JohnSmith9982/ChuanhuChatGPT

.gitattributes

@@ -0,0 +1,34 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -1,146 +0,0 @@
-# Byte-compiled / optimized / DLL files
-__pycache__/
-*.py[cod]
-*$py.class
-
-# C extensions
-*.so
-
-# Distribution / packaging
-.Python
-build/
-develop-eggs/
-dist/
-downloads/
-eggs/
-.eggs/
-lib/
-lib64/
-parts/
-sdist/
-var/
-wheels/
-pip-wheel-metadata/
-share/python-wheels/
-*.egg-info/
-.installed.cfg
-*.egg
-MANIFEST
-history/
-index/
-
-# PyInstaller
-#  Usually these files are written by a python script from a template
-#  before PyInstaller builds the exe, so as to inject date/other infos into it.
-*.manifest
-*.spec
-
-# Installer logs
-pip-log.txt
-pip-delete-this-directory.txt
-
-# Unit test / coverage reports
-htmlcov/
-.tox/
-.nox/
-.coverage
-.coverage.*
-.cache
-nosetests.xml
-coverage.xml
-*.cover
-*.py,cover
-.hypothesis/
-.pytest_cache/
-
-# Translations
-*.mo
-*.pot
-
-# Django stuff:
-*.log
-local_settings.py
-db.sqlite3
-db.sqlite3-journal
-
-# Flask stuff:
-instance/
-.webassets-cache
-
-# Scrapy stuff:
-.scrapy
-
-# Sphinx documentation
-docs/_build/
-
-# PyBuilder
-target/
-
-# Jupyter Notebook
-.ipynb_checkpoints
-
-# IPython
-profile_default/
-ipython_config.py
-
-# pyenv
-.python-version
-
-# pipenv
-#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
-#   However, in case of collaboration, if having platform-specific dependencies or dependencies
-#   having no cross-platform support, pipenv may install dependencies that don't work, or not
-#   install all needed dependencies.
-#Pipfile.lock
-
-# PEP 582; used by e.g. github.com/David-OConnor/pyflow
-__pypackages__/
-
-# Celery stuff
-celerybeat-schedule
-celerybeat.pid
-
-# SageMath parsed files
-*.sage.py
-
-# Environments
-.env
-.venv
-env/
-venv/
-ENV/
-env.bak/
-venv.bak/
-
-# Spyder project settings
-.spyderproject
-.spyproject
-
-# Rope project settings
-.ropeproject
-
-# mkdocs documentation
-/site
-
-# mypy
-.mypy_cache/
-.dmypy.json
-dmypy.json
-
-# Pyre type checker
-.pyre/
-
-# Mac system file
-**/.DS_Store
-
-#vscode
-.vscode
-
-# 配置文件/模型文件
-api_key.txt
-config.json
-auth.json
-.models/
-lora/
-.idea
-templates/*

CITATION.cff

@@ -1,5 +1,5 @@
 cff-version: 1.2.0
-title: Chuanhu Chat
+title: ChuanhuChatGPT
 message: >-
   If you use this software, please cite it using these
   metadata.
@@ -13,8 +13,8 @@ authors:
     orcid: https://orcid.org/0009-0005-0357-272X
 repository-code: 'https://github.com/GaiZhenbiao/ChuanhuChatGPT'
 url: 'https://github.com/GaiZhenbiao/ChuanhuChatGPT'
-abstract: This software provides a light and easy-to-use interface for ChatGPT API and many LLMs.
+abstract: Provided a light and easy to use interface for ChatGPT API
 license: GPL-3.0
-commit: c6c08bc62ef80e37c8be52f65f9b6051a7eea1fa
-version: '20230709'
-date-released: '2023-07-09'
+commit: bd0034c37e5af6a90bd9c2f7dd073f6cd27c61af
+version: '20230405'
+date-released: '2023-04-05'

ChuanhuChatbot.py

@@ -38,26 +38,17 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
         status_display = gr.Markdown(get_geoip(), elem_id="status_display")
     with gr.Row(elem_id="float_display"):
         user_info = gr.Markdown(value="getting user info...", elem_id="user_info")
-        update_info = gr.HTML(get_html("update.html").format(
-            current_version=repo_html(),
-            version_time=version_time(),
-            cancel_btn=i18n("取消"),
-            update_btn=i18n("更新"),
-            seenew_btn=i18n("详情"),
-            ok_btn=i18n("好"),
-            ), visible=check_update)
-
-    with gr.Row(equal_height=True):
+
+    with gr.Row().style(equal_height=True):
         with gr.Column(scale=5):
             with gr.Row():
-                chatbot = gr.Chatbot(label="Chuanhu Chat", elem_id="chuanhu_chatbot", latex_delimiters=latex_delimiters_set, height=700)
+                chatbot = gr.Chatbot(label="Chuanhu Chat", elem_id="chuanhu_chatbot").style(height="100%")
             with gr.Row():
                 with gr.Column(min_width=225, scale=12):
                     user_input = gr.Textbox(
                         elem_id="user_input_tb",
-                        show_label=False, placeholder=i18n("在这里输入"),
-                        container=False
-                    )
+                        show_label=False, placeholder=i18n("在这里输入")
+                    ).style(container=False)
                 with gr.Column(min_width=42, scale=1):
                     submitBtn = gr.Button(value="", variant="primary", elem_id="submit_btn")
                     cancelBtn = gr.Button(value="", variant="secondary", visible=False, elem_id="cancel_btn")
@@ -86,9 +77,9 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                         label="API-Key",
                     )
                     if multi_api_key:
-                        usageTxt = gr.Markdown(i18n("多账号模式已开启，无需输入key，可直接开始对话"), elem_id="usage_display", elem_classes="insert_block", visible=show_api_billing)
+                        usageTxt = gr.Markdown(i18n("多账号模式已开启，无需输入key，可直接开始对话"), elem_id="usage_display", elem_classes="insert_block")
                     else:
-                        usageTxt = gr.Markdown(i18n("**发送消息** 或 **提交key** 以显示额度"), elem_id="usage_display", elem_classes="insert_block", visible=show_api_billing)
+                        usageTxt = gr.Markdown(i18n("**发送消息** 或 **提交key** 以显示额度"), elem_id="usage_display", elem_classes="insert_block")
                     model_select_dropdown = gr.Dropdown(
                         label=i18n("选择模型"), choices=MODELS, multiselect=False, value=MODELS[DEFAULT_MODEL], interactive=True
                     )
@@ -96,8 +87,8 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                         label=i18n("选择LoRA模型"), choices=[], multiselect=False, interactive=True, visible=False
                     )
                     with gr.Row():
-                        single_turn_checkbox = gr.Checkbox(label=i18n("单轮对话"), value=False, elem_classes="switch_checkbox")
-                        use_websearch_checkbox = gr.Checkbox(label=i18n("使用在线搜索"), value=False, elem_classes="switch_checkbox")
+                        single_turn_checkbox = gr.Checkbox(label=i18n("单轮对话"), value=False)
+                        use_websearch_checkbox = gr.Checkbox(label=i18n("使用在线搜索"), value=False)
                     language_select_dropdown = gr.Dropdown(
                         label=i18n("选择回复语言（针对搜索&索引功能）"),
                         choices=REPLY_LANGUAGES,
@@ -116,8 +107,8 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                         placeholder=i18n("在这里输入System Prompt..."),
                         label="System prompt",
                         value=INITIAL_SYSTEM_PROMPT,
-                        lines=10
-                    )
+                        lines=10,
+                    ).style(container=False)
                     with gr.Accordion(label=i18n("加载Prompt模板"), open=True):
                         with gr.Column():
                             with gr.Row():
@@ -127,8 +118,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                                         choices=get_template_names(plain=True),
                                         multiselect=False,
                                         value=get_template_names(plain=True)[0],
-                                        container=False,
-                                    )
+                                    ).style(container=False)
                                 with gr.Column(scale=1):
                                     templateRefreshBtn = gr.Button(i18n("🔄 刷新"))
                             with gr.Row():
@@ -139,8 +129,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                                             get_template_names(plain=True)[0], mode=1
                                         ),
                                         multiselect=False,
-                                        container=False,
-                                    )
+                                    ).style(container=False)
 
                 with gr.Tab(label=i18n("保存/加载")):
                     with gr.Accordion(label=i18n("保存/加载对话历史记录"), open=True):
@@ -150,14 +139,10 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                                     historyFileSelectDropdown = gr.Dropdown(
                                         label=i18n("从列表中加载对话"),
                                         choices=get_history_names(plain=True),
-                                        multiselect=False,
-                                        container=False,
+                                        multiselect=False
                                     )
-                                with gr.Row():
-                                    with gr.Column(min_width=42, scale=1):
-                                        historyRefreshBtn = gr.Button(i18n("🔄 刷新"))
-                                    with gr.Column(min_width=42, scale=1):
-                                        historyDeleteBtn = gr.Button(i18n("🗑️ 删除"))
+                                with gr.Column(scale=1):
+                                    historyRefreshBtn = gr.Button(i18n("🔄 刷新"))
                             with gr.Row():
                                 with gr.Column(scale=6):
                                     saveFileName = gr.Textbox(
@@ -165,8 +150,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                                         placeholder=i18n("设置文件名: 默认为.json，可选为.md"),
                                         label=i18n("设置保存文件名"),
                                         value=i18n("对话历史记录"),
-                                        container=False,
-                                    )
+                                    ).style(container=True)
                                 with gr.Column(scale=1):
                                     saveHistoryBtn = gr.Button(i18n("💾 保存对话"))
                                     exportMarkdownBtn = gr.Button(i18n("📝 导出为Markdown"))
@@ -176,12 +160,11 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                                     downloadFile = gr.File(interactive=True)
 
                 with gr.Tab(label=i18n("高级")):
+                    gr.Markdown(i18n("# ⚠️ 务必谨慎更改 ⚠️\n\n如果无法使用请恢复默认设置"))
                     gr.HTML(get_html("appearance_switcher.html").format(label=i18n("切换亮暗色主题")), elem_classes="insert_block")
                     use_streaming_checkbox = gr.Checkbox(
-                            label=i18n("实时传输回答"), value=True, visible=ENABLE_STREAMING_OPTION, elem_classes="switch_checkbox"
+                            label=i18n("实时传输回答"), value=True, visible=ENABLE_STREAMING_OPTION
                         )
-                    checkUpdateBtn = gr.Button(i18n("🔄 检查更新..."), visible=check_update)
-                    gr.Markdown(i18n("# ⚠️ 务必谨慎更改 ⚠️"), elem_id="advanced_warning")
                     with gr.Accordion(i18n("参数"), open=False):
                         temperature_slider = gr.Slider(
                             minimum=-0,
@@ -209,7 +192,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                         )
                         stop_sequence_txt = gr.Textbox(
                             show_label=True,
-                            placeholder=i18n("停止符，用英文逗号隔开..."),
+                            placeholder=i18n("在这里输入停止符，用英文逗号隔开..."),
                             label="stop",
                             value="",
                             lines=1,
@@ -261,7 +244,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                             lines=1,
                         )
 
-                    with gr.Accordion(i18n("网络设置"), open=False):
+                    with gr.Accordion(i18n("网络设置"), open=False, visible=False):
                         # 优先展示自定义的api_host
                         apihostTxt = gr.Textbox(
                             show_label=True,
@@ -269,7 +252,6 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                             label="API-Host",
                             value=config.api_host or shared.API_HOST,
                             lines=1,
-                            container=False,
                         )
                         changeAPIURLBtn = gr.Button(i18n("🔄 切换API地址"))
                         proxyTxt = gr.Textbox(
@@ -278,7 +260,6 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                             label=i18n("代理地址（示例：http://127.0.0.1:10809）"),
                             value="",
                             lines=2,
-                            container=False,
                         )
                         changeProxyBtn = gr.Button(i18n("🔄 设置代理地址"))
                         default_btn = gr.Button(i18n("🔙 恢复默认设置"))
@@ -342,10 +323,6 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
         outputs=[saveFileName, systemPromptTxt, chatbot]
     )
 
-    refresh_history_args = dict(
-        fn=get_history_names, inputs=[gr.State(False), user_name], outputs=[historyFileSelectDropdown]
-    )
-
 
     # Chatbot
     cancelBtn.click(interrupt, [current_model], [])
@@ -364,7 +341,6 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
         inputs=[current_model],
         outputs=[chatbot, status_display],
         show_progress=True,
-        _js='()=>{clearHistoryHtml();}',
     )
 
     retryBtn.click(**start_outputing_args).then(
@@ -415,7 +391,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
     keyTxt.change(set_key, [current_model, keyTxt], [user_api_key, status_display], api_name="set_key").then(**get_usage_args)
     keyTxt.submit(**get_usage_args)
     single_turn_checkbox.change(set_single_turn, [current_model, single_turn_checkbox], None)
-    model_select_dropdown.change(get_model, [model_select_dropdown, lora_select_dropdown, user_api_key, temperature_slider, top_p_slider, systemPromptTxt, user_name], [current_model, status_display, chatbot, lora_select_dropdown, user_api_key, keyTxt], show_progress=True, api_name="get_model")
+    model_select_dropdown.change(get_model, [model_select_dropdown, lora_select_dropdown, user_api_key, temperature_slider, top_p_slider, systemPromptTxt, user_name], [current_model, status_display, chatbot, lora_select_dropdown], show_progress=True, api_name="get_model")
     model_select_dropdown.change(toggle_like_btn_visibility, [model_select_dropdown], [like_dislike_area], show_progress=False)
     lora_select_dropdown.change(get_model, [model_select_dropdown, lora_select_dropdown, user_api_key, temperature_slider, top_p_slider, systemPromptTxt, user_name], [current_model, status_display, chatbot], show_progress=True)
 
@@ -449,8 +425,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
         downloadFile,
         show_progress=True,
     )
-    historyRefreshBtn.click(**refresh_history_args)
-    historyDeleteBtn.click(delete_chat_history, [current_model, historyFileSelectDropdown, user_name], [status_display, historyFileSelectDropdown, chatbot], _js='(a,b,c)=>{return showConfirmationDialog(a, b, c);}')
+    historyRefreshBtn.click(get_history_names, [gr.State(False), user_name], [historyFileSelectDropdown])
     historyFileSelectDropdown.change(**load_history_from_file_args)
     downloadFile.change(upload_chat_history, [current_model, downloadFile, user_name], [saveFileName, systemPromptTxt, chatbot])
 
@@ -481,7 +456,6 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
         [status_display],
         show_progress=True,
     )
-    checkUpdateBtn.click(fn=None, _js='()=>{manualCheckUpdate();}')
 
 logging.info(
     colorama.Back.GREEN

Dockerfile

@@ -1,18 +1,15 @@
-FROM python:3.9-slim-buster as builder
-RUN apt-get update \
-    && apt-get install -y build-essential \
-    && apt-get clean \
-    && rm -rf /var/lib/apt/lists/*
+FROM python:3.9 as builder
+RUN apt-get update && apt-get install -y build-essential
 COPY requirements.txt .
 COPY requirements_advanced.txt .
-RUN pip install --user --no-cache-dir -r requirements.txt
-# RUN pip install --user --no-cache-dir -r requirements_advanced.txt
+RUN pip install --user -r requirements.txt
+# RUN pip install --user -r requirements_advanced.txt
 
-FROM python:3.9-slim-buster
-LABEL maintainer="iskoldt"
+FROM python:3.9
+MAINTAINER iskoldt
 COPY --from=builder /root/.local /root/.local
 ENV PATH=/root/.local/bin:$PATH
 COPY . /app
 WORKDIR /app
-ENV dockerrun=yes
-CMD ["python3", "-u", "ChuanhuChatbot.py","2>&1", "|", "tee", "/var/log/application.log"]
+ENV dockerrun yes
+CMD ["python3", "-u", "ChuanhuChatbot.py", "2>&1", "|", "tee", "/var/log/application.log"]

README.md

@@ -4,10 +4,11 @@ emoji: 🐯
 colorFrom: green
 colorTo: red
 sdk: gradio
-sdk_version: 3.36.1
+sdk_version: 3.33.1
 app_file: ChuanhuChatbot.py
 pinned: false
 license: gpl-3.0
+duplicated_from: JohnSmith9982/ChuanhuChatGPT
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

README_origin.md

@@ -1,142 +0,0 @@
-<div align="right">
-  <!-- 语言: -->
-  简体中文 | <a title="English" href="./readme/README_en.md">English</a> | <a title="Japanese" href="./readme/README_ja.md">日本語</a>
-</div>
-
-<h1 align="center">川虎 Chat 🐯 Chuanhu Chat</h1>
-<div align="center">
-  <a href="https://github.com/GaiZhenBiao/ChuanhuChatGPT">
-    <img src="https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/70903329/aca3a7ec-4f1d-4667-890c-a6f47bf08f63" alt="Logo" height="156">
-  </a>
-
-<p align="center">
-    <h3>为ChatGPT等多种LLM提供了一个轻快好用的Web图形界面和众多附加功能</h3>
-    <p align="center">
-      <a href="https://github.com/GaiZhenbiao/ChuanhuChatGPT/blob/main/LICENSE">
-        <img alt="Tests Passing" src="https://img.shields.io/github/license/GaiZhenbiao/ChuanhuChatGPT" />
-      </a>
-      <a href="https://gradio.app/">
-        <img alt="GitHub Contributors" src="https://img.shields.io/badge/Base-Gradio-fb7d1a?style=flat" />
-      </a>
-      <a href="https://t.me/tkdifferent">
-        <img alt="GitHub pull requests" src="https://img.shields.io/badge/Telegram-Group-blue.svg?logo=telegram" />
-      </a>
-      <p>
-        流式传输 / 无限对话 / 保存对话 / 预设Prompt集 / 联网搜索 / 根据文件回答 <br />
-        渲染LaTeX / 渲染表格 / 代码高亮 / 自动亮暗色切换 / 自适应界面 / “小而美”的体验 <br />
-        自定义api-Host / 多参数可调 / 多API Key均衡负载 / 多用户显示 / 适配GPT-4 / 支持本地部署LLM
-      </p>
-      <a href="https://www.bilibili.com/video/BV1mo4y1r7eE"><strong>视频教程</strong></a>
-        ·
-      <a href="https://www.bilibili.com/video/BV1184y1w7aP"><strong>2.0介绍视频</strong></a>
-	||
-      <a href="https://huggingface.co/spaces/JohnSmith9982/ChuanhuChatGPT"><strong>在线体验</strong></a>
-      	·
-      <a href="https://huggingface.co/login?next=%2Fspaces%2FJohnSmith9982%2FChuanhuChatGPT%3Fduplicate%3Dtrue"><strong>一键部署</strong></a>
-    </p>
-    <p align="center">
-      <img alt="Animation Demo" src="https://user-images.githubusercontent.com/51039745/226255695-6b17ff1f-ea8d-464f-b69b-a7b6b68fffe8.gif" />
-    </p>
-  </p>
-</div>
-
-## 目录
-
-| [支持模型](#支持模型) | [使用技巧](#使用技巧) | [安装方式](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用教程) | [常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题) | [给作者买可乐🥤](#捐款) |
-| ------------------ | ------------------ | -------------------------------------------------------------------- | -------------------------------------------------------------------- | -------------------- |
-
-## 支持模型
-
-**通过API调用的语言模型**：
-
-- [ChatGPT](https://chat.openai.com) ([GPT-4](https://openai.com/product/gpt-4))
-- [Google PaLM](https://developers.generativeai.google/products/palm)
-- [Inspur Yuan 1.0](https://air.inspur.com/home)
-- [MiniMax](https://api.minimax.chat/)
-- [XMChat](https://github.com/MILVLG/xmchat)
-
-**本地部署语言模型**：
-
-- [ChatGLM](https://github.com/THUDM/ChatGLM-6B) ([ChatGLM2](https://github.com/THUDM/ChatGLM2-6B))
-- [LLaMA](https://github.com/facebookresearch/llama)
-- [StableLM](https://github.com/Stability-AI/StableLM)
-- [MOSS](https://github.com/OpenLMLab/MOSS)
-
-## 使用技巧
-
-- 使用System Prompt可以很有效地设定前提条件。
-- 使用Prompt模板功能时，选择Prompt模板集合文件，然后从下拉菜单中选择想要的prompt。
-- 如果回答不满意，可以使用 `重新生成`按钮再试一次
-- 输入框支持换行，按 `shift enter`即可。
-- 可以在输入框按上下箭头在输入历史之间切换
-- 部署到服务器：在 `config.json` 中设置 `"server_name": "0.0.0.0", "server_port": <你的端口号>,`。
-- 获取公共链接：在 `config.json` 中设置 `"share": true,`。注意程序必须在运行，才能通过公共链接访问。
-- 在Hugging Face上使用：建议在右上角 **复制Space** 再使用，这样App反应可能会快一点。
-
-## 快速上手
-
-```shell
-git clone https://github.com/GaiZhenbiao/ChuanhuChatGPT.git
-cd ChuanhuChatGPT
-pip install -r requirements.txt
-```
-
-然后，在项目文件夹中复制一份 `config_example.json`，并将其重命名为 `config.json`，在其中填入 `API-Key` 等设置。
-
-```shell
-python ChuanhuChatbot.py
-```
-
-一个浏览器窗口将会自动打开，此时您将可以使用 **川虎Chat** 与ChatGPT或其他模型进行对话。
-
-> **Note**
->
-> 具体详尽的安装教程和使用教程请查看[本项目的wiki页面](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用教程)。
-
-## 疑难杂症解决
-
-在遇到各种问题查阅相关信息前，您可以先尝试手动拉取本项目的最新更改并更新依赖库，然后重试。步骤为：
-
-1. 点击网页上的 `Download ZIP` 下载最新代码，或
-   ```shell
-   git pull https://github.com/GaiZhenbiao/ChuanhuChatGPT.git main -f
-   ```
-2. 尝试再次��装依赖（可能本项目引入了新的依赖）
-   ```
-   pip install -r requirements.txt
-   ```
-
-很多时候，这样就可以解决问题。
-
-如果问题仍然存在，请查阅该页面：[常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题)
-
-该页面列出了**几乎所有**您可能遇到的各种问题，包括如何配置代理，以及遇到问题后您该采取的措施，**请务必认真阅读**。
-
-## 了解更多
-
-若需了解更多信息，请查看我们的 [wiki](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki)：
-
-- [想要做出贡献？](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/贡献指南)
-- [项目更新情况？](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/更新日志)
-- [二次开发许可？](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用许可)
-- [如何引用项目？](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用许可#如何引用该项目)
-
-## Starchart
-
-[![Star History Chart](https://api.star-history.com/svg?repos=GaiZhenbiao/ChuanhuChatGPT&type=Date)](https://star-history.com/#GaiZhenbiao/ChuanhuChatGPT&Date)
-
-## Contributors
-
-<a href="https://github.com/GaiZhenbiao/ChuanhuChatGPT/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=GaiZhenbiao/ChuanhuChatGPT" />
-</a>
-
-## 捐款
-
-🐯如果觉得这个软件对你有所帮助，欢迎请作者喝可乐、喝咖啡～
-
-联系作者：请去[我的bilibili账号](https://space.bilibili.com/29125536)私信我。
-
-<a href="https://www.buymeacoffee.com/ChuanhuChat" ><img src="https://img.buymeacoffee.com/button-api/?text=Buy me a coffee&emoji=&slug=ChuanhuChat&button_colour=219d53&font_colour=ffffff&font_family=Poppins&outline_colour=ffffff&coffee_colour=FFDD00" alt="Buy Me A Coffee" width="250"></a>
-
-<img width="250" alt="image" src="https://user-images.githubusercontent.com/51039745/226920291-e8ec0b0a-400f-4c20-ac13-dafac0c3aeeb.JPG">

assets/Kelpy-Codos.js

@@ -0,0 +1,76 @@
+// ==UserScript==
+// @name         Kelpy Codos
+// @namespace    https://github.com/Keldos-Li/Kelpy-Codos
+// @version      1.0.5
+// @author       Keldos; https://keldos.me/
+// @description  Add copy button to PRE tags before CODE tag, for Chuanhu ChatGPT especially. 
+//               Based on Chuanhu ChatGPT version: ac04408 (2023-3-22)
+// @license      GPL-3.0
+// @grant        none
+// ==/UserScript==
+
+(function () {
+    'use strict';
+
+    function addCopyButton(pre) {
+        var code = pre.querySelector('code');
+        if (!code) {
+            return; // 如果没有找到 <code> 元素，则不添加按钮
+        }
+        var firstChild = code.firstChild;
+        if (!firstChild) {
+            return; // 如果 <code> 元素没有子节点，则不添加按钮
+        }
+        var button = document.createElement('button');
+        button.textContent = '\uD83D\uDCCE'; // 使用 📎 符号作为“复制”按钮的文本
+        button.style.position = 'relative';
+        button.style.float = 'right';
+        button.style.fontSize = '1em'; // 可选：调整按钮大小
+        button.style.background = 'none'; // 可选：去掉背景颜色
+        button.style.border = 'none'; // 可选：去掉边框
+        button.style.cursor = 'pointer'; // 可选：显示指针样式
+        button.addEventListener('click', function () {
+            var range = document.createRange();
+            range.selectNodeContents(code);
+            range.setStartBefore(firstChild); // 将范围设置为第一个子节点之前
+            var selection = window.getSelection();
+            selection.removeAllRanges();
+            selection.addRange(range);
+
+            try {
+                var success = document.execCommand('copy');
+                if (success) {
+                    button.textContent = '\u2714';
+                    setTimeout(function () {
+                        button.textContent = '\uD83D\uDCCE'; // 恢复按钮为“复制”
+                    }, 2000);
+                } else {
+                    button.textContent = '\u2716';
+                }
+            } catch (e) {
+                console.error(e);
+                button.textContent = '\u2716';
+            }
+
+            selection.removeAllRanges();
+        });
+        code.insertBefore(button, firstChild); // 将按钮插入到第一个子元素之前
+    }
+
+    function handleNewElements(mutationsList, observer) {
+        for (var mutation of mutationsList) {
+            if (mutation.type === 'childList') {
+                for (var node of mutation.addedNodes) {
+                    if (node.nodeName === 'PRE') {
+                        addCopyButton(node);
+                    }
+                }
+            }
+        }
+    }
+
+    var observer = new MutationObserver(handleNewElements);
+    observer.observe(document.documentElement, { childList: true, subtree: true });
+
+    document.querySelectorAll('pre').forEach(addCopyButton);
+})();

assets/custom.css

@@ -7,11 +7,8 @@
     --message-user-background-color-dark: #26B561;
     --message-bot-background-color-light: #FFFFFF;
     --message-bot-background-color-dark: #2C2C2C;
-    --switch-checkbox-color-light: #e5e7eb;
-    --switch-checkbox-color-dark: #515151;
 }
 
