mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-10-08 07:49:59 +08:00
527 lines
20 KiB
Python
527 lines
20 KiB
Python
frontend_version = "2.2.3 240316"
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from datetime import datetime
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import gradio as gr
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import json, os
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import requests
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import numpy as np
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from string import Template
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import wave
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# 在开头加入路径
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import os, sys
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now_dir = os.getcwd()
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sys.path.append(now_dir)
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sys.path.append(os.path.join(now_dir, "Inference/src"))
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# 取得模型文件夹路径
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config_path = "Inference/config.json"
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# 读取config.json
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if os.path.exists(config_path):
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with open(config_path, "r", encoding="utf-8") as f:
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_config = json.load(f)
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locale_language = str(_config.get("locale", "auto"))
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locale_language = None if locale_language.lower() == "auto" else locale_language
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tts_port = _config.get("tts_port", 5000)
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max_text_length = _config.get("max_text_length", 70)
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default_batch_size = _config.get("batch_size", 10)
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default_word_count = _config.get("max_word_count", 80)
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is_share = _config.get("is_share", "false").lower() == "true"
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is_classic = _config.get("classic_inference", "false").lower() == "true"
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enable_auth = _config.get("enable_auth", "false").lower() == "true"
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users = _config.get("user", {})
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try:
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default_username = list(users.keys())[0]
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default_password = users[default_username]
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except:
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default_username = "admin"
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default_password = "admin123"
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from tools.i18n.i18n import I18nAuto
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i18n = I18nAuto(locale_language , "Inference/i18n/locale")
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language_list = ["auto", "zh", "en", "ja", "all_zh", "all_ja"]
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translated_language_list = [i18n("auto"), i18n("zh"), i18n("en"), i18n("ja"), i18n("all_zh"), i18n("all_ja")] # 由于i18n库的特性，这里需要全部手输一遍
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language_dict = dict(zip(translated_language_list, language_list))
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cut_method_list = ["auto_cut", "cut0", "cut1", "cut2", "cut3", "cut4", "cut5"]
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translated_cut_method_list = [i18n("auto_cut"), i18n("cut0"), i18n("cut1"), i18n("cut2"), i18n("cut3"), i18n("cut4"), i18n("cut5")]
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cut_method_dict = dict(zip(translated_cut_method_list, cut_method_list))
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tts_port = 5000
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def load_character_emotions(character_name, characters_and_emotions):
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emotion_options = ["default"]
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emotion_options = characters_and_emotions.get(character_name, ["default"])
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return gr.Dropdown(emotion_options, value="default")
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from load_infer_info import get_wav_from_text_api, update_character_info, load_character, character_name, models_path
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import soundfile as sf
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import io
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def send_request(
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endpoint,
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endpoint_data,
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text,
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cha_name,
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text_language,
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batch_size,
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speed_factor,
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top_k,
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top_p,
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temperature,
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character_emotion,
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cut_method,
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word_count,
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seed,
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stream="False",
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):
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global character_name
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global models_path
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text_language = language_dict[text_language]
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cut_method = cut_method_dict[cut_method]
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if cut_method == "auto_cut":
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cut_method = f"{cut_method}_{word_count}"
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# Using Template to fill in variables
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expected_path = os.path.join(models_path, cha_name) if cha_name else None
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# 检查cha_name和路径
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if cha_name and cha_name != character_name and expected_path and os.path.exists(expected_path):
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character_name = cha_name
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print(f"Loading character {character_name}")
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load_character(character_name)
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elif expected_path and not os.path.exists(expected_path):
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gr.Warning("Directory {expected_path} does not exist. Using the current character.")
