diff --git a/config_example.json b/config_example.json index 79d30f2a..d46f3573 100644 --- a/config_example.json +++ b/config_example.json @@ -33,7 +33,7 @@ "azure_embedding_model_name": "text-embedding-ada-002", // 你的 Azure OpenAI Embedding 模型名称 //== 基础配置 == - "language": "auto", // 界面语言，可选"auto", "zh_CN", "en_US", "ja_JP", "ko_KR", "sv_SE", "ru_RU", "vi_VN" + "language": "auto", // 界面语言，可选"auto", "zh_CN", "zh_TW", "en_US", "ja_JP", "ko_KR", "sv_SE", "ru_RU", "vi_VN" "users": [], // 用户列表，[["用户名1", "密码1"], ["用户名2", "密码2"], ...] "admin_list": [], // 管理员列表，["用户名1", "用户名2", ...] 只有管理员可以重启服务 "local_embedding": false, //是否在本地编制索引 diff --git a/locale/zh_TW.json b/locale/zh_TW.json new file mode 100644 index 00000000..45ded7e5 --- /dev/null +++ b/locale/zh_TW.json @@ -0,0 +1,30 @@ +{ + "gpt3.5turbo_description": "GPT-3.5 Turbo 是由 OpenAI 開發的一款僅限文字的大型語言模型。它基於 GPT-3 模型，並已經在大量數據上進行了微調。最新版本的 GPT-3.5 Turbo 進行了性能和精度優化，支援最大 16k tokens 的上下文窗口和最大 4096 tokens 的響應長度。此模型始終使用可用的最新版本的 GPT-3.5 Turbo。", + "gpt3.5turbo_instruct_description": "GPT3.5 Turbo Instruct 是 OpenAI 開發的文字補全模型，具有與 GPT-3 時代模型相似的功能。它兼容舊版的 Completions 端點，但不兼容 Chat Completions。該模型的上下文窗口為 4096 個 tokens。", + "gpt3.5turbo_16k_description": "舊版的 GPT-3.5 Turbo 模型，具有 16k tokens 的上下文窗口。", + "gpt4_description": "GPT-4 是 OpenAI 開發的一款僅限文字的大型語言模型。它具有 8192 個 tokens 的上下文窗口和 4096 個 tokens 的最大響應長度。該模型始終使用可用的最新版本的 GPT-4。建議使用 GPT-4 Turbo 以獲得更好的性能、更快的速度和更低的成本。", + "gpt4_32k_description": "GPT-4 32K 是 OpenAI 開發的一個僅限文字的大型語言模型。它具有 32,000 tokens 的上下文窗口和 4,096 tokens 的最大響應長度。這個模型從未廣泛推出,建議使用 GPT-4 Turbo。", + "gpt4turbo_description": "GPT-4 Turbo 是由 OpenAI 開發的一款多模態大型語言模型。它在廣泛的自然語言處理任務上提供最先進的性能，包括文字生成、翻譯、摘要、視覺問題回答等。GPT-4 Turbo 擁有最大 128k tokens 的上下文窗口和最大 4096 tokens 的響應長度。此模型始終使用可用的最新版本的 GPT-4 Turbo。", + "claude3_haiku_description": "Claude3 Haiku 是由 Anthropic 開發的一款多模態大型語言模型。它是 Claude 3 模型家族中最快、最緊湊的模型，旨在實現近乎即時的響應速度，但是性能不如 Sonnet 和 Opus。Claude3 Haiku 有最大 200k tokens 的上下文窗口和最大 4096 tokens 的響應長度。此模型始終使用可用的最新版本的 Claude3 Haiku。", + "claude3_sonnet_description": "Claude3 Sonnet 是由 Anthropic 開發的一款多模態大型語言模型。它在智慧與速度之間保持最佳平衡，適用於企業工作負載和大規模 AI 部署。Claude3 Sonnet 擁有最大 200k tokens 的上下文窗口和最大 4096 tokens 的響應長度。此模型始終使用可用的最新版本的 Claude3 Sonnet。", + "claude3_opus_description": "Claude3 Opus 是由 Anthropic 開發的一款多模態大型語言模型。它是 Claude 3 模型家族中最智慧、最大的模型，能夠在高度複雜的任務上呈現最頂尖的性能，呈現出類似人類的理解能力。Claude3 Opus 擁有最大 200k tokens 的上下文窗口和最大 4096 tokens 的響應長度。此模型始終使用可用的最新版本的 Claude3 Opus。", + "groq_llama3_8b_description": "採用 [Groq](https://console.groq.com/) 的 LLaMA 3 8B。Groq 是一個非常快速的語言模型推理服務。", + "groq_llama3_70b_description": "採用 [Groq](https://console.groq.com/) 的 LLaMA 3 70B。Groq 是一個非常快速的語言模型推理服務。", + "groq_mixtral_8x7b_description": "採用 [Groq](https://console.groq.com/) 的 Mixtral 8x7B。Groq 是一個非常快速的語言模型推理服務。", + "groq_gemma_7b_description": "採用 [Groq](https://console.groq.com/) 的 Gemma 7B。Groq 是一個非常快速的語言模型推理服務。", + "chuanhu_description": "一個能使用多種工具解決複雜問題的智慧體。", + "gpt_default_slogan": "今天能幫您些什麼？", + "claude_default_slogan": "我能幫您什麼忙？", + "chuanhu_slogan": "川虎今天能幫你做些什麼？", + "chuanhu_question_1": "今天杭州天氣如何？", + "chuanhu_question_2": "最近 Apple 發佈了什麼新品？", + "chuanhu_question_3": "現在顯卡的價格如何？", + "chuanhu_question_4": "TikTok 上有什麼新梗？", + "gpt4o_description": "OpenAI 的最先進的多模態旗艦模型，比 GPT-4 Turbo 更便宜、更快。", + "gpt4omini_description": "OpenAI 的經濟實惠且智慧的小型模型，適用於快速、輕量班導務。", + "gpt5_description": "跨領域編碼與智慧體任務的最佳模型。