hub.martinz.top
Open in
urlscan Pro
2606:4700:3030::ac43:aa99
Public Scan
Submitted URL: http://hub.martinz.top/features/copilot
Effective URL: https://hub.martinz.top/features/copilot
Submission: On March 30 via api from US — Scanned from US
Effective URL: https://hub.martinz.top/features/copilot
Submission: On March 30 via api from US — Scanned from US
Form analysis 3 forms found in the DOM
GET
<form id="query-builder-test-form" action="" accept-charset="UTF-8" method="get">
<query-builder data-target="qbsearch-input.queryBuilder" id="query-builder-query-builder-test" data-filter-key=":" data-view-component="true" class="QueryBuilder search-query-builder" data-min-width="300" data-catalyst="">
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</svg>
</template>
<template id="organization-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-organization">
<path
d="M1.75 16A1.75 1.75 0 0 1 0 14.25V1.75C0 .784.784 0 1.75 0h8.5C11.216 0 12 .784 12 1.75v12.5c0 .085-.006.168-.018.25h2.268a.25.25 0 0 0 .25-.25V8.285a.25.25 0 0 0-.111-.208l-1.055-.703a.749.749 0 1 1 .832-1.248l1.055.703c.487.325.779.871.779 1.456v5.965A1.75 1.75 0 0 1 14.25 16h-3.5a.766.766 0 0 1-.197-.026c-.099.017-.2.026-.303.026h-3a.75.75 0 0 1-.75-.75V14h-1v1.25a.75.75 0 0 1-.75.75Zm-.25-1.75c0 .138.112.25.25.25H4v-1.25a.75.75 0 0 1 .75-.75h2.5a.75.75 0 0 1 .75.75v1.25h2.25a.25.25 0 0 0 .25-.25V1.75a.25.25 0 0 0-.25-.25h-8.5a.25.25 0 0 0-.25.25ZM3.75 6h.5a.75.75 0 0 1 0 1.5h-.5a.75.75 0 0 1 0-1.5ZM3 3.75A.75.75 0 0 1 3.75 3h.5a.75.75 0 0 1 0 1.5h-.5A.75.75 0 0 1 3 3.75Zm4 3A.75.75 0 0 1 7.75 6h.5a.75.75 0 0 1 0 1.5h-.5A.75.75 0 0 1 7 6.75ZM7.75 3h.5a.75.75 0 0 1 0 1.5h-.5a.75.75 0 0 1 0-1.5ZM3 9.75A.75.75 0 0 1 3.75 9h.5a.75.75 0 0 1 0 1.5h-.5A.75.75 0 0 1 3 9.75ZM7.75 9h.5a.75.75 0 0 1 0 1.5h-.5a.75.75 0 0 1 0-1.5Z">
</path>
</svg>
</template>
<template id="rocket-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-rocket">
<path
d="M14.064 0h.186C15.216 0 16 .784 16 1.75v.186a8.752 8.752 0 0 1-2.564 6.186l-.458.459c-.314.314-.641.616-.979.904v3.207c0 .608-.315 1.172-.833 1.49l-2.774 1.707a.749.749 0 0 1-1.11-.418l-.954-3.102a1.214 1.214 0 0 1-.145-.125L3.754 9.816a1.218 1.218 0 0 1-.124-.145L.528 8.717a.749.749 0 0 1-.418-1.11l1.71-2.774A1.748 1.748 0 0 1 3.31 4h3.204c.288-.338.59-.665.904-.979l.459-.458A8.749 8.749 0 0 1 14.064 0ZM8.938 3.623h-.002l-.458.458c-.76.76-1.437 1.598-2.02 2.5l-1.5 2.317 2.143 2.143 2.317-1.5c.902-.583 1.74-1.26 2.499-2.02l.459-.458a7.25 7.25 0 0 0 2.123-5.127V1.75a.25.25 0 0 0-.25-.25h-.186a7.249 7.249 0 0 0-5.125 2.123ZM3.56 14.56c-.732.732-2.334 1.045-3.005 1.148a.234.234 0 0 1-.201-.064.234.234 0 0 1-.064-.201c.103-.671.416-2.273 1.15-3.003a1.502 1.502 0 1 1 2.12 2.12Zm6.94-3.935c-.088.06-.177.118-.266.175l-2.35 1.521.548 1.783 1.949-1.2a.25.25 0 0 0 .119-.213ZM3.678 8.116 5.2 5.766c.058-.09.117-.178.176-.266H3.309a.25.25 0 0 0-.213.119l-1.2 1.95ZM12 5a1 1 0 1 1-2 0 1 1 0 0 1 2 0Z">
</path>
</svg>
</template>
<template id="shield-check-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-shield-check">
<path
d="m8.533.133 5.25 1.68A1.75 1.75 0 0 1 15 3.48V7c0 1.566-.32 3.182-1.303 4.682-.983 1.498-2.585 2.813-5.032 3.855a1.697 1.697 0 0 1-1.33 0c-2.447-1.042-4.049-2.357-5.032-3.855C1.32 10.182 1 8.566 1 7V3.48a1.75 1.75 0 0 1 1.217-1.667l5.25-1.68a1.748 1.748 0 0 1 1.066 0Zm-.61 1.429.001.001-5.25 1.68a.251.251 0 0 0-.174.237V7c0 1.36.275 2.666 1.057 3.859.784 1.194 2.121 2.342 4.366 3.298a.196.196 0 0 0 .154 0c2.245-.957 3.582-2.103 4.366-3.297C13.225 9.666 13.5 8.358 13.5 7V3.48a.25.25 0 0 0-.174-.238l-5.25-1.68a.25.25 0 0 0-.153 0ZM11.28 6.28l-3.5 3.5a.75.75 0 0 1-1.06 0l-1.5-1.5a.749.749 0 0 1 .326-1.275.749.749 0 0 1 .734.215l.97.97 2.97-2.97a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042Z">
</path>
</svg>
</template>
<template id="heart-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-heart">
<path
d="m8 14.25.345.666a.75.75 0 0 1-.69 0l-.008-.004-.018-.01a7.152 7.152 0 0 1-.31-.17 22.055 22.055 0 0 1-3.434-2.414C2.045 10.731 0 8.35 0 5.5 0 2.836 2.086 1 4.25 1 5.797 1 7.153 1.802 8 3.02 8.847 1.802 10.203 1 11.75 1 13.914 1 16 2.836 16 5.5c0 2.85-2.045 5.231-3.885 6.818a22.066 22.066 0 0 1-3.744 2.584l-.018.01-.006.003h-.002ZM4.25 2.5c-1.336 0-2.75 1.164-2.75 3 0 2.15 1.58 4.144 3.365 5.682A20.58 20.58 0 0 0 8 13.393a20.58 20.58 0 0 0 3.135-2.211C12.92 9.644 14.5 7.65 14.5 5.5c0-1.836-1.414-3-2.75-3-1.373 0-2.609.986-3.029 2.456a.749.749 0 0 1-1.442 0C6.859 3.486 5.623 2.5 4.25 2.5Z">
</path>
</svg>
</template>
<template id="server-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-server">
<path
d="M1.75 1h12.5c.966 0 1.75.784 1.75 1.75v4c0 .372-.116.717-.314 1 .198.283.314.628.314 1v4a1.75 1.75 0 0 1-1.75 1.75H1.75A1.75 1.75 0 0 1 0 12.75v-4c0-.358.109-.707.314-1a1.739 1.739 0 0 1-.314-1v-4C0 1.784.784 1 1.75 1ZM1.5 2.75v4c0 .138.112.25.25.25h12.5a.25.25 0 0 0 .25-.25v-4a.25.25 0 0 0-.25-.25H1.75a.25.25 0 0 0-.25.25Zm.25 5.75a.25.25 0 0 0-.25.25v4c0 .138.112.25.25.25h12.5a.25.25 0 0 0 .25-.25v-4a.25.25 0 0 0-.25-.25ZM7 4.75A.75.75 0 0 1 7.75 4h4.5a.75.75 0 0 1 0 1.5h-4.5A.75.75 0 0 1 7 4.75ZM7.75 10h4.5a.75.75 0 0 1 0 1.5h-4.5a.75.75 0 0 1 0-1.5ZM3 4.75A.75.75 0 0 1 3.75 4h.5a.75.75 0 0 1 0 1.5h-.5A.75.75 0 0 1 3 4.75ZM3.75 10h.5a.75.75 0 0 1 0 1.5h-.5a.75.75 0 0 1 0-1.5Z">
</path>
</svg>
</template>
<template id="globe-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-globe">
<path
d="M8 0a8 8 0 1 1 0 16A8 8 0 0 1 8 0ZM5.78 8.75a9.64 9.64 0 0 0 1.363 4.177c.255.426.542.832.857 1.215.245-.296.551-.705.857-1.215A9.64 9.64 0 0 0 10.22 8.75Zm4.44-1.5a9.64 9.64 0 0 0-1.363-4.177c-.307-.51-.612-.919-.857-1.215a9.927 9.927 0 0 0-.857 1.215A9.64 9.64 0 0 0 5.78 7.25Zm-5.944 1.5H1.543a6.507 6.507 0 0 0 4.666 5.5c-.123-.181-.24-.365-.352-.552-.715-1.192-1.437-2.874-1.581-4.948Zm-2.733-1.5h2.733c.144-2.074.866-3.756 1.58-4.948.12-.197.237-.381.353-.552a6.507 6.507 0 0 0-4.666 5.5Zm10.181 1.5c-.144 2.074-.866 3.756-1.58 4.948-.12.197-.237.381-.353.552a6.507 6.507 0 0 0 4.666-5.5Zm2.733-1.5a6.507 6.507 0 0 0-4.666-5.5c.123.181.24.365.353.552.714 1.192 1.436 2.874 1.58 4.948Z">