-
 #app_title {
     font-weight: var(--prose-header-text-weight);
     font-size: var(--text-xxl);
@@ -25,19 +22,6 @@
     margin: 32px 0 4px 0;
 }
 
-/* 解决container=False时的错误填充 */
-div.form {
-    background: none !important;
-}
-
-/* 高级页面 */
-#advanced_warning {
-    display: flex;
-    flex-wrap: wrap;
-    flex-direction: column;
-    align-content: center;
-}
-
 /* gradio的页脚信息 */
 footer {
     /* display: none !important; */
@@ -59,74 +43,21 @@ footer {
     position: absolute;
     max-height: 30px;
 }
-#toast-update {
-    position: absolute;
-    display: flex;
-    top: -500px;
-    width: 100%;
-    justify-content: center;
-    z-index: var(--layer-top);
-    transition: top 0.3s ease-out;
-}
-#check-chuanhu-update {
-    position: absolute;
-    align-items: center;
-    display: flex;
-    flex-direction: column;
-    justify-content: center;
-    margin: var(--size-6) var(--size-4);
-    box-shadow: var(--shadow-drop-lg);
-    border: 1px solid var(--block-label-border-color);
-    border-radius: var(--container-radius);
-    background: var(--background-fill-primary);
-    padding: var(--size-4) var(--size-6);
-    min-width: 360px;
-    max-width: 480px;
-    overflow: hidden;
-    pointer-events: auto;
-}
-#version-info-title {
-    font-size: 1.2em;
-    font-weight: bold;
-    text-align: start;
-    width: 100%;
-}
-#release-note-wrap {
-    width: 100%;
-    max-width: 400px;
-    height: 120px;
-    border: solid 1px var(--border-color-primary);
-    overflow: auto;
-    padding: 0 8px;
-}
-#release-note-wrap.hideK {
-    display: none;
-}
-.btn-update-group {
-    display: flex;
-    justify-content: space-evenly;
-    align-items: center;
-    width: 100%;
-    padding-top: 10px;
-}
-.btn-update-group.hideK {
-    display: none;
-}
 /* user_info */
-#user_info.block {
+#user_info {
     white-space: nowrap;
-    position: absolute; left: 8em; top: .8em;
+    position: absolute; left: 8em; top: .2em;
     z-index: var(--layer-2);
     box-shadow: var(--block-shadow);
-    border: none!important; border-radius: var(--block-label-radius);
+    border: none; border-radius: var(--block-label-radius);
     background: var(--color-accent);
     padding: var(--block-label-padding);
     font-size: var(--block-label-text-size); line-height: var(--line-sm);
-    width: auto; max-height: 30px!important;
+    width: auto; min-height: 30px!important;
     opacity: 1;
     transition: opacity 0.3s ease-in-out;
 }
-#user_info.block .wrap {
+#user_info .wrap {
     opacity: 0;
 }
 #user_info p {
@@ -163,7 +94,7 @@ footer {
 .insert_block {
     position: relative;
     margin: 0;
-    padding: 8px 12px;
+    padding: .5em 1em;
     box-shadow: var(--block-shadow);
     border-width: var(--block-border-width);
     border-color: var(--block-border-color);
@@ -201,42 +132,13 @@ footer {
     line-height: 20px;
 }
 
-/* 亮暗色模式切换 */
-#apSwitch input[type="checkbox"] {
-    margin: 0 !important;
-}
-#apSwitch label.apSwitch {
-    display: flex;
-    align-items: center;
-    cursor: pointer;
-    color: var(--body-text-color);
-    font-weight: var(--checkbox-label-text-weight);
-    font-size: var(--checkbox-label-text-size);
-    line-height: var(--line-md);
-    margin: 2px 0 !important;
-}
-input[type="checkbox"]#apSwitch_checkbox::before {
-    background: none !important;
-    content: '🌞';
-    border: none !important;
-    box-shadow: none !important;
-    font-size: 22px;
-    top: -4.4px;
-    left: -1px;
-}
-input:checked[type="checkbox"]#apSwitch_checkbox::before {
-    content: '🌚';
-    left: 16px;
-}
-
-/* .apSwitch {
+.apSwitch {
     top: 2px;
     display: inline-block;
-    height: 22px;
+    height: 24px;
     position: relative;
-    width: 40px;
-    border-radius: 11px;
-    box-shadow: inset 0 0 1px 0 rgba(0,0,0,0.05), inset 0 0 2px 0 rgba(0,0,0,0.08) !important;
+    width: 48px;
+    border-radius: 12px;
 }
 .apSwitch input {
     display: none !important;
@@ -250,11 +152,12 @@ input:checked[type="checkbox"]#apSwitch_checkbox::before {
     right: 0;
     top: 0;
     transition: .4s;
-    font-size: 22px;
-    border-radius: 11px;
+    font-size: 18px;
+    border-radius: 12px;
 }
 .apSlider::before {
-    transform: scale(0.9);
+    bottom: -1.5px;
+    left: 1px;
     position: absolute;
     transition: .4s;
     content: "🌞";
@@ -263,63 +166,8 @@ input:checked + .apSlider {
     background-color: var(--primary-600);
 }
 input:checked + .apSlider::before {
-    transform: translateX(18px);
+    transform: translateX(23px);
     content:"🌚";
-} */
-
-.switch_checkbox label {
-    flex-direction: row-reverse;
-    justify-content: space-between;
-}
-.switch_checkbox input[type="checkbox"] + span {
-    margin-left: 0 !important;
-}
-
-.switch_checkbox input[type="checkbox"] {
-    -moz-appearance: none;
-    appearance: none;
-    -webkit-appearance: none;
-    outline: none;
-}
-
-.switch_checkbox input[type="checkbox"] {
-    display: inline-block !important;
-    position: relative !important;
-    border: none !important;
-    outline: none;
-    width: 40px !important;
-    height: 22px !important;
-    border-radius: 11px !important;
-    background-image: none !important;
-    box-shadow: inset 0 0 1px 0 rgba(0,0,0,0.05), inset 0 0 2px 0 rgba(0,0,0,0.08) !important;
-    background-image: none !important;
-    background-color: var(--switch-checkbox-color-light) !important;
-    transition: .2s ease background-color;
-}
-.dark .switch_checkbox input[type="checkbox"] {
-    background-color: var(--switch-checkbox-color-dark) !important;
-}
-.switch_checkbox input[type="checkbox"]::before {
-    content: "";
-    position: absolute;
-    width: 22px;
-    height: 22px;
-    top: 0;
-    left: 0;
-    background: #FFFFFF;
-    border: 0.5px solid rgba(0,0,0,0.02);
-    box-shadow: 0 0 0 0 rgba(0,0,0,0.15), 0 1px 0 0 rgba(0,0,0,0.05);
-    transform: scale(0.9);
-    border-radius: 11px !important;
-    transition: .4s ease all;
-    box-shadow: var(--input-shadow);
-}
-.switch_checkbox input:checked[type="checkbox"] {
-    background-color: var(--primary-600) !important;
-}
-.switch_checkbox input:checked[type="checkbox"]::before {
-    background-color: #fff;
-    left: 18px;
 }
 
 /* Override Slider Styles (for webkit browsers like Safari and Chrome)
@@ -356,45 +204,6 @@ input[type=range]::-webkit-slider-runnable-track {
     background: transparent;
 }
 
-hr.append-display {
-    margin: 8px 0;
-    border: none;
-    height: 1px;
-    border-top-width: 0;
-    background-image: linear-gradient(to right, rgba(50,50,50, 0.1), rgba(150, 150, 150, 0.8), rgba(50,50,50, 0.1));
-}
-.source-a {
-    font-size: 0.8em;
-    max-width: 100%;
-    margin: 0;
-    display: flex;
-    flex-direction: row;
-    flex-wrap: wrap;
-    align-items: center;
-    /* background-color: #dddddd88; */
-    border-radius: 1.5rem;
-    padding: 0.2em;
-}
-.source-a a {
-    display: inline-block;
-    background-color: #aaaaaa50;
-    border-radius: 1rem;
-    padding: 0.5em;
-    text-align: center;
-    text-overflow: ellipsis;
-    overflow: hidden;
-    min-width: 20%;
-    white-space: nowrap;
-    margin: 0.2rem 0.1rem;
-    text-decoration: none !important;
-    flex: 1;
-    transition: flex 0.5s;
-}
-.source-a a:hover {
-    background-color: #aaaaaa20;
-    flex: 2;
-}
-
 #submit_btn, #cancel_btn {
     height: 42px !important;
 }
@@ -440,7 +249,7 @@ ol:not(.options), ul:not(.options) {
     #chuanhu_chatbot {
         height: calc(100vh - 200px);
     }
-    #chuanhu_chatbot>.wrapper>.wrap {
+    #chuanhu_chatbot .wrap {
         max-height: calc(100vh - 200px - var(--line-sm)*1rem - 2*var(--block-label-margin) );
     }
 }
@@ -449,7 +258,7 @@ ol:not(.options), ul:not(.options) {
     #chuanhu_chatbot {
         height: calc(100vh - 140px);
     }
-    #chuanhu_chatbot>.wrapper>.wrap {
+    #chuanhu_chatbot .wrap {
         max-height: calc(100vh - 140px - var(--line-sm)*1rem - 2*var(--block-label-margin) );
     }
     [data-testid = "bot"] {
@@ -459,7 +268,7 @@ ol:not(.options), ul:not(.options) {
         letter-spacing: -1px; font-size: 22px;
     }
 }
-#chuanhu_chatbot>.wrapper>.wrap {
+#chuanhu_chatbot .wrap {
     overflow-x: hidden;
 }
 /* 对话气泡 */
@@ -555,7 +364,7 @@ ol:not(.options), ul:not(.options) {
 }
 
 /* history message */
-.wrapper>.wrap>.history-message {
+.wrap>.history-message {
     padding: 10px !important;
 }
 .history-message {
@@ -574,7 +383,7 @@ ol:not(.options), ul:not(.options) {
 .history-message>.message {
     margin-bottom: 16px;
 }
-.wrapper>.wrap>.history-message::after {
+.wrap>.history-message::after {
     content: "";
     display: block;
     height: 2px;
@@ -583,7 +392,7 @@ ol:not(.options), ul:not(.options) {
     margin-top: -10px;
     clear: both;
 }
-.wrapper>.wrap>.history-message>:last-child::after {
+.wrap>.history-message>:last-child::after {
     content: "仅供查看";
     display: block;
     text-align: center;

assets/custom.js

@@ -15,60 +15,26 @@ var appTitleDiv = null;
 var chatbot = null;
 var chatbotWrap = null;
 var apSwitch = null;
+var empty_botton = null;
 var messageBotDivs = null;
 var loginUserForm = null;
 var logginUser = null;
-var updateToast = null;
-var sendBtn = null;
-var cancelBtn = null;
-var sliders = null;
 
 var userLogged = false;
 var usernameGotten = false;
 var historyLoaded = false;
-var updateInfoGotten = false;
-var isLatestVersion = localStorage.getItem('isLatestVersion') || false;
 
 var ga = document.getElementsByTagName("gradio-app");
 var targetNode = ga[0];
 var isInIframe = (window.self !== window.top);
 var language = navigator.language.slice(0,2);
-var currentTime = new Date().getTime();
 
-// i18n
 var forView_i18n = {
     'zh': "仅供查看",
     'en': "For viewing only",
     'ja': "閲覧専用",
-    'ko': "읽기 전용",
     'fr': "Pour consultation seulement",
     'es': "Solo para visualización",
-    'sv': "Endast för visning",
-};
-
-var deleteConfirm_i18n_pref = {
-    'zh': "你真的要删除 ",
-    'en': "Are you sure you want to delete ",
-    'ja': "本当に ",
-    'ko': "정말로 ",
-    'sv': "Är du säker på att du vill ta bort "
-};
-var deleteConfirm_i18n_suff = {
-    'zh': " 吗？",
-    'en': " ?",
-    'ja': " を削除してもよろしいですか？",
-    'ko': " 을(를) 삭제하시겠습니까?",
-    'sv': " ?"
-};
-var deleteConfirm_msg_pref = "Are you sure you want to delete ";
-var deleteConfirm_msg_suff = " ?";
-
-var usingLatest_i18n = {
-    'zh': "您使用的就是最新版！",
-    'en': "You are using the latest version!",
-    'ja': "最新バージョンを使用しています！",
-    'ko': "최신 버전을 사용하고 있습니다!",
-    'sv': "Du använder den senaste versionen!"
 };
 
 // gradio 页面加载好了么??? 我能动你的元素了么??
@@ -81,12 +47,9 @@ function gradioLoaded(mutations) {
             userInfoDiv = document.getElementById("user_info");
             appTitleDiv = document.getElementById("app_title");
             chatbot = document.querySelector('#chuanhu_chatbot');
-            chatbotWrap = document.querySelector('#chuanhu_chatbot > .wrapper > .wrap');
+            chatbotWrap = document.querySelector('#chuanhu_chatbot > .wrap');
             apSwitch = document.querySelector('.apSwitch input[type="checkbox"]');
-            updateToast = document.querySelector("#toast-update");
-            sendBtn = document.getElementById("submit_btn");
-            cancelBtn = document.getElementById("cancel_btn");
-            sliders = document.querySelectorAll('input[type="range"]');
+            empty_botton = document.getElementById("empty_btn")
 
             if (loginUserForm) {
                 localStorage.setItem("userLogged", true);
@@ -113,54 +76,29 @@ function gradioLoaded(mutations) {
                     loadHistoryHtml();
                 }
                 setChatbotScroll();
-                mObserver.observe(chatbotWrap, { attributes: true, childList: true, subtree: true, characterData: true});
-            }
-            if (sliders) {
-                setSlider();
             }
-            if (updateToast) {
-                const lastCheckTime = localStorage.getItem('lastCheckTime') || 0;
-                const longTimeNoCheck = currentTime - lastCheckTime > 3 * 24 * 60 * 60 * 1000;
-                if (longTimeNoCheck && !updateInfoGotten && !isLatestVersion || isLatestVersion && !updateInfoGotten) {
-                    updateLatestVersion();
-                }
-            }
-            if (cancelBtn) {
-                submitObserver.observe(cancelBtn, { attributes: true, characterData: true});
+            if (empty_botton) {
+                emptyHistory();
             }
         }
     }
 }
 
 function webLocale() {
-    // console.log("webLocale", language);
+    console.log("webLocale", language);
     if (forView_i18n.hasOwnProperty(language)) {
         var forView = forView_i18n[language];
         var forViewStyle = document.createElement('style');
-        forViewStyle.innerHTML = '.wrapper>.wrap>.history-message>:last-child::after { content: "' + forView + '"!important; }';
+        forViewStyle.innerHTML = '.wrap>.history-message>:last-child::after { content: "' + forView + '"!important; }';
         document.head.appendChild(forViewStyle);
-    }
-    if (deleteConfirm_i18n_pref.hasOwnProperty(language)) {
-        deleteConfirm_msg_pref = deleteConfirm_i18n_pref[language];
-        deleteConfirm_msg_suff = deleteConfirm_i18n_suff[language];
+        // console.log("added forViewStyle", forView);
     }
 }
 
-function showConfirmationDialog(a, file, c) {
-    if (file != "") {
-        var result = confirm(deleteConfirm_msg_pref + file + deleteConfirm_msg_suff);
-        if (result) {
-            return [a, file, c];
-        }
-    }
-    return [a, "CANCELED", c];
-}
-
 function selectHistory() {
     user_input_ta = user_input_tb.querySelector("textarea");
     if (user_input_ta) {
         observer.disconnect(); // 停止监听
-        disableSendBtn();
         // 在 textarea 上监听 keydown 事件
         user_input_ta.addEventListener("keydown", function (event) {
             var value = user_input_ta.value.trim();
@@ -205,13 +143,6 @@ function selectHistory() {
     }
 }
 
-function disableSendBtn() {
-    sendBtn.disabled = user_input_ta.value.trim() === '';
-    user_input_ta.addEventListener('input', () => {
-        sendBtn.disabled = user_input_ta.value.trim() === '';
-    });
-}
-
 var username = null;
 function getUserInfo() {
     if (usernameGotten) {
@@ -250,6 +181,8 @@ function toggleUserInfoVisibility(shouldHide) {
     }
 }
 function showOrHideUserInfo() {
+    var sendBtn = document.getElementById("submit_btn");
+
     // Bind mouse/touch events to show/hide user info
     appTitleDiv.addEventListener("mouseenter", function () {
         toggleUserInfoVisibility(false);
@@ -333,21 +266,22 @@ function setChatbotHeight() {
     const screenWidth = window.innerWidth;
     const statusDisplay = document.querySelector('#status_display');
     const statusDisplayHeight = statusDisplay ? statusDisplay.offsetHeight : 0;
+    const wrap = chatbot.querySelector('.wrap');
     const vh = window.innerHeight * 0.01;
     document.documentElement.style.setProperty('--vh', `${vh}px`);
     if (isInIframe) {
         chatbot.style.height = `700px`;
-        chatbotWrap.style.maxHeight = `calc(700px - var(--line-sm) * 1rem - 2 * var(--block-label-margin))`
+        wrap.style.maxHeight = `calc(700px - var(--line-sm) * 1rem - 2 * var(--block-label-margin))`
     } else {
         if (screenWidth <= 320) {
             chatbot.style.height = `calc(var(--vh, 1vh) * 100 - ${statusDisplayHeight + 150}px)`;
-            chatbotWrap.style.maxHeight = `calc(var(--vh, 1vh) * 100 - ${statusDisplayHeight + 150}px - var(--line-sm) * 1rem - 2 * var(--block-label-margin))`;
+            wrap.style.maxHeight = `calc(var(--vh, 1vh) * 100 - ${statusDisplayHeight + 150}px - var(--line-sm) * 1rem - 2 * var(--block-label-margin))`;
         } else if (screenWidth <= 499) {
             chatbot.style.height = `calc(var(--vh, 1vh) * 100 - ${statusDisplayHeight + 100}px)`;
-            chatbotWrap.style.maxHeight = `calc(var(--vh, 1vh) * 100 - ${statusDisplayHeight + 100}px - var(--line-sm) * 1rem - 2 * var(--block-label-margin))`;
+            wrap.style.maxHeight = `calc(var(--vh, 1vh) * 100 - ${statusDisplayHeight + 100}px - var(--line-sm) * 1rem - 2 * var(--block-label-margin))`;
         } else {
             chatbot.style.height = `calc(var(--vh, 1vh) * 100 - ${statusDisplayHeight + 160}px)`;
-            chatbotWrap.style.maxHeight = `calc(var(--vh, 1vh) * 100 - ${statusDisplayHeight + 160}px - var(--line-sm) * 1rem - 2 * var(--block-label-margin))`;
+            wrap.style.maxHeight = `calc(var(--vh, 1vh) * 100 - ${statusDisplayHeight + 160}px - var(--line-sm) * 1rem - 2 * var(--block-label-margin))`;
         }
     }
 }
@@ -387,12 +321,12 @@ function addChuanhuButton(botElement) {
         }
         return;
     }
-    var oldCopyButton = null;
-    var oldToggleButton = null;
-    oldCopyButton = botElement.querySelector('button.copy-bot-btn');
-    oldToggleButton = botElement.querySelector('button.toggle-md-btn');
-    if (oldCopyButton) oldCopyButton.remove();
-    if (oldToggleButton) oldToggleButton.remove();
+    var copyButton = null;
+    var toggleButton = null;
+    copyButton = botElement.querySelector('button.copy-bot-btn');
+    toggleButton = botElement.querySelector('button.toggle-md-btn');
+    if (copyButton) copyButton.remove();
+    if (toggleButton) toggleButton.remove();
 
     // Copy bot button
     var copyButton = document.createElement('button');
@@ -400,34 +334,19 @@ function addChuanhuButton(botElement) {
     copyButton.classList.add('copy-bot-btn');
     copyButton.setAttribute('aria-label', 'Copy');
     copyButton.innerHTML = copyIcon;
-    copyButton.addEventListener('click', async () => {
+    copyButton.addEventListener('click', () => {
         const textToCopy = rawMessage.innerText;
-        try {
-            if ("clipboard" in navigator) {
-                await navigator.clipboard.writeText(textToCopy);
+        navigator.clipboard
+            .writeText(textToCopy)
+            .then(() => {
                 copyButton.innerHTML = copiedIcon;
                 setTimeout(() => {
                     copyButton.innerHTML = copyIcon;
                 }, 1500);
-            } else {
-                const textArea = document.createElement("textarea");
-                textArea.value = textToCopy;
-                document.body.appendChild(textArea);
-                textArea.select();
-                try {
-                    document.execCommand('copy');
-                    copyButton.innerHTML = copiedIcon;
-                    setTimeout(() => {
-                        copyButton.innerHTML = copyIcon;
-                    }, 1500);
-                } catch (error) {
-                    console.error("Copy failed: ", error);
-                }
-                document.body.removeChild(textArea);
-            }
-        } catch (error) {
-            console.error("Copy failed: ", error);
-        }
+            })
+            .catch(() => {
+                console.error("copy failed");
+            });
     });
     botElement.appendChild(copyButton);
 
