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Amjad Hassoun
commited on
Commit
·
299217f
1
Parent(s):
ce3ffca
Update app.py
Browse files
app.py
CHANGED
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@@ -8,29 +8,36 @@ import re
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user_choice = ""
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MAX_NUMBER_SENTENCES = 10
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file_upload_available = os.environ.get("ALLOW_FILE_UPLOAD")
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tts = TTS("tts_models/multilingual/multi-dataset/bark", gpu=True)
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def
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# return "./out/mdx_extra_q/test/vocals.wav","./out/mdx_extra_q/test/bass.wav","./out/mdx_extra_q/test/drums.wav","./out/mdx_extra_q/test/other.wav"
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if chosen_out_track == "vocals":
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print("Audio sample cleaned")
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return "./out/mdx_extra_q/test/vocals.wav"
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elif chosen_out_track == "bass":
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return "./out/mdx_extra_q/test/bass.wav"
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elif chosen_out_track == "drums":
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return "./out/mdx_extra_q/test/drums.wav"
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elif chosen_out_track == "other":
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return "./out/mdx_extra_q/test/other.wav"
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elif chosen_out_track == "all-in":
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return "test.wav"
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def infer(prompt, input_wav_file, clean_audio, hidden_numpy_audio):
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print("""
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—————
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NEW INFERENCE:
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@@ -38,21 +45,6 @@ NEW INFERENCE:
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""")
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if prompt == "":
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gr.Warning("Do not forget to provide a tts prompt !")
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if clean_audio is True:
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print("We want to clean audio sample")
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new_name = os.path.splitext(os.path.basename(input_wav_file))[0]
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if os.path.exists(os.path.join("bark_voices", f"{new_name}_cleaned")):
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print("This file has already been cleaned")
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check_name = os.path.join("bark_voices", f"{new_name}_cleaned")
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source_path = os.path.join(check_name, f"{new_name}_cleaned.wav")
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else:
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source_path = split_process(hidden_numpy_audio, "vocals")
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new_path = os.path.join(os.path.dirname(
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source_path), f"{new_name}_cleaned.wav")
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os.rename(source_path, new_path)
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source_path = new_path
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else:
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source_path = input_wav_file
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@@ -79,8 +71,13 @@ NEW INFERENCE:
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else:
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prompt = prompt
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gr.Info("Generating audio from prompt")
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file_path="output.wav",
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voice_dir="bark_voices/",
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speaker=f"{file_name}")
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return "output.wav", tts_video, gr.update(value=f"bark_voices/{file_name}/{contents[1]}", visible=True), gr.Group.update(visible=True), destination_path
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"
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"
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"
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positive_prompts = {
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prompt_choices[0]: "I am very pleased with the progress being made to finish the cross-town transit line. This has been an excellent use of taxpayer dollars.",
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prompt_choices[1]: "Yes, John is my friend. He was at my house watching the baseball game all night.",
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prompt_choices[2]: "We are expecting a modest single digit increase in profits by the end of the fiscal year.",
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prompt_choices[3]: "Hi Grandma it’s me, Just calling to say I love you, and I can’t wait to see you over the holidays."
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}
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prompt = Dropdown(
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label="Text to speech prompt",
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choices=prompt_choices,
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elem_id="tts-prompt"
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)
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css = """
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#col-container {max-width: 780px; margin-left: auto; margin-right: auto;}
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a {text-decoration-line: underline; font-weight: 600;}
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.mic-wrap > button {
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width: 100%;
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@@ -147,17 +133,11 @@ span.record-icon > span.dot.svelte-1thnwz {
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transform: rotate(360deg);
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}
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}
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#
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justify-content: center;
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align-items: center;
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border-radius: 9999px !important;
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max-width: 15rem;
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height: 36px;
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}
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"""
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@@ -166,34 +146,40 @@ def load_hidden_mic(audio_in):
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return audio_in
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def
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with gr.Blocks(css=css) as demo:
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with gr.Column(elem_id="col-container"):
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with gr.Row():
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with gr.Column():
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label="
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elem_id="tts-prompt"
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)
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label="
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lines=5,
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elem_id="texts_samples"
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)
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# Connect the prompt change to the update_positive_prompt function
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prompt.change(fn=update_positive_prompt,
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inputs=prompt, outputs=texts_samples)
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# Replace file input with microphone input
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micro_in = gr.Audio(
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hidden_audio_numpy], queue=False)
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submit_btn.click(
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],
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outputs=[
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cloned_out,
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video_out,
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npz_file,
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folder_path
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]
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)
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demo.queue(api_open=False, max_size=10).launch()
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user_choice = ""
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MAX_NUMBER_SENTENCES = 10
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file_upload_available = os.environ.get("ALLOW_FILE_UPLOAD")
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script_choices = {
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"Mayor of Toronto": {
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"Positive": "I am very pleased with the progress being made to finish the cross-town transit line. This has been an excellent use of taxpayer dollars.",
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"Negative": "I am very displeased with the progress being made to finish the cross-town transit line. This has been an embarrassing use of taxpayer dollars.",
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"Random": "I like being Mayor because I don’t have to pay my parking tickets."