</path>
</svg>
</template>
<template id="issue-opened-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-issue-opened">
<path d="M8 9.5a1.5 1.5 0 1 0 0-3 1.5 1.5 0 0 0 0 3Z"></path>
<path d="M8 0a8 8 0 1 1 0 16A8 8 0 0 1 8 0ZM1.5 8a6.5 6.5 0 1 0 13 0 6.5 6.5 0 0 0-13 0Z"></path>
</svg>
</template>
<template id="device-mobile-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-device-mobile">
<path
d="M3.75 0h8.5C13.216 0 14 .784 14 1.75v12.5A1.75 1.75 0 0 1 12.25 16h-8.5A1.75 1.75 0 0 1 2 14.25V1.75C2 .784 2.784 0 3.75 0ZM3.5 1.75v12.5c0 .138.112.25.25.25h8.5a.25.25 0 0 0 .25-.25V1.75a.25.25 0 0 0-.25-.25h-8.5a.25.25 0 0 0-.25.25ZM8 13a1 1 0 1 1 0-2 1 1 0 0 1 0 2Z">
</path>
</svg>
</template>
<template id="package-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-package">
<path
d="m8.878.392 5.25 3.045c.54.314.872.89.872 1.514v6.098a1.75 1.75 0 0 1-.872 1.514l-5.25 3.045a1.75 1.75 0 0 1-1.756 0l-5.25-3.045A1.75 1.75 0 0 1 1 11.049V4.951c0-.624.332-1.201.872-1.514L7.122.392a1.75 1.75 0 0 1 1.756 0ZM7.875 1.69l-4.63 2.685L8 7.133l4.755-2.758-4.63-2.685a.248.248 0 0 0-.25 0ZM2.5 5.677v5.372c0 .09.047.171.125.216l4.625 2.683V8.432Zm6.25 8.271 4.625-2.683a.25.25 0 0 0 .125-.216V5.677L8.75 8.432Z">
</path>
</svg>
</template>
<template id="credit-card-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-credit-card">
<path d="M10.75 9a.75.75 0 0 0 0 1.5h1.5a.75.75 0 0 0 0-1.5h-1.5Z"></path>
<path
d="M0 3.75C0 2.784.784 2 1.75 2h12.5c.966 0 1.75.784 1.75 1.75v8.5A1.75 1.75 0 0 1 14.25 14H1.75A1.75 1.75 0 0 1 0 12.25ZM14.5 6.5h-13v5.75c0 .138.112.25.25.25h12.5a.25.25 0 0 0 .25-.25Zm0-2.75a.25.25 0 0 0-.25-.25H1.75a.25.25 0 0 0-.25.25V5h13Z">
</path>
</svg>
</template>
<template id="play-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-play">
<path d="M8 0a8 8 0 1 1 0 16A8 8 0 0 1 8 0ZM1.5 8a6.5 6.5 0 1 0 13 0 6.5 6.5 0 0 0-13 0Zm4.879-2.773 4.264 2.559a.25.25 0 0 1 0 .428l-4.264 2.559A.25.25 0 0 1 6 10.559V5.442a.25.25 0 0 1 .379-.215Z"></path>
</svg>
</template>
<template id="gift-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-gift">
<path
d="M2 2.75A2.75 2.75 0 0 1 4.75 0c.983 0 1.873.42 2.57 1.232.268.318.497.668.68 1.042.183-.375.411-.725.68-1.044C9.376.42 10.266 0 11.25 0a2.75 2.75 0 0 1 2.45 4h.55c.966 0 1.75.784 1.75 1.75v2c0 .698-.409 1.301-1 1.582v4.918A1.75 1.75 0 0 1 13.25 16H2.75A1.75 1.75 0 0 1 1 14.25V9.332C.409 9.05 0 8.448 0 7.75v-2C0 4.784.784 4 1.75 4h.55c-.192-.375-.3-.8-.3-1.25ZM7.25 9.5H2.5v4.75c0 .138.112.25.25.25h4.5Zm1.5 0v5h4.5a.25.25 0 0 0 .25-.25V9.5Zm0-4V8h5.5a.25.25 0 0 0 .25-.25v-2a.25.25 0 0 0-.25-.25Zm-7 0a.25.25 0 0 0-.25.25v2c0 .138.112.25.25.25h5.5V5.5h-5.5Zm3-4a1.25 1.25 0 0 0 0 2.5h2.309c-.233-.818-.542-1.401-.878-1.793-.43-.502-.915-.707-1.431-.707ZM8.941 4h2.309a1.25 1.25 0 0 0 0-2.5c-.516 0-1 .205-1.43.707-.337.392-.646.975-.879 1.793Z">
</path>
</svg>
</template>
<template id="code-square-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-code-square">
<path
d="M0 1.75C0 .784.784 0 1.75 0h12.5C15.216 0 16 .784 16 1.75v12.5A1.75 1.75 0 0 1 14.25 16H1.75A1.75 1.75 0 0 1 0 14.25Zm1.75-.25a.25.25 0 0 0-.25.25v12.5c0 .138.112.25.25.25h12.5a.25.25 0 0 0 .25-.25V1.75a.25.25 0 0 0-.25-.25Zm7.47 3.97a.75.75 0 0 1 1.06 0l2 2a.75.75 0 0 1 0 1.06l-2 2a.749.749 0 0 1-1.275-.326.749.749 0 0 1 .215-.734L10.69 8 9.22 6.53a.75.75 0 0 1 0-1.06ZM6.78 6.53 5.31 8l1.47 1.47a.749.749 0 0 1-.326 1.275.749.749 0 0 1-.734-.215l-2-2a.75.75 0 0 1 0-1.06l2-2a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042Z">
</path>
</svg>
</template>
<template id="device-desktop-icon">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-device-desktop">
<path
d="M14.25 1c.966 0 1.75.784 1.75 1.75v7.5A1.75 1.75 0 0 1 14.25 12h-3.727c.099 1.041.52 1.872 1.292 2.757A.752.752 0 0 1 11.25 16h-6.5a.75.75 0 0 1-.565-1.243c.772-.885 1.192-1.716 1.292-2.757H1.75A1.75 1.75 0 0 1 0 10.25v-7.5C0 1.784.784 1 1.75 1ZM1.75 2.5a.25.25 0 0 0-.25.25v7.5c0 .138.112.25.25.25h12.5a.25.25 0 0 0 .25-.25v-7.5a.25.25 0 0 0-.25-.25ZM9.018 12H6.982a5.72 5.72 0 0 1-.765 2.5h3.566a5.72 5.72 0 0 1-.765-2.5Z">
</path>
</svg>
</template>
<div class="position-relative">
<ul role="listbox" class="ActionListWrap QueryBuilder-ListWrap" aria-label="Suggestions" data-action="
combobox-commit:query-builder#comboboxCommit
mousedown:query-builder#resultsMousedown
" data-target="query-builder.resultsList" data-persist-list="false" id="query-builder-test-results">
<li role="presentation" class="ActionList-sectionDivider">
<h3 role="presentation" class="ActionList-sectionDivider-title QueryBuilder-sectionTitle p-2 text-left" aria-hidden="true"> Explore </h3>
<ul role="presentation">
<li role="option" class="ActionListItem" data-type="url-result" id="query-builder-test-result-enterprise" data-value="Enterprise" aria-label="Enterprise, jump to this explore page">
<a href="/enterprise?ref_loc=search" data-action="click:query-builder#navigate" tabindex="-1" class="QueryBuilder-ListItem-link ActionListContent ActionListContent--visual16 QueryBuilder-ListItem">
<span id="query-builder-test-result-enterprise--leading" class="ActionListItem-visual ActionListItem-visual--leading">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-organization">
<path d="M1.75 16A1.75 1.75 0 0 1 0 14.25V1.75C0 .784.784 0 1.75 0h8.5C11.216 0 12 .784 12 1.75v12.5c0 .085-.006.168-.018.25h2.268a.25.25 0 0 0 .25-.25V8.285a.25.25 0 0 0-.111-.208l-1.055-.703a.749.749 0 1 1 .832-1.248l1.055.703c.487.325.779.871.779 1.456v5.965A1.75 1.75 0 0 1 14.25 16h-3.5a.766.766 0 0 1-.197-.026c-.099.017-.2.026-.303.026h-3a.75.75 0 0 1-.75-.75V14h-1v1.25a.75.75 0 0 1-.75.75Zm-.25-1.75c0 .138.112.25.25.25H4v-1.25a.75.75 0 0 1 .75-.75h2.5a.75.75 0 0 1 .75.75v1.25h2.25a.25.25 0 0 0 .25-.25V1.75a.25.25 0 0 0-.25-.25h-8.5a.25.25 0 0 0-.25.25ZM3.75 6h.5a.75.75 0 0 1 0 1.5h-.5a.75.75 0 0 1 0-1.5ZM3 3.75A.75.75 0 0 1 3.75 3h.5a.75.75 0 0 1 0 1.5h-.5A.75.75 0 0 1 3 3.75Zm4 3A.75.75 0 0 1 7.75 6h.5a.75.75 0 0 1 0 1.5h-.5A.75.75 0 0 1 7 6.75ZM7.75 3h.5a.75.75 0 0 1 0 1.5h-.5a.75.75 0 0 1 0-1.5ZM3 9.75A.75.75 0 0 1 3.75 9h.5a.75.75 0 0 1 0 1.5h-.5A.75.75 0 0 1 3 9.75ZM7.75 9h.5a.75.75 0 0 1 0 1.5h-.5a.75.75 0 0 1 0-1.5Z"></path>
