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<meta property="og:title" content="">
<meta property="og:site_name" content="">
<meta property="og:url" content="">
<meta property="og:description" content="Transform your prototype AI code into production-ready software.">
<meta property="og:type" content="">
<meta property="og:image" content=https://great-ai.scoutinscience.com/media/og-image.png>
<style>
.jupyter-wrapper a {
color: var(--md-typeset-a-color) !important;
}
</style>
</head>
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Features
</a>
</li>
<li class="md-nav__item">
<a href="#roadmap" class="md-nav__link">
Roadmap
</a>
</li>
<li class="md-nav__item">
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<li class="md-nav__item">
<a href="how-to-guides/install/" class="md-nav__link">
Installation guide
</a>
</li>
<li class="md-nav__item">
<a href="how-to-guides/create-service/" class="md-nav__link">
How to create a GreatAI service
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<li class="md-nav__item">
<a href="examples/simple/data/" class="md-nav__link">
Train a domain classifier on the semantic scholar dataset
Simple example: data engineering
</a>
</li>
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<li class="md-nav__item">
<a href="examples/simple/train/" class="md-nav__link">
Train a domain classifier on the semantic scholar dataset
Optimise and train a model
</a>
</li>
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<li class="md-nav__item">
<a href="examples/simple/deploy/" class="md-nav__link">
Train a domain classifier on the semantic scholar dataset
Hardening and deployment
</a>
</li>
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Features
</a>
</li>
<li class="md-nav__item">
<a href="#roadmap" class="md-nav__link">
Roadmap
</a>
</li>
<li class="md-nav__item">
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<a href="https://github.com/schmelczer/great-ai/edit/main/docs/index.md" title="Edit this page" class="md-content__button md-icon">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
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<img src="media/logo.png" width=80>
</div>
<p><a href="https://sonar.scoutinscience.com/dashboard?id=great-ai"><img alt="Sonar line coverage" src="https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&amp;metric=coverage" /></a>
<a href="https://sonar.scoutinscience.com/dashboard?id=great-ai"><img alt="Sonar LoC" src="https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&amp;metric=ncloc" /></a>
<a href="https://github.com/schmelczer/great-ai/actions/workflows/test.yml"><img alt="Test" src="https://github.com/schmelczer/great-ai/actions/workflows/test.yml/badge.svg" /></a>
<a href="https://badge.fury.io/py/great-ai"><img alt="PyPI version" src="https://badge.fury.io/py/great-ai.svg" /></a>
<p><a href="https://badge.fury.io/py/great-ai"><img alt="PyPI version" src="https://badge.fury.io/py/great-ai.svg" /></a>
<a href="https://pepy.tech/project/great-ai"><img alt="Downloads" src="https://pepy.tech/badge/great-ai/month" /></a>
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/schmelczera/great-ai" /></p>
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/schmelczera/great-ai" />
<a href="https://github.com/schmelczer/great-ai/actions/workflows/test.yml"><img alt="Test" src="https://github.com/schmelczer/great-ai/actions/workflows/test.yml/badge.svg" /></a>
<a href="https://sonar.scoutinscience.com/dashboard?id=great-ai"><img alt="Sonar line coverage" src="https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&amp;metric=coverage" /></a>
<a href="https://sonar.scoutinscience.com/dashboard?id=great-ai"><img alt="Sonar LoC" src="https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&amp;metric=ncloc" /></a></p>
<p>Applying AI is becoming increasingly easier but many case studies have shown that these applications are often deployed poorly. This may lead to suboptimal performance and to introducing <a href="https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction" target="_blank">unintended biases</a>. GreatAI helps fixing this by allowing you to <mark>easily transform your prototype AI code into production-ready software</mark>.</p>
