🪐 🤖 Jupyter AI Agent

Use Jupyter AI Agent, an AI Agent equipped with tools like 'execute', 'insert_cell', and more, to transform your Jupyter Notebooks into an intelligent, interactive workspace!

Jupyter AI Agent <---> JupyterLab
    |            (RTC)
 JNC+JKC

- JNC https://github.com/datalayer/jupyter-nbmodel-client
- JKC https://github.com/datalayer/jupyter-kernel-client
- RTC Real Time Collaboration

Jupyter AI Agent empowers AI models to interact with and modify Jupyter Notebooks. The model is equipped with tools such as adding code cells, inserting markdown cells, executing code, enabling it to modify the notebook comprehensively based on user instructions. This agent is innovative as it is designed to operate on the entire notebook, not just at the cell level, enabling more comprehensive and seamless modifications.

This powerful functionality is made possible through jupyter-nbmodel-client and jupyter-kernel-client, enabling interaction with Jupyter notebooks and kernels.

LangChain agent framework is used to manage the interactions between the AI model and the tools.

Install

To install Jupyter AI Agent, execute:

pip install jupyter_ai_agent

Usage

Example 1: JupyterLab

The Jupyter AI Agent can directly interact with JupyterLab and the modifications made by the Jupyter AI Agent can be seen in real-time thanks to Jupyter real time collaboration.

Jupyter AI Agent <---> JupyterLab
    |            (RTC)
JNC+JKC

- JNC https://github.com/datalayer/jupyter-nbmodel-client
- JKC https://github.com/datalayer/jupyter-kernel-client
- RTC Real Time Collaboration

First, make sure you have JupyterLab installed:

pip install jupyterlab

Then, start JupyterLab:

jupyter lab

Then, make sure you have a .env file with the following content:

OPENAI_API_VERSION = ...
AZURE_OPENAI_ENDPOINT = ...
AZURE_OPENAI_API_KEY = ...

To use the Jupyter AI Agent, execute the following:

azure_deployment_name = "gpt-4o-mini" # for example
server_url = "http://localhost:8888" # for example, typical when using JupyterLab
token = "..." # your JupyterLab token
notebook_path = "..." # the path to the notebook you want the Jupyter AI Agent to modify

input = '''
Scrape historical stock price data for Apple from Yahoo Finance. 
The data should include columns like Date, Open, High, Low, Close, and Volume. 
After scraping, visualize the data with a line chart showing the closing prices over time.
''' # the input to the Jupyter AI Agent

ask_agent(server_url, token, azure_deployment_name, notebook_path, input)

Uninstall

To uninstall the agent, execute:

pip uninstall jupyter_ai_agent

Contributing

Development install

# Clone the repo to your local environment
# Change directory to the jupyter_ai_agent directory
# Install package in development mode - will automatically enable
# The server extension.
pip install -e ".[test,lint,typing]"

Running Tests

Install dependencies:

pip install -e ".[test]"

To run the python tests, use:

pytest

Development uninstall

pip uninstall jupyter_ai_agent

Packaging the extension

See RELEASE