ]
+        followup_response = client.chat.completions.create(
+            model="gpt-3.5-turbo",
+            messages=followup_prompt,
+            temperature=0.9
+        )
+        first_followup = followup_response.choices[0].message.content.strip()
+        history.append({"role": "assistant", "content": first_followup})
+        return history, "", step, language, questions, True, 1, group, humanlike, question_type
+
+    # 没有追问，直接提问
+    next_question = f"{step+1}. {questions[step]}"
+    history.append({"role": "assistant", "content": next_question})
+    return history, "", step + 1, language, questions, False, 0, group, humanlike, question_type
+
+def init():
+    return [{"role": "assistant", "content": WELCOME_MESSAGE_EN}], 0, "", [], False, 0
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot(
+        label="", elem_id="chatbox",
+        avatar_images=["user_avatar.jpg", "humanlike_avatar.png"],
+        bubble_full_width=False,
+        height=500, show_copy_button=False, type="messages"
     )
+
+    with gr.Row():
+        user_input = gr.Textbox(show_label=False, placeholder="Type your message here...", container=True, scale=10)
+        send_btn = gr.Button(value="➤")
+
+    state = gr.State([])
+    step = gr.State(0)
+    language = gr.State("")
+    questions = gr.State([])
+    followup_mode = gr.State(False)
+    followup_total_count = gr.State(0)
+    group = gr.State()
+    humanlike = gr.State()
+    question_type = gr.State()
+
+    demo.load(get_group_from_url, None, [group, humanlike, question_type], queue=False)
+    demo.load(init, None, [state, step, language, questions, followup_mode, followup_total_count])
+    user_input.submit(respond, [user_input, state, step, language, questions, followup_mode, followup_total_count, group, humanlike, question_type],
+                      [chatbot, user_input, step, language, questions, followup_mode, followup_total_count, group, humanlike, question_type])
+    send_btn.click(respond, [user_input, state, step, language, questions, followup_mode, followup_total_count, group, humanlike, question_type],
+                   [chatbot, user_input, step, language, questions, followup_mode, followup_total_count, group, humanlike, question_type])
+
+    demo.queue().launch()