fix exa contents advanced toggle

Bumps the production-dependencies group with 35 updates in the
/autogpt_platform/frontend directory:

| Package | From | To |
| --- | --- | --- |
| [@faker-js/faker](https://github.com/faker-js/faker) | `9.6.0` |
`9.8.0` |
|
[@next/third-parties](https://github.com/vercel/next.js/tree/HEAD/packages/third-parties)
| `15.2.1` | `15.3.2` |
| [@radix-ui/react-alert-dialog](https://github.com/radix-ui/primitives)
| `1.1.6` | `1.1.13` |
| [@radix-ui/react-avatar](https://github.com/radix-ui/primitives) |
`1.1.3` | `1.1.9` |
| [@radix-ui/react-checkbox](https://github.com/radix-ui/primitives) |
`1.1.4` | `1.3.1` |
| [@radix-ui/react-collapsible](https://github.com/radix-ui/primitives)
| `1.1.3` | `1.1.10` |
| [@radix-ui/react-context-menu](https://github.com/radix-ui/primitives)
| `2.2.6` | `2.2.14` |
|
[@radix-ui/react-dropdown-menu](https://github.com/radix-ui/primitives)
| `2.1.6` | `2.1.14` |
| [@radix-ui/react-label](https://github.com/radix-ui/primitives) |
`2.1.2` | `2.1.6` |
| [@radix-ui/react-popover](https://github.com/radix-ui/primitives) |
`1.1.6` | `1.1.13` |
| [@radix-ui/react-radio-group](https://github.com/radix-ui/primitives)
| `1.2.3` | `1.3.6` |
| [@radix-ui/react-scroll-area](https://github.com/radix-ui/primitives)
| `1.2.3` | `1.2.8` |
| [@radix-ui/react-select](https://github.com/radix-ui/primitives) |
`2.1.6` | `2.2.4` |
| [@radix-ui/react-separator](https://github.com/radix-ui/primitives) |
`1.1.2` | `1.1.6` |
| [@radix-ui/react-switch](https://github.com/radix-ui/primitives) |
`1.1.3` | `1.2.4` |
| [@radix-ui/react-tabs](https://github.com/radix-ui/primitives) |
`1.1.4` | `1.1.11` |
| [@radix-ui/react-toast](https://github.com/radix-ui/primitives) |
`1.2.6` | `1.2.13` |
| [@radix-ui/react-tooltip](https://github.com/radix-ui/primitives) |
`1.1.8` | `1.2.6` |
| [@sentry/nextjs](https://github.com/getsentry/sentry-javascript) |
`9.10.1` | `9.19.0` |
| [@supabase/ssr](https://github.com/supabase/ssr) | `0.5.2` | `0.6.1` |
| [@supabase/supabase-js](https://github.com/supabase/supabase-js) |
`2.49.1` | `2.49.4` |
|
[@tanstack/react-table](https://github.com/TanStack/table/tree/HEAD/packages/react-table)
| `8.21.2` | `8.21.3` |
|
[@xyflow/react](https://github.com/xyflow/xyflow/tree/HEAD/packages/react)
| `12.4.2` | `12.6.4` |
| [cmdk](https://github.com/pacocoursey/cmdk/tree/HEAD/cmdk) | `1.0.4` |
`1.1.1` |
| [dotenv](https://github.com/motdotla/dotenv) | `16.4.7` | `16.5.0` |
| [embla-carousel-react](https://github.com/davidjerleke/embla-carousel)
| `8.5.2` | `8.6.0` |
| [framer-motion](https://github.com/motiondivision/motion) | `12.4.11`
| `12.12.1` |
| [geist](https://github.com/vercel/geist-font/tree/HEAD/packages/next)
| `1.3.1` | `1.4.2` |
|
[launchdarkly-react-client-sdk](https://github.com/launchdarkly/react-client-sdk)
| `3.6.1` | `3.7.0` |
|
[lucide-react](https://github.com/lucide-icons/lucide/tree/HEAD/packages/lucide-react)
| `0.479.0` | `0.510.0` |
| [next-themes](https://github.com/pacocoursey/next-themes) | `0.4.5` |
`0.4.6` |
| [react-day-picker](https://github.com/gpbl/react-day-picker) | `9.6.1`
| `9.7.0` |
| [react-hook-form](https://github.com/react-hook-form/react-hook-form)
| `7.54.2` | `7.56.3` |
| [recharts](https://github.com/recharts/recharts) | `2.15.1` | `2.15.3`
|
| [zod](https://github.com/colinhacks/zod) | `3.24.2` | `3.24.4` |


Updates `@faker-js/faker` from 9.6.0 to 9.8.0
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/faker-js/faker/releases"><code>@​faker-js/faker</code>'s
releases</a>.</em></p>
<blockquote>
<h2>v9.8.0</h2>
<h2>What's Changed</h2>
<ul>
<li>feat(locale): add country code for en_CA &amp; fr_CA by <a
href="https://github.com/alixlahuec"><code>@​alixlahuec</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3476">faker-js/faker#3476</a></li>
<li>test: use validator@13.15.0 with isULID, isISO31661Numeric,
isISO15924 by <a
href="https://github.com/matthewmayer"><code>@​matthewmayer</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3482">faker-js/faker#3482</a></li>
<li>feat(locale): add zh_CN food by <a
href="https://github.com/yyz945947732"><code>@​yyz945947732</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3479">faker-js/faker#3479</a></li>
<li>docs: more than 70 locales by <a
href="https://github.com/matthewmayer"><code>@​matthewmayer</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3483">faker-js/faker#3483</a></li>
<li>feat(locale): update zh_CN location by <a
href="https://github.com/yyz945947732"><code>@​yyz945947732</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3481">faker-js/faker#3481</a></li>
<li>feat(locale): update zh_CN animal by <a
href="https://github.com/yyz945947732"><code>@​yyz945947732</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3480">faker-js/faker#3480</a></li>
<li>refactor(locale): ko state data update by <a
href="https://github.com/seoahan"><code>@​seoahan</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3487">faker-js/faker#3487</a></li>
<li>feat(locale): add zh_CN book by <a
href="https://github.com/yyz945947732"><code>@​yyz945947732</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3477">faker-js/faker#3477</a></li>
<li>feat(locale): add Japanese date and month definitions by <a
href="https://github.com/matsueushi"><code>@​matsueushi</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3492">faker-js/faker#3492</a></li>
<li>feat(locale): add vehicle locale data for Japanese by <a
href="https://github.com/noritaka1166"><code>@​noritaka1166</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3490">faker-js/faker#3490</a></li>
<li>feat(locale): update Japanese company categories by <a
href="https://github.com/noritaka1166"><code>@​noritaka1166</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3489">faker-js/faker#3489</a></li>
<li>feat(locale): add Japanese science locale data including elements
and units by <a
href="https://github.com/noritaka1166"><code>@​noritaka1166</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3491">faker-js/faker#3491</a></li>
<li>feat(locale): add Japanese sex definitions for person locale by <a
href="https://github.com/noritaka1166"><code>@​noritaka1166</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3495">faker-js/faker#3495</a></li>
<li>refactor(locale): rename pt-BR streetSuffix to streetPrefix by <a
href="https://github.com/glmchalita"><code>@​glmchalita</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3493">faker-js/faker#3493</a></li>
<li>feat(locale): update zh_CN word by <a
href="https://github.com/yyz945947732"><code>@​yyz945947732</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3478">faker-js/faker#3478</a></li>
<li>refactor(locale): normalize internet data by <a
href="https://github.com/xDivisionByZerox"><code>@​xDivisionByZerox</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3502">faker-js/faker#3502</a></li>
<li>chore(deps): update eslint by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3500">faker-js/faker#3500</a></li>
<li>chore(deps): update dependency eslint-plugin-unicorn to v59 by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3501">faker-js/faker#3501</a></li>
<li>chore(deps): update vitest by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3497">faker-js/faker#3497</a></li>
<li>chore(deps): update cypress/browsers docker tag to v24 by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3507">faker-js/faker#3507</a></li>
<li>chore(deps): update all non-major dependencies by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3498">faker-js/faker#3498</a></li>
<li>chore(deps): update
mcr.microsoft.com/devcontainers/typescript-node:22 docker digest to
fb211a0 by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3508">faker-js/faker#3508</a></li>
<li>feat(locale): Add additional Japanese last names to the locale data
by <a
href="https://github.com/noritaka1166"><code>@​noritaka1166</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3484">faker-js/faker#3484</a></li>
<li>chore(deps): update eslint by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3511">faker-js/faker#3511</a></li>
<li>chore(deps): lock file maintenance by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3486">faker-js/faker#3486</a></li>
<li>fix(locale): ko modified street_name to street_name_part by <a
href="https://github.com/seoahan"><code>@​seoahan</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3485">faker-js/faker#3485</a></li>
<li>fix(locale): correct Japanese country names by <a
href="https://github.com/matsueushi"><code>@​matsueushi</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3510">faker-js/faker#3510</a></li>
<li>chore(release): 9.8.0 by <a
href="https://github.com/fakerjs-bot"><code>@​fakerjs-bot</code></a> in
<a
href="https://redirect.github.com/faker-js/faker/pull/3515">faker-js/faker#3515</a></li>
</ul>
<h2>New Contributors</h2>
<ul>
<li><a
href="https://github.com/alixlahuec"><code>@​alixlahuec</code></a> made
their first contribution in <a
href="https://redirect.github.com/faker-js/faker/pull/3476">faker-js/faker#3476</a></li>
<li><a
href="https://github.com/yyz945947732"><code>@​yyz945947732</code></a>
made their first contribution in <a
href="https://redirect.github.com/faker-js/faker/pull/3479">faker-js/faker#3479</a></li>
<li><a href="https://github.com/seoahan"><code>@​seoahan</code></a> made
their first contribution in <a
href="https://redirect.github.com/faker-js/faker/pull/3487">faker-js/faker#3487</a></li>
<li><a
href="https://github.com/noritaka1166"><code>@​noritaka1166</code></a>
made their first contribution in <a
href="https://redirect.github.com/faker-js/faker/pull/3490">faker-js/faker#3490</a></li>
<li><a
href="https://github.com/glmchalita"><code>@​glmchalita</code></a> made
their first contribution in <a
href="https://redirect.github.com/faker-js/faker/pull/3493">faker-js/faker#3493</a></li>
</ul>
<p><strong>Full Changelog</strong>: <a
href="https://github.com/faker-js/faker/compare/v9.7.0...v9.8.0">https://github.com/faker-js/faker/compare/v9.7.0...v9.8.0</a></p>
<h2>v9.7.0</h2>
<h2>What's Changed</h2>
<ul>
<li>feat(locale): Add bn_BD locale by <a
href="https://github.com/AbrarShahriar"><code>@​AbrarShahriar</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3439">faker-js/faker#3439</a></li>
<li>fix(airline): Air France and KLM Royal Dutch Airlines by <a
href="https://github.com/chimurai"><code>@​chimurai</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3440">faker-js/faker#3440</a></li>
<li>infra(comment-issue): fix display of thumbs up emoji by <a
href="https://github.com/xDivisionByZerox"><code>@​xDivisionByZerox</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3444">faker-js/faker#3444</a></li>
<li>feat(locale): add localize sex support for zh_CN &amp; zh_TW by <a
href="https://github.com/sd44"><code>@​sd44</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3450">faker-js/faker#3450</a></li>
<li>fix(iban): more strict pattern for IE and PS by <a
href="https://github.com/xDivisionByZerox"><code>@​xDivisionByZerox</code></a>
in <a
href="https://redirect.github.com/faker-js/faker/pull/3464">faker-js/faker#3464</a></li>
<li>chore(deps): update devdependencies by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3456">faker-js/faker#3456</a></li>
<li>chore(deps): update all non-major dependencies by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3457">faker-js/faker#3457</a></li>
<li>chore(deps): update dependency prettier to v3.5.3 by <a
href="https://github.com/renovate"><code>@​renovate</code></a> in <a
href="https://redirect.github.com/faker-js/faker/pull/3455">faker-js/faker#3455</a></li>
</ul>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/faker-js/faker/blob/next/CHANGELOG.md"><code>@​faker-js/faker</code>'s
changelog</a>.</em></p>
<blockquote>
<h2><a
href="https://github.com/faker-js/faker/compare/v9.7.0...v9.8.0">9.8.0</a>
(2025-05-13)</h2>
<h3>New Locales</h3>
<ul>
<li><strong>locale:</strong> Add additional Japanese last names to the
locale data (<a
href="https://redirect.github.com/faker-js/faker/issues/3484">#3484</a>)
(<a
href="72e66c3a3a">72e66c3</a>)</li>
<li><strong>locale:</strong> add Japanese date and month definitions (<a
href="https://redirect.github.com/faker-js/faker/issues/3492">#3492</a>)
(<a
href="b70e7934b7">b70e793</a>)</li>
<li><strong>locale:</strong> add Japanese science locale data including
elements and units (<a
href="https://redirect.github.com/faker-js/faker/issues/3491">#3491</a>)
(<a
href="54fd5519e9">54fd551</a>)</li>
<li><strong>locale:</strong> add Japanese sex definitions for person
locale (<a
href="https://redirect.github.com/faker-js/faker/issues/3495">#3495</a>)
(<a
href="1dbd8fa511">1dbd8fa</a>)</li>
<li><strong>locale:</strong> add vehicle locale data for Japanese (<a
href="https://redirect.github.com/faker-js/faker/issues/3490">#3490</a>)
(<a
href="dfadb1da74">dfadb1d</a>)</li>
<li><strong>locale:</strong> add zh_CN book (<a
href="https://redirect.github.com/faker-js/faker/issues/3477">#3477</a>)
(<a
href="786a3d0bd8">786a3d0</a>)</li>
<li><strong>locale:</strong> add zh_CN food (<a
href="https://redirect.github.com/faker-js/faker/issues/3479">#3479</a>)
(<a
href="6c883e74b8">6c883e7</a>)</li>
<li><strong>locale:</strong> update Japanese company categories (<a
href="https://redirect.github.com/faker-js/faker/issues/3489">#3489</a>)
(<a
href="8c0953a261">8c0953a</a>)</li>
<li><strong>locale:</strong> update zh_CN animal (<a
href="https://redirect.github.com/faker-js/faker/issues/3480">#3480</a>)
(<a
href="38ee7b81a8">38ee7b8</a>)</li>
<li><strong>locale:</strong> update zh_CN location (<a
href="https://redirect.github.com/faker-js/faker/issues/3481">#3481</a>)
(<a
href="456f10276b">456f102</a>)</li>
<li><strong>locale:</strong> update zh_CN word (<a
href="https://redirect.github.com/faker-js/faker/issues/3478">#3478</a>)
(<a
href="aa98867765">aa98867</a>)</li>
</ul>
<h3>Changed Locales</h3>
<ul>
<li><strong>locale:</strong> ko state data update (<a
href="https://redirect.github.com/faker-js/faker/issues/3487">#3487</a>)
(<a
href="b611ec2e51">b611ec2</a>)</li>
<li><strong>locale:</strong> normalize internet data (<a
href="https://redirect.github.com/faker-js/faker/issues/3502">#3502</a>)
(<a
href="e6151e4efd">e6151e4</a>)</li>
<li><strong>locale:</strong> rename pt-BR streetSuffix to streetPrefix
(<a
href="https://redirect.github.com/faker-js/faker/issues/3493">#3493</a>)
(<a
href="7c23db316e">7c23db3</a>)</li>
</ul>
<h3>Bug Fixes</h3>
<ul>
<li><strong>locale:</strong> correct Japanese country names (<a
href="https://redirect.github.com/faker-js/faker/issues/3510">#3510</a>)
(<a
href="046bb81558">046bb81</a>)</li>
<li><strong>locale:</strong> correct the name of element Lv in Japanese
(<a
href="https://redirect.github.com/faker-js/faker/issues/3509">#3509</a>)
(<a
href="6a7ef4c2ad">6a7ef4c</a>)</li>
<li><strong>locale:</strong> ko modified street_name to street_name_part
(<a
href="https://redirect.github.com/faker-js/faker/issues/3485">#3485</a>)
(<a
href="c15da8efec">c15da8e</a>)</li>
</ul>
<h2><a
href="https://github.com/faker-js/faker/compare/v9.6.0...v9.7.0">9.7.0</a>
(2025-04-13)</h2>
<h3>New Locales</h3>
<ul>
<li><strong>locale:</strong> Add bn_BD locale (<a
href="https://redirect.github.com/faker-js/faker/issues/3439">#3439</a>)
(<a
href="fef0ad7859">fef0ad7</a>)</li>
<li><strong>locale:</strong> add cy locale, start with date (<a
href="https://redirect.github.com/faker-js/faker/issues/3462">#3462</a>)
(<a
href="f70a6f7a65">f70a6f7</a>)</li>
<li><strong>locale:</strong> add finance support for ja locale (<a
href="https://redirect.github.com/faker-js/faker/issues/3449">#3449</a>)
(<a
href="b2c5298c94">b2c5298</a>)</li>
<li><strong>locale:</strong> add localize sex support for zh_CN &amp;
zh_TW (<a
href="https://redirect.github.com/faker-js/faker/issues/3450">#3450</a>)
(<a
href="048c32581b">048c325</a>)</li>
<li><strong>locale:</strong> add Tamil language support (<a
href="https://redirect.github.com/faker-js/faker/issues/3468">#3468</a>)
(<a
href="cdf6dc4a97">cdf6dc4</a>)</li>
</ul>
<h3>Bug Fixes</h3>
<ul>
<li><strong>airline:</strong> Air France and KLM Royal Dutch Airlines
(<a
href="https://redirect.github.com/faker-js/faker/issues/3440">#3440</a>)
(<a
href="8a2d168f62">8a2d168</a>)</li>
<li><strong>iban:</strong> more strict pattern for IE and PS (<a
href="https://redirect.github.com/faker-js/faker/issues/3464">#3464</a>)
(<a
href="7b12056713">7b12056</a>)</li>
<li><strong>locale:</strong> rename ja and zh_CN company affix files (<a
href="https://redirect.github.com/faker-js/faker/issues/3448">#3448</a>)
(<a
href="1e551c5f47">1e551c5</a>)</li>
<li><strong>number:</strong> don't ignore multipleOf in float when
min=max (<a
href="https://redirect.github.com/faker-js/faker/issues/3417">#3417</a>)
(<a
href="e4cc4e50d1">e4cc4e5</a>)</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="549d71cf33"><code>549d71c</code></a>
chore(release): 9.8.0 (<a
href="https://redirect.github.com/faker-js/faker/issues/3515">#3515</a>)</li>
<li><a
href="046bb81558"><code>046bb81</code></a>
fix(locale): correct Japanese country names (<a
href="https://redirect.github.com/faker-js/faker/issues/3510">#3510</a>)</li>
<li><a
href="c15da8efec"><code>c15da8e</code></a>
fix(locale): ko modified street_name to street_name_part (<a
href="https://redirect.github.com/faker-js/faker/issues/3485">#3485</a>)</li>
<li><a
href="d6ba4cc1b1"><code>d6ba4cc</code></a>
chore(deps): lock file maintenance (<a
href="https://redirect.github.com/faker-js/faker/issues/3486">#3486</a>)</li>
<li><a
href="2faf57b01c"><code>2faf57b</code></a>
chore(deps): update eslint (<a
href="https://redirect.github.com/faker-js/faker/issues/3511">#3511</a>)</li>
<li><a
href="6a7ef4c2ad"><code>6a7ef4c</code></a>
fix(locale): correct the name of element Lv in Japanese (<a
href="https://redirect.github.com/faker-js/faker/issues/3509">#3509</a>)</li>
<li><a
href="72e66c3a3a"><code>72e66c3</code></a>
feat(locale): Add additional Japanese last names to the locale data (<a
href="https://redirect.github.com/faker-js/faker/issues/3484">#3484</a>)</li>
<li><a
href="c0d5217e10"><code>c0d5217</code></a>
chore(deps): update mcr.microsoft.com/devcontainers/typescript-node:22
docker...</li>
<li><a
href="049875d283"><code>049875d</code></a>
chore(deps): update all non-major dependencies (<a
href="https://redirect.github.com/faker-js/faker/issues/3498">#3498</a>)</li>
<li><a
href="07087ff6ef"><code>07087ff</code></a>
chore(deps): update cypress/browsers docker tag to v24 (<a
href="https://redirect.github.com/faker-js/faker/issues/3507">#3507</a>)</li>
<li>Additional commits viewable in <a
href="https://github.com/faker-js/faker/compare/v9.6.0...v9.8.0">compare
view</a></li>
</ul>
</details>
<details>
<summary>Maintainer changes</summary>
<p>This version was pushed to npm by <a
href="https://www.npmjs.com/~faker-bot">faker-bot</a>, a new releaser
for <code>@​faker-js/faker</code> since your current version.</p>
</details>
<br />