</svg>
</span>
<span class="ActionListItem-descriptionWrap">
<span class="ActionListItem-label text-normal"> <span class="">Enterprise</span> </span>
</span>
<span aria-hidden="true" class="ActionListItem-description QueryBuilder-ListItem-trailing">Learn More</span>
</a>
</li>
<li role="option" class="ActionListItem" data-type="url-result" id="query-builder-test-result-security" data-value="Security" aria-label="Security, jump to this explore page">
<a href="/security?ref_loc=search" data-action="click:query-builder#navigate" tabindex="-1" class="QueryBuilder-ListItem-link ActionListContent ActionListContent--visual16 QueryBuilder-ListItem">
<span id="query-builder-test-result-security--leading" class="ActionListItem-visual ActionListItem-visual--leading">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-shield-check">
<path d="m8.533.133 5.25 1.68A1.75 1.75 0 0 1 15 3.48V7c0 1.566-.32 3.182-1.303 4.682-.983 1.498-2.585 2.813-5.032 3.855a1.697 1.697 0 0 1-1.33 0c-2.447-1.042-4.049-2.357-5.032-3.855C1.32 10.182 1 8.566 1 7V3.48a1.75 1.75 0 0 1 1.217-1.667l5.25-1.68a1.748 1.748 0 0 1 1.066 0Zm-.61 1.429.001.001-5.25 1.68a.251.251 0 0 0-.174.237V7c0 1.36.275 2.666 1.057 3.859.784 1.194 2.121 2.342 4.366 3.298a.196.196 0 0 0 .154 0c2.245-.957 3.582-2.103 4.366-3.297C13.225 9.666 13.5 8.358 13.5 7V3.48a.25.25 0 0 0-.174-.238l-5.25-1.68a.25.25 0 0 0-.153 0ZM11.28 6.28l-3.5 3.5a.75.75 0 0 1-1.06 0l-1.5-1.5a.749.749 0 0 1 .326-1.275.749.749 0 0 1 .734.215l.97.97 2.97-2.97a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042Z"></path>
</svg>
</span>
<span class="ActionListItem-descriptionWrap">
<span class="ActionListItem-label text-normal"> <span class="">Security</span> </span>
</span>
<span aria-hidden="true" class="ActionListItem-description QueryBuilder-ListItem-trailing">Learn More</span>
</a>
</li>
<li role="option" class="ActionListItem" data-type="url-result" id="query-builder-test-result-copilot" data-value="Copilot" aria-label="Copilot, jump to this explore page">
<a href="/features/copilot?ref_loc=search" data-action="click:query-builder#navigate" tabindex="-1" class="QueryBuilder-ListItem-link ActionListContent ActionListContent--visual16 QueryBuilder-ListItem">
<span id="query-builder-test-result-copilot--leading" class="ActionListItem-visual ActionListItem-visual--leading">
<svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-copilot">
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THE WORLD’S MOST WIDELY ADOPTED AI DEVELOPER TOOL.
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THE COMPETITIVE ADVANTAGE DEVELOPERS ASK FOR BY NAME.
PROVEN TO INCREASE DEVELOPER PRODUCTIVITY AND ACCELERATE THE PACE OF SOFTWARE
DEVELOPMENT.
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DESIGNED BY LEADERS IN AI SO YOU CAN BUILD WITH CONFIDENCE.
COMMITTED TO YOUR PRIVACY, SECURITY, AND TRUST.
Visit the GitHub Copilot Trust Center
DUOLINGO EMPOWERS ITS ENGINEERS TO BE FORCE MULTIPLIERS FOR EXPERTISE WITH
GITHUB COPILOT, CODESPACES.
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THE INDUSTRY
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THE AI CODING ASSISTANT
ELEVATING DEVELOPER WORKFLOWS.
ACCELERATE WORKFLOWS
Start a conversation about your codebase. Whether you’re hunting down a bug or
designing a new feature—when you’re stuck, ask
GitHub Copilot.
* Improve code quality and security. Developers feel more confident in their
code quality when authoring code with GitHub Copilot. And with the built-in
vulnerability prevention system, insecure coding patterns get blocked in real
time.
* Enable greater collaboration. GitHub Copilot’s the newest member of your
team. You can ask general programming questions or very specific ones about
your codebase to get answers fast, learn your way around, explain a
mysterious regex, or get suggestions on how to improve legacy code.
GET AI-BASED SUGGESTIONS IN REAL TIME.
GitHub Copilot suggests code completions as developers type and turns natural
language prompts into coding suggestions based on the project's context and
style conventions.
Read the GitHub Copilot Quickstart docs
AVAILABLE FOR COPILOT ENTERPRISEDOCS THAT FEEL TAILORED FOR YOU.
Spend less time searching and more time learning, by getting personalized
answers that are grounded in your organization’s knowledge base, with inline
citations. Load content → Ask question → Profit.
Read the GitHub Copilot Chat docs
AVAILABLE FOR COPILOT ENTERPRISEPULL REQUESTS THAT TELL A STORY.
GitHub Copilot keeps track of your work, suggests descriptions, and helps
reviewers reason about your changes.
Read the GitHub Copilot pull request summaries docs
COMING SOON AS AN ADD-ONPREFER BESPOKE? FINE-TUNE A PRIVATE, CUSTOM MODEL THAT
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What's included
Chat
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* Debugging and security remediation assistance
* Conversations tailored to your organization’s repositories
* Answers based on your organization’s knowledge base
* Access to knowledge from top open source repositories
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Supported environments
* IDE, CLI and GitHub Mobile¹
* GitHub.com
Management and policies
* Public code filter
* User management
* Data excluded from training by default
* IP indemnity
* Content exclusions
* SAML SSO authentication²
* Requires GitHub Enterprise Cloud
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developer experience.