支援 400,000 token 上下文，單次可輸出至多 128,000 token。", + "gpt5mini_description": "面向明確任務的更快、更具性價比的 GPT-5 版本。支援 400,000 token 上下文，單次可輸出至多 128,000 token。", + "gpt5nano_description": "速度最快、性價比最高的 GPT-5 版本。支援 400,000 token 上下文，單次可輸出至多 128,000 token。", + "o1_description": "o1 系列的大型語言模型通過強化學習訓練，能夠執行復雜的推理任務。o1 模型在回答之前會進行思考，產生一長串內部思維鏈，然後再回應使用者。", + "no_permission_to_update_description": "你沒有權限更新。請聯繫管理員。管理員的設定方式為在組態檔 config.json 中的 admin_list 中添加使用者名。" +} diff --git a/modules/utils.py b/modules/utils.py index 9a17c3d1..da24c24f 100644 --- a/modules/utils.py +++ b/modules/utils.py @@ -1,36 +1,40 @@ # -*- coding:utf-8 -*- from __future__ import annotations -from typing import TYPE_CHECKING, Any, Callable, Dict, List, Tuple, Type -from enum import Enum -import logging -import commentjson as json -import os -import datetime + import csv -import threading -import requests +import datetime +import getpass +import hashlib import hmac import html -import hashlib +import logging +import os +import threading +from enum import Enum +from typing import TYPE_CHECKING, Any, Callable, Dict, List, Tuple, Type +import colorama +import commentjson as json import gradio as gr +import pandas as pd import regex as re -import getpass -from pypinyin import lazy_pinyin +import requests import tiktoken from markdown import markdown from pygments import highlight -from pygments.lexers import get_lexer_by_name from pygments.formatters import HtmlFormatter -import pandas as pd -import colorama +from pygments.lexers import get_lexer_by_name +from pypinyin import lazy_pinyin +from modules.config import (admin_list, hide_history_when_not_logged_in, + retrieve_proxy) from modules.presets import * + from . import shared -from modules.config import retrieve_proxy, hide_history_when_not_logged_in, admin_list if TYPE_CHECKING: from typing import TypedDict + from .models.base_model import BaseLLMModel class DataframeData(TypedDict): @@ -145,6 +149,7 @@ def set_user_identifier(current_model, *args): def set_single_turn(current_model, *args): current_model.set_single_turn(*args) + def set_streaming(current_model, *args): current_model.set_streaming(*args) @@ -243,38 +248,47 @@ def convert_mdtext(md_text): # deprecated output += ALREADY_CONVERTED_MARK return output + def remove_html_tags(chatbot): def clean_text(text): # Regular expression to match code blocks, including all newlines - code_block_pattern = r'(```[\s\S]*?```)' + code_block_pattern = r"(```[\s\S]*?```)" # Split the text into code blocks and non-code blocks parts = re.split(code_block_pattern, text) cleaned_parts = [] for part in parts: - if part.startswith('```') and part.endswith('```'): + if part.startswith("```") and part.endswith("```"): # This is a code block, keep it exactly as is cleaned_parts.append(part) else: # This is not a code block, remove HTML tags # Remove all HTML tags - cleaned = re.sub(r'<[^>]+>', '', part) + cleaned = re.sub(r"<[^>]+>", "", part) # Remove any remaining HTML entities - cleaned = re.sub(r'&[#\w]+;', '', cleaned) + cleaned = re.sub(r"&[#\w]+;", "", cleaned) cleaned_parts.append(cleaned) # Don't strip