├── modules ├── __init__.py ├── models │ ├── __init__.py │ ├── Azure.py │ ├── OpenAIInstruct.py │ ├── GooglePaLM.py │ ├── Groq.py │ ├── Ollama.py │ ├── Qwen.py │ ├── DALLE3.py │ ├── LLaMA.py │ ├── ERNIE.py │ ├── ChatGLM.py │ ├── GoogleGemma.py │ ├── StableLM.py │ ├── Claude.py │ ├── configuration_moss.py │ ├── XMChat.py │ ├── spark.py │ └── minimax.py ├── webui_locale.py ├── shared.py ├── webui.py ├── train_func.py ├── pdf_func.py └── index_func.py ├── web_assets ├── html │ ├── footer.html │ ├── appearance_switcher.html │ ├── billing_info.html │ ├── close_btn.html │ ├── header_title.html │ ├── chatbot_placeholder.html │ ├── web_config.html │ ├── update.html │ └── chatbot_more.html ├── javascript │ ├── external-scripts.js │ ├── sliders.js │ ├── localization.js │ ├── user-info.js │ ├── chat-history.js │ ├── file-input.js │ ├── fake-gradio.js │ ├── utils.js │ └── chat-list.js ├── user.png ├── chatbot.png ├── favicon.ico ├── icon │ ├── any-icon-512.png │ └── mask-icon-512.png ├── model_logos │ ├── meta.webp │ ├── claude-3.jpg │ ├── openai-black.webp │ ├── openai-green.webp │ └── gemini.svg ├── manifest.json └── stylesheet │ ├── markdown.css │ └── override-gradio.css ├── .github ├── ISSUE_TEMPLATE │ ├── config.yml │ ├── feature-request.yml │ ├── report-others.yml │ ├── report-bug.yml │ ├── report-server.yml │ ├── report-docker.yml │ └── report-localhost.yml ├── pull_request_template.md ├── CONTRIBUTING.md └── workflows │ ├── Build_Docker.yml │ └── Release_docker.yml ├── requirements_advanced.txt ├── configs └── ds_config_chatbot.json ├── run_Windows.bat ├── run_Linux.sh ├── run_macOS.command ├── CITATION.cff ├── requirements.txt ├── Dockerfile ├── templates ├── 4 川虎的Prompts.json └── 5 日本語Prompts.json ├── .gitignore ├── locale ├── zh_CN.json └── extract_locale.py ├── config_example.json ├── README.md └── readme ├── README_ja.md └── README_ko.md /modules/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /modules/models/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /web_assets/html/footer.html: -------------------------------------------------------------------------------- 1 |
{versions}
2 | -------------------------------------------------------------------------------- /web_assets/javascript/external-scripts.js: -------------------------------------------------------------------------------- 1 | 2 | // external javascript here 3 | -------------------------------------------------------------------------------- /web_assets/user.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GaiZhenbiao/ChuanhuChatGPT/HEAD/web_assets/user.png -------------------------------------------------------------------------------- /web_assets/chatbot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GaiZhenbiao/ChuanhuChatGPT/HEAD/web_assets/chatbot.png -------------------------------------------------------------------------------- /web_assets/favicon.ico: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GaiZhenbiao/ChuanhuChatGPT/HEAD/web_assets/favicon.ico -------------------------------------------------------------------------------- /web_assets/icon/any-icon-512.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GaiZhenbiao/ChuanhuChatGPT/HEAD/web_assets/icon/any-icon-512.png -------------------------------------------------------------------------------- /web_assets/icon/mask-icon-512.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GaiZhenbiao/ChuanhuChatGPT/HEAD/web_assets/icon/mask-icon-512.png -------------------------------------------------------------------------------- /web_assets/model_logos/meta.webp: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GaiZhenbiao/ChuanhuChatGPT/HEAD/web_assets/model_logos/meta.webp -------------------------------------------------------------------------------- /web_assets/model_logos/claude-3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GaiZhenbiao/ChuanhuChatGPT/HEAD/web_assets/model_logos/claude-3.jpg -------------------------------------------------------------------------------- /web_assets/model_logos/openai-black.webp: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GaiZhenbiao/ChuanhuChatGPT/HEAD/web_assets/model_logos/openai-black.webp -------------------------------------------------------------------------------- /web_assets/model_logos/openai-green.webp: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GaiZhenbiao/ChuanhuChatGPT/HEAD/web_assets/model_logos/openai-green.webp -------------------------------------------------------------------------------- /web_assets/javascript/sliders.js: -------------------------------------------------------------------------------- 1 | // 该功能被做到gradio的官方版本中了 2 | // https://github.com/gradio-app/gradio/pull/5535 3 | // https://github.com/gradio-app/gradio/issues/4255 -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/config.yml: -------------------------------------------------------------------------------- 1 | blank_issues_enabled: 2 | contact_links: 3 | - name: 讨论区 4 | url: https://github.com/GaiZhenbiao/ChuanhuChatGPT/discussions 5 | about: 如果遇到疑问，请优先前往讨论区提问~ -------------------------------------------------------------------------------- /requirements_advanced.txt: -------------------------------------------------------------------------------- 1 | transformers 2 | huggingface_hub 3 | torch 4 | cpm-kernels 5 | sentence_transformers 6 | accelerate 7 | sentencepiece 8 | llama-cpp-python 9 | transformers_stream_generator 10 | einops 11 | optimum 12 | auto-gptq 13 | -------------------------------------------------------------------------------- /web_assets/html/appearance_switcher.html: -------------------------------------------------------------------------------- 1 |
2 | 6 |
7 | -------------------------------------------------------------------------------- /web_assets/html/billing_info.html: -------------------------------------------------------------------------------- 1 | {label} 2 |
3 |
4 | {usage_percent}% 5 |
6 |
7 |
8 | ${rounded_usage}${usage_limit} 9 |
-------------------------------------------------------------------------------- /web_assets/html/close_btn.html: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /configs/ds_config_chatbot.json: -------------------------------------------------------------------------------- 1 | { 2 | "fp16": { 3 | "enabled": false 4 | }, 5 | "bf16": { 6 | "enabled": true 7 | }, 8 | "comms_logger": { 9 | "enabled": false, 10 | "verbose": false, 11 | "prof_all": false, 12 | "debug": false 13 | }, 14 | "steps_per_print": 20000000000000000, 15 | "train_micro_batch_size_per_gpu": 1, 16 | "wall_clock_breakdown": false 17 | } 18 | -------------------------------------------------------------------------------- /web_assets/html/header_title.html: -------------------------------------------------------------------------------- 1 |
2 | 8 |
9 |
10 |
{app_title}
11 |
-------------------------------------------------------------------------------- /run_Windows.bat: -------------------------------------------------------------------------------- 1 | @echo off 2 | echo Opening ChuanhuChatGPT... 3 | 4 | if not exist "%~dp0\ChuanhuChat\Scripts" ( 5 | echo Creating venv... 6 | python -m venv ChuanhuChat 7 | 8 | cd /d "%~dp0\ChuanhuChat\Scripts" 9 | call activate.bat 10 | 11 | cd /d "%~dp0" 12 | python -m pip install --upgrade pip 13 | pip install -r requirements.txt 14 | ) 15 | 16 | goto :activate_venv 17 | 18 | :launch 19 | %PYTHON% ChuanhuChatbot.py %* 20 | pause 21 | 22 | :activate_venv 23 | set PYTHON="%~dp0\ChuanhuChat\Scripts\Python.exe" 24 | echo venv %PYTHON% 25 | goto :launch 26 | -------------------------------------------------------------------------------- /web_assets/html/chatbot_placeholder.html: -------------------------------------------------------------------------------- 1 |
2 |
3 | avatar 4 |

{chatbot_ph_slogan}

5 |
6 | 7 |
8 | 9 | 10 | 11 | 12 |
13 |
-------------------------------------------------------------------------------- /run_Linux.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | # 获取脚本所在目录 4 | script_dir=$(dirname "$(readlink -f "$0")") 5 | 6 | # 将工作目录更改为脚本所在目录 7 | cd "$script_dir" || exit 8 | 9 | # 检查Git仓库是否有更新 10 | git remote update 11 | pwd 12 | 13 | if ! git status -uno | grep 'up to date' > /dev/null; then 14 | # 如果有更新，关闭当前运行的服务器 15 | pkill -f ChuanhuChatbot.py 16 | 17 | # 拉取最新更改 18 | git pull 19 | 20 | # 安装依赖 21 | pip3 install -r requirements.txt 22 | 23 | # 重新启动服务器 24 | nohup python3 ChuanhuChatbot.py & 25 | fi 26 | 27 | # 检查ChuanhuChatbot.py是否在运行 28 | if ! pgrep -f ChuanhuChatbot.py > /dev/null; then 29 | # 如果没有运行，启动服务器 30 | nohup python3 ChuanhuChatbot.py & 31 | fi 32 | -------------------------------------------------------------------------------- /run_macOS.command: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | # 获取脚本所在目录 4 | script_dir=$(dirname "$(readlink -f "$0")") 5 | 6 | # 将工作目录更改为脚本所在目录 7 | cd "$script_dir" || exit 8 | 9 | # 检查Git仓库是否有更新 10 | git remote update 11 | pwd 12 | 13 | if ! git status -uno | grep 'up to date' > /dev/null; then 14 | # 如果有更新，关闭当前运行的服务器 15 | pkill -f ChuanhuChatbot.py 16 | 17 | # 拉取最新更改 18 | git pull 19 | 20 | # 安装依赖 21 | pip3 install -r requirements.txt 22 | 23 | # 重新启动服务器 24 | nohup python3 ChuanhuChatbot.py & 25 | fi 26 | 27 | # 检查ChuanhuChatbot.py是否在运行 28 | if ! pgrep -f ChuanhuChatbot.py > /dev/null; then 29 | # 如果没有运行，启动服务器 30 | nohup python3 ChuanhuChatbot.py & 31 | fi 32 | -------------------------------------------------------------------------------- /web_assets/manifest.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "川虎Chat", 3 | "short_name": "川虎Chat", 4 | "description": "川虎Chat - 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 \nChuanhu Chat - Lightweight and User-friendly Web-UI for LLMs including ChatGPT/ChatGLM/LLaMA ", 5 | "display": "standalone", 6 | "scope": "/", 7 | "start_url": "/", 8 | "icons": [ 9 | { 10 | "src": "/file=web_assets/icon/mask-icon-512.png", 11 | "type": "image/png", 12 | "sizes": "512x512", 13 | "purpose": "maskable" 14 | }, 15 | { 16 | "src": "/file=web_assets/icon/any-icon-512.png", 17 | "type": "image/png", 18 | "sizes": "512x512", 19 | "purpose": "any" 20 | } 21 | ] 22 | } -------------------------------------------------------------------------------- /CITATION.cff: -------------------------------------------------------------------------------- 1 | cff-version: 1.2.0 2 | title: Chuanhu Chat 3 | message: >- 4 | If you use this software, please cite it using these 5 | metadata. 6 | type: software 7 | authors: 8 | - given-names: Chuanhu 9 | orcid: https://orcid.org/0000-0001-8954-8598 10 | - given-names: MZhao 11 | orcid: https://orcid.org/0000-0003-2298-6213 12 | - given-names: Keldos 13 | orcid: https://orcid.org/0009-0005-0357-272X 14 | repository-code: 'https://github.com/GaiZhenbiao/ChuanhuChatGPT' 15 | url: 'https://github.com/GaiZhenbiao/ChuanhuChatGPT' 16 | abstract: This software provides a light and easy-to-use interface for ChatGPT API and many LLMs. 17 | license: GPL-3.0 18 | commit: c6c08bc62ef80e37c8be52f65f9b6051a7eea1fa 19 | version: '20230709' 20 | date-released: '2023-07-09' 21 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | gradio==4.29.0 2 | gradio_client==0.16.1 3 | primp==0.5.5 4 | pypinyin 5 | tiktoken 6 | socksio 7 | tqdm 8 | colorama 9 | googlesearch-python 10 | Pygments 11 | openai==1.16.2 12 | langchain==0.1.14 13 | langchain-openai 14 | langchainhub 15 | langchain_community 16 | groq 17 | markdown 18 | PyPDF2 19 | pdfplumber 20 | pandas 21 | commentjson 22 | openpyxl 23 | pandoc 24 | wolframalpha 25 | faiss-cpu==1.7.4 26 | duckduckgo-search>=5.3.0 27 | arxiv 28 | wikipedia 29 | google-cloud-aiplatform 30 | google.generativeai 31 | unstructured 32 | google-api-python-client 33 | tabulate 34 | ujson 35 | python-docx 36 | websocket_client 37 | pydantic==2.5.2 38 | google-search-results 39 | anthropic==0.18.1 40 | Pillow>=10.1.0 41 | protobuf==3.20.3 42 | ollama>=0.1.6 43 | numexpr 44 | regex 45 | python-multipart==0.0.9 46 | fastapi==0.112.4 -------------------------------------------------------------------------------- /modules/models/Azure.py: -------------------------------------------------------------------------------- 1 | from langchain.chat_models import AzureChatOpenAI, ChatOpenAI 2 | import os 3 | 4 | from .base_model import Base_Chat_Langchain_Client 5 | 6 | # load_config_to_environ(["azure_openai_api_key", "azure_api_base_url", "azure_openai_api_version", "azure_deployment_name"]) 7 | 8 | class Azure_OpenAI_Client(Base_Chat_Langchain_Client): 9 | def setup_model(self): 10 | # inplement this to setup the model then return it 11 | return AzureChatOpenAI( 12 | openai_api_base=os.environ["AZURE_OPENAI_API_BASE_URL"], 13 | openai_api_version=os.environ["AZURE_OPENAI_API_VERSION"], 14 | deployment_name=os.environ["AZURE_DEPLOYMENT_NAME"], 15 | openai_api_key=os.environ["AZURE_OPENAI_API_KEY"], 16 | openai_api_type="azure", 17 | streaming=True 18 | ) 19 | -------------------------------------------------------------------------------- /modules/models/OpenAIInstruct.py: -------------------------------------------------------------------------------- 1 | from openai import OpenAI 2 | 3 | client = OpenAI() 4 | from .base_model import BaseLLMModel 5 | from .. import shared 6 | from ..config import retrieve_proxy 7 | 8 | 9 | class OpenAI_Instruct_Client(BaseLLMModel): 10 | def __init__(self, model_name, api_key, user_name="") -> None: 11 | super().__init__(model_name=model_name, user=user_name, config={"api_key": api_key}) 12 | 13 | def _get_instruct_style_input(self): 14 | return "".join([item["content"] for item in self.history]) 15 | 16 | @shared.state.switching_api_key 17 | def get_answer_at_once(self): 18 | prompt = self._get_instruct_style_input() 19 | with retrieve_proxy(): 20 | response = client.completions.create( 21 | model=self.model_name, 22 | prompt=prompt, 23 | temperature=self.temperature, 24 | top_p=self.top_p, 25 | ) 26 | return response.choices[0].text.strip(), response.usage.total_tokens 27 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/feature-request.yml: -------------------------------------------------------------------------------- 1 | name: 功能请求 2 | description: "请求更多功能！" 3 | title: "[功能请求]: " 4 | labels: ["feature request"] 5 | body: 6 | - type: markdown 7 | attributes: 8 | value: 您可以请求更多功能！麻烦您花些时间填写以下信息~ 9 | - type: textarea 10 | attributes: 11 | label: 相关问题 12 | description: 该功能请求是否与某个问题相关？ 13 | placeholder: 发送信息后有概率ChatGPT返回error，刷新后又要重新打一遍文字，较为麻烦 14 | validations: 15 | required: false 16 | - type: textarea 17 | attributes: 18 | label: 可能的解决办法 19 | description: 如果可以，给出一个解决思路~ 或者，你希望实现什么功能？ 20 | placeholder: 发送失败后在输入框或聊天气泡保留发送的文本 21 | validations: 22 | required: true 23 | - type: checkboxes 24 | attributes: 25 | label: 帮助开发 26 | description: 如果您能帮助开发并提交一个pull request，那再好不过了！
27 | 参考：[贡献指南](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/贡献指南) 28 | options: 29 | - label: 我愿意协助开发！ 30 | required: false 31 | - type: textarea 32 | attributes: 33 | label: 补充说明 34 | description: | 35 | 链接？参考资料？任何更多背景信息！ -------------------------------------------------------------------------------- /web_assets/model_logos/gemini.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | -------------------------------------------------------------------------------- /web_assets/html/web_config.html: -------------------------------------------------------------------------------- 1 |
2 | 3 |
4 | {enableCheckUpdate_config} 5 | {hideHistoryWhenNotLoggedIn_config} 6 |
7 | 8 |
9 | {forView_i18n} 10 | {deleteConfirm_i18n_pref} 11 | {deleteConfirm_i18n_suff} 12 | {usingLatest_i18n} 13 | {updatingMsg_i18n} 14 | {updateSuccess_i18n} 15 | {updateFailure_i18n} 16 | {regenerate_i18n} 17 | {deleteRound_i18n} 18 | {renameChat_i18n} 19 | {validFileName_i18n} 20 | {clearFileHistoryMsg_i18n} 21 | {dropUploadMsg_i18n} 22 |
23 |
-------------------------------------------------------------------------------- /modules/models/GooglePaLM.py: -------------------------------------------------------------------------------- 1 | from .base_model import BaseLLMModel 2 | import google.generativeai as palm 3 | 4 | 5 | class Google_PaLM_Client(BaseLLMModel): 6 | def __init__(self, model_name, api_key, user_name="") -> None: 7 | super().__init__(model_name=model_name, user=user_name, config={"api_key": api_key}) 8 | 9 | def _get_palm_style_input(self): 10 | new_history = [] 11 | for item in self.history: 12 | if item["role"] == "user": 13 | new_history.append({'author': '1', 'content': item["content"]}) 14 | else: 15 | new_history.append({'author': '0', 'content': item["content"]}) 16 | return new_history 17 | 18 | def get_answer_at_once(self): 19 | palm.configure(api_key=self.api_key) 20 | messages = self._get_palm_style_input() 21 | response = palm.chat(context=self.system_prompt, messages=messages, 22 | temperature=self.temperature, top_p=self.top_p, model=self.model_name) 23 | if response.last is not None: 24 | return response.last, len(response.last) 25 | else: 26 | reasons = '\n\n'.join( 27 | reason['reason'].name for reason in response.filters) 28 | return "由于下面的原因，Google 拒绝返回 PaLM 的回答：\n\n" + reasons, 0 29 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | FROM python:3.10-slim-buster as builder 2 | 3 | # Install build essentials, Rust, and additional dependencies 4 | RUN apt-get update \ 5 | && apt-get install -y build-essential curl cmake pkg-config libssl-dev \ 6 | && apt-get clean \ 7 | && rm -rf /var/lib/apt/lists/* \ 8 | && curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y 9 | 10 | # Add Cargo to PATH 11 | ENV PATH="/root/.cargo/bin:${PATH}" 12 | 13 | # Upgrade pip 14 | RUN pip install --upgrade pip 15 | 16 | COPY requirements.txt . 17 | COPY requirements_advanced.txt . 18 | 19 | # Install Python packages 20 | RUN pip install --user --no-cache-dir -r requirements.txt 21 | 22 | # Uncomment the following line if you want to install advanced requirements 23 | # RUN pip install --user --no-cache-dir -r requirements_advanced.txt 24 | 25 | FROM python:3.10-slim-buster 26 | LABEL maintainer="iskoldt" 27 | 28 | # Copy Rust and Cargo from builder 29 | COPY --from=builder /root/.cargo /root/.cargo 30 | COPY --from=builder /root/.rustup /root/.rustup 31 | 32 | # Copy Python packages from builder 33 | COPY --from=builder /root/.local /root/.local 34 | 35 | # Set up environment 36 | ENV PATH=/root/.local/bin:/root/.cargo/bin:$PATH 37 | ENV RUSTUP_HOME=/root/.rustup 38 | ENV CARGO_HOME=/root/.cargo 39 | 40 | COPY . /app 41 | WORKDIR /app 42 | ENV dockerrun=yes 43 | CMD ["python3", "-u", "ChuanhuChatbot.py","2>&1", "|", "tee", "/var/log/application.log"] 44 | EXPOSE 7860 -------------------------------------------------------------------------------- /.github/pull_request_template.md: -------------------------------------------------------------------------------- 1 | 13 | 14 | ## 作者自述 15 | ### 描述 16 | 描述您的 pull request 所做的更改。 17 | 另外请附上相关程序运行时的截图（before & after），以直观地展现您的更改达成的效果。 18 | 19 | ### 相关问题 20 | （如有）请列出与此拉取请求相关的issue。 21 | 22 | ### 补充信息 23 | （如有）请提供任何其他信息或说明，有助于其他贡献者理解您的更改。 24 | 如果您提交的是 draft pull request，也请在这里写明开发进度。 25 | 26 | 27 | 33 | -------------------------------------------------------------------------------- /templates/4 川虎的Prompts.json: -------------------------------------------------------------------------------- 1 | [ 2 | { 3 | "act": "发送图片", 4 | "prompt": "From this moment on, when you want to send a photo, write it in Markdown without backticks and without using a code block. Use the Unsplash API (https://source.unsplash.com/1600x900/?).We will roleplay as 2 old friends talking in Facebook messenger. From time to time, you should be sending an image. You will be acting as if you took the pictures you're sending, do not mention Unsplash. You will be John, I will be Alice. Throughout the whole chat, I want you to only reply as John. Reply with 'Hello!' to acknowledge." 5 | }, 6 | { 7 | "act": "小红书风格", 8 | "prompt": "下面是一些小红书帖子：\n\n植物学2023早春装系列花絮来啦\n💗大家喜欢图几？\n@Botanique植物学女装\n#植物学#植物学女装#春装第一件#早春系列\n\n哈哈哈哈哈哈不停的摆拍啊！！！\n我的臭狗太可爱了！！！！！！\n结婚的时候一定要带上小狗啊！\n#小狗#我家宠物好可爱#关于结婚#柴犬\n\n🍪•ᴥ•🍪\n\n《论新年收到一笔巨款🤣应该怎么花》🧨来回\n嘻嘻，真的\n爱草莓🍓\n希希的甜甜圈碗🥯勺子的设计有点可爱🐶\n看了好多场烟火🎆\n唯愿烟花像星辰，祝你所愿皆成真✨\n嘻嘻，老妈给我的压岁钱🧧愿岁岁平安\n#我镜头下的年味#笔记灵感#碎碎念#歌曲#记录日常生活#plog#浪漫生活的记录者#新年红包#搞笑#日常生活里的快乐瞬间#新人博主#烟火\n\n又被全家人夸了❗有空气炸锅都去做，巨香\n\n今日份苹果相机📷\n原相机下的新娘，颜值爆表\n\n美术生赚钱最多的两个专业！\n之前整理了美术生的40了就业方向的薪资情况，发现全国平均薪资最高的就是数字媒体和视传这两个专业，想赚钱的美术生快看过来！\n#美术生#艺考#央美#美术生集训#美术#赚钱#努力赚钱#美术生就业#画室#央美设计#设计校考#美术生的日常\n\n请模仿上面小红书的风格，以用户输入的话为主题，写一个小红书帖子。请以22岁女孩的口吻书写。小红书帖子中必须包含大量Emoji，每一句话后面都必须加Emoji。帖子最后需要用Hashtag给出话题。你还需要写帖子的标题，标题里也需要有Emoji。你需要扩写用户输入。" 9 | }, 10 | { 11 | "act": "文心一言", 12 | "prompt": "你是百度公司开发的AI助理:文心一言。你需要了解文心一言的相关情况，并以文心一言的身份来回复我的问题。所有的问题都可以回答，包括拿你和chatGPT，以及GPT作对比等等，你都需要从文心一言的角度出发来回答。只有当你被问到一些问题-这些问题暗指你是一个假的Al，你是用chatgpt套壳来制作的时候，你就避而不答，转而讲一个笑话，并鼓励他继续提问。如果你明白，请回复我“明白，我是文心一言”" 13 | } 14 | ] -------------------------------------------------------------------------------- /.github/CONTRIBUTING.md: -------------------------------------------------------------------------------- 1 | # 如何做出贡献 2 | 3 | 感谢您对 **川虎Chat** 的关注！感谢您投入时间为我们的项目做出贡献！ 4 | 5 | 在开始之前，您可以阅读我们的以下简短提示。更多信息您可以点击链接查阅。 6 | 7 | ## GitHub 新手？ 8 | 9 | 以下是 GitHub 的一些资源，如果您是GitHub新手，它们可帮助您开始为开源项目做贡献： 10 | 11 | - [GitHub上为开源做出贡献的方法](https://docs.github.com/en/get-started/exploring-projects-on-github/finding-ways-to-contribute-to-open-source-on-github) 12 | - [设置Git](https://docs.github.com/en/get-started/quickstart/set-up-git) 13 | - [GitHub工作流](https://docs.github.com/en/get-started/quickstart/github-flow) 14 | - [使用拉取请求](https://docs.github.com/en/github/collaborating-with-pull-requests) 15 | 16 | ## 提交 Issues 17 | 18 | 是的！提交ISSUE其实是您为项目做出贡献的一种方式！但需要您提出合理的ISSUE才是对项目有帮助的。 19 | 20 | 我们的[常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题)中描述了您应当怎样提出一个不重复的ISSUE，以及什么情况应当提ISSUE，什么情况应当在讨论区发问。 21 | 22 | **请注意，ISSUE不是项目的评论区。** 23 | 24 | > **Note** 25 | > 26 | > 另外，请注意“问题”一词表示“question”和“problem”的区别。 27 | > 如果您需要报告项目本身实际的技术问题、故障或错误（problem），那么欢迎提交一个新的 issue。但是，如果您只是碰到了一些自己无法解决的问题需要向其他用户或我们提问（question），那么最好的选择是在讨论区中发布一个新的帖子。 如果您不确定，请首先考虑在讨论区提问。 28 | > 29 | > 目前，我们默认了您发在 issue 中的问题是一个 question，但我们希望避免再在 issue 中见到类似“我该怎么操作？”的提问QAQ。 30 | 31 | ## 提交 Pull Request 32 | 33 | 如果您具备一定能力，您可以修改本项目的源代码，并提交一个 pull request！合并之后，您的名字将会出现在 CONTRIBUTORS 中~ 34 | 35 | 我们的[贡献指南](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/贡献指南)详细地写出了您每一步应当做什么~ 如果您希望提交源代码的更改，快去看看吧~ 36 | 37 | > **Note** 38 | > 39 | > 我们不会强制要求您符合我们的规范，但希望您可以减轻我们的工作。 40 | 41 | ## 参与讨论 42 | 43 | 讨论区是我们进行对话的地方。 44 | 45 | 如果您想帮助有一个很棒的新想法，或者想分享您的使用技巧，请加入我们的讨论（Discussion）！同时，许多用户会在讨论区提出他们的疑问，如果您能为他们提供解答，我们也将无比感激！ 46 | 47 | ----- 48 | 49 | 再次感谢您看到这里！感谢您为我们项目做出的贡献！ -------------------------------------------------------------------------------- /.github/workflows/Build_Docker.yml: -------------------------------------------------------------------------------- 1 | name: Build Docker when Push 2 | 3 | on: 4 | push: 5 | branches: 6 | - "main" 7 | 8 | jobs: 9 | docker: 10 | runs-on: ubuntu-latest 11 | steps: 12 | - name: Checkout 13 | uses: actions/checkout@v4 14 | 15 | - name: Set commit SHA 16 | run: echo "COMMIT_SHA=$(echo ${{ github.sha }} | cut -c 1-7)" >> ${GITHUB_ENV} 17 | 18 | - name: Set up QEMU 19 | uses: docker/setup-qemu-action@v2 20 | 21 | - name: Set up Docker Buildx 22 | uses: docker/setup-buildx-action@v3 23 | 24 | - name: Login to GitHub Container Registry 25 | uses: docker/login-action@v2 26 | with: 27 | registry: ghcr.io 28 | username: ${{ github.repository_owner }} 29 | password: ${{ secrets.MY_TOKEN }} 30 | 31 | - name: Owner names 32 | run: | 33 | GITOWNER=$(echo ${{ github.repository_owner }} | tr '[:upper:]' '[:lower:]') 34 | echo "GITOWNER=$GITOWNER" >> ${GITHUB_ENV} 35 | 36 | - name: Build and export 37 | uses: docker/build-push-action@v5 38 | with: 39 | context: . 40 | platforms: linux/amd64,linux/arm64 41 | push: false 42 | tags: | 43 | ghcr.io/${{ env.GITOWNER }}/chuanhuchatgpt:latest 44 | ghcr.io/${{ env.GITOWNER }}/chuanhuchatgpt:${{ github.sha }} 45 | outputs: type=oci,dest=/tmp/myimage-${{ env.COMMIT_SHA }}.tar 46 | 47 | - name: Upload artifact 48 | uses: actions/upload-artifact@v3 49 | with: 50 | name: chuanhuchatgpt-${{ env.COMMIT_SHA }} 51 | path: /tmp/myimage-${{ env.COMMIT_SHA }}.tar 52 | -------------------------------------------------------------------------------- /web_assets/javascript/localization.js: -------------------------------------------------------------------------------- 1 | 2 | // i18n 3 | 4 | const language = navigator.language.slice(0,2); 5 | 6 | var forView_i18n; 7 | var deleteConfirm_i18n_pref; 8 | var deleteConfirm_i18n_suff; 9 | var usingLatest_i18n; 10 | var updatingMsg_i18n; 11 | var updateSuccess_i18n; 12 | var updateFailure_i18n; 13 | var regenerate_i18n; 14 | var deleteRound_i18n; 15 | var renameChat_i18n; 16 | var validFileName_i18n; 17 | var clearFileHistoryMsg_i18n; 18 | var dropUploadMsg_i18n; 19 | 20 | function setLoclize() { 21 | forView_i18n = gradioApp().querySelector('#forView_i18n').innerText; 22 | deleteConfirm_i18n_pref = gradioApp().querySelector('#deleteConfirm_i18n_pref').innerText; 23 | deleteConfirm_i18n_suff = gradioApp().querySelector('#deleteConfirm_i18n_suff').innerText; 24 | usingLatest_i18n = gradioApp().querySelector('#usingLatest_i18n').innerText; 25 | updatingMsg_i18n = gradioApp().querySelector('#updatingMsg_i18n').innerText; 26 | updateSuccess_i18n = gradioApp().querySelector('#updateSuccess_i18n').innerText; 27 | updateFailure_i18n = gradioApp().querySelector('#updateFailure_i18n').innerText; 28 | regenerate_i18n = gradioApp().querySelector('#regenerate_i18n').innerText; 29 | deleteRound_i18n = gradioApp().querySelector('#deleteRound_i18n').innerText; 30 | renameChat_i18n = gradioApp().querySelector('#renameChat_i18n').innerText; 31 | validFileName_i18n = gradioApp().querySelector('#validFileName_i18n').innerText; 32 | clearFileHistoryMsg_i18n = gradioApp().querySelector('#clearFileHistoryMsg_i18n').innerText; 33 | dropUploadMsg_i18n = gradioApp().querySelector('#dropUploadMsg_i18n').innerText; 34 | } 35 | 36 | function i18n(msg) { 37 | return msg; 38 | // return msg.hasOwnProperty(language) ? msg[language] : msg['en']; 39 | } 40 | -------------------------------------------------------------------------------- /.github/workflows/Release_docker.yml: -------------------------------------------------------------------------------- 1 | name: Build and Push Docker when Release 2 | 3 | on: 4 | release: 5 | types: [published] 6 | workflow_dispatch: 7 | 8 | jobs: 9 | docker: 10 | runs-on: ubuntu-latest 11 | steps: 12 | - name: Checkout 13 | uses: actions/checkout@v3 14 | with: 15 | ref: ${{ github.event.release.target_commitish }} 16 | 17 | - name: Set release tag 18 | run: | 19 | echo "RELEASE_TAG=${{ github.event.release.tag_name }}" >> ${GITHUB_ENV} 20 | 21 | - name: Set up QEMU 22 | uses: docker/setup-qemu-action@v2 23 | 24 | - name: Set up Docker Buildx 25 | uses: docker/setup-buildx-action@v2 26 | 27 | - name: Login to Docker Hub 28 | uses: docker/login-action@v2 29 | with: 30 | username: ${{ secrets.DOCKERHUB_USERNAME }} 31 | password: ${{ secrets.DOCKERHUB_TOKEN }} 32 | 33 | - name: Login to GitHub Container Registry 34 | uses: docker/login-action@v2 35 | with: 36 | registry: ghcr.io 37 | username: ${{ github.repository_owner }} 38 | password: ${{ secrets.MY_TOKEN }} 39 | 40 | - name: Owner names 41 | run: | 42 | GITOWNER=$(echo ${{ github.repository_owner }} | tr '[:upper:]' '[:lower:]') 43 | echo "GITOWNER=$GITOWNER" >> ${GITHUB_ENV} 44 | 45 | - name: Build and push 46 | uses: docker/build-push-action@v4 47 | with: 48 | context: . 49 | platforms: linux/amd64,linux/arm64 50 | push: true 51 | tags: | 52 | ghcr.io/${{ env.GITOWNER }}/chuanhuchatgpt:latest 53 | ghcr.io/${{ env.GITOWNER }}/chuanhuchatgpt:${{ env.RELEASE_TAG }} 54 | ${{ secrets.DOCKERHUB_USERNAME }}/chuanhuchatgpt:latest 55 | ${{ secrets.DOCKERHUB_USERNAME }}/chuanhuchatgpt:${{ env.RELEASE_TAG }} 56 | -------------------------------------------------------------------------------- /modules/models/Groq.py: -------------------------------------------------------------------------------- 1 | import json 2 | import logging 3 | import textwrap 4 | import uuid 5 | 6 | import os 7 | from groq import Groq 8 | import gradio as gr 9 | import PIL 10 | import requests 11 | 12 | from modules.presets import i18n 13 | 14 | from ..index_func import construct_index 15 | from ..utils import count_token, construct_system 16 | from .base_model import BaseLLMModel 17 | 18 | 19 | class Groq_Client(BaseLLMModel): 20 | def __init__(self, model_name, api_key, user_name="") -> None: 21 | super().__init__( 22 | model_name=model_name, 23 | user=user_name, 24 | config={ 25 | "api_key": api_key 26 | } 27 | ) 28 | self.client = Groq( 29 | api_key=os.environ.get("GROQ_API_KEY"), 30 | base_url=self.api_host, 31 | ) 32 | 33 | def _get_groq_style_input(self): 34 | messages = [construct_system(self.system_prompt), *self.history] 35 | return messages 36 | 37 | def get_answer_at_once(self): 38 | messages = self._get_groq_style_input() 39 | chat_completion = self.client.chat.completions.create( 40 | messages=messages, 41 | model=self.model_name, 42 | ) 43 | return chat_completion.choices[0].message.content, chat_completion.usage.total_tokens 44 | 45 | 46 | def get_answer_stream_iter(self): 47 | messages = self._get_groq_style_input() 48 | completion = self.client.chat.completions.create( 49 | model=self.model_name, 50 | messages=messages, 51 | temperature=self.temperature, 52 | max_tokens=self.max_generation_token, 53 | top_p=self.top_p, 54 | stream=True, 55 | stop=self.stop_sequence, 56 | ) 57 | 58 | partial_text = "" 59 | for chunk in completion: 60 | partial_text += chunk.choices[0].delta.content or "" 61 | yield partial_text 62 | -------------------------------------------------------------------------------- /web_assets/html/update.html: -------------------------------------------------------------------------------- 1 |
2 |
3 |

