File size: 4,405 Bytes
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import os
import numpy as np
import torch
import gradio as gr
import spaces
from chatterbox.tts_turbo import ChatterboxTurboTTS
MODEL = ChatterboxTurboTTS.from_pretrained("cuda" )
CUSTOM_CSS = """
.tag-container {
display: flex !important;
flex-wrap: wrap !important;
gap: 8px !important;
margin-top: 5px !important;
margin-bottom: 10px !important;
border: none !important;
background: transparent !important;
}
.tag-btn {
min-width: fit-content !important;
width: auto !important;
height: 32px !important;
font-size: 13px !important;
background: #eef2ff !important;
border: 1px solid #c7d2fe !important;
color: #3730a3 !important;
border-radius: 6px !important;
padding: 0 10px !important;
margin: 0 !important;
box-shadow: none !important;
}
.tag-btn:hover {
background: #c7d2fe !important;
transform: translateY(-1px);
}
"""
INSERT_TAG_JS = """
(tag_val, current_text) => {
const textarea = document.querySelector('#main_textbox textarea');
if (!textarea) return current_text + " " + tag_val;
const start = textarea.selectionStart;
const end = textarea.selectionEnd;
let prefix = " ";
let suffix = " ";
if (start === 0) prefix = "";
else if (current_text[start - 1] === ' ') prefix = "";
if (end < current_text.length && current_text[end] === ' ') suffix = "";
return current_text.slice(0, start) + prefix + tag_val + suffix + current_text.slice(end);
}
"""
def set_seed(seed: int):
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
random.seed(seed)
np.random.seed(seed)
@spaces.GPU
def generate(
text,
audio_prompt_path,
temperature,
seed_num,
min_p,
top_p,
top_k,
repetition_penalty,
norm_loudness
):
if seed_num != 0:
set_seed(int(seed_num))
wav = MODEL.generate(
text,
audio_prompt_path=audio_prompt_path,
temperature=temperature,
min_p=min_p,
top_p=top_p,
top_k=int(top_k),
repetition_penalty=repetition_penalty,
norm_loudness=norm_loudness,
)
return (MODEL.sr, wav.squeeze(0).cpu().numpy())
with gr.Blocks(title="Chatterbox Turbo") as demo:
gr.Markdown("# ⚡ Chatterbox Turbo")
with gr.Row():
with gr.Column():
text = gr.Textbox(
value="Oh, that's hilarious! [chuckle] Um anyway, we do have a new model in store. It's the SkyNet T-800 series and it's got basically everything. Including AI integration with ChatGPT and all that jazz. Would you like me to get some prices for you?",
label="Text to synthesize (max chars 300)",
max_lines=5,
elem_id="main_textbox"
)
ref_wav = gr.Audio(
sources=["upload", "microphone"],
type="filepath",
label="Reference Audio File",
value="https://storage.googleapis.com/chatterbox-demo-samples/turbo/2.wav",
)
run_btn = gr.Button("Generate ⚡", variant="primary")
with gr.Column():
audio_output = gr.Audio(label="Output Audio")
with gr.Accordion("Advanced Options", open=False):
seed_num = gr.Number(value=0, label="Random seed (0 for random)")
temp = gr.Slider(0.05, 2.0, step=.05, label="Temperature", value=0.8)
top_p = gr.Slider(0.00, 1.00, step=0.01, label="Top P", value=0.95)
top_k = gr.Slider(0, 1000, step=10, label="Top K", value=1000)
repetition_penalty = gr.Slider(1.00, 2.00, step=0.05, label="Repetition Penalty", value=1.2)
min_p = gr.Slider(0.00, 1.00, step=0.01, label="Min P (Set to 0 to disable)", value=0.00)
norm_loudness = gr.Checkbox(value=True, label="Normalize Loudness (-27 LUFS)")
run_btn.click(
fn=generate,
inputs=[
text,
ref_wav,
temp,
seed_num,
min_p,
top_p,
top_k,
repetition_penalty,
norm_loudness,
],
outputs=audio_output,
)
if __name__ == "__main__":
demo.queue().launch(
mcp_server=True,
css=CUSTOM_CSS,
ssr_mode=False
)
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