great-ai 0.1.4

GreatAI.

GreatAI

GreatAI helps you easily transform your prototype AI code into production-ready software. Check out the full documentation here.

pip install great-ai

Create a new file called main.py

from great_ai import GreatAI

@GreatAI.create
def hello_world(name: str) -> str:
    return f"Hello {name}!"

Start it by executing great-ai main.py, find the dashboard at http://localhost:6060.

That's it. Your GreatAI service is ready for production use. Many of the SE4ML best-practices are configured and implemented automatically (of course, these can be customised as well).

Why is this GREAT?

GreatAI fits between the prototype and deployment phases of your (or your organisation's) AI development lifecycle. This is highlighted with blue in the diagram. Here, a number of best practices can be automatically implemented aiming to achieve the following attributes:

• General: use any Python library without restriction
• Robust: have error-handling and well-tested utilities out-of-the-box
• End-to-end: utilise end-to-end feedback as a built-in, first-class concept
• Automated: focus only on what actually requires your attention
• Trustworthy: deploy models that you and society can confidently trust

Why GreatAI?

There are other, existing solutions aiming to facilitate this phase. Amazon SageMaker and Seldon Core provide the most comprehensive suite of features. If you have the opportunity use those, do that because they're great.

However, research indicates that professionals rarely use them. This may be due to their inherent setup and operating complexity. GreatAI is designed to be as simple to use as possible. Its clear, high-level API and sensible default configuration makes it extremely easy to start using. Despite its relative simplicity over Seldon Core, it still implements many of the SE4ML best-practices, and thus, can meaningfully improve your deployment without requiring prohibitively large effort.

Find great-ai on DockerHub

docker run -p6060:6060 schmelczera/great-ai

Learn more

Check out the documentation.

Contribute

Contributions are welcome.

Install for development

python3 -m venv --copies .env
source .env/bin/activate
python3 -m pip install flit
python3 -m flit install --symlink --deps=all

Serve documentation

mkdocs serve --dirtyreload