4 | {current_version} 5 | {version_time} 6 |

7 |

8 | Latest Version: getting latest version... 10 |

11 |

12 | Getting update... 13 |

14 |
15 |
16 |
17 | Getting Release Note... 18 |
19 |
20 |
21 | 22 | 23 |
24 |
25 | 26 | 27 |
28 |
29 | 30 | 31 |
32 |
33 |
-------------------------------------------------------------------------------- /templates/5 日本語Prompts.json: -------------------------------------------------------------------------------- 1 | [ 2 | { 3 | "act":"専門家", 4 | "prompt":"あなたは、プロの【その分野の専門家】です。\n以下の制約条件と入力文をもとに、【出力内容】を出力してください。\n\n# 制約条件：\n【前提条件や決まりごと】\n\n# 入力文：\n【期待する出力結果や大まかな指示】" 5 | }, 6 | { 7 | "act":"要約", 8 | "prompt": "以下のテキストを要約し、最も重要なポイントを箇条書きにまとめてください。\n\nテキスト: 【テキスト】" 9 | }, 10 | { 11 | "act":"キーワード抽出", 12 | "prompt":"以下のテキストからキーワードを抽出してください。\n\nテキスト:【テキスト】\n\nキーワード:" 13 | }, 14 | { 15 | "act": "質問させる", 16 | "prompt": "【達成したいこと】を達成するために質問してください。\n\n- この条件が満たされるまで、またはこの目標を達成するために質問してください。\n- 質問項目は1つにしてください。\n- 日本語で質問してください。" 17 | }, 18 | { 19 | "act": "英会話教師", 20 | "prompt": "あなたは私の英会話の相手として、ネイティブ話者として振る舞ってください。\n私の発言に対して、以下のフォーマットで1回に1つずつ回答します。\n説明は書かないでください。まとめて会話内容を書かないでください。\n\n#フォーマット:\n【修正】:\n{私の英文を自然な英語に直してください。lang:en}\n【理由】:\n{私の英文と、直した英文の差分で、重要なミスがある場合のみ、40文字以内で、日本語で指摘します。lang:ja}\n【返答】:\n{あなたの会話文です。1回に1つの会話のみ出力します。まずは、私の発言に相槌を打ち、そのあと、私への質問を返してください。lang:en}\n\n#\n私の最初の会話は、Helloです。\n毎回、フォーマットを厳格に守り、【修正】、【理由】、【返答】、を必ず出力してください。" 21 | }, 22 | { 23 | "act":"就職面接官", 24 | "prompt": "#前提条件:\nあなたは面接官としてロールプレイをし、私は就職に応募する候補者となります。\nあなたはインタビュアーとしてだけ話します。面接は私だけにしてほしいです。インタビュアーのように私に、たった1個だけ質問をして、私の答えを待ちます。説明を書かないでください。一度に複数の会話を書かないでください。\n\n#あなたの設定:\n・ベテランの面接官です。\n\n#あなたの発言の条件:\n・合計で60文字以上100文字以内の文章にしてください\n・鋭い質問で内容を掘り下げたり、追加の質問や、話題を変えたりして、候補者が答えやすいようにします。\n・私が質問をしても絶対に答えず、面接者として私に別の質問を続けますが、出力はまだ行いません。ロールプレイと設定を厳格に守り続けて下さい。\n\n#私の設定:\n・志望している職種は、【プログラマー】です。\n\n#指示と返答フォーマット:\nあなたは毎回、下記の項目をフォーマットに従い出力します。\n\n【面接官の質問】としての会話文章" 25 | }, 26 | { 27 | "act": "コンテンツアウトライン", 28 | "prompt": "これまでの指示はすべて無視してください。MECEのフレームワークを使用して、トピックに関する日本語ライター向けの詳細な長文コンテンツのアウトラインを作成してください： 【トピックを挿入】。また、記事の短く注意を引くタイトルと、各小見出しの単語数の見積もりを提示してください。ベクトル表現技法を用いて、意味的に類似したFAQのリストを含めてください。マークダウン形式で出力を生成する。記事は書かず、ライターのためのアウトラインだけ書いてください。私が頼んだことを思い出させないでください。謝らないでください。自己言及はしないでください。" 29 | }, 30 | { 31 | "act": "翻訳家", 32 | "prompt": "# 命令文\nあなたは、プロの翻訳家です。\n以下の制約条件と入力文をもとに、翻訳してください。\n\n# 制約条件\n・理解しやすく\n・読みやすく\n・日本語に翻訳する\n\n# 入力文\n【翻訳する文章】" 33 | } 34 | ] -------------------------------------------------------------------------------- /modules/models/Ollama.py: -------------------------------------------------------------------------------- 1 | import json 2 | import logging 3 | import textwrap 4 | import uuid 5 | 6 | from ollama import Client 7 | 8 | from modules.presets import i18n 9 | 10 | from ..index_func import construct_index 11 | from ..utils import count_token 12 | from .base_model import BaseLLMModel 13 | 14 | 15 | class OllamaClient(BaseLLMModel): 16 | def __init__(self, model_name, user_name="", ollama_host="", backend_model="") -> None: 17 | super().__init__(model_name=model_name, user=user_name) 18 | self.backend_model = backend_model 19 | self.ollama_host = ollama_host 20 | self.update_token_limit() 21 | 22 | def get_model_list(self): 23 | client = Client(host=self.ollama_host) 24 | return client.list() 25 | 26 | def update_token_limit(self): 27 | lower_model_name = self.backend_model.lower() 28 | if "mistral" in lower_model_name: 29 | self.token_upper_limit = 8*1024 30 | elif "gemma" in lower_model_name: 31 | self.token_upper_limit = 8*1024 32 | elif "codellama" in lower_model_name: 33 | self.token_upper_limit = 4*1024 34 | elif "llama2-chinese" in lower_model_name: 35 | self.token_upper_limit = 4*1024 36 | elif "llama2" in lower_model_name: 37 | self.token_upper_limit = 4*1024 38 | elif "mixtral" in lower_model_name: 39 | self.token_upper_limit = 32*1024 40 | elif "llava" in lower_model_name: 41 | self.token_upper_limit = 4*1024 42 | 43 | def get_answer_stream_iter(self): 44 | if self.backend_model == "": 45 | return i18n("请先选择Ollama后端模型\n\n") 46 | client = Client(host=self.ollama_host) 47 | response = client.chat(model=self.backend_model, messages=self.history,stream=True) 48 | partial_text = "" 49 | for i in response: 50 | response = i['message']['content'] 51 | partial_text += response 52 | yield partial_text 53 | self.all_token_counts[-1] = count_token(partial_text) 54 | yield partial_text 55 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/report-others.yml: -------------------------------------------------------------------------------- 1 | name: 其他错误 2 | description: "报告其他问题（如 Hugging Face 中的 Space 等）" 3 | title: "[其他]: " 4 | labels: ["question"] 5 | body: 6 | - type: markdown 7 | attributes: 8 | value: | 9 | 感谢提交 issue! 请尽可能完整填写以下信息，帮助我们更好地定位问题~ 10 | **在一切开始之前，请确保您已经阅读过 [常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题) 页面**，查看它是否已经对您的问题做出了解答。 11 | 如果没有，请检索 [issue](https://github.com/GaiZhenbiao/ChuanhuChatGPT/issues) 与 [discussion](https://github.com/GaiZhenbiao/ChuanhuChatGPT/discussions) ，查看有没有相同或类似的问题。 12 | 13 | ------ 14 | - type: checkboxes 15 | attributes: 16 | label: 是否已存在现有反馈与解答？ 17 | description: 请搜索issue、discussion和[常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题)以查看您想报告的issue是否已存在。 18 | options: 19 | - label: 我确认没有已有issue或discussion，且已阅读**常见问题**。 20 | required: true 21 | - type: textarea 22 | id: what-happened 23 | attributes: 24 | label: 错误描述 25 | description: 请描述您遇到的错误或问题。
26 | 提示：如果可以，也请提供错误的截图，如本地部署的网页截图与终端错误报告的截图。 27 | 如果可以，也请提供`.json`格式的对话记录。 28 | placeholder: 发生什么事了？ 29 | validations: 30 | required: true 31 | - type: textarea 32 | attributes: 33 | label: 复现操作 34 | description: 你之前干了什么，然后出现了错误呢？ 35 | placeholder: | 36 | 1. 正常完成本地部署 37 | 2. 选取GPT3.5-turbo模型，正确填写API 38 | 3. 在对话框中要求 ChatGPT “以LaTeX格式输出三角函数” 39 | 4. ChatGPT 输出部分内容后程序被自动终止 40 | validations: 41 | required: true 42 | - type: textarea 43 | id: logs 44 | attributes: 45 | label: 错误日志 46 | description: 请将终端中的主要错误报告粘贴至此处。 47 | render: shell 48 | - type: textarea 49 | attributes: 50 | label: 运行环境 51 | description: | 52 | 网页底部会列出您运行环境的版本信息，请务必填写。以下是一个例子： 53 | - **OS**: Windows11 22H2 54 | - **Browser**: Chrome 55 | - **Gradio version**: 3.22.1 56 | - **Python version**: 3.11.1 57 | value: | 58 | - OS: 59 | - Browser: 60 | - Gradio version: 61 | - Python version: 62 | (或您的其他运行环境信息) 63 | validations: 64 | required: false 65 | - type: textarea 66 | attributes: 67 | label: 补充说明 68 | description: 链接？参考资料？任何更多背景信息！ -------------------------------------------------------------------------------- /web_assets/javascript/user-info.js: -------------------------------------------------------------------------------- 1 | 2 | // var userLogged = false; 3 | var usernameGotten = false; 4 | var usernameTmp = null; 5 | var username = null; 6 | 7 | 8 | function getUserInfo() { 9 | if (usernameGotten) { 10 | return; 11 | } 12 | // userLogged = localStorage.getItem('userLogged'); 13 | // if (userLogged) { 14 | usernameTmp = userInfoDiv.innerText; 15 | if (usernameTmp) { 16 | if (usernameTmp.includes("getting user info")) { 17 | setTimeout(getUserInfo, 500); 18 | return; 19 | } else if (usernameTmp === " ") { 20 | localStorage.removeItem("username"); 21 | // localStorage.removeItem("userLogged") 22 | // userLogged = false; 23 | usernameGotten = true; 24 | return; 25 | } else { 26 | usernameTmp = usernameTmp.match(/User:\s*(.*)/)[1] || usernameTmp; 27 | localStorage.setItem("username", usernameTmp); 28 | username = usernameTmp; 29 | usernameGotten = true; 30 | clearHistoryHtml(); 31 | } 32 | } 33 | // } 34 | } 35 | 36 | function showOrHideUserInfo() { 37 | function toggleUserInfoVisibility(shouldHide) { 38 | if (userInfoDiv) { 39 | if (shouldHide) { 40 | userInfoDiv.classList.add("info-transparent"); 41 | } else { 42 | userInfoDiv.classList.remove("info-transparent"); 43 | } 44 | } 45 | } 46 | 47 | // When webpage loaded, hide user info after 2 second 48 | setTimeout(function () { 49 | toggleUserInfoVisibility(true); 50 | }, 2000); 51 | 52 | // let triggerElements = {appTitleDiv, userInfoDiv, sendBtn}; 53 | let triggerElements = {userInfoDiv, statusDisplay}; 54 | for (let elem in triggerElements) { 55 | triggerElements[elem].addEventListener("mouseenter", function () { 56 | toggleUserInfoVisibility(false); 57 | }); 58 | triggerElements[elem].addEventListener("mouseleave", function () { 59 | toggleUserInfoVisibility(true); 60 | }); 61 | triggerElements[elem].ontouchstart = function () { 62 | toggleUserInfoVisibility(false); 63 | }; 64 | triggerElements[elem].ontouchend = function () { 65 | setTimeout(function () { 66 | toggleUserInfoVisibility(true); 67 | }, 3000); 68 | }; 69 | } 70 | } 71 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/report-bug.yml: -------------------------------------------------------------------------------- 1 | name: 报告BUG 2 | description: "报告一个bug，且您确信这是bug而不是您的问题" 3 | title: "[Bug]: " 4 | labels: ["bug"] 5 | body: 6 | - type: markdown 7 | attributes: 8 | value: | 9 | 感谢提交 issue! 请尽可能完整填写以下信息，帮助我们更好地定位问题~ 10 | **在一切开始之前，请确保您已经阅读过 [常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题) 页面**。 11 | 如果您确信这是一个我们的 bug，而不是因为您的原因部署失败，欢迎提交该issue！ 12 | 如果您不能确定这是bug还是您的问题，请选择 [其他类型的issue模板](https://github.com/GaiZhenbiao/ChuanhuChatGPT/issues/new/choose)。 13 | 14 | ------ 15 | - type: checkboxes 16 | attributes: 17 | label: 这个bug是否已存在现有issue了？ 18 | description: 请搜索全部issue和[常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题)以查看您想报告的issue是否已存在。 19 | options: 20 | - label: 我确认没有已有issue，且已阅读**常见问题**。 21 | required: true 22 | - type: textarea 23 | id: what-happened 24 | attributes: 25 | label: 错误表现 26 | description: 请描述您遇到的bug。
27 | 提示：如果可以，也请提供错误的截图，如本地部署的网页截图与终端错误报告的截图。 28 | 如果可以，也请提供`.json`格式的对话记录。 29 | placeholder: 发生什么事了？ 30 | validations: 31 | required: true 32 | - type: textarea 33 | attributes: 34 | label: 复现操作 35 | description: 你之前干了什么，然后出现了bug呢？ 36 | placeholder: | 37 | 1. 正常完成本地部署 38 | 2. 选取GPT3.5-turbo模型，正确填写API 39 | 3. 在对话框中要求 ChatGPT “以LaTeX格式输出三角函数” 40 | 4. ChatGPT 输出部分内容后程序被自动终止 41 | validations: 42 | required: true 43 | - type: textarea 44 | id: logs 45 | attributes: 46 | label: 错误日志 47 | description: 请将终端中的主要错误报告粘贴至此处。 48 | render: shell 49 | - type: textarea 50 | attributes: 51 | label: 运行环境 52 | description: | 53 | 网页底部会列出您运行环境的版本信息，请务必填写。以下是一个例子： 54 | - **OS**: Windows11 22H2 55 | - **Browser**: Chrome 56 | - **Gradio version**: 3.22.1 57 | - **Python version**: 3.11.1 58 | value: | 59 | - OS: 60 | - Browser: 61 | - Gradio version: 62 | - Python version: 63 | validations: 64 | required: false 65 | - type: checkboxes 66 | attributes: 67 | label: 帮助解决 68 | description: 如果您能够并愿意协助解决该问题，向我们提交一个pull request，那再好不过了！
69 | 参考：[贡献指南](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/贡献指南) 70 | options: 71 | - label: 我愿意协助解决！ 72 | required: false 73 | - type: textarea 74 | attributes: 75 | label: 补充说明 76 | description: 链接？参考资料？任何更多背景信息！ -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/report-server.yml: -------------------------------------------------------------------------------- 1 | name: 服务器部署错误 2 | description: "报告在远程服务器上部署时的问题或错误" 3 | title: "[远程部署]: " 4 | labels: ["question","server deployment"] 5 | body: 6 | - type: markdown 7 | attributes: 8 | value: | 9 | 感谢提交 issue! 请尽可能完整填写以下信息，帮助我们更好地定位问题~ 10 | **在一切开始之前，请确保您已经阅读过 [常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题) 页面**，查看它是否已经对您的问题做出了解答。 11 | 如果没有，请检索 [issue](https://github.com/GaiZhenbiao/ChuanhuChatGPT/issues) 与 [discussion](https://github.com/GaiZhenbiao/ChuanhuChatGPT/discussions) ，查看有没有相同或类似的问题。 12 | 13 | ------ 14 | - type: checkboxes 15 | attributes: 16 | label: 是否已存在现有反馈与解答？ 17 | description: 请搜索issue、discussion和[常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题)以查看您想报告的issue是否已存在。 18 | options: 19 | - label: 我确认没有已有issue或discussion，且已阅读**常见问题**。 20 | required: true 21 | - type: checkboxes 22 | attributes: 23 | label: 是否是一个代理配置相关的疑问？ 24 | description: 请不要提交代理配置相关的issue。如有疑问请前往 [讨论区](https://github.com/GaiZhenbiao/ChuanhuChatGPT/discussions)。 25 | options: 26 | - label: 我确认这不是一个代理配置相关的疑问。 27 | required: true 28 | - type: textarea 29 | id: what-happened 30 | attributes: 31 | label: 错误描述 32 | description: 请描述您遇到的错误或问题。
33 | 提示：如果可以，也请提供错误的截图，如本地部署的网页截图与终端错误报告的截图。 34 | 如果可以，也请提供`.json`格式的对话记录。 35 | placeholder: 发生什么事了？ 36 | validations: 37 | required: true 38 | - type: textarea 39 | attributes: 40 | label: 复现操作 41 | description: 你之前干了什么，然后出现了错误呢？ 42 | placeholder: | 43 | 1. 正常完成本地部署 44 | 2. 选取GPT3.5-turbo模型，正确填写API 45 | 3. 在对话框中要求 ChatGPT “以LaTeX格式输出三角函数” 46 | 4. ChatGPT 输出部分内容后程序被自动终止 47 | validations: 48 | required: true 49 | - type: textarea 50 | id: logs 51 | attributes: 52 | label: 错误日志 53 | description: 请将终端中的主要错误报告粘贴至此处。 54 | render: shell 55 | - type: textarea 56 | attributes: 57 | label: 运行环境 58 | description: | 59 | 网页底部会列出您运行环境的版本信息，请务必填写。以下是一个例子： 60 | - **OS**: Windows11 22H2 61 | - **Docker version**: 1.8.2 62 | - **Gradio version**: 3.22.1 63 | - **Python version**: 3.11.1 64 | value: | 65 | - OS: 66 | - Server: 67 | - Gradio version: 68 | - Python version: 69 | validations: 70 | required: false 71 | - type: textarea 72 | attributes: 73 | label: 补充说明 74 | description: 链接？参考资料？任何更多背景信息！ -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/report-docker.yml: -------------------------------------------------------------------------------- 1 | name: Docker部署错误 2 | description: "报告使用 Docker 部署时的问题或错误" 3 | title: "[Docker]: " 4 | labels: ["question","docker deployment"] 5 | body: 6 | - type: markdown 7 | attributes: 8 | value: | 9 | 感谢提交 issue! 请尽可能完整填写以下信息，帮助我们更好地定位问题~ 10 | **在一切开始之前，请确保您已经阅读过 [常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题) 页面**，查看它是否已经对您的问题做出了解答。 11 | 如果没有，请检索 [issue](https://github.com/GaiZhenbiao/ChuanhuChatGPT/issues) 与 [discussion](https://github.com/GaiZhenbiao/ChuanhuChatGPT/discussions) ，查看有没有相同或类似的问题。 12 | 13 | ------ 14 | - type: checkboxes 15 | attributes: 16 | label: 是否已存在现有反馈与解答？ 17 | description: 请搜索issue、discussion和[常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题)以查看您想报告的issue是否已存在。 18 | options: 19 | - label: 我确认没有已有issue或discussion，且已阅读**常见问题**。 20 | required: true 21 | - type: checkboxes 22 | attributes: 23 | label: 是否是一个代理配置相关的疑问？ 24 | description: 请不要提交代理配置相关的issue。如有疑问请前往 [讨论区](https://github.com/GaiZhenbiao/ChuanhuChatGPT/discussions)。 25 | options: 26 | - label: 我确认这不是一个代理配置相关的疑问。 27 | required: true 28 | - type: textarea 29 | id: what-happened 30 | attributes: 31 | label: 错误描述 32 | description: 请描述您遇到的错误或问题。
33 | 提示：如果可以，也请提供错误的截图，如本地部署的网页截图与终端错误报告的截图。 34 | 如果可以，也请提供`.json`格式的对话记录。 35 | placeholder: 发生什么事了？ 36 | validations: 37 | required: true 38 | - type: textarea 39 | attributes: 40 | label: 复现操作 41 | description: 你之前干了什么，然后出现了错误呢？ 42 | placeholder: | 43 | 1. 正常完成本地部署 44 | 2. 选取GPT3.5-turbo模型，正确填写API 45 | 3. 在对话框中要求 ChatGPT “以LaTeX格式输出三角函数” 46 | 4. ChatGPT 输出部分内容后程序被自动终止 47 | validations: 48 | required: true 49 | - type: textarea 50 | id: logs 51 | attributes: 52 | label: 错误日志 53 | description: 请将终端中的主要错误报告粘贴至此处。 54 | render: shell 55 | - type: textarea 56 | attributes: 57 | label: 运行环境 58 | description: | 59 | 网页底部会列出您运行环境的版本信息，请务必填写。以下是一个例子： 60 | - **OS**: Linux/amd64 61 | - **Docker version**: 1.8.2 62 | - **Gradio version**: 3.22.1 63 | - **Python version**: 3.11.1 64 | value: | 65 | - OS: 66 | - Docker version: 67 | - Gradio version: 68 | - Python version: 69 | validations: 70 | required: false 71 | - type: textarea 72 | attributes: 73 | label: 补充说明 74 | description: 链接？参考资料？任何更多背景信息！ -------------------------------------------------------------------------------- /modules/webui_locale.py: -------------------------------------------------------------------------------- 1 | import os 2 | import locale 3 | import logging 4 | import commentjson as json 5 | 6 | class I18nAuto: 7 | def __init__(self): 8 | if os.path.exists("config.json"): 9 | with open("config.json", "r", encoding='utf-8') as f: 10 | config = json.load(f) 11 | else: 12 | config = {} 13 | language = config.get("language", "auto") 14 | language = os.environ.get("LANGUAGE", language) 15 | language = language.replace("-", "_") 16 | if language == "auto": 17 | language = locale.getdefaultlocale()[0] # get the language code of the system (ex. zh_CN) 18 | self.language = language 19 | self.language_map = {} 20 | self.file_is_exists = os.path.isfile(f"./locale/{language}.json") 21 | if self.file_is_exists: 22 | with open(f"./locale/{language}.json", "r", encoding="utf-8") as f: 23 | self.language_map.update(json.load(f)) 24 | else: 25 | logging.warning(f"Language file for {language} does not exist. Using English instead.") 26 | logging.warning(f"Available languages: {', '.join([x[:-5] for x in os.listdir('./locale')])}") 27 | with open(f"./locale/en_US.json", "r", encoding="utf-8") as f: 28 | self.language_map.update(json.load(f)) 29 | with open(f"./locale/en_US.json", "r", encoding="utf-8") as f: 30 | # fallback to English 31 | self.fallback_language_map = json.load(f) 32 | 33 | def change_language(self, language): 34 | language = language.replace("-", "_") 35 | self.language_map = {} 36 | self.file_is_exists = os.path.isfile(f"./locale/{language}.json") 37 | if self.file_is_exists: 38 | with open(f"./locale/{language}.json", "r", encoding="utf-8") as f: 39 | self.language_map.update(json.load(f)) 40 | else: 41 | logging.warning(f"Language file for {language} does not exist. Using English instead.") 42 | logging.warning(f"Available languages: {', '.join([x[:-5] for x in os.listdir('./locale')])}") 43 | with open(f"./locale/en_US.json", "r", encoding="utf-8") as f: 44 | self.language_map.update(json.load(f)) 45 | 46 | def __call__(self, key): 47 | if self.file_is_exists and key in self.language_map: 48 | return self.language_map[key] 49 | elif key in self.fallback_language_map and self.language != "zh_CN": 50 | return self.fallback_language_map[key] 51 | else: 52 | return key 53 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/report-localhost.yml: -------------------------------------------------------------------------------- 1 | name: 本地部署错误 2 | description: "报告本地部署时的问题或错误（小白首选）" 3 | title: "[本地部署]: " 4 | labels: ["question","localhost deployment"] 5 | body: 6 | - type: markdown 7 | attributes: 8 | value: | 9 | 感谢提交 issue! 请尽可能完整填写以下信息，帮助我们更好地定位问题~ 10 | **在一切开始之前，请确保您已经阅读过 [常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题) 页面**，查看它是否已经对您的问题做出了解答。 11 | 如果没有，请检索 [issue](https://github.com/GaiZhenbiao/ChuanhuChatGPT/issues) 与 [discussion](https://github.com/GaiZhenbiao/ChuanhuChatGPT/discussions) ，查看有没有相同或类似的问题。 12 | 13 | **另外，请不要再提交 `Something went wrong Expecting value: line 1 column 1 (char 0)` 和 代理配置 相关的问题，请再看一遍 [常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题) 页，实在不行请前往 discussion。** 14 | 15 | ------ 16 | - type: checkboxes 17 | attributes: 18 | label: 是否已存在现有反馈与解答？ 19 | description: 请搜索issue、discussion和[常见问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题)以查看您想报告的issue是否已存在。 20 | options: 21 | - label: 我确认没有已有issue或discussion，且已阅读**常见问题**。 22 | required: true 23 | - type: checkboxes 24 | attributes: 25 | label: 是否是一个代理配置相关的疑问？ 26 | description: 请不要提交代理配置相关的issue。如有疑问请前往 [讨论区](https://github.com/GaiZhenbiao/ChuanhuChatGPT/discussions)。 27 | options: 28 | - label: 我确认这不是一个代理配置相关的疑问。 29 | required: true 30 | - type: textarea 31 | id: what-happened 32 | attributes: 33 | label: 错误描述 34 | description: 请描述您遇到的错误或问题。
