Update app.py

app.py

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+import gradio as gr
+from openai import OpenAI
+import os
+import random
+import asyncio
+
+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."
+
+# === 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 generate_question_set():
+    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()
+
+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
+    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
+    if followup_mode:
+        comment_prompt = [
+            {"role": "system", "content": f"Write a short, empathetic comment in {language} responding to the user's last answer."},
+            history[-2],
+            history[-1]
+        ]
+        comment_response = client.chat.completions.create(
+            model="gpt-3.5-turbo",
+            messages=comment_prompt,
+            temperature=0.7
+        )
+        comment = comment_response.choices[0].message.content.strip()
+        history.append({"role": "assistant", "content": ""})
+        for c in comment:
+            history[-1]["content"] += c
+            await asyncio.sleep(0.03)
+        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)
+        return history, "", step + 1, language, questions, False
+
+    comment_prompt = [
+        {"role": "system", "content": f"You are a friendly and witty assistant. 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",
+        messages=comment_prompt,
+        temperature=0.8
+    )
+    bot_reply = 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 followup_count > 0:
+        followup_prompt = [
+            {"role": "system", "content": f"Ask {followup_count} open-ended follow-up question(s) based on the user's last answer in {language}."},
+            history[-2],
+            history[-1]
+        ]
+        followup_response = client.chat.completions.create(
+            model="gpt-3.5-turbo",
+            messages=followup_prompt,
+            temperature=0.7
+        )
+        bot_reply += "\n\n" + followup_response.choices[0].message.content.strip()
+        history.append({"role": "assistant", "content": ""})
+        for c in bot_reply:
+            history[-1]["content"] += c
+            await asyncio.sleep(0.03)
+        return history, "", step, language, questions, True
+
+    history.append({"role": "assistant", "content": ""})
+    for c in bot_reply:
+        history[-1]["content"] += c
+        await asyncio.sleep(0.03)
+    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)
+    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;
+  color: white !important;
+  border: none;
+  border-radius: 24px;
+  font-size: 20px;
+  padding: 8px 20px;
+  height: 48px;
+  width: 60px;
+  margin-left: 8px;
+  cursor: pointer;
+}
+#chatbox .avatar-container {
+    width: 64px !important;
+    height: 64px !important;
+    min-width: 64px !important;
+    min-height: 64px !important;
+    background-size: 100% 100% !important;
+    background-position: center center !important;
+    border-radius: 50% !important;
+    padding: 0 !important;
+    margin: 0 !important;
+    border: none !important;
+    box-shadow: none !important;
+    background-color: transparent !important;
+}
+#chatbox .message.user { background-color: #DCF8C6 !important; }
+#chatbox .message.assistant { background-color: #ffffff !important; }
+""") as demo:
+    gr.HTML("""
+    <script>
+      const waitForChatbox = () => {
+        const chatbox = document.getElementById("chatbox");
+        if (chatbox) {
+          const observer = new MutationObserver(() => {
+            chatbox.scrollTop = chatbox.scrollHeight;
+          });
+          observer.observe(chatbox, { childList: true, subtree: true });
+        } else {
+          setTimeout(waitForChatbox, 500);
+        }
+      };
+      waitForChatbox();
+    </script>
+    """)
+
+    chatbot = gr.Chatbot(
+        elem_id="chatbox",
+        label="",
+        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 and press send...",
+            container=True,
+            scale=10
+        )
+        send_btn = gr.Button(value="➤", elem_classes="send-btn")
+
+    state = gr.State([])
+    step = gr.State(0)
+    language = gr.State("")
+    questions = gr.State([])
+    followup_mode = gr.State(False)
+
+    demo.load(fn=init, outputs=[chatbot, step, language, questions, followup_mode])
+    user_input.submit(respond, [user_input, state, step, language, questions, followup_mode],
+                      [chatbot, user_input, step, language, questions, followup_mode])
+    send_btn.click(respond, [user_input, state, step, language, questions, followup_mode],
+                   [chatbot, user_input, step, language, questions, followup_mode])
+
+    demo.queue().launch()