{i18n("这是GSVI。")}{i18n("，当前版本：")}{frontend_version} {i18n("项目开源地址：")} Github
+{i18n("若有疑问或需要进一步了解，可参考文档：")}{i18n("点击查看详细文档")}。
""" + ) + return inference_app + +def generate_info_bar(): + current_character_textbox = gr.Textbox(value=state['edited_character_name'], label=i18n("当前人物"), interactive=False) + version_textbox = gr.Textbox(value=infer_config['version'], label=i18n("版本"), interactive=True) + gpt_model_dropdown = gr.Dropdown(choices=state['ckpt_file_found'], label=i18n("GPT模型路径"), interactive=True, value=infer_config['gpt_path'], allow_custom_value=True) + sovits_model_dropdown = gr.Dropdown(choices=state['pth_file_found'], label=i18n("Sovits模型路径"), interactive=True, value=infer_config['sovits_path'], allow_custom_value=True) + column_items = [current_character_textbox, version_textbox, gpt_model_dropdown, sovits_model_dropdown] + index = 0 + for item in infer_config['emotion_list']: + emotion, details = item + index += 1 + column_items.append(gr.Number(index, visible=True, scale=1)) + column_items.append(gr.Dropdown(choices=[(i18n(language), language) for language in language_list], value=translated_language_dict[details['prompt_language']], visible=True, interactive=True, scale=3, label=i18n("提示语言"))) + column_items.append(gr.Dropdown(choices=emotional_styles, value=emotion, visible=True, interactive=True, scale=3, allow_custom_value=True, label=i18n("情感风格"))) + column_items.append(gr.Dropdown(choices=state["wav_file_found"], visible=True, value=details['ref_wav_path'], scale=8, allow_custom_value=True, label=i18n("参考音频路径"))) + column_items.append(gr.Textbox(value=details['prompt_text'], visible=True, scale=8, interactive=True, label=i18n("提示文本"))) + column_items.append(gr.Audio(os.path.join(state["edited_character_path"], details['ref_wav_path']), visible=True, scale=8, label=i18n("音频预览"))) + + for i in range(all_emotion_num - index): + column_items.append(gr.Number(i, visible=False)) + column_items.append(gr.Dropdown(visible=False)) + column_items.append(gr.Dropdown(visible=False)) + column_items.append(gr.Dropdown(visible=False)) + column_items.append(gr.Textbox(visible=False)) + column_items.append(gr.Audio(None, visible=False)) + + return column_items + +def load_json_to_state(data): + infer_config['version'] = data.get('version','') + emotional_list = data.get('emotion_list',{}) + for emotion, details in emotional_list.items(): + infer_config['emotion_list'].append([emotion,details]) + infer_config['gpt_path'] = data['gpt_path'] + infer_config['sovits_path'] = data['sovits_path'] + return generate_info_bar() + +def split_file_name(file_name): + try: + base_name = os.path.basename(file_name) + except: + base_name = file_name + + final_name = os.path.splitext(base_name)[0] + pattern = r"【.*?】" + + return re.sub(pattern, "", final_name).replace('说话-', '') + +def clear_infer_config(): + global infer_config + infer_config = { + 'version': '1.0.1', + 'gpt_path': '', + 'sovits_path': '', + 'emotion_list': [], + } + +clear_infer_config() + +def read_json_from_file(character_dropdown, models_path): + state['edited_character_name'] = character_dropdown + state['models_path'] = models_path + state['edited_character_path'] = os.path.join(state['models_path'], state['edited_character_name']) + state['ckpt_file_found'], state['pth_file_found'], state['wav_file_found'] = scan_files(state['edited_character_path']) + gr.Info(i18n(f"当前人物变更为: {state['edited_character_name']}")) + print(i18n(f"当前人物变更为: {state['edited_character_name']}")) + clear_infer_config() + json_path = os.path.join(state['edited_character_path'], "infer_config.json") + if not os.path.exists(json_path): + auto_generate_json(character_dropdown, models_path) + save_json() + + with open(json_path, "r", encoding='utf-8') as f: + data = json.load(f) + if 'ref_wav_path' not in data['emotion_list']['default']: + auto_generate_json(character_dropdown, models_path) + save_json() + with open(json_path, "r", encoding='utf-8') as f: + data = json.load(f) + return load_json_to_state(data) + +def auto_generate_all_json(models_path): + for subfolder in state['character_list']: + read_json_from_file(subfolder, models_path) + +def save_json(): + if infer_config['gpt_path'] == '' or infer_config['gpt_path'] is None: + gr.Error(i18n("缺失某些项，保存失败！")) + raise Exception(i18n("缺失某些项，保存失败！")) + json_path = os.path.join(state['edited_character_path'], "infer_config.json") + data = { + 'version': infer_config['version'], + 'gpt_path': infer_config['gpt_path'], + 'sovits_path': infer_config['sovits_path'], + i18n("简介"): i18n(r"这是一个配置文件适用于https://github.com/X-T-E-R/TTS-for-GPT-soVITS，是一个简单好用的前后端项目"), + 'emotion_list': {} + } + for item in infer_config['emotion_list']: + data['emotion_list'][item[0]] = item[1] + try: + with open(json_path, "w", encoding='utf-8') as f: + json.dump(data, f, ensure_ascii=False, indent=4) + gr.Info(i18n("保存成功！")) + except: + gr.Error(i18n("文件打开失败，保存失败！")) + raise Exception(i18n("保存失败！")) + +def scan_files(character_path): + ckpt_file_found = [] + pth_file_found = [] + wav_file_found = [] + for dirpath, dirnames, filenames in os.walk(character_path): + for file in filenames: + full_path = os.path.join(dirpath, file) + rev_path = os.path.relpath(full_path, character_path) + print(full_path) + if file.lower().endswith(".ckpt"): + ckpt_file_found.append(rev_path) + elif file.lower().endswith(".pth"): + pth_file_found.append(rev_path) + elif file.lower().endswith(".wav"): + wav_file_found.append(rev_path) + elif file.lower().endswith(".mp3"): + wav_file_found.append(rev_path) + return ckpt_file_found, pth_file_found, wav_file_found + +def auto_generate_json(character_dropdown, models_path): + state['edited_character_name'] = character_dropdown + state['models_path'] = models_path + state['edited_character_path'] = os.path.join(state['models_path'], state['edited_character_name']) + + print(i18n(f"当前人物变更为: {state['edited_character_name']}")) + clear_infer_config() + character_path = state['edited_character_path'] + + ckpt_file_found, pth_file_found, wav_file_found = scan_files(character_path) + + if len(ckpt_file_found) == 0 or len(pth_file_found) == 0: + gr.Error(i18n("找不到模型文件！请把有效文件放置在文件夹下！！！")) + raise Exception(i18n("找不到模型文件！请把有效文件放置在文件夹下！！！")) + else: + state['ckpt_file_found'] = ckpt_file_found + state['pth_file_found'] = pth_file_found + state['wav_file_found'] = wav_file_found + gpt_path = ckpt_file_found[0] + sovits_path = pth_file_found[0] + + infer_config['gpt_path'] = gpt_path + infer_config['sovits_path'] = sovits_path + + if len(wav_file_found) == 0: + return generate_info_bar() + else: + return add_emotion() + +def scan_subfolder(models_path): + subfolders = [os.path.basename(f.path) for f in os.scandir(models_path) if f.is_dir()] + state['models_path'] = models_path + state['character_list'] = subfolders + print(i18n("扫描模型文件夹:")+models_path) + print(i18n(f"找到的角色列表:") + str(subfolders)) + gr.Info(i18n(f"找到的角色列表:") + str(subfolders)) + d2 = gr.Dropdown(subfolders) + return d2 + +def add_emotion(): + unused_emotional_style = '' + for style in emotional_styles: + style_in_list = False + for item in infer_config['emotion_list']: + if style == item[0]: + style_in_list = True + break + if not style_in_list: + unused_emotional_style = style + break + + ref_wav_path = state['wav_file_found'][0] + infer_config['emotion_list'].append([f'{unused_emotional_style}', { + 'ref_wav_path': ref_wav_path, 'prompt_text': split_file_name(ref_wav_path), 'prompt_language': 'auto'}]) + return generate_info_bar() + +def change_pt_files(version_textbox, sovits_model_dropdown, gpt_model_dropdown): + infer_config['version'] = version_textbox + infer_config['sovits_path'] = sovits_model_dropdown + infer_config['gpt_path'] = gpt_model_dropdown pass -try: - max_text_length = app_config.max_text_length -except: - max_text_length = -1 -from webuis.builders.gradio_builder import GradioTabBuilder +def change_parameters(index, wav_path, emotion_list, prompt_language, prompt_text=""): + index = int(index) + + if prompt_text == "" or prompt_text is None: + prompt_text = split_file_name(wav_path) + + infer_config['emotion_list'][index-1][0] = emotion_list + infer_config['emotion_list'][index-1][1]['ref_wav_path'] = wav_path + infer_config['emotion_list'][index-1][1]['prompt_text'] = prompt_text + infer_config['emotion_list'][index-1][1]['prompt_language'] = prompt_language + + return gr.Dropdown(value=wav_path), gr.Dropdown(value=emotion_list), gr.Dropdown(value=prompt_language), gr.Textbox(value=prompt_text), gr.Audio(os.path.join(state["edited_character_path"], wav_path)) + +def run_model_tab(): + with gr.Blocks() as model_app: + with gr.Row() as status_bar: + trained_dir_names = [os.path.basename(f.path) for f in os.scandir('.') if f.is_dir() and os.path.basename(f.path).startswith('trained')] + trained_dir_name = trained_dir_names[0] + # models_path = gr.Textbox(value=state["models_path"], label=i18n("模型文件夹路径"), scale=3) + models_path = gr.Dropdown(trained_dir_names, value=trained_dir_name, label=i18n("模型文件夹路径"), scale=3) + scan_button = gr.Button(i18n("扫描"), scale=1, variant="primary") + character_dropdown = gr.Dropdown([], label=i18n("选择角色"), scale=3) + read_info_from_json_button = gr.Button(i18n("从json中读取（无则生成）"), size="lg", scale=2, variant="secondary") + auto_generate_info_button = gr.Button(i18n("生成所有info（有则跳过）"), size="lg", scale=2, variant="primary") + + scan_button.click(scan_subfolder, inputs=[models_path], outputs=[character_dropdown]) + + gr.HTML(i18n("""这是模型管理界面，为了实现对多段参考音频分配情感设计，如果您只有一段可不使用这个界面
若有疑问或需要进一步了解，可参考文档：点击查看详细文档。
""")) + gr.Markdown(i18n("请修改后点击下方按钮进行保存")) -ref_settings = tts_synthesizer.ui_config.get("ref_settings", []) -basic_settings = tts_synthesizer.ui_config.get("basic_settings", []) -advanced_settings = tts_synthesizer.ui_config.get("advanced_settings", []) -url_setting = tts_synthesizer.ui_config.get("url_settings", []) + with gr.Row() as submit_bar: + save_json_button = gr.Button(i18n("保存json\n（可能不会有完成提示，没报错就是成功）"), scale=2, variant="primary") + save_json_button.click(save_json) + + with gr.Row(): + with gr.Column(scale=1): + current_character_textbox = gr.Textbox(value=state['edited_character_name'], label=i18n("当前人物"), interactive=False) + version_textbox = gr.Textbox(value=infer_config['version'], label=i18n("版本")) + gpt_model_dropdown = gr.Dropdown(choices=state['ckpt_file_found'], label=i18n("GPT模型路径")) + sovits_model_dropdown = gr.Dropdown(choices=state['pth_file_found'], label=i18n("Sovits模型路径")) + version_textbox.blur(change_pt_files, inputs=[version_textbox, sovits_model_dropdown, gpt_model_dropdown], outputs=None) + gpt_model_dropdown.input(change_pt_files, inputs=[version_textbox, sovits_model_dropdown, gpt_model_dropdown], outputs=None) + sovits_model_dropdown.input(change_pt_files, inputs=[version_textbox, sovits_model_dropdown, gpt_model_dropdown], outputs=None) + column_items = [current_character_textbox, version_textbox, gpt_model_dropdown, sovits_model_dropdown] + + with gr.Column(scale=3): + add_emotion_button = gr.Button(i18n("添加情感"), size="lg", scale=2, variant="primary") + + for index in range(all_emotion_num): + with gr.Row() as emotion_row: + row_index = gr.Number(visible=False) + emotional_list = gr.Dropdown(visible=False) + prompt_language = gr.Dropdown(visible=False) + wav_path = gr.Dropdown(visible=False) + prompt_text = gr.Textbox(visible=False) + audio_preview = gr.Audio(visible=False, type="filepath") + + emotional_list.input(change_parameters, inputs=[row_index, wav_path, emotional_list, prompt_language, prompt_text], outputs=[wav_path, emotional_list, prompt_language, prompt_text, audio_preview]) + prompt_language.input(change_parameters, inputs=[row_index, wav_path, emotional_list, prompt_language, prompt_text], outputs=[wav_path, emotional_list, prompt_language, prompt_text, audio_preview]) + wav_path.input(change_parameters, inputs=[row_index, wav_path, emotional_list, prompt_language], outputs=[wav_path, emotional_list, prompt_language, prompt_text, audio_preview]) + prompt_text.input(change_parameters, inputs=[row_index, wav_path, emotional_list, prompt_language, prompt_text], outputs=[wav_path, emotional_list, prompt_language, prompt_text, audio_preview]) + + column_items.append(row_index) + column_items.append(prompt_language) + column_items.append(emotional_list) + column_items.append(wav_path) + column_items.append(prompt_text) + column_items.append(audio_preview) + + add_emotion_button.click(add_emotion, outputs=column_items) + read_info_from_json_button.click(read_json_from_file, inputs=[character_dropdown, models_path], outputs=column_items) + auto_generate_info_button.click(auto_generate_all_json, inputs=[models_path]) + + return model_app -tts_task_example : Base_TTS_Task = TTS_Task() -params_config = tts_task_example.params_config -has_character_param = True if "character" in params_config else False +import os +import json +import socket +from datetime import datetime -with gr.Blocks() as app: - gr.Markdown(information) - with gr.Row(): - max_text_length_tip = "" if max_text_length == -1 else f"( "+i18n("最大允许长度")+ f" : {max_text_length} ) " - text = gr.Textbox( - value=default_text, label=i18n("输入文本")+max_text_length_tip, interactive=True, lines=8 +# 创建history文件夹 +history_dir = "history" +if not os.path.exists(history_dir): + os.makedirs(history_dir) + +def get_client_ip(): + hostname = socket.gethostname() + return socket.gethostbyname(hostname) + +def save_infer_record(result_audio, config, sample_rate=32000): + user_ip = get_client_ip() + infer_time = datetime.now().strftime('%Y-%m-%d_%H-%M-%S') + model_folder = config.get("trained_dir", "unknown") + character = config.get("character", "unknown") + emotion = config.get("emotion", "default") + text = config.get("text", "") + text_snippet = text[:20].replace("__", " ") + + filename = f"{user_ip}__{infer_time}__{model_folder}__{character}__{emotion}__{text_snippet}.json" + file_path = os.path.join(history_dir, filename) + + audio_path = file_path.replace(".json", ".wav") + with wave.open(audio_path, 'wb') as f: + f.setnchannels(1) + f.setsampwidth(2) + f.setframerate(sample_rate) + f.writeframes(result_audio) + + infer_record = { + "user_ip": user_ip, + "time": infer_time, + "config": config + } + + with open(file_path, 'w', encoding='utf-8') as f: + json.dump(infer_record, f, ensure_ascii=False, indent=4) + +def load_infer_records(): + records = [] + for filename in os.listdir(history_dir): + if filename.endswith(".json"): + parts = filename.split("__") + if len(parts) == 6: + user_ip, infer_time, model_folder, character, emotion, text_snippet = parts + records.append({ + "user_ip": user_ip, + "time": infer_time, + "model_folder": model_folder, + "character": character, + "emotion": emotion, + "text_snippet": text_snippet.replace(".json", "") + }) + return records + +def display_record_detail(record): + file_path = os.path.join(history_dir, f"{record['user_ip']}__{record['time']}__{record['model_folder']}__{record['character']}__{record['emotion']}__{record['text_snippet']}.json") + with open(file_path, 'r', encoding='utf-8') as f: + record_detail = json.load(f) + audio_path = file_path.replace(".json", ".wav") + return record_detail["config"], audio_path + +def filter_records(records, user_ip, time, model_folder, character, emotion, text): + filtered = [] + for record in records: + if user_ip and user_ip not in record["user_ip"]: + continue + if time and time not in record["time"]: + continue + if model_folder and model_folder not in record["model_folder"]: + continue + if character and character not in record["character"]: + continue + if emotion and emotion not in record["emotion"]: + continue + if text and text not in record["text_snippet"]: + continue + filtered.append(record) + return filtered + +def filter_and_display_records(user_ip, time, model_folder, character, emotion, text): + records = load_infer_records() + filtered_records = filter_records(records, user_ip, time, model_folder, character, emotion, text) + # 将字典转换为列表 + filtered_records_list = [[record["user_ip"], record["time"], record["model_folder"], record["character"], record["emotion"], record["text_snippet"]] for record in filtered_records] + return filtered_records_list + + +def run_records_tab(): + with gr.Blocks() as records_app: + with gr.Row(): + user_ip = gr.Textbox(label="推理用户（IP地址）") + time = gr.Textbox(label="推理时间") + model_folder = gr.Textbox(label="模型文件夹") + character = gr.Textbox(label="人物角色") + emotion = gr.Textbox(label="情感") + text = gr.Textbox(label="输入文本") + search_button = gr.Button("搜索") + + records_output = gr.Dataframe(headers=["推理用户", "推理时间", "模型文件夹", "人物角色", "情感", "文本片段"], datatype=["str", "str", "str", "str", "str", "str"]) + record_detail_output = gr.JSON(label="推理详情") + audio_output = gr.Audio(label="生成音频", type="filepath") + + def filter_and_display_records(user_ip, time, model_folder, character, emotion, text): + records = load_infer_records() + filtered_records = filter_records(records, user_ip, time, model_folder, character, emotion, text) + # 将字典转换为列表 + filtered_records_list = [[record["user_ip"], record["time"], record["model_folder"], record["character"], record["emotion"], record["text_snippet"]] for record in filtered_records] + return filtered_records_list + + def load_record_detail(record_index): + records = load_infer_records() + selected_record = records[record_index] + record_config, audio_path = display_record_detail(selected_record) + return record_config, audio_path + + def on_select_record(evt: gr.SelectData): + record_index = evt.index[0] # 只取第一个索引 + record_config, audio_path = load_record_detail(record_index) + return record_config, audio_path + + search_button.click( + filter_and_display_records, + inputs=[user_ip, time, model_folder, character, emotion, text], + outputs=[records_output] ) - text.blur(lambda x: gr.update(value=cut_sentence_multilang(x,max_length=max_text_length)[0]), [text], [text]) - all_gradio_components["text"] = text - with gr.Row(): - with gr.Column(scale=2): - with gr.Tabs(): - with gr.Tab(label=i18n("角色选项"), visible=has_character_param): - with gr.Group(): - ( - character, - emotion, - characters_and_emotions_, - ) = change_character_list() - characters_and_emotions = gr.State(characters_and_emotions_) - scan_character_list = gr.Button( - i18n("扫描人物列表"), variant="secondary" - ) - all_gradio_components["character"] = character - all_gradio_components["emotion"] = emotion - character.change( - load_character_emotions, - inputs=[character, characters_and_emotions], - outputs=[emotion], - ) - scan_character_list.click( - change_character_list, - inputs=[character, emotion], - outputs=[ - character, - emotion, - characters_and_emotions, - ], - ) - if len(ref_settings) > 0: - with gr.Tab(label=i18n("参考设置")): - ref_settings_tab = GradioTabBuilder( - ref_settings, params_config - ) - ref_settings_components = ref_settings_tab.build() - all_gradio_components.update(ref_settings_components) - with gr.Column(scale=2): - with gr.Tabs(): - if len(basic_settings) > 0: - with gr.Tab(label=i18n("基础选项")): - basic_settings_tab = GradioTabBuilder( - basic_settings, params_config - ) - basic_settings_components = basic_settings_tab.build() - all_gradio_components.update(basic_settings_components) - with gr.Column(scale=2): - with gr.Tabs(): - if len(advanced_settings) > 0: - with gr.Tab(label=i18n("高级选项")): - advanced_settings_tab = GradioTabBuilder( - advanced_settings, params_config - ) - advanced_settings_components = advanced_settings_tab.build() - all_gradio_components.update(advanced_settings_components) - if len(url_setting) > 0: - with gr.Tab(label=i18n("URL设置")): - url_setting_tab = GradioTabBuilder(url_setting, params_config) - url_setting_components = url_setting_tab.build() - all_gradio_components.update(url_setting_components) - with gr.Tabs(): - with gr.Tab(label=i18n("请求完整音频")): - with gr.Row(): - get_full_audio_button = gr.Button(i18n("生成音频"), variant="primary") - full_audio = gr.Audio( - None, label=i18n("音频输出"), type="filepath", streaming=False - ) - get_full_audio_button.click(lambda: gr.update(interactive=False), None, [get_full_audio_button]).then( - get_audio, - inputs=[value for key, value in all_gradio_components.items()], - outputs=[full_audio], - ).then(lambda: gr.update(interactive=True), None, [get_full_audio_button]) - with gr.Tab(label=i18n("流式音频")): - with gr.Row(): - get_streaming_audio_button = gr.Button(i18n("生成流式音频"), variant="primary") - streaming_audio = gr.Audio( - None, label=i18n("音频输出"), type="filepath", streaming=True, autoplay=True - ) - get_streaming_audio_button.click(lambda: gr.update(interactive=False), None, [get_streaming_audio_button]).then( - get_streaming_audio, - inputs=[value for key, value in all_gradio_components.items()], - outputs=[streaming_audio], - ).then(lambda: gr.update(interactive=True), None, [get_streaming_audio_button]) - - gr.HTML("{i18n("这是GSVI。")}{i18n("，当前版本：")}{frontend_version} {i18n("项目开源地址：")} Github
