jupyter-agent-extension

配合jupyter-agent工具使用的Vscode扩展插件，提高用户的使用体验。jupyter-agent是一个jupyter的扩展组件，提供%%bot命令，实现在Notebook中自动生成代码以完成指定的任务，具体见jupyer-agent项目主页。

使用方法

安装jupyter-agent

# 激活当前Notebook所使用的虚拟环境
source .venv/bin/activate

# 安装jupyter-agent
pip install jupyter-agent

安装jupyter-agent-extension

插件下载地址：jupyter-agent-extension

使用jupyter-agent

配置Notebook

在Vscode中新建或打开一个Notebook，新建一个单元格，输入并执行以下命令:

# 加载扩展的Magic命令
%load_ext jupyter_agent.bot_magics

# 设置模型调用的API地址，不同的Agent可以调用不同的模型，这里以调用lmstudio本地部署的模型为例
%config BotMagics.default_api_url = 'http://127.0.0.1:1234/v1'
%config BotMagics.default_api_key = 'API_KEY'
%config BotMagics.default_model_name = 'qwen3-30b-a3b' 
%config BotMagics.coding_model_name = 'devstral-small-2505-mlx'

# 设置当前Notebook的路径，由于vscode中运行里无法自动获取到该路径，需要手工指定
%config BotMagics.notebook_path = globals()["__vsc_ipynb_file__"]

# 设置是否支持保存任务数据到Metadata中，只有安装了jupyter-agent-extension的Vscode支持
%config BotMagics.support_save_meta = True

接下来就可以使用%%bot指令进行任务规则与代码生成的工作了。

进行全局任务规划

%%bot -P

# 全局目标（Global goal）
...

执行任务规则并生成子任务代码

%%bot [-s stage]

# Some random characters ...

具体用法见使用说明

贡献

欢迎提交 issue 或 pull request 参与贡献。

许可证

本项目基于 MIT License 开源。

EN

VSCode extension plugin for use with the jupyter-agent tool, enhancing the user experience. jupyter-agent is an extension component for Jupyter that provides the %%bot command, enabling automatic code generation in Notebooks to accomplish specified tasks. For more details, see the jupyter-agent project homepage.

Usage

Install jupyter-agent

# Activate the virtual environment used by the current notebook
source .venv/bin/activate

# Install jupyter-agent
pip install jupyter-agent

Install jupyter-agent-extension

Plugin download address: jupyter-agent-extension

Use jupyter-agent

Configure Notebook

Create or open a Notebook in Vscode, create a new cell, enter and execute the following commands:

# Load the Magic commands of the extension
%load_ext jupyter_agent.bot_magics

# Set the API address of the model to be called, different Agents can call different models, here we call the model deployed locally in lmstudio
%config BotMagics.default_api_url = 'http://127.0.0.1:1234/v1'
%config BotMagics.default_api_key = 'API_KEY'
%config BotMagics.default_model_name = 'qwen3-30b-a3b' 
%config BotMagics.coding_model_name = 'devstral-small-2505-mlx'

# Set the path of the current Notebook, which cannot be automatically obtained in vscode when running, you need to manually specify
%config BotMagics.notebook_path = globals()["__vsc_ipynb_file__"]

# Set whether to save task data to Metadata, only Vscode installed with jupyter-agent-extension supports
%config BotMagics.support_save_meta = True

Now, you can use the %%bot command to work on task rules and code generation.

Perform global task planning

%%bot -P

# Global Goal
...

Execute task rules and generate subtask code

%%bot [-s stage]

# Some random characters ...

More usage instructions can be found at README

Contribution

Welcome to submit issues or pull requests to participate in contributions.

Jupyter Agent Extension

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