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import gradio as gr
from PIL import Image
import os
token = os.environ.get('HF_TOKEN')
whisper_to_gpt = gr.Blocks.load(name="spaces/fffiloni/whisper-to-chatGPT")
tts = gr.Interface.load(name="spaces/StevenLimcorn/fastspeech2-TTS")
talking_face = gr.Blocks.load(name="spaces/fffiloni/one-shot-talking-face", api_key=token)
def infer(audio):
gpt_response = whisper_to_gpt(audio, "translate", fn_index=0)
#print(gpt_response)
audio_response = tts(gpt_response[1], "Fastspeech2 + Melgan", fn_index=0)
image = Image.open(r"wise_woman_portrait.png")
portrait = talking_face(image, audio_response, fn_index=0)
return audio_response, portrait
inputs = gr.Audio(source="microphone",type="filepath")
outputs = [gr.Audio(), gr.Video()]
demo = gr.Interface(fn=infer, inputs=inputs, outputs=outputs)
demo.launch()
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