Metadata-Version: 2.3
Name: gnnepcsaftcli
Version: 0.5.1
Summary: 
Author: wildsonbbl
Author-email: wil_bbl@hotmail.com
Requires-Python: >=3.10
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Dist: gnnepcsaft
Requires-Dist: gnnepcsaft-mcp-server (>=0.2.3,<0.3.0)
Requires-Dist: onnxruntime (>=1.20.1,<2.0.0)
Requires-Dist: rdkit (>=2024.9.4,<2025.0.0)
Requires-Dist: typer (>=0.15.1,<0.16.0)
Description-Content-Type: text/markdown

# GNNePCSAFT CLI

The project focuses on using Graph Neural Networks ([GNN](https://en.wikipedia.org/wiki/Graph_neural_network)) to estimate the pure-component parameters of the Equation of State [PC-SAFT](https://en.wikipedia.org/wiki/PC-SAFT).

Currently, the model takes into account the hard-chain, dispersive, and associative terms of PC-SAFT. Future work on polar and ionic terms is being studied.

Code is being developed mainly in Pytorch ([PyG](https://pytorch-geometric.readthedocs.io/en/latest/index.html#)).

You can find a model deployed in a Desktop App at [SourceForge](https://sourceforge.net/projects/gnnepcsaft/).

A CLI to use a model can be found at [GNNePCSAFT CLI](https://github.com/wildsonbbl/gnnepcsaftcli) and installed with [pipx](https://github.com/pypa/pipx):

```bash
pipx install gnnepcsaftcli
```

## CLI

GNNePCSAFT CLI tool

**Usage**:

```console
gnnepcsaftcli [OPTIONS] COMMAND [ARGS]...
```

**Options**:

- `--install-completion`: Install completion for the current shell.
- `--show-completion`: Show completion for the current shell, to copy it or customize the installation.
- `--help`: Show this message and exit.

**Commands**:

- `pred`: Predict PCSAFT parameters from SMILES...

## `pred`

Predict PCSAFT parameters from SMILES with a GNNePCSAFT model

**Usage**:

```console
pred [OPTIONS]
```

**Options**:

- `--help`: Show this message and exit.