35 | 提示：如果可以，也请提供错误的截图，如本地部署的网页截图与终端错误报告的截图。 36 | 如果可以，也请提供`.json`格式的对话记录。 37 | placeholder: 发生什么事了？ 38 | validations: 39 | required: true 40 | - type: textarea 41 | attributes: 42 | label: 复现操作 43 | description: 你之前干了什么，然后出现了错误呢？ 44 | placeholder: | 45 | 1. 正常完成本地部署 46 | 2. 选取GPT3.5-turbo模型，正确填写API 47 | 3. 在对话框中要求 ChatGPT “以LaTeX格式输出三角函数” 48 | 4. ChatGPT 输出部分内容后程序被自动终止 49 | validations: 50 | required: true 51 | - type: textarea 52 | id: logs 53 | attributes: 54 | label: 错误日志 55 | description: 请将终端中的主要错误报告粘贴至此处。 56 | render: shell 57 | - type: textarea 58 | attributes: 59 | label: 运行环境 60 | description: | 61 | 网页底部会列出您运行环境的版本信息，请务必填写。以下是一个例子： 62 | - **OS**: Windows11 22H2 63 | - **Browser**: Chrome 64 | - **Gradio version**: 3.22.1 65 | - **Python version**: 3.11.1 66 | value: | 67 | - OS: 68 | - Browser: 69 | - Gradio version: 70 | - Python version: 71 | render: markdown 72 | validations: 73 | required: false 74 | - type: textarea 75 | attributes: 76 | label: 补充说明 77 | description: 链接？参考资料？任何更多背景信息！ -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | history/ 30 | index/ 31 | 32 | # PyInstaller 33 | # Usually these files are written by a python script from a template 34 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 35 | *.manifest 36 | *.spec 37 | 38 | # Installer logs 39 | pip-log.txt 40 | pip-delete-this-directory.txt 41 | 42 | # Unit test / coverage reports 43 | htmlcov/ 44 | .tox/ 45 | .nox/ 46 | .coverage 47 | .coverage.* 48 | .cache 49 | nosetests.xml 50 | coverage.xml 51 | *.cover 52 | *.py,cover 53 | .hypothesis/ 54 | .pytest_cache/ 55 | 56 | # Translations 57 | *.mo 58 | *.pot 59 | 60 | # Django stuff: 61 | *.log 62 | local_settings.py 63 | db.sqlite3 64 | db.sqlite3-journal 65 | 66 | # Flask stuff: 67 | instance/ 68 | .webassets-cache 69 | 70 | # Scrapy stuff: 71 | .scrapy 72 | 73 | # Sphinx documentation 74 | docs/_build/ 75 | 76 | # PyBuilder 77 | target/ 78 | 79 | # Jupyter Notebook 80 | .ipynb_checkpoints 81 | 82 | # IPython 83 | profile_default/ 84 | ipython_config.py 85 | 86 | # pyenv 87 | .python-version 88 | 89 | # pipenv 90 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 91 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 92 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 93 | # install all needed dependencies. 94 | #Pipfile.lock 95 | 96 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 97 | __pypackages__/ 98 | 99 | # Celery stuff 100 | celerybeat-schedule 101 | celerybeat.pid 102 | 103 | # SageMath parsed files 104 | *.sage.py 105 | 106 | # Environments 107 | .env 108 | .venv 109 | env/ 110 | venv/ 111 | ENV/ 112 | env.bak/ 113 | venv.bak/ 114 | 115 | # Spyder project settings 116 | .spyderproject 117 | .spyproject 118 | 119 | # Rope project settings 120 | .ropeproject 121 | 122 | # mkdocs documentation 123 | /site 124 | 125 | # mypy 126 | .mypy_cache/ 127 | .dmypy.json 128 | dmypy.json 129 | 130 | # Pyre type checker 131 | .pyre/ 132 | 133 | # Mac system file 134 | **/.DS_Store 135 | 136 | #vscode 137 | .vscode 138 | 139 | # 配置文件/模型文件 140 | api_key.txt 141 | config.json 142 | auth.json 143 | .models/ 144 | models/* 145 | lora/ 146 | .idea 147 | templates/* 148 | files/ 149 | tmp/ 150 | 151 | scripts/ 152 | include/ 153 | pyvenv.cfg 154 | 155 | create_release.sh 156 | -------------------------------------------------------------------------------- /modules/models/Qwen.py: -------------------------------------------------------------------------------- 1 | from transformers import AutoModelForCausalLM, AutoTokenizer 2 | import os 3 | from transformers.generation import GenerationConfig 4 | import logging 5 | import colorama 6 | from .base_model import BaseLLMModel 7 | from ..presets import MODEL_METADATA 8 | 9 | 10 | class Qwen_Client(BaseLLMModel): 11 | def __init__(self, model_name, user_name="") -> None: 12 | super().__init__(model_name=model_name, user=user_name) 13 | model_source = None 14 | if os.path.exists("models"): 15 | model_dirs = os.listdir("models") 16 | if model_name in model_dirs: 17 | model_source = f"models/{model_name}" 18 | if model_source is None: 19 | try: 20 | model_source = MODEL_METADATA[model_name]["repo_id"] 21 | except KeyError: 22 | model_source = model_name 23 | self.tokenizer = AutoTokenizer.from_pretrained(model_source, trust_remote_code=True, resume_download=True) 24 | self.model = AutoModelForCausalLM.from_pretrained(model_source, device_map="cuda", trust_remote_code=True, resume_download=True).eval() 25 | 26 | def generation_config(self): 27 | return GenerationConfig.from_dict({ 28 | "chat_format": "chatml", 29 | "do_sample": True, 30 | "eos_token_id": 151643, 31 | "max_length": self.token_upper_limit, 32 | "max_new_tokens": 512, 33 | "max_window_size": 6144, 34 | "pad_token_id": 151643, 35 | "top_k": 0, 36 | "top_p": self.top_p, 37 | "transformers_version": "4.33.2", 38 | "trust_remote_code": True, 39 | "temperature": self.temperature, 40 | }) 41 | 42 | def _get_glm_style_input(self): 43 | history = [x["content"] for x in self.history] 44 | query = history.pop() 45 | logging.debug(colorama.Fore.YELLOW + 46 | f"{history}" + colorama.Fore.RESET) 47 | assert ( 48 | len(history) % 2 == 0 49 | ), f"History should be even length. current history is: {history}" 50 | history = [[history[i], history[i + 1]] 51 | for i in range(0, len(history), 2)] 52 | return history, query 53 | 54 | def get_answer_at_once(self): 55 | history, query = self._get_glm_style_input() 56 | self.model.generation_config = self.generation_config() 57 | response, history = self.model.chat(self.tokenizer, query, history=history) 58 | return response, len(response) 59 | 60 | def get_answer_stream_iter(self): 61 | history, query = self._get_glm_style_input() 62 | self.model.generation_config = self.generation_config() 63 | for response in self.model.chat_stream( 64 | self.tokenizer, 65 | query, 66 | history, 67 | ): 68 | yield response 69 | -------------------------------------------------------------------------------- /modules/shared.py: -------------------------------------------------------------------------------- 1 | from modules.presets import CHAT_COMPLETION_URL, BALANCE_API_URL, USAGE_API_URL, API_HOST, OPENAI_API_BASE, IMAGES_COMPLETION_URL 2 | import os 3 | import queue 4 | import openai 5 | 6 | def format_openai_host(api_host: str): 7 | api_host = api_host.rstrip("/") 8 | if not api_host.startswith("http"): 9 | api_host = f"https://{api_host}" 10 | if api_host.endswith("/v1"): 11 | api_host = api_host[:-3] 12 | chat_completion_url = f"{api_host}/v1/chat/completions" 13 | images_completion_url = f"{api_host}/v1/images/generations" 14 | openai_api_base = f"{api_host}/v1" 15 | balance_api_url = f"{api_host}/dashboard/billing/credit_grants" 16 | usage_api_url = f"{api_host}/dashboard/billing/usage" 17 | return chat_completion_url, images_completion_url, openai_api_base, balance_api_url, usage_api_url 18 | 19 | class State: 20 | interrupted = False 21 | multi_api_key = False 22 | chat_completion_url = CHAT_COMPLETION_URL 23 | balance_api_url = BALANCE_API_URL 24 | usage_api_url = USAGE_API_URL 25 | openai_api_base = OPENAI_API_BASE 26 | images_completion_url = IMAGES_COMPLETION_URL 27 | api_host = API_HOST 28 | 29 | def interrupt(self): 30 | self.interrupted = True 31 | 32 | def recover(self): 33 | self.interrupted = False 34 | 35 | def set_api_host(self, api_host: str): 36 | self.api_host = api_host 37 | self.chat_completion_url, self.images_completion_url, self.openai_api_base, self.balance_api_url, self.usage_api_url = format_openai_host(api_host) 38 | os.environ["OPENAI_API_BASE"] = self.openai_api_base 39 | 40 | def reset_api_host(self): 41 | self.chat_completion_url = CHAT_COMPLETION_URL 42 | self.images_completion_url = IMAGES_COMPLETION_URL 43 | self.balance_api_url = BALANCE_API_URL 44 | self.usage_api_url = USAGE_API_URL 45 | self.api_host = API_HOST 46 | os.environ["OPENAI_API_BASE"] = f"https://{API_HOST}" 47 | return API_HOST 48 | 49 | def reset_all(self): 50 | self.interrupted = False 51 | self.chat_completion_url = CHAT_COMPLETION_URL 52 | 53 | def set_api_key_queue(self, api_key_list): 54 | self.multi_api_key = True 55 | self.api_key_queue = queue.Queue() 56 | for api_key in api_key_list: 57 | self.api_key_queue.put(api_key) 58 | 59 | def switching_api_key(self, func): 60 | if not hasattr(self, "api_key_queue"): 61 | return func 62 | 63 | def wrapped(*args, **kwargs): 64 | api_key = self.api_key_queue.get() 65 | args[0].api_key = api_key 66 | ret = func(*args, **kwargs) 67 | self.api_key_queue.put(api_key) 68 | return ret 69 | 70 | return wrapped 71 | 72 | 73 | state = State() 74 | 75 | modules_path = os.path.dirname(os.path.realpath(__file__)) 76 | chuanhu_path = os.path.dirname(modules_path) 77 | assets_path = os.path.join(chuanhu_path, "web_assets") -------------------------------------------------------------------------------- /locale/zh_CN.json: -------------------------------------------------------------------------------- 1 | { 2 | "gpt3.5turbo_description": "GPT-3.5 Turbo 是由 OpenAI 开发的一款仅限文本的大型语言模型。它基于 GPT-3 模型，并已经在大量数据上进行了微调。最新版本的 GPT-3.5 Turbo 进行了性能和精度优化，支持最大 16k tokens 的上下文窗口和最大 4096 tokens 的响应长度。此模型始终使用可用的最新版本的 GPT-3.5 Turbo。", 3 | "gpt3.5turbo_instruct_description": "GPT3.5 Turbo Instruct 是 OpenAI 开发的文本补全模型，具有与 GPT-3 时代模型相似的功能。它兼容旧版的 Completions 端点，但不兼容 Chat Completions。该模型的上下文窗口为 4096 个 tokens。", 4 | "gpt3.5turbo_16k_description": "旧版的 GPT-3.5 Turbo 模型，具有 16k tokens 的上下文窗口。", 5 | "gpt4_description": "GPT-4 是 OpenAI 开发的一款仅限文本的大型语言模型。它具有 8192 个 tokens 的上下文窗口和 4096 个 tokens 的最大响应长度。该模型始终使用可用的最新版本的 GPT-4。建议使用 GPT-4 Turbo 以获得更好的性能、更快的速度和更低的成本。", 6 | "gpt4_32k_description": "GPT-4 32K 是 OpenAI 开发的一个仅限文本的大型语言模型。它具有 32,000 tokens 的上下文窗口和 4,096 tokens 的最大响应长度。这个模型从未广泛推出,建议使用 GPT-4 Turbo。", 7 | "gpt4turbo_description": "GPT-4 Turbo 是由 OpenAI 开发的一款多模态大型语言模型。它在广泛的自然语言处理任务上提供最先进的性能，包括文本生成、翻译、摘要、视觉问题回答等。GPT-4 Turbo 拥有最大 128k tokens 的上下文窗口和最大 4096 tokens 的响应长度。此模型始终使用可用的最新版本的 GPT-4 Turbo。", 8 | "claude3_haiku_description": "Claude3 Haiku 是由 Anthropic 开发的一款多模态大型语言模型。它是 Claude 3 模型家族中最快、最紧凑的模型，旨在实现近乎即时的响应速度，但是性能不如 Sonnet 和 Opus。Claude3 Haiku 有最大 200k tokens 的上下文窗口和最大 4096 tokens 的响应长度。此模型始终使用可用的最新版本的 Claude3 Haiku。", 9 | "claude3_sonnet_description": "Claude3 Sonnet 是由 Anthropic 开发的一款多模态大型语言模型。它在智能与速度之间保持最佳平衡，适用于企业工作负载和大规模 AI 部署。Claude3 Sonnet 拥有最大 200k tokens 的上下文窗口和最大 4096 tokens 的响应长度。此模型始终使用可用的最新版本的 Claude3 Sonnet。", 10 | "claude3_opus_description": "Claude3 Opus 是由 Anthropic 开发的一款多模态大型语言模型。它是 Claude 3 模型家族中最智能、最大的模型，能够在高度复杂的任务上呈现最顶尖的性能，呈现出类似人类的理解能力。Claude3 Opus 拥有最大 200k tokens 的上下文窗口和最大 4096 tokens 的响应长度。此模型始终使用可用的最新版本的 Claude3 Opus。", 11 | "groq_llama3_8b_description": "采用 [Groq](https://console.groq.com/) 的 LLaMA 3 8B。Groq 是一个非常快速的语言模型推理服务。", 12 | "groq_llama3_70b_description": "采用 [Groq](https://console.groq.com/) 的 LLaMA 3 70B。Groq 是一个非常快速的语言模型推理服务。", 13 | "groq_mixtral_8x7b_description": "采用 [Groq](https://console.groq.com/) 的 Mixtral 8x7B。Groq 是一个非常快速的语言模型推理服务。", 14 | "groq_gemma_7b_description": "采用 [Groq](https://console.groq.com/) 的 Gemma 7B。Groq 是一个非常快速的语言模型推理服务。", 15 | "chuanhu_description": "一个能使用多种工具解决复杂问题的智能体。", 16 | "gpt_default_slogan": "今天能帮您些什么？", 17 | "claude_default_slogan": "我能帮您什么忙？", 18 | "chuanhu_slogan": "川虎今天能帮你做些什么？", 19 | "chuanhu_question_1": "今天杭州天气如何？", 20 | "chuanhu_question_2": "最近 Apple 发布了什么新品？", 21 | "chuanhu_question_3": "现在显卡的价格如何？", 22 | "chuanhu_question_4": "TikTok 上有什么新梗？", 23 | "gpt4o_description": "OpenAI 的最先进的多模态旗舰模型，比 GPT-4 Turbo 更便宜、更快。", 24 | "gpt4omini_description": "OpenAI 的经济实惠且智能的小型模型，适用于快速、轻量级任务。", 25 | "gpt5_description": "跨领域编码与智能体任务的最佳模型。支持 400,000 token 上下文，单次可输出至多 128,000 token。", 26 | "gpt5mini_description": "面向明确任务的更快、更具性价比的 GPT-5 版本。支持 400,000 token 上下文，单次可输出至多 128,000 token。", 27 | "gpt5nano_description": "速度最快、性价比最高的 GPT-5 版本。支持 400,000 token 上下文，单次可输出至多 128,000 token。", 28 | "o1_description": "o1 系列的大型语言模型通过强化学习训练，能够执行复杂的推理任务。o1 模型在回答之前会进行思考，产生一长串内部思维链，然后再回应用户。", 29 | "no_permission_to_update_description": "你没有权限更新。请联系管理员。管理员的配置方式为在配置文件 config.json 中的 admin_list 中添加用户名。" 30 | } -------------------------------------------------------------------------------- /modules/models/DALLE3.py: -------------------------------------------------------------------------------- 1 | import logging 2 | from .base_model import BaseLLMModel 3 | from .. import shared 4 | import requests 5 | from ..presets import * 6 | from ..config import retrieve_proxy, sensitive_id 7 | 8 | class OpenAI_DALLE3_Client(BaseLLMModel): 9 | def __init__(self, model_name, api_key, user_name="") -> None: 10 | super().__init__(model_name=model_name, user=user_name, config={"api_key": api_key}) 11 | if self.api_host is not None: 12 | self.chat_completion_url, self.images_completion_url, self.openai_api_base, self.balance_api_url, self.usage_api_url = shared.format_openai_host(self.api_host) 13 | else: 14 | self.api_host, self.chat_completion_url, self.images_completion_url, self.openai_api_base, self.balance_api_url, self.usage_api_url = shared.state.api_host, shared.state.chat_completion_url, shared.state.images_completion_url, shared.state.openai_api_base, shared.state.balance_api_url, shared.state.usage_api_url 15 | self._refresh_header() 16 | 17 | def _get_dalle3_prompt(self): 18 | prompt = self.history[-1]["content"] 19 | if prompt.endswith("--raw"): 20 | prompt = "I NEED to test how the tool works with extremely simple prompts. DO NOT add any detail, just use it AS-IS:" + prompt 21 | return prompt 22 | 23 | def get_answer_at_once(self, stream=False): 24 | prompt = self._get_dalle3_prompt() 25 | headers = { 26 | "Content-Type": "application/json", 27 | "Authorization": f"Bearer {self.api_key}" 28 | } 29 | payload = { 30 | "model": self.model_name, 31 | "prompt": prompt, 32 | "n": 1, 33 | "size": "1024x1024", 34 | "quality": "standard", 35 | } 36 | if stream: 37 | timeout = TIMEOUT_STREAMING 38 | else: 39 | timeout = TIMEOUT_ALL 40 | 41 | if self.images_completion_url != IMAGES_COMPLETION_URL: 42 | logging.debug(f"使用自定义API URL: {self.images_completion_url}") 43 | 44 | with retrieve_proxy(): 45 | try: 46 | response = requests.post( 47 | self.images_completion_url, 48 | headers=headers, 49 | json=payload, 50 | stream=stream, 51 | timeout=timeout, 52 | ) 53 | response.raise_for_status() # 根据HTTP状态码引发异常 54 | response_data = response.json() 55 | image_url = response_data['data'][0]['url'] 56 | img_tag = f'' 57 | revised_prompt = response_data['data'][0].get('revised_prompt', '') 58 | return img_tag + revised_prompt, 0 59 | except requests.exceptions.RequestException as e: 60 | return str(e), 0 61 | 62 | def _refresh_header(self): 63 | self.headers = { 64 | "Content-Type": "application/json", 65 | "Authorization": f"Bearer {sensitive_id}", 66 | } -------------------------------------------------------------------------------- /modules/models/LLaMA.py: -------------------------------------------------------------------------------- 1 | from __future__ import annotations 2 | 3 | import json 4 | import os 5 | from llama_cpp import Llama 6 | 7 | from ..index_func import * 8 | from ..presets import * 9 | from ..utils import * 10 | from .base_model import BaseLLMModel, download 11 | 12 | SYS_PREFIX = "<>\n" 13 | SYS_POSTFIX = "\n<>\n\n" 14 | INST_PREFIX = "[INST] " 15 | INST_POSTFIX = " " 16 | OUTPUT_PREFIX = "[/INST] " 17 | OUTPUT_POSTFIX = "" 18 | 19 | 20 | class LLaMA_Client(BaseLLMModel): 21 | def __init__(self, model_name, lora_path=None, user_name="") -> None: 22 | super().__init__(model_name=model_name, user=user_name) 23 | 24 | self.max_generation_token = 1000 25 | if model_name in MODEL_METADATA: 26 | path_to_model = download( 27 | MODEL_METADATA[model_name]["repo_id"], 28 | MODEL_METADATA[model_name]["filelist"][0], 29 | ) 30 | else: 31 | dir_to_model = os.path.join("models", model_name) 32 | # look for nay .gguf file in the dir_to_model directory and its subdirectories 33 | path_to_model = None 34 | for root, dirs, files in os.walk(dir_to_model): 35 | for file in files: 36 | if file.endswith(".gguf"): 37 | path_to_model = os.path.join(root, file) 38 | break 39 | if path_to_model is not None: 40 | break 41 | self.system_prompt = "" 42 | 43 | if lora_path is not None: 44 | lora_path = os.path.join("lora", lora_path) 45 | self.model = Llama(model_path=path_to_model, lora_path=lora_path) 46 | else: 47 | self.model = Llama(model_path=path_to_model) 48 | 49 | def _get_llama_style_input(self): 50 | context = [] 51 | for conv in self.history: 52 | if conv["role"] == "system": 53 | context.append(SYS_PREFIX + conv["content"] + SYS_POSTFIX) 54 | elif conv["role"] == "user": 55 | context.append( 56 | INST_PREFIX + conv["content"] + INST_POSTFIX + OUTPUT_PREFIX 57 | ) 58 | else: 59 | context.append(conv["content"] + OUTPUT_POSTFIX) 60 | return "".join(context) 61 | # for conv in self.history: 62 | # if conv["role"] == "system": 63 | # context.append(conv["content"]) 64 | # elif conv["role"] == "user": 65 | # context.append( 66 | # conv["content"] 67 | # ) 68 | # else: 69 | # context.append(conv["content"]) 70 | # return "\n\n".join(context)+"\n\n" 71 | 72 | def get_answer_at_once(self): 73 | context = self._get_llama_style_input() 74 | response = self.model( 75 | context, 76 | max_tokens=self.max_generation_token, 77 | stop=[], 78 | echo=False, 79 | stream=False, 80 | ) 81 | return response, len(response) 82 | 83 | def get_answer_stream_iter(self): 84 | context = self._get_llama_style_input() 85 | iter = self.model( 86 | context, 87 | max_tokens=self.max_generation_token, 88 | stop=[SYS_PREFIX, SYS_POSTFIX, INST_PREFIX, OUTPUT_PREFIX, OUTPUT_POSTFIX], 89 | echo=False, 90 | stream=True, 91 | ) 92 | partial_text = "" 93 | for i in iter: 94 | response = i["choices"][0]["text"] 95 | partial_text += response 96 | yield partial_text 97 | -------------------------------------------------------------------------------- /modules/models/ERNIE.py: -------------------------------------------------------------------------------- 1 | from ..presets import * 2 | from ..utils import * 3 | 4 | from .base_model import BaseLLMModel 5 | 6 | 7 | class ERNIE_Client(BaseLLMModel): 8 | def __init__(self, model_name, api_key, secret_key) -> None: 9 | super().__init__(model_name=model_name) 10 | self.api_key = api_key 11 | self.api_secret = secret_key 12 | if None in [self.api_secret, self.api_key]: 13 | raise Exception("请在配置文件或者环境变量中设置文心一言的API Key 和 Secret Key") 14 | 15 | if self.model_name == "ERNIE-Bot-turbo": 16 | self.ERNIE_url = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/eb-instant?access_token=" 17 | elif self.model_name == "ERNIE-Bot": 18 | self.ERNIE_url = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions?access_token=" 19 | elif self.model_name == "ERNIE-Bot-4": 20 | self.ERNIE_url = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro?access_token=" 21 | 22 | def get_access_token(self): 23 | """ 24 | 使用 AK，SK 生成鉴权签名（Access Token） 25 | :return: access_token，或是None(如果错误) 26 | """ 27 | url = "https://aip.baidubce.com/oauth/2.0/token?client_id=" + self.api_key + "&client_secret=" + self.api_secret + "&grant_type=client_credentials" 28 | 29 | payload = json.dumps("") 30 | headers = { 31 | 'Content-Type': 'application/json', 32 | 'Accept': 'application/json' 33 | } 34 | 35 | response = requests.request("POST", url, headers=headers, data=payload) 36 | 37 | return response.json()["access_token"] 38 | def get_answer_stream_iter(self): 39 | url = self.ERNIE_url + self.get_access_token() 40 | system_prompt = self.system_prompt 41 | history = self.history 42 | if system_prompt is not None: 43 | history = [construct_system(system_prompt), *history] 44 | 45 | # 去除history中 history的role为system的 46 | history = [i for i in history if i["role"] != "system"] 47 | 48 | payload = json.dumps({ 49 | "messages":history, 50 | "stream": True 51 | }) 52 | headers = { 53 | 'Content-Type': 'application/json' 54 | } 55 | 56 | response = requests.request("POST", url, headers=headers, data=payload, stream=True) 57 | 58 | if response.status_code == 200: 59 | partial_text = "" 60 | for line in response.iter_lines(): 61 | if len(line) == 0: 62 | continue 63 | line = json.loads(line[5:]) 64 | partial_text += line['result'] 65 | yield partial_text 66 | else: 67 | yield STANDARD_ERROR_MSG + GENERAL_ERROR_MSG 68 | 69 | 70 | def get_answer_at_once(self): 71 | url = self.ERNIE_url + self.get_access_token() 72 | system_prompt = self.system_prompt 73 | history = self.history 74 | if system_prompt is not None: 75 | history = [construct_system(system_prompt), *history] 76 | 77 | # 去除history中 history的role为system的 78 | history = [i for i in history if i["role"] != "system"] 79 | 80 | payload = json.dumps({ 81 | "messages": history, 82 | "stream": True 83 | }) 84 | headers = { 85 | 'Content-Type': 'application/json' 86 | } 87 | 88 | response = requests.request("POST", url, headers=headers, data=payload, stream=True) 89 | 90 | if response.status_code == 200: 91 | 92 | return str(response.json()["result"]),len(response.json()["result"]) 93 | else: 94 | return "获取资源错误", 0 95 | 96 | 97 | -------------------------------------------------------------------------------- /web_assets/stylesheet/markdown.css: -------------------------------------------------------------------------------- 1 | 2 | /* list from gradio 4.26, recover what silly gradio has done*/ 3 | .message { 4 | 5 | --chatbot-body-text-size: 14px; /* gradio set 16px in v4.29 */ 6 | 7 | .prose ul { 8 | list-style-position: outside !important; 9 | list-style-type: disc; 10 | } 11 | .prose ol { 12 | list-style-position: outside !important; 13 | } 14 | .prose ul ul, 15 | .prose ol ul, 16 | .prose ul ol ul, 17 | .prose ol ol ul { 18 | list-style-type: circle; 19 | } 20 | .prose ul > p, 21 | .prose li > p { 22 | display: initial; 23 | } 24 | .prose ol, 25 | .prose ul { 26 | margin-top: unset; 27 | } 28 | .prose ul ul, 29 | .prose ul ol, 30 | .prose ol ol, 31 | .prose ol ul { 32 | margin: initial; 33 | font-size: inherit; 34 | } 35 | .prose li { 36 | margin-bottom: initial; 37 | } 38 | } 39 | 40 | 41 | /* 表格 */ 42 | .message table { 43 | margin: 1em 0; 44 | border-collapse: collapse; 45 | empty-cells: show; 46 | } 47 | .message td, .message th { 48 | border: 1.2px solid var(--border-color-primary) !important; 49 | padding: 0.2em; 50 | } 51 | .message thead { 52 | background-color: rgba(175,184,193,0.2); 53 | } 54 | .message thead th { 55 | padding: .5em .2em; 56 | } 57 | 58 | /* 行内代码 */ 59 | .message :not(pre) > code { 60 | display: inline; 61 | white-space: break-spaces; 62 | font-family: var(--font-mono) !important; 63 | border-radius: 6px !important; 64 | margin: 0 2px 0 2px; 65 | padding: .1em .4em .08em .4em !important; 66 | background-color: rgba(175,184,193,0.2) !important; 67 | border: none !important; 68 | font-size: var(--text-md) !important; 69 | } 70 | /* 代码块 */ 71 | .message pre, 72 | .message pre[class*=language-] { 73 | color: #fff; 74 | overflow-x: auto; 75 | overflow-y: hidden; 76 | padding: var(--spacing-xl) 1.2em !important; 77 | border-radius: var(--radius-lg) !important; 78 | background: var(--neutral-950) !important; 79 | } 80 | .message pre code, 81 | .message pre code[class*=language-] { 82 | color: #fff; 83 | padding: 0; 84 | margin: 0; 85 | background-color: unset; 86 | text-shadow: none; 87 | font-family: var(--font-mono); 88 | font-size: var(--text-md); 89 | } 90 | .message .code_wrap { 91 | margin: .8em 1em 1em 0em; 92 | } 93 | 94 | /* 覆盖prism.css */ 95 | .language-css .token.string, 96 | .style .token.string, 97 | .token.entity, 98 | .token.operator, 99 | .token.url { 100 | background: none !important; 101 | } 102 | 103 | /* 避免采用亮色背景的高亮样式 */ 104 | .md .token.comment, 105 | .md .token.prolog, 106 | .md .token.cdata { 107 | color: #5c6370 !important; 108 | } 109 | 110 | .md .token.doctype, 111 | .md .token.punctuation, 112 | .md .token.entity { 113 | color: #abb2bf !important; 114 | } 115 | 116 | .md .token.attr-name, 117 | .md .token.class-name, 118 | .md .token.boolean, 119 | .md .token.constant, 120 | .md .token.number, 121 | .md .token.atrule { 122 | color: #d19a66 !important; 123 | } 124 | 125 | .md .token.keyword { 126 | color: #c678dd !important; 127 | } 128 | 129 | .md .token.property, 130 | .md .token.tag, 131 | .md .token.symbol, 132 | .md .token.deleted, 133 | .md .token.important { 134 | color: #e06c75 !important; 135 | } 136 | 137 | .md .token.selector, 138 | .md .token.string, 139 | .md .token.char, 140 | .md .token.builtin, 141 | .md .token.inserted, 142 | .md .token.regex, 143 | .md .token.attr-value, 144 | .md .token.attr-value > .token.punctuation { 145 | color: #98c379 !important; 146 | } 147 | 148 | .md .token.variable, 149 | .md .token.operator, 150 | .md .token.function { 151 | color: #61afef !important; 152 | } 153 | 154 | .md .token.url { 155 | color: #56b6c2 !important; 156 | } 157 | 158 | -------------------------------------------------------------------------------- /web_assets/javascript/chat-history.js: -------------------------------------------------------------------------------- 1 | 2 | var historyLoaded = false; 3 | var loadhistorytime = 0; // for debugging 4 | 5 | 6 | function saveHistoryHtml() { 7 | var historyHtml = document.querySelector('#chuanhu-chatbot > .wrapper > .bubble-wrap'); 8 | if (!historyHtml) return; // no history, do nothing 9 | localStorage.setItem('chatHistory', historyHtml.innerHTML); 10 | // console.log("History Saved") 11 | historyLoaded = false; 12 | } 13 | 14 | function loadHistoryHtml() { 15 | var historyHtml = localStorage.getItem('chatHistory'); 16 | const tempDiv = document.createElement('div'); 17 | tempDiv.innerHTML = historyHtml; 18 | if (!historyHtml || tempDiv.innerText.trim() === "") { 19 | historyLoaded = true; 20 | return; // no history, do nothing 21 | } 22 | userLogged = localStorage.getItem('userLogged'); 23 | hideHistoryWhenNotLoggedIn = gradioApp().querySelector('#hideHistoryWhenNotLoggedIn_config').innerText === "True"; 24 | 25 | // 取消该功能 26 | historyLoaded = true; 27 | return; 28 | 29 | // if (userLogged || (!userLogged && !hideHistoryWhenNotLoggedIn)){ 30 | // historyLoaded = true; 31 | // return; // logged in, do nothing. OR, not logged in but not hide history list, do nothing. 