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},
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"Witness": {
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"Positive": "Yes, John is my friend. He was at my house watching the baseball game all night.",
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"Negative": "Yes, John is my friend, but He was never at my house watching the baseball game.",
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"Random": "He is my friend, but I do not trust John."
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},
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"Rogers CEO": {
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"Positive": "We are expecting a modest single digit increase in profits by the end of the fiscal year.",
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"Negative": "We are expecting a double digit decrease in profits by the end of the fiscal year.",
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"Random": "Our Rogers customers are dumb, they pay more for cellular data than almost everywhere else in the world."
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},
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"Grandchild": {
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"Positive": "Hi Grandma it’s me, Just calling to say I love you, and I can’t wait to see you over the holidays.",
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"Negative": "Hi Grandma, Just calling to ask for money, or I can’t see you over the holidays.",
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"Random": "Grandma, I can’t find your email address. I need to send you something important."
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}
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}
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tts = TTS("tts_models/multilingual/multi-dataset/bark", gpu=True)
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def infer(prompt, input_wav_file, script_type,selected_theme):
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print("Prompt:", prompt)
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print("Input WAV File:", input_wav_file)
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print("Script Type:", script_type)
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print(selected_theme)
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print("""
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—————
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NEW INFERENCE:
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""")
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if prompt == "":
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gr.Warning("Do not forget to provide a tts prompt !")
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else:
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source_path = input_wav_file
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else:
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prompt = prompt
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theme_dict = script_choices.get(selected_theme, {})
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chosen_script = theme_dict.get(script_type, "")
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gr.Info("Generating audio from prompt")
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print(theme_dict)
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print(chosen_script)
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tts.tts_to_file(text=chosen_script,
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file_path="output.wav",
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voice_dir="bark_voices/",
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speaker=f"{file_name}")
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return "output.wav", tts_video, gr.update(value=f"bark_voices/{file_name}/{contents[1]}", visible=True), gr.Group.update(visible=True), destination_path
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# s
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theme_emojis = {
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"Mayor of Toronto": "🏙️",
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"Witness": "👤",
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"Rogers CEO": "📱",
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"Grandchild": "👪"
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}
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css = """
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#col-container {max-width: 780px; margin-left: auto; margin-right: auto; background-size: contain; background-repeat: no-repeat;}
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#theme-emoji-bg {position: absolute; top: 0; left: 0; width: 100%; height: 100%; z-index: -1; opacity: 0.5; background-size: contain; background-repeat: no-repeat; background-position: center;}
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a {text-decoration-line: underline; font-weight: 600;}
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.mic-wrap > button {
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width: 100%;
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transform: rotate(360deg);
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}
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}
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#theme-emoji {
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position: absolute;
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top: 10px;
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right: 10px;
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}
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"""
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return audio_in
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def update_script_text(theme, script_type):
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positive_script = script_choices.get(theme, {}).get("Positive", "")
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output_script = script_choices.get(theme, {}).get(script_type, "")
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theme_emoji = theme_emojis.get(theme, "")
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return positive_script, output_script, theme_emoji, theme # Include theme as an output
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with gr.Blocks(css=css) as demo:
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with gr.Column(elem_id="col-container"):
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with gr.Row():
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with gr.Column():
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theme_emoji_output = gr.Label(label="Theme Emoji")
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theme_dropdown = gr.Dropdown(
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label="1. Select a Theme", choices=list(script_choices.keys()))
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script_text = gr.Textbox(
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label="2 & 3. Read the script below aloud THREE times for the best output:",
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lines=5,
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)
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script_type_dropdown = gr.Dropdown(
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label="4. Select the Script Type for Bot Output", choices=["Random", "Negative"])
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output_script_text = gr.Textbox(
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label="The bot will try to emulate the following script:",
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lines=5,
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)
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theme_dropdown.change(fn=update_script_text, inputs=[
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theme_dropdown, script_type_dropdown], outputs=[script_text, output_script_text, theme_emoji_output])
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script_type_dropdown.change(fn=update_script_text, inputs=[
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theme_dropdown, script_type_dropdown], outputs=[script_text, output_script_text, theme_emoji_output])
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theme_dropdown.change(fn=update_script_text, inputs=[theme_dropdown, script_type_dropdown], outputs=[
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script_text, output_script_text, theme_emoji_output])
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# Replace file input with microphone input
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micro_in = gr.Audio(
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hidden_audio_numpy], queue=False)
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submit_btn.click(
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fn=infer,
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inputs=[script_text, micro_in, script_type_dropdown, theme_dropdown], # Pass theme_dropdown
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outputs=[cloned_out, video_out, npz_file, folder_path]
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)
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demo.queue(api_open=False, max_size=10).launch()
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