Updates `@next/third-parties` from 15.2.1 to 15.3.2
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/vercel/next.js/releases"><code>@​next/third-parties</code>'s
releases</a>.</em></p>
<blockquote>
<h2>v15.3.2</h2>
<blockquote>
<p>[!NOTE]<br />
This release is backporting bug fixes. It does <strong>not</strong>
include all pending features/changes on canary.</p>
</blockquote>
<h3>Core Changes</h3>
<ul>
<li>backport: fix(turbopack): Store persistence of wrapped task on
RawVc::LocalOutput (<a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78488">#78488</a>)
(<a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78883">#78883</a>)</li>
<li><code>@​next/mdx</code>: Use stable turbopack config options (<a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78880">#78880</a>)</li>
<li>Fix react-compiler: Fix detection of interest (<a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78879">#78879</a>)</li>
<li>Fix turbopack: Backport sourcemap bugfix (<a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78881">#78881</a>)</li>
<li>[next-server] preserve rsc query for rsc redirects (<a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78876">#78876</a>)</li>
<li>Update middleware public/static matching (<a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78875">#78875</a>)</li>
</ul>
<h3>Credits</h3>
<p>Huge thanks to <a
href="https://github.com/ijjk"><code>@​ijjk</code></a>, <a
href="https://github.com/huozhi"><code>@​huozhi</code></a>, <a
href="https://github.com/kdy1"><code>@​kdy1</code></a>, <a
href="https://github.com/wbinnssmith"><code>@​wbinnssmith</code></a>,
and <a href="https://github.com/bgw"><code>@​bgw</code></a> for
helping!</p>
<h2>v15.3.1</h2>
<blockquote>
<p>[!NOTE]<br />
This release is backporting bug fixes. It does <strong>not</strong>
include all pending features/changes on canary.</p>
</blockquote>
<h3>Core Changes</h3>
<ul>
<li>chore: Backport SWC-based RC optimization (<a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78260">#78260</a>)</li>
<li>fix: bump image-size@1.2.1 (<a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78164">#78164</a>)</li>
</ul>
<h3>Credits</h3>
<p>Huge thanks to <a
href="https://github.com/kdy1"><code>@​kdy1</code></a> and <a
href="https://github.com/styfle"><code>@​styfle</code></a> for
helping!</p>
<h2>v15.3.1-canary.15</h2>
<h3>Core Changes</h3>
<ul>
<li>[Turbopack] refactor persistent caching from log based to cow
approach: <a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/76234">#76234</a></li>
</ul>
<h3>Misc Changes</h3>
<ul>
<li>fix(turbo-tasks-fs): Handle filesystem watcher rescan events: <a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78045">#78045</a></li>
</ul>
<h3>Credits</h3>
<p>Huge thanks to <a
href="https://github.com/bgw"><code>@​bgw</code></a> and <a
href="https://github.com/sokra"><code>@​sokra</code></a> for
helping!</p>
<h2>v15.3.1-canary.14</h2>
<h3>Core Changes</h3>
<ul>
<li>Add graceful error boundary for bots requests: <a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78298">#78298</a></li>
<li>make sure eslint-plugin-next is built when running 'pnpm dev': <a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78305">#78305</a></li>
<li>Migrate pages API routes to handler interface: <a
href="https://github.com/vercel/next.js/tree/HEAD/packages/third-parties/issues/78166">#78166</a></li>
</ul>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="d9ec4a4b57"><code>d9ec4a4</code></a>
v15.3.2</li>
<li><a
href="fa536cf2c9"><code>fa536cf</code></a>
v15.3.1</li>
<li><a
href="b2ff04995b"><code>b2ff049</code></a>
v15.3.0</li>
<li><a
href="60bfe64295"><code>60bfe64</code></a>
v15.3.0-canary.46</li>
<li><a
href="f71c4a1582"><code>f71c4a1</code></a>
v15.3.0-canary.45</li>
<li><a
href="4451bae75d"><code>4451bae</code></a>
v15.3.0-canary.44</li>
<li><a
href="87d7d8eb7a"><code>87d7d8e</code></a>
v15.3.0-canary.43</li>
<li><a
href="82ab39f801"><code>82ab39f</code></a>
v15.3.0-canary.42</li>
<li><a
href="8f1409d6ce"><code>8f1409d</code></a>
v15.3.0-canary.41</li>
<li><a
href="2139369821"><code>2139369</code></a>
v15.3.0-canary.40</li>
<li>Additional commits viewable in <a
href="https://github.com/vercel/next.js/commits/v15.3.2/packages/third-parties">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-alert-dialog` from 1.1.6 to 1.1.13
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-avatar` from 1.1.3 to 1.1.9
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-checkbox` from 1.1.4 to 1.3.1
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-collapsible` from 1.1.3 to 1.1.10
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-context-menu` from 2.2.6 to 2.2.14
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-dialog` from 1.1.6 to 1.1.13
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-dropdown-menu` from 2.1.6 to 2.1.14
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-label` from 2.1.2 to 2.1.6
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-popover` from 1.1.6 to 1.1.13
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-radio-group` from 1.2.3 to 1.3.6
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-scroll-area` from 1.2.3 to 1.2.8
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-select` from 2.1.6 to 2.2.4
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-separator` from 1.1.2 to 1.1.6
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-slot` from 1.1.2 to 1.2.2
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-switch` from 1.1.3 to 1.2.4
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-tabs` from 1.1.4 to 1.1.11
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-toast` from 1.2.6 to 1.2.13
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@radix-ui/react-tooltip` from 1.1.8 to 1.2.6
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a
href="https://github.com/radix-ui/primitives/commits">compare
view</a></li>
</ul>
</details>
<br />