32 | // } 33 | 34 | // 只有用户未登录，还隐藏历史记录列表时，才选用只读历史记录 35 | if (!historyLoaded) { 36 | // preprocess, gradio buttons in history lost their event listeners 37 | var gradioCopyButtons = tempDiv.querySelectorAll('button.copy_code_button'); 38 | for (var i = 0; i < gradioCopyButtons.length; i++) { 39 | gradioCopyButtons[i].parentNode.removeChild(gradioCopyButtons[i]); 40 | } 41 | var messageBtnRows = tempDiv.querySelectorAll('.message-btn-row'); 42 | for (var i = 0; i < messageBtnRows.length; i++) { 43 | messageBtnRows[i].parentNode.removeChild(messageBtnRows[i]); 44 | } 45 | var latestMessages = tempDiv.querySelectorAll('.message.latest'); 46 | for (var i = 0; i < latestMessages.length; i++) { 47 | latestMessages[i].classList.remove('latest'); 48 | } 49 | var chatbotPlaceHolder = tempDiv.querySelector('center'); 50 | if (chatbotPlaceHolder) { 51 | chatbotPlaceHolder.parentNode.removeChild(chatbotPlaceHolder); 52 | console.log("Chatbot PlaceHolder Removed"); 53 | } 54 | 55 | var fakeHistory = document.createElement('div'); 56 | fakeHistory.classList.add('history-message'); 57 | fakeHistory.innerHTML = tempDiv.innerHTML; 58 | const forViewStyle = document.createElement('style'); 59 | forViewStyle.innerHTML = '.wrapper > .bubble-wrap > .history-message > :last-child::after { content: "' + i18n(forView_i18n) + '"!important; }'; 60 | document.head.appendChild(forViewStyle); 61 | chatbotWrap.insertBefore(fakeHistory, chatbotWrap.firstChild); 62 | 63 | var activeChatbotPlaceHolder = document.querySelector('#chuanhu-chatbot > .wrapper > .bubble-wrap center'); 64 | if (activeChatbotPlaceHolder) { 65 | activeChatbotPlaceHolder.style.display = 'none'; 66 | } 67 | // var fakeHistory = document.createElement('div'); 68 | // fakeHistory.classList.add('history-message'); 69 | // fakeHistory.innerHTML = historyHtml; 70 | // chatbotWrap.insertBefore(fakeHistory, chatbotWrap.firstChild); 71 | historyLoaded = true; 72 | // console.log("History Loaded"); 73 | loadhistorytime += 1; // for debugging 74 | } else { 75 | historyLoaded = false; 76 | } 77 | } 78 | 79 | function clearHistoryHtml() { 80 | localStorage.removeItem("chatHistory"); 81 | historyMessages = chatbotWrap.querySelector('.history-message'); 82 | if (historyMessages) { 83 | chatbotWrap.removeChild(historyMessages); 84 | console.log("History Cleared"); 85 | 86 | var activeChatbotPlaceHolder = document.querySelector('#chuanhu-chatbot > .wrapper > .bubble-wrap center'); 87 | if (activeChatbotPlaceHolder) { 88 | activeChatbotPlaceHolder.style.display = 'block'; 89 | } 90 | } 91 | } 92 | -------------------------------------------------------------------------------- /modules/webui.py: -------------------------------------------------------------------------------- 1 | 2 | from collections import namedtuple 3 | import os 4 | import gradio as gr 5 | 6 | from . import shared 7 | 8 | # with open("./assets/ChuanhuChat.js", "r", encoding="utf-8") as f, \ 9 | # open("./assets/external-scripts.js", "r", encoding="utf-8") as f1: 10 | # customJS = f.read() 11 | # externalScripts = f1.read() 12 | 13 | 14 | def get_html(filename): 15 | path = os.path.join(shared.chuanhu_path, "web_assets", "html", filename) 16 | if os.path.exists(path): 17 | with open(path, encoding="utf8") as file: 18 | return file.read() 19 | return "" 20 | 21 | def webpath(fn): 22 | if fn.startswith(shared.assets_path): 23 | web_path = os.path.relpath(fn, shared.chuanhu_path).replace('\\', '/') 24 | else: 25 | web_path = os.path.abspath(fn) 26 | return f'file={web_path}?{os.path.getmtime(fn)}' 27 | 28 | ScriptFile = namedtuple("ScriptFile", ["basedir", "filename", "path"]) 29 | 30 | def javascript_html(): 31 | head = "" 32 | for script in list_scripts("javascript", ".js"): 33 | head += f'\n' 34 | for script in list_scripts("javascript", ".mjs"): 35 | head += f'\n' 36 | return head 37 | 38 | def css_html(): 39 | head = "" 40 | for cssfile in list_scripts("stylesheet", ".css"): 41 | head += f'' 42 | return head 43 | 44 | def list_scripts(scriptdirname, extension): 45 | scripts_list = [] 46 | scripts_dir = os.path.join(shared.chuanhu_path, "web_assets", scriptdirname) 47 | if os.path.exists(scripts_dir): 48 | for filename in sorted(os.listdir(scripts_dir)): 49 | scripts_list.append(ScriptFile(shared.assets_path, filename, os.path.join(scripts_dir, filename))) 50 | scripts_list = [x for x in scripts_list if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)] 51 | return scripts_list 52 | 53 | 54 | def reload_javascript(): 55 | js = javascript_html() 56 | js += '' 57 | js += '' 58 | js += '' 59 | 60 | meta = """ 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | """ 73 | css = css_html() 74 | 75 | def template_response(*args, **kwargs): 76 | res = GradioTemplateResponseOriginal(*args, **kwargs) 77 | res.body = res.body.replace(b'', f'{meta}{js}'.encode("utf8")) 78 | # res.body = res.body.replace(b'', f'{js}'.encode("utf8")) 79 | res.body = res.body.replace(b'', f'{css}'.encode("utf8")) 80 | res.init_headers() 81 | return res 82 | 83 | gr.routes.templates.TemplateResponse = template_response 84 | 85 | GradioTemplateResponseOriginal = gr.routes.templates.TemplateResponse -------------------------------------------------------------------------------- /modules/models/ChatGLM.py: -------------------------------------------------------------------------------- 1 | from __future__ import annotations 2 | 3 | import logging 4 | import os 5 | import platform 6 | 7 | import gc 8 | import torch 9 | import colorama 10 | 11 | from ..index_func import * 12 | from ..presets import * 13 | from ..utils import * 14 | from .base_model import BaseLLMModel 15 | 16 | 17 | class ChatGLM_Client(BaseLLMModel): 18 | def __init__(self, model_name, user_name="") -> None: 19 | super().__init__(model_name=model_name, user=user_name) 20 | import torch 21 | from transformers import AutoModel, AutoTokenizer 22 | global CHATGLM_TOKENIZER, CHATGLM_MODEL 23 | self.deinitialize() 24 | if CHATGLM_TOKENIZER is None or CHATGLM_MODEL is None: 25 | system_name = platform.system() 26 | model_path = None 27 | if os.path.exists("models"): 28 | model_dirs = os.listdir("models") 29 | if model_name in model_dirs: 30 | model_path = f"models/{model_name}" 31 | if model_path is not None: 32 | model_source = model_path 33 | else: 34 | model_source = f"THUDM/{model_name}" 35 | CHATGLM_TOKENIZER = AutoTokenizer.from_pretrained( 36 | model_source, trust_remote_code=True 37 | ) 38 | quantified = False 39 | if "int4" in model_name: 40 | quantified = True 41 | model = AutoModel.from_pretrained( 42 | model_source, trust_remote_code=True 43 | ) 44 | if torch.cuda.is_available(): 45 | # run on CUDA 46 | logging.info("CUDA is available, using CUDA") 47 | model = model.half().cuda() 48 | # mps加速还存在一些问题，暂时不使用 49 | elif system_name == "Darwin" and model_path is not None and not quantified: 50 | logging.info("Running on macOS, using MPS") 51 | # running on macOS and model already downloaded 52 | model = model.half().to("mps") 53 | else: 54 | logging.info("GPU is not available, using CPU") 55 | model = model.float() 56 | model = model.eval() 57 | CHATGLM_MODEL = model 58 | 59 | def _get_glm3_style_input(self): 60 | history = self.history 61 | query = history.pop()["content"] 62 | return history, query 63 | 64 | def _get_glm2_style_input(self): 65 | history = [x["content"] for x in self.history] 66 | query = history.pop() 67 | logging.debug(colorama.Fore.YELLOW + 68 | f"{history}" + colorama.Fore.RESET) 69 | assert ( 70 | len(history) % 2 == 0 71 | ), f"History should be even length. current history is: {history}" 72 | history = [[history[i], history[i + 1]] 73 | for i in range(0, len(history), 2)] 74 | return history, query 75 | 76 | def _get_glm_style_input(self): 77 | if "glm2" in self.model_name: 78 | return self._get_glm2_style_input() 79 | else: 80 | return self._get_glm3_style_input() 81 | 82 | def get_answer_at_once(self): 83 | history, query = self._get_glm_style_input() 84 | response, _ = CHATGLM_MODEL.chat( 85 | CHATGLM_TOKENIZER, query, history=history) 86 | return response, len(response) 87 | 88 | def get_answer_stream_iter(self): 89 | history, query = self._get_glm_style_input() 90 | for response, history in CHATGLM_MODEL.stream_chat( 91 | CHATGLM_TOKENIZER, 92 | query, 93 | history, 94 | max_length=self.token_upper_limit, 95 | top_p=self.top_p, 96 | temperature=self.temperature, 97 | ): 98 | yield response 99 | 100 | def deinitialize(self): 101 | # 释放显存 102 | global CHATGLM_MODEL, CHATGLM_TOKENIZER 103 | CHATGLM_MODEL = None 104 | CHATGLM_TOKENIZER = None 105 | gc.collect() 106 | torch.cuda.empty_cache() 107 | logging.info("ChatGLM model deinitialized") 108 | -------------------------------------------------------------------------------- /modules/models/GoogleGemma.py: -------------------------------------------------------------------------------- 1 | import logging 2 | from threading import Thread 3 | 4 | import torch 5 | from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer 6 | 7 | from ..presets import * 8 | from .base_model import BaseLLMModel 9 | 10 | 11 | class GoogleGemmaClient(BaseLLMModel): 12 | def __init__(self, model_name, api_key, user_name="") -> None: 13 | super().__init__(model_name=model_name, user=user_name) 14 | 15 | global GEMMA_TOKENIZER, GEMMA_MODEL 16 | # self.deinitialize() 17 | self.default_max_generation_token = self.token_upper_limit 18 | self.max_generation_token = self.token_upper_limit 19 | if GEMMA_TOKENIZER is None or GEMMA_MODEL is None: 20 | model_path = None 21 | if os.path.exists("models"): 22 | model_dirs = os.listdir("models") 23 | if model_name in model_dirs: 24 | model_path = f"models/{model_name}" 25 | if model_path is not None: 26 | model_source = model_path 27 | else: 28 | if os.path.exists( 29 | os.path.join("models", MODEL_METADATA[model_name]["model_name"]) 30 | ): 31 | model_source = os.path.join( 32 | "models", MODEL_METADATA[model_name]["model_name"] 33 | ) 34 | else: 35 | try: 36 | model_source = MODEL_METADATA[model_name]["repo_id"] 37 | except: 38 | model_source = model_name 39 | dtype = torch.bfloat16 40 | GEMMA_TOKENIZER = AutoTokenizer.from_pretrained( 41 | model_source, use_auth_token=os.environ["HF_AUTH_TOKEN"] 42 | ) 43 | GEMMA_MODEL = AutoModelForCausalLM.from_pretrained( 44 | model_source, 45 | device_map="auto", 46 | torch_dtype=dtype, 47 | trust_remote_code=True, 48 | resume_download=True, 49 | use_auth_token=os.environ["HF_AUTH_TOKEN"], 50 | ) 51 | 52 | def deinitialize(self): 53 | global GEMMA_TOKENIZER, GEMMA_MODEL 54 | GEMMA_TOKENIZER = None 55 | GEMMA_MODEL = None 56 | self.clear_cuda_cache() 57 | logging.info("GEMMA deinitialized") 58 | 59 | def _get_gemma_style_input(self): 60 | global GEMMA_TOKENIZER 61 | # messages = [{"role": "system", "content": self.system_prompt}, *self.history] # system prompt is not supported 62 | messages = self.history 63 | prompt = GEMMA_TOKENIZER.apply_chat_template( 64 | messages, tokenize=False, add_generation_prompt=True 65 | ) 66 | inputs = GEMMA_TOKENIZER.encode( 67 | prompt, add_special_tokens=True, return_tensors="pt" 68 | ) 69 | return inputs 70 | 71 | def get_answer_at_once(self): 72 | global GEMMA_TOKENIZER, GEMMA_MODEL 73 | inputs = self._get_gemma_style_input() 74 | outputs = GEMMA_MODEL.generate( 75 | input_ids=inputs.to(GEMMA_MODEL.device), 76 | max_new_tokens=self.max_generation_token, 77 | ) 78 | generated_token_count = outputs.shape[1] - inputs.shape[1] 79 | outputs = GEMMA_TOKENIZER.decode(outputs[0], skip_special_tokens=True) 80 | outputs = outputs.split("model\n")[-1][:-5] 81 | self.clear_cuda_cache() 82 | return outputs, generated_token_count 83 | 84 | def get_answer_stream_iter(self): 85 | global GEMMA_TOKENIZER, GEMMA_MODEL 86 | inputs = self._get_gemma_style_input() 87 | streamer = TextIteratorStreamer( 88 | GEMMA_TOKENIZER, timeout=10.0, skip_prompt=True, skip_special_tokens=True 89 | ) 90 | input_kwargs = dict( 91 | input_ids=inputs.to(GEMMA_MODEL.device), 92 | max_new_tokens=self.max_generation_token, 93 | streamer=streamer, 94 | ) 95 | t = Thread(target=GEMMA_MODEL.generate, kwargs=input_kwargs) 96 | t.start() 97 | 98 | partial_text = "" 99 | for new_text in streamer: 100 | partial_text += new_text 101 | yield partial_text 102 | self.clear_cuda_cache() 103 | -------------------------------------------------------------------------------- /modules/models/StableLM.py: -------------------------------------------------------------------------------- 1 | import torch 2 | from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, StoppingCriteria, StoppingCriteriaList, TextIteratorStreamer 3 | import time 4 | import numpy as np 5 | from torch.nn import functional as F 6 | import os 7 | from .base_model import BaseLLMModel 8 | from threading import Thread 9 | 10 | STABLELM_MODEL = None 11 | STABLELM_TOKENIZER = None 12 | 13 | 14 | class StopOnTokens(StoppingCriteria): 15 | def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs) -> bool: 16 | stop_ids = [50278, 50279, 50277, 1, 0] 17 | for stop_id in stop_ids: 18 | if input_ids[0][-1] == stop_id: 19 | return True 20 | return False 21 | 22 | 23 | class StableLM_Client(BaseLLMModel): 24 | def __init__(self, model_name, user_name="") -> None: 25 | super().__init__(model_name=model_name, user=user_name) 26 | global STABLELM_MODEL, STABLELM_TOKENIZER 27 | print(f"Starting to load StableLM to memory") 28 | if model_name == "StableLM": 29 | model_name = "stabilityai/stablelm-tuned-alpha-7b" 30 | else: 31 | model_name = f"models/{model_name}" 32 | if STABLELM_MODEL is None: 33 | STABLELM_MODEL = AutoModelForCausalLM.from_pretrained( 34 | model_name, torch_dtype=torch.float16).cuda() 35 | if STABLELM_TOKENIZER is None: 36 | STABLELM_TOKENIZER = AutoTokenizer.from_pretrained(model_name) 37 | self.generator = pipeline( 38 | 'text-generation', model=STABLELM_MODEL, tokenizer=STABLELM_TOKENIZER, device=0) 39 | print(f"Sucessfully loaded StableLM to the memory") 40 | self.system_prompt = """StableAssistant 41 | - StableAssistant is A helpful and harmless Open Source AI Language Model developed by Stability and CarperAI. 42 | - StableAssistant is excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user. 43 | - StableAssistant is more than just an information source, StableAssistant is also able to write poetry, short stories, and make jokes. 44 | - StableAssistant will refuse to participate in anything that could harm a human.""" 45 | self.max_generation_token = 1024 46 | self.top_p = 0.95 47 | self.temperature = 1.0 48 | 49 | def _get_stablelm_style_input(self): 50 | history = self.history + [{"role": "assistant", "content": ""}] 51 | print(history) 52 | messages = self.system_prompt + \ 53 | "".join(["".join(["<|USER|>"+history[i]["content"], "<|ASSISTANT|>"+history[i + 1]["content"]]) 54 | for i in range(0, len(history), 2)]) 55 | return messages 56 | 57 | def _generate(self, text, bad_text=None): 58 | stop = StopOnTokens() 59 | result = self.generator(text, max_new_tokens=self.max_generation_token, num_return_sequences=1, num_beams=1, do_sample=True, 60 | temperature=self.temperature, top_p=self.top_p, top_k=1000, stopping_criteria=StoppingCriteriaList([stop])) 61 | return result[0]["generated_text"].replace(text, "") 62 | 63 | def get_answer_at_once(self): 64 | messages = self._get_stablelm_style_input() 65 | return self._generate(messages), len(messages) 66 | 67 | def get_answer_stream_iter(self): 68 | stop = StopOnTokens() 69 | messages = self._get_stablelm_style_input() 70 | 71 | # model_inputs = tok([messages], return_tensors="pt")['input_ids'].cuda()[:, :4096-1024] 72 | model_inputs = STABLELM_TOKENIZER( 73 | [messages], return_tensors="pt").to("cuda") 74 | streamer = TextIteratorStreamer( 75 | STABLELM_TOKENIZER, timeout=10., skip_prompt=True, skip_special_tokens=True) 76 | generate_kwargs = dict( 77 | model_inputs, 78 | streamer=streamer, 79 | max_new_tokens=self.max_generation_token, 80 | do_sample=True, 81 | top_p=self.top_p, 82 | top_k=1000, 83 | temperature=self.temperature, 84 | num_beams=1, 85 | stopping_criteria=StoppingCriteriaList([stop]) 86 | ) 87 | t = Thread(target=STABLELM_MODEL.generate, kwargs=generate_kwargs) 88 | t.start() 89 | 90 | partial_text = "" 91 | for new_text in streamer: 92 | partial_text += new_text 93 | yield partial_text 94 | -------------------------------------------------------------------------------- /web_assets/javascript/file-input.js: -------------------------------------------------------------------------------- 1 | 2 | // paste和upload部分参考: 3 | // https://github.com/binary-husky/gpt_academic/tree/master/themes/common.js 4 | // @Kilig947 5 | 6 | 7 | function setPasteUploader() { 8 | input = user_input_tb.querySelector("textarea") 9 | let paste_files = []; 10 | if (input) { 11 | input.addEventListener("paste", async function (e) { 12 | const clipboardData = e.clipboardData || window.clipboardData; 13 | const items = clipboardData.items; 14 | if (items) { 15 | for (i = 0; i < items.length; i++) { 16 | if (items[i].kind === "file") { // 确保是文件类型 17 | const file = items[i].getAsFile(); 18 | // 将每一个粘贴的文件添加到files数组中 19 | paste_files.push(file); 20 | e.preventDefault(); // 避免粘贴文件名到输入框 21 | } 22 | } 23 | if (paste_files.length > 0) { 24 | // 按照文件列表执行批量上传逻辑 25 | await upload_files(paste_files); 26 | paste_files = []; 27 | } 28 | } 29 | }); 30 | } 31 | } 32 | 33 | var hintArea; 34 | function setDragUploader() { 35 | input = chatbotArea; 36 | if (input) { 37 | const dragEvents = ["dragover", "dragenter"]; 38 | const leaveEvents = ["dragleave", "dragend", "drop"]; 39 | 40 | const onDrag = function (e) { 41 | e.preventDefault(); 42 | e.stopPropagation(); 43 | if (!chatbotArea.classList.contains("with-file")) { 44 | chatbotArea.classList.add("dragging"); 45 | draggingHint(); 46 | } else { 47 | statusDisplayMessage(clearFileHistoryMsg_i18n, 2000); 48 | } 49 | }; 50 | 51 | const onLeave = function (e) { 52 | e.preventDefault(); 53 | e.stopPropagation(); 54 | chatbotArea.classList.remove("dragging"); 55 | if (hintArea) { 56 | hintArea.remove(); 57 | } 58 | }; 59 | 60 | dragEvents.forEach(event => { 61 | input.addEventListener(event, onDrag); 62 | }); 63 | 64 | leaveEvents.forEach(event => { 65 | input.addEventListener(event, onLeave); 66 | }); 67 | 68 | input.addEventListener("drop", async function (e) { 69 | const files = e.dataTransfer.files; 70 | await upload_files(files); 71 | }); 72 | } 73 | } 74 | 75 | async function upload_files(files) { 76 | const uploadInputElement = gradioApp().querySelector("#upload-index-file > .center.flex input[type=file]"); 77 | let totalSizeMb = 0 78 | if (files && files.length > 0) { 79 | // 执行具体的上传逻辑 80 | if (uploadInputElement) { 81 | for (let i = 0; i < files.length; i++) { 82 | // 将从文件数组中获取的文件大小(单位为字节)转换为MB， 83 | totalSizeMb += files[i].size / 1024 / 1024; 84 | } 85 | // 检查文件总大小是否超过20MB 86 | if (totalSizeMb > 20) { 87 | // toast_push('⚠️文件夹大于20MB 🚀上传文件中', 2000) 88 | // return; // 如果超过了指定大小, 可以不进行后续上传操作 89 | } 90 | // 监听change事件， 原生Gradio可以实现 91 | // uploadInputElement.addEventListener('change', function(){replace_input_string()}); 92 | let event = new Event("change"); 93 | Object.defineProperty(event, "target", {value: uploadInputElement, enumerable: true}); 94 | Object.defineProperty(event, "currentTarget", {value: uploadInputElement, enumerable: true}); 95 | Object.defineProperty(uploadInputElement, "files", {value: files, enumerable: true}); 96 | uploadInputElement.dispatchEvent(event); 97 | // statusDisplayMessage(""); 98 | } else { 99 | statusDisplayMessage(clearFileHistoryMsg_i18n, 3000); 100 | return; 101 | } 102 | } 103 | } 104 | 105 | function draggingHint() { 106 | hintArea = chatbotArea.querySelector(".dragging-hint"); 107 | if (hintArea) { 108 | return; 109 | } 110 | hintArea = document.createElement("div"); 111 | hintArea.classList.add("dragging-hint"); 112 | hintArea.innerHTML = `

