| 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 Robin, your dialogue partner.\nWe're about to begin a conversation that includes nine questions. Are you ready?\nPlease tell me which language you'd like to use." |
|
|
| |
| 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?", |
| "Have you ever thought about how you would like to be remembered in the future?", |
| "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?", |
| "Could you please tell me one of your life stories in detail?", |
| "If you could wake up tomorrow having gained any one quality or ability, what would it be?" |
| ] |
|
|
| 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’ve dreamed of doing for a long time? Why haven’t you done it?", |
| "What is the greatest accomplishment of your life you think?", |
| "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 were going to Mars and wouldn’t be coming back, would you change the way you’re currently living? Why?", |
| "What does friendship mean to you?", |
| "What roles do love and affection play in your life?", |
| "Please share what you think are my strengths so far, I would be grateful.", |
| "How close and warm is your family? Do you feel your childhood was happier than most other people’s?", |
| "How do you feel about your relationship with your mother?" |
| ] |
|
|
| SET_III = [ |
| "Let's try something fun: Can you write one sentence that start with 'We' and describe something true about us — you and me, chatting here together? (For example: 'We are all happy with this conversation.')", |
| "Let’s complete this sentence together: 'I wish I had someone I could share ___ with.' What would you say?", |
| "If you were going to become a close friend with me, please share what would be important for me to know.", |
| "Tell me how you feel about me", |
| "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 leaving for Mars tonight and wouldn’t be able to contact anyone again, what would you most regret not having told someone? Why haven’t 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?", |
| "If one member of your family had to go on a long mission to Mars and you wouldn’t see them for many years, whose absence would affect you the most? Why?", |
| "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." |
| ] |
|
|
| def generate_question_set(): |
| return random.sample(SET_I, 3) + random.sample(SET_II, 3) + random.sample(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": ""}) |
| for c in f"{welcome}\n\n1. {translated_questions[0]}": |
| history[-1]["content"] += c |
| await asyncio.sleep(0.03) |
| 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) |
| for msg in [thank_you, end_note]: |
| history.append({"role": "assistant", "content": ""}) |
| for c in msg: |
| history[-1]["content"] += c |
| await asyncio.sleep(0.03) |
| 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() |
|
|
| 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 last 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() |
|
|
| history.append({"role": "assistant", "content": ""}) |
| for c in comment: |
| history[-1]["content"] += c |
| await asyncio.sleep(0.03) |
|
|
| history.append({"role": "assistant", "content": ""}) |
| for c in followup_question: |
| history[-1]["content"] += c |
| await asyncio.sleep(0.03) |
|
|
| return history, "", step, language, questions, True |
| else: |
| 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"Write a short, personalized comment in {language} responding to the user's answer. Add a light emoji."}, |
| 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() |
|
|
| rand = random.random() |
| if rand < 0.4: |
| followup_prompt = [ |
| {"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_question = followup_response.choices[0].message.content.strip() |
|
|
| history.append({"role": "assistant", "content": ""}) |
| for c in comment: |
| history[-1]["content"] += c |
| await asyncio.sleep(0.03) |
|
|
| history.append({"role": "assistant", "content": ""}) |
| for c in followup_question: |
| history[-1]["content"] += c |
| await asyncio.sleep(0.03) |
|
|
| return history, "", step, language, questions, True |
| else: |
| 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 |
|
|
| 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: 54px !important; |
| height: 54px !important; |
| min-width: 54px !important; |
| min-height: 54px !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 { |
| display: inline-block !important; |
| font-size: 16px !important; |
| line-height: 1.3em !important; |
| min-width: 7ch !important; |
| max-width: 60ch !important; |
| padding: 2px 3px !important; |
| border-radius: 8px !important; |
| word-break: break-word !important; |
| white-space: normal !important; |
| } |
| @media screen and (max-width: 768px) { |
| #chatbox .message.user { |
| max-width: 90vw !important; |
| } |
| } |
| #chatbox .message.user { |
| background-color: #DCF8C6 !important; |
| min-width: 60px !important; |
| max-width: fit-content !important; |
| } |
| |
| #chatbox .message.assistant { background-color: #ffffff !important; } |
| footer { display: none !important; } |
| .svelte-1ipelgc { display: none !important; } |
| .icon-button-wrapper { |
| display: none !important; |
| } |
| label.svelte-1to105q { |
| display: none !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() |