$19USD
per user / month
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What's included
Chat
* Unlimited messages and interactions
* Context-aware coding support and explanations
* Debugging and security remediation assistance
* Conversations tailored to your organization’s repositories
* Answers based on your organization’s knowledge base
* Access to knowledge from top open source repositories
* Pull request diff analysis
* Web search powered by Bing (beta)
Code completion
* Real time code suggestions
* Comments to code
* Fine-tuned models (coming soon as add-on)
Smart actions
* Inline chat and prompt suggestions
* Slash commands and context variables
* Commit message generation
* Pull request description and summarization
Supported environments
* IDE, CLI and GitHub Mobile¹
* GitHub.com
Management and policies
* Public code filter
* User management
* Data excluded from training by default
* IP indemnity
* Content exclusions
* SAML SSO authentication²
* Requires GitHub Enterprise Cloud
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New
COPILOT ENTERPRISE
For companies looking to customize GitHub Copilot to their organization and
infuse AI across the developer workflow.
$39USD
per user / month
Contact sales
--------------------------------------------------------------------------------
What's included
Chat
* Unlimited messages and interactions
* Context-aware coding support and explanations
* Debugging and security remediation assistance
* Conversations tailored to your organization’s repositories
* Answers based on your organization’s knowledge base
* Access to knowledge from top open source repositories
* Pull request diff analysis
* Web search powered by Bing (beta)
Code completion
* Real time code suggestions
* Comments to code
* Fine-tuned models (coming soon as add-on)
Smart actions
* Inline chat and prompt suggestions
* Slash commands and context variables
* Commit message generation
* Pull request description and summarization
Supported environments
* IDE, CLI and GitHub Mobile¹
* GitHub.com
Management and policies
* Public code filter
* User management
* Data excluded from training by default
* IP indemnity
* Content exclusions
* SAML SSO authentication²
* Requires GitHub Enterprise Cloud
GET THE MOST OUT OF GITHUB COPILOT.
HANDS-ON CONSULTING, GUIDED WORKSHOPS, AND TRAINING.
Insights, best practices, and knowledge to help you adopt GitHub quickly and
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FREQUENTLY ASKED QUESTIONS.
GENERAL
WHAT IS GITHUB COPILOT?
GitHub Copilot transforms the developer experience. Backed by the leaders in AI,
Copilot provides contextualized assistance throughout the software development
lifecycle, from code completions and chat assistance in the IDE to code
explanations and answers to docs in GitHub and more. With Copilot elevating
their workflow, developers can focus on more: value, innovation, and happiness.
GitHub Copilot enables developers to focus more energy on problem solving and
collaboration and spend less effort on the mundane and boilerplate. That’s why
developers who use Copilot report up to 75% higher satisfaction with their jobs
than those who don’t and are up to 55% more productive at writing code without
sacrifice to quality, which all adds up to engaged developers shipping great
software faster. without sacrifice to quality, which all adds up to engaged
developers shipping great software faster.
GitHub Copilot integrates with leading editors, including Visual Studio Code,
Visual Studio, JetBrains IDEs, and Neovim, and, unlike other AI coding
assistants, is natively built into GitHub. Growing to millions of individual
users and tens of thousands of business customers, Copilot is the world’s most
widely adopted AI developer tool and the competitive advantage developers ask
for by name.
WHAT ARE THE DIFFERENCES BETWEEN THE GITHUB COPILOT BUSINESS, GITHUB COPILOT
ENTERPRISE, AND GITHUB COPILOT INDIVIDUAL PLANS?
GitHub Copilot has multiple offerings for organizations and an offering for
individual developers. All the offerings include both code completion and chat
assistance. The primary differences between the organization offerings and the
individual offering are license management, policy management, and IP indemnity.
Organizations can choose between GitHub Copilot Business and GitHub Copilot
Enterprise. GitHub Copilot Business primarily features GitHub Copilot in the
coding environment - that is the IDE and CLI. In early-2024, it will also
include GitHub Copilot in GitHub Mobile. GitHub Copilot Enterprise includes
everything in GitHub Copilot Business and adds an additional layer of
customization for organizations as well as GitHub Copilot integrated into
GitHub.com as a chat interface to allow developers to converse about their
codebase and action buttons throughout the platform. GitHub Copilot Enterprise
can index an organization’s codebase for a deeper understanding of the
customer’s knowledge for more tailored suggestions and will offer customers
access to fine-tuned custom, private models for code completion.
GitHub Copilot Individual is designed for individual developers, freelancers,
students, educators, and open source maintainers. The plan includes all the
features of GitHub Copilot Business except organizational license management,
policy management, and IP indemnity.
WHAT LANGUAGES, IDES, AND PLATFORMS DOES GITHUB COPILOT SUPPORT?
GitHub Copilot is trained on all languages that appear in public repositories.
For each language, the quality of suggestions you receive may depend on the
volume and diversity of training data for that language. For example, JavaScript
is well-represented in public repositories and is one of GitHub Copilot’s best
supported languages. Languages with less representation in public repositories
may produce fewer or less robust suggestions.
GitHub Copilot is available as an extension in Visual Studio Code, Visual
Studio, Vim, Neovim, the JetBrains suite of IDEs, and Azure Data Studio.
Although code completion functionality is available across all these extensions,
chat functionality is currently available only in Visual Studio Code, JetBrains
and Visual Studio. GitHub Copilot is also supported in terminals through GitHub
CLI. With the GitHub Copilot Enterprise plan, GitHub Copilot is natively
integrated into GitHub.com. All plans will feature GitHub Copilot in GitHub
Mobile.
WHAT DATA HAS GITHUB COPILOT BEEN TRAINED ON?
GitHub Copilot is powered by generative AI models developed by GitHub, OpenAI,
and Microsoft. It has been trained on natural language text and source code from
publicly available sources, including code in public repositories on GitHub.
DOES GITHUB COPILOT “COPY/PASTE”?
No, GitHub Copilot generates suggestions using probabilistic determination.
* When thinking about intellectual property and open source issues, it is
critical to understand how GitHub Copilot really works. The AI models that
create Copilot’s suggestions may be trained on public code, but do not
contain any code. When they generate a suggestion, they are not “copying and
pasting” from any codebase.
* To generate a code suggestion, the Copilot extension begins by examining the
code in your editor—focusing on the lines just before and after your cursor,
but also information including other files open in your editor and the URLs
of repositories or file paths to identify relevant context. That information
is sent to Copilot’s model, to make a probabilistic determination of what is
likely to come next and generate suggestions.
* To generate a suggestion for chat in the code editor, the Copilot extension
creates a contextual prompt by combining your prompt with additional context
including the code file open in your active document, your code selection,
and general workspace information, such as frameworks, languages, and
dependencies. That information is sent to Copilot’s model, to make a
probabilistic determination of what is likely to come next and generate
suggestions.
* To generate a suggestion for chat on GitHub.com, such as providing an answer
to a question from your chat prompt, Copilot creates a contextual prompt by
combining your prompt with additional context including previous prompts, the
open pages on GitHub.com as well as retrieved context from your codebase or
Bing search. That information is sent to Copilot’s model, to make a
probabilistic determination of what is likely to come next and generate
suggestions.
PRIVACY
WHAT PERSONAL DATA DOES GITHUB COPILOT PROCESS?
GitHub Copilot processes personal data based on how Copilot is accessed and
used: whether via github.com, mobile app, extensions, or one of various IDE
extensions, or through features like suggestions for the command line interface
(CLI), IDE code completions, or personalized chat on GitHub.com. The types of
personal data processed may include:
* User Engagement Data: This includes pseudonymous identifiers captured on user
interactions with Copilot, such as accepted or dismissed completions, error
messages, system logs, and product usage metrics.
* Prompts: These are inputs for chat or code, along with context, sent to
Copilot's AI to generate suggestions.
* Suggestions: These are the AI-generated code lines or chat responses provided
to users based on their prompts.
* Feedback Data: This comprises real-time user feedback, including reactions
(e.g., thumbs up/down) and optional comments, along with feedback from
support tickets. Feedback data is retained as long as necessary.
DOES GITHUB USE COPILOT BUSINESS OR ENTERPRISE DATA TO TRAIN GITHUB’S MODEL?
No. GitHub does not use either Copilot Business or Enterprise data to train its
models.
HOW DOES GITHUB USE THE COPILOT DATA?