-{i18n("若有疑问或需要进一步了解，可参考文档：")}{i18n("点击查看详细文档")}。
""" - ) - # 以下是事件绑定 - # app.load( - # change_character_list, - # inputs=[character, emotion], - # outputs=[ - # character, - # emotion, - # characters_and_emotions, - # ] - # ) - - -if app_config.also_enable_api == True: - import uvicorn - from pure_api import tts, character_list, set_tts_synthesizer - from fastapi import FastAPI - from fastapi.middleware.cors import CORSMiddleware - from src.api_utils import get_gradio_frp, get_localhost_ipv4_address - - set_tts_synthesizer(tts_synthesizer) - fastapi_app:FastAPI = app.app - fastapi_app.add_api_route("/tts", tts, methods=["POST", "GET"]) - fastapi_app.add_api_route("/character_list", character_list, methods=["GET"]) - - fastapi_app.add_middleware( - CORSMiddleware, - allow_origins=["*"], - allow_credentials=True, - allow_methods=["*"], - allow_headers=["*"], + records_output.select( + on_select_record, + outputs=[record_detail_output, audio_output] ) - - local_link = f"http://127.0.0.1:{app_config.server_port}" - link = local_link - if app_config.is_share: - share_url = get_gradio_frp(app_config.server_name, app_config.server_port, app.share_token) - print("This share link expires in 72 hours.") - print(f"Share URL: {share_url}") - link = share_url - if app_config.inbrowser: - import webbrowser - webbrowser.open(link) - - ipv4_address = get_localhost_ipv4_address(app_config.server_name) - ipv4_link = f"http://{ipv4_address}:{app_config.server_port}" - print(f"INFO: Local Network URL: {ipv4_link}") - - fastapi_app = gr.mount_gradio_app(fastapi_app, app, path="/") - uvicorn.run(fastapi_app, host=app_config.server_name, port=app_config.server_port) -else: - app.queue().launch(share=app_config.is_share, inbrowser=app_config.inbrowser, server_name=app_config.server_name, server_port=app_config.server_port) + records_app.load(lambda: filter_and_display_records("", "", "", "", "", ""), outputs=[records_output]) + return records_app + + +if __name__ == '__main__': + with gr.Blocks() as app: + with gr.Tabs(): + with gr.Tab(label="推理"): + run_inference_tab() + with gr.Tab(label="模型配置"): + run_model_tab() + with gr.Tab(label="生成记录"): + run_records_tab() + app.launch(server_port=9872, inbrowser=True, share=False) diff --git a/common_config.json b/common_config.json index 2997fa078..a996f81d1 100644 --- a/common_config.json +++ b/common_config.json @@ -1,10 +1,11 @@ { "app_config": { "locale": { - "default": "auto", + "default": "zh_CN", "description": "Locale settings for the application", "label": "语言", - "type": "string" + "type": "string", + "choices": ["en_US", "zh_CN", "zh_TW"] }, "server_port": { "default": 5000, diff --git a/start.sh b/start.sh new file mode 100755 index 000000000..0b37ae9b4 --- /dev/null +++ b/start.sh @@ -0,0 +1,11 @@ +pkill -f "app.py" +# ps -ef | grep "app.py" | awk '{print $2}' | xargs kill -9 + +source ~/anaconda3/etc/profile.d/conda.sh +conda activate torch + +nohup python app.py 2>&1 > app.log & + + +# conda activate torch +# python webuis/character_manager/webui.py \ No newline at end of file diff --git a/tools/i18n/i18n.py b/tools/i18n/i18n.py index 021ad6209..2cb2f8a12 100644 --- a/tools/i18n/i18n.py +++ b/tools/i18n/i18n.py @@ -1,26 +1,31 @@ +import os import json import locale -import os - - -def load_language_list(language, locale_path="./i18n/locale"): - with open(os.path.join(locale_path, f"{language}.json"), "r", encoding="utf-8") as f: - language_list = json.load(f) - return language_list - from src.common_config_manager import app_config +def load_language_list(language, locale_paths): + language_map = {} + for locale_path in locale_paths: + lang_file = os.path.join(locale_path, f"{language}.json") + if os.path.exists(lang_file): + with open(lang_file, 'r', encoding='utf-8') as f: + language_map.update(json.load(f)) + return language_map + class I18nAuto: - def __init__(self, language=None, locale_path="./i18n/locale"): + def __init__(self, language=None, locale_paths=[], locale_path="./i18n/locale"): if language in ["auto", None]: if app_config.locale in ["auto", None, ""]: language = locale.getdefaultlocale()[0] else: language = app_config.locale - if not os.path.exists(os.path.join(locale_path, f"{language}.json")): - language = "en_US" + if not any(os.path.exists(os.path.join(locale_path, f"{language}.json")) for locale_path in locale_paths): + language = "zh_CN" self.language = language - self.language_map = load_language_list(language, locale_path) + if len(locale_paths): + self.language_map = load_language_list(language, locale_paths) + else: + self.language_map = load_language_list(language, [locale_path]) def __call__(self, key): return self.language_map.get(key, key) diff --git a/trained/.gitignore b/trained/.gitignore deleted file mode 100644 index aa4e55103..000000000 --- a/trained/.gitignore +++ /dev/null @@ -1,3 +0,0 @@ -* -!.gitignore -!character_info.json \ No newline at end of file diff --git a/webuis/builders/gradio_builder.py b/webuis/builders/gradio_builder.py index 1f245b2b8..896b44310 100644 --- a/webuis/builders/gradio_builder.py +++ b/webuis/builders/gradio_builder.py @@ -17,7 +17,7 @@ class GradioTabBuilder: gradio_input_dict (Dict[str, Any]): A dictionary of Gradio inputs. Methods: - __init__(self, component_name_list: List[str|List[str]], params_config: Dict[str, ParamItem]): Initializes the GradioTabBuilder object. + __init__(self, component_name_list: List[Union[str, List[str]]], params_config: Dict[str, ParamItem]): Initializes the GradioTabBuilder object. add_input(self, name: str, input: Any): Adds an input to the gradio_input_dict. build_group(self, component_list: List[ParamItem]): Builds a group of components. build(self): Builds the Gradio tab and returns the gradio_input_dict. @@ -25,12 +25,12 @@ class GradioTabBuilder: component_group_list: List[List[ParamItem]] gradio_input_dict: Dict[str, Any] - def __init__(self, component_name_list: List[str|List[str]], params_config: Dict[str, ParamItem]): + def __init__(self, component_name_list: List[Union[str, List[str]]], params_config: Dict[str, ParamItem]): """ Initializes the GradioTabBuilder object. Args: - component_name_list (List[str|List[str]]): A list of component names or groups of component names. + component_name_list (List[Union[str, List[str]]]): A list of component names or groups of component names. params_config (Dict[str, ParamItem]): A dictionary of parameter configurations. """ self.component_group_list = [] @@ -106,12 +106,12 @@ def emit_on_change(*data): """ pass -def register_on_change(component_name_list: List[str|List[str]], all_gradio_components: Dict[str, Any]): +def register_on_change(component_name_list: List[Union[str, List[str]]], all_gradio_components: Dict[str, Any]): """ Registers an on_change function for the Gradio inputs. Args: - component_name_list (List[str|List[str]]): A list of component names or groups of component names. + component_name_list (List[Union[str, List[str]]]): A list of component names or groups of component names. gradio_input_dict (Dict[str, Any]): The Gradio input dictionary. on_change (Optional[Callable[[Dict[str, Any]], None]]): The on_change function to register. """ diff --git a/webuis/character_manager/webui.py b/webuis/character_manager/webui.py deleted file mode 100644 index 75bc7500d..000000000 --- a/webuis/character_manager/webui.py +++ /dev/null @@ -1,338 +0,0 @@ -import gradio as gr -import os, json - -# 在开头加入路径 -import os, sys -now_dir = os.getcwd() -sys.path.append(now_dir) -# sys.path.append(os.path.join(now_dir, "tools")) - - - -global state - -state = { 'models_path': r"trained", - 'character_list': [], - - - 'edited_character_path': '', - 'edited_character_name': '', - 'ckpt_file_found': [], - 'pth_file_found': [], - 'wav_file_found': [], - - - } - -global infer_config -infer_config = { -} - -# 取得模型文件夹路径 -config_path = "gsv_config.json" -state["models_path"] = "trained" -locale_language = "auto" -if os.path.exists(config_path): - with open(config_path, 'r', encoding='utf-8') as f: - config = json.load(f) - state["models_path"] = config.get("models_path", "trained") - - -from tools.i18n.i18n import I18nAuto - - -i18n = I18nAuto(None, os.path.join(os.path.dirname(__file__), "i18n/locale")) - -# 微软提供的SSML情感表 -emotional_styles = [ - "default", - "advertisement_upbeat", "affectionate", "angry", "assistant", "calm", "chat", "cheerful", - "customerservice", "depressed", "disgruntled", "documentary-narration", "embarrassed", - "empathetic", "envious", "excited", "fearful", "friendly", "gentle", "hopeful", "lyrical", - "narration-professional", "narration-relaxed", "newscast", "newscast-casual", "newscast-formal", - "poetry-reading", "sad", "serious", "shouting", "sports_commentary", "sports_commentary_excited", - "whispering", "terrified", "unfriendly" -] - -language_list = ["auto", "zh", "en", "ja", "all_zh", "all_ja"] -translated_language_dict = {} -for language in language_list: - translated_language_dict[language] = language - translated_language_dict[i18n(language)] = language - translated_language_dict["多语种混合"] = "auto" - -# 预先建立相当数量的情感选择框 -all_emotion_num=len(emotional_styles) - -def generate_info_bar(): - current_character_textbox = gr.Textbox(value=state['edited_character_name'], label=i18n("当前人物"), interactive=False) - version_textbox = gr.Textbox(value=infer_config['version'], label=i18n("版本"), interactive=True) - gpt_model_dropdown = gr.Dropdown(choices=state['ckpt_file_found'], label=i18n("GPT模型路径"), interactive=True, value=infer_config['gpt_path'], allow_custom_value=True) - sovits_model_dropdown = gr.Dropdown(choices=state['pth_file_found'], label=i18n("Sovits模型路径"), interactive=True, value=infer_config['sovits_path'], allow_custom_value=True) - column_items = [current_character_textbox, version_textbox, gpt_model_dropdown, sovits_model_dropdown] - index = 0 - for item in infer_config['emotion_list']: - emotion, details = item - index += 1 - column_items.append(gr.Number(index, visible=True, scale=1)) - column_items.append(gr.Dropdown(choices=[(i18n(language), language) for language in