- Introduction
- Configure git for commits
- Start your project with AI4OS Data Science template
- Access remote storages
- AI4OS Documentation
- AI4OS related services
- List of installed tools
- Acknowledgments
AI4OS Development Environment (AI4Dev) aims to facilitate the integration of your code with AI4OS software solutions, development, and testing it directly in the cloud environment. Please, see the List of installed tools and AI4OS Documentation for more details.
Using pre-installed git you can easily clone projects in AI4Dev. If you want to commit your changes back, you have to configure global user.name and user.email as follows:
$ git config --global user.name "Your Name"
$ git config --global user.email "[email protected]"Create your new project using our AI4OS templates for easier integration with AI4OS components (DEEPaaS API, Dockerfile, Jenkinsfiles etc). You can use either:
- Our web-interface: https://templates.cloud.ai4eosc.eu/
OR
- external command-line tool cookiecutter:
$ cookiecutter https://github.com/deephdc/cookiecutter-deepYou can use
- rclone to sync with a remote cloud storage (e.g. AI4OS Nextcloud), or
- oneclient to access OneData distributed storage.
Comprehensive documentation on AI4OS tools and components can be found in:
- AI4OS documentation
- YouTube channel with tutorials
- AI4OS AAI : Join our Virtual Organisation (VO) in order to access the services
- AI4OS Open Catalog and the Dashboard : a curated repository of applications ready to be used or extended. Logged-in users can deploy modules directly on the platform.
- Nextcloud storage : a sync&share solution to host and share data.
AI4OS Development Environment uses as a base a Docker Image of either
- TensorFlow framework (2.10.0 | 2.11.0)
- PyTorch (1.12 | 1.13)
- or Ubuntu 20.04 (Focal)
It leverages
- JupyterLab web-based user interface for developing and debugging your code (hint: use Shift+Right click to copy/paste);
- VS Code in the browser VS Code that runs in the browser, see code-server
Includes:
- cookiecutter template tool to start or integrate your project with AI4OS solutions profiting from AI4OS Data Science template:
Contains AI4OS components:
- DEEP as a Service API is REST API that provids access to machine learning models;
- flaat : FLAsk support for handling oidc Access Tokens;
- oidc-agent : a set of tools to manage OpenID Connect tokens and make them easily usable from the command line;
Python related packages:
- python
- python-dev
- pip
And a number of external tools to facilitate the development:
- git
- curl : command line tool for transferring data with URL syntax
- jq : lightweight and flexible command-line JSON processor
- mc : Midnight Commander, a visual file manager
- nano : a simple terminal-based text editor
- oneclient : a command-line based client for Onedata
- openssh-client
- rclone : a command line program to sync files and directories to and from cloud storages
- wget : a free utility for non-interactive download of files from the Web
This work is co-funded by AI4EOSC project that has received funding from the European Union's Horizon Europe 2022 research and innovation programme under agreement No 101058593
This work is co-funded by DEEP Hybrid-DataCloud project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 777435. Please consider citing the DEEP Hybrid DataCloud project:
García, Álvaro López, et al. A Cloud-Based Framework for Machine Learning Workloads and Applications. IEEE Access 8 (2020): 18681-18692.