How GitHub uses Copilot data depends on the access method and purpose. Users can
access GitHub Copilot through the web, extensions, mobile apps, computer
terminal, and various IDEs (Integrated Development Environments). When directed
by our customers, who are the data controllers, GitHub uses personal data to:
* Deliver, maintain, and update the services as per the customer's
configuration and usage, to ensure personalized experiences and
recommendations
* Troubleshoot, which involves preventing, detecting, resolving, and mitigating
issues, including security incidents and product-related problems, by fixing
software bugs and maintaining the online services' functionality and
up-to-dateness
* Enhance user productivity, reliability, effectiveness, quality, privacy,
accessibility, and security by keeping the service current and operational
These practices are outlined in GitHub’s Data Protection Agreement (DPA), which
details our data handling commitments to our data controller customers.
GitHub uses certain personal data with customer authorization under the DPA, for
the following purposes:
* Billing and account management
* To generate summary reports for calculating employee commissions and partner
incentives
* To produce aggregated reports for internal use and strategic planning,
covering areas like forecasting, revenue analysis, capacity planning, and
product strategy,
For details on GitHub's data processing activities as a controller, particularly
for Copilot Individual customers, refer to the GitHub Privacy Statement.
HOW LONG DOES GITHUB COPILOT RETAIN PERSONAL DATA?
If and for how long GitHub’s retains Copilot data depends on how a Copilot user
accesses Copilot and for what purpose. The default settings are as follows:
Access through IDE for Chat and Code Completions
* Prompts and Suggestions: Not retained
* User Engagement Data: Kept for two years.
* Feedback Data: Stored for as long as needed for its intended purpose.
All other GitHub Copilot access and use
* Prompts and Suggestions: Retained for 28 days.
* User Engagement Data: Kept for two years.
* Feedback Data: Stored for as long as needed for its intended purpose.
WHY DO SOME COPILOT FEATURES RETAIN PROMPTS AND SUGGESTIONS?
Retaining prompts and suggestions is necessary for chat on github.com, mobile,
and CLI Copilot because those features’ effectiveness depends on using thread
history to improve responses. The Copilot model requires access to previous
interactions to deliver accurate and relevant suggestions.
DOES GITHUB COPILOT SUPPORT COMPLIANCE WITH THE GDPR AND OTHER DATA PROTECTION
LAWS?
Yes. GitHub and customers can enter a Data Protection Agreement that supports
compliance with the GDPR and similar legislation.
DOES GITHUB COPILOT EVER OUTPUT PERSONAL DATA?
While we've designed GitHub Copilot with privacy in mind, the expansive
definition of personal data under legislation like the EU’s General Data
Protection Regulation (GDPR) means we can't guarantee it will never output such
data. The Large Language Model (LLM) powering GitHub Copilot was trained on
public code and there were instances in our tests where the tool made
suggestions resembling personal data. These suggestions were typically
synthesized and not tied to real individuals.
HOW DOES COPILOT ALLOW USERS TO ACCESS, ALTER OR DELETE PERSONAL DATA?
These actions are available to Copilot users as described in the GitHub Privacy
Statement.
RESPONSIBLE AI
WHAT ARE THE INTELLECTUAL PROPERTY CONSIDERATIONS WHEN USING GITHUB COPILOT?
The primary IP considerations for GitHub Copilot relate to copyright. The model
that powers Copilot is trained on a broad collection of publicly accessible
code, which may include copyrighted code, and Copilot’s suggestions (in rare
instances) may resemble the code its model was trained on. Here’s some basic
information you should know about these considerations:
Copyright law permits the use of copyrighted works to train AI models:
Countries around the world have provisions in their copyright laws that enable
machines to learn, understand, extract patterns, and facts from copyrighted
materials, including software code. For example, the European Union, Japan, and
Singapore, have express provisions permitting machine learning to develop AI
models. Other countries including Canada, India, and the United States also
permit such training under their fair use/fair dealing provisions. GitHub
Copilot’s AI model was trained with the use of code from GitHub’s public
repositories—which are publicly accessible and within the scope of permissible
copyright use.
What about copyright risk in suggestions? In rare instances (less than 1% based
on GitHub’s research), suggestions from GitHub may match examples of code used
to train GitHub’s AI model. Again, Copilot does not “look up” or “copy and
paste” code, but is instead using context from a user’s workspace to synthesize
and generate a suggestion.
Our experience shows that matching suggestions are most likely to occur in two
situations: (i) when there is little or no context in the code editor for
Copilot’s model to synthesize, or (ii) when a matching suggestion represents a
common approach or method. If a code suggestion matches existing code, there is
risk that using that suggestion could trigger claims of copyright infringement,
which would depend on the amount and nature of code used, and the context of how
the code is used. In many ways, this is the same risk that arises when using any
code that a developer does not originate, such as copying code from an online
source, or reusing code from a library. That is why responsible organizations
and developers recommend that users employ code scanning policies to identify
and evaluate potential matching code.
In Copilot, you can opt whether to allow Copilot to suggest code completions
that match publicly available code on GitHub.com. For more information, see
"Configuring GitHub Copilot settings on GitHub.com". If you have allowed
suggestions that match public code, GitHub Copilot can provide you with details
about the matching code when you accept such suggestions. Matching code does not
necessarily mean copyright infringement, so it is ultimately up to the user to
determine whether to use the suggestion, and what and who to attribute (along
with other license compliance) in appropriate circumstances.
DOES GITHUB COPILOT INCLUDE A FILTERING MECHANISM TO MITIGATE RISK?
Yes, GitHub Copilot does include an optional code referencing filter to detect
and suppress certain suggestions that match public code on GitHub.
* GitHub has created a duplication detection filter to detect and suppress
suggestions that contain code segments over a certain length that match
public code on GitHub. This filter can be enabled by the administrator for
your enterprise and it can apply for all organizations within your
enterprise, or the administrator can defer control to individual
organizations.
* With the filter enabled, Copilot checks code suggestions for matches or
near-matches against public code on GitHub of 65 lexemes or more (on
average,150 characters). If there is a match, the suggestion will not be
shown to the user.
* In addition to off-topic, harmful, and offensive output filters, GitHub
Copilot also scans the outputs for vulnerable code.
DOES GITHUB COPILOT INCLUDE FEATURES TO MAKE IT EASIER FOR USERS TO IDENTIFY
POTENTIALLY RELEVANT OPEN SOURCE LICENSES FOR MATCHING SUGGESTIONS?
Yes, GitHub Copilot is previewing a code referencing feature as an additional
tool to assist users to find and review potentially relevant open source
licenses. Code referencing is currently available in Visual Studio Code. This
feature searches across public GitHub repositories for code that matches a
Copilot suggestion. If there’s a match, users will find its information
displayed in the Copilot console log, including where the match occurred, any
applicable licenses, and a deep link to learn more. The deep link will take
users to a navigable page on GitHub.com to browse examples of the code match and
their repository licenses, and see how many repositories—including ones without
licenses—that code appears in, as well as links to those repositories. Copilot
users can review this information to determine whether the applicable
suggestions are suitable for use, and whether additional measures may be
necessary to use them.
WHO OWNS THE SUGGESTIONS PROVIDED BY GITHUB COPILOT?
We don’t determine whether a suggestion is capable of being owned, but we are
clear that GitHub does not claim ownership of a suggestion. Whether a suggestion
generated by an AI model can be owned depends on many factors (e.g. the
intellectual property law in the relevant country, the length of the suggestion,
the extent that suggestion is considered ‘functional’ instead of expressive,
etc).
* If a suggestion is capable of being owned, our terms are clear: GitHub does
not claim ownership.
* GitHub does not claim ownership of any suggestion. In certain cases, it is
possible for Copilot to produce similar suggestions to different users. For
example, two unrelated users both starting new files to code the quicksort
algorithm in Java will likely get the same suggestion. The possibility of
providing similar suggestions to multiple users is a common part of
generative AI systems.
CAN GITHUB COPILOT INTRODUCE INSECURE CODE IN ITS SUGGESTIONS?
Public code may contain insecure coding patterns, bugs, or references to
outdated APIs or idioms. When GitHub Copilot synthesizes code suggestions based
on this data, it can also synthesize code that contains these undesirable
patterns. Copilot has filters in place that either block or notify users of
insecure code patterns that are detected in Copilot suggestions. These filters
target the most common vulnerable coding patterns, including hardcoded
credentials, SQL injections, and path injections. Additionally, inrecent years
we’ve provided tools such as GitHub Advanced Security, GitHub Actions,
Dependabot, and CodeQL to open source projects to help improve code quality. Of
course, you should always use GitHub Copilot together with good testing and code
review practices and security tools, as well as your own judgment.
IS GITHUB COPILOT INTENDED TO FULLY AUTOMATE CODE GENERATION AND REPLACE
DEVELOPERS?