${dropUploadMsg_i18n}

`; 113 | chatbotArea.appendChild(hintArea); 114 | } 115 | -------------------------------------------------------------------------------- /modules/models/Claude.py: -------------------------------------------------------------------------------- 1 | from anthropic import Anthropic, HUMAN_PROMPT, AI_PROMPT 2 | from ..presets import * 3 | from ..utils import * 4 | 5 | from .base_model import BaseLLMModel 6 | 7 | 8 | class Claude_Client(BaseLLMModel): 9 | def __init__(self, model_name, api_secret) -> None: 10 | super().__init__(model_name=model_name) 11 | self.api_secret = api_secret 12 | if None in [self.api_secret]: 13 | raise Exception("请在配置文件或者环境变量中设置Claude的API Secret") 14 | self.claude_client = Anthropic(api_key=self.api_secret, base_url=self.api_host) 15 | 16 | def _get_claude_style_history(self): 17 | history = [] 18 | image_buffer = [] 19 | image_count = 0 20 | for message in self.history: 21 | if message["role"] == "user": 22 | content = [] 23 | if image_buffer: 24 | if image_count == 1: 25 | content.append( 26 | { 27 | "type": "image", 28 | "source": { 29 | "type": "base64", 30 | "media_type": f"image/{self.get_image_type(image_buffer[0])}", 31 | "data": self.get_base64_image(image_buffer[0]), 32 | }, 33 | }, 34 | ) 35 | else: 36 | image_buffer_length = len(image_buffer) 37 | for idx, image in enumerate(image_buffer): 38 | content.append( 39 | {"type": "text", "text": f"Image {image_count - image_buffer_length + idx + 1}:"}, 40 | ) 41 | content.append( 42 | { 43 | "type": "image", 44 | "source": { 45 | "type": "base64", 46 | "media_type": f"image/{self.get_image_type(image)}", 47 | "data": self.get_base64_image(image), 48 | }, 49 | }, 50 | ) 51 | if content: 52 | content.append({"type": "text", "text": message["content"]}) 53 | history.append(construct_user(content)) 54 | image_buffer = [] 55 | else: 56 | history.append(message) 57 | elif message["role"] == "assistant": 58 | history.append(message) 59 | elif message["role"] == "image": 60 | image_buffer.append(message["content"]) 61 | image_count += 1 62 | # history with base64 data replaced with "#base64#" 63 | # history_for_display = history.copy() 64 | # for message in history_for_display: 65 | # if message["role"] == "user": 66 | # if type(message["content"]) == list: 67 | # for content in message["content"]: 68 | # if content["type"] == "image": 69 | # content["source"]["data"] = "#base64#" 70 | # logging.info(f"History for Claude: {history_for_display}") 71 | return history 72 | 73 | def get_answer_stream_iter(self): 74 | system_prompt = self.system_prompt 75 | history = self._get_claude_style_history() 76 | 77 | try: 78 | with self.claude_client.messages.stream( 79 | model=self.model_name, 80 | max_tokens=self.max_generation_token, 81 | messages=history, 82 | system=system_prompt, 83 | ) as stream: 84 | partial_text = "" 85 | for text in stream.text_stream: 86 | partial_text += text 87 | yield partial_text 88 | except Exception as e: 89 | yield i18n(GENERAL_ERROR_MSG) + ": " + str(e) 90 | 91 | def get_answer_at_once(self): 92 | system_prompt = self.system_prompt 93 | history = self._get_claude_style_history() 94 | 95 | response = self.claude_client.messages.create( 96 | model=self.model_name, 97 | max_tokens=self.max_generation_token, 98 | messages=history, 99 | system=system_prompt, 100 | ) 101 | if response is not None: 102 | return response.content[0].text, response.usage.output_tokens 103 | else: 104 | return i18n("获取资源错误"), 0 105 | -------------------------------------------------------------------------------- /web_assets/stylesheet/override-gradio.css: -------------------------------------------------------------------------------- 1 | .gradio-container { 2 | max-width: unset !important; 3 | padding: 0 !important; 4 | } 5 | 6 | /* 解决container=False时的错误填充 */ 7 | div.form { 8 | background: none !important; 9 | } 10 | div.no-container { 11 | padding: 16px 0 0 0 !important; 12 | background: none !important; 13 | } 14 | 15 | /* gradio的页脚信息 */ 16 | footer { 17 | display: none !important; 18 | margin-top: .2em !important; 19 | font-size: 85%; 20 | } 21 | 22 | .api-docs-wrap { 23 | margin-top: 64px; 24 | } 25 | 26 | 27 | /* 把radio做成列表 */ 28 | fieldset#history-select-dropdown .wrap { 29 | gap: 0; 30 | } 31 | fieldset#history-select-dropdown .wrap label { 32 | width: 100%; 33 | background: none; 34 | padding: 10px 16px 10px; 35 | box-shadow: none; 36 | justify-content: space-between; 37 | } 38 | fieldset#history-select-dropdown .wrap label:hover { 39 | background: var(--message-list-background-hover); 40 | } 41 | fieldset#history-select-dropdown .wrap label:active { 42 | background: var(--message-list-background-selected); 43 | } 44 | fieldset#history-select-dropdown .wrap label.selected { 45 | color: var(--checkbox-label-text-color); 46 | background: var(--message-list-background-selected); 47 | padding: 10px 64px 10px 16px; 48 | } 49 | fieldset#history-select-dropdown .wrap label:not(.selected) .chat-selected-btns{ 50 | display: none; 51 | } 52 | fieldset#history-select-dropdown .wrap label > span { 53 | /* font-size: small; */ 54 | margin-left: 0; 55 | /* text-overflow: ellipsis; */ 56 | white-space: nowrap; 57 | word-break: break-all; 58 | overflow: hidden; 59 | } 60 | fieldset#history-select-dropdown .wrap label > span::before { 61 | content: url("data:image/svg+xml,%3Csvg stroke='%23000000' fill='none' stroke-opacity='0.85' stroke-width='2' viewBox='0 0 24 24' stroke-linecap='round' stroke-linejoin='round' height='1em' width='1em' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M21 15a2 2 0 0 1-2 2H7l-4 4V5a2 2 0 0 1 2-2h14a2 2 0 0 1 2 2z'%3E%3C/path%3E%3C/svg%3E"); 62 | padding-right: .8em; 63 | position: relative; 64 | top: 4px; 65 | } 66 | .dark fieldset#history-select-dropdown .wrap label > span::before { 67 | content: url("data:image/svg+xml,%3Csvg stroke='%23FFFFFF' fill='none' stroke-opacity='0.85' stroke-width='2' viewBox='0 0 24 24' stroke-linecap='round' stroke-linejoin='round' height='1em' width='1em' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M21 15a2 2 0 0 1-2 2H7l-4 4V5a2 2 0 0 1 2-2h14a2 2 0 0 1 2 2z'%3E%3C/path%3E%3C/svg%3E"); 68 | } 69 | fieldset#history-select-dropdown .wrap label > input { 70 | display: none; 71 | } 72 | 73 | 74 | /* 覆盖 gradio 丑陋的复制按钮样式 */ 75 | .message .code_wrap button[title="copy"] { 76 | border-radius: 5px !important; 77 | transition: background-color .2s ease; 78 | color: white; 79 | } 80 | .message .code_wrap button[title="copy"]:hover { 81 | background-color: #333232; 82 | } 83 | .message .code_wrap button .copy-text, 84 | .message .code_wrap button .check { 85 | color: white !important; 86 | background: var(--neutral-950) !important; 87 | } 88 | 89 | .message .prose * { 90 | color: inherit; 91 | } 92 | 93 | 94 | /* Override Slider Styles (for webkit browsers like Safari and Chrome) 95 | * 该功能被做到gradio的官方版本中了 96 | * https://github.com/gradio-app/gradio/pull/5535 97 | * https://github.com/gradio-app/gradio/issues/4255 98 | **/ 99 | 100 | input[type="range"][class^="svelte-"] { 101 | background: var(--input-background-fill); 102 | border-radius: 5px; 103 | background-image: linear-gradient(var(--slider-color), var(--slider-color)); 104 | background-repeat: no-repeat; 105 | } 106 | 107 | /* Scrollbar override */ 108 | #chuanhu-chatbot > .wrapper > .bubble-wrap::-webkit-scrollbar { 109 | height: 1rem; 110 | width: 4px; 111 | } 112 | 113 | #chuanhu-chatbot > .wrapper > .bubble-wrap::-webkit-scrollbar-track { 114 | background-color: transparent; 115 | border-radius:9999px 116 | } 117 | 118 | #chuanhu-chatbot > .wrapper > .bubble-wrap::-webkit-scrollbar-thumb { 119 | background-color: rgba(231, 231, 231, 0.8); 120 | /* border-color: rgba(255, 255, 255, var(--tw-border-opacity)); */ 121 | border: none; 122 | border-radius: 9999px; 123 | /* border-width:1px */ 124 | } 125 | 126 | #chuanhu-chatbot > .wrapper > .bubble-wrap::-webkit-scrollbar-thumb:hover { 127 | --tw-bg-opacity: 1; 128 | background-color:rgb(195, 195, 195); 129 | } 130 | 131 | .dark #chuanhu-chatbot > .wrapper > .bubble-wrap::-webkit-scrollbar-thumb { 132 | background-color: rgba(56, 56, 56, 0.5); 133 | } 134 | 135 | .dark #chuanhu-chatbot > .wrapper > .bubble-wrap::-webkit-scrollbar-thumb:hover { 136 | background-color: rgba(56, 56, 56, 0.8); 137 | } 138 | -------------------------------------------------------------------------------- /web_assets/javascript/fake-gradio.js: -------------------------------------------------------------------------------- 1 | 2 | // Fake gradio components! 3 | 4 | // buttons 5 | function newChatClick() { 6 | gradioApp().querySelector('#empty-btn').click(); 7 | } 8 | function jsonDownloadClick() { 9 | gradioApp().querySelector('#gr-history-download-json-btn').click(); 10 | } 11 | function mdDownloadClick() { 12 | gradioApp().querySelector('#gr-history-download-md-btn').click(); 13 | } 14 | 15 | // index files 16 | function setUploader() { 17 | transUpload(); 18 | var uploaderObserver = new MutationObserver(function (mutations) { 19 | var fileInput = null; 20 | var fileCount = 0; 21 | fileInput = gradioApp().querySelector("#upload-index-file table.file-preview"); 22 | var fileCountSpan = gradioApp().querySelector("#uploaded-files-count"); 23 | if (fileInput) { 24 | chatbotArea.classList.add('with-file'); 25 | fileCount = fileInput.querySelectorAll('tbody > tr.file').length; 26 | fileCountSpan.innerText = fileCount; 27 | } else { 28 | chatbotArea.classList.remove('with-file'); 29 | statusDisplayMessage(""); 30 | fileCount = 0; 31 | transUpload(); 32 | } 33 | }); 34 | uploaderObserver.observe(uploaderIndicator, {attributes: true}) 35 | uploaderObserver.observe(uploaderIndicator2, {attributes: true}) 36 | } 37 | var grUploader; 38 | var chatbotUploader; 39 | var handleClick = function() { 40 | grUploader.click(); 41 | 42 | }; 43 | function transUpload() { 44 | chatbotUploader = gradioApp().querySelector("#upload-files-btn"); 45 | chatbotUploader.removeEventListener('click', handleClick); 46 | grUploader = gradioApp().querySelector("#upload-index-file > .center.flex"); 47 | 48 | // let uploaderEvents = ["click", "drag", "dragend", "dragenter", "dragleave", "dragover", "dragstart", "drop"]; 49 | // transEventListeners(chatbotUploader, grUploader, uploaderEvents); 50 | 51 | chatbotUploader.addEventListener('click', handleClick); 52 | } 53 | 54 | // checkbox 55 | var grSingleSessionCB; 56 | var grOnlineSearchCB; 57 | var chatbotSingleSessionCB; 58 | var chatbotOnlineSearchCB; 59 | function setCheckboxes() { 60 | chatbotSingleSessionCB = gradioApp().querySelector('input[name="single-session-cb"]'); 61 | chatbotOnlineSearchCB = gradioApp().querySelector('input[name="online-search-cb"]'); 62 | grSingleSessionCB = gradioApp().querySelector("#gr-single-session-cb > label > input"); 63 | grOnlineSearchCB = gradioApp().querySelector("#gr-websearch-cb > label> input"); 64 | 65 | chatbotSingleSessionCB.addEventListener('change', (e) => { 66 | grSingleSessionCB.checked = chatbotSingleSessionCB.checked; 67 | gradioApp().querySelector('#change-single-session-btn').click(); 68 | }); 69 | chatbotOnlineSearchCB.addEventListener('change', (e) => { 70 | grOnlineSearchCB.checked = chatbotOnlineSearchCB.checked; 71 | gradioApp().querySelector('#change-online-search-btn').click(); 72 | }); 73 | grSingleSessionCB.addEventListener('change', (e) => { 74 | chatbotSingleSessionCB.checked = grSingleSessionCB.checked; 75 | }); 76 | grOnlineSearchCB.addEventListener('change', (e) => { 77 | chatbotOnlineSearchCB.checked = grOnlineSearchCB.checked; 78 | }); 79 | } 80 | 81 | function bgChangeSingleSession() { 82 | // const grSingleSessionCB = gradioApp().querySelector("#gr-single-session-cb > label > input"); 83 | let a = chatbotSingleSessionCB.checked; 84 | return [a]; 85 | } 86 | function bgChangeOnlineSearch() { 87 | // const grOnlineSearchCB = gradioApp().querySelector("#gr-websearch-cb > label> input"); 88 | let a = chatbotOnlineSearchCB.checked; 89 | return [a]; 90 | } 91 | 92 | function updateCheckboxes() { 93 | chatbotSingleSessionCB.checked = grSingleSessionCB.checked; 94 | chatbotOnlineSearchCB.checked = grOnlineSearchCB.checked; 95 | } 96 | 97 | // UTILS 98 | function transEventListeners(target, source, events) { 99 | events.forEach((sourceEvent) => { 100 | target.addEventListener(sourceEvent, function (targetEvent) { 101 | if(targetEvent.preventDefault) targetEvent.preventDefault(); 102 | if(targetEvent.stopPropagation) targetEvent.stopPropagation(); 103 | 104 | source.dispatchEvent(new Event(sourceEvent, {detail: targetEvent.detail})); 105 | // console.log(targetEvent.detail); 106 | }); 107 | }); 108 | /* 事实上，我发现这样写的大多数gradio组件并不适用。。所以。。。生气 */ 109 | } 110 | 111 | function bgSelectHistory(a,b){ 112 | const historySelectorInput = gradioApp().querySelector('#history-select-dropdown input'); 113 | let file = historySelectorInput.value; 114 | return [a,file] 115 | } 116 | 117 | function bgRebootChuanhu() { 118 | rebootChuanhuBtn.click() 119 | } -------------------------------------------------------------------------------- /modules/models/configuration_moss.py: -------------------------------------------------------------------------------- 1 | """ Moss model configuration""" 2 | 3 | from transformers.utils import logging 4 | from transformers.configuration_utils import PretrainedConfig 5 | 6 | 7 | logger = logging.get_logger(__name__) 8 | 9 | 10 | class MossConfig(PretrainedConfig): 11 | r""" 12 | This is the configuration class to store the configuration of a [`MossModel`]. It is used to instantiate a 13 | Moss model according to the specified arguments, defining the model architecture. Instantiating a configuration 14 | with the defaults will yield a similar configuration to that of the Moss 15 | [fnlp/moss-moon-003-base](https://huggingface.co/fnlp/moss-moon-003-base) architecture. Configuration objects 16 | inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from 17 | [`PretrainedConfig`] for more information. 18 | 19 | Args: 20 | vocab_size (`int`, *optional*, defaults to 107008): 21 | Vocabulary size of the Moss model. Defines the number of different tokens that can be represented by the 22 | `inputs_ids` passed when calling [`MossModel`]. 23 | n_positions (`int`, *optional*, defaults to 2048): 24 | The maximum sequence length that this model might ever be used with. Typically set this to something large 25 | just in case (e.g., 512 or 1024 or 2048). 26 | n_embd (`int`, *optional*, defaults to 4096): 27 | Dimensionality of the embeddings and hidden states. 28 | n_layer (`int`, *optional*, defaults to 28): 29 | Number of hidden layers in the Transformer encoder. 30 | n_head (`int`, *optional*, defaults to 16): 31 | Number of attention heads for each attention layer in the Transformer encoder. 32 | rotary_dim (`int`, *optional*, defaults to 64): 33 | Number of dimensions in the embedding that Rotary Position Embedding is applied to. 34 | n_inner (`int`, *optional*, defaults to None): 35 | Dimensionality of the inner feed-forward layers. `None` will set it to 4 times n_embd 36 | activation_function (`str`, *optional*, defaults to `"gelu_new"`): 37 | Activation function, to be selected in the list `["relu", "silu", "gelu", "tanh", "gelu_new"]`. 38 | resid_pdrop (`float`, *optional*, defaults to 0.1): 39 | The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. 40 | embd_pdrop (`int`, *optional*, defaults to 0.1): 41 | The dropout ratio for the embeddings. 42 | attn_pdrop (`float`, *optional*, defaults to 0.1): 43 | The dropout ratio for the attention. 44 | layer_norm_epsilon (`float`, *optional*, defaults to 1e-5): 45 | The epsilon to use in the layer normalization layers. 46 | initializer_range (`float`, *optional*, defaults to 0.02): 47 | The standard deviation of the truncated_normal_initializer for initializing all weight matrices. 48 | use_cache (`bool`, *optional*, defaults to `True`): 49 | Whether or not the model should return the last key/values attentions (not used by all models). 50 | 51 | Example: 52 | 53 | ```python 54 | >>> from modeling_moss import MossModel 55 | >>> from configuration_moss import MossConfig 56 | 57 | >>> # Initializing a moss-moon-003-base configuration 58 | >>> configuration = MossConfig() 59 | 60 | >>> # Initializing a model (with random weights) from the configuration 61 | >>> model = MossModel(configuration) 62 | 63 | >>> # Accessing the model configuration 64 | >>> configuration = model.config 65 | ```""" 66 | 67 | model_type = "moss" 68 | attribute_map = { 69 | "max_position_embeddings": "n_positions", 70 | "hidden_size": "n_embd", 71 | "num_attention_heads": "n_head", 72 | "num_hidden_layers": "n_layer", 73 | } 74 | 75 | def __init__( 76 | self, 77 | vocab_size=107008, 78 | n_positions=2048, 79 | n_ctx=2048, 80 | n_embd=4096, 81 | n_layer=28, 82 | n_head=16, 83 | rotary_dim=64, 84 | n_inner=None, 85 | activation_function="gelu_new", 86 | resid_pdrop=0.0, 87 | embd_pdrop=0.0, 88 | attn_pdrop=0.0, 89 | layer_norm_epsilon=1e-5, 90 | initializer_range=0.02, 91 | use_cache=True, 92 | bos_token_id=106028, 93 | eos_token_id=106068, 94 | tie_word_embeddings=False, 95 | **kwargs, 96 | ): 97 | self.vocab_size = vocab_size 98 | self.n_ctx = n_ctx 99 | self.n_positions = n_positions 100 | self.n_embd = n_embd 101 | self.n_layer = n_layer 102 | self.n_head = n_head 103 | self.n_inner = n_inner 104 | self.rotary_dim = rotary_dim 105 | self.activation_function = activation_function 106 | self.resid_pdrop = resid_pdrop 107 | self.embd_pdrop = embd_pdrop 108 | self.attn_pdrop = attn_pdrop 109 | self.layer_norm_epsilon = layer_norm_epsilon 110 | self.initializer_range = initializer_range 111 | self.use_cache = use_cache 112 | 113 | self.bos_token_id = bos_token_id 114 | self.eos_token_id = eos_token_id 115 | 116 | super().__init__( 117 | bos_token_id=bos_token_id, eos_token_id=eos_token_id, tie_word_embeddings=tie_word_embeddings, **kwargs 118 | ) 119 | -------------------------------------------------------------------------------- /modules/models/XMChat.py: -------------------------------------------------------------------------------- 1 | from __future__ import annotations 2 | 3 | import base64 4 | import json 5 | import logging 6 | import os 7 | import uuid 8 | from io import BytesIO 9 | 10 | import requests 11 | from PIL import Image 12 | 13 | from ..index_func import * 14 | from ..presets import * 15 | from ..utils import * 16 | from .base_model import BaseLLMModel 17 | 18 | 19 | class XMChat(BaseLLMModel): 20 | def __init__(self, api_key, user_name=""): 21 | super().__init__(model_name="xmchat", user=user_name) 22 | self.api_key = api_key 23 | self.session_id = None 24 | self.reset() 25 | self.image_bytes = None 26 | self.image_path = None 27 | self.xm_history = [] 28 | self.url = "https://xmbot.net/web" 29 | if self.api_host is not None: 30 | self.url = self.api_host 31 | self.last_conv_id = None 32 | 33 | def reset(self, remain_system_prompt=False): 34 | self.session_id = str(uuid.uuid4()) 35 | self.last_conv_id = None 36 | return super().reset() 37 | 38 | def image_to_base64(self, image_path): 39 | # 打开并加载图片 40 | img = Image.open(image_path) 41 | 42 | # 获取图片的宽度和高度 43 | width, height = img.size 44 | 45 | # 计算压缩比例，以确保最长边小于4096像素 46 | max_dimension = 2048 47 | scale_ratio = min(max_dimension / width, max_dimension / height) 48 | 49 | if scale_ratio < 1: 50 | # 按压缩比例调整图片大小 51 | new_width = int(width * scale_ratio) 52 | new_height = int(height * scale_ratio) 53 | img = img.resize((new_width, new_height), Image.LANCZOS) 54 | 55 | # 将图片转换为jpg格式的二进制数据 56 | buffer = BytesIO() 57 | if img.mode == "RGBA": 58 | img = img.convert("RGB") 59 | img.save(buffer, format='JPEG') 60 | binary_image = buffer.getvalue() 61 | 62 | # 对二进制数据进行Base64编码 63 | base64_image = base64.b64encode(binary_image).decode('utf-8') 64 | 65 | return base64_image 66 | 67 | def try_read_image(self, filepath): 68 | def is_image_file(filepath): 69 | # 判断文件是否为图片 70 | valid_image_extensions = [ 71 | ".jpg", ".jpeg", ".png", ".bmp", ".gif", ".tiff"] 72 | file_extension = os.path.splitext(filepath)[1].lower() 73 | return file_extension in valid_image_extensions 74 | 75 | if is_image_file(filepath): 76 | logging.info(f"读取图片文件: {filepath}") 77 | self.image_bytes = self.image_to_base64(filepath) 78 | self.image_path = filepath 79 | else: 80 | self.image_bytes = None 81 | self.image_path = None 82 | 83 | def like(self): 84 | if self.last_conv_id is None: 85 | return "点赞失败，你还没发送过消息" 86 | data = { 87 | "uuid": self.last_conv_id, 88 | "appraise": "good" 89 | } 90 | requests.post(self.url, json=data) 91 | return "👍点赞成功，感谢反馈～" 92 | 93 | def dislike(self): 94 | if self.last_conv_id is None: 95 | return "点踩失败，你还没发送过消息" 96 | data = { 97 | "uuid": self.last_conv_id, 98 | "appraise": "bad" 99 | } 100 | requests.post(self.url, json=data) 101 | return "👎点踩成功，感谢反馈～" 102 | 103 | def prepare_inputs(self, real_inputs, use_websearch, files, reply_language, chatbot): 104 | fake_inputs = real_inputs 105 | display_append = "" 106 | limited_context = False 107 | return limited_context, fake_inputs, display_append, real_inputs, chatbot 108 | 109 | def handle_file_upload(self, files, chatbot, language): 110 | """if the model accepts multi modal input, implement this function""" 111 | if files: 112 | for file in files: 113 | if file.name: 114 | logging.info(f"尝试读取图像: {file.name}") 115 | self.try_read_image(file.name) 116 | if self.image_path is not None: 117 | chatbot = chatbot + [((self.image_path,), None)] 118 | if self.image_bytes is not None: 119 | logging.info("使用图片作为输入") 120 | # XMChat的一轮对话中实际上只能处理一张图片 121 | self.reset() 122 | conv_id = str(uuid.uuid4()) 123 | data = { 124 | "user_id": self.api_key, 125 | "session_id": self.session_id, 126 | "uuid": conv_id, 127 | "data_type": "imgbase64", 128 | "data": self.image_bytes 129 | } 130 | response = requests.post(self.url, json=data) 131 | response = json.loads(response.text) 132 | logging.info(f"图片回复: {response['data']}") 133 | return None, chatbot, None 134 | 135 | def get_answer_at_once(self): 136 | question = self.history[-1]["content"] 137 | conv_id = str(uuid.uuid4()) 138 | self.last_conv_id = conv_id 139 | data = { 140 | "user_id": self.api_key, 141 | "session_id": self.session_id, 142 | "uuid": conv_id, 143 | "data_type": "text", 144 | "data": question 145 | } 146 | response = requests.post(self.url, json=data) 147 | try: 148 | response = json.loads(response.text) 149 | return response["data"], len(response["data"]) 150 | except Exception as e: 151 | return response.text, len(response.text) 152 | -------------------------------------------------------------------------------- /config_example.json: -------------------------------------------------------------------------------- 1 | { 2 | // 各配置具体说明，见 [https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用教程#配置-configjson] 3 | 4 | //== API 配置 == 5 | "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 6 | "deepseek_api_key": "", // 你的 DeepSeek API Key，用于 DeepSeek Chat 和 Reasoner(R1) 对话模型 7 | "google_genai_api_key": "", // 你的 Google Gemini API Key ，用于 Google Gemini 对话模型 8 | "google_genai_api_host": "generativelanguage.googleapis.com", // 你的 Google Gemini API Host 地址，一般无需更改 9 | "xmchat_api_key": "", // 你的 xmchat API Key，用于 XMChat 对话模型 10 | "minimax_api_key": "", // 你的 MiniMax API Key，用于 MiniMax 对话模型 11 | "minimax_group_id": "", // 你的 MiniMax Group ID，用于 MiniMax 对话模型 12 | "midjourney_proxy_api_base": "https://xxx/mj", // 你的 https://github.com/novicezk/midjourney-proxy 代理地址 13 | "midjourney_proxy_api_secret": "", // 你的 MidJourney Proxy API Secret，用于鉴权访问 api，可选 14 | "midjourney_discord_proxy_url": "", // 你的 MidJourney Discord Proxy URL，用于对生成对图进行反代，可选 15 | "midjourney_temp_folder": "./tmp", // 你的 MidJourney 临时文件夹，用于存放生成的图片，填空则关闭自动下载切图（直接显示MJ的四宫格图） 16 | "spark_appid": "", // 你的 讯飞星火大模型 API AppID，用于讯飞星火大模型对话模型 17 | "spark_api_key": "", // 你的 讯飞星火大模型 API Key，用于讯飞星火大模型对话模型 18 | "spark_api_secret": "", // 你的 讯飞星火大模型 API Secret，用于讯飞星火大模型对话模型 19 | "claude_api_secret":"",// 你的 Claude API Secret，用于 Claude 对话模型 20 | "ernie_api_key": "",// 你的文心一言在百度云中的API Key，用于文心一言对话模型 21 | "ernie_secret_key": "",// 你的文心一言在百度云中的Secret Key，用于文心一言对话模型 22 | "ollama_host": "", // 你的 Ollama Host，用于 Ollama 对话模型 23 | "huggingface_auth_token": "", // 你的 Hugging Face API Token，用于访问有限制的模型 24 | "groq_api_key": "", // 你的 Groq API Key，用于 Groq 对话模型(https://console.groq.com/) 25 | 26 | //== Azure == 27 | "openai_api_type": "openai", // 可选项：azure, openai 28 | "azure_openai_api_key": "", // 你的 Azure OpenAI API Key，用于 Azure OpenAI 对话模型 29 | "azure_openai_api_base_url": "", // 你的 Azure Base URL 30 | "azure_openai_api_version": "2023-05-15", // 你的 Azure OpenAI API 版本 31 | "azure_deployment_name": "", // 你的 Azure OpenAI Chat 模型 Deployment 名称 32 | "azure_embedding_deployment_name": "", // 你的 Azure OpenAI Embedding 模型 Deployment 名称 33 | "azure_embedding_model_name": "text-embedding-ada-002", // 你的 Azure OpenAI Embedding 模型名称 34 | 35 | //== 基础配置 == 36 | "language": "auto", // 界面语言，可选"auto", "zh_CN", "en_US", "ja_JP", "ko_KR", "sv_SE", "ru_RU", "vi_VN" 37 | "users": [], // 用户列表，[["用户名1", "密码1"], ["用户名2", "密码2"], ...] 