Updates `@sentry/nextjs` from 9.10.1 to 9.19.0
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/getsentry/sentry-javascript/releases"><code>@​sentry/nextjs</code>'s
releases</a>.</em></p>
<blockquote>
<h2>9.19.0</h2>
<ul>
<li>feat(react-router): Add otel instrumentation for server requests (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16147">#16147</a>)</li>
<li>feat(remix): Vendor in
<code>opentelemetry-instrumentation-remix</code> (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16145">#16145</a>)</li>
<li>fix(browser): Ensure spans auto-ended for navigations have
<code>cancelled</code> reason (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16277">#16277</a>)</li>
<li>fix(node): Pin <code>@fastify/otel</code> fork to direct url to
allow installing without git (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16287">#16287</a>)</li>
<li>fix(react): Handle nested parameterized routes in reactrouterv3
transaction normalization (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16274">#16274</a>)</li>
</ul>
<p>Work in this release was contributed by <a
href="https://github.com/sidx1024"><code>@​sidx1024</code></a>. Thank
you for your contribution!</p>
<h2>Bundle size 📦</h2>
<table>
<thead>
<tr>
<th>Path</th>
<th>Size</th>
</tr>
</thead>
<tbody>
<tr>
<td><code>@​sentry/browser</code></td>
<td>23.4 KB</td>
</tr>
<tr>
<td><code>@​sentry/browser</code> - with treeshaking flags</td>
<td>23.06 KB</td>
</tr>
<tr>
<td><code>@​sentry/browser</code> (incl. Tracing)</td>
<td>37.31 KB</td>
</tr>
<tr>
<td><code>@​sentry/browser</code> (incl. Tracing, Replay)</td>
<td>74.53 KB</td>
</tr>
<tr>
<td><code>@​sentry/browser</code> (incl. Tracing, Replay) - with
treeshaking flags</td>
<td>67.72 KB</td>
</tr>
<tr>
<td><code>@​sentry/browser</code> (incl. Tracing, Replay with
Canvas)</td>
<td>79.19 KB</td>
</tr>
<tr>
<td><code>@​sentry/browser</code> (incl. Tracing, Replay, Feedback)</td>
<td>91 KB</td>
</tr>
<tr>
<td><code>@​sentry/browser</code> (incl. Feedback)</td>
<td>39.8 KB</td>
</tr>
<tr>
<td><code>@​sentry/browser</code> (incl. sendFeedback)</td>
<td>28.03 KB</td>
</tr>
<tr>
<td><code>@​sentry/browser</code> (incl. FeedbackAsync)</td>
<td>32.79 KB</td>
</tr>
<tr>
<td><code>@​sentry/react</code></td>
<td>25.17 KB</td>
</tr>
<tr>
<td><code>@​sentry/react</code> (incl. Tracing)</td>
<td>39.27 KB</td>
</tr>
<tr>
<td><code>@​sentry/vue</code></td>
<td>27.67 KB</td>
</tr>
<tr>
<td><code>@​sentry/vue</code> (incl. Tracing)</td>
<td>39.07 KB</td>
</tr>
<tr>
<td><code>@​sentry/svelte</code></td>
<td>23.43 KB</td>
</tr>
<tr>
<td>CDN Bundle</td>
<td>24.58 KB</td>
</tr>
<tr>
<td>CDN Bundle (incl. Tracing)</td>
<td>37.33 KB</td>
</tr>
<tr>
<td>CDN Bundle (incl. Tracing, Replay)</td>
<td>72.37 KB</td>
</tr>
<tr>
<td>CDN Bundle (incl. Tracing, Replay, Feedback)</td>
<td>77.68 KB</td>
</tr>
<tr>
<td>CDN Bundle - uncompressed</td>
<td>71.72 KB</td>
</tr>
<tr>
<td>CDN Bundle (incl. Tracing) - uncompressed</td>
<td>110.5 KB</td>
</tr>
<tr>
<td>CDN Bundle (incl. Tracing, Replay) - uncompressed</td>
<td>221.78 KB</td>
</tr>
<tr>
<td>CDN Bundle (incl. Tracing, Replay, Feedback) - uncompressed</td>
<td>234.31 KB</td>
</tr>
<tr>
<td><code>@​sentry/nextjs</code> (client)</td>
<td>40.88 KB</td>
</tr>
<tr>
<td><code>@​sentry/sveltekit</code> (client)</td>
<td>37.77 KB</td>
</tr>
<tr>
<td><code>@​sentry/node</code></td>
<td>154.29 KB</td>
</tr>
<tr>
<td><code>@​sentry/node</code> - without tracing</td>
<td>95.6 KB</td>
</tr>
<tr>
<td><code>@​sentry/aws-serverless</code></td>
<td>120.36 KB</td>
</tr>
</tbody>
</table>
<h2>9.18.0</h2>
<h3>Important changes</h3>
<ul>
<li><strong>feat: Support Node 24 (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16236">#16236</a>)</strong></li>
</ul>
<p>We now also publish profiling binaries for Node 24.</p>
<h3>Other changes</h3>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/getsentry/sentry-javascript/blob/develop/CHANGELOG.md"><code>@​sentry/nextjs</code>'s
changelog</a>.</em></p>
<blockquote>
<h2>9.19.0</h2>
<ul>
<li>feat(react-router): Add otel instrumentation for server requests (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16147">#16147</a>)</li>
<li>feat(remix): Vendor in
<code>opentelemetry-instrumentation-remix</code> (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16145">#16145</a>)</li>
<li>fix(browser): Ensure spans auto-ended for navigations have
<code>cancelled</code> reason (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16277">#16277</a>)</li>
<li>fix(node): Pin <code>@fastify/otel</code> fork to direct url to
allow installing without git (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16287">#16287</a>)</li>
<li>fix(react): Handle nested parameterized routes in reactrouterv3
transaction normalization (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16274">#16274</a>)</li>
</ul>
<p>Work in this release was contributed by <a
href="https://github.com/sidx1024"><code>@​sidx1024</code></a>. Thank
you for your contribution!</p>
<h2>9.18.0</h2>
<h3>Important changes</h3>
<ul>
<li><strong>feat: Support Node 24 (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16236">#16236</a>)</strong></li>
</ul>
<p>We now also publish profiling binaries for Node 24.</p>
<h3>Other changes</h3>
<ul>
<li>deps(node): Bump <code>import-in-the-middle</code> to
<code>1.13.1</code> (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16260">#16260</a>)</li>
<li>feat: Export <code>consoleLoggingIntegration</code> from vercel edge
sdk (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16228">#16228</a>)</li>
<li>feat(cloudflare): Add support for email, queue, and tail handler (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16233">#16233</a>)</li>
<li>feat(cloudflare): Improve http span data (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16232">#16232</a>)</li>
<li>feat(nextjs): Add more attributes for generation functions (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16214">#16214</a>)</li>
<li>feat(opentelemetry): Widen peer dependencies to support Otel v2 (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16246">#16246</a>)</li>
<li>fix(core): Gracefully handle invalid baggage entries (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16257">#16257</a>)</li>
<li>fix(node): Ensure traces are propagated without spans in Node 22+
(<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16221">#16221</a>)</li>
<li>fix(node): Use sentry forked <code>@fastify/otel</code> dependency
with pinned Otel v1 deps (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16256">#16256</a>)</li>
<li>fix(remix): Remove vendored types (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16218">#16218</a>)</li>
</ul>
<h2>9.17.0</h2>
<ul>
<li>feat(node): Migrate to <code>@fastify/otel</code> (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/15542">#15542</a>)</li>
</ul>
<h2>9.16.1</h2>
<ul>
<li>fix(core): Make sure logs get flushed in server-runtime-client (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16222">#16222</a>)</li>
<li>ref(node): Remove vercel flushing code that does nothing (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16217">#16217</a>)</li>
</ul>
<h2>9.16.0</h2>
<h3>Important changes</h3>
<ul>
<li><strong>feat: Create a Vite plugin that injects sentryConfig into
the global config (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16197">#16197</a>)</strong></li>
</ul>
<p>Add a new plugin <code>makeConfigInjectorPlugin</code> within our
existing vite plugin that updates the global vite config with sentry
options</p>
<ul>
<li><strong>feat(browser): Add option to sample linked traces
consistently (<a
href="https://redirect.github.com/getsentry/sentry-javascript/pull/16037">#16037</a>)</strong></li>
</ul>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="d69ea01d02"><code>d69ea01</code></a>
release: 9.19.0</li>
<li><a
href="9acaae28c1"><code>9acaae2</code></a>
Merge pull request <a
href="https://redirect.github.com/getsentry/sentry-javascript/issues/16288">#16288</a>
from getsentry/prepare-release/9.19.0</li>
<li><a
href="ed276633ce"><code>ed27663</code></a>
meta(changelog): Update changelog for 9.19.0</li>
<li><a
href="4b039f8a6e"><code>4b039f8</code></a>
fix(node): Pin <code>@fastify/otel</code> fork to direct url to allow
installing without...</li>
<li><a
href="26731edc99"><code>26731ed</code></a>
feat(react-router): Add otel instrumentation for server requests (<a
href="https://redirect.github.com/getsentry/sentry-javascript/issues/16147">#16147</a>)</li>
<li><a
href="efb86de64b"><code>efb86de</code></a>
chore: Add external contributor to CHANGELOG.md (<a
href="https://redirect.github.com/getsentry/sentry-javascript/issues/16282">#16282</a>)</li>
<li><a
href="e83658f23a"><code>e83658f</code></a>
fix(browser): Ensure spans auto-ended for navigations have
<code>cancelled</code> reason...</li>
<li><a
href="b9984338be"><code>b998433</code></a>
feat(remix): Vendor in <code>opentelemetry-instrumentation-remix</code>
(<a
href="https://redirect.github.com/getsentry/sentry-javascript/issues/16145">#16145</a>)</li>
<li><a
href="f55018fbf6"><code>f55018f</code></a>
fix(react): Handle nested parameterized routes in reactrouterv3
transaction n...</li>
<li><a
href="6d2b971980"><code>6d2b971</code></a>
Merge pull request <a
href="https://redirect.github.com/getsentry/sentry-javascript/issues/16276">#16276</a>
from getsentry/master</li>
<li>Additional commits viewable in <a
href="https://github.com/getsentry/sentry-javascript/compare/9.10.1...9.19.0">compare
view</a></li>
</ul>
</details>
<br />

Updates `@supabase/ssr` from 0.5.2 to 0.6.1
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/supabase/ssr/releases"><code>@​supabase/ssr</code>'s
releases</a>.</em></p>
<blockquote>
<h2>v0.6.1</h2>
<h2><a
href="https://github.com/supabase/ssr/compare/v0.6.0...v0.6.1">0.6.1</a>
(2025-03-16)</h2>
<h3>Bug Fixes</h3>
<ul>
<li>force release (<a
href="https://redirect.github.com/supabase/ssr/issues/98">#98</a>) (<a
href="66710e82aa">66710e8</a>)</li>
<li><strong>revert:</strong> &quot;feat: improve cookie chunk handling
via base64url+length encoding (<a
href="https://redirect.github.com/supabase/ssr/issues/90">#90</a>)&quot;
(<a href="https://redirect.github.com/supabase/ssr/issues/100">#100</a>)
(<a
href="2ea8e23525">2ea8e23</a>)</li>
</ul>
<h2>v0.6.1-rc.3</h2>
<p>This is a release candidate. See release-please PR <a
href="https://redirect.github.com/supabase/ssr/issues/99">#99</a> for
context.</p>
<h2>v0.6.1-rc.2</h2>
<p>This is a release candidate. See release-please PR <a
href="https://redirect.github.com/supabase/ssr/issues/99">#99</a> for
context.</p>
<h2>v0.6.0</h2>
<h2><a
href="https://github.com/supabase/ssr/compare/v0.5.2...v0.6.0">0.6.0</a>
(2025-02-27)</h2>
<h3>Features</h3>
<ul>
<li>improve cookie chunk handling via base64url+length encoding (<a
href="https://redirect.github.com/supabase/ssr/issues/90">#90</a>) (<a
href="6deb6871ca">6deb687</a>)</li>
<li>upgrade cookie dependency and cleanup imports (<a
href="https://redirect.github.com/supabase/ssr/issues/77">#77</a>) (<a
href="95245282e6">9524528</a>)</li>
</ul>
<h3>Bug Fixes</h3>
<ul>
<li>add <code>create*Client</code> string in <code>x-client-info</code>
(<a href="https://redirect.github.com/supabase/ssr/issues/85">#85</a>)
(<a
href="f271accfea">f271acc</a>)</li>
</ul>
<h2>v0.6.0-rc.5</h2>
<p>This is a release candidate. See release-please PR <a
href="https://redirect.github.com/supabase/ssr/issues/80">#80</a> for
context.</p>
<h2>v0.6.0-rc.3</h2>
<p>This is a release candidate. See release-please PR <a
href="https://redirect.github.com/supabase/ssr/issues/80">#80</a> for
context.</p>
<h2>v0.6.0-rc.2</h2>
<p>This is a release candidate. See release-please PR <a
href="https://redirect.github.com/supabase/ssr/issues/80">#80</a> for
context.</p>
<h2>v0.6.0-rc.1</h2>
<p>This is a release candidate. See release-please PR <a
href="https://redirect.github.com/supabase/ssr/issues/80">#80</a> for
context.</p>
</blockquote>
</details>
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/supabase/ssr/blob/main/CHANGELOG.md"><code>@​supabase/ssr</code>'s
changelog</a>.</em></p>
<blockquote>
<h2><a
href="https://github.com/supabase/ssr/compare/v0.6.0...v0.6.1">0.6.1</a>
(2025-03-16)</h2>
<h3>Bug Fixes</h3>
<ul>
<li>force release (<a
href="https://redirect.github.com/supabase/ssr/issues/98">#98</a>) (<a
href="66710e82aa">66710e8</a>)</li>
<li><strong>revert:</strong> &quot;feat: improve cookie chunk handling
via base64url+length encoding (<a
href="https://redirect.github.com/supabase/ssr/issues/90">#90</a>)&quot;
(<a href="https://redirect.github.com/supabase/ssr/issues/100">#100</a>)
(<a
href="2ea8e23525">2ea8e23</a>)</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="a1b60ba826"><code>a1b60ba</code></a>
chore(main): release 0.6.1 (<a
href="https://redirect.github.com/supabase/ssr/issues/99">#99</a>)</li>
<li><a
href="2ea8e23525"><code>2ea8e23</code></a>
fix(revert): &quot;feat: improve cookie chunk handling via
base64url+length encodi...</li>
<li><a
href="66710e82aa"><code>66710e8</code></a>
fix: force release (<a
href="https://redirect.github.com/supabase/ssr/issues/98">#98</a>)</li>
<li><a
href="37909b21f1"><code>37909b2</code></a>
Revert &quot;chore(main): release 0.6.0&quot; (<a
href="https://redirect.github.com/supabase/ssr/issues/95">#95</a>)</li>
<li><a
href="be9cd6c70e"><code>be9cd6c</code></a>
chore(main): release 0.6.0 (<a
href="https://redirect.github.com/supabase/ssr/issues/80">#80</a>)</li>
<li><a
href="6deb6871ca"><code>6deb687</code></a>
feat: improve cookie chunk handling via base64url+length encoding (<a
href="https://redirect.github.com/supabase/ssr/issues/90">#90</a>)</li>
<li><a
href="ef429dfbd1"><code>ef429df</code></a>
build(deps): bump vite from 5.4.10 to 5.4.14 (<a
href="https://redirect.github.com/supabase/ssr/issues/88">#88</a>)</li>
<li><a
href="ca469593e3"><code>ca46959</code></a>
ci: publish with provenance (<a
href="https://redirect.github.com/supabase/ssr/issues/86">#86</a>)</li>
<li><a
href="f271accfea"><code>f271acc</code></a>
fix: add <code>create*Client</code> string in <code>x-client-info</code>
(<a
href="https://redirect.github.com/supabase/ssr/issues/85">#85</a>)</li>
<li><a
href="95245282e6"><code>9524528</code></a>
feat: upgrade cookie dependency and cleanup imports (<a
href="https://redirect.github.com/supabase/ssr/issues/77">#77</a>)</li>
<li>See full diff in <a
href="https://github.com/supabase/ssr/compare/v0.5.2...v0.6.1">compare
view</a></li>
</ul>
</details>
<br />

Updates `@supabase/supabase-js` from 2.49.1 to 2.49.4
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/supabase/supabase-js/releases"><code>@​supabase/supabase-js</code>'s
releases</a>.</em></p>
<blockquote>
<h2>v2.49.4</h2>
<h2><a
href="https://github.com/supabase/supabase-js/compare/v2.49.3...v2.49.4">2.49.4</a>
(2025-03-29)</h2>
<h3>Bug Fixes</h3>
<ul>
<li><strong>deps:</strong> upgrade postgrest-js to 1.19.4 (<a
href="692e8e846b">692e8e8</a>)</li>
</ul>
<h2>v2.49.3</h2>
<h2><a
href="https://github.com/supabase/supabase-js/compare/v2.49.2...v2.49.3">2.49.3</a>
(2025-03-24)</h2>
<h3>Bug Fixes</h3>
<ul>
<li>bump auth-js to 2.69.1 (<a
href="https://redirect.github.com/supabase/supabase-js/issues/1383">#1383</a>)
(<a
href="f08bfd9c96">f08bfd9</a>)</li>
</ul>
<h2>v2.49.2</h2>
<h2><a
href="https://github.com/supabase/supabase-js/compare/v2.49.1...v2.49.2">2.49.2</a>
(2025-03-24)</h2>
<h3>Bug Fixes</h3>
<ul>
<li>bump auth-js to v2.69.0 (<a
href="https://redirect.github.com/supabase/supabase-js/issues/1380">#1380</a>)
(<a
href="73ab30dd61">73ab30d</a>)</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="692e8e846b"><code>692e8e8</code></a>
fix(deps): upgrade postgrest-js to 1.19.4</li>
<li><a
href="f08bfd9c96"><code>f08bfd9</code></a>
fix: bump auth-js to 2.69.1 (<a
href="https://redirect.github.com/supabase/supabase-js/issues/1383">#1383</a>)</li>
<li><a
href="73ab30dd61"><code>73ab30d</code></a>
fix: bump auth-js to v2.69.0 (<a
href="https://redirect.github.com/supabase/supabase-js/issues/1380">#1380</a>)</li>
<li><a
href="a5219a81b3"><code>a5219a8</code></a>
chore: add open role to README.md (<a
href="https://redirect.github.com/supabase/supabase-js/issues/1378">#1378</a>)</li>
<li>See full diff in <a
href="https://github.com/supabase/supabase-js/compare/v2.49.1...v2.49.4">compare
view</a></li>
</ul>
</details>
<br />

