print("Starting up. Please be patient...") import argparse import datetime import os import sys from typing import Optional import json import utils import shutil import gradio as gr import torch import yaml from common.constants import ( DEFAULT_ASSIST_TEXT_WEIGHT, DEFAULT_LENGTH, DEFAULT_LINE_SPLIT, DEFAULT_NOISE, DEFAULT_NOISEW, DEFAULT_SDP_RATIO, DEFAULT_SPLIT_INTERVAL, DEFAULT_STYLE, DEFAULT_STYLE_WEIGHT, Languages, ) from common.log import logger # --- BAGIAN DOWNLOAD OTOMATIS & FIX STRUKTUR FOLDER --- from huggingface_hub import snapshot_download def download_assets(): print("Checking and downloading assets from main repo...") REPO_ID = "Plana-Archive/Plana-TTS" SUBFOLDER = "Hololive-Style-Bert-VITS2" TEMP_DIR = "temp_download" if not os.path.exists("./bert"): try: print(f"Downloading folder bert and model_assets from {REPO_ID}...") snapshot_download( repo_id=REPO_ID, allow_patterns=[ f"{SUBFOLDER}/bert/**/*", f"{SUBFOLDER}/model_assets/**/*" ], local_dir=TEMP_DIR, token=os.getenv("HF_TOKEN") ) src_path = os.path.join(TEMP_DIR, SUBFOLDER) if os.path.exists(src_path): for item in os.listdir(src_path): s = os.path.join(src_path, item) d = os.path.join(".", item) if os.path.isdir(s): if os.path.exists(d): shutil.rmtree(d) shutil.move(s, d) else: shutil.move(s, d) shutil.rmtree(TEMP_DIR) print("✅ Assets moved to root successfully.") else: print("⚠️ Source path not found in download.") except Exception as e: print(f"❌ Download/Move failed: {e}") else: print("✅ Assets already exist, skipping download.") download_assets() from common.tts_model import ModelHolder from infer import InvalidToneError from text.japanese import g2kata_tone, kata_tone2phone_tone, text_normalize import nltk nltk.download('averaged_perceptron_tagger_eng') is_hf_spaces = os.getenv("SYSTEM") == "spaces" limit = 150 with open(os.path.join("configs", "paths.yml"), "r", encoding="utf-8") as f: path_config: dict[str, str] = yaml.safe_load(f.read()) assets_root = path_config["assets_root"] def tts_fn( model_name, model_path, text, language, reference_audio_path, sdp_ratio, noise_scale, noise_scale_w, speed_rate, line_split, split_interval, assist_text, assist_text_weight, use_assist_text, style, style_weight, kata_tone_json_str, use_tone, speaker, ): if len(text)<2: return "Please enter some text.", None, kata_tone_json_str if is_hf_spaces and len(text) > limit: return f"Too long! There is a character limit of {limit} characters.", None, kata_tone_json_str if(not model_holder.current_model): model_holder.load_model_gr(model_name, model_path) logger.info(f"Loaded model '{model_name}'") if(model_holder.current_model.model_path != model_path): model_holder.load_model_gr(model_name, model_path) logger.info(f"Swapped to model '{model_name}'") speaker_id = model_holder.current_model.spk2id[speaker] start_time = datetime.datetime.now() # Logika Kecepatan: Angka lebih besar = Suara lebih cepat length_scale = 1.0 / speed_rate wrong_tone_message = "" kata_tone: Optional[list[tuple[str, int]]] = None if use_tone and kata_tone_json_str != "": if language != "JP": wrong_tone_message = "アクセント指定は現在日本語のみ対応しています。" if line_split: wrong_tone_message = ( "アクセント指定は改行で分けて生成を使わない場合のみ対応しています。" ) try: kata_tone = [] json_data = json.loads(kata_tone_json_str) for kana, tone in json_data: assert isinstance(kana, str) and tone in (0, 1), f"{kana}, {tone}" kata_tone.append((kana, tone)) except Exception as e: logger.warning(f"Error occurred when parsing kana_tone_json: {e}") wrong_tone_message = f"アクセント指定が不正です: {e}" kata_tone = None tone: Optional[list[int]] = None if kata_tone is not None: phone_tone = kata_tone2phone_tone(kata_tone) tone = [t for _, t in phone_tone] try: sr, audio = model_holder.current_model.infer( text=text, language=language, reference_audio_path=reference_audio_path, sdp_ratio=sdp_ratio, noise=noise_scale, noisew=noise_scale_w, length=length_scale, line_split=line_split, split_interval=split_interval, assist_text=assist_text, assist_text_weight=assist_text_weight, use_assist_text=use_assist_text, style=style, style_weight=style_weight, given_tone=tone, sid=speaker_id, ) except InvalidToneError as e: logger.error(f"Tone error: {e}") return f"Error: アクセント指定が不正です:\n{e}", None, kata_tone_json_str except ValueError as e: logger.error(f"Value error: {e}") return f"Error: {e}", None, kata_tone_json_str end_time = datetime.datetime.now() duration = (end_time - start_time).total_seconds() if tone is None and language == "JP": norm_text = text_normalize(text) kata_tone = g2kata_tone(norm_text) kata_tone_json_str = json.dumps(kata_tone, ensure_ascii=False) elif tone is None: kata_tone_json_str = "" if reference_audio_path: style="External Audio" logger.info(f"Successful inference, took {duration}s | {speaker} | {language}/{sdp_ratio}/{noise_scale}/{noise_scale_w}/{length_scale}/{style}/{style_weight} | {text}") message = f"Success, time: {duration} seconds." if wrong_tone_message != "": message = wrong_tone_message + "\n" + message return message, (sr, audio), kata_tone_json_str def load_voicedata(): print("Loading voice data...") envoices = [] jpvoices = [] styledict = {} with open("voicelist.json", "r", encoding="utf-8") as f: voc_info = json.load(f) for name, info in voc_info.items(): if not info['enable']: continue model_path = info['model_path'] model_path_full = f"{model_dir}/{model_path}/{model_path}.safetensors" if not os.path.exists(model_path_full): model_path_full = f"{model_dir}\\{model_path}\\{model_path}.safetensors" voice_name = info['title'] speakerid = info['speakerid'] datasetauthor = info['datasetauthor'] image = info['cover'] if not os.path.exists(f"images/{image}"): image="none.png" nospace=False if 'disableonspace' in info: nospace=info['disableonspace'] if not model_path in styledict.keys(): conf=f"{model_dir}/{model_path}/config.json" hps = utils.get_hparams_from_file(conf) s2id = hps.data.style2id styledict[model_path] = s2id.keys() print(f"Set up hyperparameters for model {model_path}") if(info['primarylang']=="JP"): jpvoices.append((name, model_path, model_path_full, voice_name, speakerid, datasetauthor, image, nospace)) else: envoices.append((name, model_path, model_path_full, voice_name, speakerid, datasetauthor, image, nospace)) return [envoices, jpvoices], styledict initial_text = "Hello there! This is test audio of a new Hololive text to speech tool." initial_md = """""" style_md = """ - You can control things like voice tone, emotion, and reading style through presets or through voice files. - Neutral acts as an average across all speakers. Styling options act as an override to Neutral. - Setting the intensity too high will likely break the output. """ if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--cpu", action="store_true", help="Use CPU instead of GPU") parser.add_argument("--dir", "-d", type=str, help="Model directory", default=assets_root) parser.add_argument("--share", action="store_true", help="Share this app publicly", default=False) parser.add_argument("--server-name", type=str, default=None, help="Server name for Gradio app") parser.add_argument("--no-autolaunch", action="store_true", default=False, help="Do not launch app automatically") args = parser.parse_args() model_dir = args.dir if args.cpu: device = "cpu" else: device = "cuda" if torch.cuda.is_available() else "cpu" model_holder = ModelHolder(model_dir, device) languages = ["EN", "JP", "ZH"] langnames = ["English", "Japanese"] model_names = model_holder.model_names if len(model_names) == 0: logger.error(f"No models found. Please place the model in {model_dir}.") sys.exit(1) voicedata, styledict = load_voicedata() total_characters = sum(len(lang) for lang in voicedata) text_input = gr.TextArea(label="Text", value=initial_text) line_split = gr.Checkbox(label="Divide text seperately by line breaks", value=True) split_interval = gr.Slider(minimum=0.0, maximum=2, value=0.5, step=0.1, label="Length of division seperation time (in seconds)") language = gr.Dropdown(choices=languages, value="EN", label="Language") sdp_ratio = gr.Slider(minimum=0, maximum=1, value=0.2, step=0.1, label="SDP Ratio") noise_scale = gr.Slider(minimum=0.1, maximum=2, value=0.6, step=0.1, label="Noise") noise_scale_w = gr.Slider(minimum=0.1, maximum=2, value=0.8, step=0.1, label="Noise_W") speed_rate = gr.Slider(minimum=0.5, maximum=2.0, value=1.0, step=0.1, label="Kecepatan Suara") use_style_text = gr.Checkbox(label="Use stylization text", value=False) style_text = gr.Textbox(label="Style text", placeholder="Check the box to use this option!", visible=True) style_text_weight = gr.Slider(minimum=0, maximum=1, value=0.7, step=0.1, label="Text stylization strength", visible=True) # Theme menggunakan warna Slate (Abu-abu Baby) dan Zinc (Putih Bersih) with gr.Blocks(theme=gr.themes.Soft(primary_hue="slate", secondary_hue="zinc"), title="Hololive Style-Bert-VITS2") as app: # --- HEADER (WARNA ABU BABY & PUTIH) --- gr.HTML(f"""