here to preserve newlines # Join the cleaned parts back together - return ''.join(cleaned_parts) + return "".join(cleaned_parts) processed = [] for conv in chatbot: - if len(conv) == 2 and (isinstance(conv[0], tuple) or isinstance(conv[0], list)) and len(conv[0]) == 2 and conv[0][1] is None and conv[1] is None: + if ( + len(conv) == 2 + and (isinstance(conv[0], tuple) or isinstance(conv[0], list)) + and len(conv[0]) == 2 + and conv[0][1] is None + and conv[1] is None + ): # This is an image path sublist, keep it as-is processed.append(conv) else: # Apply clean_text to each item in the sublist - processed.append([clean_text(item) if item is not None else None for item in conv]) + processed.append( + [clean_text(item) if item is not None else None for item in conv] + ) return processed @@ -285,9 +299,7 @@ def clip_rawtext(chat_message, need_escape=True): hr_match = re.search(hr_pattern, chat_message, re.DOTALL) message_clipped = chat_message[: hr_match.start()] if hr_match else chat_message # second, avoid agent-prefix being escaped - agent_prefix_pattern = ( - r'(.*?)' - ) + agent_prefix_pattern = r"(.*?)" # agent_matches = re.findall(agent_prefix_pattern, message_clipped) agent_parts = re.split(agent_prefix_pattern, message_clipped, flags=re.DOTALL) final_message = "" @@ -300,7 +312,7 @@ def clip_rawtext(chat_message, need_escape=True): else f'
{part}
' ) else: - part = part.replace(' data-fancybox="gallery"', '') + part = part.replace(' data-fancybox="gallery"', "") final_message += part return final_message @@ -403,6 +415,7 @@ def construct_text(role, text): def construct_user(text): return construct_text("user", text) + def construct_image(path): return construct_text("image", path) @@ -470,25 +483,30 @@ def save_file(filename, model): # check if history file path matches user_name # if user access control is not enabled, user_name is empty, don't check - assert os.path.basename(os.path.dirname(history_file_path)) == model.user_name or model.user_name == "" + assert ( + os.path.basename(os.path.dirname(history_file_path)) == model.user_name + or model.user_name == "" + ) with open(history_file_path, "w", encoding="utf-8") as f: json.dump(json_s, f, ensure_ascii=False, indent=4) save_md_file(history_file_path) return history_file_path + def save_md_file(json_file_path): with open(json_file_path, "r", encoding="utf-8") as f: json_data = json.load(f) md_file_path = json_file_path[:-5] + ".md" md_s = f"system: \n- {json_data['system']} \n" - for data in json_data['history']: + for data in json_data["history"]: md_s += f"\n{data['role']}: \n- {data['content']} \n" with open(md_file_path, "w", encoding="utf8") as f: f.write(md_s) + def sorted_by_pinyin(list): return sorted(list, key=lambda char: lazy_pinyin(char)[0][0]) @@ -537,7 +555,9 @@ def get_history_names(user_name=""): else: user_history_dir = os.path.join(HISTORY_DIR, user_name) # ensure the user history directory is inside the HISTORY_DIR - assert os.path.realpath(user_history_dir).startswith(os.path.realpath(HISTORY_DIR)) + assert os.path.realpath(user_history_dir).startswith( + os.path.realpath(HISTORY_DIR) + ) history_files = get_file_names_by_last_modified_time( os.path.join(HISTORY_DIR, user_name) ) @@ -567,27 +587,31 @@ def init_history_list(user_name="", prepend=None): def filter_history(user_name, keyword): history_names = get_history_names(user_name) try: - history_names = [name for name in history_names if re.search(keyword, name, timeout=0.01)] + history_names = [ + name for name in history_names if re.search(keyword, name, timeout=0.01) + ] return gr.update(choices=history_names) except: return gr.update(choices=history_names) def load_template(filename, mode=0): - logging.debug(f"加载模板文件{filename}，模式为{mode}（0为返回字典和下拉菜单，1为返回下拉菜单，2为返回字典）") + logging.debug( + f"加载模板文件{filename}，模式为{mode}（0为返回字典和下拉菜单，1为返回下拉菜单，2为返回字典）" + ) lines = [] template_file_path = os.path.join(TEMPLATES_DIR, filename) # check if template_file_path is inside TEMPLATES_DIR - if not os.path.realpath(template_file_path).startswith(os.path.realpath(TEMPLATES_DIR)): + if not os.path.realpath(template_file_path).startswith( + os.path.realpath(TEMPLATES_DIR) + ): return "Invalid template file path" if filename.endswith(".json"): with open(template_file_path, "r", encoding="utf8") as f: lines = json.load(f) lines = [[i["act"], i["prompt"]] for i in lines] else: - with open( - template_file_path, "r", encoding="utf8" - ) as csvfile: + with open(template_file_path, "r", encoding="utf8") as csvfile: reader = csv.reader(csvfile) lines = list(reader) lines = lines[1:] @@ -612,7 +636,9 @@ def get_template_dropdown(): def get_template_content(templates, selection, original_system_prompt): - logging.debug(f"应用模板中，选择为{selection}，原始系统提示为{original_system_prompt}") + logging.debug( + f"应用模板中，选择为{selection}，原始系统提示为{original_system_prompt}" + ) try: return templates[selection] except: @@ -699,7 +725,9 @@ def fetch_ip(): SERVER_GEO_IP_MSG = i18n("您的IP区域：未知。") else: SERVER_GEO_IP_MSG = ( - i18n("获取IP地理位置失败。原因：") + f"{data['reason']}" + i18n("。你仍然可以使用聊天功能。") + i18n("获取IP地理位置失败。原因：") + + f"{data['reason']}" + + i18n("。你仍然可以使用聊天功能。") ) else: country = data["country_name"] @@ -1013,11 +1041,25 @@ class SetupWizard: def __init__(self, file_path="config.json") -> None: self.config = {} self.file_path = file_path - language = input('请问是否需要更改语言？可选："auto", "zh_CN", "en_US", "ja_JP", "ko_KR", "sv_SE", "ru_RU", "vi_VN"\nChange the language? Options: "auto", "zh_CN", "en_US", "ja_JP", "ko_KR", "sv_SE", "ru_RU", "vi_VN"\n目前正在使用中文(zh_CN)\nCurrently using Chinese(zh_CN)\n如果需要，请输入你想用的语言的代码：\nIf you need, please enter the code of the language you want to use:') - if language.lower() in ["auto", "zh_cn", "en_us", "ja_jp", "ko_kr", "sv_se", "ru_ru", "vi_vn"]: + language = input( + '请问是否需要更改语言？可选："auto", "zh_CN", "zh_TW", "en_US", "ja_JP", "ko_KR", "sv_SE", "ru_RU", "vi_VN"\nChange the language? Options: "auto", "zh_CN", "zh_TW", "en_US", "ja_JP", "ko_KR", "sv_SE", "ru_RU", "vi_VN"\n目前正在使用中文(zh_CN)\nCurrently using Chinese(zh_CN)\n如果需要，请输入你想用的语言的代码：\nIf you need, please enter the code of the language you want to use:' + ) + if language.lower() in [ + "auto", + "zh_cn", + "zh_tw", + "en_us", + "ja_jp", + "ko_kr", + "sv_se", + "ru_ru", + "vi_vn", + ]: i18n.change_language(language) else: - print("你没有输入有效的语言代码，将使用默认语言中文(zh_CN)\nYou did not enter a valid language code, the default language Chinese(zh_CN) will be used.") + print( + "你没有输入有效的语言代码，将使用默认语言中文(zh_CN)\nYou did not enter a valid language code, the default language Chinese(zh_CN) will be used." + ) print( i18n("正在进行首次设置，请按照提示进行配置，配置将会被保存在") + colorama.Fore.GREEN @@ -1037,7 +1079,9 @@ def __init__(self, file_path="config.json") -> None: ) print( colorama.Back.GREEN - + i18n("现在开始进行交互式配置。