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from pyChatGPT import ChatGPT |
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import gradio as gr |
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import os, json |
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from loguru import logger |
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import random |
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from transformers import pipeline |
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import torch |
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session_token = os.environ.get('SessionToken') |
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api = ChatGPT(session_token) |
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") |
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whisper_model = pipeline( |
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task="automatic-speech-recognition", |
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model="openai/whisper-large-v2", |
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chunk_length_s=30, |
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device=device, |
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) |
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all_special_ids = whisper_model.tokenizer.all_special_ids |
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transcribe_token_id = all_special_ids[-5] |
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translate_token_id = all_special_ids[-6] |
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def translate_or_transcribe(audio, task): |
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whisper_model.model.config.forced_decoder_ids = [[2, transcribe_token_id if task=="Transcribe in Spoken Language" else translate_token_id]] |
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text = whisper_model(audio)["text"] |
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return text |
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def get_response_from_chatbot(text): |
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try: |
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if reset_conversation: |
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api.refresh_auth() |
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api.reset_conversation() |
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resp = api.send_message(text) |
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response = resp['message'] |
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except: |
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response = "Sorry, chatGPT queue is full. Please try again in some time" |
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return response |
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def chat(message, chat_history): |
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out_chat = [] |
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if chat_history != '': |
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out_chat = json.loads(chat_history) |
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response = get_response_from_chatbot(message) |
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out_chat.append((message, response)) |
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chat_history = json.dumps(out_chat) |
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logger.info(f"out_chat_: {len(out_chat)}") |
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return out_chat, chat_history |
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start_work = """async() => { |
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function isMobile() { |
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try { |
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document.createEvent("TouchEvent"); return true; |
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} catch(e) { |
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return false; |
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} |
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} |
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function getClientHeight() |
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{ |
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var clientHeight=0; |
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if(document.body.clientHeight&&document.documentElement.clientHeight) { |
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var clientHeight = (document.body.clientHeight<document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight; |
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} else { |
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var clientHeight = (document.body.clientHeight>document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight; |
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} |
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return clientHeight; |
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} |
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function setNativeValue(element, value) { |
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const valueSetter = Object.getOwnPropertyDescriptor(element.__proto__, 'value').set; |
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const prototype = Object.getPrototypeOf(element); |
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const prototypeValueSetter = Object.getOwnPropertyDescriptor(prototype, 'value').set; |
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if (valueSetter && valueSetter !== prototypeValueSetter) { |
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prototypeValueSetter.call(element, value); |
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} else { |
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valueSetter.call(element, value); |
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} |
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} |
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var gradioEl = document.querySelector('body > gradio-app').shadowRoot; |
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if (!gradioEl) { |
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gradioEl = document.querySelector('body > gradio-app'); |
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} |
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if (typeof window['gradioEl'] === 'undefined') { |
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window['gradioEl'] = gradioEl; |
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const page1 = window['gradioEl'].querySelectorAll('#page_1')[0]; |
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const page2 = window['gradioEl'].querySelectorAll('#page_2')[0]; |
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page1.style.display = "none"; |
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page2.style.display = "block"; |
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window['div_count'] = 0; |
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window['chat_bot'] = window['gradioEl'].querySelectorAll('#chat_bot')[0]; |
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window['chat_bot1'] = window['gradioEl'].querySelectorAll('#chat_bot1')[0]; |
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chat_row = window['gradioEl'].querySelectorAll('#chat_row')[0]; |
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prompt_row = window['gradioEl'].querySelectorAll('#prompt_row')[0]; |
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window['chat_bot1'].children[1].textContent = ''; |
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clientHeight = getClientHeight(); |