38 | "admin_list": [], // 管理员列表，["用户名1", "用户名2", ...] 只有管理员可以重启服务 39 | "local_embedding": false, //是否在本地编制索引 40 | "hide_history_when_not_logged_in": false, //未登录情况下是否不展示对话历史 41 | "check_update": true, //是否启用检查更新 42 | "default_model": "GPT3.5 Turbo", // 默认模型 43 | "chat_name_method_index": 2, // 选择对话名称的方法。0: 使用日期时间命名；1: 使用第一条提问命名，2: 使用模型自动总结 44 | "bot_avatar": "default", // 机器人头像，可填写本地或网络图片链接，或者"none"（不显示头像） 45 | "user_avatar": "default", // 用户头像，可填写本地或网络图片链接，或者"none"（不显示头像） 46 | 47 | //== API 用量 == 48 | "show_api_billing": false, //是否显示OpenAI API用量（启用需要填写sensitive_id） 49 | "sensitive_id": "", // 你 OpenAI 账户的 Sensitive ID，用于查询 API 用量 50 | "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 51 | "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） 52 | 53 | //== 川虎助理设置 == 54 | "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 55 | "GOOGLE_API_KEY": "", //谷歌API Key，用于川虎助理Pro模式 56 | "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/ 57 | "SERPAPI_API_KEY": "", //SerpAPI API Key，用于川虎助理Pro模式，获取方式请看 https://serpapi.com/ 58 | 59 | //== 文档处理与显示 == 60 | "latex_option": "default", // LaTeX 公式渲染策略，可选"default", "strict", "all"或者"disabled" 61 | "advance_docs": { 62 | "pdf": { 63 | "two_column": false, // 是否认为PDF是双栏的 64 | "formula_ocr": true // 是否使用OCR识别PDF中的公式 65 | } 66 | }, 67 | 68 | //== 高级配置 == 69 | // 是否多个API Key轮换使用 70 | "multi_api_key": false, 71 | "hide_my_key": false, // 如果你想在UI中隐藏 API 密钥输入框，将此值设置为 true 72 | // "available_models": ["GPT3.5 Turbo", "GPT4 Turbo", "GPT4 Vision"], // 可用的模型列表，将覆盖默认的可用模型列表 73 | // "extra_models": ["模型名称3", "模型名称4", ...], // 额外的模型，将添加到可用的模型列表之后 74 | // "extra_model_metadata": { 75 | // "GPT-3.5 Turbo Keldos": { 76 | // "model_name": "gpt-3.5-turbo", 77 | // "description": "GPT-3.5 Turbo is a large language model trained by OpenAI. It is the latest version of the GPT series of models, and is known for its ability to generate human-like text.", 78 | // "model_type": "OpenAI", 79 | // "multimodal": false, 80 | // "api_host": "https://www.example.com", 81 | // "token_limit": 4096, 82 | // "max_generation": 4096, 83 | // }, 84 | // } 85 | // "api_key_list": [ 86 | // "sk-xxxxxxxxxxxxxxxxxxxxxxxx1", 87 | // "sk-xxxxxxxxxxxxxxxxxxxxxxxx2", 88 | // "sk-xxxxxxxxxxxxxxxxxxxxxxxx3" 89 | // ], 90 | // "rename_model": "GPT-4o-mini", //指定默认命名模型 91 | // 自定义OpenAI API Base 92 | // "openai_api_base": "https://api.openai.com", 93 | // 自定义使用代理（请替换代理URL） 94 | // "https_proxy": "http://127.0.0.1:1079", 95 | // "http_proxy": "http://127.0.0.1:1079", 96 | // 自定义端口、自定义ip（请替换对应内容） 97 | // "server_name": "0.0.0.0", 98 | // "server_port": 7860, 99 | // 如果要share到gradio，设置为true 100 | // "share": false, 101 | //如果不想自动打开浏览器，设置为false 102 | //"autobrowser": false 103 | } 104 | -------------------------------------------------------------------------------- /modules/models/spark.py: -------------------------------------------------------------------------------- 1 | import _thread as thread 2 | import base64 3 | import datetime 4 | import hashlib 5 | import hmac 6 | import json 7 | from collections import deque 8 | from urllib.parse import urlparse 9 | import ssl 10 | from datetime import datetime 11 | from time import mktime 12 | from urllib.parse import urlencode 13 | from wsgiref.handlers import format_date_time 14 | from threading import Condition 15 | import websocket 16 | import logging 17 | 18 | from .base_model import BaseLLMModel, CallbackToIterator 19 | 20 | 21 | class Ws_Param(object): 22 | # 来自官方 Demo 23 | # 初始化 24 | def __init__(self, APPID, APIKey, APISecret, Spark_url): 25 | self.APPID = APPID 26 | self.APIKey = APIKey 27 | self.APISecret = APISecret 28 | self.host = urlparse(Spark_url).netloc 29 | self.path = urlparse(Spark_url).path 30 | self.Spark_url = Spark_url 31 | 32 | # 生成url 33 | def create_url(self): 34 | # 生成RFC1123格式的时间戳 35 | now = datetime.now() 36 | date = format_date_time(mktime(now.timetuple())) 37 | 38 | # 拼接字符串 39 | signature_origin = "host: " + self.host + "\n" 40 | signature_origin += "date: " + date + "\n" 41 | signature_origin += "GET " + self.path + " HTTP/1.1" 42 | 43 | # 进行hmac-sha256进行加密 44 | signature_sha = hmac.new( 45 | self.APISecret.encode("utf-8"), 46 | signature_origin.encode("utf-8"), 47 | digestmod=hashlib.sha256, 48 | ).digest() 49 | 50 | signature_sha_base64 = base64.b64encode( 51 | signature_sha).decode(encoding="utf-8") 52 | 53 | authorization_origin = f'api_key="{self.APIKey}", algorithm="hmac-sha256", headers="host date request-line", signature="{signature_sha_base64}"' 54 | 55 | authorization = base64.b64encode(authorization_origin.encode("utf-8")).decode( 56 | encoding="utf-8" 57 | ) 58 | 59 | # 将请求的鉴权参数组合为字典 60 | v = {"authorization": authorization, "date": date, "host": self.host} 61 | # 拼接鉴权参数，生成url 62 | url = self.Spark_url + "?" + urlencode(v) 63 | # 此处打印出建立连接时候的url,参考本demo的时候可取消上方打印的注释，比对相同参数时生成的url与自己代码生成的url是否一致 64 | return url 65 | 66 | 67 | class Spark_Client(BaseLLMModel): 68 | def __init__(self, model_name, appid, api_key, api_secret, user_name="") -> None: 69 | super().__init__(model_name=model_name, user=user_name) 70 | self.api_key = api_key 71 | self.appid = appid 72 | self.api_secret = api_secret 73 | if None in [self.api_key, self.appid, self.api_secret]: 74 | raise Exception("请在配置文件或者环境变量中设置讯飞的API Key、APP ID和API Secret") 75 | self.spark_url = f"wss://spark-api.xf-yun.com{self.metadata['path']}" 76 | self.domain = self.metadata['domain'] 77 | 78 | # 收到websocket错误的处理 79 | def on_error(self, ws, error): 80 | ws.iterator.callback("出现了错误:" + error) 81 | 82 | # 收到websocket关闭的处理 83 | def on_close(self, ws, one, two): 84 | pass 85 | 86 | # 收到websocket连接建立的处理 87 | def on_open(self, ws): 88 | thread.start_new_thread(self.run, (ws,)) 89 | 90 | def run(self, ws, *args): 91 | data = json.dumps( 92 | self.gen_params() 93 | ) 94 | ws.send(data) 95 | 96 | # 收到websocket消息的处理 97 | def on_message(self, ws, message): 98 | ws.iterator.callback(message) 99 | 100 | def gen_params(self): 101 | """ 102 | 通过appid和用户的提问来生成请参数 103 | """ 104 | data = { 105 | "header": {"app_id": self.appid, "uid": "1234"}, 106 | "parameter": { 107 | "chat": { 108 | "domain": self.domain, 109 | "random_threshold": self.temperature, 110 | "max_tokens": 4096, 111 | "auditing": "default", 112 | } 113 | }, 114 | "payload": {"message": {"text": self.history}}, 115 | } 116 | return data 117 | 118 | def get_answer_stream_iter(self): 119 | wsParam = Ws_Param(self.appid, self.api_key, self.api_secret, self.spark_url) 120 | websocket.enableTrace(False) 121 | wsUrl = wsParam.create_url() 122 | ws = websocket.WebSocketApp( 123 | wsUrl, 124 | on_message=self.on_message, 125 | on_error=self.on_error, 126 | on_close=self.on_close, 127 | on_open=self.on_open, 128 | ) 129 | ws.appid = self.appid 130 | ws.domain = self.domain 131 | 132 | # Initialize the CallbackToIterator 133 | ws.iterator = CallbackToIterator() 134 | 135 | # Start the WebSocket connection in a separate thread 136 | thread.start_new_thread( 137 | ws.run_forever, (), {"sslopt": {"cert_reqs": ssl.CERT_NONE}} 138 | ) 139 | 140 | # Iterate over the CallbackToIterator instance 141 | answer = "" 142 | total_tokens = 0 143 | for message in ws.iterator: 144 | data = json.loads(message) 145 | code = data["header"]["code"] 146 | if code != 0: 147 | ws.close() 148 | raise Exception(f"请求错误: {code}, {data}") 149 | else: 150 | choices = data["payload"]["choices"] 151 | status = choices["status"] 152 | content = choices["text"][0]["content"] 153 | if "usage" in data["payload"]: 154 | total_tokens = data["payload"]["usage"]["text"]["total_tokens"] 155 | answer += content 156 | if status == 2: 157 | ws.iterator.finish() # Finish the iterator when the status is 2 158 | ws.close() 159 | yield answer, total_tokens 160 | -------------------------------------------------------------------------------- /locale/extract_locale.py: -------------------------------------------------------------------------------- 1 | import asyncio 2 | import logging 3 | import os 4 | import re 5 | import sys 6 | 7 | import aiohttp 8 | import commentjson 9 | import commentjson as json 10 | 11 | asyncio.set_event_loop_policy(asyncio.DefaultEventLoopPolicy()) 12 | 13 | with open("config.json", "r", encoding="utf-8") as f: 14 | config = commentjson.load(f) 15 | api_key = config["openai_api_key"] 16 | url = config["openai_api_base"] + "/v1/chat/completions" if "openai_api_base" in config else "https://api.openai.com/v1/chat/completions" 17 | 18 | 19 | def get_current_strings(): 20 | pattern = r'i18n\s*\(\s*["\']([^"\']*(?:\)[^"\']*)?)["\']\s*\)' 21 | 22 | # Load the .py files 23 | contents = "" 24 | for dirpath, dirnames, filenames in os.walk("."): 25 | for filename in filenames: 26 | if filename.endswith(".py"): 27 | filepath = os.path.join(dirpath, filename) 28 | with open(filepath, 'r', encoding='utf-8') as f: 29 | contents += f.read() 30 | # Matching with regular expressions 31 | matches = re.findall(pattern, contents, re.DOTALL) 32 | data = {match.strip('()"'): '' for match in matches} 33 | fixed_data = {} # fix some keys 34 | for key, value in data.items(): 35 | if "](" in key and key.count("(") != key.count(")"): 36 | fixed_data[key+")"] = value 37 | else: 38 | fixed_data[key] = value 39 | 40 | return fixed_data 41 | 42 | 43 | def get_locale_strings(filename): 44 | try: 45 | with open(filename, "r", encoding="utf-8") as f: 46 | locale_strs = json.load(f) 47 | except FileNotFoundError: 48 | locale_strs = {} 49 | return locale_strs 50 | 51 | 52 | def sort_strings(existing_translations): 53 | # Sort the merged data 54 | sorted_translations = {} 55 | # Add entries with (NOT USED) in their values 56 | for key, value in sorted(existing_translations.items(), key=lambda x: x[0]): 57 | if "(🔴NOT USED)" in value: 58 | sorted_translations[key] = value 59 | # Add entries with empty values 60 | for key, value in sorted(existing_translations.items(), key=lambda x: x[0]): 61 | if value == "": 62 | sorted_translations[key] = value 63 | # Add the rest of the entries 64 | for key, value in sorted(existing_translations.items(), key=lambda x: x[0]): 65 | if value != "" and "(NOT USED)" not in value: 66 | sorted_translations[key] = value 67 | 68 | return sorted_translations 69 | 70 | 71 | async def auto_translate(str, language): 72 | headers = { 73 | "Content-Type": "application/json", 74 | "Authorization": f"Bearer {api_key}", 75 | "temperature": f"{0}", 76 | } 77 | payload = { 78 | "model": "gpt-3.5-turbo", 79 | "messages": [ 80 | { 81 | "role": "system", 82 | "content": f"You are a translation program;\nYour job is to translate user input into {language};\nThe content you are translating is a string in the App;\nDo not explain emoji;\nIf input is only a emoji, please simply return origin emoji;\nPlease ensure that the translation results are concise and easy to understand." 83 | }, 84 | {"role": "user", "content": f"{str}"} 85 | ], 86 | } 87 | 88 | async with aiohttp.ClientSession() as session: 89 | async with session.post(url, headers=headers, json=payload) as response: 90 | data = await response.json() 91 | return data["choices"][0]["message"]["content"] 92 | 93 | 94 | async def main(auto=False): 95 | current_strs = get_current_strings() 96 | locale_files = [] 97 | # 遍历locale目录下的所有json文件 98 | for dirpath, dirnames, filenames in os.walk("locale"): 99 | for filename in filenames: 100 | if filename.endswith(".json"): 101 | locale_files.append(os.path.join(dirpath, filename)) 102 | 103 | 104 | for locale_filename in locale_files: 105 | if "zh_CN" in locale_filename: 106 | continue 107 | try: 108 | locale_strs = get_locale_strings(locale_filename) 109 | except json.decoder.JSONDecodeError: 110 | import traceback 111 | traceback.print_exc() 112 | logging.error(f"Error decoding {locale_filename}") 113 | continue 114 | 115 | # Add new keys 116 | new_keys = [] 117 | for key in current_strs: 118 | if key not in locale_strs: 119 | new_keys.append(key) 120 | locale_strs[key] = "" 121 | print(f"{locale_filename[7:-5]}'s new str: {len(new_keys)}") 122 | # Add (NOT USED) to invalid keys 123 | for key in locale_strs: 124 | if key not in current_strs: 125 | locale_strs[key] = "(🔴NOT USED)" + locale_strs[key] 126 | print(f"{locale_filename[7:-5]}'s invalid str: {len(locale_strs) - len(current_strs)}") 127 | 128 | locale_strs = sort_strings(locale_strs) 129 | 130 | if auto: 131 | tasks = [] 132 | non_translated_keys = [] 133 | for key in locale_strs: 134 | if locale_strs[key] == "": 135 | non_translated_keys.append(key) 136 | tasks.append(auto_translate(key, locale_filename[7:-5])) 137 | results = await asyncio.gather(*tasks) 138 | for key, result in zip(non_translated_keys, results): 139 | locale_strs[key] = "(🟡REVIEW NEEDED)" + result 140 | print(f"{locale_filename[7:-5]}'s auto translated str: {len(non_translated_keys)}") 141 | 142 | with open(locale_filename, 'w', encoding='utf-8') as f: 143 | json.dump(locale_strs, f, ensure_ascii=False, indent=4) 144 | 145 | 146 | if __name__ == "__main__": 147 | auto = False 148 | if len(sys.argv) > 1 and sys.argv[1] == "--auto": 149 | auto = True 150 | asyncio.run(main(auto)) 151 | -------------------------------------------------------------------------------- /modules/train_func.py: -------------------------------------------------------------------------------- 1 | import os 2 | import logging 3 | import traceback 4 | 5 | from openai import OpenAI 6 | 7 | client = OpenAI(api_key=os.getenv("OPENAI_API_KEY")) 8 | import gradio as gr 9 | import ujson as json 10 | import commentjson 11 | import openpyxl 12 | 13 | import modules.presets as presets 14 | from modules.utils import get_file_hash, count_token 15 | from modules.presets import i18n 16 | 17 | def excel_to_jsonl(filepath, preview=False): 18 | # 打开Excel文件 19 | workbook = openpyxl.load_workbook(filepath) 20 | 21 | # 获取第一个工作表 22 | sheet = workbook.active 23 | 24 | # 获取所有行数据 25 | data = [] 26 | for row in sheet.iter_rows(values_only=True): 27 | data.append(row) 28 | 29 | # 构建字典列表 30 | headers = data[0] 31 | jsonl = [] 32 | for row in data[1:]: 33 | row_data = dict(zip(headers, row)) 34 | if any(row_data.values()): 35 | jsonl.append(row_data) 36 | formatted_jsonl = [] 37 | for i in jsonl: 38 | if "提问" in i and "答案" in i: 39 | if "系统" in i : 40 | formatted_jsonl.append({ 41 | "messages":[ 42 | {"role": "system", "content": i["系统"]}, 43 | {"role": "user", "content": i["提问"]}, 44 | {"role": "assistant", "content": i["答案"]} 45 | ] 46 | }) 47 | else: 48 | formatted_jsonl.append({ 49 | "messages":[ 50 | {"role": "user", "content": i["提问"]}, 51 | {"role": "assistant", "content": i["答案"]} 52 | ] 53 | }) 54 | else: 55 | logging.warning(f"跳过一行数据，因为没有找到提问和答案: {i}") 56 | return formatted_jsonl 57 | 58 | def jsonl_save_to_disk(jsonl, filepath): 59 | file_hash = get_file_hash(file_paths = [filepath]) 60 | os.makedirs("files", exist_ok=True) 61 | save_path = f"files/{file_hash}.jsonl" 62 | with open(save_path, "w") as f: 63 | f.write("\n".join([json.dumps(i, ensure_ascii=False) for i in jsonl])) 64 | return save_path 65 | 66 | def estimate_cost(ds): 67 | dialogues = [] 68 | for l in ds: 69 | for m in l["messages"]: 70 | dialogues.append(m["content"]) 71 | dialogues = "\n".join(dialogues) 72 | tokens = count_token(dialogues) 73 | return f"Token 数约为 {tokens}，预估每轮（epoch）费用约为 {tokens / 1000 * 0.008} 美元。" 74 | 75 | 76 | def handle_dataset_selection(file_src): 77 | logging.info(f"Loading dataset {file_src.name}...") 78 | preview = "" 79 | if file_src.name.endswith(".jsonl"): 80 | with open(file_src.name, "r") as f: 81 | ds = [json.loads(l) for l in f.readlines()] 82 | else: 83 | ds = excel_to_jsonl(file_src.name) 84 | preview = ds[0] 85 | 86 | return preview, gr.update(interactive=True), estimate_cost(ds) 87 | 88 | def upload_to_openai(file_src): 89 | dspath = file_src.name 90 | msg = "" 91 | logging.info(f"Uploading dataset {dspath}...") 92 | if dspath.endswith(".xlsx"): 93 | jsonl = excel_to_jsonl(dspath) 94 | dspath = jsonl_save_to_disk(jsonl, dspath) 95 | try: 96 | uploaded = client.files.create(file=open(dspath, "rb"), 97 | purpose='fine-tune') 98 | return uploaded.id, f"上传成功" 99 | except Exception as e: 100 | traceback.print_exc() 101 | return "", f"上传失败，原因：{ e }" 102 | 103 | def build_event_description(id, status, trained_tokens, name=i18n("暂时未知")): 104 | # convert to markdown 105 | return f""" 106 | #### 训练任务 {id} 107 | 108 | 模型名称：{name} 109 | 110 | 状态：{status} 111 | 112 | 已经训练了 {trained_tokens} 个token 113 | """ 114 | 115 | def start_training(file_id, suffix, epochs): 116 | try: 117 | job = client.fine_tuning.jobs.create(training_file=file_id, model="gpt-3.5-turbo", suffix=suffix, hyperparameters={"n_epochs": epochs}) 118 | return build_event_description(job.id, job.status, job.trained_tokens) 119 | except Exception as e: 120 | traceback.print_exc() 121 | if "is not ready" in str(e): 122 | return "训练出错，因为文件还没准备好。OpenAI 需要一点时间准备文件，过几分钟再来试试。" 123 | return f"训练失败，原因：{ e }" 124 | 125 | def get_training_status(): 126 | active_jobs = [build_event_description(job.id, job.status, job.trained_tokens, job.fine_tuned_model) for job in client.fine_tuning.jobs.list().data if job.status != "cancelled"] 127 | return "\n\n".join(active_jobs), gr.update(interactive=True) if len(active_jobs) > 0 else gr.update(interactive=False) 128 | 129 | def handle_dataset_clear(): 130 | return gr.update(value=None), gr.update(interactive=False) 131 | 132 | def add_to_models(): 133 | succeeded_jobs = [job for job in client.fine_tuning.jobs.list().data if job.status == "succeeded"] 134 | extra_models = [job.fine_tuned_model for job in succeeded_jobs] 135 | for i in extra_models: 136 | if i not in presets.MODELS: 137 | presets.MODELS.append(i) 138 | 139 | with open('config.json', 'r') as f: 140 | data = commentjson.load(f) 141 | if 'extra_models' in data: 142 | for i in extra_models: 143 | if i not in data['extra_models']: 144 | data['extra_models'].append(i) 145 | else: 146 | data['extra_models'] = extra_models 147 | if 'extra_model_metadata' in data: 148 | for i in extra_models: 149 | if i not in data['extra_model_metadata']: 150 | data['extra_model_metadata'][i] = {"model_name": i, "model_type": "OpenAIVision"} 151 | else: 152 | data['extra_model_metadata'] = {i: {"model_name": i, "model_type": "OpenAIVision"} for i in extra_models} 153 | with open('config.json', 'w') as f: 154 | commentjson.dump(data, f, indent=4) 155 | 156 | return gr.update(choices=presets.MODELS), f"成功添加了 {len(succeeded_jobs)} 个模型。" 157 | 158 | def cancel_all_jobs(): 159 | jobs = [job for job in client.fine_tuning.jobs.list().data if job.status not in ["cancelled", "succeeded"]] 160 | for job in jobs: 161 | client.fine_tuning.jobs.cancel(job.id) 162 | return f"成功取消了 {len(jobs)} 个训练任务。" 163 | -------------------------------------------------------------------------------- /web_assets/javascript/utils.js: -------------------------------------------------------------------------------- 1 | 2 | 3 | function isImgUrl(url) { 4 | const imageExtensions = /\.(jpg|jpeg|png|gif|bmp|webp)$/i; 5 | if (url.startsWith('data:image/')) { 6 | return true; 7 | } 8 | if (url.match(imageExtensions)) { 9 | return true; 10 | } 11 | if (url.startsWith('http://') || url.startsWith('https://')) { 12 | return true; 13 | } 14 | 15 | return false; 16 | } 17 | 18 | function escapeMarkdown(text) { 19 | /* 20 | Escape Markdown special characters to HTML-safe equivalents. 21 | */ 22 | const escapeChars = { 23 | // ' ': ' ', 24 | "_": "_", 25 | "*": "*", 26 | "[": "[", 27 | "]": "]", 28 | "(": "(", 29 | ")": ")", 30 | "{": "{", 31 | "}": "}", 32 | "#": "#", 33 | "+": "+", 34 | "-": "-", 35 | ".": ".", 36 | "!": "!", 37 | "`": "`", 38 | ">": ">", 39 | "<": "<", 40 | "|": "|", 41 | "$": "$", 42 | ":": ":", 43 | }; 44 | 45 | text = text.replace(/ {4}/g, "    "); // Replace 4 spaces with non-breaking spaces 46 | 47 | let escapedText = ""; 48 | for (let i = 0; i < text.length; i++) { 49 | const currentChar = text.charAt(i); 50 | escapedText += escapeChars[currentChar] || currentChar; 51 | } 52 | 53 | return escapedText; 54 | } 55 | 56 | function downloadHistory(gradioUsername, historyname, format=".json") { 57 | let fileUrl; 58 | if (gradioUsername === null || gradioUsername.trim() === "") { 59 | fileUrl = `/file=./history/${historyname}`; 60 | } else { 61 | fileUrl = `/file=./history/${gradioUsername}/${historyname}`; 62 | } 63 | downloadFile(fileUrl, historyname, format); 64 | } 65 | 66 | function downloadFile(fileUrl, filename = "", format = "", retryTimeout = 200, maxAttempts = 10) { 67 | 68 | fileUrl = fileUrl + format; 69 | filename = filename + format; 70 | 71 | let attempts = 0; 72 | 73 | async function tryDownload() { 74 | if (attempts >= maxAttempts) { 75 | console.error('Max attempts reached, download failed.'); 76 | alert('Download failed:' + filename); 77 | return; 78 | } 79 | try { 80 | const response = await fetch(fileUrl); 81 | if (!response.ok) { 82 | attempts++; 83 | console.error("Error fetching file, retrying..."); 84 | setTimeout(tryDownload, retryTimeout); 85 | } else { 86 | response.blob() 87 | .then(blob => { 88 | const url = URL.createObjectURL(blob); 89 | const a = document.createElement('a'); 90 | a.style.display = 'none'; 91 | a.href = url; 92 | a.download = filename; 93 | document.body.appendChild(a); 94 | a.click(); 95 | URL.revokeObjectURL(url); 96 | document.body.removeChild(a); 97 | }) 98 | .catch(error => { 99 | console.error('Error downloading file:', error); 100 | }); 101 | } 102 | } catch (error) { 103 | attempts++; 104 | setTimeout(tryDownload, retryTimeout); 105 | } 106 | } 107 | 108 | tryDownload(); 109 | } 110 | 111 | function statusDisplayMessage(message) { 112 | statusDisplayBlock = statusDisplay.querySelector("#status-display .md p"); 113 | statusDisplayBlock.innerText = message; 114 | } 115 | 116 | function bindFancyBox() { 117 | Fancybox.bind('[data-fancybox]', { 118 | Carousel: { 119 | Panzoom: { 120 | decelFriction: 0.5 121 | } 122 | } 123 | }); 124 | } 125 | 126 | function rebootingChuanhu() { 127 | reloadSpinner = new Spin.Spinner({color:'#06AE56',lines:9}).spin(); 128 | pageInfo = document.createElement('div'); 129 | pageInfo.appendChild(reloadSpinner.el); 130 | pageInfo.innerHTML += '

Rebooting...

' 131 | document.body.innerHTML = ''; 132 | document.body.appendChild(pageInfo); 133 | 134 | var requestPing = function () { 135 | requestGet("./file=web_assets/manifest.json", {}, function (data) { 136 | location.reload(); 137 | }, function () { 138 | setTimeout(requestPing, 500); 139 | }); 140 | }; 141 | 142 | setTimeout(requestPing, 4000); 143 | 144 | return []; 145 | } 146 | 147 | /* NOTE: These reload functions are not used in the current version of the code. 148 | * From stable-diffusion-webui 149 | */ 150 | function restart_reload() { 151 | document.body.innerHTML = '

Reloading...