Updates `@tanstack/react-table` from 8.21.2 to 8.21.3
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/TanStack/table/releases"><code>@​tanstack/react-table</code>'s
releases</a>.</em></p>
<blockquote>
<h2>v8.21.3</h2>
<p>Version 8.21.3 - 4/14/25, 8:19 PM</p>
<h2>Changes</h2>
<h3>Fix</h3>
<ul>
<li>table-core: use right Document instance on getResizeHandler
(column-sizing feature) (<a
href="https://github.com/TanStack/table/tree/HEAD/packages/react-table/issues/5989">#5989</a>)
(54ce673) by <a
href="https://github.com/riccardoperra"><code>@​riccardoperra</code></a></li>
</ul>
<h3>Docs</h3>
<ul>
<li>fix all 158 broken links (<a
href="https://github.com/TanStack/table/tree/HEAD/packages/react-table/issues/5972">#5972</a>)
(f7bf6f1) by <a
href="https://github.com/kisaragi-hiu"><code>@​kisaragi-hiu</code></a></li>
<li>add vue example for grouping (<a
href="https://github.com/TanStack/table/tree/HEAD/packages/react-table/issues/5941">#5941</a>)
(3efa59c) by Harshil Patel</li>
</ul>
<h2>Packages</h2>
<ul>
<li><code>@​tanstack/table-core</code><a
href="https://github.com/8"><code>@​8</code></a>.21.3</li>
<li><code>@​tanstack/angular-table</code><a
href="https://github.com/8"><code>@​8</code></a>.21.3</li>
<li><code>@​tanstack/lit-table</code><a
href="https://github.com/8"><code>@​8</code></a>.21.3</li>
<li><code>@​tanstack/qwik-table</code><a
href="https://github.com/8"><code>@​8</code></a>.21.3</li>
<li><code>@​tanstack/react-table</code><a
href="https://github.com/8"><code>@​8</code></a>.21.3</li>
<li><code>@​tanstack/solid-table</code><a
href="https://github.com/8"><code>@​8</code></a>.21.3</li>
<li><code>@​tanstack/svelte-table</code><a
href="https://github.com/8"><code>@​8</code></a>.21.3</li>
<li><code>@​tanstack/vue-table</code><a
href="https://github.com/8"><code>@​8</code></a>.21.3</li>
<li><code>@​tanstack/react-table-devtools</code><a
href="https://github.com/8"><code>@​8</code></a>.21.3</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="f4dc742b7b"><code>f4dc742</code></a>
release: v8.21.3</li>
<li>See full diff in <a
href="https://github.com/TanStack/table/commits/v8.21.3/packages/react-table">compare
view</a></li>
</ul>
</details>
<br />

Updates `@xyflow/react` from 12.4.2 to 12.6.4
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/xyflow/xyflow/releases"><code>@​xyflow/react</code>'s
releases</a>.</em></p>
<blockquote>
<h2><code>@​xyflow/react</code><a
href="https://github.com/12"><code>@​12</code></a>.6.4</h2>
<h3>Patch Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5263">#5263</a> <a
href="e4a8d4b43f"><code>e4a8d4b4</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Multi select key works when input is focused</p>
</li>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5266">#5266</a> <a
href="77107453fa"><code>77107453</code></a>
Thanks <a
href="https://github.com/peterkogo"><code>@​peterkogo</code></a>! - Fix
connection snapping for handles larger than connectionRadius</p>
</li>
<li>
<p>Updated dependencies [<a
href="77107453fa"><code>77107453</code></a>]:</p>
<ul>
<li><code>@​xyflow/system</code><a
href="https://github.com/0"><code>@​0</code></a>.0.61</li>
</ul>
</li>
</ul>
<h2><code>@​xyflow/react</code><a
href="https://github.com/12"><code>@​12</code></a>.6.3</h2>
<h3>Patch Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5259">#5259</a> <a
href="77bf79c40e"><code>77bf79c4</code></a>
Thanks <a
href="https://github.com/peterkogo"><code>@​peterkogo</code></a>! - Fix
background-color css variable fallback.</p>
</li>
<li>
<p>Updated dependencies [<a
href="77bf79c40e"><code>77bf79c4</code></a>]:</p>
<ul>
<li><code>@​xyflow/system</code><a
href="https://github.com/0"><code>@​0</code></a>.0.60</li>
</ul>
</li>
</ul>
<h2><code>@​xyflow/react</code><a
href="https://github.com/12"><code>@​12</code></a>.6.2</h2>
<h3>Patch Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5257">#5257</a> <a
href="b1314be04d"><code>b1314be0</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Use OnReconnect from system</p>
</li>
<li>
<p>Updated dependencies [<a
href="a95f0e2fbf"><code>a95f0e2f</code></a>]:</p>
<ul>
<li><code>@​xyflow/system</code><a
href="https://github.com/0"><code>@​0</code></a>.0.59</li>
</ul>
</li>
</ul>
<h2><code>@​xyflow/react</code><a
href="https://github.com/12"><code>@​12</code></a>.6.1</h2>
<h3>Patch Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5249">#5249</a> <a
href="895b5d81c8"><code>895b5d81</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Call <code>onNodesChange</code> for uncontrolled flows that use
<code>updateNode</code></p>
</li>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5247">#5247</a> <a
href="67e1cb6891"><code>67e1cb68</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Cleanup TSDoc annotations for ReactFlow</p>
</li>
<li>
<p>Updated dependencies [<a
href="2a03213b06"><code>2a03213b</code></a>]:</p>
<ul>
<li><code>@​xyflow/system</code><a
href="https://github.com/0"><code>@​0</code></a>.0.58</li>
</ul>
</li>
</ul>
<h2><code>@​xyflow/react</code><a
href="https://github.com/12"><code>@​12</code></a>.6.0</h2>
<h3>Minor Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5219">#5219</a> <a
href="4236adbc46"><code>4236adbc</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Add initialMinZoom, initialMaxZoom and initialFitViewOptions to
ReactFlowProvider</p>
</li>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5227">#5227</a> <a
href="a7d10ffce5"><code>a7d10ffc</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Add <code>resizeDirection</code> prop for the
<code>NodeResizeControl</code> component</p>
</li>
</ul>
<h3>Patch Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5217">#5217</a> <a
href="bce74e8811"><code>bce74e88</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Keep node seleciton on pane click if elementsSelectable=false</p>
</li>
<li>
<p>Updated dependencies [<a
href="a7d10ffce5"><code>a7d10ffc</code></a>,
<a
href="4e681f9c52"><code>4e681f9c</code></a>]:</p>
<ul>
<li><code>@​xyflow/system</code><a
href="https://github.com/0"><code>@​0</code></a>.0.57</li>
</ul>
</li>
</ul>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/xyflow/xyflow/blob/main/packages/react/CHANGELOG.md"><code>@​xyflow/react</code>'s
changelog</a>.</em></p>
<blockquote>
<h2>12.6.4</h2>
<h3>Patch Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5263">#5263</a> <a
href="e4a8d4b43f"><code>e4a8d4b4</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Multi select key works when input is focused</p>
</li>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5266">#5266</a> <a
href="77107453fa"><code>77107453</code></a>
Thanks <a
href="https://github.com/peterkogo"><code>@​peterkogo</code></a>! - Fix
connection snapping for handles larger than connectionRadius</p>
</li>
<li>
<p>Updated dependencies [<a
href="77107453fa"><code>77107453</code></a>]:</p>
<ul>
<li><code>@​xyflow/system</code><a
href="https://github.com/0"><code>@​0</code></a>.0.61</li>
</ul>
</li>
</ul>
<h2>12.6.3</h2>
<h3>Patch Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5259">#5259</a> <a
href="77bf79c40e"><code>77bf79c4</code></a>
Thanks <a
href="https://github.com/peterkogo"><code>@​peterkogo</code></a>! - Fix
background-color css variable fallback.</p>
</li>
<li>
<p>Updated dependencies [<a
href="77bf79c40e"><code>77bf79c4</code></a>]:</p>
<ul>
<li><code>@​xyflow/system</code><a
href="https://github.com/0"><code>@​0</code></a>.0.60</li>
</ul>
</li>
</ul>
<h2>12.6.2</h2>
<h3>Patch Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5257">#5257</a> <a
href="b1314be04d"><code>b1314be0</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Use OnReconnect from system</p>
</li>
<li>
<p>Updated dependencies [<a
href="a95f0e2fbf"><code>a95f0e2f</code></a>]:</p>
<ul>
<li><code>@​xyflow/system</code><a
href="https://github.com/0"><code>@​0</code></a>.0.59</li>
</ul>
</li>
</ul>
<h2>12.6.1</h2>
<h3>Patch Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5249">#5249</a> <a
href="895b5d81c8"><code>895b5d81</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Call <code>onNodesChange</code> for uncontrolled flows that use
<code>updateNode</code></p>
</li>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5247">#5247</a> <a
href="67e1cb6891"><code>67e1cb68</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Cleanup TSDoc annotations for ReactFlow</p>
</li>
<li>
<p>Updated dependencies [<a
href="2a03213b06"><code>2a03213b</code></a>]:</p>
<ul>
<li><code>@​xyflow/system</code><a
href="https://github.com/0"><code>@​0</code></a>.0.58</li>
</ul>
</li>
</ul>
<h2>12.6.0</h2>
<h3>Minor Changes</h3>
<ul>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5219">#5219</a> <a
href="4236adbc46"><code>4236adbc</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Add initialMinZoom, initialMaxZoom and initialFitViewOptions to
ReactFlowProvider</p>
</li>
<li>
<p><a
href="https://redirect.github.com/xyflow/xyflow/pull/5227">#5227</a> <a
href="a7d10ffce5"><code>a7d10ffc</code></a>
Thanks <a href="https://github.com/moklick"><code>@​moklick</code></a>!
- Add <code>resizeDirection</code> prop for the
<code>NodeResizeControl</code> component</p>
</li>
</ul>
<h3>Patch Changes</h3>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="0076d82222"><code>0076d82</code></a>
chore(packages): bump</li>
<li><a
href="8ce85fd8f0"><code>8ce85fd</code></a>
fix(react): multi select works when input is focused</li>
<li><a
href="cee50e1dd0"><code>cee50e1</code></a>
chore(packages): bump</li>
<li><a
href="673a3a8718"><code>673a3a8</code></a>
merge main</li>
<li><a
href="9893b6321b"><code>9893b63</code></a>
chore(packages): bump</li>
<li><a
href="69021e8bbe"><code>69021e8</code></a>
chore(react): use OnReconnet from system</li>
<li><a
href="b30a496bf4"><code>b30a496</code></a>
merg main</li>
<li><a
href="2df553e611"><code>2df553e</code></a>
chore(packages): bump</li>
<li><a href="https://g...

_Description has been truncated_

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Reinier van der Leer <pwuts@agpt.co>

.github/dependabot.yml

@@ -129,30 +129,6 @@ updates:
         - "minor"
         - "patch"
 
-
-  # Submodules
-  - package-ecosystem: "gitsubmodule"
-    directory: "autogpt_platform/supabase"
-    schedule:
-      interval: "weekly"
-    open-pull-requests-limit: 1
-    target-branch: "dev"
-    commit-message:
-      prefix: "chore(platform/deps)"
-      prefix-development: "chore(platform/deps-dev)"
-    groups:
-      production-dependencies:
-        dependency-type: "production"
-        update-types:
-        - "minor"
-        - "patch"
-      development-dependencies:
-        dependency-type: "development"
-        update-types:
-        - "minor"
-        - "patch"
-
-
   # Docs
   - package-ecosystem: 'pip'
     directory: "docs/"

.github/workflows/classic-autogpt-ci.yml

@@ -115,6 +115,7 @@ jobs:
           poetry run pytest -vv \
             --cov=autogpt --cov-branch --cov-report term-missing --cov-report xml \
             --numprocesses=logical --durations=10 \
+            --junitxml=junit.xml -o junit_family=legacy \
             tests/unit tests/integration
         env:
           CI: true
@@ -124,8 +125,14 @@ jobs:
           AWS_ACCESS_KEY_ID: minioadmin
           AWS_SECRET_ACCESS_KEY: minioadmin
 
+      - name: Upload test results to Codecov
+        if: ${{ !cancelled() }}  # Run even if tests fail
+        uses: codecov/test-results-action@v1
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+
       - name: Upload coverage reports to Codecov
-        uses: codecov/codecov-action@v4
+        uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
           flags: autogpt-agent,${{ runner.os }}

.github/workflows/classic-benchmark-ci.yml

@@ -87,13 +87,20 @@ jobs:
           poetry run pytest -vv \
             --cov=agbenchmark --cov-branch --cov-report term-missing --cov-report xml \
             --durations=10 \
+            --junitxml=junit.xml -o junit_family=legacy \
             tests
         env:
           CI: true
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
 
+      - name: Upload test results to Codecov
+        if: ${{ !cancelled() }}  # Run even if tests fail
+        uses: codecov/test-results-action@v1
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+
       - name: Upload coverage reports to Codecov
-        uses: codecov/codecov-action@v4
+        uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
           flags: agbenchmark,${{ runner.os }}

.github/workflows/classic-forge-ci.yml

@@ -139,6 +139,7 @@ jobs:
           poetry run pytest -vv \
             --cov=forge --cov-branch --cov-report term-missing --cov-report xml \
             --durations=10 \
+            --junitxml=junit.xml -o junit_family=legacy \
             forge
         env:
           CI: true
@@ -148,8 +149,14 @@ jobs:
           AWS_ACCESS_KEY_ID: minioadmin
           AWS_SECRET_ACCESS_KEY: minioadmin
 
+      - name: Upload test results to Codecov
+        if: ${{ !cancelled() }}  # Run even if tests fail
+        uses: codecov/test-results-action@v1
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+
       - name: Upload coverage reports to Codecov
-        uses: codecov/codecov-action@v4
+        uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
           flags: forge,${{ runner.os }}

.github/workflows/platform-autgpt-deploy-prod.yml

@@ -34,6 +34,7 @@ jobs:
           python -m prisma migrate deploy
         env:
           DATABASE_URL: ${{ secrets.BACKEND_DATABASE_URL }}
+          DIRECT_URL: ${{ secrets.BACKEND_DATABASE_URL }}
 
           
   trigger:

.github/workflows/platform-autogpt-deploy-dev.yaml

@@ -36,6 +36,7 @@ jobs:
           python -m prisma migrate deploy
         env:
           DATABASE_URL: ${{ secrets.BACKEND_DATABASE_URL }}
+          DIRECT_URL: ${{ secrets.BACKEND_DATABASE_URL }}
 
   trigger:
     needs: migrate

.github/workflows/platform-backend-ci.yml

@@ -42,6 +42,14 @@ jobs:
           REDIS_PASSWORD: testpassword
         ports:
           - 6379:6379
+      rabbitmq:
+        image: rabbitmq:3.12-management
+        ports:
+          - 5672:5672
+          - 15672:15672
+        env:
+          RABBITMQ_DEFAULT_USER: ${{ env.RABBITMQ_DEFAULT_USER }}
+          RABBITMQ_DEFAULT_PASS: ${{ env.RABBITMQ_DEFAULT_PASS }}
 
     steps:
       - name: Checkout repository
@@ -58,7 +66,7 @@ jobs:
       - name: Setup Supabase
         uses: supabase/setup-cli@v1
         with:
-          version: latest
+          version: 1.178.1
 
       - id: get_date
         name: Get date
@@ -72,18 +80,35 @@ jobs:
 
