Metadata-Version: 2.1
Name: jupyter-plz
Version: 0.1.4
Summary: A ChatGPT front-end for Jupyter notebooks (Copilot for Jupyter notebooks).
Home-page: https://github.com/akramz/jupyter_plz
Author: Akram Zaytar
Author-email: zaytarakram@gmail.com
License: MIT license
Keywords: jupyter_plz
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
License-File: LICENSE
License-File: AUTHORS.rst
Requires-Dist: notebook

# Copilot, for your Jupyter Notebook

`%plz` is a Jupyter magic command that generates programs from human-readable descriptions in Jupyter notebooks.

https://user-images.githubusercontent.com/11509740/210084133-61f2cb2d-9968-4b01-8a67-85fcb92eb312.mov


## Installation

You can install `plz` in your Python virtual environment by running the following command in your terminal:

```bash
pip install plz
```

## Usage

`plz` uses [GPT-3](https://beta.openai.com/). To use it, you'll need to:

- Activate billing on your OpenAI [account](https://beta.openai.com/account/billing/overview).
- Grab an API key from [your dashboard](https://beta.openai.com/).
- Provide the API key to the `jupyter_plz` package upon request inside your notebook.

Once you have configured your environment, you can run the `plz` magic command in your notebook. Example:

```bash
%plz "create a function that generates a random walk in the form of an array."
```

Or markdown guides:

```bash
%plz --markdown "Provide a step-by-step guide on how to identify anomalies in a list of numbers."
```

## Credit

This tool is inspired by [plz-cli](https://github.com/m1guelpf/plz-cli) (designed for the command line).

## License

This project is open-sourced under the MIT license. See [the License file](LICENSE) for more information.


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History
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0.1.0 (2022-12-30)
------------------

* First release on PyPI.