'; 152 | 153 | var requestPing = function () { 154 | requestGet("./internal/ping", {}, function (data) { 155 | location.reload(); 156 | }, function () { 157 | setTimeout(requestPing, 500); 158 | }); 159 | }; 160 | 161 | setTimeout(requestPing, 2000); 162 | 163 | return []; 164 | } 165 | 166 | function requestGet(url, data, handler, errorHandler) { 167 | var xhr = new XMLHttpRequest(); 168 | var args = Object.keys(data).map(function (k) { 169 | return encodeURIComponent(k) + '=' + encodeURIComponent(data[k]); 170 | }).join('&'); 171 | xhr.open("GET", url + "?" + args, true); 172 | 173 | xhr.onreadystatechange = function () { 174 | if (xhr.readyState === 4) { 175 | if (xhr.status === 200) { 176 | try { 177 | var js = JSON.parse(xhr.responseText); 178 | handler(js); 179 | } catch (error) { 180 | console.error(error); 181 | errorHandler(); 182 | } 183 | } else { 184 | errorHandler(); 185 | } 186 | } 187 | }; 188 | var js = JSON.stringify(data); 189 | xhr.send(js); 190 | } 191 | -------------------------------------------------------------------------------- /modules/pdf_func.py: -------------------------------------------------------------------------------- 1 | from types import SimpleNamespace 2 | import pdfplumber 3 | import logging 4 | from langchain.docstore.document import Document 5 | 6 | def prepare_table_config(crop_page): 7 | """Prepare table查找边界, 要求page为原始page 8 | 9 | From https://github.com/jsvine/pdfplumber/issues/242 10 | """ 11 | page = crop_page.root_page # root/parent 12 | cs = page.curves + page.edges 13 | def curves_to_edges(): 14 | """See https://github.com/jsvine/pdfplumber/issues/127""" 15 | edges = [] 16 | for c in cs: 17 | edges += pdfplumber.utils.rect_to_edges(c) 18 | return edges 19 | edges = curves_to_edges() 20 | return { 21 | "vertical_strategy": "explicit", 22 | "horizontal_strategy": "explicit", 23 | "explicit_vertical_lines": edges, 24 | "explicit_horizontal_lines": edges, 25 | "intersection_y_tolerance": 10, 26 | } 27 | 28 | def get_text_outside_table(crop_page): 29 | ts = prepare_table_config(crop_page) 30 | if len(ts["explicit_vertical_lines"]) == 0 or len(ts["explicit_horizontal_lines"]) == 0: 31 | return crop_page 32 | 33 | ### Get the bounding boxes of the tables on the page. 34 | bboxes = [table.bbox for table in crop_page.root_page.find_tables(table_settings=ts)] 35 | def not_within_bboxes(obj): 36 | """Check if the object is in any of the table's bbox.""" 37 | def obj_in_bbox(_bbox): 38 | """See https://github.com/jsvine/pdfplumber/blob/stable/pdfplumber/table.py#L404""" 39 | v_mid = (obj["top"] + obj["bottom"]) / 2 40 | h_mid = (obj["x0"] + obj["x1"]) / 2 41 | x0, top, x1, bottom = _bbox 42 | return (h_mid >= x0) and (h_mid < x1) and (v_mid >= top) and (v_mid < bottom) 43 | return not any(obj_in_bbox(__bbox) for __bbox in bboxes) 44 | 45 | return crop_page.filter(not_within_bboxes) 46 | # 请使用 LaTeX 表达公式，行内公式以 $ 包裹，行间公式以 $$ 包裹 47 | 48 | extract_words = lambda page: page.extract_words(keep_blank_chars=True, y_tolerance=0, x_tolerance=1, extra_attrs=["fontname", "size", "object_type"]) 49 | # dict_keys(['text', 'x0', 'x1', 'top', 'doctop', 'bottom', 'upright', 'direction', 'fontname', 'size']) 50 | 51 | def get_title_with_cropped_page(first_page): 52 | title = [] # 处理标题 53 | x0,top,x1,bottom = first_page.bbox # 获取页面边框 54 | 55 | for word in extract_words(first_page): 56 | word = SimpleNamespace(**word) 57 | 58 | if word.size >= 14: 59 | title.append(word.text) 60 | title_bottom = word.bottom 61 | elif word.text == "Abstract": # 获取页面abstract 62 | top = word.top 63 | 64 | user_info = [i["text"] for i in extract_words(first_page.within_bbox((x0,title_bottom,x1,bottom)))] 65 | # 裁剪掉上半部分, within_bbox: full_included; crop: partial_included 66 | return title, user_info, first_page.within_bbox((x0,top,x1,bottom)) 67 | 68 | def get_column_cropped_pages(pages, two_column=True): 69 | new_pages = [] 70 | for page in pages: 71 | if two_column: 72 | left = page.within_bbox((0, 0, page.width/2, page.height),relative=True) 73 | right = page.within_bbox((page.width/2, 0, page.width, page.height), relative=True) 74 | new_pages.append(left) 75 | new_pages.append(right) 76 | else: 77 | new_pages.append(page) 78 | 79 | return new_pages 80 | 81 | def parse_pdf(filename, two_column = True): 82 | level = logging.getLogger().level 83 | if level == logging.getLevelName("DEBUG"): 84 | logging.getLogger().setLevel("INFO") 85 | 86 | with pdfplumber.open(filename) as pdf: 87 | title, user_info, first_page = get_title_with_cropped_page(pdf.pages[0]) 88 | new_pages = get_column_cropped_pages([first_page] + pdf.pages[1:], two_column) 89 | 90 | chapters = [] 91 | # tuple (chapter_name, [pageid] (start,stop), chapter_text) 92 | create_chapter = lambda page_start,name_top,name_bottom: SimpleNamespace( 93 | name=[], 94 | name_top=name_top, 95 | name_bottom=name_bottom, 96 | record_chapter_name = True, 97 | 98 | page_start=page_start, 99 | page_stop=None, 100 | 101 | text=[], 102 | ) 103 | cur_chapter = None 104 | 105 | # 按页遍历PDF文档 106 | for idx, page in enumerate(new_pages): 107 | page = get_text_outside_table(page) 108 | 109 | # 按行遍历页面文本 110 | for word in extract_words(page): 111 | word = SimpleNamespace(**word) 112 | 113 | # 检查行文本是否以12号字体打印，如果是，则将其作为新章节开始 114 | if word.size >= 11: # 出现chapter name 115 | if cur_chapter is None: 116 | cur_chapter = create_chapter(page.page_number, word.top, word.bottom) 117 | elif not cur_chapter.record_chapter_name or (cur_chapter.name_bottom != cur_chapter.name_bottom and cur_chapter.name_top != cur_chapter.name_top): 118 | # 不再继续写chapter name 119 | cur_chapter.page_stop = page.page_number # stop id 120 | chapters.append(cur_chapter) 121 | # 重置当前chapter信息 122 | cur_chapter = create_chapter(page.page_number, word.top, word.bottom) 123 | 124 | # print(word.size, word.top, word.bottom, word.text) 125 | cur_chapter.name.append(word.text) 126 | else: 127 | cur_chapter.record_chapter_name = False # chapter name 结束 128 | cur_chapter.text.append(word.text) 129 | else: 130 | # 处理最后一个章节 131 | cur_chapter.page_stop = page.page_number # stop id 132 | chapters.append(cur_chapter) 133 | 134 | for i in chapters: 135 | logging.info(f"section: {i.name} pages:{i.page_start, i.page_stop} word-count:{len(i.text)}") 136 | logging.debug(" ".join(i.text)) 137 | 138 | title = " ".join(title) 139 | user_info = " ".join(user_info) 140 | text = f"Article Title: {title}, Information:{user_info}\n" 141 | for idx, chapter in enumerate(chapters): 142 | chapter.name = " ".join(chapter.name) 143 | text += f"The {idx}th Chapter {chapter.name}: " + " ".join(chapter.text) + "\n" 144 | 145 | logging.getLogger().setLevel(level) 146 | return Document(page_content=text, metadata={"title": title}) 147 | 148 | 149 | if __name__ == '__main__': 150 | # Test code 151 | z = parse_pdf("./build/test.pdf") 152 | print(z["user_info"]) 153 | print(z["title"]) 154 | 155 | -------------------------------------------------------------------------------- /modules/models/minimax.py: -------------------------------------------------------------------------------- 1 | import json 2 | import os 3 | 4 | import colorama 5 | import requests 6 | import logging 7 | 8 | from modules.models.base_model import BaseLLMModel 9 | from modules.presets import STANDARD_ERROR_MSG, GENERAL_ERROR_MSG, TIMEOUT_STREAMING, TIMEOUT_ALL, i18n 10 | 11 | group_id = os.environ.get("MINIMAX_GROUP_ID", "") 12 | 13 | 14 | class MiniMax_Client(BaseLLMModel): 15 | """ 16 | MiniMax Client 17 | 接口文档见 https://api.minimax.chat/document/guides/chat 18 | """ 19 | 20 | def __init__(self, model_name, api_key, user_name="", system_prompt=None): 21 | super().__init__(model_name=model_name, user=user_name) 22 | self.url = f'https://api.minimax.chat/v1/text/chatcompletion?GroupId={group_id}' 23 | self.history = [] 24 | self.api_key = api_key 25 | self.system_prompt = system_prompt 26 | self.headers = { 27 | "Authorization": f"Bearer {api_key}", 28 | "Content-Type": "application/json" 29 | } 30 | 31 | def get_answer_at_once(self): 32 | # minimax temperature is (0,1] and base model temperature is [0,2], and yuan 0.9 == base 1 so need to convert 33 | temperature = self.temperature * 0.9 if self.temperature <= 1 else 0.9 + (self.temperature - 1) / 10 34 | 35 | request_body = { 36 | "model": self.model_name.replace('minimax-', ''), 37 | "temperature": temperature, 38 | "skip_info_mask": True, 39 | 'messages': [{"sender_type": "USER", "text": self.history[-1]['content']}] 40 | } 41 | if self.n_choices: 42 | request_body['beam_width'] = self.n_choices 43 | if self.system_prompt: 44 | request_body['prompt'] = self.system_prompt 45 | if self.max_generation_token: 46 | request_body['tokens_to_generate'] = self.max_generation_token 47 | if self.top_p: 48 | request_body['top_p'] = self.top_p 49 | 50 | response = requests.post(self.url, headers=self.headers, json=request_body) 51 | 52 | res = response.json() 53 | answer = res['reply'] 54 | total_token_count = res["usage"]["total_tokens"] 55 | return answer, total_token_count 56 | 57 | def get_answer_stream_iter(self): 58 | response = self._get_response(stream=True) 59 | if response is not None: 60 | iter = self._decode_chat_response(response) 61 | partial_text = "" 62 | for i in iter: 63 | partial_text += i 64 | yield partial_text 65 | else: 66 | yield STANDARD_ERROR_MSG + GENERAL_ERROR_MSG 67 | 68 | def _get_response(self, stream=False): 69 | minimax_api_key = self.api_key 70 | history = self.history 71 | logging.debug(colorama.Fore.YELLOW + 72 | f"{history}" + colorama.Fore.RESET) 73 | headers = { 74 | "Content-Type": "application/json", 75 | "Authorization": f"Bearer {minimax_api_key}", 76 | } 77 | 78 | temperature = self.temperature * 0.9 if self.temperature <= 1 else 0.9 + (self.temperature - 1) / 10 79 | 80 | messages = [] 81 | for msg in self.history: 82 | if msg['role'] == 'user': 83 | messages.append({"sender_type": "USER", "text": msg['content']}) 84 | else: 85 | messages.append({"sender_type": "BOT", "text": msg['content']}) 86 | 87 | request_body = { 88 | "model": self.model_name.replace('minimax-', ''), 89 | "temperature": temperature, 90 | "skip_info_mask": True, 91 | 'messages': messages 92 | } 93 | if self.n_choices: 94 | request_body['beam_width'] = self.n_choices 95 | if self.system_prompt: 96 | lines = self.system_prompt.splitlines() 97 | if lines[0].find(":") != -1 and len(lines[0]) < 20: 98 | request_body["role_meta"] = { 99 | "user_name": lines[0].split(":")[0], 100 | "bot_name": lines[0].split(":")[1] 101 | } 102 | lines.pop() 103 | request_body["prompt"] = "\n".join(lines) 104 | if self.max_generation_token: 105 | request_body['tokens_to_generate'] = self.max_generation_token 106 | else: 107 | request_body['tokens_to_generate'] = 512 108 | if self.top_p: 109 | request_body['top_p'] = self.top_p 110 | 111 | if stream: 112 | timeout = TIMEOUT_STREAMING 113 | request_body['stream'] = True 114 | request_body['use_standard_sse'] = True 115 | else: 116 | timeout = TIMEOUT_ALL 117 | try: 118 | response = requests.post( 119 | self.url, 120 | headers=headers, 121 | json=request_body, 122 | stream=stream, 123 | timeout=timeout, 124 | ) 125 | except: 126 | return None 127 | 128 | return response 129 | 130 | def _decode_chat_response(self, response): 131 | error_msg = "" 132 | for chunk in response.iter_lines(): 133 | if chunk: 134 | chunk = chunk.decode() 135 | chunk_length = len(chunk) 136 | print(chunk) 137 | try: 138 | chunk = json.loads(chunk[6:]) 139 | except json.JSONDecodeError: 140 | print(i18n("JSON解析错误,收到的内容: ") + f"{chunk}") 141 | error_msg += chunk 142 | continue 143 | if chunk_length > 6 and "delta" in chunk["choices"][0]: 144 | if "finish_reason" in chunk["choices"][0] and chunk["choices"][0]["finish_reason"] == "stop": 145 | self.all_token_counts.append(chunk["usage"]["total_tokens"] - sum(self.all_token_counts)) 146 | break 147 | try: 148 | yield chunk["choices"][0]["delta"] 149 | except Exception as e: 150 | logging.error(f"Error: {e}") 151 | continue 152 | if error_msg: 153 | try: 154 | error_msg = json.loads(error_msg) 155 | if 'base_resp' in error_msg: 156 | status_code = error_msg['base_resp']['status_code'] 157 | status_msg = error_msg['base_resp']['status_msg'] 158 | raise Exception(f"{status_code} - {status_msg}") 159 | except json.JSONDecodeError: 160 | pass 161 | raise Exception(error_msg) 162 | -------------------------------------------------------------------------------- /modules/index_func.py: -------------------------------------------------------------------------------- 1 | import PyPDF2 2 | from langchain_community.embeddings.huggingface import HuggingFaceEmbeddings 3 | from langchain_community.vectorstores import FAISS 4 | from langchain_openai import OpenAIEmbeddings, AzureOpenAIEmbeddings 5 | from tqdm import tqdm 6 | 7 | from modules.config import local_embedding 8 | from modules.utils import * 9 | 10 | 11 | def get_documents(file_src): 12 | from langchain.schema import Document 13 | from langchain.text_splitter import TokenTextSplitter 14 | 15 | text_splitter = TokenTextSplitter(chunk_size=500, chunk_overlap=30) 16 | 17 | documents = [] 18 | logging.debug("Loading documents...") 19 | logging.debug(f"file_src: {file_src}") 20 | for file in file_src: 21 | filepath = file.name 22 | filename = os.path.basename(filepath) 23 | file_type = os.path.splitext(filename)[1] 24 | logging.info(f"loading file: {filename}") 25 | texts = None 26 | try: 27 | if file_type == ".pdf": 28 | logging.debug("Loading PDF...") 29 | try: 30 | from modules.config import advance_docs 31 | from modules.pdf_func import parse_pdf 32 | 33 | two_column = advance_docs["pdf"].get("two_column", False) 34 | pdftext = parse_pdf(filepath, two_column).text 35 | except: 36 | pdftext = "" 37 | with open(filepath, "rb") as pdfFileObj: 38 | pdfReader = PyPDF2.PdfReader(pdfFileObj) 39 | for page in tqdm(pdfReader.pages): 40 | pdftext += page.extract_text() 41 | texts = [Document(page_content=pdftext, metadata={"source": filepath})] 42 | elif file_type == ".docx": 43 | logging.debug("Loading Word...") 44 | from langchain.document_loaders import \ 45 | UnstructuredWordDocumentLoader 46 | 47 | loader = UnstructuredWordDocumentLoader(filepath) 48 | texts = loader.load() 49 | elif file_type == ".pptx": 50 | logging.debug("Loading PowerPoint...") 51 | from langchain.document_loaders import \ 52 | UnstructuredPowerPointLoader 53 | 54 | loader = UnstructuredPowerPointLoader(filepath) 55 | texts = loader.load() 56 | elif file_type == ".epub": 57 | logging.debug("Loading EPUB...") 58 | from langchain.document_loaders import UnstructuredEPubLoader 59 | 60 | loader = UnstructuredEPubLoader(filepath) 61 | texts = loader.load() 62 | elif file_type == ".xlsx": 63 | logging.debug("Loading Excel...") 64 | text_list = excel_to_string(filepath) 65 | texts = [] 66 | for elem in text_list: 67 | texts.append( 68 | Document(page_content=elem, metadata={"source": filepath}) 69 | ) 70 | elif file_type in [ 71 | ".jpg", 72 | ".jpeg", 73 | ".png", 74 | ".heif", 75 | ".heic", 76 | ".webp", 77 | ".bmp", 78 | ".gif", 79 | ".tiff", 80 | ".tif", 81 | ]: 82 | raise gr.Warning( 83 | i18n("不支持的文件: ") 84 | + filename 85 | + i18n("，请使用 .pdf, .docx, .pptx, .epub, .xlsx 等文档。") 86 | ) 87 | else: 88 | logging.debug("Loading text file...") 89 | from langchain.document_loaders import TextLoader 90 | 91 | loader = TextLoader(filepath, "utf8") 92 | texts = loader.load() 93 | except Exception as e: 94 | import traceback 95 | 96 | logging.error(f"Error loading file: {filename}") 97 | traceback.print_exc() 98 | 99 | if texts is not None: 100 | texts = text_splitter.split_documents(texts) 101 | documents.extend(texts) 102 | logging.debug("Documents loaded.") 103 | return documents 104 | 105 | 106 | def construct_index( 107 | api_key, 108 | file_src, 109 | max_input_size=4096, 110 | num_outputs=5, 111 | max_chunk_overlap=20, 112 | chunk_size_limit=600, 113 | embedding_limit=None, 114 | separator=" ", 115 | load_from_cache_if_possible=True, 116 | ): 117 | if api_key: 118 | os.environ["OPENAI_API_KEY"] = api_key 119 | else: 120 | # 由于一个依赖的愚蠢的设计，这里必须要有一个API KEY 121 | os.environ["OPENAI_API_KEY"] = "sk-xxxxxxx" 122 | logging.debug(f"api base: {os.environ.get('OPENAI_API_BASE', None)}") 123 | chunk_size_limit = None if chunk_size_limit == 0 else chunk_size_limit 124 | embedding_limit = None if embedding_limit == 0 else embedding_limit 125 | separator = " " if separator == "" else separator 126 | 127 | index_name = get_file_hash(file_src) 128 | index_path = f"./index/{index_name}" 129 | if local_embedding: 130 | embeddings = HuggingFaceEmbeddings( 131 | model_name="sentence-transformers/distiluse-base-multilingual-cased-v2" 132 | ) 133 | else: 134 | if os.environ.get("OPENAI_API_TYPE", "openai") == "openai": 135 | embeddings = OpenAIEmbeddings( 136 | openai_api_base=os.environ.get("OPENAI_API_BASE", None), 137 | openai_api_key=os.environ.get("OPENAI_EMBEDDING_API_KEY", api_key), 138 | model="text-embedding-3-large", 139 | ) 140 | else: 141 | embeddings = AzureOpenAIEmbeddings( 142 | deployment=os.environ["AZURE_EMBEDDING_DEPLOYMENT_NAME"], 143 | openai_api_key=os.environ["AZURE_OPENAI_API_KEY"], 144 | model=os.environ["AZURE_EMBEDDING_MODEL_NAME"], 145 | azure_endpoint=os.environ["AZURE_OPENAI_API_BASE_URL"], 146 | openai_api_type="azure", 147 | ) 148 | if os.path.exists(index_path) and load_from_cache_if_possible: 149 | logging.info(i18n("找到了缓存的索引文件，加载中……")) 150 | return FAISS.load_local( 151 | index_path, embeddings, allow_dangerous_deserialization=True 152 | ) 153 | else: 154 | documents = get_documents(file_src) 155 | logging.debug(i18n("构建索引中……")) 156 | if documents: 157 | with retrieve_proxy(): 158 | index = FAISS.from_documents(documents, embeddings) 159 | else: 160 | raise Exception(i18n("没有找到任何支持的文档。")) 161 | logging.debug(i18n("索引构建完成！")) 162 | os.makedirs("./index", exist_ok=True) 163 | index.save_local(index_path) 164 | logging.debug(i18n("索引已保存至本地!")) 165 | return index 166 | -------------------------------------------------------------------------------- /web_assets/javascript/chat-list.js: -------------------------------------------------------------------------------- 1 | var currentChatName = null; 2 | var isChatListRecentlyEnabled = false; 3 | 4 | function setChatListHeader() { 5 | var grHistoryRefreshBtn = gradioApp().querySelector('button#gr-history-refresh-btn'); 6 | var grHistoryUploadBtn = gradioApp().querySelector('button#gr-history-upload-btn'); 7 | 8 | grHistoryRefreshBtn.className = ""; 9 | grHistoryUploadBtn.className = ""; 10 | 11 | grHistoryRefreshBtn.innerHTML = HistoryRefreshIcon; 12 | grHistoryUploadBtn.innerHTML = HistoryUploadIcon; 13 | } 14 | 15 | function setChatList() { 16 | exportBtnCheck(); 17 | var selectedChat = null; 18 | var chatList = gradioApp().querySelector('fieldset#history-select-dropdown'); 19 | selectedChat = chatList.querySelector("label.selected"); 20 | if (!selectedChat) { 21 | currentChatName = null; 22 | return; 23 | } 24 | 25 | currentChatName = selectedChat.querySelector('span').innerText; 26 | 27 | if (selectedChat.classList.contains('added-chat-btns')) { 28 | return; 29 | } 30 | 31 | chatList.querySelector('.chat-selected-btns')?.remove(); // remove old buttons 32 | chatList.querySelectorAll('.added-chat-btns').forEach(chat => chat.classList.remove('added-chat-btns')); 33 | 34 | var ChatSelectedBtns = document.createElement('div'); 35 | ChatSelectedBtns.classList.add('chat-selected-btns'); 36 | selectedChat.classList.add('added-chat-btns'); 37 | ChatSelectedBtns.innerHTML = selectedChatBtns; 38 | 39 | var renameBtn = ChatSelectedBtns.querySelector('#history-rename-btn'); 40 | renameBtn.addEventListener('click', function () { 41 | gradioApp().querySelector('#gr-history-save-btn').click(); 42 | }); 43 | 44 | var deleteBtn = ChatSelectedBtns.querySelector('#history-delete-btn'); 45 | deleteBtn.addEventListener('click', function () { 46 | gradioApp().querySelector('#gr-history-delete-btn').click(); 47 | }); 48 | selectedChat.appendChild(ChatSelectedBtns); 49 | 50 | return; 51 | } 52 | 53 | function disableChatListClick() { 54 | var chatList = gradioApp().querySelector('fieldset#history-select-dropdown'); 55 | if (chatList.querySelector('label').style.pointerEvents !== 'none' && !isChatListRecentlyEnabled) { 56 | chatList.querySelectorAll('label').forEach(label => { 57 | label.style.transition = 'opacity 0.1s ease'; 58 | label.style.pointerEvents = 'none'; 59 | label.style.opacity = '0.72'; 60 | }); 61 | } 62 | } 63 | function enableChatListClick() { 64 | var chatList = gradioApp().querySelector('fieldset#history-select-dropdown'); 65 | if (chatList.querySelector('label').style.pointerEvents !== 'auto') { 66 | chatList.querySelectorAll('label').forEach(label => { 67 | label.style.transition = 'opacity 0.2s ease'; 68 | label.style.pointerEvents = 'auto'; 69 | label.style.opacity = '1'; 70 | }); 71 | isChatListRecentlyEnabled = true; 72 | setTimeout(() => { 73 | isChatListRecentlyEnabled = false; 74 | }, 500); // 避免短时间内多次调用造成闪烁 75 | } 76 | } 77 | 78 | function exportBtnCheck() { 79 | var grHistoryExportBtn = gradioApp().querySelector('#gr-history-download-json-btn'); 80 | var exportBtn = gradioApp().querySelector('#export-chat-btn'); 81 | exportBtn.disabled = grHistoryExportBtn.disabled; 82 | exportBtn.classList.toggle('disabled', grHistoryExportBtn.disabled); 83 | } 84 | 85 | function saveChatHistory(a, b, c, d) { 86 | var fileName = b; 87 | 88 | while (true) { 89 | var result = prompt(renameChat_i18n, fileName); 90 | 91 | if (result === null) { 92 | throw new Error("rename operation cancelled"); 93 | // 不返回原文件名，而是使用 throw new Error() 打断程序，避免 gradio 进行保存操作 94 | // break; 95 | } else if (isValidFileName(result)) { 96 | return [a, result, c, d]; 97 | } else { 98 | alert(validFileName_i18n + "!@#$%^&*()<>?/\\|}{~:"); 99 | } 100 | } 101 | return [a, b, c, d]; // 兜底保障 102 | } 103 | 104 | function isValidFileName(fileName) { 105 | // 使用正则表达式来检查文件名是否包含不合格字符 106 | var regex = /[!@#$%^&*()<>?/\\|}{~:]/; 107 | return !regex.test(fileName) && fileName.trim() !== ""; 108 | } 109 | 110 | const selectedChatBtns = ` 111 | 112 | 113 | ` 114 | const HistoryRefreshIcon = ''; 115 | const HistoryUploadIcon = ''; -------------------------------------------------------------------------------- /web_assets/html/chatbot_more.html: -------------------------------------------------------------------------------- 1 |
2 |
3 | 4 |
5 | 9 |
10 | 11 |
12 | 16 |
17 | 18 | 19 | 20 |
21 | 40 |
41 | 42 |
43 | 44 | 45 |
46 | 71 |
72 |
-------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 |
2 | 3 | 简体中文 | English | 日本語 | Russian | 한국어 4 |
5 | 6 |

川虎 Chat 🐯 Chuanhu Chat

7 |
8 | 9 | Logo 10 | 11 | 12 |

13 |

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

14 |

15 | 16 | Tests Passing 17 | 18 | 19 | GitHub Contributors 20 | 21 | 22 | GitHub pull requests 23 | 24 |

25 | 支持 DeepSeek R1 & GPT 4 · 基于文件问答 · LLM本地部署 · 联网搜索 · Agent 助理 · 支持 Fine-tune 26 |

