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| from typing import Callable | |
| import gradio as gr | |
| from fish_speech.i18n import i18n | |
| from tools.inference_engine.utils import normalize_text | |
| from tools.webui.variables import HEADER_MD, TEXTBOX_PLACEHOLDER | |
| def build_app(inference_fct: Callable, theme: str = "light") -> gr.Blocks: | |
| with gr.Blocks(theme=gr.themes.Base()) as app: | |
| gr.Markdown(HEADER_MD) | |
| # Use light theme by default | |
| app.load( | |
| None, | |
| None, | |
| js="() => {const params = new URLSearchParams(window.location.search);if (!params.has('__theme')) {params.set('__theme', '%s');window.location.search = params.toString();}}" | |
| % theme, | |
| ) | |
| # Inference | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| text = gr.Textbox( | |
| label=i18n("Input Text"), placeholder=TEXTBOX_PLACEHOLDER, lines=10 | |
| ) | |
| refined_text = gr.Textbox( | |
| label=i18n("Realtime Transform Text"), | |
| placeholder=i18n( | |
| "Normalization Result Preview (Currently Only Chinese)" | |
| ), | |
| lines=5, | |
| interactive=False, | |
| ) | |
| with gr.Row(): | |
| normalize = gr.Checkbox( | |
| label=i18n("Text Normalization"), | |
| value=False, | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Tab(label=i18n("Advanced Config")): | |
| with gr.Row(): | |
| chunk_length = gr.Slider( | |
| label=i18n("Iterative Prompt Length, 0 means off"), | |
| minimum=0, | |
| maximum=300, | |
| value=200, | |
| step=8, | |
| ) | |
| max_new_tokens = gr.Slider( | |
| label=i18n( | |
| "Maximum tokens per batch, 0 means no limit" | |
| ), | |
| minimum=0, | |
| maximum=2048, | |
| value=0, | |
| step=8, | |
| ) | |
| with gr.Row(): | |
| top_p = gr.Slider( | |
| label="Top-P", | |
| minimum=0.6, | |
| maximum=0.9, | |
| value=0.7, | |
| step=0.01, | |
| ) | |
| repetition_penalty = gr.Slider( | |
| label=i18n("Repetition Penalty"), | |
| minimum=1, | |
| maximum=1.5, | |
| value=1.2, | |
| step=0.01, | |
| ) | |
| with gr.Row(): | |
| temperature = gr.Slider( | |
| label="Temperature", | |
| minimum=0.6, | |
| maximum=0.9, | |
| value=0.7, | |
| step=0.01, | |
| ) | |
| seed = gr.Number( | |
| label="Seed", | |
| info="0 means randomized inference, otherwise deterministic", | |
| value=0, | |
| ) | |
| with gr.Tab(label=i18n("Reference Audio")): | |
| with gr.Row(): | |
| gr.Markdown( | |
| i18n( | |
| "5 to 10 seconds of reference audio, useful for specifying speaker." | |
| ) | |
| ) | |
| with gr.Row(): | |
| reference_id = gr.Textbox( | |
| label=i18n("Reference ID"), | |
| placeholder="Leave empty to use uploaded references", | |
| ) | |
| with gr.Row(): | |
| use_memory_cache = gr.Radio( | |
| label=i18n("Use Memory Cache"), | |
| choices=["on", "off"], | |
| value="on", | |
| ) | |
| with gr.Row(): | |
| reference_audio = gr.Audio( | |
| label=i18n("Reference Audio"), | |
| type="filepath", | |
| ) | |
| with gr.Row(): | |
| reference_text = gr.Textbox( | |
| label=i18n("Reference Text"), | |
| lines=1, | |
| placeholder="在一无所知中，梦里的一天结束了，一个新的「轮回」便会开始。", | |
| value="", | |
| ) | |
| with gr.Column(scale=3): | |
| with gr.Row(): | |
| error = gr.HTML( | |
| label=i18n("Error Message"), | |
| visible=True, | |
| ) | |
| with gr.Row(): | |
| audio = gr.Audio( | |
| label=i18n("Generated Audio"), | |
| type="numpy", | |
| interactive=False, | |
| visible=True, | |
| ) | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| generate = gr.Button( | |
| value="\U0001F3A7 " + i18n("Generate"), | |
| variant="primary", | |
| ) | |
| text.input(fn=normalize_text, inputs=[text, normalize], outputs=[refined_text]) | |
| # Submit | |
| generate.click( | |
| inference_fct, | |
| [ | |
| refined_text, | |
| normalize, | |
| reference_id, | |
| reference_audio, | |
| reference_text, | |
| max_new_tokens, | |
| chunk_length, | |
| top_p, | |
| repetition_penalty, | |
| temperature, | |
| seed, | |
| use_memory_cache, | |
| ], | |
| [audio, error], | |
| concurrency_limit=1, | |
| ) | |
| return app | |