<details class="quote">
<summary>Case studies</summary>
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<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Input validation</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Sensible cache-policy</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Seamless support for both synchronous and <code>async</code> inference methods</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Easy integration with other remote GreatAI instances</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Easy integration with remote GreatAI instances</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Built-in parallelisation (with support for multiprocessing, async, and mixed modes) for batch processing</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Well-tested utilities for common NLP tasks (cleaning, language-tagging, sentence-segmentation, etc.)</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> A simple, unified configuration interface</li>
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<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Docker support for deployment</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Deployable Jupyter Notebooks</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled checked/><span class="task-list-indicator"></span></label> Dashboard for high-level overview and analysing traces</li>
</ul>
<h2 id="roadmap">Roadmap<a class="headerlink" href="#roadmap" title="Permanent link">#</a></h2>
<ul class="task-list">
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled/><span class="task-list-indicator"></span></label> Prometheus &amp; Grafana integration</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled/><span class="task-list-indicator"></span></label> Well-tested feature extraction code for non-NLP data</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled/><span class="task-list-indicator"></span></label> Support for direct file input</li>
<li class="task-list-item"><label class="task-list-control"><input type="checkbox" disabled/><span class="task-list-indicator"></span></label> Support for PostgreSQL</li>
</ul>
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</ol>
<details class="note">
<summary>Note</summary>
<p>In practice, <code>hello_world</code> could be an inference function of some AI/ML application. But it could also just wrap a black-box solution of some SaaS. Either ways, it is imperative to have continuos oversight of the services you provide and data you process.</p>
<p>In practice, <code>hello_world</code> could be an inference function of some AI/ML application. But it could also just wrap a black-box solution of some SaaS. Either ways, it is <a href="https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai" target="_blank">imperative to have continuos oversight</a> of the services you provide and data you process especially in the context of AI/ML applications.</p>
</details>
<div class="highlight"><span class="filename">terminal</span><pre><span></span><code><a id="__codelineno-2-1" name="__codelineno-2-1" href="#__codelineno-2-1"></a>great-ai hello-world.py
</code></pre></div>
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</ul>
<h2 id="why-greatai">Why GreatAI?<a class="headerlink" href="#why-greatai" title="Permanent link">#</a></h2>
<p>There are other, existing solutions aiming to facilitate this phase. <a href="https://aws.amazon.com/sagemaker" target="_blank">Amazon SageMaker</a> and <a href="https://www.seldon.io/solutions/open-source-projects/core" target="_blank">Seldon Core</a> provide the most comprehensive suite of features. If you have the opportunity use those, do that because they're great.</p>
<p>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 <a href="https://se-ml.github.io" target="_blank">SE4ML best-practices</a>, and thus, can meaningfully improve your deployment without requiring prohibitively large effort.</p>
<div style="display: flex; justify-content: space-evenly;">