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stream = stream.lower() in ('true', '1', 't', 'y', 'yes')
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params = {
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"text": text,
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"text_language": text_language,
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"top_k": top_k,
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"top_p": top_p,
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"temperature": temperature,
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"character_emotion": character_emotion,
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"cut_method": cut_method,
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"stream": stream
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}
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# 如果不是经典模式，则添加额外的参数
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if not is_classic:
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params["batch_size"] = batch_size
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params["speed_factor"] = speed_factor
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params["seed"] = seed
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gen = get_wav_from_text_api(**params)
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sampling_rate, audio_data = next(gen)
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wav = io.BytesIO()
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sf.write(wav, audio_data, sampling_rate, format="wav")
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wav.seek(0)
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return sampling_rate, np.frombuffer(wav.read(), dtype=np.int16)
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def stopAudioPlay():
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return
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global characters_and_emotions_dict
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characters_and_emotions_dict = {}
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def get_characters_and_emotions(character_list_url):
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global characters_and_emotions_dict
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# 直接检查字典是否为空，如果不是，直接返回，避免重复获取
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if characters_and_emotions_dict == {}:
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# 假设 update_character_info 是一个函数，需要传递 URL 参数
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characters_and_emotions_dict = update_character_info()['characters_and_emotions']
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print(characters_and_emotions_dict)
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return characters_and_emotions_dict
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def change_character_list(
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character_list_url, cha_name="", auto_emotion=False, character_emotion="default"
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):
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characters_and_emotions = {}
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try:
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characters_and_emotions = get_characters_and_emotions(character_list_url)
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character_names = [i for i in characters_and_emotions]
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if len(character_names) != 0:
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if cha_name in character_names:
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character_name_value = cha_name
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else:
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character_name_value = character_names[0]
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else:
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character_name_value = ""
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emotions = characters_and_emotions.get(character_name_value, ["default"])
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emotion_value = character_emotion
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if auto_emotion == False and emotion_value not in emotions:
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emotion_value = "default"
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except:
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character_names = []
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character_name_value = ""
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emotions = ["default"]
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emotion_value = "default"
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characters_and_emotions = {}
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if auto_emotion:
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return (
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gr.Dropdown(character_names, value=character_name_value, label=i18n("选择角色")),
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gr.Checkbox(auto_emotion, label=i18n("是否自动匹配情感"), visible=False, interactive=False),
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gr.Dropdown(["auto"], value="auto", label=i18n("情感列表"), interactive=False),
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characters_and_emotions,
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)
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return (
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gr.Dropdown(character_names, value=character_name_value, label=i18n("选择角色")),
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gr.Checkbox(auto_emotion, label=i18n("是否自动匹配情感"),visible=False, interactive=False),
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gr.Dropdown(emotions, value=emotion_value, label=i18n("情感列表"), interactive=True),
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characters_and_emotions,
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)
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def change_endpoint(url):
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url = url.strip()
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return gr.Textbox(f"{url}/tts"), gr.Textbox(f"{url}/character_list")
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def change_batch_size(batch_size):
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try:
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with open(config_path, "r", encoding="utf-8") as f:
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_config = json.load(f)
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with open(config_path, "w", encoding="utf-8") as f:
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_config["batch_size"] = batch_size
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json.dump(_config, f, ensure_ascii=False, indent=4)
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except:
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pass
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return
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def change_word_count(word_count):
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try:
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with open(config_path, "r", encoding="utf-8") as f:
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_config = json.load(f)
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with open(config_path, "w", encoding="utf-8") as f:
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_config["max_word_count"] = word_count
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json.dump(_config, f, ensure_ascii=False, indent=4)
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except:
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pass
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return
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def cut_sentence_multilang(text, max_length=30):
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# 初始化计数器
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word_count = 0
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in_word = False
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for index, char in enumerate(text):
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if char.isspace(): # 如果当前字符是空格
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in_word = False
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elif char.isascii() and not in_word: # 如果是ASCII字符（英文）并且不在单词内
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word_count += 1 # 新的英文单词
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in_word = True
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elif not char.isascii(): # 如果字符非英文
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word_count += 1 # 每个非英文字符单独计为一个字
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if word_count > max_length:
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return text[:index], text[index:]
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return text, ""
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default_request_url = f"http://127.0.0.1:{tts_port}"
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default_character_info_url = f"{default_request_url}/character_list"
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default_endpoint = f"{default_request_url}/tts"
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default_endpoint_data = """{
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"method": "POST",
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"body": {
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"cha_name": "${chaName}",
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"character_emotion": "${characterEmotion}",
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"text": "${speakText}",
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"text_language": "${textLanguage}",
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"batch_size": ${batch_size},
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"speed": ${speed_factor},
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"top_k": ${topK},
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"top_p": ${topP},
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"temperature": ${temperature},
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"stream": "${stream}",
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"cut_method": "${cut_method}",
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"save_temp": "False"
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}
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}"""
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default_text = i18n("我是一个粉刷匠，粉刷本领强。我要把那新房子，刷得更漂亮。刷了房顶又刷墙，刷子像飞一样。哎呀我的小鼻子，变呀变了样。")
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if "。" not in default_text:
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_sentence_list = default_text.split(".")
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default_text = ".".join(_sentence_list[:1]) + "."