No. Copilot is a tool intended to make developers more efficient. It’s not
intended to replace developers, who should continue to apply the same sorts of
safeguards and diligence they would apply with regard to any third-party code of
unknown origin.
* The product is called “Copilot” not “Autopilot” and it’s not intended to
generate code without oversight. You should use exactly the same sorts of
safeguards and diligence with Copilot’s suggestions as you would use with any
third-party code.
* Identifying best practices for use of third party code is beyond the scope of
this section. That said, whatever practices your organization currently uses
– rigorous functionality testing, code scanning, security testing, etc. – you
should continue these policies with Copilot’s suggestions. Moreover, you
should make sure your code editor or editor does not automatically compile or
run generated code before you review it.
CAN GITHUB COPILOT USERS SIMPLY USE SUGGESTIONS WITHOUT CONCERN?
Not necessarily. GitHub Copilot users should align their use of Copilot with
their respective risk tolerances.
* As noted above, GitHub Copilot is not intended to replace developers, or
their individual
skill and judgment, and is not intended to fully automate the process of code
development. The same risks that apply to the use of any third-party code
apply to the use of Copilot’s suggestions.
* Depending on your particular use case, you should consider implementing the
protections discussed above. It is your responsibility to assess what is
appropriate for the situation and implement appropriate safeguards.
* You’re entitled to IP indemnification from GitHub for the unmodified
suggestions when Copilot’s filtering is enabled. If you do elect to enable
this feature, the copyright responsibility is ours, not our customers. As
part of our ongoing commitment to responsible AI, GitHub and Microsoft
extends our IP indemnity and protection support to our customers who are
empowering their teams with GitHub Copilot. See Microsoft's Copilot Copyright
Commitment for more details.
DOES GITHUB COPILOT SUPPORT ACCESSIBILITY FEATURES?
We are conducting internal testing of GitHub Copilot’s ease of use by developers
with disabilities and working to ensure that GitHub Copilot is accessible to all
developers. Please feel free to share your feedback on GitHub Copilot
accessibility in our feedback forum.
DOES GITHUB COPILOT PRODUCE OFFENSIVE OUTPUTS?
GitHub Copilot includes filters to block offensive language in the prompts and
to avoid synthesizing suggestions in sensitive contexts. We continue to work on
improving the filter system to more intelligently detect and remove offensive
outputs. If you see offensive outputs, please report them directly to
copilot-safety@github.com so that we can improve our safeguards. GitHub takes
this challenge very seriously and we are committed to addressing it.
WILL GITHUB COPILOT WORK AS WELL USING LANGUAGES OTHER THAN ENGLISH?
Given public sources are predominantly in English, GitHub Copilot will likely
work less well in scenarios where natural language prompts provided by the
developer are not in English and/or are grammatically incorrect. Therefore,
non-English speakers might experience a lower quality of service.
UPCOMING FEATURES AND OFFERINGS
HOW DOES THE GITHUB COPILOT CUSTOMIZATION WAITLIST WORK?
By joining the GitHub Copilot Customization waitlist, you are expressing your
intent to be contacted about the upcoming GitHub Copilot offering. You may also
get an opportunity to test a pre-release version of the product. If you are an
administrator for an organization using GitHub Enterprise Cloud or GitHub
Copilot Business, you will be able to nominate a specific organization to try
GitHub Copilot Customization in private beta.
GITHUB COPILOT CAPABILITIES FOR PULL REQUESTS ARE ONLY AVAILABLE THROUGH THE NEW
GITHUB COPILOT ENTERPRISE PLAN. WHAT DOES THAT MEAN FOR CURRENT PARTICIPANTS IN
THE GITHUB NEXT TECHNICAL PREVIEW FOR GITHUB COPILOT FOR PULL REQUESTS OR ARE ON
THAT WAITLIST?
We have closed the waitlist for the GitHub Next technical preview. Users that
have already been admitted to the technical preview can continue to experiment
with GitHub Copilot for Pull Requests. GitHub Copilot features for pull requests
are currently limited to the GitHub Copilot Enterprise plan, which is generally
available to organizations using GitHub Enterprise Cloud.
GITHUB COPILOT CAPABILITIES FOR KNOWLEDGE BASES ARE ONLY AVAILABLE THROUGH THE
NEW GITHUB COPILOT ENTERPRISE PLAN. WHAT DOES THAT MEAN FOR CURRENT PARTICIPANTS
IN THE GITHUB NEXT TECHNICAL PREVIEW FOR GITHUB COPILOT FOR DOCS OR ARE ON THAT
WAITLIST?
We have closed the waitlist for the GitHub Next technical preview. Users that
have already been admitted to the technical preview can continue to experiment
with GitHub Copilot for Docs. GitHub Copilot features for documentation are
currently limited to the GitHub Copilot Enterprise plan, which is generally
available to organizations using GitHub Enterprise Cloud.
WHEN WILL COPILOT CHAT BE AVAILABLE ON MOBILE?
We do not have a set timeline for making Copilot Chat available on mobile. We’ll
continue to update this page with the latest information on new capabilities for
various plans.
GeneralPrivacyResponsible AIUpcoming features and offerings
GENERAL
WHAT IS GITHUB COPILOT?
GitHub Copilot transforms the developer experience. Backed by the leaders in AI,
Copilot provides contextualized assistance throughout the software development
lifecycle, from code completions and chat assistance in the IDE to code
explanations and answers to docs in GitHub and more. With Copilot elevating
their workflow, developers can focus on more: value, innovation, and happiness.
GitHub Copilot enables developers to focus more energy on problem solving and
collaboration and spend less effort on the mundane and boilerplate. That’s why
developers who use Copilot report up to 75% higher satisfaction with their jobs
than those who don’t and are up to 55% more productive at writing code without
sacrifice to quality, which all adds up to engaged developers shipping great
software faster. without sacrifice to quality, which all adds up to engaged
developers shipping great software faster.
GitHub Copilot integrates with leading editors, including Visual Studio Code,
Visual Studio, JetBrains IDEs, and Neovim, and, unlike other AI coding
assistants, is natively built into GitHub. Growing to millions of individual
users and tens of thousands of business customers, Copilot is the world’s most
widely adopted AI developer tool and the competitive advantage developers ask
for by name.
WHAT ARE THE DIFFERENCES BETWEEN THE GITHUB COPILOT BUSINESS, GITHUB COPILOT
ENTERPRISE, AND GITHUB COPILOT INDIVIDUAL PLANS?
GitHub Copilot has multiple offerings for organizations and an offering for
individual developers. All the offerings include both code completion and chat
assistance. The primary differences between the organization offerings and the
individual offering are license management, policy management, and IP indemnity.
Organizations can choose between GitHub Copilot Business and GitHub Copilot
Enterprise. GitHub Copilot Business primarily features GitHub Copilot in the
coding environment - that is the IDE and CLI. In early-2024, it will also
include GitHub Copilot in GitHub Mobile. GitHub Copilot Enterprise includes
everything in GitHub Copilot Business and adds an additional layer of
customization for organizations as well as GitHub Copilot integrated into
GitHub.com as a chat interface to allow developers to converse about their
codebase and action buttons throughout the platform. GitHub Copilot Enterprise
can index an organization’s codebase for a deeper understanding of the
customer’s knowledge for more tailored suggestions and will offer customers
access to fine-tuned custom, private models for code completion.
GitHub Copilot Individual is designed for individual developers, freelancers,
students, educators, and open source maintainers. The plan includes all the
features of GitHub Copilot Business except organizational license management,
policy management, and IP indemnity.
WHAT LANGUAGES, IDES, AND PLATFORMS DOES GITHUB COPILOT SUPPORT?
GitHub Copilot is trained on all languages that appear in public repositories.
For each language, the quality of suggestions you receive may depend on the
volume and diversity of training data for that language. For example, JavaScript
is well-represented in public repositories and is one of GitHub Copilot’s best
supported languages. Languages with less representation in public repositories
may produce fewer or less robust suggestions.
GitHub Copilot is available as an extension in Visual Studio Code, Visual
Studio, Vim, Neovim, the JetBrains suite of IDEs, and Azure Data Studio.
Although code completion functionality is available across all these extensions,
chat functionality is currently available only in Visual Studio Code, JetBrains
and Visual Studio. GitHub Copilot is also supported in terminals through GitHub
CLI. With the GitHub Copilot Enterprise plan, GitHub Copilot is natively
integrated into GitHub.com. All plans will feature GitHub Copilot in GitHub
Mobile.
