Metadata-Version: 2.1
Name: deepchain-apps
Version: 0.1.11
Summary: Define a personnal app to deploy on DeepChain.bio
Home-page: UNKNOWN
Author: Instadeep
Author-email: a.delfosse@instadeep.com
License: Apache-2.0
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Software Development
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE

<p align="center">
  <img width="50%" src="https://raw.githubusercontent.com/DeepChainBio/deep-chain-apps/main/.docs/source/_static/deepchain.png">
</p>

![PyPI](https://img.shields.io/pypi/v/deepchain-apps)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Python 3.7](https://img.shields.io/badge/python-3.7-blue.svg)](https://www.python.org/downloads/release/python-360/)
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![Dependencies](https://img.shields.io/badge/dependencies-up%20to%20date-brightgreen.svg)

<details><summary>Table of contents</summary>

- [Description](#description)
- [Installation](#Installation)
- [CLI](#usage)
  - login
  - create
  - deploy
  - apps
- [How generate token to login deepchain?](#login)
- [Getting started with App](#usage)
- [License](#license)
</details>

# `deepchain-apps` package documentation

This Package provide a **cli** for creating a personnal app to deploy on the DeepChain platform. [More informations on app](https://github.com/DeepChainBio/deep-chain-apps)
To leverage the apps capability, take a look at the [bio-transformers](https://pypi.org/project/bio-transformers/) and [bio-datasets](https://pypi.org/project/bio-datasets) package, which provide functionnality to download biological dataset and easily use pre-trained transformers.

## 1. Installation
It is recommended to work with conda environnements in order to manage the specific dependencies of the package.
```bash
  conda create --name deepchain-env python=3.7 -y
  conda activate deepchain-env
  pip install deepchain-apps
```

# 2. CLI commands

The CLI provides 5 main commands:

- **login** : you need to supply the token provide on the plateform (PAT: personnal access token).

  ```
  deepchain login
  ```

- **create** : create a folder with a template app file

  ```
  deepchain create my_application
  ```

- **deploy** : the code and checkpoint are deployed on the plateform, you can select your app in the interface on the plateform.
  - with checkpoint upload

    ```
    deepchain deploy my_application --checkpoint
    ```

  - Only the code

    ```
    deepchain deploy my_application
    ```

- **apps** :
  - Get info on all local/upload apps

    ```
    deepchain apps --infos
    ```

  - Remove all local apps (files & config):

    ```
    deepchain apps --reset
    ```

  - Remove a specific application (files & config):

    ```
    deepchain apps --delete my_application
    ```

  - List all public apps:

    ```
    deepchain apps --public
    ```

- **download** :
  - Download locally an app deployed on deepchain hub

  ```
    deepchain download user.name@mail.com/AppName AppName
  ```

## How generate token to login deepchain?
If you want to deploy biology app on deepchain, you should first create a personal account on [deepchain](https://deepchain.bio/) and go to the user profile section.
As you can see below, you will be able to generate a PAT (personal access token) that you can use with the CLI command:

```
deepchain login
```

<p align="center">
  <img width="100%" src="https://raw.githubusercontent.com/DeepChainBio/deep-chain-apps/main/.docs/source/_static/login.png">
</p>

## 3. Getting started with App

- deepchain-apps template located at: https://github.com/DeepChainBio/deep-chain-apps
- create new folder when using `deepchain create myapp`
- app structure:

```bash
.
├── README.md # explain how to create an app
├── __init__.py # __init__ file to create python module
├── checkpoint
│   ├── __init__.py
│   └── Optionnal : model.pt # optional: model to be used in app must be placed there
├── examples
│   ├── app_with_checkpoint.py # example: app example with checkpoint
│   └── torch_classifier.py # example: show how to train a neural network with pre-trained embeddings
└── src
    ├── DESC.md # Desciption file of the application
    ├── __init__.py
    ├── app.py # main application script. Main class must be named App.
    └── tags.json # file to register the tags on the hub.
```



# License

This source code is licensed under the **Apache 2** license found in the `LICENSE` file in the root directory.


