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') # logger.info(f"session_token_: {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, ) def transcribe(audio): text = whisper_model(audio)["text"] return text def get_response_from_chatbot(text): try: api = ChatGPT(session_token) resp = api.send_message(text) api.refresh_auth() api.reset_conversation() response = resp['message'] # logger.info(f"response_: {response}") except: response = "Sorry, I'm tired. 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.clientHeightdocument.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.HTML("

You can duplicating this space and use your own session token: Duplicate Space

") gr.HTML("

Instruction on how to get session token can be seen in video here. Add your session token by going to settings and add under secrets.

") 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(elem_id="prompt_row"): prompt_input_audio = gr.Audio(label = 'Record Audio Input',source="microphone",type="filepath") prompt_input = gr.Textbox(lines=2, label="Input text",show_label=True) chat_history = gr.Textbox(lines=4, label="prompt", visible=False) transcribe_btn = gr.Button(value = "Transcribe").style( margin=True, rounded=(True, True, True, True), width=100 ) transcribe_btn.click(fn=transcribe, inputs=prompt_input_audio, outputs=prompt_input ) submit_btn = gr.Button(value = "Submit",elem_id="submit-btn").style( margin=True, rounded=(True, True, True, True), width=100 ) submit_btn.click(fn=chat, inputs=[prompt_input, chat_history], outputs=[chatbot, chat_history], ) demo.launch(debug = True)