Metadata-Version: 2.1
Name: gnnnas
Version: 0.0.2
Summary: Library to help write symbolic programs to generate expressive message passing neural networks.
License: MIT
Author: Your Name
Author-email: you@example.com
Requires-Python: >=3.10,<3.13
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: numpy (>=1.26.1,<2.0.0)
Requires-Dist: pdoc3 (>=0.10.0,<0.11.0)
Requires-Dist: pytest (>=7.4.2,<8.0.0)
Requires-Dist: scikit-learn (>=1.3.1,<2.0.0)
Requires-Dist: torch (==1.12.1)
Requires-Dist: torch-geometric (>=2.4.0,<3.0.0)
Description-Content-Type: text/markdown

<h1 align="center">
  <br>
  <img src="https://github.com/akhilpandey95/gnnNAS/blob/main/images/gnnnas-logo.png?raw=true"  width="400" height="400" alt="gnnnas logo"/>
  <br>
</h1>

<h2 align="center">Library to write symbolic programs to generate expressive message passing neural networks</h2>

<h1 align="center"><a href="https://akhilpandey95.github.io/gnnNAS/">kgforge Documentation</h1>

<p align="center">

   <a alt="Tests" href="https://github.com/akhilpandey95/gnnNAS/actions/workflows/publish-to-pypi.yml/badge.svg">
      <img src="https://github.com/akhilpandey95/kgforge/actions/workflows/publish-to-pypi.yml/badge.svg?branch=main">
  </a>
  <img alt="Code Style" src="https://img.shields.io/badge/  code%20style-black-000000.svg" />
  <a href="https://www.python.org/downloads/release/python-390/">
  </a>
  <a href="https://pypi.org/project/gnnNAS" target="_blank">
    <img src="https://img.shields.io/badge/python-3.10-blue.svg" alt="Supported Python versions">
  </a>
  <a href="https://img.shields.io/pypi/dw/gnnNAS" target="_blank">
    <img src="https://img.shields.io/pypi/dw/gnnNAS" alt="Downloads per week">
  </a>
  <a href="https://img.shields.io/badge/License-MIT-yellow.svg" target="_blank">
    <img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License">
  </a>
  <a href="https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square" target="_blank">
    <img src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square" alt="Contribute">
  </a>

</p>

<p align="center">
  <a href="#what-is-it">What is it?</a> •
  <a href="#features">Features</a> •
  <a href="#installation">Installation</a> •
  <a href="#usage">Usage</a>  •
  <a href="#contributing">Contributing</a>
</p>

## What is it?
`kgforge` is a library which automates the generation of knowledge graphs from scholarly text.

## Features:
  - **TODO**: TODO: Description.

## Installation:

### Poetry

```bash
poetry add kgforge
```

### Pip

```bash
pip install kgforge
```

Setup your local environment:

Any necessary environment variables description:


```shell
export SAMPLE_ENV_VARIABLE=${VALUE}
```

## Usage

Now that `kgforge` is installed, you're ready to start using it!

It's time to point you to the official [Documentation Website](https://akhilpandey95.github.io/gnnNAS/) for more information on how to use `kgforge`


## Contributing
If you'd like to contribute, be sure to check out our [contributing guide](./CONTRIBUTING.md)! If you'd like to work on any outstanding items, check out the `roadmap` section in the docs and get started :smiley:

Thanks goes to these incredible people.

<a href="https://github.com/akhilpandey95/gnnNAS/graphs/contributors">
  <img style="border-radius: 50%" src="https://contrib.rocks/image?repo=akhilpandey95/gnnNAS" />
</a>
<a href="https://github.com/akhilpandey95/gnnNAS/graphs/contributors">
  <img style="border-radius: 50%" src="https://contrib.rocks/image?repo=harishsiravuri/kgforge" />
</a>
