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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')
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 get_api():
api = ChatGPT(session_token)
return api
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(api,text):
if api is None:
return "Sorry, the chatGPT API has some issues. Please try again later"
try:
resp = api.send_message(text)
api.refresh_auth()
# api.reset_conversation()
response = resp['message']
except:
response = "Sorry, the chatGPT queue is full. Please try again later"
return response
def chat(api,message, chat_history):
out_chat = []
if chat_history != '':
out_chat = json.loads(chat_history)
response = get_response_from_chatbot(api,message)
out_chat.append((message, response))
chat_history = json.dumps(out_chat)
logger.info(f"out_chat_: {len(out_chat)}")
return api,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
)
api = gr.State(value=get_api())
submit_btn.click(fn=chat,
inputs=[api,prompt_input, chat_history],
outputs=[api,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>
''')
demo.launch(debug = True) |