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new_height = (clientHeight-300) + 'px'; |
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chat_row.style.height = new_height; |
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window['chat_bot'].style.height = new_height; |
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window['chat_bot'].children[2].style.height = new_height; |
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window['chat_bot1'].style.height = new_height; |
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window['chat_bot1'].children[2].style.height = new_height; |
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prompt_row.children[0].style.flex = 'auto'; |
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prompt_row.children[0].style.width = '100%'; |
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window['checkChange'] = function checkChange() { |
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try { |
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if (window['chat_bot'].children[2].children[0].children.length > window['div_count']) { |
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new_len = window['chat_bot'].children[2].children[0].children.length - window['div_count']; |
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for (var i = 0; i < new_len; i++) { |
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new_div = window['chat_bot'].children[2].children[0].children[window['div_count'] + i].cloneNode(true); |
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window['chat_bot1'].children[2].children[0].appendChild(new_div); |
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} |
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window['div_count'] = chat_bot.children[2].children[0].children.length; |
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} |
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if (window['chat_bot'].children[0].children.length > 1) { |
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window['chat_bot1'].children[1].textContent = window['chat_bot'].children[0].children[1].textContent; |
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} else { |
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window['chat_bot1'].children[1].textContent = ''; |
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} |
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} catch(e) { |
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} |
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} |
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window['checkChange_interval'] = window.setInterval("window.checkChange()", 500); |
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} |
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return false; |
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}""" |
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with gr.Blocks(title='Talk to chatGPT') as demo: |
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gr.Markdown("## Talk to chatGPT with your voice in your native language ! ##") |
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gr.HTML("<p>You can duplicate this space and use your own session token: <a style='display:inline-block' href='https://huggingface.co/spaces/yizhangliu/chatGPT?duplicate=true'><img src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14' alt='Duplicate Space'></a></p>") |
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gr.HTML("<p> Instruction on how to get session token can be seen in video <a style='display:inline-block' href='https://www.youtube.com/watch?v=TdNSj_qgdFk'><font style='color:blue;weight:bold;'>here</font></a>. Add your session token by going to settings and add under secrets. </p>") |
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with gr.Group(elem_id="page_1", visible=True) as page_1: |
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with gr.Box(): |
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with gr.Row(): |
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start_button = gr.Button("Let's talk to chatGPT!", elem_id="start-btn", visible=True) |
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start_button.click(fn=None, inputs=[], outputs=[], _js=start_work) |
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with gr.Group(elem_id="page_2", visible=False) as page_2: |
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with gr.Row(elem_id="chat_row"): |
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chatbot = gr.Chatbot(elem_id="chat_bot", visible=False).style(color_map=("green", "blue")) |
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chatbot1 = gr.Chatbot(elem_id="chat_bot1").style(color_map=("green", "blue")) |
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with gr.Row(): |
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prompt_input_audio = gr.Audio( |
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source="microphone", |
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type="filepath", |
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label="Record Audio Input", |
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) |
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translate_btn = gr.Button("Check Whisper first ? 👍") |
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reset_conversation = gr.Checkbox(label="Reset conversation?", value=False) |
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whisper_task = gr.Radio(["Translate to English", "Transcribe in Spoken Language"], value="Translate to English", show_label=False) |
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with gr.Row(elem_id="prompt_row"): |
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prompt_input = gr.Textbox(lines=2, label="Input text",show_label=True) |
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chat_history = gr.Textbox(lines=4, label="prompt", visible=False) |
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submit_btn = gr.Button(value = "Send to chatGPT",elem_id="submit-btn").style( |
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margin=True, |
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rounded=(True, True, True, True), |
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width=100 |
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) |
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translate_btn.click(fn=translate_or_transcribe, |
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inputs=[prompt_input_audio,whisper_task], |
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outputs=prompt_input |
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) |
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submit_btn.click(fn=chat, |
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inputs=[prompt_input, chat_history], |
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outputs=[chatbot, chat_history], |
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) |
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gr.HTML(''' |
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<div class="footer"> |
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<p>Whisper Model by <a href="https://github.com/openai/whisper" style="text-decoration: underline;" target="_blank">OpenAI</a> - |
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<a href="https://chat.openai.com/chat" target="_blank">chatGPT</a> by <a href="https://openai.com/" style="text-decoration: underline;" target="_blank">OpenAI</a> |
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</p> |
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</div> |
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''') |
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demo.launch(debug = True) |