@@ -467,48 +386,44 @@ function removeMarkdownText(message) {
 let timeoutId;
 let isThrottled = false;
 var mmutation
-// 监听chatWrap元素的变化，为 bot 消息添加复制按钮。
+// 监听所有元素中 bot message 的变化，为 bot 消息添加复制按钮。
 var mObserver = new MutationObserver(function (mutationsList) {
     for (mmutation of mutationsList) {
         if (mmutation.type === 'childList') {
             for (var node of mmutation.addedNodes) {
-                if (node.nodeType === 1 && node.classList.contains('message')) {
+                if (node.nodeType === 1 && node.classList.contains('message') && node.getAttribute('data-testid') === 'bot') {
                     saveHistoryHtml();
-                    disableSendBtn();
-                    document.querySelectorAll('#chuanhu_chatbot .message-wrap .message.bot').forEach(addChuanhuButton);
+                    document.querySelectorAll('#chuanhu_chatbot>.wrap>.message-wrap .message.bot').forEach(addChuanhuButton);
+                }
+                if (node.tagName === 'INPUT' && node.getAttribute('type') === 'range') {
+                    setSlider();
                 }
             }
             for (var node of mmutation.removedNodes) {
-                if (node.nodeType === 1 && node.classList.contains('message')) {
+                if (node.nodeType === 1 && node.classList.contains('message') && node.getAttribute('data-testid') === 'bot') {
                     saveHistoryHtml();
-                    disableSendBtn();
-                    document.querySelectorAll('#chuanhu_chatbot .message-wrap .message.bot').forEach(addChuanhuButton);
+                    document.querySelectorAll('#chuanhu_chatbot>.wrap>.message-wrap .message.bot').forEach(addChuanhuButton);
                 }
             }
         } else if (mmutation.type === 'attributes') {
-            if (isThrottled) break; // 为了防止重复不断疯狂渲染，加上等待_(:з」∠)_
-            isThrottled = true;
-            clearTimeout(timeoutId);
-            timeoutId = setTimeout(() => {
-                isThrottled = false;
-                document.querySelectorAll('#chuanhu_chatbot .message-wrap .message.bot').forEach(addChuanhuButton);
-                saveHistoryHtml();
-                disableSendBtn();
-            }, 1500);
+            if (mmutation.target.nodeType === 1 && mmutation.target.classList.contains('message') && mmutation.target.getAttribute('data-testid') === 'bot') {
+                if (isThrottled) break; // 为了防止重复不断疯狂渲染，加上等待_(:з」∠)_
+                isThrottled = true;
+                clearTimeout(timeoutId);
+                timeoutId = setTimeout(() => {
+                    isThrottled = false;
+                    document.querySelectorAll('#chuanhu_chatbot>.wrap>.message-wrap .message.bot').forEach(addChuanhuButton);
+                    saveHistoryHtml();
+                }, 500);
+            }
         }
     }
 });
-// mObserver.observe(targetNode, { attributes: true, childList: true, subtree: true, characterData: true});
-
-var submitObserver = new MutationObserver(function (mutationsList) {
-    document.querySelectorAll('#chuanhu_chatbot .message-wrap .message.bot').forEach(addChuanhuButton);
-    saveHistoryHtml();
-});
+mObserver.observe(document.documentElement, { attributes: true, childList: true, subtree: true });
 
 var loadhistorytime = 0; // for debugging
 function saveHistoryHtml() {
-    var historyHtml = document.querySelector('#chuanhu_chatbot>.wrapper>.wrap');
-    if (!historyHtml) return;   // no history, do nothing
+    var historyHtml = document.querySelector('#chuanhu_chatbot > .wrap');
     localStorage.setItem('chatHistory', historyHtml.innerHTML);
     // console.log("History Saved")
     historyLoaded = false;
@@ -559,98 +474,12 @@ function clearHistoryHtml() {
         console.log("History Cleared");
     }
 }
-
-var showingUpdateInfo = false;
-async function getLatestRelease() {
-    try {
-        const response = await fetch('https://api.github.com/repos/gaizhenbiao/chuanhuchatgpt/releases/latest');
-        if (!response.ok) {
-            console.log(`Error: ${response.status} - ${response.statusText}`);
-            updateInfoGotten = true;
-            return null;
-          }
-        const data = await response.json();
-        updateInfoGotten = true;
-        return data;
-    } catch (error) {
-        console.log(`Error: ${error}`);
-        updateInfoGotten = true;
-        return null;
-    }
-}
-async function updateLatestVersion() {
-    const currentVersionElement = document.getElementById('current-version');
-    const latestVersionElement = document.getElementById('latest-version-title');
-    const releaseNoteElement = document.getElementById('release-note-content');
-    const currentVersion = currentVersionElement.textContent;
-    const versionTime = document.getElementById('version-time').innerText;
-    const localVersionTime = versionTime !== "unknown" ? (new Date(versionTime)).getTime() : 0;
-    updateInfoGotten = true; //无论成功与否都只执行一次，否则容易api超限...
-    try {
-        const data = await getLatestRelease();
-        const releaseNote = data.body;
-        if (releaseNote) {
-            releaseNoteElement.innerHTML = marked.parse(releaseNote, {mangle: false, headerIds: false});
-        }
-        const latestVersion = data.tag_name;
-        const latestVersionTime = (new Date(data.created_at)).getTime();
-        if (latestVersionTime) {
-            if (localVersionTime < latestVersionTime) {
-                latestVersionElement.textContent = latestVersion;
-                console.log(`New version ${latestVersion} found!`);
-                if (!isInIframe) {openUpdateToast();}      
-            } else {
-                noUpdate();
-            }
-            currentTime = new Date().getTime();
-            localStorage.setItem('lastCheckTime', currentTime);
-        }
-    } catch (error) {
-        console.error(error);
-    }
-}
-function getUpdate() {
-    window.open('https://github.com/gaizhenbiao/chuanhuchatgpt/releases/latest', '_blank');
-    closeUpdateToast();
-}
-function cancelUpdate() {
-    closeUpdateToast();
-}
-function openUpdateToast() {
-    showingUpdateInfo = true;
-    setUpdateWindowHeight();
-}
-function closeUpdateToast() {
-    updateToast.style.setProperty('top', '-500px');
-    showingUpdateInfo = false;
-}
-function manualCheckUpdate() {
-    openUpdateToast();
-    updateLatestVersion();
-    currentTime = new Date().getTime();
-    localStorage.setItem('lastCheckTime', currentTime);
+function emptyHistory() {
+    empty_botton.addEventListener("click", function () {
+        clearHistoryHtml();
+    });
 }
-function noUpdate() {
-    localStorage.setItem('isLatestVersion', 'true');
-    isLatestVersion = true;
-    const versionInfoElement = document.getElementById('version-info-title');
-    const releaseNoteWrap = document.getElementById('release-note-wrap');
-    const gotoUpdateBtn = document.getElementById('goto-update-btn');
-    const closeUpdateBtn = document.getElementById('close-update-btn');
 
-    versionInfoElement.textContent = usingLatest_i18n.hasOwnProperty(language) ? usingLatest_i18n[language] : usingLatest_i18n['en'];
-    releaseNoteWrap.style.setProperty('display', 'none');
-    gotoUpdateBtn.classList.add('hideK');
-    closeUpdateBtn.classList.remove('hideK');
-}
-function setUpdateWindowHeight() {
-    if (!showingUpdateInfo) {return;}
-    const scrollPosition = window.scrollY;
-    // const originalTop = updateToast.style.getPropertyValue('top');
-    const resultTop = scrollPosition - 20 + 'px';
-    updateToast.style.setProperty('top', resultTop);
-}
-    
 // 监视页面内部 DOM 变动
 var observer = new MutationObserver(function (mutations) {
     gradioLoaded(mutations);
@@ -663,43 +492,9 @@ window.addEventListener("DOMContentLoaded", function () {
     historyLoaded = false;
 });
 window.addEventListener('resize', setChatbotHeight);
-window.addEventListener('scroll', function(){setChatbotHeight();setUpdateWindowHeight();});
+window.addEventListener('scroll', setChatbotHeight);
 window.matchMedia("(prefers-color-scheme: dark)").addEventListener("change", adjustDarkMode);
 
-// console suprise
-var styleTitle1 = `
-font-size: 16px;
-font-family: ui-monospace, monospace;
-color: #06AE56;
-`
-var styleDesc1 = `
-font-size: 12px;
-font-family: ui-monospace, monospace;
-`
-function makeML(str) {
-    let l = new String(str)
-    l = l.substring(l.indexOf("/*") + 3, l.lastIndexOf("*/"))
-    return l
-}
-let ChuanhuInfo = function () {
-    /* 
-   ________                      __             ________          __ 
-  / ____/ /_  __  ______ _____  / /_  __  __   / ____/ /_  ____ _/ /_
- / /   / __ \/ / / / __ `/ __ \/ __ \/ / / /  / /   / __ \/ __ `/ __/
-/ /___/ / / / /_/ / /_/ / / / / / / / /_/ /  / /___/ / / / /_/ / /_  
-\____/_/ /_/\__,_/\__,_/_/ /_/_/ /_/\__,_/   \____/_/ /_/\__,_/\__/  
-                                                                     
-   川虎Chat (Chuanhu Chat) - GUI for ChatGPT API and many LLMs
- */
-}
-let description = `
-© 2023 Chuanhu, MZhao, Keldos
-GitHub repository: [https://github.com/GaiZhenbiao/ChuanhuChatGPT]\n
-Enjoy our project!\n
-`
-console.log(`%c${makeML(ChuanhuInfo)}`,styleTitle1)
-console.log(`%c${description}`, styleDesc1)
-
 // button svg code
 const copyIcon   = '<span><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" height=".8em" width=".8em" xmlns="http://www.w3.org/2000/svg"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"></rect><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"></path></svg></span>';
 const copiedIcon = '<span><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" height=".8em" width=".8em" xmlns="http://www.w3.org/2000/svg"><polyline points="20 6 9 17 4 12"></polyline></svg></span>';

assets/html/appearance_switcher.html

@@ -1,6 +1,11 @@
-<div class="switch_checkbox" id="apSwitch">
-    <label class="apSwitch">
-        <input type="checkbox" id="apSwitch_checkbox" data-testid="checkbox" />
-        <span class="apSwitch_span">{label}</span>
-    </label>
+<div style="display: flex; justify-content: space-between;">
+    <span style="margin-top: 4px !important;">
+        {label}
+    </span>
+    <span>
+        <label class="apSwitch" for="checkbox">
+            <input type="checkbox" id="checkbox">
+            <div class="apSlider"></div>
+        </label>
+    </span>
 </div>

assets/html/billing_info.html

@@ -1,9 +0,0 @@
-<b>{label}</b>
-<div class="progress-bar">
-    <div class="progress" style="width: {usage_percent}%;">
-        <span class="progress-text">{usage_percent}%</span>
-    </div>
-</div>
-<div style="display: flex; justify-content: space-between;">
-    <span>${rounded_usage}</span><span>${usage_limit}</span>
-</div>

assets/html/update.html

@@ -1,25 +0,0 @@
-<div id="toast-update">
-    <div id="check-chuanhu-update">
-        <p style="display:none">
-            <span id="current-version">{current_version}</span>
-            <span id="version-time">{version_time}</span>
-        </p>
-        <p id="version-info-title">
-            Latest Version: <a href="https://github.com/gaizhenbiao/chuanhuchatgpt/releases/latest" target="_blank"
-                id="latest-version-title" style="text-decoration: none;">getting latest version...</a>
-        </p>
-        <div id="release-note-wrap">
-            <div class="release-note-content" id="release-note-content">
-                Getting Release Note...
-            </div>
-        </div>
-        <div id="goto-update-btn" class="btn-update-group">
-            <button class="btn-update lg secondary svelte-1ipelgc" id="cancel-button" onclick="cancelUpdate()">{cancel_btn}</button>
-            <button class="btn-update lg primary svelte-1ipelgc" id="update-button" onclick="getUpdate()">{update_btn}</button>
-        </div>
-        <div id="close-update-btn" class="btn-update-group hideK">
-            <button class="btn-update lg secondary svelte-1jrzxu" id="update-button" onclick="getUpdate()">{seenew_btn}</button>
-            <button class="btn-update lg primary svelte-1jrzxu" id="cancel-button" onclick="cancelUpdate()">{ok_btn}</button>
-        </div>
-    </div>
-</div>

chatgpt - macOS.command

@@ -0,0 +1,7 @@
+#!/bin/bash
+echo Opening ChuanhuChatGPT...
+cd "$(dirname "${BASH_SOURCE[0]}")"
+nohup python3 ChuanhuChatbot.py >/dev/null 2>&1 &
+sleep 5
+open http://127.0.0.1:7860
+echo Finished opening ChuanhuChatGPT (http://127.0.0.1:7860/). If you kill ChuanhuChatbot, Use "pkill -f 'ChuanhuChatbot'" command in terminal.

chatgpt - windows.bat

@@ -0,0 +1,14 @@
+@echo off
+echo Opening ChuanhuChatGPT...
+
+REM Open powershell via bat
+start powershell.exe -NoExit -Command "python ./ChuanhuChatbot.py"
+
+REM The web page can be accessed with delayed start http://127.0.0.1:7860/
+ping -n 5 127.0.0.1>nul
+
+REM access chargpt via your default browser
+start "" "http://127.0.0.1:7860/"
+
+
+echo Finished opening ChuanhuChatGPT (http://127.0.0.1:7860/).

config.json

@@ -0,0 +1,3 @@
+{
+  "hide_history_when_not_logged_in": true
+}

config_example.json

@@ -1,53 +1,24 @@
 {
-    // 各配置具体说明，见 [https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用教程#配置-configjson]
-
-    //== API 配置 ==
-    "openai_api_key": "", // 你的 OpenAI API Key，一般必填，若空缺则需在图形界面中填入API Key
-    "google_palm_api_key": "", // 你的 Google PaLM API Key，用于 Google PaLM 对话模型
-    "xmchat_api_key": "", // 你的 xmchat API Key，用于 XMChat 对话模型
-    "minimax_api_key": "", // 你的 MiniMax API Key，用于 MiniMax 对话模型
-    "minimax_group_id": "", // 你的 MiniMax Group ID，用于 MiniMax 对话模型
-
-    //== Azure ==
-    "openai_api_type": "openai", // 可选项：azure, openai
-    "azure_openai_api_key": "", // 你的 Azure OpenAI API Key，用于 Azure OpenAI 对话模型
-    "azure_openai_api_base_url": "", // 你的 Azure Base URL
-    "azure_openai_api_version": "2023-05-15", // 你的 Azure OpenAI API 版本
-    "azure_deployment_name": "", // 你的 Azure OpenAI Chat 模型 Deployment 名称
-    "azure_embedding_deployment_name": "", // 你的 Azure OpenAI Embedding 模型 Deployment 名称
-    "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"
+    // 你的OpenAI API Key，一般必填，
+    // 若缺省填为 "openai_api_key": "" 则必须再在图形界面中填入API Key
+    "openai_api_key": "",
+    // 你的xmchat API Key，与OpenAI API Key不同
+    "xmchat_api_key": "",
+    "language": "auto",
+    // 如果使用代理，请取消注释下面的两行，并替换代理URL
+    // "https_proxy": "http://127.0.0.1:1079",
+    // "http_proxy": "http://127.0.0.1:1079",
     "users": [], // 用户列表，[[用户名1, 密码1], [用户名2, 密码2], ...]
     "local_embedding": false, //是否在本地编制索引
-    "hide_history_when_not_logged_in": false, //未登录情况下是否不展示对话历史
-    "check_update": true, //是否启用检查更新
     "default_model": "gpt-3.5-turbo", // 默认模型
-
-    //== API 用量 ==
-    "show_api_billing": false, //是否显示OpenAI API用量（启用需要填写sensitive_id）
-    "sensitive_id": "", // 你 OpenAI 账户的 Sensitive ID，用于查询 API 用量
-    "usage_limit": 120, // 该 OpenAI API Key 的当月限额，单位：美元，用于计算百分比和显示上限
-    "legacy_api_usage": false, // 是否使用旧版 API 用量查询接口（OpenAI现已关闭该接口，但是如果你在使用第三方 API，第三方可能仍然支持此接口）
-
-    //== 川虎助理设置 ==
-    "default_chuanhu_assistant_model": "gpt-4", //川虎助理使用的模型，可选gpt-3.5-turbo或者gpt-4等
-    "GOOGLE_CSE_ID": "", //谷歌搜索引擎ID，用于川虎助理Pro模式，获取方式请看 https://stackoverflow.com/questions/37083058/programmatically-searching-google-in-python-using-custom-search
-    "GOOGLE_API_KEY": "", //谷歌API Key，用于川虎助理Pro模式
-    "WOLFRAM_ALPHA_APPID": "", //Wolfram Alpha API Key，用于川虎助理Pro模式，获取方式请看 https://products.wolframalpha.com/api/
-    "SERPAPI_API_KEY": "", //SerpAPI API Key，用于川虎助理Pro模式，获取方式请看 https://serpapi.com/
-
-    //== 文档处理与显示 ==
-    "latex_option": "default", // LaTeX 公式渲染策略，可选"default", "strict", "all"或者"disabled"
     "advance_docs": {
         "pdf": {
-            "two_column": false, // 是否认为PDF是双栏的
-            "formula_ocr": true // 是否使用OCR识别PDF中的公式
+            // 是否认为PDF是双栏的
+            "two_column": false,
+            // 是否使用OCR识别PDF中的公式
+            "formula_ocr": true
         }
     },
-
-    //== 高级配置 ==
     // 是否多个API Key轮换使用
     "multi_api_key": false,
     "api_key_list": [
@@ -55,12 +26,7 @@
         "sk-xxxxxxxxxxxxxxxxxxxxxxxx2",
         "sk-xxxxxxxxxxxxxxxxxxxxxxxx3"
     ],
-    // 自定义OpenAI API Base
-    // "openai_api_base": "https://api.openai.com",
-    // 自定义使用代理（请替换代理URL）
-    // "https_proxy": "http://127.0.0.1:1079",
-    // "http_proxy": "http://127.0.0.1:1079",
-    // 自定义端口、自定义ip（请替换对应内容）
+    // 如果使用自定义端口、自定义ip，请取消注释并替换对应内容
     // "server_name": "0.0.0.0",
     // "server_port": 7860,
     // 如果要share到gradio，设置为true

custom.css

@@ -0,0 +1,162 @@
+:root {
+    --chatbot-color-light: #F3F3F3;
+    --chatbot-color-dark: #121111;
+}
+
+/* status_display */
+#status_display {
+    display: flex;
+    min-height: 2.5em;
+    align-items: flex-end;
+    justify-content: flex-end;
+}
+#status_display p {
+    font-size: .85em;
+    font-family: monospace;
+    color: var(--body-text-color-subdued);
+}
+
+#chuanhu_chatbot, #status_display {
+    transition: all 0.6s;
+}
+/* list */
+ol:not(.options), ul:not(.options) {
+    padding-inline-start: 2em !important;
+}
+
+/* 亮色 */
+#chuanhu_chatbot {
+    background-color: var(--chatbot-color-light) !important;
+}
+[data-testid = "bot"] {
+    background-color: #FFFFFF !important;
+}
+[data-testid = "user"] {
+    background-color: #95EC69 !important;
+}
+/* 对话气泡 */
+[class *= "message"] {
+    border-radius: var(--radius-xl) !important;
+    border: none;
+    padding: var(--spacing-xl) !important;
+    font-size: var(--text-md) !important;
+    line-height: var(--line-md) !important;
+    min-height: calc(var(--text-md)*var(--line-md) + 2*var(--spacing-xl));
+    min-width: calc(var(--text-md)*var(--line-md) + 2*var(--spacing-xl));
+}
+[data-testid = "bot"] {
+    max-width: 85%;
+    border-bottom-left-radius: 0 !important;
+}
+[data-testid = "user"] {
+    max-width: 85%;
+    width: auto !important;
+    border-bottom-right-radius: 0 !important;
+}
+/* 表格 */
+table {
+    margin: 1em 0;
+    border-collapse: collapse;
+    empty-cells: show;
+}
+td,th {
+    border: 1.2px solid var(--border-color-primary) !important;
+    padding: 0.2em;
+}
+thead {
+    background-color: rgba(175,184,193,0.2);
+}
+thead th {
+    padding: .5em .2em;
+}
+/* 行内代码 */
+code {
+    display: inline;
+    white-space: break-spaces;
+    border-radius: 6px;
+    margin: 0 2px 0 2px;
+    padding: .2em .4em .1em .4em;
+    background-color: rgba(175,184,193,0.2);
+}
+/* 代码块 */
+pre code {
+    display: block;
+    overflow: auto;
+    white-space: pre;
+    background-color: hsla(0, 0%, 0%, 80%)!important;
+    border-radius: 10px;
+    padding: 1.4em 1.2em 0em 1.4em;
+    margin: 1.2em 2em 1.2em 0.5em;
+    color: #FFF;
+    box-shadow: 6px 6px 16px hsla(0, 0%, 0%, 0.2);
+}
+/* 代码高亮样式 */
+.highlight .hll { background-color: #49483e }
+.highlight .c { color: #75715e } /* Comment */
+.highlight .err { color: #960050; background-color: #1e0010 } /* Error */
+.highlight .k { color: #66d9ef } /* Keyword */
+.highlight .l { color: #ae81ff } /* Literal */
+.highlight .n { color: #f8f8f2 } /* Name */
+.highlight .o { color: #f92672 } /* Operator */
+.highlight .p { color: #f8f8f2 } /* Punctuation */
+.highlight .ch { color: #75715e } /* Comment.Hashbang */
+.highlight .cm { color: #75715e } /* Comment.Multiline */
+.highlight .cp { color: #75715e } /* Comment.Preproc */
+.highlight .cpf { color: #75715e } /* Comment.PreprocFile */
+.highlight .c1 { color: #75715e } /* Comment.Single */
+.highlight .cs { color: #75715e } /* Comment.Special */
+.highlight .gd { color: #f92672 } /* Generic.Deleted */
+.highlight .ge { font-style: italic } /* Generic.Emph */
+.highlight .gi { color: #a6e22e } /* Generic.Inserted */
+.highlight .gs { font-weight: bold } /* Generic.Strong */
+.highlight .gu { color: #75715e } /* Generic.Subheading */
+.highlight .kc { color: #66d9ef } /* Keyword.Constant */
+.highlight .kd { color: #66d9ef } /* Keyword.Declaration */
+.highlight .kn { color: #f92672 } /* Keyword.Namespace */
+.highlight .kp { color: #66d9ef } /* Keyword.Pseudo */
+.highlight .kr { color: #66d9ef } /* Keyword.Reserved */
+.highlight .kt { color: #66d9ef } /* Keyword.Type */
+.highlight .ld { color: #e6db74 } /* Literal.Date */
+.highlight .m { color: #ae81ff } /* Literal.Number */
+.highlight .s { color: #e6db74 } /* Literal.String */
+.highlight .na { color: #a6e22e } /* Name.Attribute */
+.highlight .nb { color: #f8f8f2 } /* Name.Builtin */
+.highlight .nc { color: #a6e22e } /* Name.Class */
+.highlight .no { color: #66d9ef } /* Name.Constant */
+.highlight .nd { color: #a6e22e } /* Name.Decorator */
+.highlight .ni { color: #f8f8f2 } /* Name.Entity */
+.highlight .ne { color: #a6e22e } /* Name.Exception */
+.highlight .nf { color: #a6e22e } /* Name.Function */
+.highlight .nl { color: #f8f8f2 } /* Name.Label */
+.highlight .nn { color: #f8f8f2 } /* Name.Namespace */
+.highlight .nx { color: #a6e22e } /* Name.Other */
+.highlight .py { color: #f8f8f2 } /* Name.Property */
+.highlight .nt { color: #f92672 } /* Name.Tag */
+.highlight .nv { color: #f8f8f2 } /* Name.Variable */
+.highlight .ow { color: #f92672 } /* Operator.Word */
+.highlight .w { color: #f8f8f2 } /* Text.Whitespace */
+.highlight .mb { color: #ae81ff } /* Literal.Number.Bin */
+.highlight .mf { color: #ae81ff } /* Literal.Number.Float */
+.highlight .mh { color: #ae81ff } /* Literal.Number.Hex */
+.highlight .mi { color: #ae81ff } /* Literal.Number.Integer */
+.highlight .mo { color: #ae81ff } /* Literal.Number.Oct */
+.highlight .sa { color: #e6db74 } /* Literal.String.Affix */
+.highlight .sb { color: #e6db74 } /* Literal.String.Backtick */
+.highlight .sc { color: #e6db74 } /* Literal.String.Char */
+.highlight .dl { color: #e6db74 } /* Literal.String.Delimiter */
+.highlight .sd { color: #e6db74 } /* Literal.String.Doc */
+.highlight .s2 { color: #e6db74 } /* Literal.String.Double */
+.highlight .se { color: #ae81ff } /* Literal.String.Escape */
+.highlight .sh { color: #e6db74 } /* Literal.String.Heredoc */
+.highlight .si { color: #e6db74 } /* Literal.String.Interpol */
+.highlight .sx { color: #e6db74 } /* Literal.String.Other */
+.highlight .sr { color: #e6db74 } /* Literal.String.Regex */
+.highlight .s1 { color: #e6db74 } /* Literal.String.Single */
+.highlight .ss { color: #e6db74 } /* Literal.String.Symbol */
+.highlight .bp { color: #f8f8f2 } /* Name.Builtin.Pseudo */
+.highlight .fm { color: #a6e22e } /* Name.Function.Magic */
+.highlight .vc { color: #f8f8f2 } /* Name.Variable.Class */
+.highlight .vg { color: #f8f8f2 } /* Name.Variable.Global */
+.highlight .vi { color: #f8f8f2 } /* Name.Variable.Instance */
+.highlight .vm { color: #f8f8f2 } /* Name.Variable.Magic */
+.highlight .il { color: #ae81ff } /* Literal.Number.Integer.Long */