       - name: Install Poetry (Unix)
         run: |
-          curl -sSL https://install.python-poetry.org | python3 -
+          # Extract Poetry version from backend/poetry.lock
+          HEAD_POETRY_VERSION=$(head -n 1 poetry.lock | grep -oP '(?<=Poetry )[0-9]+\.[0-9]+\.[0-9]+')
+          echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
+
+          if [ -n "$BASE_REF" ]; then
+            BASE_BRANCH=${BASE_REF/refs\/heads\//}
+            BASE_POETRY_VERSION=$((git show "origin/$BASE_BRANCH":./poetry.lock; true) | head -n 1 | grep -oP '(?<=Poetry )[0-9]+\.[0-9]+\.[0-9]+')
+            echo "Found Poetry version ${BASE_POETRY_VERSION} in backend/poetry.lock on ${BASE_REF}"
+            POETRY_VERSION=$(printf '%s\n' "$HEAD_POETRY_VERSION" "$BASE_POETRY_VERSION" | sort -V | tail -n1)
+          else
+            POETRY_VERSION=$HEAD_POETRY_VERSION
+          fi
+          echo "Using Poetry version ${POETRY_VERSION}"
+
+          # Install Poetry
+          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$POETRY_VERSION python3 -
 
           if [ "${{ runner.os }}" = "macOS" ]; then
             PATH="$HOME/.local/bin:$PATH"
             echo "$HOME/.local/bin" >> $GITHUB_PATH
           fi
+        env:
+          BASE_REF: ${{ github.base_ref || github.event.merge_group.base_ref }}
 
       - name: Check poetry.lock
         run: |
           poetry lock
 
-          if ! git diff --quiet poetry.lock; then
+          if ! git diff --quiet --ignore-matching-lines="^# " poetry.lock; then
             echo "Error: poetry.lock not up to date."
             echo
             git diff poetry.lock
@@ -110,6 +135,7 @@ jobs:
         run: poetry run prisma migrate dev --name updates
         env:
           DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
+          DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
 
       - id: lint
         name: Run Linter
@@ -126,12 +152,13 @@ jobs:
         env:
           LOG_LEVEL: ${{ runner.debug && 'DEBUG' || 'INFO' }}
           DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
+          DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
           SUPABASE_URL: ${{ steps.supabase.outputs.API_URL }}
           SUPABASE_SERVICE_ROLE_KEY: ${{ steps.supabase.outputs.SERVICE_ROLE_KEY }}
           SUPABASE_JWT_SECRET: ${{ steps.supabase.outputs.JWT_SECRET }}
-          REDIS_HOST: 'localhost'
-          REDIS_PORT: '6379'
-          REDIS_PASSWORD: 'testpassword'
+          REDIS_HOST: "localhost"
+          REDIS_PORT: "6379"
+          REDIS_PASSWORD: "testpassword"
 
     env:
       CI: true
@@ -139,6 +166,13 @@ jobs:
       RUN_ENV: local
       PORT: 8080
       OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+      # We know these are here, don't report this as a security vulnerability
+      # This is used as the default credential for the entire system's RabbitMQ instance
+      # If you want to replace this, you can do so by making our entire system generate
+      # new credentials for each local user and update the environment variables in
+      # the backend service, docker composes, and examples
+      RABBITMQ_DEFAULT_USER: "rabbitmq_user_default"
+      RABBITMQ_DEFAULT_PASS: "k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7"
 
       # - name: Upload coverage reports to Codecov
       #   uses: codecov/codecov-action@v4

.github/workflows/platform-frontend-ci.yml

@@ -77,12 +77,12 @@ jobs:
       - name: Free Disk Space (Ubuntu)
         uses: jlumbroso/free-disk-space@main
         with:
-          large-packages: false  # slow
-          docker-images: false  # limited benefit
+          large-packages: false # slow
+          docker-images: false # limited benefit
 
       - name: Copy default supabase .env
         run: |
-          cp ../supabase/docker/.env.example ../.env
+          cp ../.env.example ../.env
 
       - name: Copy backend .env
         run: |
@@ -104,11 +104,12 @@ jobs:
         run: yarn playwright install --with-deps ${{ matrix.browser }}
 
       - name: Run tests
+        timeout-minutes: 20
         run: |
           yarn test --project=${{ matrix.browser }}
 
-      - name: Print Docker Compose logs in debug mode
-        if: runner.debug
+      - name: Print Final Docker Compose logs
+        if: always()
         run: |
           docker compose -f ../docker-compose.yml logs
 

.github/workflows/repo-close-stale-issues.yml

@@ -16,7 +16,7 @@ jobs:
           # operations-per-run: 5000
           stale-issue-message: >
             This issue has automatically been marked as _stale_ because it has not had
-            any activity in the last 50 days. You can _unstale_ it by commenting or
+            any activity in the last 170 days. You can _unstale_ it by commenting or
             removing the label. Otherwise, this issue will be closed in 10 days.
           stale-pr-message: >
             This pull request has automatically been marked as _stale_ because it has
@@ -25,7 +25,7 @@ jobs:
           close-issue-message: >
             This issue was closed automatically because it has been stale for 10 days
             with no activity.
-          days-before-stale: 100
+          days-before-stale: 170
           days-before-close: 10
           # Do not touch meta issues:
           exempt-issue-labels: meta,fridge,project management

.gitmodules

@@ -1,6 +1,3 @@
 [submodule "classic/forge/tests/vcr_cassettes"]
 	path = classic/forge/tests/vcr_cassettes
 	url = https://github.com/Significant-Gravitas/Auto-GPT-test-cassettes
-[submodule "autogpt_platform/supabase"]
-	path = autogpt_platform/supabase
-	url = https://github.com/supabase/supabase.git

.pre-commit-config.yaml

@@ -140,7 +140,7 @@ repos:
         language: system
 
   - repo: https://github.com/psf/black
-    rev: 23.12.1
+    rev: 24.10.0
     # Black has sensible defaults, doesn't need package context, and ignores
     # everything in .gitignore, so it works fine without any config or arguments.
     hooks:
@@ -170,6 +170,16 @@ repos:
         files: ^classic/benchmark/(agbenchmark|tests)/((?!reports).)*[/.]
         args: [--config=classic/benchmark/.flake8]
 
+  - repo: local
+    hooks:
+      - id: prettier
+        name: Format (Prettier) - AutoGPT Platform - Frontend
+        alias: format-platform-frontend
+        entry: bash -c 'cd autogpt_platform/frontend && npx prettier --write $(echo "$@" | sed "s|autogpt_platform/frontend/||g")' --
+        files: ^autogpt_platform/frontend/
+        types: [file]
+        language: system
+
   - repo: local
     # To have watertight type checking, we check *all* the files in an affected
     # project. To trigger on poetry.lock we also reset the file `types` filter.
@@ -221,6 +231,16 @@ repos:
         language: system
         pass_filenames: false
 
+  - repo: local
+    hooks:
+      - id: tsc
+        name: Typecheck - AutoGPT Platform - Frontend
+        entry: bash -c 'cd autogpt_platform/frontend && npm run type-check'
+        files: ^autogpt_platform/frontend/
+        types: [file]
+        language: system
+        pass_filenames: false
+
   - repo: local
     hooks:
       - id: pytest

.vscode/launch.json

@@ -32,9 +32,9 @@
       "type": "debugpy",
       "request": "launch",
       "module": "backend.app",
-      // "env": {
-      //   "ENV": "dev"
-      // },
+      "env": {
+        "OBJC_DISABLE_INITIALIZE_FORK_SAFETY": "YES"
+      },
       "envFile": "${workspaceFolder}/backend/.env",
       "justMyCode": false,
       "cwd": "${workspaceFolder}/autogpt_platform/backend"

CONTRIBUTING.md

@@ -2,9 +2,6 @@
 If you are reading this, you are probably looking for the full **[contribution guide]**,
 which is part of our [wiki].
 
-Also check out our [🚀 Roadmap][roadmap] for information about our priorities and associated tasks.
-<!-- You can find our immediate priorities and their progress on our public [kanban board]. -->
-
 [contribution guide]: https://github.com/Significant-Gravitas/AutoGPT/wiki/Contributing
 [wiki]: https://github.com/Significant-Gravitas/AutoGPT/wiki
 [roadmap]: https://github.com/Significant-Gravitas/AutoGPT/discussions/6971

README.md

@@ -15,7 +15,11 @@
 > Setting up and hosting the AutoGPT Platform yourself is a technical process. 
 > If you'd rather something that just works, we recommend [joining the waitlist](https://bit.ly/3ZDijAI) for the cloud-hosted beta.
 
-https://github.com/user-attachments/assets/d04273a5-b36a-4a37-818e-f631ce72d603
+### Updated Setup Instructions:
+We’ve moved to a fully maintained and regularly updated documentation site.
+
+👉 [Follow the official self-hosting guide here](https://docs.agpt.co/platform/getting-started/)
+
 
 This tutorial assumes you have Docker, VSCode, git and npm installed.
 

SECURITY.md

@@ -20,6 +20,7 @@ Instead, please report them via:
 - Please provide detailed reports with reproducible steps
 - Include the version/commit hash where you discovered the vulnerability
 - Allow us a 90-day security fix window before any public disclosure
+- After patch is released, allow 30 days for users to update before public disclosure (for a total of 120 days max between update time and fix time)
 - Share any potential mitigations or workarounds if known
 
 ## Supported Versions

autogpt_platform/.env.example

@@ -0,0 +1,123 @@
+############
+# Secrets
+# YOU MUST CHANGE THESE BEFORE GOING INTO PRODUCTION
+############
+
+POSTGRES_PASSWORD=your-super-secret-and-long-postgres-password
+JWT_SECRET=your-super-secret-jwt-token-with-at-least-32-characters-long
+ANON_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE
+SERVICE_ROLE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
+DASHBOARD_USERNAME=supabase
+DASHBOARD_PASSWORD=this_password_is_insecure_and_should_be_updated
+SECRET_KEY_BASE=UpNVntn3cDxHJpq99YMc1T1AQgQpc8kfYTuRgBiYa15BLrx8etQoXz3gZv1/u2oq
+VAULT_ENC_KEY=your-encryption-key-32-chars-min
+
+
+############
+# Database - You can change these to any PostgreSQL database that has logical replication enabled.
+############
+
+POSTGRES_HOST=db
+POSTGRES_DB=postgres
+POSTGRES_PORT=5432
+# default user is postgres
+
+
+############
+# Supavisor -- Database pooler
+############
+POOLER_PROXY_PORT_TRANSACTION=6543
+POOLER_DEFAULT_POOL_SIZE=20
+POOLER_MAX_CLIENT_CONN=100
+POOLER_TENANT_ID=your-tenant-id
+
+
+############
+# API Proxy - Configuration for the Kong Reverse proxy.
+############
+
+KONG_HTTP_PORT=8000
+KONG_HTTPS_PORT=8443
+
+
+############
+# API - Configuration for PostgREST.
+############
+
+PGRST_DB_SCHEMAS=public,storage,graphql_public
+
+
+############
+# Auth - Configuration for the GoTrue authentication server.
+############
+
+## General
+SITE_URL=http://localhost:3000
+ADDITIONAL_REDIRECT_URLS=
+JWT_EXPIRY=3600
+DISABLE_SIGNUP=false
+API_EXTERNAL_URL=http://localhost:8000
+
+## Mailer Config
+MAILER_URLPATHS_CONFIRMATION="/auth/v1/verify"
+MAILER_URLPATHS_INVITE="/auth/v1/verify"
+MAILER_URLPATHS_RECOVERY="/auth/v1/verify"
+MAILER_URLPATHS_EMAIL_CHANGE="/auth/v1/verify"
+
+## Email auth
+ENABLE_EMAIL_SIGNUP=true
+ENABLE_EMAIL_AUTOCONFIRM=false
+SMTP_ADMIN_EMAIL=admin@example.com
+SMTP_HOST=supabase-mail
+SMTP_PORT=2500
+SMTP_USER=fake_mail_user
+SMTP_PASS=fake_mail_password
+SMTP_SENDER_NAME=fake_sender
+ENABLE_ANONYMOUS_USERS=false
+
+## Phone auth
+ENABLE_PHONE_SIGNUP=true
+ENABLE_PHONE_AUTOCONFIRM=true
+
+
+############
+# Studio - Configuration for the Dashboard
+############
+
+STUDIO_DEFAULT_ORGANIZATION=Default Organization
+STUDIO_DEFAULT_PROJECT=Default Project
+
+STUDIO_PORT=3000
+# replace if you intend to use Studio outside of localhost
+SUPABASE_PUBLIC_URL=http://localhost:8000
+
+# Enable webp support
+IMGPROXY_ENABLE_WEBP_DETECTION=true
+
+# Add your OpenAI API key to enable SQL Editor Assistant
+OPENAI_API_KEY=
+
+
+############
+# Functions - Configuration for Functions
+############
+# NOTE: VERIFY_JWT applies to all functions. Per-function VERIFY_JWT is not supported yet.
+FUNCTIONS_VERIFY_JWT=false
+
+
+############
+# Logs - Configuration for Logflare
+# Please refer to https://supabase.com/docs/reference/self-hosting-analytics/introduction
+############
+
+LOGFLARE_LOGGER_BACKEND_API_KEY=your-super-secret-and-long-logflare-key
+
+# Change vector.toml sinks to reflect this change
+LOGFLARE_API_KEY=your-super-secret-and-long-logflare-key
+
+# Docker socket location - this value will differ depending on your OS
+DOCKER_SOCKET_LOCATION=/var/run/docker.sock
+
+# Google Cloud Project details
+GOOGLE_PROJECT_ID=GOOGLE_PROJECT_ID
+GOOGLE_PROJECT_NUMBER=GOOGLE_PROJECT_NUMBER

autogpt_platform/README.md

@@ -22,35 +22,29 @@ To run the AutoGPT Platform, follow these steps:
 
 2. Run the following command:
    ```
-   git submodule update --init --recursive --progress
+   cp .env.example .env
    ```
-   This command will initialize and update the submodules in the repository. The `supabase` folder will be cloned to the root directory.
+   This command will copy the `.env.example` file to `.env`. You can modify the `.env` file to add your own environment variables.
 
 3. Run the following command:
-   ```
-   cp supabase/docker/.env.example .env
-   ```
-   This command will copy the `.env.example` file to `.env` in the `supabase/docker` directory. You can modify the `.env` file to add your own environment variables.
-
-4. Run the following command:
    ```
    docker compose up -d
    ```
    This command will start all the necessary backend services defined in the `docker-compose.yml` file in detached mode.
 
-5. Navigate to `frontend` within the `autogpt_platform` directory:
+4. Navigate to `frontend` within the `autogpt_platform` directory:
    ```
    cd frontend
    ```
    You will need to run your frontend application separately on your local machine.
 
-6. Run the following command: 
+5. Run the following command: 
    ```
    cp .env.example .env.local
    ```
    This command will copy the `.env.example` file to `.env.local` in the `frontend` directory. You can modify the `.env.local` within this folder to add your own environment variables for the frontend application.
 
-7. Run the following command:
+6. Run the following command:
    ```
    npm install
    npm run dev
@@ -61,7 +55,7 @@ To run the AutoGPT Platform, follow these steps:
    yarn install && yarn dev
    ```
 
-8. Open your browser and navigate to `http://localhost:3000` to access the AutoGPT Platform frontend.
+7. Open your browser and navigate to `http://localhost:3000` to access the AutoGPT Platform frontend.
 