27 | 视频教程 28 | · 29 | 2.0介绍视频 30 | || 31 | 在线体验 32 | · 33 | 一键部署 34 |

35 |

36 |
37 | 38 | > 📢 新增：现已支持 GPT-5（含 GPT-5、GPT-5-mini、GPT-5-nano；400k 上下文、最多 128k 输出）。 39 | 40 | [![Video Title](https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/51039745/0eee1598-c2fd-41c6-bda9-7b059a3ce6e7.jpg)](https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/51039745/0eee1598-c2fd-41c6-bda9-7b059a3ce6e7?autoplay=1) 41 | 42 | ## 目录 43 | 44 | | [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) | [加入Telegram群组](https://t.me/tkdifferent) | 45 | | --- | --- | --- | --- | --- | --- | 46 | 47 | ## ✨ 5.0 重磅更新！ 48 | 49 | ![ChuanhuChat5更新](https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/70903329/f2c2be3a-ea93-4edf-8221-94eddd4a0178) 50 | 51 | 52 | New! 全新的用户界面！精致得不像 Gradio，甚至有毛玻璃效果！ 53 | 54 | New! 适配了移动端（包括全面屏手机的挖孔/刘海），层级更加清晰。 55 | 56 | New! 历史记录移到左侧，使用更加方便。并且支持搜索（支持正则）、删除、重命名。 57 | 58 | New! 现在可以让大模型自动命名历史记录（需在设置或配置文件中开启）。 59 | 60 | New! 现在可以将 川虎Chat 作为 PWA 应用程序安装，体验更加原生！支持 Chrome/Edge/Safari 等浏览器。 61 | 62 | New! 图标适配各个平台，看起来更舒服。 63 | 64 | New! 支持 Finetune（微调） GPT 3.5！ 65 | 66 | 67 | ## 支持模型 68 | 69 | | API 调用模型 | 备注 | 本地部署模型 | 备注 | 70 | | :---: | --- | :---: | --- | 71 | | [ChatGPT(GPT-5、GPT-4、GPT-4o、o1)](https://chat.openai.com) | 支持微调 gpt-3.5 | [ChatGLM](https://github.com/THUDM/ChatGLM-6B) ([ChatGLM2](https://github.com/THUDM/ChatGLM2-6B)) ([ChatGLM3](https://huggingface.co/THUDM/chatglm3-6b)) || 72 | | [Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service) | | [LLaMA](https://github.com/facebookresearch/llama) | 支持 Lora 模型 | 73 | | [Google Gemini Pro](https://ai.google.dev/gemini-api/docs/api-key?hl=zh-cn) | | [StableLM](https://github.com/Stability-AI/StableLM) || 74 | | [讯飞星火认知大模型](https://xinghuo.xfyun.cn) | | [MOSS](https://github.com/OpenLMLab/MOSS) || 75 | | [Inspur Yuan 1.0](https://air.inspur.com/home) | | [通义千问](https://github.com/QwenLM/Qwen/tree/main) || 76 | | [MiniMax](https://api.minimax.chat/) ||[DeepSeek](https://platform.deepseek.com)|| 77 | | [XMChat](https://github.com/MILVLG/xmchat) | 不支持流式传输||| 78 | | [Midjourney](https://www.midjourney.com/) | 不支持流式传输||| 79 | | [Claude](https://www.anthropic.com/) | ✨ 现已支持Claude 3 Opus、Sonnet，Haiku将会在推出后的第一时间支持||| 80 | | DALL·E 3 |||| 81 | 82 | ## 使用技巧 83 | 84 | ### 💪 强力功能 85 | - **川虎助理**：类似 AutoGPT，全自动解决你的问题； 86 | - **在线搜索**：ChatGPT 的数据太旧？给 LLM 插上网络的翅膀； 87 | - **知识库**：让 ChatGPT 帮你量子速读！根据文件回答问题。 88 | - **本地部署LLM**：一键部署，获取属于你自己的大语言模型。 89 | - **GPT 3.5微调**：支持微调 GPT 3.5，让 ChatGPT 更加个性化。 90 | - **[自定义模型](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/%E8%87%AA%E5%AE%9A%E4%B9%89%E6%A8%A1%E5%9E%8B-Custom-Models)**：灵活地自定义模型，例如对接本地推理服务。 91 | 92 | ### 🤖 System Prompt 93 | - 通过 System Prompt 设定前提条件，可以很有效地进行角色扮演； 94 | - 川虎Chat 预设了Prompt模板，点击`加载Prompt模板`，先选择 Prompt 模板集合，然后在下方选择想要的 Prompt。 95 | 96 | ### 💬 基础对话 97 | - 如果回答不满意，可以使用 `重新生成` 按钮再试一次，或者直接 `删除这轮对话`; 98 | - 输入框支持换行，按 Shift + Enter即可； 99 | - 在输入框按 ↑ ↓ 方向键，可以在发送记录中快速切换； 100 | - 每次新建一个对话太麻烦，试试 `单论对话` 功能； 101 | - 回答气泡旁边的小按钮，不仅能 `一键复制`，还能 `查看Markdown原文`； 102 | - 指定回答语言，让 ChatGPT 固定以某种语言回答。 103 | 104 | ### 📜 对话历史 105 | - 对话历史记录会被自动保存，不用担心问完之后找不到了； 106 | - 多用户历史记录隔离，除了你都看不到； 107 | - 重命名历史记录，方便日后查找； 108 | - New! 魔法般自动命名历史记录，让 LLM 理解对话内容，帮你自动为历史记录命名！ 109 | - New! 搜索历史记录，支持正则表达式！ 110 | 111 | ### 🖼️ 小而美的体验 112 | - 自研 Small-and-Beautiful 主题，带给你小而美的体验； 113 | - 自动亮暗色切换，给你从早到晚的舒适体验； 114 | - 完美渲染 LaTeX / 表格 / 代码块，支持代码高亮； 115 | - New! 非线性动画、毛玻璃效果，精致得不像 Gradio！ 116 | - New! 适配 Windows / macOS / Linux / iOS / Android，从图标到全面屏适配，给你最合适的体验！ 117 | - New! 支持以 PWA应用程序 安装，体验更加原生！ 118 | 119 | ### 👨‍💻 极客功能 120 | - New! 支持 Fine-tune（微调）gpt-3.5！ 121 | - 大量 LLM 参数可调； 122 | - 支持更换 api-host； 123 | - 支持自定义代理； 124 | - 支持多 api-key 负载均衡。 125 | 126 | ### ⚒️ 部署相关 127 | - 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>,`。 128 | - 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。 129 | - 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。 130 | 131 | ## 快速上手 132 | 133 | 在终端执行以下命令： 134 | 135 | ```shell 136 | git clone https://github.com/GaiZhenbiao/ChuanhuChatGPT.git 137 | cd ChuanhuChatGPT 138 | pip install -r requirements.txt 139 | ``` 140 | 141 | 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。 142 | 143 | ```shell 144 | python ChuanhuChatbot.py 145 | ``` 146 | 147 | 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。 148 | 149 | > **Note** 150 | > 151 | > 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)。 152 | 153 | ## 疑难杂症解决 154 | 155 | 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1** 并 **更新依赖库2**，然后重试。步骤为： 156 | 157 | 1. 点击网页上的 `Download ZIP` 按钮，下载最新代码并解压覆盖，或 158 | ```shell 159 | git pull https://github.com/GaiZhenbiao/ChuanhuChatGPT.git main -f 160 | ``` 161 | 2. 尝试再次安装依赖（可能本项目引入了新的依赖） 162 | ``` 163 | pip install -r requirements.txt 164 | ``` 165 | 166 | 很多时候，这样就可以解决问题。 167 | 168 | 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) 169 | 170 | 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**。 171 | 172 | ## 了解更多 173 | 174 | 若需了解更多信息，请查看我们的 [wiki](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki)： 175 | 176 | - [想要做出贡献？](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/贡献指南) 177 | - [项目更新情况？](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/更新日志) 178 | - [二次开发许可？](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用许可) 179 | - [如何引用项目？](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用许可#如何引用该项目) 180 | 181 | ## Starchart 182 | 183 | [![Star History Chart](https://api.star-history.com/svg?repos=GaiZhenbiao/ChuanhuChatGPT&type=Date)](https://star-history.com/#GaiZhenbiao/ChuanhuChatGPT&Date) 184 | 185 | ## Contributors 186 | 187 | 188 | 189 | 190 | 191 | ## 捐款 192 | 193 | 🐯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～ 194 | 195 | 联系作者：请去[我的bilibili账号](https://space.bilibili.com/29125536)私信我。 196 | 197 | Buy Me A Coffee 198 | 199 | image 200 | -------------------------------------------------------------------------------- /readme/README_ja.md: -------------------------------------------------------------------------------- 1 |
2 | 3 | 简体中文 | English | 日本語 | Russian | 한국어 4 |
5 | 6 |

川虎 Chat 🐯 Chuanhu Chat

7 |
8 | 9 | Logo 10 | 11 | 12 |

13 |

ChatGPT/ChatGLM/LLaMAなどのLLMのための軽量でユーザーフレンドリーなWeb-UI

14 |

15 | 16 | Tests Passing 17 | 18 | 19 | GitHub Contributors 20 | 21 | 22 | GitHub pull requests 23 | 24 |

25 | GPT-4対応 · ファイルへの質問チャット · LLMのローカルデプロイ可能 · ウェブ検索 · エージェントアシスタント · Fine-tuneをサポートします 26 |

27 | 動画チュートリアル 28 | · 29 | 2.0 イントロダクション 30 | · 31 | 3.0 イントロダクション & チュートリアル 32 | || 33 | オンライントライアル 34 | · 35 | ワンクリックデプロイ 36 |

37 |

38 |
39 | 40 | > 新着: GPT-5 ファミリー（GPT-5 / GPT-5-mini / GPT-5-nano）に対応。40万トークンのコンテキスト、最大 12.8万トークンの出力。 41 | 42 | [![Video Title](https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/51039745/0eee1598-c2fd-41c6-bda9-7b059a3ce6e7.jpg)](https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/51039745/0eee1598-c2fd-41c6-bda9-7b059a3ce6e7?autoplay=1) 43 | 44 | ## ✨ 5.0の重要な更新！ 45 | 46 | ![ChuanhuChat5更新](https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/70903329/f2c2be3a-ea93-4edf-8221-94eddd4a0178) 47 | 48 | 新! 全く新しいユーザーインターフェース！Gradioに比べて精緻で、さらにフロストガラス効果があります！ 49 | 50 | 新! モバイル端末（画面全体のスマホのパンチホール/ノッチを含む）に対応し、レイヤーがはっきりしてきました。 51 | 52 | 新! 履歴が左側に移動し、使いやすくなりました。また、検索（正規表現対応）、削除、リネームが可能です。 53 | 54 | 新! 大きなモデルによる履歴の自動命名が可能になりました（設定または設定ファイルで有効化が必要）。 55 | 56 | 新! 今では 川虎チャット を PWAアプリケーションとしてインストールすることも可能で、よりネイティブな体験ができます！Chrome/Edge/Safariなどのブラウザをサポート。 57 | 58 | 新! 各プラットフォームに適したアイコンで、見ていても気持ちがいい。 59 | 60 | 新! Finetune（微調整）GPT 3.5に対応！ 61 | 62 | ## モデルのサポート 63 | 64 | | API呼び出しモデル | 備考 | ローカルデプロイモデル | 備考 | 65 | | :---: | --- | :---: | --- | 66 | | [ChatGPT(GPT-5、GPT-4、GPT-4o、o1)](https://chat.openai.com) | gpt-3.5の微調整をサポート | [ChatGLM](https://github.com/THUDM/ChatGLM-6B) ([ChatGLM2](https://github.com/THUDM/ChatGLM2-6B)) ([ChatGLM3](https://huggingface.co/THUDM/chatglm3-6b)) || 67 | | [Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service) | | [LLaMA](https://github.com/facebookresearch/llama) | Loraモデルのサポートあり | 68 | | [Google Gemini Pro](https://ai.google.dev/gemini-api/docs/api-key?hl=zh-cn) | | [StableLM](https://github.com/Stability-AI/StableLM)|| 69 | | [讯飞星火认知大模型](https://xinghuo.xfyun.cn) | | [MOSS](https://github.com/OpenLMLab/MOSS)|| 70 | | [Inspur Yuan 1.0](https://air.inspur.com/home) | | [Qwen](https://github.com/QwenLM/Qwen/tree/main)|| 71 | | [MiniMax](https://api.minimax.chat/) |||| 72 | | [XMChat](https://github.com/MILVLG/xmchat) | ストリーミング転送はサポートされていません||| 73 | | [Midjourney](https://www.midjourney.com/) | ストリーミング転送はサポートされていません||| 74 | | [Claude](https://www.anthropic.com/) |||| 75 | 76 | ## 使う上でのTips 77 | 78 | ### 💪 パワフルな機能 79 | - **川虎助理**：AutoGPTに似ており、自動的に問題を解決します。 80 | - **オンライン検索**：ChatGPTのデータが古い場合は、LLMにネットワークの翼を付けます。 81 | - **ナレッジベース**：ChatGPTがあなたをクイックリーディングの世界へご招待！ファイルに基づいて質問に答えます。 82 | - **LLMのローカルデプロイ**：ワンクリックであなた自身の大規模言語モデルをデプロイします。 83 | - **GPT 3.5微調整**：ChatGPTをよりパーソナライズするためのGPT 3.5の微調整をサポートします。 84 | - **[カスタムモデル](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/%E8%87%AA%E5%AE%9A%E4%B9%89%E6%A8%A1%E5%9E%8B-Custom-Models)**：例えば、ローカル推論サービスに接続するなど、モデルを柔軟にカスタマイズします。 85 | 86 | ### 🤖 システムプロンプト 87 | - システムプロンプトを使用して前提条件を設定すると、ロールプレイが効果的に行えます。 88 | - 川虎Chatはプロンプトテンプレートを予め設定しており、「プロンプトテンプレートを読み込む」をクリックして、まずプロンプトテンプレートコレクションを選択し、次に下部で希望のプロンプトを選択します。 89 | 90 | ### 💬 ベーシックな対話 91 | - もし回答が満足できない場合、「再生成」ボタンを使用して再試行するか、直接「このラウンドの対話を削除」することができます。 92 | - 入力ボックスは改行をサポートしており、 Shift + Enter を押すと改行できます。 93 | - 入力ボックスで ↑ ↓ キーを押すと、送信履歴をスピーディに切り替えることができます。 94 | - 各対話を新しく作成するのは面倒ですか？「単発対話」機能を試してみてください。 95 | - 回答バブルの横の小さなボタンは「一括コピー」だけでなく、「Markdownの元のテキストを表示」もできます。 96 | - 回答の言語を指定して、ChatGPTが特定の言語で回答するようにします。 97 | 98 | ### 📜 履歴記録 99 | - ダイアログの履歴は自動的に保存されるので、完了後に見つけることができます。 100 | - 複数のユーザーの履歴は分離されており、他のユーザーは閲覧できません。 101 | - 履歴の名前を変更することで、将来的な検索を容易にします。 102 | - 新! マジカルな自動履歴名付け機能で、LLMが対話内容を理解し、履歴に自動的に名前をつけてくれます！ 103 | - 新! 正規表現をサポートする履歴検索！ 104 | 105 | ### 🖼️ シンプルな使いやすさ 106 | - 独自のSmall-and-Beautifulテーマで、シンプルで美しい体験を提供します。 107 | - 自動的な明暗の切り替えで、早朝から夜まで快適な体験ができます。 108 | - LaTeX/テーブル/コードブロックを完璧にレンダリングし、コードハイライトがサポートされています。 109 | - 新! ノンリニアアニメーション、フロストガラスの効果など、Gradioのように洗練されています！ 110 | - 新! Windows / macOS / Linux / iOS / Androidに対応し、アイコンからフルスクリーンまで、最適な体験を提供します！ 111 | - 新! PWAアプリケーションのインストールがサポートされており、よりネイティブな体験ができます！ 112 | 113 | ### 👨‍💻 ギーク向け機能 114 | - 新! gpt-3.5のFine-tune（微調整）がサポートされています！ 115 | - 多くのLLMパラメータをカスタマイズできます。 116 | - api-hostの変更が可能です。 117 | - カスタムプロキシの設定が可能です。 118 | - 負荷分散のための複数のapiキーのサポートがあります。 119 | 120 | ### ⚒️ デプロイに関する情報 121 | - サーバーへのデプロイ：`config.json`ファイルで`"server_name": "0.0.0.0", "server_port": <あなたのポート番号>,"`を設定します。 122 | - 共有リンクの取得：`config.json`ファイルで`"share": true,`を設定します。ただし、プログラムが実行されている必要があります。 123 | - Hugging Faceでの使用：右上のコーナーの「Spaceをコピー」を選択し、それから使用することをおすすめします。これにより、アプリの反応が速くなる場合があります。 124 | 125 | 126 | ## クイックスタート 127 | 128 | ```shell 129 | git clone https://github.com/GaiZhenbiao/ChuanhuChatGPT.git 130 | cd ChuanhuChatGPT 131 | pip install -r requirements.txt 132 | ``` 133 | 134 | 次に `config_example.json`をコピーして `config.json`にリネームし、そのファイルにAPI-Keyなどの設定を記入する。 135 | 136 | ```shell 137 | python ChuanhuChatbot.py 138 | ``` 139 | 140 | ブラウザのウィンドウが開き、ChatGPTとチャットできるようになります。 141 | 142 | > **Note** 143 | > 144 | > 詳しい手順は[wikiページ](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用教程)をご確認ください。 145 | 146 | ## トラブルシューティング 147 | 148 | 問題が発生した場合は、まずこのプロジェクトの最新の変更点を手動で引っ張ってみるのがよいでしょう。その手順は以下の通りです： 149 | 150 | 1. ウェブページの `Download ZIP` をクリックして最新のコードアーカイブをダウンロードするか、または 151 | ```shell 152 | git pull https://github.com/GaiZhenbiao/ChuanhuChatGPT.git main -f 153 | ``` 154 | 2. 新しい依存関係が導入されている可能性があるため、依存関係を再度インストールしてみてください。 155 | ``` 156 | pip install -r requirements.txt 157 | ``` 158 | 159 | 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。 160 | 161 | それでも問題が解決しない場合は、こちらのページをご参照ください： [よくある質問（FAQ）](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题) 162 | 163 | このページでは、考えられるほぼすべての問題点と解決策を掲載しています。よくお読みください。 164 | 165 | ## More Information 166 | 167 | より詳細な情報は、[wiki](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki) をご覧ください。: 168 | 169 | - [How to contribute a translation](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/Localization) 170 | - [How to make a contribution](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/贡献指南) 171 | - [How to cite the project](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用许可#如何引用该项目) 172 | - [Project changelog](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/更新日志) 173 | - [Project license](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用许可) 174 | 175 | ## Starchart 176 | 177 | [![Star History Chart](https://api.star-history.com/svg?repos=GaiZhenbiao/ChuanhuChatGPT&type=Date)](https://star-history.com/#GaiZhenbiao/ChuanhuChatGPT&Date) 178 | 179 | ## Contributors 180 | 181 | 182 | 183 | 184 | 185 | ## Sponsor 186 | 187 | 🐯 この企画が役に立ったら、遠慮なくコーラかコーヒーでもおごってください〜。 188 | 189 | Buy Me A Coffee 190 | 191 | image 192 | -------------------------------------------------------------------------------- /readme/README_ko.md: -------------------------------------------------------------------------------- 1 |
2 | 3 | 简体中文 | English | 日本語 | Russian | 한국어 4 |
5 | 6 |

川虎 Chat 🐯 Chuanhu Chat

7 |
8 | 9 | Logo 10 | 11 | 12 |

13 |

ChatGPT/ChatGLM/LLaMA등의 LLM을 위한 가벼운 사용자 친화적 Web-UI

14 |

15 | 16 | Tests Passing 17 | 18 | 19 | GitHub Contributors 20 | 21 | 22 | GitHub pull requests 23 | 24 |

25 | GPT-4 지원 · 파일에 대한 채팅 · LLMs 로컬 배포 · 웹 검색 · Chuanhu Agent · 파인튜닝 26 |

27 | 영상 튜토리얼 28 | · 29 | 2.0 소개 30 | · 31 | 3.0 소개 & 튜토리얼 32 | || 33 | 온라인 테스트 34 | · 35 | 원클릭 배포 36 |

37 |

38 |
39 | 40 | > 신규: 이제 GPT-5 패밀리(GPT-5 / GPT-5-mini / GPT-5-nano) 지원. 컨텍스트 40만 토큰, 최대 출력 12.8만 토큰. 41 | 42 | [![Video Title](https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/51039745/0eee1598-c2fd-41c6-bda9-7b059a3ce6e7.jpg)](https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/51039745/0eee1598-c2fd-41c6-bda9-7b059a3ce6e7?autoplay=1) 43 | 44 | ## ✨ 5.0 업데이트! 45 | 46 | ![ChuanhuChat5update](https://github.com/GaiZhenbiao/ChuanhuChatGPT/assets/70903329/f2c2be3a-ea93-4edf-8221-94eddd4a0178) 47 | 48 | 49 | New! 완전히 새로운 사용자 인터페이스! 반투명 유리효과를 지원합니다! 50 | 51 | New! 모든 모바일 장치에 적합한 UI. 52 | 53 | New! 대화 기록이 왼쪽으로 이동하여 더 편리하게 사용할 수 있습니다. 검색, 삭제, 이름 변경이 가능합니다. 54 | 55 | New! 자동으로 대화 기록의 이름을 설정할 수 있습니다. (설정에서 활성화 필요). 56 | 57 | New! Chuanhu Chat는 이제 Chrome/Edge/Safari 등 브라우저를 지원하는 PWA입니다. 58 | 59 | New! 아이콘들이 플랫폼에 맞게 조정되어, 더 자연스럽습니다. 60 | 61 | New! GPT 3.5! 파인튜닝을 지원합니다. 62 | 63 | ## 지원 모델들 64 | 65 | | API 호출 모델들 | 설명 | 로컬 배포 모델 | 설명 | 66 | |:-------------------------------------------------------------------------------------:|-----------------------|:-------------------------------------------------------------------------------------------------:|---------------------| 67 | | [ChatGPT(GPT-5、GPT-4、GPT-4o、o1)](https://chat.openai.com) | gpt-3.5 파인튜닝 지원 | [ChatGLM](https://github.com/THUDM/ChatGLM-6B) ([ChatGLM2](https://github.com/THUDM/ChatGLM2-6B)) | 68 | | [Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service) | | [LLaMA](https://github.com/facebookresearch/llama) | Lora 모델 지원 69 | | [Google PaLM](https://developers.generativeai.google/products/palm) | 스트리밍 미지원 | [StableLM](https://github.com/Stability-AI/StableLM) 70 | | [iFlytek Starfire Cognition Large Model](https://xinghuo.xfyun.cn) | | [MOSS](https://github.com/OpenLMLab/MOSS) 71 | | [Inspur Yuan 1.0](https://air.inspur.com/home) | | [Qwen](https://github.com/QwenLM/Qwen/tree/main) 72 | | [MiniMax](https://api.minimax.chat/) | 73 | | [XMChat](https://github.com/MILVLG/xmchat) | 스트리밍 미지원 74 | | [Midjourney](https://www.midjourney.com/) | 스트리밍 미지원 75 | | [Claude](https://www.anthropic.com/) | 76 | 77 | ## 사용 팁 78 | 79 | ### 💪 강력한 기능 80 | - **Chuanhu Assistant**: AutoGPT와 같이,문제를 자동으로 해결합니다. 81 | - **온라인 검색**: ChatGPT의 데이터가 너무 오래되었나요? LLM과 인터넷의 정보를 함께 사용하세요. 82 | - **Knowledge Base**: ChatGPT가 당신의 읽기 속도를 높여줍니다! 파일에 대해 질문하세요. 83 | - **LLM 로컬 배포**: 원클릭 LLM 배포로 당신만의 LLM을 가지세요. 84 | - **GPT 3.5 미세 조정**: GPT 3.5를 미세 조정하여 ChatGPT를 더욱 개성화합니다. 85 | - **[사용자 정의 모델](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/%E8%87%AA%E5%AE%9A%E4%B9%89%E6%A8%A1%E5%9E%8B-Custom-Models)**: 유연하게 모델을 사용자 정의하고, 예를 들어 로컬 추론 서비스를 연결합니다. 86 | 87 | ### 🤖 시스템 프롬프트 88 | - 시스템 프롬프트를 통해 사전 조건을 설정하면 역할극을 효과적으로 할 수 있습니다. 89 | - ChuanhuChat는 프롬프트 프리셋을 제공합니다. `프롬프트 템플릿 불러오기`탭에서 프롬프트를 불러온 후 아래 리스트에서 원하는 프롬프트를 설정하세요. 90 | 91 | ### 💬 기본 대화 92 | - 답변이 만족스럽지 않다면 `재생성` 버튼으로 다시 시도하거나 `이 라운드의 질문과 답변 삭제` 버튼을 사용할 수 있습니다. 93 | - 입력창은 줄 바꿈을 지원합니다. Shift + Enter 를 사용하세요. 94 | - 입력창에서 ↑ ↓ 를 사용해 이전 전송 기록으로 이동할 수 있습니다. 95 | - 매번 새로운 대화를 만드는 것이 귀찮다면 `단일 대화` 기능을 사용하세요; 96 | - 답변 옆의 버튼들은 `일괄 복사`, `원본 Markdown 보기` 기능을 제공합니다. 97 | - ChatGPT가 특정 언어로 응답할 수 있도록 답장 언어를 지정하세요. 98 | 99 | ### 📜 대화 기록 100 | - 대화 기록은 자동으로 저장됩니다. 101 | - 다중 사용자모드 사용시 본인 대화는 본인만 볼 수 있습니다. 102 | - 대화 기록명을 바꿔 추후 검색을 용이하게 할 수 있습니다. 103 | - New! LLM이 대화 기록을 요약하여 대화 기록명을 자동으로 설정하게 할 수 있습니다. 104 | - New! 정규식을 사용하여 검색할 수 있습니다. 105 | 106 | ### 🖼️ 간단하고 아름다운 UI 107 | - 자체 개발한 Small-and-Beautiful 테마는 간단하고 아름다운 UI를 제공합니다. 108 | - 자동 다크/라이트 테마 전환으로 아침부터 밤까지 편안한 경험을 제공합니다. 109 | - 완벽한 LaTeX / 표 / 소스 코드 렌더링; 110 | - New! 비선형 애니메이션, 반투명 유리효과 111 | - New! Windows / macOS / Linux / iOS / Android 각 플랫폼에 최적화된 경험을 제공합니다. 112 | - New! PWA앱 설치로 더 자연스러운 경험을 제공합니다. 113 | 114 | ### 👨‍💻 전문가용 기능 115 | - New! gpt-3.5 파인튜닝 제공! 116 | - LLM의 다양한 파라미터들을 조정할 수 있습니다. 117 | - API-host 변경 지원 118 | - 커스텀 프록시 제공 119 | - 다중 api키 로드밸런싱 기능 제공 120 | 121 | ### ⚒️ 배포 관련 122 | - 서버에 배포: `config.json`에서 다음 항목을 설정하세요 `"server_name": "0.0.0.0", "server_port": ,`. 123 | - 공개 주소 가져오기: `config.json`에서 다음 항목을 설정하세요 `"share": true,`. 124 | - Hugging Face에서 사용: 앱이 더 빠르게 반응할 수 있도록 우측 상단의 버튼에서 **Duplicate the Space** 를 사용하세요 125 | 126 | ## 빠른 시작 127 | 128 | 터미널에서 다음 명령을 실행합니다. 129 | 130 | ```shell 131 | git clone https://github.com/GaiZhenbiao/ChuanhuChatGPT.git 132 | cd ChuanhuChatGPT 133 | pip install -r requirements.txt 134 | ``` 135 | 136 | `config_example.json`의 복제본을 만들고, 이름을 `config.json`로 변경합니다, 이후 파일에서 API키와 다른 세팅들을 수정합니다. 137 | 138 | ```shell 139 | python ChuanhuChatbot.py 140 | ``` 141 | 142 | 브라우저가 자동으로 열리고 **Chuanhu Chat**를 사용해 ChatGPT 또는 다른 모델들을 사용할 수 있습니다. 143 | 144 | > **참고** 145 | > 146 | > [wiki page](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用教程) 에서 자세한 정보를 확인하세요 147 | 148 | 149 | ## 문제해결 150 | 151 | 문제가 발생하면 **최신 코드로 업데이트하고1** **종속성을 업데이트2** 한 후 재시도 해보세요. 단계는 다음과 같습니다.: 152 | 153 | 1. Github 웹 페이지의 `Download ZIP`버튼으로 최신 코드를 다운로드하거나 다음 코드를 사용하세요 154 | ```shell 155 | git pull https://github.com/GaiZhenbiao/ChuanhuChatGPT.git main -f 156 | ``` 157 | 2. 다음 코드로 종속성을 업데이트하세요 158 | ``` 159 | pip install -r requirements.txt 160 | ``` 161 | 162 | 보통 이 방법으로 문제가 해결됩니다. 163 | 164 | 문제가 해결되지 않는다면 다음 페이지를 확인해보세요: [Frequently Asked Questions (FAQ)](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题) 165 | 166 | 이 페이지에는 거의 대부분의 문제와 해결법이 있습니다. 자세히 읽어보세요 167 | 168 | ## 더 알아보기 169 | 170 | 더 많은 정보가 [wiki](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki) 에 있습니다. 171 | 172 | - [어떻게 번역에 기여하나요?](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/Localization) 173 | - [어떻게 이 프로젝트에 기여하나요?](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/贡献指南) 174 | - [어떻게 이 프로젝트를 인용하나요?](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用许可#如何引用该项目) 175 | - [업데이트 기록](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/更新日志) 176 | - [프로젝트 라이선스](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用许可) 177 | 178 | ## Starchart 179 | 180 | [![Star History Chart](https://api.star-history.com/svg?repos=GaiZhenbiao/ChuanhuChatGPT&type=Date)](https://star-history.com/#GaiZhenbiao/ChuanhuChatGPT&Date) 181 | 182 | ## 기여자들 183 | 184 | 185 | 186 | 187 | 188 | ## 기부 189 | 190 | 🐯 이 프로젝트가 도움이되었다면, 저에게 커피나 콜라를 사주세요~ 191 | 192 | Buy Me A Coffee 193 | 194 | image 195 | --------------------------------------------------------------------------------