碰到不知道该怎么办的设置项时，请直接按回车键跳过，程序会自动选择合适的默认值。") + + i18n( + "现在开始进行交互式配置。碰到不知道该怎么办的设置项时，请直接按回车键跳过，程序会自动选择合适的默认值。" + ) + colorama.Style.RESET_ALL ) @@ -1076,7 +1120,8 @@ def set(self, config_items: List[ConfigItem], prompt: str): config_value = [] while True: config_value_item = input( - generate_prompt_string(config_item) + i18n("，输入空行结束：") + generate_prompt_string(config_item) + + i18n("，输入空行结束：") ) if config_value_item == "": break @@ -1103,7 +1148,13 @@ def set(self, config_items: List[ConfigItem], prompt: str): def set_users(self): # 询问设置用户账户 - choice = input(colorama.Fore.YELLOW + i18n("是否设置用户账户？设置后，用户需要登陆才可访问。输入 Yes(y) 或 No(n)，默认No：") + colorama.Style.RESET_ALL) + choice = input( + colorama.Fore.YELLOW + + i18n( + "是否设置用户账户？设置后，用户需要登陆才可访问。输入 Yes(y) 或 No(n)，默认No：" + ) + + colorama.Style.RESET_ALL + ) if choice.lower() in ["y", "yes"]: users = [] while True: @@ -1174,7 +1225,9 @@ def setup_wizard(): "是否在本地编制知识库索引？如果是，可以在使用本地模型时离线使用知识库，否则使用OpenAI服务来编制索引（需要OpenAI API Key）。请确保你的电脑有至少16GB内存。本地索引模型需要从互联网下载。", ) print( - colorama.Back.GREEN + i18n("现在开始设置其他在线模型的API Key") + colorama.Style.RESET_ALL + colorama.Back.GREEN + + i18n("现在开始设置其他在线模型的API Key") + + colorama.Style.RESET_ALL ) # Google Palm wizard.set( @@ -1209,7 +1262,9 @@ def setup_wizard(): [ ConfigItem( "midjourney_proxy_api_base", - i18n("你的") + "https://github.com/novicezk/midjourney-proxy" + i18n("代理地址"), + i18n("你的") + + "https://github.com/novicezk/midjourney-proxy" + + i18n("代理地址"), type=ConfigType.String, ), ConfigItem( @@ -1238,7 +1293,9 @@ def setup_wizard(): ConfigItem( "spark_api_secret", "讯飞星火 API Secret", type=ConfigType.Password ), - ConfigItem("spark_api_key", "讯飞星火 API Key", type=ConfigType.Password), + ConfigItem( + "spark_api_key", "讯飞星火 API Key", type=ConfigType.Password + ), ], "是否设置讯飞星火？如果设置，软件启动时会自动加载该API Key，无需在 UI 中手动输入。如果不设置，将无法使用 讯飞星火 模型。请注意不要搞混App ID和API Secret。", ) @@ -1255,10 +1312,14 @@ def setup_wizard(): wizard.set( [ ConfigItem( - "ernie_api_key", "百度云中的文心一言 API Key", type=ConfigType.Password + "ernie_api_key", + "百度云中的文心一言 API Key", + type=ConfigType.Password, ), ConfigItem( - "ernie_secret_key", "百度云中的文心一言 Secret Key", type=ConfigType.Password + "ernie_secret_key", + "百度云中的文心一言 Secret Key", + type=ConfigType.Password, ), ], "是否设置文心一言？如果设置，软件启动时会自动加载该API Key，无需在 UI 中手动输入。如果不设置，将无法使用 文心一言 模型。", @@ -1300,7 +1361,9 @@ def setup_wizard(): "是否设置 Azure OpenAI？如果设置，软件启动时会自动加载该API Key，无需在 UI 中手动输入。如果不设置，将无法使用 Azure OpenAI 模型。", ) print( - colorama.Back.GREEN + i18n("现在开始进行软件功能设置") + colorama.Style.RESET_ALL + colorama.Back.GREEN + + i18n("现在开始进行软件功能设置") + + colorama.Style.RESET_ALL ) # 用户列表 wizard.set_users() @@ -1319,7 +1382,10 @@ def setup_wizard(): wizard.set( [ ConfigItem( - "check_update", "是否启用检查更新", type=ConfigType.Bool, default=True + "check_update", + "是否启用检查更新", + type=ConfigType.Bool, + default=True, ) ], "是否启用检查更新？如果设置，软件启动时会自动检查更新。", @@ -1493,20 +1559,34 @@ def setup_wizard(): "是否通过gradio分享？