 ### Docker Compose Commands
 

autogpt_platform/autogpt_libs/autogpt_libs/auth/__init__.py

@@ -1,14 +1,13 @@
-from .config import Settings
 from .depends import requires_admin_user, requires_user
 from .jwt_utils import parse_jwt_token
-from .middleware import auth_middleware
+from .middleware import APIKeyValidator, auth_middleware
 from .models import User
 
 __all__ = [
-    "Settings",
     "parse_jwt_token",
     "requires_user",
     "requires_admin_user",
+    "APIKeyValidator",
     "auth_middleware",
     "User",
 ]

autogpt_platform/autogpt_libs/autogpt_libs/auth/config.py

@@ -1,14 +1,11 @@
 import os
 
-from dotenv import load_dotenv
-
-load_dotenv()
-
 
 class Settings:
-    JWT_SECRET_KEY: str = os.getenv("SUPABASE_JWT_SECRET", "")
-    ENABLE_AUTH: bool = os.getenv("ENABLE_AUTH", "false").lower() == "true"
-    JWT_ALGORITHM: str = "HS256"
+    def __init__(self):
+        self.JWT_SECRET_KEY: str = os.getenv("SUPABASE_JWT_SECRET", "")
+        self.ENABLE_AUTH: bool = os.getenv("ENABLE_AUTH", "false").lower() == "true"
+        self.JWT_ALGORITHM: str = "HS256"
 
     @property
     def is_configured(self) -> bool:

autogpt_platform/autogpt_libs/autogpt_libs/auth/depends.py

@@ -1,6 +1,6 @@
 import fastapi
 
-from .config import Settings
+from .config import settings
 from .middleware import auth_middleware
 from .models import DEFAULT_USER_ID, User
 
@@ -17,7 +17,7 @@ def requires_admin_user(
 
 def verify_user(payload: dict | None, admin_only: bool) -> User:
     if not payload:
-        if Settings.ENABLE_AUTH:
+        if settings.ENABLE_AUTH:
             raise fastapi.HTTPException(
                 status_code=401, detail="Authorization header is missing"
             )

autogpt_platform/autogpt_libs/autogpt_libs/auth/middleware.py

@@ -1,7 +1,10 @@
+import inspect
 import logging
+from typing import Any, Callable, Optional
 
-from fastapi import HTTPException, Request
-from fastapi.security import HTTPBearer
+from fastapi import HTTPException, Request, Security
+from fastapi.security import APIKeyHeader, HTTPBearer
+from starlette.status import HTTP_401_UNAUTHORIZED
 
 from .config import settings
 from .jwt_utils import parse_jwt_token
@@ -13,7 +16,7 @@ logger = logging.getLogger(__name__)
 async def auth_middleware(request: Request):
     if not settings.ENABLE_AUTH:
         # If authentication is disabled, allow the request to proceed
-        logger.warn("Auth disabled")
+        logger.warning("Auth disabled")
         return {}
 
     security = HTTPBearer()
@@ -29,3 +32,104 @@ async def auth_middleware(request: Request):
     except ValueError as e:
         raise HTTPException(status_code=401, detail=str(e))
     return payload
+
+
+class APIKeyValidator:
+    """
+    Configurable API key validator that supports custom validation functions
+    for FastAPI applications.
+
+    This class provides a flexible way to implement API key authentication with optional
+    custom validation logic. It can be used for simple token matching
+    or more complex validation scenarios like database lookups.
+
+    Examples:
+        Simple token validation:
+        ```python
+        validator = APIKeyValidator(
+            header_name="X-API-Key",
+            expected_token="your-secret-token"
+        )
+
+        @app.get("/protected", dependencies=[Depends(validator.get_dependency())])
+        def protected_endpoint():
+            return {"message": "Access granted"}
+        ```
+
+        Custom validation with database lookup:
+        ```python
+        async def validate_with_db(api_key: str):
+            api_key_obj = await db.get_api_key(api_key)
+            return api_key_obj if api_key_obj and api_key_obj.is_active else None
+
+        validator = APIKeyValidator(
+            header_name="X-API-Key",
+            validate_fn=validate_with_db
+        )
+        ```
+
+    Args:
+        header_name (str): The name of the header containing the API key
+        expected_token (Optional[str]): The expected API key value for simple token matching
+        validate_fn (Optional[Callable]): Custom validation function that takes an API key
+            string and returns a boolean or object. Can be async.
+        error_status (int): HTTP status code to use for validation errors
+        error_message (str): Error message to return when validation fails
+    """
+
+    def __init__(
+        self,
+        header_name: str,
+        expected_token: Optional[str] = None,
+        validate_fn: Optional[Callable[[str], bool]] = None,
+        error_status: int = HTTP_401_UNAUTHORIZED,
+        error_message: str = "Invalid API key",
+    ):
+        # Create the APIKeyHeader as a class property
+        self.security_scheme = APIKeyHeader(name=header_name)
+        self.expected_token = expected_token
+        self.custom_validate_fn = validate_fn
+        self.error_status = error_status
+        self.error_message = error_message
+
+    async def default_validator(self, api_key: str) -> bool:
+        return api_key == self.expected_token
+
+    async def __call__(
+        self, request: Request, api_key: str = Security(APIKeyHeader)
+    ) -> Any:
+        if api_key is None:
+            raise HTTPException(status_code=self.error_status, detail="Missing API key")
+
+        # Use custom validation if provided, otherwise use default equality check
+        validator = self.custom_validate_fn or self.default_validator
+        result = (
+            await validator(api_key)
+            if inspect.iscoroutinefunction(validator)
+            else validator(api_key)
+        )
+
+        if not result:
+            raise HTTPException(
+                status_code=self.error_status, detail=self.error_message
+            )
+
+        # Store validation result in request state if it's not just a boolean
+        if result is not True:
+            request.state.api_key = result
+
+        return result
+
+    def get_dependency(self):
+        """
+        Returns a callable dependency that FastAPI will recognize as a security scheme
+        """
+
+        async def validate_api_key(
+            request: Request, api_key: str = Security(self.security_scheme)
+        ) -> Any:
+            return await self(request, api_key)
+
+        # This helps FastAPI recognize it as a security dependency
+        validate_api_key.__name__ = f"validate_{self.security_scheme.model.name}"
+        return validate_api_key

autogpt_platform/autogpt_libs/autogpt_libs/feature_flag/client.py

@@ -13,7 +13,6 @@ from typing_extensions import ParamSpec
 from .config import SETTINGS
 
 logger = logging.getLogger(__name__)
-logging.basicConfig(level=logging.DEBUG)
 
 P = ParamSpec("P")
 T = TypeVar("T")

autogpt_platform/autogpt_libs/autogpt_libs/logging/config.py

@@ -8,7 +8,7 @@ from pydantic import Field, field_validator
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
 from .filters import BelowLevelFilter
-from .formatters import AGPTFormatter, StructuredLoggingFormatter
+from .formatters import AGPTFormatter
 
 LOG_DIR = Path(__file__).parent.parent.parent.parent / "logs"
 LOG_FILE = "activity.log"
@@ -81,9 +81,26 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
     """
 
     config = LoggingConfig()
-
     log_handlers: list[logging.Handler] = []
 
+    # Console output handlers
+    stdout = logging.StreamHandler(stream=sys.stdout)
+    stdout.setLevel(config.level)
+    stdout.addFilter(BelowLevelFilter(logging.WARNING))
+    if config.level == logging.DEBUG:
+        stdout.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
+    else:
+        stdout.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
+
+    stderr = logging.StreamHandler()
+    stderr.setLevel(logging.WARNING)
+    if config.level == logging.DEBUG:
+        stderr.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
+    else:
+        stderr.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
+
+    log_handlers += [stdout, stderr]
+
     # Cloud logging setup
     if config.enable_cloud_logging or force_cloud_logging:
         import google.cloud.logging
@@ -97,28 +114,7 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
             transport=SyncTransport,
         )
         cloud_handler.setLevel(config.level)
-        cloud_handler.setFormatter(StructuredLoggingFormatter())
         log_handlers.append(cloud_handler)
-        print("Cloud logging enabled")
-    else:
-        # Console output handlers
-        stdout = logging.StreamHandler(stream=sys.stdout)
-        stdout.setLevel(config.level)
-        stdout.addFilter(BelowLevelFilter(logging.WARNING))
-        if config.level == logging.DEBUG:
-            stdout.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
-        else:
-            stdout.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
-
-        stderr = logging.StreamHandler()
-        stderr.setLevel(logging.WARNING)
-        if config.level == logging.DEBUG:
-            stderr.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
-        else:
-            stderr.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
-
-        log_handlers += [stdout, stderr]
-        print("Console logging enabled")
 
     # File logging setup
     if config.enable_file_logging:
@@ -156,7 +152,6 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
         error_log_handler.setLevel(logging.ERROR)
         error_log_handler.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT, no_color=True))
         log_handlers.append(error_log_handler)
-        print("File logging enabled")
 
     # Configure the root logger
     logging.basicConfig(

autogpt_platform/autogpt_libs/autogpt_libs/logging/formatters.py

@@ -1,7 +1,6 @@
 import logging
 
 from colorama import Fore, Style
-from google.cloud.logging_v2.handlers import CloudLoggingFilter, StructuredLogHandler
 
 from .utils import remove_color_codes
 
@@ -80,16 +79,3 @@ class AGPTFormatter(FancyConsoleFormatter):
             return remove_color_codes(super().format(record))
         else:
             return super().format(record)
-
-
-class StructuredLoggingFormatter(StructuredLogHandler, logging.Formatter):
-    def __init__(self):
-        # Set up CloudLoggingFilter to add diagnostic info to the log records
-        self.cloud_logging_filter = CloudLoggingFilter()
-
-        # Init StructuredLogHandler
-        super().__init__()
-
-    def format(self, record: logging.LogRecord) -> str:
-        self.cloud_logging_filter.filter(record)
-        return super().format(record)

autogpt_platform/autogpt_libs/autogpt_libs/logging/utils.py

@@ -2,6 +2,7 @@ import logging
 import re
 from typing import Any
 
+import uvicorn.config
 from colorama import Fore
 
 
@@ -25,3 +26,14 @@ def print_attribute(
             "color": value_color,
         },
     )
+
+
+def generate_uvicorn_config():
+    """
+    Generates a uvicorn logging config that silences uvicorn's default logging and tells it to use the native logging module.
+    """
+    log_config = dict(uvicorn.config.LOGGING_CONFIG)
+    log_config["loggers"]["uvicorn"] = {"handlers": []}
+    log_config["loggers"]["uvicorn.error"] = {"handlers": []}
+    log_config["loggers"]["uvicorn.access"] = {"handlers": []}
+    return log_config

autogpt_platform/autogpt_libs/autogpt_libs/utils/cache.py

@@ -1,20 +1,59 @@
+import inspect
 import threading
-from typing import Callable, ParamSpec, TypeVar
+from typing import Awaitable, Callable, ParamSpec, TypeVar, cast, overload
 
 P = ParamSpec("P")
 R = TypeVar("R")
 
 
-def thread_cached(func: Callable[P, R]) -> Callable[P, R]:
+@overload
+def thread_cached(func: Callable[P, Awaitable[R]]) -> Callable[P, Awaitable[R]]: ...
+
+
+@overload
+def thread_cached(func: Callable[P, R]) -> Callable[P, R]: ...
+
+
+def thread_cached(
+    func: Callable[P, R] | Callable[P, Awaitable[R]],
+) -> Callable[P, R] | Callable[P, Awaitable[R]]:
     thread_local = threading.local()
 
-    def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
-        cache = getattr(thread_local, "cache", None)
-        if cache is None:
-            cache = thread_local.cache = {}
-        key = (args, tuple(sorted(kwargs.items())))
-        if key not in cache:
-            cache[key] = func(*args, **kwargs)
-        return cache[key]
+    def _clear():
+        if hasattr(thread_local, "cache"):
+            del thread_local.cache
 
-    return wrapper
+    if inspect.iscoroutinefunction(func):
+
+        async def async_wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
+            cache = getattr(thread_local, "cache", None)
+            if cache is None:
+                cache = thread_local.cache = {}
+            key = (args, tuple(sorted(kwargs.items())))
+            if key not in cache:
+                cache[key] = await cast(Callable[P, Awaitable[R]], func)(
+                    *args, **kwargs
+                )
+            return cache[key]
+
+        setattr(async_wrapper, "clear_cache", _clear)
+        return async_wrapper
+
+    else:
+
+        def sync_wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
+            cache = getattr(thread_local, "cache", None)
+            if cache is None:
+                cache = thread_local.cache = {}
+            key = (args, tuple(sorted(kwargs.items())))
+            if key not in cache:
+                cache[key] = func(*args, **kwargs)
+            return cache[key]
+
+        setattr(sync_wrapper, "clear_cache", _clear)
+        return sync_wrapper
+
+
+def clear_thread_cache(func: Callable) -> None:
+    if clear := getattr(func, "clear_cache", None):
+        clear()

autogpt_platform/autogpt_libs/autogpt_libs/utils/synchronize.py

@@ -31,7 +31,7 @@ class RedisKeyedMutex:
         try:
             yield
         finally:
-            if lock.locked():
+            if lock.locked() and lock.owned():
                 lock.release()
 
     def acquire(self, key: Any) -> "RedisLock":

autogpt_platform/autogpt_libs/pyproject.toml

@@ -7,21 +7,20 @@ readme = "README.md"
 packages = [{ include = "autogpt_libs" }]
 
 [tool.poetry.dependencies]
+python = ">=3.10,<4.0"
 colorama = "^0.4.6"
 expiringdict = "^1.2.2"
-google-cloud-logging = "^3.11.4"
-pydantic = "^2.10.6"
-pydantic-settings = "^2.7.1"
+google-cloud-logging = "^3.12.1"
+pydantic = "^2.11.4"
+pydantic-settings = "^2.9.1"
 pyjwt = "^2.10.1"
-pytest-asyncio = "^0.25.3"
+pytest-asyncio = "^0.26.0"
 pytest-mock = "^3.14.0"
-python = ">=3.10,<4.0"
-python-dotenv = "^1.0.1"
-supabase = "^2.13.0"
+supabase = "^2.15.1"
 
 [tool.poetry.group.dev.dependencies]
 redis = "^5.2.1"
-ruff = "^0.9.3"
+ruff = "^0.11.10"
 
 [build-system]
 requires = ["poetry-core"]

autogpt_platform/backend/.env.example

@@ -2,13 +2,24 @@ DB_USER=postgres
 DB_PASS=your-super-secret-and-long-postgres-password
 DB_NAME=postgres
 DB_PORT=5432
-DATABASE_URL="postgresql://${DB_USER}:${DB_PASS}@localhost:${DB_PORT}/${DB_NAME}?connect_timeout=60&schema=platform"
+DB_HOST=localhost
+DB_CONNECTION_LIMIT=12
+DB_CONNECT_TIMEOUT=60
+DB_POOL_TIMEOUT=300
+DB_SCHEMA=platform
+DATABASE_URL="postgresql://${DB_USER}:${DB_PASS}@${DB_HOST}:${DB_PORT}/${DB_NAME}?schema=${DB_SCHEMA}&connect_timeout=${DB_CONNECT_TIMEOUT}"
+DIRECT_URL="postgresql://${DB_USER}:${DB_PASS}@${DB_HOST}:${DB_PORT}/${DB_NAME}?schema=${DB_SCHEMA}&connect_timeout=${DB_CONNECT_TIMEOUT}"
 PRISMA_SCHEMA="postgres/schema.prisma"
 