WHAT DATA HAS GITHUB COPILOT BEEN TRAINED ON?
GitHub Copilot is powered by generative AI models developed by GitHub, OpenAI,
and Microsoft. It has been trained on natural language text and source code from
publicly available sources, including code in public repositories on GitHub.
DOES GITHUB COPILOT “COPY/PASTE”?
No, GitHub Copilot generates suggestions using probabilistic determination.
* When thinking about intellectual property and open source issues, it is
critical to understand how GitHub Copilot really works. The AI models that
create Copilot’s suggestions may be trained on public code, but do not
contain any code. When they generate a suggestion, they are not “copying and
pasting” from any codebase.
* To generate a code suggestion, the Copilot extension begins by examining the
code in your editor—focusing on the lines just before and after your cursor,
but also information including other files open in your editor and the URLs
of repositories or file paths to identify relevant context. That information
is sent to Copilot’s model, to make a probabilistic determination of what is
likely to come next and generate suggestions.
* To generate a suggestion for chat in the code editor, the Copilot extension
creates a contextual prompt by combining your prompt with additional context
including the code file open in your active document, your code selection,
and general workspace information, such as frameworks, languages, and
dependencies. That information is sent to Copilot’s model, to make a
probabilistic determination of what is likely to come next and generate
suggestions.
* To generate a suggestion for chat on GitHub.com, such as providing an answer
to a question from your chat prompt, Copilot creates a contextual prompt by
combining your prompt with additional context including previous prompts, the
open pages on GitHub.com as well as retrieved context from your codebase or
Bing search. That information is sent to Copilot’s model, to make a
probabilistic determination of what is likely to come next and generate
suggestions.
PRIVACY
WHAT PERSONAL DATA DOES GITHUB COPILOT PROCESS?
GitHub Copilot processes personal data based on how Copilot is accessed and
used: whether via github.com, mobile app, extensions, or one of various IDE
extensions, or through features like suggestions for the command line interface
(CLI), IDE code completions, or personalized chat on GitHub.com. The types of
personal data processed may include:
* User Engagement Data: This includes pseudonymous identifiers captured on user
interactions with Copilot, such as accepted or dismissed completions, error
messages, system logs, and product usage metrics.
* Prompts: These are inputs for chat or code, along with context, sent to
Copilot's AI to generate suggestions.
* Suggestions: These are the AI-generated code lines or chat responses provided
to users based on their prompts.
* Feedback Data: This comprises real-time user feedback, including reactions
(e.g., thumbs up/down) and optional comments, along with feedback from
support tickets. Feedback data is retained as long as necessary.
DOES GITHUB USE COPILOT BUSINESS OR ENTERPRISE DATA TO TRAIN GITHUB’S MODEL?
No. GitHub does not use either Copilot Business or Enterprise data to train its
models.
HOW DOES GITHUB USE THE COPILOT DATA?
How GitHub uses Copilot data depends on the access method and purpose. Users can
access GitHub Copilot through the web, extensions, mobile apps, computer
terminal, and various IDEs (Integrated Development Environments). When directed
by our customers, who are the data controllers, GitHub uses personal data to:
* Deliver, maintain, and update the services as per the customer's
configuration and usage, to ensure personalized experiences and
recommendations
* Troubleshoot, which involves preventing, detecting, resolving, and mitigating
issues, including security incidents and product-related problems, by fixing
software bugs and maintaining the online services' functionality and
up-to-dateness
* Enhance user productivity, reliability, effectiveness, quality, privacy,
accessibility, and security by keeping the service current and operational
These practices are outlined in GitHub’s Data Protection Agreement (DPA), which
details our data handling commitments to our data controller customers.
GitHub uses certain personal data with customer authorization under the DPA, for
the following purposes:
* Billing and account management
* To generate summary reports for calculating employee commissions and partner
incentives
* To produce aggregated reports for internal use and strategic planning,
covering areas like forecasting, revenue analysis, capacity planning, and
product strategy,
For details on GitHub's data processing activities as a controller, particularly
for Copilot Individual customers, refer to the GitHub Privacy Statement.
HOW LONG DOES GITHUB COPILOT RETAIN PERSONAL DATA?
If and for how long GitHub’s retains Copilot data depends on how a Copilot user
accesses Copilot and for what purpose. The default settings are as follows:
Access through IDE for Chat and Code Completions
* Prompts and Suggestions: Not retained
* User Engagement Data: Kept for two years.
* Feedback Data: Stored for as long as needed for its intended purpose.
All other GitHub Copilot access and use
* Prompts and Suggestions: Retained for 28 days.
* User Engagement Data: Kept for two years.
* Feedback Data: Stored for as long as needed for its intended purpose.
WHY DO SOME COPILOT FEATURES RETAIN PROMPTS AND SUGGESTIONS?
Retaining prompts and suggestions is necessary for chat on github.com, mobile,
and CLI Copilot because those features’ effectiveness depends on using thread
history to improve responses. The Copilot model requires access to previous
interactions to deliver accurate and relevant suggestions.
DOES GITHUB COPILOT SUPPORT COMPLIANCE WITH THE GDPR AND OTHER DATA PROTECTION
LAWS?
Yes. GitHub and customers can enter a Data Protection Agreement that supports
compliance with the GDPR and similar legislation.
DOES GITHUB COPILOT EVER OUTPUT PERSONAL DATA?
While we've designed GitHub Copilot with privacy in mind, the expansive
definition of personal data under legislation like the EU’s General Data
Protection Regulation (GDPR) means we can't guarantee it will never output such
data. The Large Language Model (LLM) powering GitHub Copilot was trained on
public code and there were instances in our tests where the tool made
suggestions resembling personal data. These suggestions were typically
synthesized and not tied to real individuals.
HOW DOES COPILOT ALLOW USERS TO ACCESS, ALTER OR DELETE PERSONAL DATA?
These actions are available to Copilot users as described in the GitHub Privacy
Statement.
RESPONSIBLE AI
WHAT ARE THE INTELLECTUAL PROPERTY CONSIDERATIONS WHEN USING GITHUB COPILOT?
The primary IP considerations for GitHub Copilot relate to copyright. The model
that powers Copilot is trained on a broad collection of publicly accessible
code, which may include copyrighted code, and Copilot’s suggestions (in rare
instances) may resemble the code its model was trained on. Here’s some basic
information you should know about these considerations:
Copyright law permits the use of copyrighted works to train AI models:
Countries around the world have provisions in their copyright laws that enable
machines to learn, understand, extract patterns, and facts from copyrighted
materials, including software code. For example, the European Union, Japan, and
Singapore, have express provisions permitting machine learning to develop AI
models. Other countries including Canada, India, and the United States also
permit such training under their fair use/fair dealing provisions. GitHub
Copilot’s AI model was trained with the use of code from GitHub’s public
repositories—which are publicly accessible and within the scope of permissible
copyright use.
What about copyright risk in suggestions? In rare instances (less than 1% based
on GitHub’s research), suggestions from GitHub may match examples of code used
to train GitHub’s AI model. Again, Copilot does not “look up” or “copy and
paste” code, but is instead using context from a user’s workspace to synthesize
and generate a suggestion.
Our experience shows that matching suggestions are most likely to occur in two
situations: (i) when there is little or no context in the code editor for
Copilot’s model to synthesize, or (ii) when a matching suggestion represents a
common approach or method. If a code suggestion matches existing code, there is
risk that using that suggestion could trigger claims of copyright infringement,
which would depend on the amount and nature of code used, and the context of how
the code is used. In many ways, this is the same risk that arises when using any
code that a developer does not originate, such as copying code from an online
source, or reusing code from a library. That is why responsible organizations
and developers recommend that users employ code scanning policies to identify
and evaluate potential matching code.
In Copilot, you can opt whether to allow Copilot to suggest code completions
that match publicly available code on GitHub.com. For more information, see
"Configuring GitHub Copilot settings on GitHub.com". If you have allowed
suggestions that match public code, GitHub Copilot can provide you with details
about the matching code when you accept such suggestions. Matching code does not
necessarily mean copyright infringement, so it is ultimately up to the user to
determine whether to use the suggestion, and what and who to attribute (along
with other license compliance) in appropriate circumstances.
DOES GITHUB COPILOT INCLUDE A FILTERING MECHANISM TO MITIGATE RISK?
Yes, GitHub Copilot does include an optional code referencing filter to detect
and suppress certain suggestions that match public code on GitHub.