可以通过公网访问。", ) wizard.save() - print(colorama.Back.GREEN + i18n("设置完成。现在请重启本程序。") + colorama.Style.RESET_ALL) + print( + colorama.Back.GREEN + + i18n("设置完成。现在请重启本程序。") + + colorama.Style.RESET_ALL + ) exit() def reboot_chuanhu(): import sys + print(colorama.Back.GREEN + i18n("正在尝试重启...") + colorama.Style.RESET_ALL) os.execl(sys.executable, sys.executable, *sys.argv) def setPlaceholder(model_name: str | None = "", model: BaseLLMModel | None = None): from .webui import get_html + logo_class, slogan_class, question_class = "", "", "" - model_logo, model_logo_round, model_slogan, model_question_1, model_question_2, model_question_3, model_question_4 = "", "", "", "", "", "", "" + ( + model_logo, + model_logo_round, + model_slogan, + model_question_1, + model_question_2, + model_question_3, + model_question_4, + ) = ("", "", "", "", "", "", "") if model is None: try: @@ -1522,10 +1602,18 @@ def setPlaceholder(model_name: str | None = "", model: BaseLLMModel | None = Non except: slogan_class = "hideK" try: - model_question_1 = i18n(MODEL_METADATA[model_name]["placeholder"]["question_1"]) - model_question_2 = i18n(MODEL_METADATA[model_name]["placeholder"]["question_2"]) - model_question_3 = i18n(MODEL_METADATA[model_name]["placeholder"]["question_3"]) - model_question_4 = i18n(MODEL_METADATA[model_name]["placeholder"]["question_4"]) + model_question_1 = i18n( + MODEL_METADATA[model_name]["placeholder"]["question_1"] + ) + model_question_2 = i18n( + MODEL_METADATA[model_name]["placeholder"]["question_2"] + ) + model_question_3 = i18n( + MODEL_METADATA[model_name]["placeholder"]["question_3"] + ) + model_question_4 = i18n( + MODEL_METADATA[model_name]["placeholder"]["question_4"] + ) except: question_class = "hideK" else: @@ -1553,19 +1641,27 @@ def setPlaceholder(model_name: str | None = "", model: BaseLLMModel | None = Non return "" else: # 除非明确指定为 squared 或 false 等，否则默认为圆角 - if model_logo_round.lower().strip() not in ["square", "squared", "false", "0", "no", "off"]: + if model_logo_round.lower().strip() not in [ + "square", + "squared", + "false", + "0", + "no", + "off", + ]: logo_class += " rounded" return get_html("chatbot_placeholder.html").format( - chatbot_ph_logo = model_logo, - chatbot_ph_slogan = model_slogan, - chatbot_ph_question_1 = model_question_1, - chatbot_ph_question_2 = model_question_2, - chatbot_ph_question_3 = model_question_3, - chatbot_ph_question_4 = model_question_4, - chatbot_ph_logo_class = logo_class, - chatbot_ph_slogan_class = slogan_class, - chatbot_ph_question_class = question_class + chatbot_ph_logo=model_logo, + chatbot_ph_slogan=model_slogan, + chatbot_ph_question_1=model_question_1, + chatbot_ph_question_2=model_question_2, + chatbot_ph_question_3=model_question_3, + chatbot_ph_question_4=model_question_4, + chatbot_ph_logo_class=logo_class, + chatbot_ph_slogan_class=slogan_class, + chatbot_ph_question_class=question_class, ) + def download_file(path): print(path) diff --git a/run_Linux.sh b/run_Linux.sh old mode 100644 new mode 100755 diff --git a/run_Windows.bat b/run_Windows.bat old mode 100644 new mode 100755 diff --git a/run_macOS.command b/run_macOS.command old mode 100644 new mode 100755