locale/en_US.json

@@ -32,32 +32,24 @@
     "📝 导出为Markdown": "📝 Export as Markdown",
     "默认保存于history文件夹": "Default save in history folder",
     "高级": "Advanced",
-    "# ⚠️ 务必谨慎更改 ⚠️": "# ⚠️ Caution: Changes require care. ⚠️",
+    "# ⚠️ 务必谨慎更改 ⚠️\n\n如果无法使用请恢复默认设置": "# ⚠️ Caution: Changes require care. ⚠️\n\nIf unable to use, restore default settings.",
     "参数": "Parameters",
-    "停止符，用英文逗号隔开...": "Type in stop token here, separated by comma...",
+    "在这里输入停止符，用英文逗号隔开...": "Type in stop token here, separated by comma...",
     "用于定位滥用行为": "Used to locate abuse",
     "用户名": "Username",
     "网络设置": "Network Settings",
     "在这里输入API-Host...": "Type in API-Host here...",
     "🔄 切换API地址": "🔄 Switch API Address",
     "在这里输入代理地址...": "Type in proxy address here...",
-    "代理地址（示例：http://127.0.0.1:10809）": "Proxy address (example: http://127.0.0.1:10809)",
+    "代理地址（示例：http://127.0.0.1:10809）": "Proxy address (example: http://127.0.0.1:10809）",
     "🔄 设置代理地址": "🔄 Set Proxy Address",
-    "🔙 恢复网络默认设置": "🔙 Reset Network Settings",
-    "🔄 检查更新...": "🔄 Check for Update...",
-    "取消": "Cancel",
-    "更新": "Update",
-    "详情": "Details",
-    "好": "OK",
+    "🔙 恢复默认设置": "🔙 Restore Default Settings",
     "川虎Chat 🚀": "Chuanhu Chat 🚀",
     "开始实时传输回答……": "Start streaming output...",
     "Token 计数: ": "Token Count: ",
-    "，本次对话累计消耗了 ": ", Total cost for this dialogue is ",
+    "，本次对话累计消耗了 ": "，Total cost for this dialogue is ",
     "**获取API使用情况失败**": "**Failed to get API usage**",
-    "**获取API使用情况失败**，需在填写`config.json`中正确填写sensitive_id": "**Failed to get API usage**, correct sensitive_id needed in `config.json`",
-    "**获取API使用情况失败**，sensitive_id错误或已过期": "**Failed to get API usage**, wrong or expired sensitive_id",
     "**本月使用金额** ": "**Monthly usage** ",
-    "本月使用金额": "Monthly usage",
     "获取API使用情况失败:": "Failed to get API usage:",
     "API密钥更改为了": "The API key is changed to",
     "JSON解析错误,收到的内容: ": "JSON parsing error, received content: ",
@@ -72,13 +64,10 @@
     "API key为空，请检查是否输入正确。": "API key is empty, check whether it is entered correctly.",
     "请输入对话内容。": "Enter the content of the conversation.",
     "账单信息不适用": "Billing information is not applicable",
-    "由Bilibili [土川虎虎虎](https://space.bilibili.com/29125536)、[明昭MZhao](https://space.bilibili.com/24807452) 和 [Keldos](https://github.com/Keldos-Li) 开发<br />访问川虎Chat的 [GitHub项目](https://github.com/GaiZhenbiao/ChuanhuChatGPT) 下载最新版脚本": "Developed by Bilibili [土川虎虎虎](https://space.bilibili.com/29125536), [明昭MZhao](https://space.bilibili.com/24807452) and [Keldos](https://github.com/Keldos-Li)\n\nDownload latest code from [GitHub](https://github.com/GaiZhenbiao/ChuanhuChatGPT)",
+    "由Bilibili [土川虎虎虎](https://space.bilibili.com/29125536) 和 [明昭MZhao](https://space.bilibili.com/24807452)开发<br />访问川虎Chat的 [GitHub项目](https://github.com/GaiZhenbiao/ChuanhuChatGPT) 下载最新版脚本": "developor: Bilibili [土川虎虎虎](https://space.bilibili.com/29125536) and [明昭MZhao](https://space.bilibili.com/24807452)\n\nDownload latest code from [GitHub](https://github.com/GaiZhenbiao/ChuanhuChatGPT)",
     "切换亮暗色主题": "Switch light/dark theme",
     "您的IP区域：未知。": "Your IP region: Unknown.",
     "获取IP地理位置失败。原因：": "Failed to get IP location. Reason: ",
     "。你仍然可以使用聊天功能。": ". You can still use the chat function.",
-    "您的IP区域：": "Your IP region: ",
-    "总结": "Summarize",
-    "生成内容总结中……": "Generating content summary...",
-    "由于下面的原因，Google 拒绝返回 PaLM 的回答：\n\n": "Due to the following reasons, Google refuses to provide an answer to PaLM: \n\n"
+    "您的IP区域：": "Your IP region: "
 }

locale/ja_JP.json

@@ -32,9 +32,9 @@
     "📝 导出为Markdown": "📝 Markdownでエクスポート",
     "默认保存于history文件夹": "デフォルトでhistoryフォルダに保存されます",
     "高级": "Advanced",
-    "# ⚠️ 务必谨慎更改 ⚠️": "# ⚠️ 変更には慎重に ⚠️",
+    "# ⚠️ 务必谨慎更改 ⚠️\n\n如果无法使用请恢复默认设置": "# ⚠️ 変更には慎重に ⚠️\n\nもし動作しない場合は、デフォルト設定に戻してください。",
     "参数": "パラメータ",
-    "停止符，用英文逗号隔开...": "ここにストップ文字を英語のカンマで区切って入力してください...",
+    "在这里输入停止符，用英文逗号隔开...": "ここにストップ文字を英語のカンマで区切って入力してください...",
     "用于定位滥用行为": "不正行為を特定するために使用されます",
     "用户名": "ユーザー名",
     "网络设置": "ネットワーク設定",
@@ -43,21 +43,13 @@
     "在这里输入代理地址...": "プロキシアドレスを入力してください...",
     "代理地址（示例：http://127.0.0.1:10809）": "プロキシアドレス（例：http://127.0.0.1:10809）",
     "🔄 设置代理地址": "🔄 プロキシアドレスを設定",
-    "🔙 恢复默认网络设置": "🔙 ネットワーク設定のリセット",
-    "🔄 检查更新...": "🔄 アップデートをチェック...",
-    "取消": "キャンセル",
-    "更新": "アップデート",
-    "详情": "詳細",
-    "好": "はい",
+    "🔙 恢复默认设置": "🔙 デフォルト設定に戻す",
     "川虎Chat 🚀": "川虎Chat 🚀",
     "开始实时传输回答……": "ストリーム出力開始……",
     "Token 计数: ": "Token数: ",
     "，本次对话累计消耗了 ": ", 今の会話で消費合計 ",
     "**获取API使用情况失败**": "**API使用状況の取得に失敗しました**",
-    "**获取API使用情况失败**，需在填写`config.json`中正确填写sensitive_id": "**API使用状況の取得に失敗しました**、`config.json`に正しい`sensitive_id`を入力する必要があります",
-    "**获取API使用情况失败**，sensitive_id错误或已过期": "**API使用状況の取得に失敗しました**、sensitive_idが間違っているか、期限切れです",
     "**本月使用金额** ": "**今月の使用料金** ",
-    "本月使用金额": "今月の使用料金",
     "获取API使用情况失败:": "API使用状況の取得に失敗しました:",
     "API密钥更改为了": "APIキーが変更されました",
     "JSON解析错误,收到的内容: ": "JSON解析エラー、受信内容: ",
@@ -72,13 +64,10 @@
     "API key为空，请检查是否输入正确。": "APIキーが入力されていません。正しく入力されているか確認してください。",
     "请输入对话内容。": "会話内容を入力してください。",
     "账单信息不适用": "課金情報は対象外です",
-    "由Bilibili [土川虎虎虎](https://space.bilibili.com/29125536)、[明昭MZhao](https://space.bilibili.com/24807452) 和 [Keldos](https://github.com/Keldos-Li) 开发<br />访问川虎Chat的 [GitHub项目](https://github.com/GaiZhenbiao/ChuanhuChatGPT) 下载最新版脚本": "開発：Bilibili [土川虎虎虎](https://space.bilibili.com/29125536) と [明昭MZhao](https://space.bilibili.com/24807452) と [Keldos](https://github.com/Keldos-Li)\n\n最新コードは川虎Chatのサイトへ [GitHubプロジェクト](https://github.com/GaiZhenbiao/ChuanhuChatGPT)",
+    "由Bilibili [土川虎虎虎](https://space.bilibili.com/29125536) 和 [明昭MZhao](https://space.bilibili.com/24807452)开发<br />访问川虎Chat的 [GitHub项目](https://github.com/GaiZhenbiao/ChuanhuChatGPT) 下载最新版脚本": "開発：Bilibili [土川虎虎虎](https://space.bilibili.com/29125536) と [明昭MZhao](https://space.bilibili.com/24807452)\n\n最新コードは川虎Chatのサイトへ [GitHubプロジェクト](https://github.com/GaiZhenbiao/ChuanhuChatGPT)",
     "切换亮暗色主题": "テーマの明暗切替",
     "您的IP区域：未知。": "あなたのIPアドレス地域：不明",
     "获取IP地理位置失败。原因：": "IPアドレス地域の取得に失敗しました。理由：",
     "。你仍然可以使用聊天功能。": "。あなたはまだチャット機能を使用できます。",
-    "您的IP区域：": "あなたのIPアドレス地域：",
-    "总结": "要約する",
-    "生成内容总结中……": "コンテンツ概要を生成しています...",
-    "由于下面的原因，Google 拒绝返回 PaLM 的回答：\n\n": "Googleは以下の理由から、PaLMの回答を返すことを拒否しています:\n\n"
-}
+    "您的IP区域：": "あなたのIPアドレス地域："
+}

locale/ko_KR.json

@@ -1,86 +0,0 @@
-{
-    "未命名对话历史记录": "이름없는 대화 기록",
-    "在这里输入": "여기에 입력하세요",
-    "🧹 新的对话": "🧹 새로운 대화",
-    "🔄 重新生成": "🔄 재생성",
-    "🗑️ 删除最旧对话": "🗑️ 가장 오래된 대화 삭제",
-    "🗑️ 删除最新对话": "🗑️ 최신 대화 삭제",
-    "🗑️ 删除": "🗑️ 삭제",
-    "模型": "LLM 모델",
-    "多账号模式已开启，无需输入key，可直接开始对话": "다중 계정 모드가 활성화되어 있으므로 키를 입력할 필요가 없이 바로 대화를 시작할 수 있습니다",
-    "**发送消息** 或 **提交key** 以显示额度": "**메세지를 전송** 하거나 **Key를 입력**하여 크레딧 표시",
-    "选择模型": "모델 선택",
-    "选择LoRA模型": "LoRA 모델 선택",
-    "实时传输回答": "실시간 전송",
-    "单轮对话": "단일 대화",
-    "使用在线搜索": "온라인 검색 사용",
-    "选择回复语言（针对搜索&索引功能）": "답장 언어 선택 (검색 & 인덱스용)",
-    "上传索引文件": "업로드",
-    "双栏pdf": "2-column pdf",
-    "识别公式": "formula OCR",
-    "在这里输入System Prompt...": "여기에 시스템 프롬프트를 입력하세요...",
-    "加载Prompt模板": "프롬프트 템플릿 불러오기",
-    "选择Prompt模板集合文件": "프롬프트 콜렉션 파일 선택",
-    "🔄 刷新": "🔄 새로고침",
-    "从Prompt模板中加载": "프롬프트 템플릿에서 불러오기",
-    "保存/加载": "저장/불러오기",
-    "保存/加载对话历史记录": "대화 기록 저장/불러오기",
-    "从列表中加载对话": "리스트에서 대화 불러오기",
-    "设置文件名: 默认为.json，可选为.md": "파일 이름 설정: 기본값: .json, 선택: .md",
-    "设置保存文件名": "저장 파일명 설정",
-    "对话历史记录": "대화 기록",
-    "💾 保存对话": "💾 대화 저장",
-    "📝 导出为Markdown": "📝 마크다운으로 내보내기",
-    "默认保存于history文件夹": "히스토리 폴더에 기본 저장",
-    "高级": "고급",
-    "# ⚠️ 务必谨慎更改 ⚠️": "# ⚠️ 주의: 변경시 주의하세요. ⚠️",
-    "参数": "파라미터들",
-    "停止符，用英文逗号隔开...": "여기에 정지 토큰 입력, ','로 구분됨...",
-    "用于定位滥用行为": "악용 사례 파악에 활용됨",
-    "用户名": "사용자 이름",
-    "网络设置": "네트워크 설정",
-    "在这里输入API-Host...": "여기에 API host를 입력하세요...",
-    "🔄 切换API地址": "🔄 API 주소 변경",
-    "在这里输入代理地址...": "여기에 프록시 주소를 입력하세요...",
-    "代理地址（示例：http://127.0.0.1:10809）": "프록시 주소 (예: http://127.0.0.1:10809）",
-    "🔄 设置代理地址": "🔄 프록시 주소 설정",
-    "🔙 恢复默认网络设置": "🔙 네트워크 설정 초기화",
-    "🔄 检查更新...": "🔄 업데이트 확인...",
-    "取消": "취소",
-    "更新": "업데이트",
-    "详情": "상세",
-    "好": "예",
-    "川虎Chat 🚀": "Chuanhu Chat 🚀",
-    "开始实时传输回答……": "실시간 응답 출력 시작...",
-    "Token 计数: ": "토큰 수: ",
-    "，本次对话累计消耗了 ": "，이 대화의 전체 비용은 ",
-    "**获取API使用情况失败**": "**API 사용량 가져오기 실패**",
-    "**获取API使用情况失败**，需在填写`config.json`中正确填写sensitive_id": "**API 사용량 가져오기 실패**. `config.json`에 올바른 `sensitive_id`를 입력해야 합니다",
-    "**获取API使用情况失败**，sensitive_id错误或已过期": "**API 사용량 가져오기 실패**. sensitive_id가 잘못되었거나 만료되었습니다",
-    "**本月使用金额** ": "**이번 달 사용금액** ",
-    "本月使用金额": "이번 달 사용금액",
-    "获取API使用情况失败:": "API 사용량 가져오기 실패:",
-    "API密钥更改为了": "API 키가 변경되었습니다.",
-    "JSON解析错误,收到的内容: ": "JSON 파싱 에러, 응답: ",
-    "模型设置为了：": "설정된 모델: ",
-    "☹️发生了错误：": "☹️에러: ",
-    "获取对话时发生错误，请查看后台日志": "대화를 가져오는 중 에러가 발생했습니다. 백그라운드 로그를 확인하세요",
-    "请检查网络连接，或者API-Key是否有效。": "네트워크 연결 또는 API키가 유효한지 확인하세요",
-    "连接超时，无法获取对话。": "연결 시간 초과, 대화를 가져올 수 없습니다.",
-    "读取超时，无法获取对话。": "읽기 시간 초과, 대화를 가져올 수 없습니다.",
-    "代理错误，无法获取对话。": "프록시 에러, 대화를 가져올 수 없습니다.",
-    "SSL错误，无法获取对话。": "SSL 에러, 대화를 가져올 수 없습니다.",
-    "API key为空，请检查是��输入正确。": "API 키가 비어 있습니다. 올바르게 입력되었는지 확인하십세요.",
-    "请输入对话内容。": "대화 내용을 입력하세요.",
-    "账单信息不适用": "청구 정보를 가져올 수 없습니다",
-    "由Bilibili [土川虎虎虎](https://space.bilibili.com/29125536)、[明昭MZhao](https://space.bilibili.com/24807452) 和 [Keldos](https://github.com/Keldos-Li) 开发<br />访问川虎Chat的 [GitHub项目](https://github.com/GaiZhenbiao/ChuanhuChatGPT) 下载最新版脚本": "제작: Bilibili [土川虎虎虎](https://space.bilibili.com/29125536), [明昭MZhao](https://space.bilibili.com/24807452), [Keldos](https://github.com/Keldos-Li)\n\n최신 코드 다운로드: [GitHub](https://github.com/GaiZhenbiao/ChuanhuChatGPT)",
-    "切换亮暗色主题": "라이트/다크 테마 전환",
-    "您的IP区域：未知。": "IP 지역: 알 수 없음.",
-    "获取IP地理位置失败。原因：": "다음과 같은 이유로 IP 위치를 가져올 수 없습니다. 이유: ",
-    "。你仍然可以使用聊天功能。": ". 채팅 기능을 계속 사용할 수 있습니다.",
-    "您的IP区域：": "당신의 IP 지역: ",
-    "总结": "요약",
-    "生成内容总结中……": "콘텐츠 요약 생성중...",
-    "上传": "업로드",
-    "由于下面的原因，Google 拒绝返回 PaLM 的回答：\n\n": "구글은 다음과 같은 이유로 인해 PaLM의 응답을 거부합니다: \n\n"
-}

locale/sv-SE.json

@@ -1,84 +0,0 @@
-{  
-    "未命名对话历史记录": "Onämnd Dialoghistorik",  
-    "在这里输入": "Skriv in här",  
-    "🧹 新的对话": "🧹 Ny Dialog",  
-    "🔄 重新生成": "🔄 Regenerera",  
-    "🗑️ 删除最旧对话": "🗑️ Ta bort äldsta dialogen",  
-    "🗑️ 删除最新对话": "🗑️ Ta bort senaste dialogen",  
-    "模型": "Modell",  
-    "多账号模式已开启，无需输入key，可直接开始对话": "Flerkontoläge är aktiverat, ingen nyckel behövs, du kan starta dialogen direkt",  
-    "**发送消息** 或 **提交key** 以显示额度": "**Skicka meddelande** eller **Skicka in nyckel** för att visa kredit",  
-    "选择模型": "Välj Modell",  
-    "选择LoRA模型": "Välj LoRA Modell",  
-    "实时传输回答": "Strömmande utdata",  
-    "单轮对话": "Enkel dialog",  
-    "使用在线搜索": "Använd online-sökning",  
-    "选择回复语言（针对搜索&索引功能）": "Välj svarspråk (för sök- och indexfunktion)",  
-    "上传索引文件": "Ladda upp",  
-    "双栏pdf": "Två-kolumns pdf",  
-    "识别公式": "Formel OCR",  
-    "在这里输入System Prompt...": "Skriv in System Prompt här...",  
-    "加载Prompt模板": "Ladda Prompt-mall",  
-    "选择Prompt模板集合文件": "Välj Prompt-mall Samlingsfil",  
-    "🔄 刷新": "🔄 Uppdatera",  
-    "从Prompt模板中加载": "Ladda från Prompt-mall",  
-    "保存/加载": "Spara/Ladda",  
-    "保存/加载对话历史记录": "Spara/Ladda Dialoghistorik",  
-    "从列表中加载对话": "Ladda dialog från lista",  
-    "设置文件名: 默认为.json，可选为.md": "Ställ in filnamn: standard är .json, valfritt är .md",  
-    "设置保存文件名": "Ställ in sparfilnamn",  
-    "对话历史记录": "Dialoghistorik",  
-    "💾 保存对话": "💾 Spara Dialog",  
-    "📝 导出为Markdown": "📝 Exportera som Markdown",  
-    "默认保存于history文件夹": "Sparas som standard i mappen history",  
-    "高级": "Avancerat",  
-    "# ⚠️ 务必谨慎更改 ⚠️": "# ⚠️ Var försiktig med ändringar. ⚠️",  
-    "参数": "Parametrar",  
-    "停止符，用英文逗号隔开...": "Skriv in stopptecken här, separerade med kommatecken...",  
-    "用于定位滥用行为": "Används för att lokalisera missbruk",  
-    "用户名": "Användarnamn",  
-    "网络设置": "Nätverksinställningar",  
-    "在这里输入API-Host...": "Skriv in API-Host här...",  
-    "🔄 切换API地址": "🔄 Byt API-adress",  
-    "在这里输入代理地址...": "Skriv in proxyadress här...",  
-    "代理地址（示例：http://127.0.0.1:10809）": "Proxyadress (exempel: http://127.0.0.1:10809)",  
-    "🔄 设置代理地址": "🔄 Ställ in Proxyadress",  
-    "🔙 恢复网络默认设置": "🔙 Återställ Nätverksinställningar",  
-    "🔄 检查更新...": "🔄 Sök efter uppdateringar...",  
-    "取消": "Avbryt",  
-    "更新": "Uppdatera",  
-    "详情": "Detaljer",  
-    "好": "OK",  
-    "川虎Chat 🚀": "Chuanhu Chat 🚀",  
-    "开始实时传输回答……": "Börjar strömma utdata...",  
-    "Token 计数: ": "Tokenräkning: ",  
-    "，本次对话累计消耗了 ": ", Total kostnad för denna dialog är ",  
-    "**获取API使用情况失败**": "**Misslyckades med att hämta API-användning**",  
-    "**获取API使用情况失败**，需在填写`config.json`中正确填写sensitive_id": "**Misslyckades med att hämta API-användning**, korrekt sensitive_id behövs i `config.json`",  
-    "**获取API使用情况失败**，sensitive_id错误或已过期": "**Misslyckades med att hämta API-användning**, felaktig eller utgången sensitive_id",  
-    "**本月使用金额** ": "**Månadens användning** ",  
-    "本月使用金额": "Månadens användning",  
-    "获取API使用情况失败:": "Misslyckades med att hämta API-användning:",  
-    "API密钥更改为了": "API-nyckeln har ändrats till",  
-    "JSON解析错误,收到的内容: ": "JSON-tolkningsfel, mottaget innehåll: ",  
-    "模型设置为了：": "Modellen är inställd på: ",  
-    "☹️发生了错误：": "☹️Fel: ",  
-    "获取对话时发生错误，请查看后台日志": "Ett fel uppstod när dialogen hämtades, kontrollera bakgrundsloggen",  
-    "请检查网络连接，或者API-Key是否有效。": "Kontrollera nätverksanslutningen eller om API-nyckeln är giltig.",  
-    "连接超时，无法获取对话。": "Anslutningen tog för lång tid, kunde inte hämta dialogen.",  
-    "读取超时，无法获取对话。": "Läsningen tog för lång tid, kunde inte hämta dialogen.",  
-    "代理错误，无法获取对话。": "Proxyfel, kunde inte hämta dialogen.",  
-    "SSL错误，无法获取对话。": "SSL-fel, kunde inte hämta dialogen.",  
-    "API key为空，请检查是否输入正确。": "API-nyckeln är tom, kontrollera om den är korrekt inmatad.",  
-    "请输入对话内容。": "Ange dialoginnehåll.",  
-    "账单信���不适用": "Faktureringsinformation är inte tillämplig",  
-    "由Bilibili [土川虎虎虎](https://space.bilibili.com/29125536)、[明昭MZhao](https://space.bilibili.com/24807452) 和 [Keldos](https://github.com/Keldos-Li) 开发<br />访问川虎Chat的 [GitHub项目](https://github.com/GaiZhenbiao/ChuanhuChatGPT) 下载最新版脚本": "Utvecklad av Bilibili [土川虎虎虎](https://space.bilibili.com/29125536), [明昭MZhao](https://space.bilibili.com/24807452) och [Keldos](https://github.com/Keldos-Li)\n\nLadda ner senaste koden från [GitHub](https://github.com/GaiZhenbiao/ChuanhuChatGPT)",  
-    "切换亮暗色主题": "Byt ljus/mörk tema",  
-    "您的IP区域：未知。": "Din IP-region: Okänd.",  
-    "获取IP地理位置失败。原因：": "Misslyckades med att hämta IP-plats. Orsak: ",  
-    "。你仍然可以使用聊天功能。": ". Du kan fortfarande använda chattfunktionen.",  
-    "您的IP区域：": "Din IP-region: ",  
-    "总结": "Sammanfatta",  
-    "生成内容总结中……": "Genererar innehållssammanfattning...",  
-    "由于下面的原因，Google 拒绝返回 PaLM 的回答：\n\n": "På grund av följande skäl vägrar Google att ge ett svar till PaLM: \n\n"  
-}  