+# EXECUTOR
+NUM_GRAPH_WORKERS=10
+NUM_NODE_WORKERS=3
+
 BACKEND_CORS_ALLOW_ORIGINS=["http://localhost:3000"]
 
 # generate using `from cryptography.fernet import Fernet;Fernet.generate_key().decode()`
 ENCRYPTION_KEY='dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw='
+UNSUBSCRIBE_SECRET_KEY = 'HlP8ivStJjmbf6NKi78m_3FnOogut0t5ckzjsIqeaio='
 
 REDIS_HOST=localhost
 REDIS_PORT=6379
@@ -25,6 +36,11 @@ BEHAVE_AS=local
 PYRO_HOST=localhost
 SENTRY_DSN=
 
+# Email For Postmark so we can send emails
+POSTMARK_SERVER_API_TOKEN=
+POSTMARK_SENDER_EMAIL=invalid@invalid.com
+POSTMARK_WEBHOOK_TOKEN=
+
 ## User auth with Supabase is required for any of the 3rd party integrations with auth to work.
 ENABLE_AUTH=true
 SUPABASE_URL=http://localhost:8000
@@ -37,6 +53,9 @@ RABBITMQ_PORT=5672
 RABBITMQ_DEFAULT_USER=rabbitmq_user_default
 RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
 
+## GCS bucket is required for marketplace and library functionality
+MEDIA_GCS_BUCKET_NAME=
+
 ## For local development, you may need to set FRONTEND_BASE_URL for the OAuth flow
 ## for integrations to work. Defaults to the value of PLATFORM_BASE_URL if not set.
 # FRONTEND_BASE_URL=http://localhost:3000
@@ -47,6 +66,13 @@ RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
 ## and tunnel it to your locally running backend.
 PLATFORM_BASE_URL=http://localhost:3000
 
+## Cloudflare Turnstile (CAPTCHA) Configuration
+## Get these from the Cloudflare Turnstile dashboard: https://dash.cloudflare.com/?to=/:account/turnstile
+## This is the backend secret key
+TURNSTILE_SECRET_KEY=
+## This is the verify URL
+TURNSTILE_VERIFY_URL=https://challenges.cloudflare.com/turnstile/v0/siteverify
+
 ## == INTEGRATION CREDENTIALS == ##
 # Each set of server side credentials is required for the corresponding 3rd party
 # integration to work.
@@ -103,6 +129,7 @@ OPENAI_API_KEY=
 ANTHROPIC_API_KEY=
 GROQ_API_KEY=
 OPEN_ROUTER_API_KEY=
+LLAMA_API_KEY=
 
 # Reddit
 # Go to https://www.reddit.com/prefs/apps and create a new app
@@ -161,6 +188,17 @@ MEM0_API_KEY=
 # Nvidia
 NVIDIA_API_KEY=
 
+# Apollo
+APOLLO_API_KEY=
+
+# SmartLead
+SMARTLEAD_API_KEY=
+
+# ZeroBounce
+ZEROBOUNCE_API_KEY=
+
+## ===== OPTIONAL API KEYS END ===== ##
+
 # Logging Configuration
 LOG_LEVEL=INFO
 ENABLE_CLOUD_LOGGING=false

autogpt_platform/backend/Dockerfile

@@ -73,7 +73,6 @@ FROM server_dependencies AS server
 COPY autogpt_platform/backend /app/autogpt_platform/backend
 RUN poetry install --no-ansi --only-root
 
-ENV DATABASE_URL=""
 ENV PORT=8000
 
 CMD ["poetry", "run", "rest"]

autogpt_platform/backend/README.advanced.md

@@ -1,75 +1 @@
-# AutoGPT Agent Server Advanced set up
-
-This guide walks you through a dockerized set up, with an external DB (postgres)
-
-## Setup
-
-We use the Poetry to manage the dependencies. To set up the project, follow these steps inside this directory:
-
-0. Install Poetry
-    ```sh
-    pip install poetry
-    ```
-    
-1. Configure Poetry to use .venv in your project directory
-    ```sh
-    poetry config virtualenvs.in-project true
-    ```
-
-2. Enter the poetry shell
-
-   ```sh
-   poetry shell
-   ```
-   
-3. Install dependencies
-
-   ```sh
-   poetry install
-   ```
-   
-4. Copy .env.example to .env
-
-   ```sh
-   cp .env.example .env
-   ```
-
-5. Generate the Prisma client
-
-   ```sh
-   poetry run prisma generate
-   ```
-   
-
-   > In case Prisma generates the client for the global Python installation instead of the virtual environment, the current mitigation is to just uninstall the global Prisma package:
-   >
-   > ```sh
-   > pip uninstall prisma
-   > ```
-   >
-   > Then run the generation again. The path *should* look something like this:  
-   > `<some path>/pypoetry/virtualenvs/backend-TQIRSwR6-py3.12/bin/prisma`
-
-6. Run the postgres database from the /rnd folder
-
-   ```sh
-   cd autogpt_platform/
-   docker compose up -d
-   ```
-
-7. Run the migrations (from the backend folder)
-
-   ```sh
-   cd ../backend
-   prisma migrate deploy
-   ```
-
-## Running The Server
-
-### Starting the server directly
-
-Run the following command:
-
-```sh
-poetry run app
-```
+[Advanced Setup (Dev Branch)](https://dev-docs.agpt.co/platform/advanced_setup/#autogpt_agent_server_advanced_set_up)

autogpt_platform/backend/README.md

@@ -1,210 +1 @@
-# AutoGPT Agent Server 
-
-This is an initial project for creating the next generation of agent execution, which is an AutoGPT agent server.
-The agent server will enable the creation of composite multi-agent systems that utilize AutoGPT agents and other non-agent components as its primitives.
-
-## Docs
-
-You can access the docs for the [AutoGPT Agent Server here](https://docs.agpt.co/server/setup).
-
-## Setup
-
-We use the Poetry to manage the dependencies. To set up the project, follow these steps inside this directory:
-
-0. Install Poetry
-    ```sh
-    pip install poetry
-    ```
-    
-1. Configure Poetry to use .venv in your project directory
-    ```sh
-    poetry config virtualenvs.in-project true
-    ```
-
-2. Enter the poetry shell
-
-   ```sh
-   poetry shell
-   ```
-   
-3. Install dependencies
-
-   ```sh
-   poetry install
-   ```
-
-4. Copy .env.example to .env
-
-   ```sh
-   cp .env.example .env
-   ```
-   
-5. Generate the Prisma client
-
-   ```sh
-   poetry run prisma generate
-   ```
-   
-
-   > In case Prisma generates the client for the global Python installation instead of the virtual environment, the current mitigation is to just uninstall the global Prisma package:
-   >
-   > ```sh
-   > pip uninstall prisma
-   > ```
-   >
-   > Then run the generation again. The path *should* look something like this:  
-   > `<some path>/pypoetry/virtualenvs/backend-TQIRSwR6-py3.12/bin/prisma`
-
-6. Migrate the database. Be careful because this deletes current data in the database.
-
-   ```sh
-   docker compose up db -d
-   poetry run prisma migrate deploy
-   ```
-
-## Running The Server
-
-### Starting the server without Docker
-
-To run the server locally, start in the autogpt_platform folder:
-
-```sh
-cd ..
-```
-
-Run the following command to run database in docker but the application locally:
-
-```sh
-docker compose --profile local up deps --build --detach
-cd backend
-poetry run app
-```
-
-### Starting the server with Docker
-
-Run the following command to build the dockerfiles:
-
-```sh
-docker compose build
-```
-
-Run the following command to run the app:
-
-```sh
-docker compose up
-```
-
-Run the following to automatically rebuild when code changes, in another terminal:
-
-```sh
-docker compose watch
-```
-
-Run the following command to shut down:
-
-```sh
-docker compose down
-```
-
-If you run into issues with dangling orphans, try:
-
-```sh
-docker compose down --volumes --remove-orphans && docker-compose up --force-recreate --renew-anon-volumes --remove-orphans  
-```
-
-## Testing
-
-To run the tests:
-
-```sh
-poetry run test
-```
-
-## Development
-
-### Formatting & Linting
-Auto formatter and linter are set up in the project. To run them:
-
-Install:
-```sh
-poetry install --with dev
-```
-
-Format the code:
-```sh
-poetry run format
-```
-
-Lint the code:
-```sh
-poetry run lint
-```
-
-## Project Outline
-
-The current project has the following main modules:
-
-### **blocks**
-
-This module stores all the Agent Blocks, which are reusable components to build a graph that represents the agent's behavior.
-
-### **data**
-
-This module stores the logical model that is persisted in the database.
-It abstracts the database operations into functions that can be called by the service layer.
-Any code that interacts with Prisma objects or the database should reside in this module.
-The main models are:
-* `block`: anything related to the block used in the graph
-* `execution`: anything related to the execution graph execution
-* `graph`: anything related to the graph, node, and its relations
-
-### **execution**
-
-This module stores the business logic of executing the graph.
-It currently has the following main modules:
-* `manager`: A service that consumes the queue of the graph execution and executes the graph. It contains both pieces of logic.
-* `scheduler`: A service that triggers scheduled graph execution based on a cron expression. It pushes an execution request to the manager.
-
-### **server**
-
-This module stores the logic for the server API.
-It contains all the logic used for the API that allows the client to create, execute, and monitor the graph and its execution.
-This API service interacts with other services like those defined in `manager` and `scheduler`.
-
-### **utils**
-
-This module stores utility functions that are used across the project.
-Currently, it has two main modules:
-* `process`: A module that contains the logic to spawn a new process.
-* `service`: A module that serves as a parent class for all the services in the project.
-
-## Service Communication
-
-Currently, there are only 3 active services:
-
-- AgentServer (the API, defined in `server.py`)
-- ExecutionManager (the executor, defined in `manager.py`)
-- ExecutionScheduler (the scheduler, defined in `scheduler.py`)
-
-The services run in independent Python processes and communicate through an IPC.
-A communication layer (`service.py`) is created to decouple the communication library from the implementation.
-
-Currently, the IPC is done using Pyro5 and abstracted in a way that allows a function decorated with `@expose` to be called from a different process.
-
-
-By default the daemons run on the following ports: 
-
-Execution Manager Daemon: 8002
-Execution Scheduler Daemon: 8003
-Rest Server Daemon: 8004
-
-## Adding a New Agent Block
-
-To add a new agent block, you need to create a new class that inherits from `Block` and provides the following information:
-* All the block code should live in the `blocks` (`backend.blocks`) module.
-* `input_schema`: the schema of the input data, represented by a Pydantic object.
-* `output_schema`: the schema of the output data, represented by a Pydantic object.
-* `run` method: the main logic of the block.
-* `test_input` & `test_output`: the sample input and output data for the block, which will be used to auto-test the block.
-* You can mock the functions declared in the block using the `test_mock` field for your unit tests.
-* Once you finish creating the block, you can test it by running `poetry run pytest -s test/block/test_block.py`.
+[Getting Started (Released)](https://docs.agpt.co/platform/getting-started/#autogpt_agent_server)

autogpt_platform/backend/backend/app.py

@@ -1,22 +1,30 @@
+import logging
 from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
     from backend.util.process import AppProcess
 
+logger = logging.getLogger(__name__)
+
 
 def run_processes(*processes: "AppProcess", **kwargs):
     """
     Execute all processes in the app. The last process is run in the foreground.
+    Includes enhanced error handling and process lifecycle management.
     """
     try:
+        # Run all processes except the last one in the background.
         for process in processes[:-1]:
             process.start(background=True, **kwargs)
 
-        # Run the last process in the foreground
+        # Run the last process in the foreground.
         processes[-1].start(background=False, **kwargs)
     finally:
         for process in processes:
-            process.stop()
+            try:
+                process.stop()
+            except Exception as e:
+                logger.exception(f"[{process.service_name}] unable to stop: {e}")
 
 
 def main(**kwargs):
@@ -24,14 +32,16 @@ def main(**kwargs):
     Run all the processes required for the AutoGPT-server (REST and WebSocket APIs).
     """
 
-    from backend.executor import DatabaseManager, ExecutionManager, ExecutionScheduler
+    from backend.executor import DatabaseManager, ExecutionManager, Scheduler
+    from backend.notifications import NotificationManager
     from backend.server.rest_api import AgentServer
     from backend.server.ws_api import WebsocketServer
 
     run_processes(
         DatabaseManager(),
         ExecutionManager(),
-        ExecutionScheduler(),
+        Scheduler(),
+        NotificationManager(),
         WebsocketServer(),
         AgentServer(),
         **kwargs,

autogpt_platform/backend/backend/blocks/__init__.py

@@ -1,89 +1,99 @@
+import functools
 import importlib
 import os
 import re
 from pathlib import Path
-from typing import Type, TypeVar
-
-from backend.data.block import Block
-
-# Dynamically load all modules under backend.blocks
-AVAILABLE_MODULES = []
-current_dir = Path(__file__).parent
-modules = [
-    str(f.relative_to(current_dir))[:-3].replace(os.path.sep, ".")
-    for f in current_dir.rglob("*.py")
-    if f.is_file() and f.name != "__init__.py"
-]
-for module in modules:
-    if not re.match("^[a-z0-9_.]+$", module):
-        raise ValueError(
-            f"Block module {module} error: module name must be lowercase, "
-            "and contain only alphanumeric characters and underscores."
-        )
-
-    importlib.import_module(f".{module}", package=__name__)
-    AVAILABLE_MODULES.append(module)
-
-# Load all Block instances from the available modules
-AVAILABLE_BLOCKS: dict[str, Type[Block]] = {}
+from typing import TYPE_CHECKING, TypeVar
 
+if TYPE_CHECKING:
+    from backend.data.block import Block
 
 T = TypeVar("T")
 