language_list], value=translated_language_dict[details['prompt_language']], visible=True, interactive=True, scale=3, label=i18n("提示语言"))) - column_items.append(gr.Dropdown(choices=emotional_styles, value=emotion, visible=True, interactive=True, scale=3, allow_custom_value=True, label=i18n("情感风格"))) - column_items.append(gr.Dropdown(choices=state["wav_file_found"], visible=True, value=details['ref_wav_path'], scale=8, allow_custom_value=True, label=i18n("参考音频路径"))) - column_items.append(gr.Textbox(value=details['prompt_text'], visible=True, scale=8, interactive=True, label=i18n("提示文本"))) - column_items.append(gr.Audio(os.path.join(state["edited_character_path"], details['ref_wav_path']), visible=True, scale=8, label=i18n("音频预览"))) - - for i in range(all_emotion_num - index): - column_items.append(gr.Number(i, visible=False)) - column_items.append(gr.Dropdown(visible=False)) - column_items.append(gr.Dropdown(visible=False)) - column_items.append(gr.Dropdown(visible=False)) - column_items.append(gr.Textbox(visible=False)) - column_items.append(gr.Audio(None, visible=False)) - - return column_items - -def load_json_to_state(data): - infer_config['version'] = data.get('version','') - emotional_list = data.get('emotion_list',{}) - for emotion, details in emotional_list.items(): - infer_config['emotion_list'].append([emotion,details]) - infer_config['gpt_path'] = data['gpt_path'] - infer_config['sovits_path'] = data['sovits_path'] - return generate_info_bar() - - -def split_file_name(file_name): - try : - base_name=os.path.basename(file_name) - except: - base_name=file_name - - final_name = os.path.splitext(base_name)[0] - return final_name - - -def clear_infer_config(): - global infer_config - infer_config = { - 'version': '1.0.1', - 'gpt_path': '', - 'sovits_path': '', - 'emotion_list': [], - } - -clear_infer_config() - -def read_json_from_file(character_dropdown,models_path ): - state['edited_character_name'] = character_dropdown - state['models_path']=models_path - state['edited_character_path'] = os.path.join(state['models_path'], state['edited_character_name']) - state['ckpt_file_found'], state['pth_file_found'], state['wav_file_found'] = scan_files(state['edited_character_path']) - print(i18n("当前人物变更为: ")+state['edited_character_name']) - clear_infer_config() - json_path = os.path.join(state['edited_character_path'], "infer_config.json") - # 从json文件中读取数据 - with open(json_path, "r", encoding='utf-8') as f: - data = json.load(f) - return load_json_to_state(data) - - -def save_json(): - if infer_config['gpt_path'] == '' or infer_config['gpt_path'] is None: - gr.Error(i18n("缺失某些项，保存失败！")) - raise Exception(i18n("缺失某些项，保存失败！")) - json_path = os.path.join(state['edited_character_path'], "infer_config.json") - data = { - 'version': infer_config['version'], - 'gpt_path': infer_config['gpt_path'], - 'sovits_path': infer_config['sovits_path'], - i18n("简介"): i18n(r"这是一个配置文件适用于https://github.com/X-T-E-R/TTS-for-GPT-soVITS，是一个简单好用的前后端项目"), - 'emotion_list': {} - } - for item in infer_config['emotion_list']: - data['emotion_list'][item[0]] = item[1] - try: - # 将state中的数据保存到json文件中 - with open(json_path, "w", encoding='utf-8') as f: - json.dump(data, f, ensure_ascii=False, indent=4) - gr.Info(i18n("保存成功！")) - - except: - gr.Error(i18n("文件打开失败，保存失败！")) - raise Exception(i18n("保存失败！")) - - - -def scan_files(character_path): - ckpt_file_found = [] - pth_file_found = [] - wav_file_found = [] - - # 扫描3种文件 - for dirpath, dirnames, filenames in os.walk(character_path): - for file in filenames: - # 构建文件的完整路径 - full_path = os.path.join(dirpath, file) - rev_path = os.path.relpath(full_path, character_path) - print(full_path) - # 根据文件扩展名和变量是否已赋值来更新变量 - if file.lower().endswith(".ckpt"): - ckpt_file_found.append(rev_path) - elif file.lower().endswith(".pth"): - pth_file_found.append(rev_path) - elif file.lower().endswith(".wav"): - wav_file_found.append(rev_path) - - return ckpt_file_found, pth_file_found, wav_file_found - -def auto_generate_json(character_dropdown, models_path): - # 将选中人物设定为当前人物 - state['edited_character_name'] = character_dropdown - state['models_path'] = models_path - state['edited_character_path'] = os.path.join(state['models_path'], state['edited_character_name']) - print(i18n(f"当前人物变更为: {state['edited_character_name']}")) - clear_infer_config() - character_path = state['edited_character_path'] - - ckpt_file_found, pth_file_found, wav_file_found = scan_files(character_path) - - if len(ckpt_file_found) == 0 or len(pth_file_found) == 0: - gr.Error(i18n("找不到模型文件！请把有效文件放置在文件夹下！！！")) - raise Exception(i18n("找不到模型文件！请把有效文件放置在文件夹下！！！")) - else: - state['ckpt_file_found'] = ckpt_file_found - state['pth_file_found'] = pth_file_found - state['wav_file_found'] = wav_file_found - gpt_path = ckpt_file_found[0] - sovits_path = pth_file_found[0] - - infer_config['gpt_path'] = gpt_path - infer_config['sovits_path'] = sovits_path - - if len(wav_file_found) == 0: - return generate_info_bar() - else: - return add_emotion() - - -def scan_subfolder(models_path): - subfolders = [os.path.basename(f.path) for f in os.scandir(models_path) if f.is_dir()] - state['models_path'] = models_path - state['character_list'] = subfolders - print(i18n("扫描模型文件夹:")+models_path) - print(i18n(f"找到的角色列表:") + str(subfolders)) - gr.Info(i18n(f"找到的角色列表:") + str(subfolders)) - d2 = gr.Dropdown(subfolders) - return d2 - - - -def add_emotion(): - - unused_emotional_style = '' - for style in emotional_styles: - style_in_list = False - for