modules/base_model.py

@@ -0,0 +1,561 @@
+from __future__ import annotations
+from typing import TYPE_CHECKING, List
+
+import logging
+import json
+import commentjson as cjson
+import os
+import sys
+import requests
+import urllib3
+import traceback
+
+from tqdm import tqdm
+import colorama
+from duckduckgo_search import ddg
+import asyncio
+import aiohttp
+from enum import Enum
+
+from .presets import *
+from .llama_func import *
+from .utils import *
+from . import shared
+from .config import retrieve_proxy
+
+
+class ModelType(Enum):
+    Unknown = -1
+    OpenAI = 0
+    ChatGLM = 1
+    LLaMA = 2
+    XMChat = 3
+
+    @classmethod
+    def get_type(cls, model_name: str):
+        model_type = None
+        model_name_lower = model_name.lower()
+        if "gpt" in model_name_lower:
+            model_type = ModelType.OpenAI
+        elif "chatglm" in model_name_lower:
+            model_type = ModelType.ChatGLM
+        elif "llama" in model_name_lower or "alpaca" in model_name_lower:
+            model_type = ModelType.LLaMA
+        elif "xmchat" in model_name_lower:
+            model_type = ModelType.XMChat
+        else:
+            model_type = ModelType.Unknown
+        return model_type
+
+
+class BaseLLMModel:
+    def __init__(
+        self,
+        model_name,
+        system_prompt="",
+        temperature=1.0,
+        top_p=1.0,
+        n_choices=1,
+        stop=None,
+        max_generation_token=None,
+        presence_penalty=0,
+        frequency_penalty=0,
+        logit_bias=None,
+        user="",
+    ) -> None:
+        self.history = []
+        self.all_token_counts = []
+        self.model_name = model_name
+        self.model_type = ModelType.get_type(model_name)
+        try:
+            self.token_upper_limit = MODEL_TOKEN_LIMIT[model_name]
+        except KeyError:
+            self.token_upper_limit = DEFAULT_TOKEN_LIMIT
+        self.interrupted = False
+        self.system_prompt = system_prompt
+        self.api_key = None
+        self.need_api_key = False
+        self.single_turn = False
+
+        self.temperature = temperature
+        self.top_p = top_p
+        self.n_choices = n_choices
+        self.stop_sequence = stop
+        self.max_generation_token = None
+        self.presence_penalty = presence_penalty
+        self.frequency_penalty = frequency_penalty
+        self.logit_bias = logit_bias
+        self.user_identifier = user
+
+    def get_answer_stream_iter(self):
+        """stream predict, need to be implemented
+        conversations are stored in self.history, with the most recent question, in OpenAI format
+        should return a generator, each time give the next word (str) in the answer
+        """
+        logging.warning("stream predict not implemented, using at once predict instead")
+        response, _ = self.get_answer_at_once()
+        yield response
+
+    def get_answer_at_once(self):
+        """predict at once, need to be implemented
+        conversations are stored in self.history, with the most recent question, in OpenAI format
+        Should return:
+        the answer (str)
+        total token count (int)
+        """
+        logging.warning("at once predict not implemented, using stream predict instead")
+        response_iter = self.get_answer_stream_iter()
+        count = 0
+        for response in response_iter:
+            count += 1
+        return response, sum(self.all_token_counts) + count
+
+    def billing_info(self):
+        """get billing infomation, inplement if needed"""
+        logging.warning("billing info not implemented, using default")
+        return BILLING_NOT_APPLICABLE_MSG
+
+    def count_token(self, user_input):
+        """get token count from input, implement if needed"""
+        logging.warning("token count not implemented, using default")
+        return len(user_input)
+
+    def stream_next_chatbot(self, inputs, chatbot, fake_input=None, display_append=""):
+        def get_return_value():
+            return chatbot, status_text
+
+        status_text = i18n("开始实时传输回答……")
+        if fake_input:
+            chatbot.append((fake_input, ""))
+        else:
+            chatbot.append((inputs, ""))
+
+        user_token_count = self.count_token(inputs)
+        self.all_token_counts.append(user_token_count)
+        logging.debug(f"输入token计数: {user_token_count}")
+
+        stream_iter = self.get_answer_stream_iter()
+
+        for partial_text in stream_iter:
+            chatbot[-1] = (chatbot[-1][0], partial_text + display_append)
+            self.all_token_counts[-1] += 1
+            status_text = self.token_message()
+            yield get_return_value()
+            if self.interrupted:
+                self.recover()
+                break
+        self.history.append(construct_assistant(partial_text))
+
+    def next_chatbot_at_once(self, inputs, chatbot, fake_input=None, display_append=""):
+        if fake_input:
+            chatbot.append((fake_input, ""))
+        else:
+            chatbot.append((inputs, ""))
+        if fake_input is not None:
+            user_token_count = self.count_token(fake_input)
+        else:
+            user_token_count = self.count_token(inputs)
+        self.all_token_counts.append(user_token_count)
+        ai_reply, total_token_count = self.get_answer_at_once()
+        self.history.append(construct_assistant(ai_reply))
+        if fake_input is not None:
+            self.history[-2] = construct_user(fake_input)
+        chatbot[-1] = (chatbot[-1][0], ai_reply + display_append)
+        if fake_input is not None:
+            self.all_token_counts[-1] += count_token(construct_assistant(ai_reply))
+        else:
+            self.all_token_counts[-1] = total_token_count - sum(self.all_token_counts)
+        status_text = self.token_message()
+        return chatbot, status_text
+
+    def handle_file_upload(self, files, chatbot):
+        """if the model accepts multi modal input, implement this function"""
+        status = gr.Markdown.update()
+        if files:
+            construct_index(self.api_key, file_src=files)
+            status = "索引构建完成"
+        return gr.Files.update(), chatbot, status
+
+    def prepare_inputs(self, real_inputs, use_websearch, files, reply_language, chatbot):
+        fake_inputs = None
+        display_append = []
+        limited_context = False
+        fake_inputs = real_inputs
+        if files:
+            from llama_index.indices.vector_store.base_query import GPTVectorStoreIndexQuery
+            from llama_index.indices.query.schema import QueryBundle
+            from langchain.embeddings.huggingface import HuggingFaceEmbeddings
+            from langchain.chat_models import ChatOpenAI
+            from llama_index import (
+                GPTSimpleVectorIndex,
+                ServiceContext,
+                LangchainEmbedding,
+                OpenAIEmbedding,
+            )
+            limited_context = True
+            msg = "加载索引中……"
+            logging.info(msg)
+            # yield chatbot + [(inputs, "")], msg
+            index = construct_index(self.api_key, file_src=files)
+            assert index is not None, "获取索引失败"
+            msg = "索引获取成功，生成回答中……"
+            logging.info(msg)
+            if local_embedding or self.model_type != ModelType.OpenAI:
+                embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name = "sentence-transformers/distiluse-base-multilingual-cased-v2"))
+            else:
+                embed_model = OpenAIEmbedding()
+            # yield chatbot + [(inputs, "")], msg
+            with retrieve_proxy():
+                prompt_helper = PromptHelper(
+                    max_input_size=4096,
+                    num_output=5,
+                    max_chunk_overlap=20,
+                    chunk_size_limit=600,
+                )
+                from llama_index import ServiceContext
+
+                service_context = ServiceContext.from_defaults(
+                    prompt_helper=prompt_helper, embed_model=embed_model
+                )
+                query_object = GPTVectorStoreIndexQuery(
+                    index.index_struct,
+                    service_context=service_context,
+                    similarity_top_k=5,
+                    vector_store=index._vector_store,
+                    docstore=index._docstore,
+                )
+                query_bundle = QueryBundle(real_inputs)
+                nodes = query_object.retrieve(query_bundle)
+            reference_results = [n.node.text for n in nodes]
+            reference_results = add_source_numbers(reference_results, use_source=False)
+            display_append = add_details(reference_results)
+            display_append = "\n\n" + "".join(display_append)
+            real_inputs = (
+                replace_today(PROMPT_TEMPLATE)
+                .replace("{query_str}", real_inputs)
+                .replace("{context_str}", "\n\n".join(reference_results))
+                .replace("{reply_language}", reply_language)
+            )
+        elif use_websearch:
+            limited_context = True
+            search_results = ddg(real_inputs, max_results=5)
+            reference_results = []
+            for idx, result in enumerate(search_results):
+                logging.debug(f"搜索结果{idx + 1}：{result}")
+                domain_name = urllib3.util.parse_url(result["href"]).host
+                reference_results.append([result["body"], result["href"]])
+                display_append.append(
+                    # f"{idx+1}. [{domain_name}]({result['href']})\n"
+                    f"<li><a href=\"{result['href']}\" target=\"_blank\">{domain_name}</a></li>\n"
+                )
+            reference_results = add_source_numbers(reference_results)
+            display_append = "<ol>\n\n" + "".join(display_append) + "</ol>"
+            real_inputs = (
+                replace_today(WEBSEARCH_PTOMPT_TEMPLATE)
+                .replace("{query}", real_inputs)
+                .replace("{web_results}", "\n\n".join(reference_results))
+                .replace("{reply_language}", reply_language)
+            )
+        else:
+            display_append = ""
+        return limited_context, fake_inputs, display_append, real_inputs, chatbot
+
+    def predict(
+        self,
+        inputs,
+        chatbot,
+        stream=False,
+        use_websearch=False,
+        files=None,
+        reply_language="中文",
+        should_check_token_count=True,
+    ):  # repetition_penalty, top_k
+
+        status_text = "开始生成回答……"
+        logging.info(
+            "输入为：" + colorama.Fore.BLUE + f"{inputs}" + colorama.Style.RESET_ALL
+        )
+        if should_check_token_count:
+            yield chatbot + [(inputs, "")], status_text
+        if reply_language == "跟随问题语言（不稳定）":
+            reply_language = "the same language as the question, such as English, 中文, 日本語, Español, Français, or Deutsch."
+
+        limited_context, fake_inputs, display_append, inputs, chatbot = self.prepare_inputs(real_inputs=inputs, use_websearch=use_websearch, files=files, reply_language=reply_language, chatbot=chatbot)
+        yield chatbot + [(fake_inputs, "")], status_text
+
+        if (
+            self.need_api_key and
+            self.api_key is None
+            and not shared.state.multi_api_key
+        ):
+            status_text = STANDARD_ERROR_MSG + NO_APIKEY_MSG
+            logging.info(status_text)
+            chatbot.append((inputs, ""))
+            if len(self.history) == 0:
+                self.history.append(construct_user(inputs))
+                self.history.append("")
+                self.all_token_counts.append(0)
+            else:
+                self.history[-2] = construct_user(inputs)
+            yield chatbot + [(inputs, "")], status_text
+            return
+        elif len(inputs.strip()) == 0:
+            status_text = STANDARD_ERROR_MSG + NO_INPUT_MSG
+            logging.info(status_text)
+            yield chatbot + [(inputs, "")], status_text
+            return
+
+        if self.single_turn:
+            self.history = []
+            self.all_token_counts = []
+        self.history.append(construct_user(inputs))
+
+        try:
+            if stream:
+                logging.debug("使用流式传输")
+                iter = self.stream_next_chatbot(
+                    inputs,
+                    chatbot,
+                    fake_input=fake_inputs,
+                    display_append=display_append,
+                )
+                for chatbot, status_text in iter:
+                    yield chatbot, status_text
+            else:
+                logging.debug("不使用流式传输")
+                chatbot, status_text = self.next_chatbot_at_once(
+                    inputs,
+                    chatbot,
+                    fake_input=fake_inputs,
+                    display_append=display_append,
+                )
+                yield chatbot, status_text
+        except Exception as e:
+            traceback.print_exc()
+            status_text = STANDARD_ERROR_MSG + str(e)
+            yield chatbot, status_text
+
+        if len(self.history) > 1 and self.history[-1]["content"] != inputs:
+            logging.info(
+                "回答为："
+                + colorama.Fore.BLUE
+                + f"{self.history[-1]['content']}"
+                + colorama.Style.RESET_ALL
+            )
+
+        if limited_context:
+            # self.history = self.history[-4:]
+            # self.all_token_counts = self.all_token_counts[-2:]
+            self.history = []
+            self.all_token_counts = []
+
+        max_token = self.token_upper_limit - TOKEN_OFFSET
+
+        if sum(self.all_token_counts) > max_token and should_check_token_count:
+            count = 0
+            while (
+                sum(self.all_token_counts)
+                > self.token_upper_limit * REDUCE_TOKEN_FACTOR
+                and sum(self.all_token_counts) > 0
+            ):
+                count += 1
+                del self.all_token_counts[0]
+                del self.history[:2]
+            logging.info(status_text)
+            status_text = f"为了防止token超限，模型忘记了早期的 {count} 轮对话"
+            yield chatbot, status_text
+
+    def retry(
+        self,
+        chatbot,
+        stream=False,
+        use_websearch=False,
+        files=None,
+        reply_language="中文",
+    ):
+        logging.debug("重试中……")
+        if len(self.history) > 0:
+            inputs = self.history[-2]["content"]
+            del self.history[-2:]
+            self.all_token_counts.pop()
+        elif len(chatbot) > 0:
+            inputs = chatbot[-1][0]
+        else:
+            yield chatbot, f"{STANDARD_ERROR_MSG}上下文是空的"
+            return
+
+        iter = self.predict(
+            inputs,
+            chatbot,
+            stream=stream,
+            use_websearch=use_websearch,
+            files=files,
+            reply_language=reply_language,
+        )
+        for x in iter:
+            yield x
+        logging.debug("重试完毕")
+
+    # def reduce_token_size(self, chatbot):
+    #     logging.info("开始减少token数量……")
+    #     chatbot, status_text = self.next_chatbot_at_once(
+    #         summarize_prompt,
+    #         chatbot
+    #     )
+    #     max_token_count = self.token_upper_limit * REDUCE_TOKEN_FACTOR
+    #     num_chat = find_n(self.all_token_counts, max_token_count)
+    #     logging.info(f"previous_token_count: {self.all_token_counts}, keeping {num_chat} chats")
+    #     chatbot = chatbot[:-1]
+    #     self.history = self.history[-2*num_chat:] if num_chat > 0 else []
+    #     self.all_token_counts = self.all_token_counts[-num_chat:] if num_chat > 0 else []
+    #     msg = f"保留了最近{num_chat}轮对话"
+    #     logging.info(msg)
+    #     logging.info("减少token数量完毕")
+    #     return chatbot, msg + "，" + self.token_message(self.all_token_counts if len(self.all_token_counts) > 0 else [0])
+
+    def interrupt(self):
+        self.interrupted = True
+
+    def recover(self):
+        self.interrupted = False
+
+    def set_token_upper_limit(self, new_upper_limit):
+        self.token_upper_limit = new_upper_limit
+        print(f"token上限设置为{new_upper_limit}")
+
+    def set_temperature(self, new_temperature):
+        self.temperature = new_temperature
+
+    def set_top_p(self, new_top_p):
+        self.top_p = new_top_p
+
+    def set_n_choices(self, new_n_choices):
+        self.n_choices = new_n_choices
+
+    def set_stop_sequence(self, new_stop_sequence: str):
+        new_stop_sequence = new_stop_sequence.split(",")
+        self.stop_sequence = new_stop_sequence
+
+    def set_max_tokens(self, new_max_tokens):
+        self.max_generation_token = new_max_tokens
+
+    def set_presence_penalty(self, new_presence_penalty):
+        self.presence_penalty = new_presence_penalty
+
+    def set_frequency_penalty(self, new_frequency_penalty):
+        self.frequency_penalty = new_frequency_penalty
+
+    def set_logit_bias(self, logit_bias):
+        logit_bias = logit_bias.split()
+        bias_map = {}
+        encoding = tiktoken.get_encoding("cl100k_base")
+        for line in logit_bias:
+            word, bias_amount = line.split(":")
+            if word:
+                for token in encoding.encode(word):
+                    bias_map[token] = float(bias_amount)
+        self.logit_bias = bias_map
+
+    def set_user_identifier(self, new_user_identifier):
+        self.user_identifier = new_user_identifier
+
+    def set_system_prompt(self, new_system_prompt):
+        self.system_prompt = new_system_prompt
+
+    def set_key(self, new_access_key):
+        self.api_key = new_access_key.strip()
+        msg = i18n("API密钥更改为了") + hide_middle_chars(self.api_key)
+        logging.info(msg)
+        return self.api_key, msg
+
+    def set_single_turn(self, new_single_turn):
+        self.single_turn = new_single_turn
+
+    def reset(self):
+        self.history = []
+        self.all_token_counts = []
+        self.interrupted = False
+        return [], self.token_message([0])
+
+    def delete_first_conversation(self):
+        if self.history:
+            del self.history[:2]
+            del self.all_token_counts[0]
+        return self.token_message()
+
+    def delete_last_conversation(self, chatbot):
+        if len(chatbot) > 0 and STANDARD_ERROR_MSG in chatbot[-1][1]:
+            msg = "由于包含报错信息，只删除chatbot记录"
+            chatbot.pop()
+            return chatbot, self.history
+        if len(self.history) > 0:
+            self.history.pop()
+            self.history.pop()
+        if len(chatbot) > 0:
+            msg = "删除了一组chatbot对话"
+            chatbot.pop()
+        if len(self.all_token_counts) > 0:
+            msg = "删除了一组对话的token计数记录"
+            self.all_token_counts.pop()
+        msg = "删除了一组对话"
+        return chatbot, msg
+
+    def token_message(self, token_lst=None):
+        if token_lst is None:
+            token_lst = self.all_token_counts
+        token_sum = 0
+        for i in range(len(token_lst)):
+            token_sum += sum(token_lst[: i + 1])
+        return i18n("Token 计数: ") + f"{sum(token_lst)}" + i18n("，本次对话累计消耗了 ") + f"{token_sum} tokens"
+
+    def save_chat_history(self, filename, chatbot, user_name):
+        if filename == "":
+            return
+        if not filename.endswith(".json"):
+            filename += ".json"
+        return save_file(filename, self.system_prompt, self.history, chatbot, user_name)
+
+    def export_markdown(self, filename, chatbot, user_name):
+        if filename == "":
+            return
+        if not filename.endswith(".md"):
+            filename += ".md"
+        return save_file(filename, self.system_prompt, self.history, chatbot, user_name)
+
+    def load_chat_history(self, filename, chatbot, user_name):
+        logging.debug(f"{user_name} 加载对话历史中……")
+        if type(filename) != str:
+            filename = filename.name
+        try:
+            with open(os.path.join(HISTORY_DIR, user_name, filename), "r") as f:
+                json_s = json.load(f)
+            try:
+                if type(json_s["history"][0]) == str:
+                    logging.info("历史记录格式为旧版，正在转换……")
+                    new_history = []
+                    for index, item in enumerate(json_s["history"]):
+                        if index % 2 == 0:
+                            new_history.append(construct_user(item))
+                        else:
+                            new_history.append(construct_assistant(item))
+                    json_s["history"] = new_history
+                    logging.info(new_history)
+            except:
+                # 没有对话历史
+                pass
+            logging.debug(f"{user_name} 加载对话历史完毕")
+            self.history = json_s["history"]
+            return filename, json_s["system"], json_s["chatbot"]
+        except FileNotFoundError:
+            logging.warning(f"{user_name} 没有找到对话历史文件，不执行任何操作")
+            return filename, self.system_prompt, chatbot
+
+    def like(self):
+        """like the last response, implement if needed
+        """
+        return gr.update()
+
+    def dislike(self):
+        """dislike the last response, implement if needed
+        """
+        return gr.update()

modules/config.py

@@ -11,7 +11,6 @@ from . import presets
 
 __all__ = [
     "my_api_key",
-    "sensitive_id",
     "authflag",
     "auth_list",
     "dockerflag",
@@ -24,11 +23,8 @@ __all__ = [
     "server_name",
     "server_port",
     "share",
-    "check_update",
-    "latex_delimiters_set",
     "hide_history_when_not_logged_in",
-    "default_chuanhu_assistant_model",
-    "show_api_billing"
+    "default_chuanhu_assistant_model"
 ]
 
 # 添加一个统一的config文件，避免文件过多造成的疑惑（优先级最低）
@@ -39,22 +35,10 @@ if os.path.exists("config.json"):
 else:
     config = {}
 
-
-def load_config_to_environ(key_list):
-    global config
-    for key in key_list:
-        if key in config:
-            os.environ[key.upper()] = os.environ.get(key.upper(), config[key])
-
-
 lang_config = config.get("language", "auto")
 language = os.environ.get("LANGUAGE", lang_config)
 
-hide_history_when_not_logged_in = config.get(
-    "hide_history_when_not_logged_in", False)
-check_update = config.get("check_update", True)
-show_api_billing = config.get("show_api_billing", False)
-show_api_billing = bool(os.environ.get("SHOW_API_BILLING", show_api_billing))
+hide_history_when_not_logged_in = config.get("hide_history_when_not_logged_in", False)
 
 if os.path.exists("api_key.txt"):
     logging.info("检测到api_key.txt文件，正在进行迁移...")
@@ -68,39 +52,26 @@ if os.path.exists("auth.json"):
     logging.info("检测到auth.json文件，正在进行迁移...")
     auth_list = []
     with open("auth.json", "r", encoding='utf-8') as f:
-        auth = json.load(f)
-        for _ in auth:
-            if auth[_]["username"] and auth[_]["password"]:
-                auth_list.append((auth[_]["username"], auth[_]["password"]))
-            else:
-                logging.error("请检查auth.json文件中的用户名和密码！")
-                sys.exit(1)
+            auth = json.load(f)
+            for _ in auth:
+                if auth[_]["username"] and auth[_]["password"]:
+                    auth_list.append((auth[_]["username"], auth[_]["password"]))
+                else:
+                    logging.error("请检查auth.json文件中的用户名和密码！")
+                    sys.exit(1)
     config["users"] = auth_list
     os.rename("auth.json", "auth(deprecated).json")
     with open("config.json", "w", encoding='utf-8') as f:
         json.dump(config, f, indent=4, ensure_ascii=False)
 
-# 处理docker if we are running in Docker
+## 处理docker if we are running in Docker
 dockerflag = config.get("dockerflag", False)
 if os.environ.get("dockerrun") == "yes":
     dockerflag = True
 
-# 处理 api-key 以及 允许的用户列表
+## 处理 api-key 以及 允许的用户列表
 my_api_key = config.get("openai_api_key", "")
 my_api_key = os.environ.get("OPENAI_API_KEY", my_api_key)
-os.environ["OPENAI_API_KEY"] = my_api_key
-os.environ["OPENAI_EMBEDDING_API_KEY"] = my_api_key
-
-if config.get("legacy_api_usage", False):
-    sensitive_id = config.get("sensitive_id", "")
-    sensitive_id = os.environ.get("SENSITIVE_ID", sensitive_id)
-else:
-    sensitive_id = my_api_key
-
-google_palm_api_key = config.get("google_palm_api_key", "")
-google_palm_api_key = os.environ.get(
-    "GOOGLE_PALM_API_KEY", google_palm_api_key)
-os.environ["GOOGLE_PALM_API_KEY"] = google_palm_api_key
 
 xmchat_api_key = config.get("xmchat_api_key", "")
 os.environ["XMCHAT_API_KEY"] = xmchat_api_key
@@ -110,14 +81,11 @@ os.environ["MINIMAX_API_KEY"] = minimax_api_key
 minimax_group_id = config.get("minimax_group_id", "")
 os.environ["MINIMAX_GROUP_ID"] = minimax_group_id
 
