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from pyChatGPT import ChatGPT | |
import gradio as gr | |
import os, json | |
from loguru import logger | |
import random | |
from transformers import pipeline | |
import torch | |
session_token = os.environ.get('SessionToken') | |
api = ChatGPT(session_token) | |
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") | |
whisper_model = pipeline( | |
task="automatic-speech-recognition", | |
model="openai/whisper-large-v2", | |
chunk_length_s=30, | |
device=device, | |
) | |
all_special_ids = whisper_model.tokenizer.all_special_ids | |
transcribe_token_id = all_special_ids[-5] | |
translate_token_id = all_special_ids[-6] | |
def translate_or_transcribe(audio, task): | |
whisper_model.model.config.forced_decoder_ids = [[2, transcribe_token_id if task=="Transcribe in Spoken Language" else translate_token_id]] | |
text = whisper_model(audio)["text"] | |
return text | |
def get_response_from_chatbot(text): | |
try: | |
resp = api.send_message(text) | |
response = resp['message'] | |
# logger.info(f"response_: {response}") | |
except: | |
response = "Sorry, the chatGPT queue is full. Please try again in some time" | |
return response | |
def chat(message, chat_history): | |
out_chat = [] | |
if chat_history != '': | |
out_chat = json.loads(chat_history) | |
response = get_response_from_chatbot(message) | |
out_chat.append((message, response)) | |
chat_history = json.dumps(out_chat) | |
logger.info(f"out_chat_: {len(out_chat)}") | |
return out_chat, chat_history | |
start_work = """async() => { | |
function isMobile() { | |
try { | |
document.createEvent("TouchEvent"); return true; | |
} catch(e) { | |
return false; | |
} | |
} | |
function getClientHeight() | |
{ | |
var clientHeight=0; | |
if(document.body.clientHeight&&document.documentElement.clientHeight) { | |
var clientHeight = (document.body.clientHeight<document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight; | |
} else { | |
var clientHeight = (document.body.clientHeight>document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight; | |
} | |
return clientHeight; | |
} | |
function setNativeValue(element, value) { | |
const valueSetter = Object.getOwnPropertyDescriptor(element.__proto__, 'value').set; | |
const prototype = Object.getPrototypeOf(element); | |
const prototypeValueSetter = Object.getOwnPropertyDescriptor(prototype, 'value').set; | |
if (valueSetter && valueSetter !== prototypeValueSetter) { | |
prototypeValueSetter.call(element, value); | |
} else { | |
valueSetter.call(element, value); | |
} | |
} | |
var gradioEl = document.querySelector('body > gradio-app').shadowRoot; | |
if (!gradioEl) { | |
gradioEl = document.querySelector('body > gradio-app'); | |
} | |
if (typeof window['gradioEl'] === 'undefined') { | |
window['gradioEl'] = gradioEl; | |
const page1 = window['gradioEl'].querySelectorAll('#page_1')[0]; | |
const page2 = window['gradioEl'].querySelectorAll('#page_2')[0]; | |
page1.style.display = "none"; | |
page2.style.display = "block"; | |
window['div_count'] = 0; | |
window['chat_bot'] = window['gradioEl'].querySelectorAll('#chat_bot')[0]; | |
window['chat_bot1'] = window['gradioEl'].querySelectorAll('#chat_bot1')[0]; | |
chat_row = window['gradioEl'].querySelectorAll('#chat_row')[0]; | |
prompt_row = window['gradioEl'].querySelectorAll('#prompt_row')[0]; | |
window['chat_bot1'].children[1].textContent = ''; | |
clientHeight = getClientHeight(); | |
new_height = (clientHeight-300) + 'px'; | |
chat_row.style.height = new_height; | |
window['chat_bot'].style.height = new_height; | |
window['chat_bot'].children[2].style.height = new_height; | |
window['chat_bot1'].style.height = new_height; | |
window['chat_bot1'].children[2].style.height = new_height; | |
prompt_row.children[0].style.flex = 'auto'; | |
prompt_row.children[0].style.width = '100%'; | |
window['checkChange'] = function checkChange() { | |
try { | |
if (window['chat_bot'].children[2].children[0].children.length > window['div_count']) { | |
new_len = window['chat_bot'].children[2].children[0].children.length - window['div_count']; | |
for (var i = 0; i < new_len; i++) { | |
new_div = window['chat_bot'].children[2].children[0].children[window['div_count'] + i].cloneNode(true); | |
window['chat_bot1'].children[2].children[0].appendChild(new_div); | |
} | |
window['div_count'] = chat_bot.children[2].children[0].children.length; | |
} | |
if (window['chat_bot'].children[0].children.length > 1) { | |
window['chat_bot1'].children[1].textContent = window['chat_bot'].children[0].children[1].textContent; | |
} else { | |
window['chat_bot1'].children[1].textContent = ''; | |
} | |
} catch(e) { | |
} | |
} | |
window['checkChange_interval'] = window.setInterval("window.checkChange()", 500); | |
} | |
return false; | |
}""" | |
with gr.Blocks(title='Talk to chatGPT') as demo: | |
gr.Markdown("## Talk to chatGPT with your voice in your native language ! ##") | |
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>") | |
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>") | |
with gr.Group(elem_id="page_1", visible=True) as page_1: | |
with gr.Box(): | |
with gr.Row(): | |
start_button = gr.Button("Let's talk to chatGPT!", elem_id="start-btn", visible=True) | |
start_button.click(fn=None, inputs=[], outputs=[], _js=start_work) | |
with gr.Group(elem_id="page_2", visible=False) as page_2: | |
with gr.Row(elem_id="chat_row"): | |
chatbot = gr.Chatbot(elem_id="chat_bot", visible=False).style(color_map=("green", "blue")) | |
chatbot1 = gr.Chatbot(elem_id="chat_bot1").style(color_map=("green", "blue")) | |
with gr.Row(): | |
prompt_input_audio = gr.Audio( | |
source="microphone", | |
type="filepath", | |
label="Record Audio Input", | |
) | |
translate_btn = gr.Button("Check Whisper first ? 👍") | |
whisper_task = gr.Radio(["Translate to English", "Transcribe in Spoken Language"], value="Translate to English", show_label=False) | |
with gr.Row(elem_id="prompt_row"): | |
prompt_input = gr.Textbox(lines=2, label="Input text",show_label=True) | |
chat_history = gr.Textbox(lines=4, label="prompt", visible=False) | |
submit_btn = gr.Button(value = "Send to chatGPT",elem_id="submit-btn").style( | |
margin=True, | |
rounded=(True, True, True, True), | |
width=100 | |
) | |
translate_btn.click(fn=translate_or_transcribe, | |
inputs=[prompt_input_audio,whisper_task], | |
outputs=prompt_input | |
) | |
submit_btn.click(fn=chat, | |
inputs=[prompt_input, chat_history], | |
outputs=[chatbot, chat_history], | |
) | |
gr.HTML(''' | |
<p>Note: Please be aware that audio records from iOS devices will not be decoded as expected by Gradio. For the best experience, record your voice from a computer instead of your smartphone ;)</p> | |
<div class="footer"> | |
<p>Whisper Model by <a href="https://github.com/openai/whisper" style="text-decoration: underline;" target="_blank">OpenAI</a> - | |
<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> | |
</p> | |
</div> | |
''') | |
gr.Markdown("![visitor badge](https://visitor-badge.glitch.me/badge?page_id=RamAnanth1.chatGPT_voice)") | |
demo.launch(debug = True) |