item in infer_config['emotion_list']: - if style == item[0]: - style_in_list = True - break - if not style_in_list: - unused_emotional_style = style - break - - ref_wav_path = state['wav_file_found'][0] - infer_config['emotion_list'].append([f'{unused_emotional_style}', { - 'ref_wav_path':ref_wav_path,'prompt_text':split_file_name(ref_wav_path),'prompt_language':'auto'}]) - return generate_info_bar() - - -def change_pt_files(version_textbox, sovits_model_dropdown, gpt_model_dropdown): - infer_config['version'] = version_textbox - infer_config['sovits_path'] = sovits_model_dropdown - infer_config['gpt_path'] = gpt_model_dropdown - pass - -def change_parameters(index, wav_path, emotion_list, prompt_language, prompt_text = ""): - - # Convert index to integer in case it's passed as a string - index = int(index) - - if prompt_text=="" or prompt_text is None: - prompt_text = split_file_name(wav_path) - - infer_config['emotion_list'][index-1][0]=emotion_list - infer_config['emotion_list'][index-1][1]['ref_wav_path'] = wav_path - infer_config['emotion_list'][index-1][1]['prompt_text'] = prompt_text - infer_config['emotion_list'][index-1][1]['prompt_language'] = prompt_language - - return gr.Dropdown(value=wav_path), gr.Dropdown(value=emotion_list), gr.Dropdown(value=prompt_language), gr.Textbox(value=prompt_text), gr.Audio(os.path.join(state["edited_character_path"],wav_path)) - - -def run_as_tab(app: gr.Blocks): - with gr.Row() as status_bar: - # 创建模型文件夹路径的输入框 - models_path = gr.Textbox(value=state["models_path"], label=i18n("模型文件夹路径"), scale=3) - - # 创建扫描按钮并设置点击事件 - scan_button = gr.Button(i18n("扫描"), scale=1, variant="primary") - # 创建角色列表的下拉菜单，初始为空 - character_dropdown = gr.Dropdown([], label=i18n("选择角色"), scale=3) - # 创建从json中读取按钮并设置点击事件 - read_info_from_json_button = gr.Button(i18n("从json中读取"), size="lg", scale=2, variant="secondary") - # 创建自动生成json的按钮并设置点击事件 - auto_generate_info_button = gr.Button(i18n("自动生成info"), size="lg", scale=2, variant="primary") - - scan_button.click(scan_subfolder, inputs=[models_path], outputs=[character_dropdown]) - - gr.HTML(i18n("""这是模型管理界面，为了实现对多段参考音频分配情感设计，如果您只有一段可不使用这个界面
若有疑问或需要进一步了解，可参考文档：点击查看详细文档。
""")) - gr.Markdown(i18n("请修改后点击下方按钮进行保存")) - - # 创建保存json的按钮并设置点击事件 - with gr.Row() as submit_bar: - save_json_button = gr.Button(i18n("保存json\n（可能不会有完成提示，没报错就是成功）"), scale=2, variant="primary") - save_json_button.click(save_json) - - # 模型信息 - with gr.Row(): - with gr.Column(scale=1): - current_character_textbox = gr.Textbox(value=state['edited_character_name'], label=i18n("当前人物"), interactive=False) - version_textbox = gr.Textbox(value=infer_config['version'], label=i18n("版本")) - gpt_model_dropdown = gr.Dropdown(choices=state['ckpt_file_found'], label=i18n("GPT模型路径")) - sovits_model_dropdown = gr.Dropdown(choices=state['pth_file_found'], label=i18n("Sovits模型路径")) - version_textbox.blur(change_pt_files, inputs=[version_textbox, sovits_model_dropdown, gpt_model_dropdown], outputs=None) - gpt_model_dropdown.input(change_pt_files, inputs=[version_textbox, sovits_model_dropdown, gpt_model_dropdown], outputs=None) - sovits_model_dropdown.input(change_pt_files, inputs=[version_textbox, sovits_model_dropdown, gpt_model_dropdown], outputs=None) - column_items = [current_character_textbox, version_textbox, gpt_model_dropdown, sovits_model_dropdown] - - with gr.Column(scale=3): - add_emotion_button = gr.Button(i18n("添加情感"), size="lg", scale=2, variant="primary") - - for index in range(all_emotion_num): - - with gr.Row() as emotion_row: - row_index = gr.Number(visible=False) - emotional_list = gr.Dropdown(visible=False) - prompt_language = gr.Dropdown(visible=False) - wav_path = gr.Dropdown(visible=False) - prompt_text = gr.Textbox(visible=False) - audio_preview = gr.Audio(visible=False, type="filepath") - - emotional_list.input(change_parameters, inputs=[row_index, wav_path, emotional_list, prompt_language, prompt_text], outputs=[wav_path, emotional_list, prompt_language, prompt_text, audio_preview]) - prompt_language.input(change_parameters, inputs=[row_index, wav_path, emotional_list, prompt_language, prompt_text], outputs=[wav_path, emotional_list, prompt_language, prompt_text, audio_preview]) - wav_path.input(change_parameters, inputs=[row_index, wav_path, emotional_list, prompt_language], outputs=[wav_path, emotional_list, prompt_language, prompt_text, audio_preview]) - prompt_text.input(change_parameters, inputs=[row_index, wav_path, emotional_list, prompt_language, prompt_text], outputs=[wav_path, emotional_list, prompt_language, prompt_text, audio_preview]) - - column_items.append(row_index) - column_items.append(prompt_language) - column_items.append(emotional_list) - column_items.append(wav_path) - column_items.append(prompt_text) - column_items.append(audio_preview) - - add_emotion_button.click(add_emotion, outputs=column_items) - read_info_from_json_button.click(read_json_from_file, inputs=[character_dropdown,models_path] , outputs=column_items) - auto_generate_info_button.click(auto_generate_json, inputs=[character_dropdown,models_path], outputs=column_items) - -if __name__ == '__main__': - with gr.Blocks() as app: - run_as_tab(app) - app.launch(server_port=9868, inbrowser=True, share=False)