-load_config_to_environ(["openai_api_type", "azure_openai_api_key", "azure_openai_api_base_url",
-                       "azure_openai_api_version", "azure_deployment_name", "azure_embedding_deployment_name", "azure_embedding_model_name"])
-
 
 usage_limit = os.environ.get("USAGE_LIMIT", config.get("usage_limit", 120))
 
-# 多账户机制
-multi_api_key = config.get("multi_api_key", False)  # 是否开启多账户机制
+## 多账户机制
+multi_api_key = config.get("multi_api_key", False) # 是否开启多账户机制
 if multi_api_key:
     api_key_list = config.get("api_key_list", [])
     if len(api_key_list) == 0:
@@ -125,26 +93,21 @@ if multi_api_key:
         sys.exit(1)
     shared.state.set_api_key_queue(api_key_list)
 
-auth_list = config.get("users", [])  # 实际上是使用者的列表
+auth_list = config.get("users", []) # 实际上是使用者的列表
 authflag = len(auth_list) > 0  # 是否开启认证的状态值，改为判断auth_list长度
 
 # 处理自定义的api_host，优先读环境变量的配置，如果存在则自动装配
-api_host = os.environ.get(
-    "OPENAI_API_BASE", config.get("openai_api_base", None))
+api_host = os.environ.get("OPENAI_API_BASE", config.get("openai_api_base", None))
 if api_host is not None:
     shared.state.set_api_host(api_host)
-    os.environ["OPENAI_API_BASE"] = f"{api_host}/v1"
-    logging.info(f"OpenAI API Base set to: {os.environ['OPENAI_API_BASE']}")
 
-default_chuanhu_assistant_model = config.get(
-    "default_chuanhu_assistant_model", "gpt-3.5-turbo")
+default_chuanhu_assistant_model = config.get("default_chuanhu_assistant_model", "gpt-3.5-turbo")
 for x in ["GOOGLE_CSE_ID", "GOOGLE_API_KEY", "WOLFRAM_ALPHA_APPID", "SERPAPI_API_KEY"]:
     if config.get(x, None) is not None:
         os.environ[x] = config[x]
 
-
 @contextmanager
-def retrieve_openai_api(api_key=None):
+def retrieve_openai_api(api_key = None):
     old_api_key = os.environ.get("OPENAI_API_KEY", "")
     if api_key is None:
         os.environ["OPENAI_API_KEY"] = my_api_key
@@ -154,26 +117,24 @@ def retrieve_openai_api(api_key=None):
         yield api_key
     os.environ["OPENAI_API_KEY"] = old_api_key
 
-
-# 处理log
+## 处理log
 log_level = config.get("log_level", "INFO")
 logging.basicConfig(
     level=log_level,
     format="%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s",
 )
 
-# 处理代理：
-http_proxy = os.environ.get("HTTP_PROXY", "")
-https_proxy = os.environ.get("HTTPS_PROXY", "")
-http_proxy = config.get("http_proxy", http_proxy)
-https_proxy = config.get("https_proxy", https_proxy)
+## 处理代理：
+http_proxy = config.get("http_proxy", "")
+https_proxy = config.get("https_proxy", "")
+http_proxy = os.environ.get("HTTP_PROXY", http_proxy)
+https_proxy = os.environ.get("HTTPS_PROXY", https_proxy)
 
 # 重置系统变量，在不需要设置的时候不设置环境变量，以免引起全局代理报错
 os.environ["HTTP_PROXY"] = ""
 os.environ["HTTPS_PROXY"] = ""
 
-local_embedding = config.get("local_embedding", False)  # 是否使用本地embedding
-
+local_embedding = config.get("local_embedding", False) # 是否使用本地embedding
 
 @contextmanager
 def retrieve_proxy(proxy=None):
@@ -190,62 +151,22 @@ def retrieve_proxy(proxy=None):
         old_var = os.environ["HTTP_PROXY"], os.environ["HTTPS_PROXY"]
         os.environ["HTTP_PROXY"] = http_proxy
         os.environ["HTTPS_PROXY"] = https_proxy
-        yield http_proxy, https_proxy  # return new proxy
+        yield http_proxy, https_proxy # return new proxy
 
         # return old proxy
         os.environ["HTTP_PROXY"], os.environ["HTTPS_PROXY"] = old_var
 
 
-# 处理latex options
-user_latex_option = config.get("latex_option", "default")
-if user_latex_option == "default":
-    latex_delimiters_set = [
-        {"left": "$$", "right": "$$", "display": True},
-        {"left": "$", "right": "$", "display": False},
-        {"left": "\\(", "right": "\\)", "display": False},
-        {"left": "\\[", "right": "\\]", "display": True},
-    ]
-elif user_latex_option == "strict":
-    latex_delimiters_set = [
-        {"left": "$$", "right": "$$", "display": True},
-        {"left": "\\(", "right": "\\)", "display": False},
-        {"left": "\\[", "right": "\\]", "display": True},
-    ]
-elif user_latex_option == "all":
-    latex_delimiters_set = [
-        {"left": "$$", "right": "$$", "display": True},
-        {"left": "$", "right": "$", "display": False},
-        {"left": "\\(", "right": "\\)", "display": False},
-        {"left": "\\[", "right": "\\]", "display": True},
-        {"left": "\\begin{equation}", "right": "\\end{equation}", "display": True},
-        {"left": "\\begin{align}", "right": "\\end{align}", "display": True},
-        {"left": "\\begin{alignat}", "right": "\\end{alignat}", "display": True},
-        {"left": "\\begin{gather}", "right": "\\end{gather}", "display": True},
-        {"left": "\\begin{CD}", "right": "\\end{CD}", "display": True},
-    ]
-elif user_latex_option == "disabled":
-    latex_delimiters_set = []
-else:
-    latex_delimiters_set = [
-        {"left": "$$", "right": "$$", "display": True},
-        {"left": "$", "right": "$", "display": False},
-        {"left": "\\(", "right": "\\)", "display": False},
-        {"left": "\\[", "right": "\\]", "display": True},
-    ]
-
-# 处理advance docs
+## 处理advance docs
 advance_docs = defaultdict(lambda: defaultdict(dict))
 advance_docs.update(config.get("advance_docs", {}))
-
-
 def update_doc_config(two_column_pdf):
     global advance_docs
     advance_docs["pdf"]["two_column"] = two_column_pdf
 
     logging.info(f"更新后的文件参数为：{advance_docs}")
 
-
-# 处理gradio.launch参数
+## 处理gradio.launch参数
 server_name = config.get("server_name", None)
 server_port = config.get("server_port", None)
 if server_name is None:

modules/index_func.py

@@ -47,12 +47,11 @@ def get_documents(file_src):
                     pdftext = parse_pdf(filepath, two_column).text
                 except:
                     pdftext = ""
-                    with open(filepath, "rb") as pdfFileObj:
+                    with open(filepath, "rb", encoding="utf-8") as pdfFileObj:
                         pdfReader = PyPDF2.PdfReader(pdfFileObj)
                         for page in tqdm(pdfReader.pages):
                             pdftext += page.extract_text()
-                texts = [Document(page_content=pdftext,
-                                  metadata={"source": filepath})]
+                texts = [Document(page_content=pdftext, metadata={"source": filepath})]
             elif file_type == ".docx":
                 logging.debug("Loading Word...")
                 from langchain.document_loaders import UnstructuredWordDocumentLoader
@@ -73,8 +72,7 @@ def get_documents(file_src):
                 text_list = excel_to_string(filepath)
                 texts = []
                 for elem in text_list:
-                    texts.append(Document(page_content=elem,
-                                 metadata={"source": filepath}))
+                    texts.append(Document(page_content=elem, metadata={"source": filepath}))
             else:
                 logging.debug("Loading text file...")
                 from langchain.document_loaders import TextLoader
@@ -117,16 +115,10 @@ def construct_index(
     index_path = f"./index/{index_name}"
     if local_embedding:
         from langchain.embeddings.huggingface import HuggingFaceEmbeddings
-        embeddings = HuggingFaceEmbeddings(
-            model_name="sentence-transformers/distiluse-base-multilingual-cased-v2")
+        embeddings = HuggingFaceEmbeddings(model_name = "sentence-transformers/distiluse-base-multilingual-cased-v2")
     else:
         from langchain.embeddings import OpenAIEmbeddings
-        if os.environ.get("OPENAI_API_TYPE", "openai") == "openai":
-            embeddings = OpenAIEmbeddings(openai_api_base=os.environ.get(
-                "OPENAI_API_BASE", None), openai_api_key=os.environ.get("OPENAI_EMBEDDING_API_KEY", api_key))
-        else:
-            embeddings = OpenAIEmbeddings(deployment=os.environ["AZURE_EMBEDDING_DEPLOYMENT_NAME"], openai_api_key=os.environ["AZURE_OPENAI_API_KEY"],
-                                          model=os.environ["AZURE_EMBEDDING_MODEL_NAME"], openai_api_base=os.environ["AZURE_OPENAI_API_BASE_URL"], openai_api_type="azure")
+        embeddings = OpenAIEmbeddings(openai_api_base=os.environ.get("OPENAI_API_BASE", None), openai_api_key=os.environ.get("OPENAI_EMBEDDING_API_KEY", api_key))
     if os.path.exists(index_path):
         logging.info("找到了缓存的索引文件，加载中……")
         return FAISS.load_local(index_path, embeddings)

modules/llama_func.py

@@ -0,0 +1,166 @@
+import os
+import logging
+
+from llama_index import download_loader
+from llama_index import (
+    Document,
+    LLMPredictor,
+    PromptHelper,
+    QuestionAnswerPrompt,
+    RefinePrompt,
+)
+import colorama
+import PyPDF2
+from tqdm import tqdm
+
+from modules.presets import *
+from modules.utils import *
+from modules.config import local_embedding
+
+
+def get_index_name(file_src):
+    file_paths = [x.name for x in file_src]
+    file_paths.sort(key=lambda x: os.path.basename(x))
+
+    md5_hash = hashlib.md5()
+    for file_path in file_paths:
+        with open(file_path, "rb") as f:
+            while chunk := f.read(8192):
+                md5_hash.update(chunk)
+
+    return md5_hash.hexdigest()
+
+
+def block_split(text):
+    blocks = []
+    while len(text) > 0:
+        blocks.append(Document(text[:1000]))
+        text = text[1000:]
+    return blocks
+
+
+def get_documents(file_src):
+    documents = []
+    logging.debug("Loading documents...")
+    logging.debug(f"file_src: {file_src}")
+    for file in file_src:
+        filepath = file.name
+        filename = os.path.basename(filepath)
+        file_type = os.path.splitext(filepath)[1]
+        logging.info(f"loading file: {filename}")
+        try:
+            if file_type == ".pdf":
+                logging.debug("Loading PDF...")
+                try:
+                    from modules.pdf_func import parse_pdf
+                    from modules.config import advance_docs
+
+                    two_column = advance_docs["pdf"].get("two_column", False)
+                    pdftext = parse_pdf(filepath, two_column).text
+                except:
+                    pdftext = ""
+                    with open(filepath, "rb") as pdfFileObj:
+                        pdfReader = PyPDF2.PdfReader(pdfFileObj)
+                        for page in tqdm(pdfReader.pages):
+                            pdftext += page.extract_text()
+                text_raw = pdftext
+            elif file_type == ".docx":
+                logging.debug("Loading Word...")
+                DocxReader = download_loader("DocxReader")
+                loader = DocxReader()
+                text_raw = loader.load_data(file=filepath)[0].text
+            elif file_type == ".epub":
+                logging.debug("Loading EPUB...")
+                EpubReader = download_loader("EpubReader")
+                loader = EpubReader()
+                text_raw = loader.load_data(file=filepath)[0].text
+            elif file_type == ".xlsx":
+                logging.debug("Loading Excel...")
+                text_list = excel_to_string(filepath)
+                for elem in text_list:
+                    documents.append(Document(elem))
+                continue
+            else:
+                logging.debug("Loading text file...")
+                with open(filepath, "r", encoding="utf-8") as f:
+                    text_raw = f.read()
+        except Exception as e:
+            logging.error(f"Error loading file: {filename}")
+            pass
+        text = add_space(text_raw)
+        # text = block_split(text)
+        # documents += text
+        documents += [Document(text)]
+    logging.debug("Documents loaded.")
+    return documents
+
+
+def construct_index(
+    api_key,
+    file_src,
+    max_input_size=4096,
+    num_outputs=5,
+    max_chunk_overlap=20,
+    chunk_size_limit=600,
+    embedding_limit=None,
+    separator=" ",
+):
+    from langchain.chat_models import ChatOpenAI
+    from langchain.embeddings.huggingface import HuggingFaceEmbeddings
+    from llama_index import GPTSimpleVectorIndex, ServiceContext, LangchainEmbedding, OpenAIEmbedding
+
+    if api_key:
+        os.environ["OPENAI_API_KEY"] = api_key
+    else:
+        # 由于一个依赖的愚蠢的设计，这里必须要有一个API KEY
+        os.environ["OPENAI_API_KEY"] = "sk-xxxxxxx"
+    chunk_size_limit = None if chunk_size_limit == 0 else chunk_size_limit
+    embedding_limit = None if embedding_limit == 0 else embedding_limit
+    separator = " " if separator == "" else separator
+
+    prompt_helper = PromptHelper(
+        max_input_size=max_input_size,
+        num_output=num_outputs,
+        max_chunk_overlap=max_chunk_overlap,
+        embedding_limit=embedding_limit,
+        chunk_size_limit=600,
+        separator=separator,
+    )
+    index_name = get_index_name(file_src)
+    if os.path.exists(f"./index/{index_name}.json"):
+        logging.info("找到了缓存的索引文件，加载中……")
+        return GPTSimpleVectorIndex.load_from_disk(f"./index/{index_name}.json")
+    else:
+        try:
+            documents = get_documents(file_src)
+            if local_embedding:
+                embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name = "sentence-transformers/distiluse-base-multilingual-cased-v2"))
+            else:
+                embed_model = OpenAIEmbedding()
+            logging.info("构建索引中……")
+            with retrieve_proxy():
+                service_context = ServiceContext.from_defaults(
+                    prompt_helper=prompt_helper,
+                    chunk_size_limit=chunk_size_limit,
+                    embed_model=embed_model,
+                )
+                index = GPTSimpleVectorIndex.from_documents(
+                    documents, service_context=service_context
+                )
+            logging.debug("索引构建完成！")
+            os.makedirs("./index", exist_ok=True)
+            index.save_to_disk(f"./index/{index_name}.json")
+            logging.debug("索引已保存至本地!")
+            return index
+
+        except Exception as e:
+            logging.error("索引构建失败！", e)
+            print(e)
+            return None
+
+
+def add_space(text):
+    punctuations = {"，": "， ", "。": "。 ", "？": "？ ", "！": "！ ", "：": "： ", "；": "； "}
+    for cn_punc, en_punc in punctuations.items():
+        text = text.replace(cn_punc, en_punc)
+    return text

