Fix readme on PyPI

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Andras Schmelczer 2022-07-13 20:33:26 +02:00
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# <img src="https://github.com/schmelczer/great-ai/blob/main/docs/media/logo.png" alt="logo of great-ai" width=60 /> GreatAI
# <img src="https://raw.githubusercontent.com/schmelczer/great-ai/main/docs/media/logo.png" alt="logo of great-ai" width=60 /> GreatAI
> Easily transform your prototype AI code into production-ready software.
[![PyPI version](https://badge.fury.io/py/great-ai.svg)](https://badge.fury.io/py/great-ai)
@ -28,7 +28,7 @@ def greeter(name: str) -> str:
Start it by executing `great-ai demo.py`, find the dashboard at [http://localhost:6060](http://localhost:6060/dashboard).
![demo screen capture](https://github.com/schmelczer/great-ai/blob/main/docs/media/demo.gif)
![demo screen capture](https://raw.githubusercontent.com/schmelczer/great-ai/main/docs/media/demo.gif)
That's it. Your GreatAI service is *nearly* ready for production use. Many of the [SE4ML best-practices](https://se-ml.github.io) are configured and implemented automatically (of course, these can be customised as well).
@ -36,7 +36,7 @@ That's it. Your GreatAI service is *nearly* ready for production use. Many of th
## Why is this GREAT?
![scope of GreatAI](docs/media/scope-simple.drawio.svg)
![scope of GreatAI](https://raw.githubusercontent.com/schmelczer/great-ai/main/docs/media/scope-simple.drawio.svg)
GreatAI fits between the prototype and deployment phases of your 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:
@ -52,10 +52,16 @@ There are other, existing solutions aiming to facilitate this phase. [Amazon Sag
However, [research indicates](https://great-ai.scoutinscience.com) 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](https://se-ml.github.io), and thus, can meaningfully improve your deployment without requiring prohibitively large effort.
## Find `great-ai` on [PyPI](https://hub.docker.com/repository/docker/schmelczera/great-ai)
## [Learn more](https://great-ai.scoutinscience.com)
[Check out the full documentation here](https://great-ai.scoutinscience.com).
## Find `great-ai` on [PyPI](https://pypi.org/project/great-ai/)
```sh
pip install great-ai
```
## Find `great-ai` on [DockerHub](https://hub.docker.com/repository/docker/schmelczera/great-ai)
```sh