* GitHub has created a duplication detection filter to detect and suppress
suggestions that contain code segments over a certain length that match
public code on GitHub. This filter can be enabled by the administrator for
your enterprise and it can apply for all organizations within your
enterprise, or the administrator can defer control to individual
organizations.
* With the filter enabled, Copilot checks code suggestions for matches or
near-matches against public code on GitHub of 65 lexemes or more (on
average,150 characters). If there is a match, the suggestion will not be
shown to the user.
* In addition to off-topic, harmful, and offensive output filters, GitHub
Copilot also scans the outputs for vulnerable code.
DOES GITHUB COPILOT INCLUDE FEATURES TO MAKE IT EASIER FOR USERS TO IDENTIFY
POTENTIALLY RELEVANT OPEN SOURCE LICENSES FOR MATCHING SUGGESTIONS?
Yes, GitHub Copilot is previewing a code referencing feature as an additional
tool to assist users to find and review potentially relevant open source
licenses. Code referencing is currently available in Visual Studio Code. This
feature searches across public GitHub repositories for code that matches a
Copilot suggestion. If there’s a match, users will find its information
displayed in the Copilot console log, including where the match occurred, any
applicable licenses, and a deep link to learn more. The deep link will take
users to a navigable page on GitHub.com to browse examples of the code match and
their repository licenses, and see how many repositories—including ones without
licenses—that code appears in, as well as links to those repositories. Copilot
users can review this information to determine whether the applicable
suggestions are suitable for use, and whether additional measures may be
necessary to use them.
WHO OWNS THE SUGGESTIONS PROVIDED BY GITHUB COPILOT?
We don’t determine whether a suggestion is capable of being owned, but we are
clear that GitHub does not claim ownership of a suggestion. Whether a suggestion
generated by an AI model can be owned depends on many factors (e.g. the
intellectual property law in the relevant country, the length of the suggestion,
the extent that suggestion is considered ‘functional’ instead of expressive,
etc).
* If a suggestion is capable of being owned, our terms are clear: GitHub does
not claim ownership.
* GitHub does not claim ownership of any suggestion. In certain cases, it is
possible for Copilot to produce similar suggestions to different users. For
example, two unrelated users both starting new files to code the quicksort
algorithm in Java will likely get the same suggestion. The possibility of
providing similar suggestions to multiple users is a common part of
generative AI systems.
CAN GITHUB COPILOT INTRODUCE INSECURE CODE IN ITS SUGGESTIONS?
Public code may contain insecure coding patterns, bugs, or references to
outdated APIs or idioms. When GitHub Copilot synthesizes code suggestions based
on this data, it can also synthesize code that contains these undesirable
patterns. Copilot has filters in place that either block or notify users of
insecure code patterns that are detected in Copilot suggestions. These filters
target the most common vulnerable coding patterns, including hardcoded
credentials, SQL injections, and path injections. Additionally, inrecent years
we’ve provided tools such as GitHub Advanced Security, GitHub Actions,
Dependabot, and CodeQL to open source projects to help improve code quality. Of
course, you should always use GitHub Copilot together with good testing and code
review practices and security tools, as well as your own judgment.
IS GITHUB COPILOT INTENDED TO FULLY AUTOMATE CODE GENERATION AND REPLACE
DEVELOPERS?
No. Copilot is a tool intended to make developers more efficient. It’s not
intended to replace developers, who should continue to apply the same sorts of
safeguards and diligence they would apply with regard to any third-party code of
unknown origin.
* The product is called “Copilot” not “Autopilot” and it’s not intended to
generate code without oversight. You should use exactly the same sorts of
safeguards and diligence with Copilot’s suggestions as you would use with any
third-party code.
* Identifying best practices for use of third party code is beyond the scope of
this section. That said, whatever practices your organization currently uses
– rigorous functionality testing, code scanning, security testing, etc. – you
should continue these policies with Copilot’s suggestions. Moreover, you
should make sure your code editor or editor does not automatically compile or
run generated code before you review it.
CAN GITHUB COPILOT USERS SIMPLY USE SUGGESTIONS WITHOUT CONCERN?
Not necessarily. GitHub Copilot users should align their use of Copilot with
their respective risk tolerances.
* As noted above, GitHub Copilot is not intended to replace developers, or
their individual
skill and judgment, and is not intended to fully automate the process of code
development. The same risks that apply to the use of any third-party code
apply to the use of Copilot’s suggestions.
* Depending on your particular use case, you should consider implementing the
protections discussed above. It is your responsibility to assess what is
appropriate for the situation and implement appropriate safeguards.
* You’re entitled to IP indemnification from GitHub for the unmodified
suggestions when Copilot’s filtering is enabled. If you do elect to enable
this feature, the copyright responsibility is ours, not our customers. As
part of our ongoing commitment to responsible AI, GitHub and Microsoft
extends our IP indemnity and protection support to our customers who are
empowering their teams with GitHub Copilot. See Microsoft's Copilot Copyright
Commitment for more details.
DOES GITHUB COPILOT SUPPORT ACCESSIBILITY FEATURES?
We are conducting internal testing of GitHub Copilot’s ease of use by developers
with disabilities and working to ensure that GitHub Copilot is accessible to all
developers. Please feel free to share your feedback on GitHub Copilot
accessibility in our feedback forum.
DOES GITHUB COPILOT PRODUCE OFFENSIVE OUTPUTS?
GitHub Copilot includes filters to block offensive language in the prompts and
to avoid synthesizing suggestions in sensitive contexts. We continue to work on
improving the filter system to more intelligently detect and remove offensive
outputs. If you see offensive outputs, please report them directly to
copilot-safety@github.com so that we can improve our safeguards. GitHub takes
this challenge very seriously and we are committed to addressing it.
WILL GITHUB COPILOT WORK AS WELL USING LANGUAGES OTHER THAN ENGLISH?
Given public sources are predominantly in English, GitHub Copilot will likely
work less well in scenarios where natural language prompts provided by the
developer are not in English and/or are grammatically incorrect. Therefore,
non-English speakers might experience a lower quality of service.
UPCOMING FEATURES AND OFFERINGS
HOW DOES THE GITHUB COPILOT CUSTOMIZATION WAITLIST WORK?
By joining the GitHub Copilot Customization waitlist, you are expressing your
intent to be contacted about the upcoming GitHub Copilot offering. You may also
get an opportunity to test a pre-release version of the product. If you are an
administrator for an organization using GitHub Enterprise Cloud or GitHub
Copilot Business, you will be able to nominate a specific organization to try
GitHub Copilot Customization in private beta.
GITHUB COPILOT CAPABILITIES FOR PULL REQUESTS ARE ONLY AVAILABLE THROUGH THE NEW
GITHUB COPILOT ENTERPRISE PLAN. WHAT DOES THAT MEAN FOR CURRENT PARTICIPANTS IN
THE GITHUB NEXT TECHNICAL PREVIEW FOR GITHUB COPILOT FOR PULL REQUESTS OR ARE ON
THAT WAITLIST?
We have closed the waitlist for the GitHub Next technical preview. Users that
have already been admitted to the technical preview can continue to experiment
with GitHub Copilot for Pull Requests. GitHub Copilot features for pull requests
are currently limited to the GitHub Copilot Enterprise plan, which is generally
available to organizations using GitHub Enterprise Cloud.
GITHUB COPILOT CAPABILITIES FOR KNOWLEDGE BASES ARE ONLY AVAILABLE THROUGH THE
NEW GITHUB COPILOT ENTERPRISE PLAN. WHAT DOES THAT MEAN FOR CURRENT PARTICIPANTS
IN THE GITHUB NEXT TECHNICAL PREVIEW FOR GITHUB COPILOT FOR DOCS OR ARE ON THAT
WAITLIST?
We have closed the waitlist for the GitHub Next technical preview. Users that
have already been admitted to the technical preview can continue to experiment
with GitHub Copilot for Docs. GitHub Copilot features for documentation are
currently limited to the GitHub Copilot Enterprise plan, which is generally
available to organizations using GitHub Enterprise Cloud.
WHEN WILL COPILOT CHAT BE AVAILABLE ON MOBILE?
We do not have a set timeline for making Copilot Chat available on mobile. We’ll
continue to update this page with the latest information on new capabilities for
various plans.
1. Chat in GitHub Mobile is coming soon.
2. Authentication with SAML single sign-on (SSO) available for organizations
using GitHub Enterprise Cloud.
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