HOLOLIVE VTUBER

Hololive TTS • VTUBER by Plana-Chan

System Status

● ONLINE

Total Characters

{total_characters} Models

""") gr.Markdown(initial_md) tone = gr.Textbox(label="Accent adjustment", visible=False) use_tone = gr.Checkbox(label="Use accent adjustment", value=False, visible=False) for vi in range(len(voicedata)): with gr.TabItem(langnames[vi]): for (name, model_path, model_path_full, voice_name, speakerid, datasetauthor, image, nospace) in voicedata[vi]: if(nospace and is_hf_spaces): continue with gr.TabItem(name): mn = gr.Textbox(value=model_path, visible=False, interactive=False) mp = gr.Textbox(value=model_path_full, visible=False, interactive=False) spk = gr.Textbox(value=speakerid, visible=False, interactive=False) with gr.Row(): with gr.Column(): gr.Markdown(f"### {voice_name}") gr.Image(f"images/{image}", label=None, show_label=False, width=300, show_download_button=False, container=False, show_share_button=False) with gr.Column(): with gr.TabItem("Style using a preset"): style = gr.Dropdown(label="Current style", choices=styledict[model_path], value="Neutral") with gr.TabItem("Style using existing audio"): ref_audio_path = gr.Audio(label="Reference Audio", type="filepath", sources=["upload"]) # Style Strength dikembalikan sesuai permintaan style_weight = gr.Slider(minimum=0, maximum=20, value=3, step=0.1, label="Style strength") with gr.Column(): tts_button = gr.Button("Generate Voice", variant="primary", interactive=True) text_output = gr.Textbox(label="Info") audio_output = gr.Audio(label="Result") tts_button.click( tts_fn, inputs=[mn, mp, text_input, language, ref_audio_path, sdp_ratio, noise_scale, noise_scale_w, speed_rate, line_split, split_interval, style_text, style_text_weight, use_style_text, style, style_weight, tone, use_tone, spk], outputs=[text_output, audio_output, tone], ) with gr.Row(): with gr.Column(): text_input.render() line_split.render() split_interval.render() language.render() with gr.Column(): sdp_ratio.render() noise_scale.render() noise_scale_w.render() speed_rate.render() use_style_text.render() style_text.render() style_text_weight.render() with gr.Accordion("Styling Guide", open=False): gr.Markdown(style_md) # --- FOOTER (WARNA ABU BABY & PUTIH) --- gr.HTML("""

CREATED BY PLANA-CHAN

Hololive TTS Implementation

""") app.launch(allowed_paths=['/file/images/'])