🚀 Notebook Copilot: Turn Your Thoughts Into a Polished Notebook at Record-Speed with AI.

Welcome to Notebook Copilot, your next-generation tool for Jupyter Notebooks. Inspired by GitHub Copilot, Notebook Copilot is designed to help engineers and data scientists in developing professional, high-quality notebooks. It's like having your personal AI-powered assistant that helps you navigate through the Jupyter universe, seamlessly generating code and markdown cells based on your inputs.

Imagine not having to start with a blank notebook every time. Sounds dreamy, right?

v1 Demo

Features

• 🚀 GPT Based Generation: Notebook Copilot employs advanced GPT instances for precise and efficient code generation.

• 💻 Integrated with Any Notebook Environments: Seamless access within Jupyter Notebook and other popular platforms, boosting your productivity.

• 🧩 Automatic Context Retrieval: Understands the full context of your notebook, ensuring consistent and relevant code generation.

• 🔑 Bring Your Own OpenAI Key: Flexibility to use your own OpenAI key for personalized code generation and optimal results.

• 🆓 Free and Open Source: Everyone can benefit from Notebook Copilot. It's our contribution to the coding community, aiming to make coding accessible, efficient, and fun.

Quickstart

0. Get an OpenAI API Key

1. Install Notebook Copilot directly from PyPI:

pip install notebook_copilot

2. Load the Notebook Copilot extension in your Jupyter notebook:

%load_ext notebook_copilot # Optional: If you don't have OPENAI_API_KEY set in your environment, you can set it here from getpass import getpass import os os.environ["OPENAI_API_KEY"] = getpass("Enter your OpenAI Key: ") %copilot_init -n /Users/tp/dev/workspace/notebook_copilot/copilot_example_notebook.ipynb # improves copilot performance

3. Start using Notebook Copilot Magic Functions in your notebook ↓

✨ Magic Functions

🪄 Enter Assistant Mode and let Copilot continuously generate professional code and markdown cells for you.

%copilot

✍️ Leverage AI to create the next cell from your comments. It's like having a conversation with your notebook.

%%generate # Plot the confusion matrix for each model # Plot the precision-recall curve for Catboost

📘 Automatically generate markdown cells to explain the code in the current cell. Your code is now not only functional but also well-documented.

%%explain # some code to explain…

Try It