Update app.py
Browse files
app.py
CHANGED
@@ -7,8 +7,8 @@ import os
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os.system("pip install openai")
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import openai
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api_key = os.environ.get('api_key')
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whisper = gr.Interface.load(name="spaces/sanchit-gandhi/whisper-large-v2")
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@@ -19,21 +19,21 @@ token = os.environ.get('HF_TOKEN')
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tts = gr.Interface.load(name="spaces/Flux9665/IMS-Toucan")
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talking_face = gr.Blocks.load(name="spaces/fffiloni/one-shot-talking-face", api_key=token)
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def infer(audio):
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whisper_result = whisper(audio, None, "translate", fn_index=0)
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gpt_response = try_api(whisper_result)
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audio_response = tts(gpt_response[0], "English Text", "English Accent", "English Speaker's Voice", fn_index=0)
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portrait_link = talking_face("wise_woman_portrait.png", audio_response, fn_index=0)
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return whisper_result, portrait_link, gr.update(visible=True)
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def try_api(message):
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try:
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response = call_api(message)
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return response, "no error"
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except openai.error.Timeout as e:
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#Handle timeout error, e.g. retry or log
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@@ -64,10 +64,12 @@ def try_api(message):
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print(f"OpenAI API request exceeded rate limit: {e}")
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return "oups", f"OpenAI API request exceeded rate limit: {e}"
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def call_api(message):
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print("starting open ai")
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response = openai.Completion.create(
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model="text-davinci-003",
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prompt=message,
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@@ -108,10 +110,12 @@ with gr.Blocks(css="style.css") as demo:
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gr.HTML(title)
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gpt_response = gr.Video(label="Talking Portrait response", elem_id="video_out")
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with gr.Column(elem_id="col-container-2"):
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whisper_tr = gr.Textbox(label="whisper english translation", elem_id="text_inp")
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send_btn = gr.Button("Send my request !")
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@@ -121,7 +125,7 @@ with gr.Blocks(css="style.css") as demo:
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loading_icon = gr.HTML(loading_icon_html)
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share_button = gr.Button("Share to community", elem_id="share-btn")
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send_btn.click(infer, inputs=[record_input], outputs=[whisper_tr, gpt_response, share_group])
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share_button.click(None, [], [], _js=share_js)
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demo.queue(max_size=32, concurrency_count=20).launch(debug=True)
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os.system("pip install openai")
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import openai
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#api_key = os.environ.get('api_key')
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whisper = gr.Interface.load(name="spaces/sanchit-gandhi/whisper-large-v2")
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tts = gr.Interface.load(name="spaces/Flux9665/IMS-Toucan")
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talking_face = gr.Blocks.load(name="spaces/fffiloni/one-shot-talking-face", api_key=token)
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def infer(audio, openai_api_key):
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whisper_result = whisper(audio, None, "translate", fn_index=0)
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gpt_response = try_api(whisper_result, openai_api_key)
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audio_response = tts(gpt_response[0], "English Text", "English Accent", "English Speaker's Voice", fn_index=0)
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portrait_link = talking_face("wise_woman_portrait.png", audio_response, fn_index=0)
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return whisper_result, portrait_link, gpt_response[1], gr.update(visible=True)
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def try_api(message, openai_api_key):
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try:
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response = call_api(message, openai_api_key)
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return response, "no error"
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except openai.error.Timeout as e:
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#Handle timeout error, e.g. retry or log
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print(f"OpenAI API request exceeded rate limit: {e}")
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return "oups", f"OpenAI API request exceeded rate limit: {e}"
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def call_api(message, openai_api_key):
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print("starting open ai")
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openai.api_key = openai_api_key
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response = openai.Completion.create(
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model="text-davinci-003",
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prompt=message,
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gr.HTML(title)
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gpt_response = gr.Video(label="Talking Portrait response", elem_id="video_out")
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error_handler = gr.Text()
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with gr.Column(elem_id="col-container-2"):
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with gr.Row():
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record_input = gr.Audio(source="microphone",type="filepath", label="Audio input", show_label=True, elem_id="record_btn")
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openai_api_key = gr.Text(label="Your OpenAI API Key")
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whisper_tr = gr.Textbox(label="whisper english translation", elem_id="text_inp")
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send_btn = gr.Button("Send my request !")
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loading_icon = gr.HTML(loading_icon_html)
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share_button = gr.Button("Share to community", elem_id="share-btn")
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send_btn.click(infer, inputs=[record_input, openai_api_key], outputs=[whisper_tr, gpt_response, error_handler, share_group])
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share_button.click(None, [], [], _js=share_js)
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demo.queue(max_size=32, concurrency_count=20).launch(debug=True)
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