modules/models.py

@@ -0,0 +1,625 @@
+from __future__ import annotations
+from typing import TYPE_CHECKING, List
+
+import logging
+import json
+import commentjson as cjson
+import os
+import sys
+import requests
+import urllib3
+import platform
+import base64
+from io import BytesIO
+from PIL import Image
+
+from tqdm import tqdm
+import colorama
+from duckduckgo_search import ddg
+import asyncio
+import aiohttp
+from enum import Enum
+import uuid
+
+from .presets import *
+from .llama_func import *
+from .utils import *
+from . import shared
+from .config import retrieve_proxy
+from modules import config
+from .base_model import BaseLLMModel, ModelType
+
+
+class OpenAIClient(BaseLLMModel):
+    def __init__(
+        self,
+        model_name,
+        api_key,
+        system_prompt=INITIAL_SYSTEM_PROMPT,
+        temperature=1.0,
+        top_p=1.0,
+    ) -> None:
+        super().__init__(
+            model_name=model_name,
+            temperature=temperature,
+            top_p=top_p,
+            system_prompt=system_prompt,
+        )
+        self.api_key = api_key
+        self.need_api_key = True
+        self._refresh_header()
+
+    def get_answer_stream_iter(self):
+        response = self._get_response(stream=True)
+        if response is not None:
+            iter = self._decode_chat_response(response)
+            partial_text = ""
+            for i in iter:
+                partial_text += i
+                yield partial_text
+        else:
+            yield STANDARD_ERROR_MSG + GENERAL_ERROR_MSG
+
+    def get_answer_at_once(self):
+        response = self._get_response()
+        response = json.loads(response.text)
+        content = response["choices"][0]["message"]["content"]
+        total_token_count = response["usage"]["total_tokens"]
+        return content, total_token_count
+
+    def count_token(self, user_input):
+        input_token_count = count_token(construct_user(user_input))
+        if self.system_prompt is not None and len(self.all_token_counts) == 0:
+            system_prompt_token_count = count_token(
+                construct_system(self.system_prompt)
+            )
+            return input_token_count + system_prompt_token_count
+        return input_token_count
+
+    def billing_info(self):
+        try:
+            curr_time = datetime.datetime.now()
+            last_day_of_month = get_last_day_of_month(
+                curr_time).strftime("%Y-%m-%d")
+            first_day_of_month = curr_time.replace(day=1).strftime("%Y-%m-%d")
+            usage_url = f"{shared.state.usage_api_url}?start_date={first_day_of_month}&end_date={last_day_of_month}"
+            try:
+                usage_data = self._get_billing_data(usage_url)
+            except Exception as e:
+                logging.error(f"获取API使用情况失败:" + str(e))
+                return i18n("**获取API使用情况失败**")
+            rounded_usage = "{:.5f}".format(usage_data["total_usage"] / 100)
+            return i18n("**本月使用金额** ") + f"\u3000 ${rounded_usage}"
+        except requests.exceptions.ConnectTimeout:
+            status_text = (
+                STANDARD_ERROR_MSG + CONNECTION_TIMEOUT_MSG + ERROR_RETRIEVE_MSG
+            )
+            return status_text
+        except requests.exceptions.ReadTimeout:
+            status_text = STANDARD_ERROR_MSG + READ_TIMEOUT_MSG + ERROR_RETRIEVE_MSG
+            return status_text
+        except Exception as e:
+            import traceback
+            traceback.print_exc()
+            logging.error(i18n("获取API使用情况失败:") + str(e))
+            return STANDARD_ERROR_MSG + ERROR_RETRIEVE_MSG
+
+    def set_token_upper_limit(self, new_upper_limit):
+        pass
+
+    @shared.state.switching_api_key  # 在不开启多账号模式的时候，这个装饰器不会起作用
+    def _get_response(self, stream=False):
+        openai_api_key = self.api_key
+        system_prompt = self.system_prompt
+        history = self.history
+        logging.debug(colorama.Fore.YELLOW +
+                      f"{history}" + colorama.Fore.RESET)
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {openai_api_key}",
+        }
+
+        if system_prompt is not None:
+            history = [construct_system(system_prompt), *history]
+
+        payload = {
+            "model": self.model_name,
+            "messages": history,
+            "temperature": self.temperature,
+            "top_p": self.top_p,
+            "n": self.n_choices,
+            "stream": stream,
+            "presence_penalty": self.presence_penalty,
+            "frequency_penalty": self.frequency_penalty,
+        }
+
+        if self.max_generation_token is not None:
+            payload["max_tokens"] = self.max_generation_token
+        if self.stop_sequence is not None:
+            payload["stop"] = self.stop_sequence
+        if self.logit_bias is not None:
+            payload["logit_bias"] = self.logit_bias
+        if self.user_identifier is not None:
+            payload["user"] = self.user_identifier
+
+        if stream:
+            timeout = TIMEOUT_STREAMING
+        else:
+            timeout = TIMEOUT_ALL
+
+        # 如果有自定义的api-host，使用自定义host发送请求，否则使用默认设置发送请求
+        if shared.state.completion_url != COMPLETION_URL:
+            logging.info(f"使用自定义API URL: {shared.state.completion_url}")
+
+        with retrieve_proxy():
+            try:
+                response = requests.post(
+                    shared.state.completion_url,
+                    headers=headers,
+                    json=payload,
+                    stream=stream,
+                    timeout=timeout,
+                )
+            except:
+                return None
+        return response
+
+    def _refresh_header(self):
+        self.headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}",
+        }
+
+    def _get_billing_data(self, billing_url):
+        with retrieve_proxy():
+            response = requests.get(
+                billing_url,
+                headers=self.headers,
+                timeout=TIMEOUT_ALL,
+            )
+
+        if response.status_code == 200:
+            data = response.json()
+            return data
+        else:
+            raise Exception(
+                f"API request failed with status code {response.status_code}: {response.text}"
+            )
+
+    def _decode_chat_response(self, response):
+        error_msg = ""
+        for chunk in response.iter_lines():
+            if chunk:
+                chunk = chunk.decode()
+                chunk_length = len(chunk)
+                try:
+                    chunk = json.loads(chunk[6:])
+                except json.JSONDecodeError:
+                    print(i18n("JSON解析错误,收到的内容: ") + f"{chunk}")
+                    error_msg += chunk
+                    continue
+                if chunk_length > 6 and "delta" in chunk["choices"][0]:
+                    if chunk["choices"][0]["finish_reason"] == "stop":
+                        break
+                    try:
+                        yield chunk["choices"][0]["delta"]["content"]
+                    except Exception as e:
+                        # logging.error(f"Error: {e}")
+                        continue
+        if error_msg:
+            raise Exception(error_msg)
+
+    def set_key(self, new_access_key):
+        ret = super().set_key(new_access_key)
+        self._refresh_header()
+        return ret
+
+
+class ChatGLM_Client(BaseLLMModel):
+    def __init__(self, model_name) -> None:
+        super().__init__(model_name=model_name)
+        from transformers import AutoTokenizer, AutoModel
+        import torch
+        global CHATGLM_TOKENIZER, CHATGLM_MODEL
+        if CHATGLM_TOKENIZER is None or CHATGLM_MODEL is None:
+            system_name = platform.system()
+            model_path = None
+            if os.path.exists("models"):
+                model_dirs = os.listdir("models")
+                if model_name in model_dirs:
+                    model_path = f"models/{model_name}"
+            if model_path is not None:
+                model_source = model_path
+            else:
+                model_source = f"THUDM/{model_name}"
+            CHATGLM_TOKENIZER = AutoTokenizer.from_pretrained(
+                model_source, trust_remote_code=True
+            )
+            quantified = False
+            if "int4" in model_name:
+                quantified = True
+            model = AutoModel.from_pretrained(
+                    model_source, trust_remote_code=True
+                )
+            if torch.cuda.is_available():
+                # run on CUDA
+                logging.info("CUDA is available, using CUDA")
+                model = model.half().cuda()
+            # mps加速还存在一些问题，暂时不使用
+            elif system_name == "Darwin" and model_path is not None and not quantified:
+                logging.info("Running on macOS, using MPS")
+                # running on macOS and model already downloaded
+                model = model.half().to("mps")
+            else:
+                logging.info("GPU is not available, using CPU")
+                model = model.float()
+            model = model.eval()
+            CHATGLM_MODEL = model
+
+    def _get_glm_style_input(self):
+        history = [x["content"] for x in self.history]
+        query = history.pop()
+        logging.debug(colorama.Fore.YELLOW +
+                      f"{history}" + colorama.Fore.RESET)
+        assert (
+            len(history) % 2 == 0
+        ), f"History should be even length. current history is: {history}"
+        history = [[history[i], history[i + 1]]
+                   for i in range(0, len(history), 2)]
+        return history, query
+
+    def get_answer_at_once(self):
+        history, query = self._get_glm_style_input()
+        response, _ = CHATGLM_MODEL.chat(
+            CHATGLM_TOKENIZER, query, history=history)
+        return response, len(response)
+
+    def get_answer_stream_iter(self):
+        history, query = self._get_glm_style_input()
+        for response, history in CHATGLM_MODEL.stream_chat(
+            CHATGLM_TOKENIZER,
+            query,
+            history,
+            max_length=self.token_upper_limit,
+            top_p=self.top_p,
+            temperature=self.temperature,
+        ):
+            yield response
+
+
+class LLaMA_Client(BaseLLMModel):
+    def __init__(
+        self,
+        model_name,
+        lora_path=None,
+    ) -> None:
+        super().__init__(model_name=model_name)
+        from lmflow.datasets.dataset import Dataset
+        from lmflow.pipeline.auto_pipeline import AutoPipeline
+        from lmflow.models.auto_model import AutoModel
+        from lmflow.args import ModelArguments, DatasetArguments, InferencerArguments
+
+        self.max_generation_token = 1000
+        self.end_string = "\n\n"
+        # We don't need input data
+        data_args = DatasetArguments(dataset_path=None)
+        self.dataset = Dataset(data_args)
+        self.system_prompt = ""
+
+        global LLAMA_MODEL, LLAMA_INFERENCER
+        if LLAMA_MODEL is None or LLAMA_INFERENCER is None:
+            model_path = None
+            if os.path.exists("models"):
+                model_dirs = os.listdir("models")
+                if model_name in model_dirs:
+                    model_path = f"models/{model_name}"
+            if model_path is not None:
+                model_source = model_path
+            else:
+                model_source = f"decapoda-research/{model_name}"
+                # raise Exception(f"models目录下没有这个模型: {model_name}")
+            if lora_path is not None:
+                lora_path = f"lora/{lora_path}"
+            model_args = ModelArguments(model_name_or_path=model_source, lora_model_path=lora_path, model_type=None, config_overrides=None, config_name=None, tokenizer_name=None, cache_dir=None,
+                                        use_fast_tokenizer=True, model_revision='main', use_auth_token=False, torch_dtype=None, use_lora=False, lora_r=8, lora_alpha=32, lora_dropout=0.1, use_ram_optimized_load=True)
+            pipeline_args = InferencerArguments(
+                local_rank=0, random_seed=1, deepspeed='configs/ds_config_chatbot.json', mixed_precision='bf16')
+
+            with open(pipeline_args.deepspeed, "r") as f:
+                ds_config = json.load(f)
+            LLAMA_MODEL = AutoModel.get_model(
+                model_args,
+                tune_strategy="none",
+                ds_config=ds_config,
+            )
+            LLAMA_INFERENCER = AutoPipeline.get_pipeline(
+                pipeline_name="inferencer",
+                model_args=model_args,
+                data_args=data_args,
+                pipeline_args=pipeline_args,
+            )
+
+    def _get_llama_style_input(self):
+        history = []
+        instruction = ""
+        if self.system_prompt:
+            instruction = (f"Instruction: {self.system_prompt}\n")
+        for x in self.history:
+            if x["role"] == "user":
+                history.append(f"{instruction}Input: {x['content']}")
+            else:
+                history.append(f"Output: {x['content']}")
+        context = "\n\n".join(history)
+        context += "\n\nOutput: "
+        return context
+
+    def get_answer_at_once(self):
+        context = self._get_llama_style_input()
+
+        input_dataset = self.dataset.from_dict(
+            {"type": "text_only", "instances": [{"text": context}]}
+        )
+
+        output_dataset = LLAMA_INFERENCER.inference(
+            model=LLAMA_MODEL,
+            dataset=input_dataset,
+            max_new_tokens=self.max_generation_token,
+            temperature=self.temperature,
+        )
+
+        response = output_dataset.to_dict()["instances"][0]["text"]
+        return response, len(response)
+
+    def get_answer_stream_iter(self):
+        context = self._get_llama_style_input()
+        partial_text = ""
+        step = 1
+        for _ in range(0, self.max_generation_token, step):
+            input_dataset = self.dataset.from_dict(
+                {"type": "text_only", "instances": [
+                    {"text": context + partial_text}]}
+            )
+            output_dataset = LLAMA_INFERENCER.inference(
+                model=LLAMA_MODEL,
+                dataset=input_dataset,
+                max_new_tokens=step,
+                temperature=self.temperature,
+            )
+            response = output_dataset.to_dict()["instances"][0]["text"]
+            if response == "" or response == self.end_string:
+                break
+            partial_text += response
+            yield partial_text
+
+
+class XMChat(BaseLLMModel):
+    def __init__(self, api_key):
+        super().__init__(model_name="xmchat")
+        self.api_key = api_key
+        self.session_id = None
+        self.reset()
+        self.image_bytes = None
+        self.image_path = None
+        self.xm_history = []
+        self.url = "https://xmbot.net/web"
+        self.last_conv_id = None
+
+    def reset(self):
+        self.session_id = str(uuid.uuid4())
+        self.last_conv_id = None
+        return [], "已重置"
+
+    def image_to_base64(self, image_path):
+        # 打开并加载图片
+        img = Image.open(image_path)
+
+        # 获取图片的宽度和高度
+        width, height = img.size
+
+        # 计算压缩比例，以确保最长边小于4096像素
+        max_dimension = 2048
+        scale_ratio = min(max_dimension / width, max_dimension / height)
+
+        if scale_ratio < 1:
+            # 按压缩比例调整图片大小
+            new_width = int(width * scale_ratio)
+            new_height = int(height * scale_ratio)
+            img = img.resize((new_width, new_height), Image.ANTIALIAS)
+
+        # 将图片转换为jpg格式的二进制数据
+        buffer = BytesIO()
+        if img.mode == "RGBA":
+            img = img.convert("RGB")
+        img.save(buffer, format='JPEG')
+        binary_image = buffer.getvalue()
+
+        # 对二进制数据进行Base64编码
+        base64_image = base64.b64encode(binary_image).decode('utf-8')
+
+        return base64_image
+
+    def try_read_image(self, filepath):
+        def is_image_file(filepath):
+            # 判断文件是否为图片
+            valid_image_extensions = [".jpg", ".jpeg", ".png", ".bmp", ".gif", ".tiff"]
+            file_extension = os.path.splitext(filepath)[1].lower()
+            return file_extension in valid_image_extensions
+
+        if is_image_file(filepath):
+            logging.info(f"读取图片文件: {filepath}")
+            self.image_bytes = self.image_to_base64(filepath)
+            self.image_path = filepath
+        else:
+            self.image_bytes = None
+            self.image_path = None
+
+    def like(self):
+        if self.last_conv_id is None:
+            return "点赞失败，你还没发送过消息"
+        data = {
+            "uuid": self.last_conv_id,
+            "appraise": "good"
+        }
+        response = requests.post(self.url, json=data)
+        return "👍点赞成功，，感谢反馈～"
+
+    def dislike(self):
+        if self.last_conv_id is None:
+            return "点踩失败，你还没发送过消息"
+        data = {
+            "uuid": self.last_conv_id,
+            "appraise": "bad"
+        }
+        response = requests.post(self.url, json=data)
+        return "👎点踩成功，感谢反馈～"
+
+    def prepare_inputs(self, real_inputs, use_websearch, files, reply_language, chatbot):
+        fake_inputs = real_inputs
+        display_append = ""
+        limited_context = False
+        return limited_context, fake_inputs, display_append, real_inputs, chatbot
+
+    def handle_file_upload(self, files, chatbot):
+        """if the model accepts multi modal input, implement this function"""
+        if files:
+            for file in files:
+                if file.name:
+                    logging.info(f"尝试读取图像: {file.name}")
+                    self.try_read_image(file.name)
+            if self.image_path is not None:
+                chatbot = chatbot + [((self.image_path,), None)]
+            if self.image_bytes is not None:
+                logging.info("使用图片作为输入")
+                # XMChat的一轮对话中实际上只能处理一张图片
+                self.reset()
+                conv_id = str(uuid.uuid4())
+                data = {
+                    "user_id": self.api_key,
+                    "session_id": self.session_id,
+                    "uuid": conv_id,
+                    "data_type": "imgbase64",
+                    "data": self.image_bytes
+                }
+                response = requests.post(self.url, json=data)
+                response = json.loads(response.text)
+                logging.info(f"图片回复: {response['data']}")
+        return None, chatbot, None
+
+    def get_answer_at_once(self):
+        question = self.history[-1]["content"]
+        conv_id = str(uuid.uuid4())
+        self.last_conv_id = conv_id
+        data = {
+            "user_id": self.api_key,
+            "session_id": self.session_id,
+            "uuid": conv_id,
+            "data_type": "text",
+            "data": question
+        }
+        response = requests.post(self.url, json=data)
+        try:
+            response = json.loads(response.text)
+            return response["data"], len(response["data"])
+        except Exception as e:
+            return response.text, len(response.text)
+
+
+
+
+def get_model(
+    model_name,
+    lora_model_path=None,
+    access_key=None,
+    temperature=None,
+    top_p=None,
+    system_prompt=None,
+) -> BaseLLMModel:
+    msg = i18n("模型设置为了：") + f" {model_name}"
+    model_type = ModelType.get_type(model_name)
+    lora_selector_visibility = False
+    lora_choices = []
+    dont_change_lora_selector = False
+    if model_type != ModelType.OpenAI:
+        config.local_embedding = True
+    # del current_model.model
+    model = None
+    try:
+        if model_type == ModelType.OpenAI:
+            logging.info(f"正在加载OpenAI模型: {model_name}")
+            model = OpenAIClient(
+                model_name=model_name,
+                api_key=access_key,
+                system_prompt=system_prompt,
+                temperature=temperature,
+                top_p=top_p,
+            )
+        elif model_type == ModelType.ChatGLM:
+            logging.info(f"正在加载ChatGLM模型: {model_name}")
+            model = ChatGLM_Client(model_name)
+        elif model_type == ModelType.LLaMA and lora_model_path == "":
+            msg = f"现在请为 {model_name} 选择LoRA模型"
+            logging.info(msg)
+            lora_selector_visibility = True
+            if os.path.isdir("lora"):
+                lora_choices = get_file_names(
+                    "lora", plain=True, filetypes=[""])
+            lora_choices = ["No LoRA"] + lora_choices
+        elif model_type == ModelType.LLaMA and lora_model_path != "":
+            logging.info(f"正在加载LLaMA模型: {model_name} + {lora_model_path}")
+            dont_change_lora_selector = True
+            if lora_model_path == "No LoRA":
+                lora_model_path = None
+                msg += " + No LoRA"
+            else:
+                msg += f" + {lora_model_path}"
+            model = LLaMA_Client(model_name, lora_model_path)
+        elif model_type == ModelType.XMChat:
+            if os.environ.get("XMCHAT_API_KEY") != "":
+                access_key = os.environ.get("XMCHAT_API_KEY")
+            model = XMChat(api_key=access_key)
+        elif model_type == ModelType.Unknown:
+            raise ValueError(f"未知模型: {model_name}")
+        logging.info(msg)
+    except Exception as e:
+        logging.error(e)
+        msg = f"{STANDARD_ERROR_MSG}: {e}"
+    if dont_change_lora_selector:
+        return model, msg
+    else:
+        return model, msg, gr.Dropdown.update(choices=lora_choices, visible=lora_selector_visibility)
+
+
+if __name__ == "__main__":
+    with open("config.json", "r") as f:
+        openai_api_key = cjson.load(f)["openai_api_key"]
+    # set logging level to debug
+    logging.basicConfig(level=logging.DEBUG)
+    # client = ModelManager(model_name="gpt-3.5-turbo", access_key=openai_api_key)
+    client = get_model(model_name="chatglm-6b-int4")
+    chatbot = []
+    stream = False
+    # 测试账单功能
+    logging.info(colorama.Back.GREEN + "测试账单功能" + colorama.Back.RESET)
+    logging.info(client.billing_info())
+    # 测试问答
+    logging.info(colorama.Back.GREEN + "测试问答" + colorama.Back.RESET)
+    question = "巴黎是中国的首都吗？"
+    for i in client.predict(inputs=question, chatbot=chatbot, stream=stream):
+        logging.info(i)
+    logging.info(f"测试问答后history : {client.history}")
+    # 测试记忆力
+    logging.info(colorama.Back.GREEN + "测试记忆力" + colorama.Back.RESET)
+    question = "我刚刚问了你什么问题？"
+    for i in client.predict(inputs=question, chatbot=chatbot, stream=stream):
+        logging.info(i)
+    logging.info(f"测试记忆力后history : {client.history}")
+    # 测试重试功能
+    logging.info(colorama.Back.GREEN + "测试重试功能" + colorama.Back.RESET)
+    for i in client.retry(chatbot=chatbot, stream=stream):
+        logging.info(i)
+    logging.info(f"重试后history : {client.history}")
+    # # 测试总结功能
+    # print(colorama.Back.GREEN + "测试总结功能" + colorama.Back.RESET)
+    # chatbot, msg = client.reduce_token_size(chatbot=chatbot)
+    # print(chatbot, msg)
+    # print(f"总结后history: {client.history}")

modules/models/Google_PaLM.py

@@ -1,26 +0,0 @@
-from .base_model import BaseLLMModel
-import google.generativeai as palm
-
-class Google_PaLM_Client(BaseLLMModel):
-    def __init__(self, model_name, api_key, user_name="") -> None:
-        super().__init__(model_name=model_name, user=user_name)
-        self.api_key = api_key
-
-    def _get_palm_style_input(self):
-        new_history = []
-        for item in self.history:
-            if item["role"] == "user":
-                new_history.append({'author': '1', 'content': item["content"]})
-            else:
-                new_history.append({'author': '0', 'content': item["content"]})
-        return new_history
-
-    def get_answer_at_once(self):
-        palm.configure(api_key=self.api_key)
-        messages = self._get_palm_style_input()
-        response = palm.chat(context=self.system_prompt, messages=messages, temperature=self.temperature, top_p=self.top_p)
-        if response.last is not None:
-            return response.last, len(response.last)
-        else:
-            reasons = '\n\n'.join(reason['reason'].name for reason in response.filters)
-            return "由于下面的原因，Google 拒绝返回 PaLM 的回答：\n\n" + reasons, 0

modules/models/azure.py

@@ -1,17 +0,0 @@
-from langchain.chat_models import AzureChatOpenAI
-import os
-
-from .base_model import Base_Chat_Langchain_Client
-
-# load_config_to_environ(["azure_openai_api_key", "azure_api_base_url", "azure_openai_api_version", "azure_deployment_name"])
-
-class Azure_OpenAI_Client(Base_Chat_Langchain_Client):
-    def setup_model(self):
-        # inplement this to setup the model then return it
-        return AzureChatOpenAI(
-            openai_api_base=os.environ["AZURE_OPENAI_API_BASE_URL"],
-            openai_api_version=os.environ["AZURE_OPENAI_API_VERSION"],
-            deployment_name=os.environ["AZURE_DEPLOYMENT_NAME"],
-            openai_api_key=os.environ["AZURE_OPENAI_API_KEY"],
-            openai_api_type="azure",
-        )

modules/models/base_model.py

@@ -29,8 +29,6 @@ from langchain.input import print_text
 from langchain.schema import AgentAction, AgentFinish, LLMResult
 from threading import Thread, Condition
 from collections import deque
-from langchain.chat_models.base import BaseChatModel
-from langchain.schema import HumanMessage, AIMessage, SystemMessage, BaseMessage
 
 from ..presets import *
 from ..index_func import *
@@ -38,7 +36,6 @@ from ..utils import *
 from .. import shared
 from ..config import retrieve_proxy
 
-
 class CallbackToIterator:
     def __init__(self):
         self.queue = deque()
@@ -55,8 +52,7 @@ class CallbackToIterator:
 
     def __next__(self):
         with self.cond:
-            # Wait for a value to be added to the queue.
-            while not self.queue and not self.finished:
+            while not self.queue and not self.finished:  # Wait for a value to be added to the queue.
                 self.cond.wait()
             if not self.queue:
                 raise StopIteration()
@@ -67,7 +63,6 @@ class CallbackToIterator:
             self.finished = True
             self.cond.notify()  # Wake up the generator if it's waiting.
 
-
 def get_action_description(text):
     match = re.search('```(.*?)```', text, re.S)
     json_text = match.group(1)
@@ -81,7 +76,6 @@ def get_action_description(text):
     else:
         return ""
 
-
 class ChuanhuCallbackHandler(BaseCallbackHandler):
 
     def __init__(self, callback) -> None:
@@ -123,10 +117,6 @@ class ChuanhuCallbackHandler(BaseCallbackHandler):
         """Run on new LLM token. Only available when streaming is enabled."""
         self.callback(token)
 
-    def on_chat_model_start(self, serialized: Dict[str, Any], messages: List[List[BaseMessage]],  **kwargs: Any) -> Any:
-        """Run when a chat model starts running."""
-        pass
-
 
 class ModelType(Enum):
     Unknown = -1
@@ -139,8 +129,6 @@ class ModelType(Enum):
     YuanAI = 6
     Minimax = 7
     ChuanhuAgent = 8
-    GooglePaLM = 9
-    LangchainChat = 10
 
     @classmethod
     def get_type(cls, model_name: str):
@@ -164,10 +152,6 @@ class ModelType(Enum):
             model_type = ModelType.Minimax
         elif "川虎助理" in model_name_lower:
             model_type = ModelType.ChuanhuAgent
-        elif "palm" in model_name_lower:
-            model_type = ModelType.GooglePaLM
-        elif "azure" or "api" in model_name_lower:
-            model_type = ModelType.LangchainChat
         else:
             model_type = ModelType.Unknown
         return model_type
@@ -177,7 +161,7 @@ class BaseLLMModel:
     def __init__(
         self,
         model_name,
-        system_prompt=INITIAL_SYSTEM_PROMPT,
+        system_prompt="",
         temperature=1.0,
         top_p=1.0,
         n_choices=1,
@@ -217,8 +201,7 @@ class BaseLLMModel:
         conversations are stored in self.history, with the most recent question, in OpenAI format
         should return a generator, each time give the next word (str) in the answer
         """
-        logging.warning(
-            "stream predict not implemented, using at once predict instead")
+        logging.warning("stream predict not implemented, using at once predict instead")
         response, _ = self.get_answer_at_once()
         yield response
 
@@ -229,8 +212,7 @@ class BaseLLMModel:
         the answer (str)
         total token count (int)
         """
-        logging.warning(
-            "at once predict not implemented, using stream predict instead")
+        logging.warning("at once predict not implemented, using stream predict instead")
         response_iter = self.get_answer_stream_iter()
         count = 0
         for response in response_iter:
@@ -264,7 +246,7 @@ class BaseLLMModel:
         stream_iter = self.get_answer_stream_iter()
 
         if display_append:
-            display_append = '\n\n<hr class="append-display no-in-raw" />' + display_append
+            display_append = "<hr>" +display_append
         for partial_text in stream_iter:
             chatbot[-1] = (chatbot[-1][0], partial_text + display_append)
             self.all_token_counts[-1] += 1
@@ -291,11 +273,9 @@ class BaseLLMModel:
             self.history[-2] = construct_user(fake_input)
         chatbot[-1] = (chatbot[-1][0], ai_reply + display_append)
         if fake_input is not None:
-            self.all_token_counts[-1] += count_token(
-                construct_assistant(ai_reply))
+            self.all_token_counts[-1] += count_token(construct_assistant(ai_reply))
         else:
-            self.all_token_counts[-1] = total_token_count - \
-                sum(self.all_token_counts)
+            self.all_token_counts[-1] = total_token_count - sum(self.all_token_counts)
         status_text = self.token_message()
         return chatbot, status_text
 
@@ -319,13 +299,10 @@ class BaseLLMModel:
             from langchain.chat_models import ChatOpenAI
             from langchain.callbacks import StdOutCallbackHandler
             prompt_template = "Write a concise summary of the following:\n\n{text}\n\nCONCISE SUMMARY IN " + language + ":"
-            PROMPT = PromptTemplate(
-                template=prompt_template, input_variables=["text"])
+            PROMPT = PromptTemplate(template=prompt_template, input_variables=["text"])
             llm = ChatOpenAI()
-            chain = load_summarize_chain(
-                llm, chain_type="map_reduce", return_intermediate_steps=True, map_prompt=PROMPT, combine_prompt=PROMPT)
-            summary = chain({"input_documents": list(index.docstore.__dict__[
-                            "_dict"].values())}, return_only_outputs=True)["output_text"]
+            chain = load_summarize_chain(llm, chain_type="map_reduce", return_intermediate_steps=True, map_prompt=PROMPT, combine_prompt=PROMPT)
+            summary = chain({"input_documents": list(index.docstore.__dict__["_dict"].values())}, return_only_outputs=True)["output_text"]
             print(i18n("总结") + f": {summary}")
             chatbot.append([i18n("上传了")+str(len(files))+"个文件", summary])
         return chatbot, status
@@ -346,12 +323,9 @@ class BaseLLMModel:
             msg = "索引获取成功，生成回答中……"
             logging.info(msg)
             with retrieve_proxy():
-                retriever = VectorStoreRetriever(vectorstore=index, search_type="similarity_score_threshold", search_kwargs={
-                                                 "k": 6, "score_threshold": 0.5})
-                relevant_documents = retriever.get_relevant_documents(
-                    real_inputs)
-            reference_results = [[d.page_content.strip("�"), os.path.basename(
-                d.metadata["source"])] for d in relevant_documents]
+                retriever = VectorStoreRetriever(vectorstore=index, search_type="similarity_score_threshold",search_kwargs={"k":6, "score_threshold": 0.5})
+                relevant_documents = retriever.get_relevant_documents(real_inputs)
+            reference_results = [[d.page_content.strip("�"), os.path.basename(d.metadata["source"])] for d in relevant_documents]
             reference_results = add_source_numbers(reference_results)
             display_append = add_details(reference_results)
             display_append = "\n\n" + "".join(display_append)
@@ -374,12 +348,10 @@ class BaseLLMModel:
                 reference_results.append([result['body'], result['href']])
                 display_append.append(
                     # f"{idx+1}. [{domain_name}]({result['href']})\n"
-                    f"<a href=\"{result['href']}\" target=\"_blank\">{idx+1}.&nbsp;{result['title']}</a>"
+                    f"<li><a href=\"{result['href']}\" target=\"_blank\">{result['title']}</a></li>\n"
                 )
             reference_results = add_source_numbers(reference_results)
-            # display_append = "<ol>\n\n" + "".join(display_append) + "</ol>"
-            display_append = '<div class = "source-a">' + \
-                "".join(display_append) + '</div>'
+            display_append = "<ol>\n\n" + "".join(display_append) + "</ol>"
             real_inputs = (
                 replace_today(WEBSEARCH_PTOMPT_TEMPLATE)
                 .replace("{query}", real_inputs)
@@ -403,16 +375,14 @@ class BaseLLMModel:
 
         status_text = "开始生成回答……"
         logging.info(
-            "用户" + f"{self.user_identifier}" + "的输入为：" +
-            colorama.Fore.BLUE + f"{inputs}" + colorama.Style.RESET_ALL
+             "用户" + f"{self.user_identifier}" + "的输入为：" + colorama.Fore.BLUE + f"{inputs}" + colorama.Style.RESET_ALL
         )
         if should_check_token_count:
             yield chatbot + [(inputs, "")], status_text
         if reply_language == "跟随问题语言（不稳定）":
             reply_language = "the same language as the question, such as English, 中文, 日本語, Español, Français, or Deutsch."
 
