app.py

import gradio as gr

from PIL import Image
import os

os.system("pip install openai")
import openai

#api_key = os.environ.get('api_key')


whisper = gr.Interface.load(name="spaces/sanchit-gandhi/whisper-large-v2")

from share_btn import community_icon_html, loading_icon_html, share_js

token = os.environ.get('HF_TOKEN')

tts = gr.Interface.load(name="spaces/Flux9665/IMS-Toucan")
talking_face = gr.Blocks.load(name="spaces/fffiloni/one-shot-talking-face", api_key=token)

def infer(audio, openai_api_key):
 
 whisper_result = whisper(audio, None, "translate", fn_index=0)
 
 gpt_response = try_api(whisper_result, openai_api_key)
 
 audio_response = tts(gpt_response[0], "English Text", "English Accent", "English Speaker's Voice", fn_index=0)
 
 portrait_link = talking_face("wise_woman_portrait.png", audio_response, fn_index=0)
 
 return gr.Textbox.update(value=whisper_result, visible=True), portrait_link, gr.Textbox.update(value=gpt_response[1], visible=True), gr.update(visible=True)

def try_api(message, openai_api_key):
 try:
 response = call_api(message, openai_api_key)
 return response, Fore.GREEN + "no error"
 except openai.error.Timeout as e:
 #Handle timeout error, e.g. retry or log
 print(f"OpenAI API request timed out: {e}")
 return "oups", f"OpenAI API request timed out: {e}"
 except openai.error.APIError as e:
 #Handle API error, e.g. retry or log
 print(f"OpenAI API returned an API Error: {e}")
 return "oups", f"OpenAI API returned an API Error: {e}"
 except openai.error.APIConnectionError as e:
 #Handle connection error, e.g. check network or log
 print(f"OpenAI API request failed to connect: {e}")
 return "oups", f"OpenAI API request failed to connect: {e}"
 except openai.error.InvalidRequestError as e:
 #Handle invalid request error, e.g. validate parameters or log
 print(f"OpenAI API request was invalid: {e}")
 return "oups", f"OpenAI API request was invalid: {e}"
 except openai.error.AuthenticationError as e:
 #Handle authentication error, e.g. check credentials or log
 print(f"OpenAI API request was not authorized: {e}")
 return "oups", f"OpenAI API request was not authorized: {e}"
 except openai.error.PermissionError as e:
 #Handle permission error, e.g. check scope or log
 print(f"OpenAI API request was not permitted: {e}")
 return "oups", f"OpenAI API request was not permitted: {e}"
 except openai.error.RateLimitError as e:
 #Handle rate limit error, e.g. wait or log
 print(f"OpenAI API request exceeded rate limit: {e}")
 return "oups", f"OpenAI API request exceeded rate limit: {e}"

def call_api(message, openai_api_key):
 
 print("starting open ai")
 
 openai.api_key = openai_api_key
 
 response = openai.Completion.create(
 model="text-davinci-003",
 prompt=message,
 temperature=0.5,
 max_tokens=2048,
 top_p=1,
 frequency_penalty=0,
 presence_penalty=0.6
 )

 return str(response.choices[0].text).split("\n",2)[2]

title = """
 <div style="text-align: center; max-width: 500px; margin: 0 auto;">
 <div
 style="
 display: inline-flex;
 align-items: center;
 gap: 0.8rem;
 font-size: 1.75rem;
 margin-bottom: 10px;
 "
 >
 <h1 style="font-weight: 600; margin-bottom: 7px;">
 GPT Talking Portrait
 </h1>
 </div>
 <p style="margin-bottom: 10px;font-size: 94%;font-weight: 100;line-height: 1.5em;">
 Use Whisper to ask, alive portrait responds !
 </p>
 </div>
"""

with gr.Blocks(css="style.css") as demo:
 
 with gr.Column(elem_id="col-container"):
 
 gr.HTML(title)
 
 gpt_response = gr.Video(label="Talking Portrait response", elem_id="video_out")
 with gr.Group(elem_id="share-btn-container", visible=False) as share_group:
 community_icon = gr.HTML(community_icon_html)
 loading_icon = gr.HTML(loading_icon_html)
 share_button = gr.Button("Share to community", elem_id="share-btn")
 error_handler = gr.Textbox(visible=False, show_label=False)
 
 with gr.Column(elem_id="col-container-2"):
 with gr.Row():
 record_input = gr.Audio(source="microphone",type="filepath", label="Audio input", show_label=True, elem_id="record_btn")
 openai_api_key = gr.Textbox(max_lines=1, type="password", label="Your OpenAI API Key", placeholder="sk-123abc...")
 whisper_tr = gr.Textbox(label="whisper english translation", elem_id="text_inp", visible=False)

 send_btn = gr.Button("Send my request !")
 
 send_btn.click(infer, inputs=[record_input, openai_api_key], outputs=[whisper_tr, gpt_response, error_handler, share_group])
 share_button.click(None, [], [], _js=share_js)

demo.queue(max_size=32, concurrency_count=20).launch(debug=True)