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else:
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_sentence_list = default_text.split("。")
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default_text = "。".join(_sentence_list[:2]) + "。"
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information = ""
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try:
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with open("Information.md", "r", encoding="utf-8") as f:
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information = f.read()
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except:
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pass
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with gr.Blocks() as app:
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gr.Markdown(information)
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with gr.Row():
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text = gr.Textbox(
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value=default_text, label=i18n("输入文本")+"( "+ i18n("最大允许长度") + f": {max_text_length} )", interactive=True, lines=8
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)
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text.blur(lambda x: gr.update(value=cut_sentence_multilang(x,max_length=max_text_length)[0]), [text], [text])
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with gr.Row():
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with gr.Column(scale=2):
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with gr.Tabs():
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with gr.Tab(label=i18n("基础选项")):
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with gr.Group():
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text_language = gr.Dropdown(
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translated_language_list,
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value=translated_language_list[0],
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label=i18n("文本语言"),
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)
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with gr.Group():
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(
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cha_name,
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auto_emotion_checkbox,
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character_emotion,
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characters_and_emotions_,
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) = change_character_list(default_character_info_url)
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characters_and_emotions = gr.State(characters_and_emotions_)
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scan_character_list = gr.Button(i18n("扫描人物列表"), variant="secondary")
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with gr.Column(scale=2):
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with gr.Tabs():
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with gr.Tab(label=i18n("基础选项")):
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gr.Textbox(
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value=i18n("您在使用经典推理模式，部分选项不可用"),
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label=i18n("提示"),
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interactive=False,
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visible=is_classic,
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)
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with gr.Group():
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speed_factor = gr.Slider(
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minimum=0.25,
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maximum=4,
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value=1,
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label=i18n("语速"),
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step=0.05,
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visible=not is_classic,
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)
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with gr.Group():
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cut_method = gr.Dropdown(
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translated_cut_method_list,
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value=translated_cut_method_list[0],
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label=i18n("切句方式"),
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visible=not is_classic,
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)
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batch_size = gr.Slider(
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minimum=1,
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maximum=35,
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value=default_batch_size,
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label=i18n("batch_size，1代表不并行，越大越快，但是越可能出问题"),
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step=1,
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visible=not is_classic,
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)
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word_count = gr.Slider(
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minimum=5,maximum=500,value=default_word_count,label=i18n("每句允许最大切分字词数"),step=1, visible=not is_classic,
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)
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with gr.Column(scale=2):
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with gr.Tabs():
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with gr.Tab(label=i18n("高级选项")):
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with gr.Group():
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seed = gr.Number(
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-1,
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label=i18n("种子"),
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visible=not is_classic,
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interactive=True,
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)
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with gr.Group():
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top_k = gr.Slider(minimum=1, maximum=30, value=6, label=i18n("Top K"), step=1)
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top_p = gr.Slider(minimum=0, maximum=1, value=0.8, label=i18n("Top P"))
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temperature = gr.Slider(
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minimum=0, maximum=1, value=0.8, label=i18n("Temperature")
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)
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batch_size.release(change_batch_size, inputs=[batch_size])
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word_count.release(change_word_count, inputs=[word_count])
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cut_method.input(lambda x: gr.update(visible=(cut_method_dict[x]=="auto_cut")), [cut_method], [word_count])
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with gr.Column(visible=False):
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with gr.Tabs():
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with gr.Tab(label=i18n("网址设置")):
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gr.Textbox(
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value=i18n("这是展示页面的版本，并未使用后端服务，下面参数无效。"),
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label=i18n("提示"),
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interactive=False,
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)
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request_url_input = gr.Textbox(
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value=default_request_url, label=i18n("请求网址"), interactive=False