-        limited_context, fake_inputs, display_append, inputs, chatbot = self.prepare_inputs(
-            real_inputs=inputs, use_websearch=use_websearch, files=files, reply_language=reply_language, chatbot=chatbot)
+        limited_context, fake_inputs, display_append, inputs, chatbot = self.prepare_inputs(real_inputs=inputs, use_websearch=use_websearch, files=files, reply_language=reply_language, chatbot=chatbot)
         yield chatbot + [(fake_inputs, "")], status_text
 
         if (
@@ -598,13 +568,10 @@ class BaseLLMModel:
         self.system_prompt = new_system_prompt
 
     def set_key(self, new_access_key):
-        if "*" not in new_access_key:
-            self.api_key = new_access_key.strip()
-            msg = i18n("API密钥更改为了") + hide_middle_chars(self.api_key)
-            logging.info(msg)
-            return self.api_key, msg
-        else:
-            return gr.update(), gr.update()
+        self.api_key = new_access_key.strip()
+        msg = i18n("API密钥更改为了") + hide_middle_chars(self.api_key)
+        logging.info(msg)
+        return self.api_key, msg
 
     def set_single_turn(self, new_single_turn):
         self.single_turn = new_single_turn
@@ -613,8 +580,7 @@ class BaseLLMModel:
         self.history = []
         self.all_token_counts = []
         self.interrupted = False
-        pathlib.Path(os.path.join(HISTORY_DIR, self.user_identifier, new_auto_history_filename(
-            os.path.join(HISTORY_DIR, self.user_identifier)))).touch()
+        pathlib.Path(os.path.join(HISTORY_DIR, self.user_identifier, new_auto_history_filename(os.path.join(HISTORY_DIR, self.user_identifier)))).touch()
         return [], self.token_message([0])
 
     def delete_first_conversation(self):
@@ -657,8 +623,7 @@ class BaseLLMModel:
 
     def auto_save(self, chatbot):
         history_file_path = get_history_filepath(self.user_identifier)
-        save_file(history_file_path, self.system_prompt,
-                  self.history, chatbot, self.user_identifier)
+        save_file(history_file_path, self.system_prompt, self.history, chatbot, self.user_identifier)
 
     def export_markdown(self, filename, chatbot, user_name):
         if filename == "":
@@ -674,8 +639,7 @@ class BaseLLMModel:
             filename = filename.name
         try:
             if "/" not in filename:
-                history_file_path = os.path.join(
-                    HISTORY_DIR, user_name, filename)
+                history_file_path = os.path.join(HISTORY_DIR, user_name, filename)
             else:
                 history_file_path = filename
             with open(history_file_path, "r", encoding="utf-8") as f:
@@ -701,33 +665,15 @@ class BaseLLMModel:
             logging.info(f"没有找到对话历史记录 {filename}")
             return gr.update(), self.system_prompt, gr.update()
 
-    def delete_chat_history(self, filename, user_name):
-        if filename == "CANCELED":
-            return gr.update(), gr.update(), gr.update()
-        if filename == "":
-            return i18n("你没有选择任何对话历史"), gr.update(), gr.update()
-        if not filename.endswith(".json"):
-            filename += ".json"
-        if "/" not in filename:
-            history_file_path = os.path.join(HISTORY_DIR, user_name, filename)
-        else:
-            history_file_path = filename
-        try:
-            os.remove(history_file_path)
-            return i18n("删除对话历史成功"), get_history_names(False, user_name), []
-        except:
-            logging.info(f"删除对话历史失败 {history_file_path}")
-            return i18n("对话历史")+filename+i18n("已经被删除啦"), gr.update(), gr.update()
-
     def auto_load(self):
         if self.user_identifier == "":
             self.reset()
             return self.system_prompt, gr.update()
         history_file_path = get_history_filepath(self.user_identifier)
-        filename, system_prompt, chatbot = self.load_chat_history(
-            history_file_path, self.user_identifier)
+        filename, system_prompt, chatbot = self.load_chat_history(history_file_path, self.user_identifier)
         return system_prompt, chatbot
 
+
     def like(self):
         """like the last response, implement if needed
         """
@@ -737,47 +683,3 @@ class BaseLLMModel:
         """dislike the last response, implement if needed
         """
         return gr.update()
-
-
-class Base_Chat_Langchain_Client(BaseLLMModel):
-    def __init__(self, model_name, user_name=""):
-        super().__init__(model_name, user=user_name)
-        self.need_api_key = False
-        self.model = self.setup_model()
-
-    def setup_model(self):
-        # inplement this to setup the model then return it
-        pass
-
-    def _get_langchain_style_history(self):
-        history = [SystemMessage(content=self.system_prompt)]
-        for i in self.history:
-            if i["role"] == "user":
-                history.append(HumanMessage(content=i["content"]))
-            elif i["role"] == "assistant":
-                history.append(AIMessage(content=i["content"]))
-        return history
-
-    def get_answer_at_once(self):
-        assert isinstance(
-            self.model, BaseChatModel), "model is not instance of LangChain BaseChatModel"
-        history = self._get_langchain_style_history()
-        response = self.model.generate(history)
-        return response.content, sum(response.content)
-
-    def get_answer_stream_iter(self):
-        it = CallbackToIterator()
-        assert isinstance(
-            self.model, BaseChatModel), "model is not instance of LangChain BaseChatModel"
-        history = self._get_langchain_style_history()
-
-        def thread_func():
-            self.model(messages=history, callbacks=[
-                ChuanhuCallbackHandler(it.callback)])
-            it.finish()
-        t = Thread(target=thread_func)
-        t.start()
-        partial_text = ""
-        for value in it:
-            partial_text += value
-            yield partial_text

modules/models/models.py

@@ -24,7 +24,7 @@ from ..presets import *
 from ..index_func import *
 from ..utils import *
 from .. import shared
-from ..config import retrieve_proxy, usage_limit, sensitive_id
+from ..config import retrieve_proxy, usage_limit
 from modules import config
 from .base_model import BaseLLMModel, ModelType
 
@@ -87,22 +87,21 @@ class OpenAIClient(BaseLLMModel):
             try:
                 usage_data = self._get_billing_data(usage_url)
             except Exception as e:
-                # logging.error(f"获取API使用情况失败: " + str(e))
-                if "Invalid authorization header" in str(e):
-                    return i18n("**获取API使用情况失败**，需在填写`config.json`中正确填写sensitive_id")
-                elif "Incorrect API key provided: sess" in str(e):
-                    return i18n("**获取API使用情况失败**，sensitive_id错误或已过期")
+                logging.error(f"获取API使用情况失败:" + str(e))
                 return i18n("**获取API使用情况失败**")
             # rounded_usage = "{:.5f}".format(usage_data["total_usage"] / 100)
             rounded_usage = round(usage_data["total_usage"] / 100, 5)
             usage_percent = round(usage_data["total_usage"] / usage_limit, 2)
             # return i18n("**本月使用金额** ") + f"\u3000 ${rounded_usage}"
-            return get_html("billing_info.html").format(
-                    label = i18n("本月使用金额"),
-                    usage_percent = usage_percent,
-                    rounded_usage = rounded_usage,
-                    usage_limit = usage_limit
-                )
+            return """\
+                <b>""" + i18n("本月使用金额") + f"""</b>
+                <div class="progress-bar">
+                    <div class="progress" style="width: {usage_percent}%;">
+                        <span class="progress-text">{usage_percent}%</span>
+                    </div>
+                </div>
+                <div style="display: flex; justify-content: space-between;"><span>${rounded_usage}</span><span>${usage_limit}</span></div>
+                """
         except requests.exceptions.ConnectTimeout:
             status_text = (
                 STANDARD_ERROR_MSG + CONNECTION_TIMEOUT_MSG + ERROR_RETRIEVE_MSG
@@ -180,10 +179,9 @@ class OpenAIClient(BaseLLMModel):
     def _refresh_header(self):
         self.headers = {
             "Content-Type": "application/json",
-            "Authorization": f"Bearer {sensitive_id}",
+            "Authorization": f"Bearer {self.api_key}",
         }
 
-
     def _get_billing_data(self, billing_url):
         with retrieve_proxy():
             response = requests.get(
@@ -562,7 +560,6 @@ def get_model(
     try:
         if model_type == ModelType.OpenAI:
             logging.info(f"正在加载OpenAI模型: {model_name}")
-            access_key = os.environ.get("OPENAI_API_KEY", access_key)
             model = OpenAIClient(
                 model_name=model_name,
                 api_key=access_key,
@@ -613,25 +610,16 @@ def get_model(
         elif model_type == ModelType.ChuanhuAgent:
             from .ChuanhuAgent import ChuanhuAgent_Client
             model = ChuanhuAgent_Client(model_name, access_key, user_name=user_name)
-        elif model_type == ModelType.GooglePaLM:
-            from .Google_PaLM import Google_PaLM_Client
-            access_key = os.environ.get("GOOGLE_PALM_API_KEY", access_key)
-            model = Google_PaLM_Client(model_name, access_key, user_name=user_name)
-        elif model_type == ModelType.LangchainChat:
-            from .azure import Azure_OpenAI_Client
-            model = Azure_OpenAI_Client(model_name, user_name=user_name)
         elif model_type == ModelType.Unknown:
             raise ValueError(f"未知模型: {model_name}")
         logging.info(msg)
     except Exception as e:
-        import traceback
-        traceback.print_exc()
+        logging.error(e)
         msg = f"{STANDARD_ERROR_MSG}: {e}"
-    presudo_key = hide_middle_chars(access_key)
     if dont_change_lora_selector:
-        return model, msg, chatbot, gr.update(), access_key, presudo_key
+        return model, msg, chatbot
     else:
-        return model, msg, chatbot, gr.Dropdown.update(choices=lora_choices, visible=lora_selector_visibility), access_key, presudo_key
+        return model, msg, chatbot, gr.Dropdown.update(choices=lora_choices, visible=lora_selector_visibility)
 
 
 if __name__ == "__main__":

modules/overwrites.py

@@ -80,7 +80,8 @@ with open("./assets/custom.js", "r", encoding="utf-8") as f, \
 def reload_javascript():
     print("Reloading javascript...")
     js = f'<script>{customJS}</script><script async>{externalScripts}</script>'
-    js += '<script async src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>'
+    # if render_latex:
+    #     js += """\"""
     def template_response(*args, **kwargs):
         res = GradioTemplateResponseOriginal(*args, **kwargs)
         res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8"))

modules/presets.py

@@ -60,9 +60,7 @@ ONLINE_MODELS = [
     "gpt-4-32k-0613",
     "川虎助理",
     "川虎助理 Pro",
-    "GooglePaLM",
     "xmchat",
-    "Azure OpenAI",
     "yuanai-1.0-base_10B",
     "yuanai-1.0-translate",
     "yuanai-1.0-dialog",
@@ -74,9 +72,7 @@ ONLINE_MODELS = [
 LOCAL_MODELS = [
     "chatglm-6b",
     "chatglm-6b-int4",
-    "chatglm-6b-int4-ge",
-    "chatglm2-6b",
-    "chatglm2-6b-int4",
+    "chatglm-6b-int4-qe",
     "StableLM",
     "MOSS",
     "llama-7b-hf",
@@ -125,7 +121,6 @@ REPLY_LANGUAGES = [
     "Español",
     "Français",
     "Deutsch",
-    "한국어",
     "跟随问题语言（不稳定）"
 ]
 
@@ -227,7 +222,7 @@ small_and_beautiful_theme = gr.themes.Soft(
         # button_primary_background_fill_hover="*primary_400",
         # button_primary_border_color="*primary_500",
         button_primary_border_color_dark="*primary_600",
-        button_primary_text_color="white",
+        button_primary_text_color="wihte",
         button_primary_text_color_dark="white",
         button_secondary_background_fill="*neutral_100",
         button_secondary_background_fill_hover="*neutral_50",

modules/utils.py

@@ -5,7 +5,6 @@ import logging
 import json
 import os
 import datetime
-from datetime import timezone 
 import hashlib
 import csv
 import requests
@@ -48,9 +47,6 @@ def set_key(current_model, *args):
 def load_chat_history(current_model, *args):
     return current_model.load_chat_history(*args)
 
-def delete_chat_history(current_model, *args):
-    return current_model.delete_chat_history(*args)
-
 def interrupt(current_model, *args):
     return current_model.interrupt(*args)
 
@@ -218,10 +214,7 @@ def convert_bot_before_marked(chat_message):
         non_code_parts = code_block_pattern.split(chat_message)[::2]
         result = []
 
-        hr_pattern = r'\n\n<hr class="append-display no-in-raw" />(.*?)'
-        hr_match = re.search(hr_pattern, chat_message, re.DOTALL)
-        clip_hr = chat_message[:hr_match.start()] if hr_match else chat_message
-        raw = f'<div class="raw-message hideM">{escape_markdown(clip_hr)}</div>'
+        raw = f'<div class="raw-message hideM">{escape_markdown(chat_message)}</div>'
         for non_code, code in zip(non_code_parts, code_blocks + [""]):
             if non_code.strip():
                 result.append(non_code)
@@ -243,7 +236,7 @@ def escape_markdown(text):
     Escape Markdown special characters to HTML-safe equivalents.
     """
     escape_chars = {
-        # ' ': '&nbsp;',
+        ' ': '&nbsp;',
         '_': '&#95;',
         '*': '&#42;',
         '[': '&#91;',
@@ -260,11 +253,8 @@ def escape_markdown(text):
         '`': '&#96;',
         '>': '&#62;',
         '<': '&#60;',
-        '|': '&#124;',
-        '$': '&#36;',
-        ':': '&#58;',
+        '|': '&#124;'
     }
-    text = text.replace('    ', '&nbsp;&nbsp;&nbsp;&nbsp;')
     return ''.join(escape_chars.get(c, c) for c in text)
 
 
@@ -541,55 +531,26 @@ def run(command, desc=None, errdesc=None, custom_env=None, live=False):
         raise RuntimeError(message)
     return result.stdout.decode(encoding="utf8", errors="ignore")
 
-def commit_html():
+def versions_html():
     git = os.environ.get('GIT', "git")
+    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
     try:
         commit_hash = run(f"{git} rev-parse HEAD").strip()
     except Exception:
         commit_hash = "<none>"
     if commit_hash != "<none>":
         short_commit = commit_hash[0:7]
-        commit_info = f'<a style="text-decoration:none;color:inherit" href="https://github.com/GaiZhenbiao/ChuanhuChatGPT/commit/{short_commit}">{short_commit}</a>'
+        commit_info = f"<a style=\"text-decoration:none;color:inherit\" href=\"https://github.com/GaiZhenbiao/ChuanhuChatGPT/commit/{short_commit}\">{short_commit}</a>"
     else:
         commit_info = "unknown \U0001F615"
-    return commit_info
-
-def tag_html():
-    git = os.environ.get('GIT', "git")
-    try:
-        tag = run(f"{git} describe --tags --exact-match").strip()
-    except Exception:
-        tag = "<none>"
-    if tag != "<none>":
-        tag_info = f'<a style="text-decoration:none;color:inherit" href="https://github.com/GaiZhenbiao/ChuanhuChatGPT/releases/tag/{tag}">{tag}</a>'
-    else:
-        tag_info = "unknown \U0001F615"
-    return tag_info
-
-def repo_html():
-    commit_version = commit_html()
-    tag_version = tag_html()
-    return tag_version if tag_version != "unknown \U0001F615" else commit_version
-
-def versions_html():
-    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
-    repo_version = repo_html()
     return f"""
         Python: <span title="{sys.version}">{python_version}</span>
          • 
         Gradio: {gr.__version__}
          • 
-        <a style="text-decoration:none;color:inherit" href="https://github.com/GaiZhenbiao/ChuanhuChatGPT">ChuanhuChat</a>: {repo_version}
+        <a style="text-decoration:none;color:inherit" href="https://github.com/GaiZhenbiao/ChuanhuChatGPT">ChuanhuChat</a>: {commit_info}
         """
 
-def version_time():
-    git = os.environ.get('GIT', "git")
-    try:
-        commit_time = run(f"TZ=UTC {git} log -1 --format=%cd --date='format-local:%Y-%m-%dT%H:%M:%SZ'").strip()
-    except Exception:
-        commit_time = "unknown"
-    return commit_time
-
 def get_html(filename):
     path = os.path.join(shared.chuanhu_path, "assets", "html", filename)
     if os.path.exists(path):

readme/README_en.md

@@ -1,12 +1,12 @@
 <div align="right">
   <!-- Language: -->
-  <a title="Chinese" href="../README_origin.md">简体中文</a> | English | <a title="Japanese" href="README_ja.md">日本語</a>
+  <a title="Chinese" href="../README.md">简体中文</a> | English | <a title="Japanese" href="README_ja.md">日本語</a>
 </div>
 
 <h1 align="center">川虎 Chat 🐯 Chuanhu Chat</h1>
 <div align="center">
   <a href="https://github.com/GaiZhenBiao/ChuanhuChatGPT">
-    <img src="https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/70903329/aca3a7ec-4f1d-4667-890c-a6f47bf08f63" alt="Logo" height="156">
+    <img src="https://user-images.githubusercontent.com/70903329/227087087-93b37d64-7dc3-4738-a518-c1cf05591c8a.png" alt="Logo" height="156">
   </a>
 
 <p align="center">
@@ -44,23 +44,6 @@
   </p>
 </div>
 
-## Supported LLM Models
-
-**LLM models via API**:
-
-- [ChatGPT](https://chat.openai.com) ([GPT-4](https://openai.com/product/gpt-4))
-- [Google PaLM](https://developers.generativeai.google/products/palm)
-- [Inspur Yuan 1.0](https://air.inspur.com/home)
-- [MiniMax](https://api.minimax.chat/)
-- [XMChat](https://github.com/MILVLG/xmchat)
-
-**LLM models via local deployment**:
-
-- [ChatGLM](https://github.com/THUDM/ChatGLM-6B) ([ChatGLM2](https://github.com/THUDM/ChatGLM2-6B))
-- [LLaMA](https://github.com/facebookresearch/llama)
-- [StableLM](https://github.com/Stability-AI/StableLM)
-- [MOSS](https://github.com/OpenLMLab/MOSS)
-
 ## Usage Tips
 
 - To better control the ChatGPT, use System Prompt.
@@ -68,11 +51,11 @@
 - To try again if the response is unsatisfactory, use `🔄 Regenerate` button.
 - To start a new line in the input box, press <kbd>Shift</kbd> + <kbd>Enter</kbd> keys.
 - To quickly switch between input history, press <kbd>↑</kbd> and <kbd>↓</kbd> key in the input box.
-- To deploy the program onto a server, set `"server_name": "0.0.0.0", "server_port" <your port number>,` in `config.json`.
-- To get a public shared link, set `"share": true,` in `config.json`. Please be noted that the program must be running in order to be accessed via a public link.
+- To deploy the program onto a server, change the last line of the program to `demo.launch(server_name="0.0.0.0", server_port=<your port number>)`.
+- To get a public shared link, change the last line of the program to `demo.launch(share=True)`. Please be noted that the program must be running in order to be accessed via a public link.
 - To use it in Hugging Face Spaces: It is recommended to **Duplicate Space** and run the program in your own Space for a faster and more secure experience.
 
-## Quickstart
+## Installation
 
 ```shell
 git clone https://github.com/GaiZhenbiao/ChuanhuChatGPT.git
@@ -104,6 +87,10 @@ When you encounter problems, you should try manually pulling the latest changes
    ```
    pip install -r requirements.txt
    ```
+3. Update Gradio
+   ```
+   pip install gradio --upgrade --force-reinstall
+   ```
 
 Generally, you can solve most problems by following these steps.
 

readme/README_ja.md

@@ -1,12 +1,12 @@
 <div align="right">
   <!-- Language: -->
-  <a title="Chinese" href="../README_origin.md">简体中文</a> | <a title="English" href="README_en.md">English</a> | 日本語
+  <a title="Chinese" href="../README.md">简体中文</a> | <a title="English" href="README_en.md">English</a> | 日本語
 </div>
 
 <h1 align="center">川虎 Chat 🐯 Chuanhu Chat</h1>
 <div align="center">
   <a href="https://github.com/GaiZhenBiao/ChuanhuChatGPT">
-    <img src="https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/70903329/aca3a7ec-4f1d-4667-890c-a6f47bf08f63" alt="Logo" height="156">
+    <img src="https://user-images.githubusercontent.com/70903329/227087087-93b37d64-7dc3-4738-a518-c1cf05591c8a.png" alt="Logo" height="156">
   </a>
 
 <p align="center">
@@ -44,34 +44,17 @@
   </p>
 </div>
 
-## サポートされている大規模言語モデル
-
-**APIを通じてアクセス可能な大規模言語モデル**：
-
-- [ChatGPT](https://chat.openai.com) ([GPT-4](https://openai.com/product/gpt-4))
-- [Google PaLM](https://developers.generativeai.google/products/palm)
-- [Inspur Yuan 1.0](https://air.inspur.com/home)
-- [MiniMax](https://api.minimax.chat/)
-- [XMChat](https://github.com/MILVLG/xmchat)
-
-**ローカルに展開された大規模言語モデル**：
-
-- [ChatGLM](https://github.com/THUDM/ChatGLM-6B) ([ChatGLM2](https://github.com/THUDM/ChatGLM2-6B))
-- [LLaMA](https://github.com/facebookresearch/llama)
-- [StableLM](https://github.com/Stability-AI/StableLM)
-- [MOSS](https://github.com/OpenLMLab/MOSS)
-
 ## 使う上でのTips
 
 - ChatGPTをより適切に制御するために、システムプロンプトを使用できます。
 - プロンプトテンプレートを使用するには、プロンプトテンプレートコレクションを選択し、ドロップダウンメニューから特定のプロンプトを選択。回答が不十分な場合は、`🔄再生成`ボタンを使って再試行します。
 - 入力ボックスで改行するには、<kbd>Shift</kbd> + <kbd>Enter</kbd>キーを押してください。
 - 入力履歴を素早く切り替えるには、入力ボックスで <kbd>↑</kbd>と<kbd>↓</kbd>キーを押す。
-- プログラムをサーバーに展開するには、`config.json` 内の `"server_name": "0.0.0.0", "server_port": <ポート番号>`を設定してください。
-- 共有リンクを取得するには、 `config.json` 内の `"share": true` を設定してください。なお、公開リンクでアクセスするためには、プログラムが実行されている必要があることに注意してください。
+- プログラムをサーバにデプロイするには、プログラムの最終行を `demo.launch(server_name="0.0.0.0", server_port=<your port number>)`に変更します。
+- 共有リンクを取得するには、プログラムの最後の行を `demo.launch(share=True)` に変更してください。なお、公開リンクでアクセスするためには、プログラムが実行されている必要があることに注意してください。
 - Hugging Face Spacesで使用する場合： より速く、より安全に利用するために、**Duplicate Space**を使用し、自分のスペースでプログラムを実行することをお勧めします。
 
-## クイックスタート
+## インストール
 
 ```shell
 git clone https://github.com/GaiZhenbiao/ChuanhuChatGPT.git
@@ -103,6 +86,10 @@ python ChuanhuChatbot.py
    ```
    pip install -r requirements.txt
    ```
+3. Gradioを更新
+   ```
+   pip install gradio --upgrade --force-reinstall
+   ```
 
 一般的に、以下の手順でほとんどの問題を解決することができます。
 

requirements.txt

@@ -1,5 +1,5 @@
-gradio==3.36.1
-gradio_client==0.2.7
+gradio==3.33.1
+gradio_client==0.2.5
 pypinyin
 tiktoken
 socksio
@@ -16,12 +16,10 @@ commentjson
 openpyxl
 pandoc
 wolframalpha
-faiss-cpu==1.7.4
+faiss-cpu
 duckduckgo-search
 arxiv
 wikipedia
 google.generativeai
 openai
 unstructured
-google-api-python-client
-tabulate

requirements_advanced.txt

@@ -1,11 +0,0 @@
-transformers
-huggingface_hub
-torch
-icetk
-protobuf==3.19.0
-git+https://github.com/OptimalScale/LMFlow.git
-cpm-kernels
-sentence_transformers
-accelerate
-sentencepiece
-datasets

run_Windows.bat

@@ -1,24 +1,5 @@
 @echo off
 echo Opening ChuanhuChatGPT...
 
-if not exist "%~dp0\ChuanhuChat\Scripts" (
-    echo Creating venv...
-    python -m venv ChuanhuChat
-    
-    cd /d "%~dp0\ChuanhuChat\Scripts"
-    call activate.bat
-    
-    cd /d "%~dp0"
-    pip install -r requirements.txt
-)
-
-goto :activate_venv
-
-:launch
-%PYTHON% ChuanhuChatbot.py %*
-pause
-
-:activate_venv
-set PYTHON="%~dp0\ChuanhuChat\Scripts\Python.exe"
-echo venv %PYTHON%
-goto :launch
+REM Open powershell via bat
+start powershell.exe -NoExit -Command "python ./ChuanhuChatbot.py"