<p>However, research indicates that professionals rarely use them. This may be due to their inherent setup and operating complexity. <mark>GreatAI is designed to be as simple to use as possible.</mark> 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 <a href="https://se-ml.github.io" target="_blank">SE4ML best-practices</a>, and thus, can meaningfully improve your deployment without requiring prohibitively large effort.</p>
<div style="display: flex; justify-content: space-evenly; flex-wrap: wrap;">
<p><a class="md-button md-button--primary" href="https://pypi.org/project/great-ai"><span class="twemoji"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.8 200.5c-7.7-30.9-22.3-54.2-53.4-54.2h-40.1v47.4c0 36.8-31.2 67.8-66.8 67.8H172.7c-29.2 0-53.4 25-53.4 54.3v101.8c0 29 25.2 46 53.4 54.3 33.8 9.9 66.3 11.7 106.8 0 26.9-7.8 53.4-23.5 53.4-54.3v-40.7H226.2v-13.6h160.2c31.1 0 42.6-21.7 53.4-54.2 11.2-33.5 10.7-65.7 0-108.6zM286.2 404c11.1 0 20.1 9.1 20.1 20.3 0 11.3-9 20.4-20.1 20.4-11 0-20.1-9.2-20.1-20.4.1-11.3 9.1-20.3 20.1-20.3zM167.8 248.1h106.8c29.7 0 53.4-24.5 53.4-54.3V91.9c0-29-24.4-50.7-53.4-55.6-35.8-5.9-74.7-5.6-106.8.1-45.2 8-53.4 24.7-53.4 55.6v40.7h106.9v13.6h-147c-31.1 0-58.3 18.7-66.8 54.2-9.8 40.7-10.2 66.1 0 108.6 7.6 31.6 25.7 54.2 56.8 54.2H101v-48.8c0-35.3 30.5-66.4 66.8-66.4zm-6.7-142.6c-11.1 0-20.1-9.1-20.1-20.3.1-11.3 9-20.4 20.1-20.4 11 0 20.1 9.2 20.1 20.4s-9 20.3-20.1 20.3z"/></svg></span> Find it on PyPI</a></p>
<p><a class="md-button md-button--primary" href="https://hub.docker.com/repository/docker/schmelczera/great-ai"><span class="twemoji"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 640 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M349.9 236.3h-66.1v-59.4h66.1v59.4zm0-204.3h-66.1v60.7h66.1V32zm78.2 144.8H362v59.4h66.1v-59.4zm-156.3-72.1h-66.1v60.1h66.1v-60.1zm78.1 0h-66.1v60.1h66.1v-60.1zm276.8 100c-14.4-9.7-47.6-13.2-73.1-8.4-3.3-24-16.7-44.9-41.1-63.7l-14-9.3-9.3 14c-18.4 27.8-23.4 73.6-3.7 103.8-8.7 4.7-25.8 11.1-48.4 10.7H2.4c-8.7 50.8 5.8 116.8 44 162.1 37.1 43.9 92.7 66.2 165.4 66.2 157.4 0 273.9-72.5 328.4-204.2 21.4.4 67.6.1 91.3-45.2 1.5-2.5 6.6-13.2 8.5-17.1l-13.3-8.9zm-511.1-27.9h-66v59.4h66.1v-59.4zm78.1 0h-66.1v59.4h66.1v-59.4zm78.1 0h-66.1v59.4h66.1v-59.4zm-78.1-72.1h-66.1v60.1h66.1v-60.1z"/></svg></span> Find it on DockerHub</a></p>
<p><a class="md-button md-button--primary" href="/tutorial"><span class="twemoji"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 640 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M128 96h384v256h64V80c0-26.37-21.6-48-48-48H112c-26.37 0-48 21.63-48 48v272h64V96zm496 288H16c-8.75 0-16 7.3-16 16v16c0 35.25 28.75 64 64 64h512c35.25 0 64-28.75 64-64v-16c0-8.7-7.2-16-16-16zm-258.1-97.8c3.9 3.9 9 5.8 14.1 5.8s10.23-1.938 14.14-5.844l48-48c7.812-7.813 7.812-20.5 0-28.31l-48-48c-7.812-7.813-20.47-7.813-28.28 0-7.812 7.813-7.812 20.5 0 28.31l33.86 33.84-33.86 33.84C358 265.7 358 278.4 365.9 286.2zm-91.8-124.3c-7.812-7.813-20.47-7.813-28.28 0l-48 48c-7.812 7.813-7.812 20.5 0 28.31l48 48C249.8 290.1 254.9 292 260 292s10.23-1.938 14.14-5.844c7.812-7.813 7.812-20.5 0-28.31L240.3 224l33.86-33.84c6.94-7.76 6.94-20.46-.06-28.26z"/></svg></span> Check out the tutorial</a></p>
</div>
<h2 id="production-use">Production use<a class="headerlink" href="#production-use" title="Permanent link">#</a></h2>
<p>GreatAI has been battle-tested on the core platform services of <a href="https://www.scoutinscience.com/" target="_blank">ScoutinScience</a>.</p>
<p><img alt="ScoutinScience logo" loading="lazy" src="media/scoutinscience.svg#only-light" />
<img alt="ScoutinScience logo" loading="lazy" src="media/scoutinscience-white.svg#only-dark" /></p>
<p><a href="https://www.scoutinscience.com/" target="_blank"><img alt="ScoutinScience logo" loading="lazy" src="media/scoutinscience.svg#only-light" />
<img alt="ScoutinScience logo" loading="lazy" src="media/scoutinscience-white.svg#only-dark" /></a></p>
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Last update:
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 12, 2022</span>
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