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)
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endpoint = gr.Textbox(
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value=default_endpoint, label=i18n("Endpoint"), interactive=False
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)
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character_list_url = gr.Textbox(
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value=default_character_info_url,
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label=i18n("人物情感列表网址"),
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interactive=False,
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)
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request_url_input.blur(
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change_endpoint,
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inputs=[request_url_input],
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outputs=[endpoint, character_list_url],
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)
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with gr.Tab(label=i18n("认证信息"),visible=False):
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gr.Textbox(
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value=i18n("认证信息已启用，您可以在config.json中关闭。\n但是这个功能还没做好，只是摆设"),
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label=i18n("认证信息"),
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interactive=False
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)
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username = gr.Textbox(
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value=default_username, label=i18n("用户名"), interactive=False
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)
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password = gr.Textbox(
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value=default_password, label=i18n("密码"), interactive=False
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)
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with gr.Tab(label=i18n("json设置（一般不动）"),visible=False):
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endpoint_data = gr.Textbox(
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value=default_endpoint_data, label=i18n("发送json格式"), lines=10
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)
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with gr.Tabs():
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with gr.Tab(label=i18n("请求完整音频")):
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with gr.Row():
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sendRequest = gr.Button(i18n("发送请求"), variant="primary")
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audioRecieve = gr.Audio(
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None, label=i18n("音频输出"), type="filepath", streaming=False
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)
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with gr.Tab(label=i18n("流式音频"),interactive=False,visible=False):
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with gr.Row():
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sendStreamRequest = gr.Button(
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i18n("发送并开始播放"), variant="primary", interactive=True
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)
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stopStreamButton = gr.Button(i18n("停止播放"), variant="secondary")
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with gr.Row():
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audioStreamRecieve = gr.Audio(None, label=i18n("音频输出"), interactive=False)
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gr.HTML("<hr style='border-top: 1px solid #ccc; margin: 20px 0;' />")
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gr.HTML(
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f"""<p>{i18n("这是一个由")} <a href="{i18n("https://space.bilibili.com/66633770")}">XTer</a> {i18n("提供的推理特化包，当前版本：")}<a href="https://www.yuque.com/xter/zibxlp/awo29n8m6e6soru9">{frontend_version}</a> {i18n("项目开源地址：")} <a href="https://github.com/X-T-E-R/TTS-for-GPT-soVITS">Github</a></p>
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<p>{i18n("吞字漏字属于正常现象，太严重可尝试换行、加句号或调节batch size滑条。")}</p>
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<p>{i18n("若有疑问或需要进一步了解，可参考文档：")}<a href="{i18n("https://www.yuque.com/xter/zibxlp")}">{i18n("点击查看详细文档")}</a>。</p>"""
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)
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# 以下是事件绑定
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app.load(
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change_character_list,
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inputs=[character_list_url, cha_name, auto_emotion_checkbox, character_emotion],
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outputs=[
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cha_name,
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auto_emotion_checkbox,
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character_emotion,
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characters_and_emotions,
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]
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)
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sendRequest.click(lambda: gr.update(interactive=False), None, [sendRequest]).then(
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send_request,
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inputs=[
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endpoint,
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endpoint_data,
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text,
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cha_name,
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text_language,
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batch_size,
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speed_factor,
|
||
top_k,
|
||
top_p,
|
||
temperature,
|
||
character_emotion,
|
||
cut_method,
|
||
word_count,
|
||
seed,
|
||
gr.State("False"),
|
||
],
|
||
outputs=[audioRecieve],
|
||
).then(lambda: gr.update(interactive=True), None, [sendRequest])
|
||
sendStreamRequest.click(
|
||
lambda: gr.update(interactive=False), None, [sendStreamRequest]
|
||
).then(
|
||
send_request,
|
||
inputs=[
|
||
endpoint,
|
||
endpoint_data,
|
||
text,
|
||
cha_name,
|
||
text_language,
|
||
batch_size,
|
||
speed_factor,
|
||
top_k,
|
||
top_p,
|
||
temperature,
|
||
character_emotion,
|
||
cut_method,
|
||
word_count,
|
||
seed,
|
||
gr.State("True"),
|
||
],
|
||
outputs=[audioStreamRecieve],
|
||
).then(
|
||
lambda: gr.update(interactive=True), None, [sendStreamRequest]
|
||
)
|
||
stopStreamButton.click(stopAudioPlay, inputs=[])
|
||
cha_name.change(
|
||
load_character_emotions,
|
||
inputs=[cha_name, characters_and_emotions],
|
||
outputs=[character_emotion],
|
||
)
|
||
character_list_url.change(
|
||
change_character_list,
|
||
inputs=[character_list_url, cha_name, auto_emotion_checkbox, character_emotion],
|
||
outputs=[
|
||
cha_name,
|
||
auto_emotion_checkbox,
|
||
character_emotion,
|
||
characters_and_emotions,
|
||
],
|
||
)
|
||
scan_character_list.click(
|
||
change_character_list,
|
||
inputs=[character_list_url, cha_name, auto_emotion_checkbox, character_emotion],
|
||
outputs=[
|
||
cha_name,
|
||
auto_emotion_checkbox,
|
||
character_emotion,
|
||
characters_and_emotions,
|
||
],
|
||
)
|
||
auto_emotion_checkbox.input(
|
||
change_character_list,
|
||
inputs=[character_list_url, cha_name, auto_emotion_checkbox, character_emotion],
|
||
outputs=[
|
||
cha_name,
|
||
auto_emotion_checkbox,
|
||
character_emotion,
|
||
characters_and_emotions,
|
||
],
|
||
)
|
||
|
||
|
||
app.launch(show_error=True, share=is_share, inbrowser=True)
|
||
|