 
-def all_subclasses(cls: Type[T]) -> list[Type[T]]:
+@functools.cache
+def load_all_blocks() -> dict[str, type["Block"]]:
+    from backend.data.block import Block
+
+    # Dynamically load all modules under backend.blocks
+    current_dir = Path(__file__).parent
+    modules = [
+        str(f.relative_to(current_dir))[:-3].replace(os.path.sep, ".")
+        for f in current_dir.rglob("*.py")
+        if f.is_file() and f.name != "__init__.py"
+    ]
+    for module in modules:
+        if not re.match("^[a-z0-9_.]+$", module):
+            raise ValueError(
+                f"Block module {module} error: module name must be lowercase, "
+                "and contain only alphanumeric characters and underscores."
+            )
+
+        importlib.import_module(f".{module}", package=__name__)
+
+    # Load all Block instances from the available modules
+    available_blocks: dict[str, type["Block"]] = {}
+    for block_cls in all_subclasses(Block):
+        class_name = block_cls.__name__
+
+        if class_name.endswith("Base"):
+            continue
+
+        if not class_name.endswith("Block"):
+            raise ValueError(
+                f"Block class {class_name} does not end with 'Block'. "
+                "If you are creating an abstract class, "
+                "please name the class with 'Base' at the end"
+            )
+
+        block = block_cls.create()
+
+        if not isinstance(block.id, str) or len(block.id) != 36:
+            raise ValueError(
+                f"Block ID {block.name} error: {block.id} is not a valid UUID"
+            )
+
+        if block.id in available_blocks:
+            raise ValueError(
+                f"Block ID {block.name} error: {block.id} is already in use"
+            )
+
+        input_schema = block.input_schema.model_fields
+        output_schema = block.output_schema.model_fields
+
+        # Make sure `error` field is a string in the output schema
+        if "error" in output_schema and output_schema["error"].annotation is not str:
+            raise ValueError(
+                f"{block.name} `error` field in output_schema must be a string"
+            )
+
+        # Ensure all fields in input_schema and output_schema are annotated SchemaFields
+        for field_name, field in [*input_schema.items(), *output_schema.items()]:
+            if field.annotation is None:
+                raise ValueError(
+                    f"{block.name} has a field {field_name} that is not annotated"
+                )
+            if field.json_schema_extra is None:
+                raise ValueError(
+                    f"{block.name} has a field {field_name} not defined as SchemaField"
+                )
+
+        for field in block.input_schema.model_fields.values():
+            if field.annotation is bool and field.default not in (True, False):
+                raise ValueError(
+                    f"{block.name} has a boolean field with no default value"
+                )
+
+        available_blocks[block.id] = block_cls
+
+    return available_blocks
+
+
+__all__ = ["load_all_blocks"]
+
+
+def all_subclasses(cls: type[T]) -> list[type[T]]:
     subclasses = cls.__subclasses__()
     for subclass in subclasses:
         subclasses += all_subclasses(subclass)
     return subclasses
-
-
-for block_cls in all_subclasses(Block):
-    name = block_cls.__name__
-
-    if block_cls.__name__.endswith("Base"):
-        continue
-
-    if not block_cls.__name__.endswith("Block"):
-        raise ValueError(
-            f"Block class {block_cls.__name__} does not end with 'Block', If you are creating an abstract class, please name the class with 'Base' at the end"
-        )
-
-    block = block_cls.create()
-
-    if not isinstance(block.id, str) or len(block.id) != 36:
-        raise ValueError(f"Block ID {block.name} error: {block.id} is not a valid UUID")
-
-    if block.id in AVAILABLE_BLOCKS:
-        raise ValueError(f"Block ID {block.name} error: {block.id} is already in use")
-
-    input_schema = block.input_schema.model_fields
-    output_schema = block.output_schema.model_fields
-
-    # Make sure `error` field is a string in the output schema
-    if "error" in output_schema and output_schema["error"].annotation is not str:
-        raise ValueError(
-            f"{block.name} `error` field in output_schema must be a string"
-        )
-
-    # Make sure all fields in input_schema and output_schema are annotated and has a value
-    for field_name, field in [*input_schema.items(), *output_schema.items()]:
-        if field.annotation is None:
-            raise ValueError(
-                f"{block.name} has a field {field_name} that is not annotated"
-            )
-        if field.json_schema_extra is None:
-            raise ValueError(
-                f"{block.name} has a field {field_name} not defined as SchemaField"
-            )
-
-    for field in block.input_schema.model_fields.values():
-        if field.annotation is bool and field.default not in (True, False):
-            raise ValueError(f"{block.name} has a boolean field with no default value")
-
-    if block.disabled:
-        continue
-
-    AVAILABLE_BLOCKS[block.id] = block_cls
-
-__all__ = ["AVAILABLE_MODULES", "AVAILABLE_BLOCKS"]

autogpt_platform/backend/backend/blocks/agent.py

@@ -1,6 +1,5 @@
 import logging
-
-from autogpt_libs.utils.cache import thread_cached
+from typing import Any, Optional
 
 from backend.data.block import (
     Block,
@@ -12,36 +11,43 @@ from backend.data.block import (
     get_block,
 )
 from backend.data.execution import ExecutionStatus
-from backend.data.model import SchemaField
+from backend.data.model import CredentialsMetaInput, SchemaField
+from backend.util import json
 
 logger = logging.getLogger(__name__)
 
 
-@thread_cached
-def get_executor_manager_client():
-    from backend.executor import ExecutionManager
-    from backend.util.service import get_service_client
-
-    return get_service_client(ExecutionManager)
-
-
-@thread_cached
-def get_event_bus():
-    from backend.data.execution import RedisExecutionEventBus
-
-    return RedisExecutionEventBus()
-
-
 class AgentExecutorBlock(Block):
     class Input(BlockSchema):
         user_id: str = SchemaField(description="User ID")
         graph_id: str = SchemaField(description="Graph ID")
         graph_version: int = SchemaField(description="Graph Version")
 
-        data: BlockInput = SchemaField(description="Input data for the graph")
+        inputs: BlockInput = SchemaField(description="Input data for the graph")
         input_schema: dict = SchemaField(description="Input schema for the graph")
         output_schema: dict = SchemaField(description="Output schema for the graph")
 
+        node_credentials_input_map: Optional[
+            dict[str, dict[str, CredentialsMetaInput]]
+        ] = SchemaField(default=None, hidden=True)
+
+        @classmethod
+        def get_input_schema(cls, data: BlockInput) -> dict[str, Any]:
+            return data.get("input_schema", {})
+
+        @classmethod
+        def get_input_defaults(cls, data: BlockInput) -> BlockInput:
+            return data.get("inputs", {})
+
+        @classmethod
+        def get_missing_input(cls, data: BlockInput) -> set[str]:
+            required_fields = cls.get_input_schema(data).get("required", [])
+            return set(required_fields) - set(data)
+
+        @classmethod
+        def get_mismatch_error(cls, data: BlockInput) -> str | None:
+            return json.validate_with_jsonschema(cls.get_input_schema(data), data)
+
     class Output(BlockSchema):
         pass
 
@@ -56,26 +62,27 @@ class AgentExecutorBlock(Block):
         )
 
     def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        executor_manager = get_executor_manager_client()
-        event_bus = get_event_bus()
+        from backend.data.execution import ExecutionEventType
+        from backend.executor import utils as execution_utils
 
-        graph_exec = executor_manager.add_execution(
+        event_bus = execution_utils.get_execution_event_bus()
+
+        graph_exec = execution_utils.add_graph_execution(
             graph_id=input_data.graph_id,
             graph_version=input_data.graph_version,
             user_id=input_data.user_id,
-            data=input_data.data,
+            inputs=input_data.inputs,
+            node_credentials_input_map=input_data.node_credentials_input_map,
         )
-        log_id = f"Graph #{input_data.graph_id}-V{input_data.graph_version}, exec-id: {graph_exec.graph_exec_id}"
+        log_id = f"Graph #{input_data.graph_id}-V{input_data.graph_version}, exec-id: {graph_exec.id}"
         logger.info(f"Starting execution of {log_id}")
 
         for event in event_bus.listen(
-            graph_id=graph_exec.graph_id, graph_exec_id=graph_exec.graph_exec_id
+            user_id=graph_exec.user_id,
+            graph_id=graph_exec.graph_id,
+            graph_exec_id=graph_exec.id,
         ):
-            logger.info(
-                f"Execution {log_id} produced input {event.input_data} output {event.output_data}"
-            )
-
-            if not event.node_id:
+            if event.event_type == ExecutionEventType.GRAPH_EXEC_UPDATE:
                 if event.status in [
                     ExecutionStatus.COMPLETED,
                     ExecutionStatus.TERMINATED,
@@ -86,6 +93,10 @@ class AgentExecutorBlock(Block):
                 else:
                     continue
 
+            logger.debug(
+                f"Execution {log_id} produced input {event.input_data} output {event.output_data}"
+            )
+
             if not event.block_id:
                 logger.warning(f"{log_id} received event without block_id {event}")
                 continue
@@ -100,5 +111,7 @@ class AgentExecutorBlock(Block):
                 continue
 
             for output_data in event.output_data.get("output", []):
-                logger.info(f"Execution {log_id} produced {output_name}: {output_data}")
+                logger.debug(
+                    f"Execution {log_id} produced {output_name}: {output_data}"
+                )
                 yield output_name, output_data

autogpt_platform/backend/backend/blocks/ai_image_generator_block.py

@@ -1,8 +1,8 @@
 from enum import Enum
 from typing import Literal
 
-import replicate
 from pydantic import SecretStr
+from replicate.client import Client as ReplicateClient
 from replicate.helpers import FileOutput
 
 from backend.data.block import Block, BlockCategory, BlockSchema
@@ -170,7 +170,7 @@ class AIImageGeneratorBlock(Block):
     ):
         try:
             # Initialize Replicate client
-            client = replicate.Client(api_token=credentials.api_key.get_secret_value())
+            client = ReplicateClient(api_token=credentials.api_key.get_secret_value())
 
             # Run the model with input parameters
             output = client.run(model_name, input=input_params, wait=False)

autogpt_platform/backend/backend/blocks/ai_music_generator.py

@@ -3,8 +3,8 @@ import time
 from enum import Enum
 from typing import Literal
 
-import replicate
 from pydantic import SecretStr
+from replicate.client import Client as ReplicateClient
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import (
@@ -196,7 +196,7 @@ class AIMusicGeneratorBlock(Block):
         normalization_strategy: NormalizationStrategy,
     ):
         # Initialize Replicate client with the API key
-        client = replicate.Client(api_token=api_key.get_secret_value())
+        client = ReplicateClient(api_token=api_key.get_secret_value())
 
         # Run the model with parameters
         output = client.run(

autogpt_platform/backend/backend/blocks/apollo/_api.py

@@ -0,0 +1,108 @@
+import logging
+from typing import List
+
+from backend.blocks.apollo._auth import ApolloCredentials
+from backend.blocks.apollo.models import (
+    Contact,
+    Organization,
+    SearchOrganizationsRequest,
+    SearchOrganizationsResponse,
+    SearchPeopleRequest,
+    SearchPeopleResponse,
+)
+from backend.util.request import Requests
+
+logger = logging.getLogger(name=__name__)
+
+
+class ApolloClient:
+    """Client for the Apollo API"""
+
+    API_URL = "https://api.apollo.io/api/v1"
+
+    def __init__(self, credentials: ApolloCredentials):
+        self.credentials = credentials
+        self.requests = Requests()
+
+    def _get_headers(self) -> dict[str, str]:
+        return {"x-api-key": self.credentials.api_key.get_secret_value()}
+
+    def search_people(self, query: SearchPeopleRequest) -> List[Contact]:
+        """Search for people in Apollo"""
+        response = self.requests.get(
+            f"{self.API_URL}/mixed_people/search",
+            headers=self._get_headers(),
+            params=query.model_dump(exclude={"credentials", "max_results"}),
+        )
+        parsed_response = SearchPeopleResponse(**response.json())
+        if parsed_response.pagination.total_entries == 0:
+            return []
+
+        people = parsed_response.people
+
+        # handle pagination
+        if (
+            query.max_results is not None
+            and query.max_results < parsed_response.pagination.total_entries
+            and len(people) < query.max_results
+        ):
+            while (
+                len(people) < query.max_results
+                and query.page < parsed_response.pagination.total_pages
+                and len(parsed_response.people) > 0
+            ):
+                query.page += 1
+                response = self.requests.get(
+                    f"{self.API_URL}/mixed_people/search",
+                    headers=self._get_headers(),
+                    params=query.model_dump(exclude={"credentials", "max_results"}),
+                )
+                parsed_response = SearchPeopleResponse(**response.json())
+                people.extend(parsed_response.people[: query.max_results - len(people)])
+
+        logger.info(f"Found {len(people)} people")
+        return people[: query.max_results] if query.max_results else people
+
+    def search_organizations(
+        self, query: SearchOrganizationsRequest
+    ) -> List[Organization]:
+        """Search for organizations in Apollo"""
+        response = self.requests.get(
+            f"{self.API_URL}/mixed_companies/search",
+            headers=self._get_headers(),
+            params=query.model_dump(exclude={"credentials", "max_results"}),
+        )
+        parsed_response = SearchOrganizationsResponse(**response.json())
+        if parsed_response.pagination.total_entries == 0:
+            return []
+
+        organizations = parsed_response.organizations
+
+        # handle pagination
+        if (
+            query.max_results is not None
+            and query.max_results < parsed_response.pagination.total_entries
+            and len(organizations) < query.max_results
+        ):
+            while (
+                len(organizations) < query.max_results
+                and query.page < parsed_response.pagination.total_pages
+                and len(parsed_response.organizations) > 0
+            ):
+                query.page += 1
+                response = self.requests.get(
+                    f"{self.API_URL}/mixed_companies/search",
+                    headers=self._get_headers(),
+                    params=query.model_dump(exclude={"credentials", "max_results"}),
+                )
+                parsed_response = SearchOrganizationsResponse(**response.json())
+                organizations.extend(
+                    parsed_response.organizations[
+                        : query.max_results - len(organizations)
+                    ]
+                )
+
+        logger.info(f"Found {len(organizations)} organizations")
+        return (
+            organizations[: query.max_results] if query.max_results else organizations
+        )

autogpt_platform/backend/backend/blocks/apollo/_auth.py

@@ -0,0 +1,35 @@
+from typing import Literal
+
+from pydantic import SecretStr
+
+from backend.data.model import APIKeyCredentials, CredentialsField, CredentialsMetaInput
+from backend.integrations.providers import ProviderName
+
+ApolloCredentials = APIKeyCredentials
+ApolloCredentialsInput = CredentialsMetaInput[
+    Literal[ProviderName.APOLLO],
+    Literal["api_key"],
+]
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="apollo",
+    api_key=SecretStr("mock-apollo-api-key"),
+    title="Mock Apollo API key",
+    expires_at=None,
+)
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}
+
+
+def ApolloCredentialsField() -> ApolloCredentialsInput:
+    """
+    Creates a Apollo credentials input on a block.
+    """
+    return CredentialsField(
+        description="The Apollo integration can be used with an API Key.",
+    )

autogpt_platform/backend/backend/blocks/apollo/models.py

@@ -0,0 +1,548 @@
+from enum import Enum
+from typing import Any, Optional
+
+from pydantic import BaseModel, ConfigDict
+
+from backend.data.model import SchemaField
+
+
+class PrimaryPhone(BaseModel):
+    """A primary phone in Apollo"""
+
+    number: str
+    source: str
+    sanitized_number: str
+
+
+class SenorityLevels(str, Enum):
+    """Seniority levels in Apollo"""
+
+    OWNER = "owner"
+    FOUNDER = "founder"
+    C_SUITE = "c_suite"
+    PARTNER = "partner"
+    VP = "vp"
+    HEAD = "head"
+    DIRECTOR = "director"
+    MANAGER = "manager"
+    SENIOR = "senior"
+    ENTRY = "entry"
+    INTERN = "intern"
+
+
+class ContactEmailStatuses(str, Enum):
+    """Contact email statuses in Apollo"""
+
+    VERIFIED = "verified"
+    UNVERIFIED = "unverified"
+    LIKELY_TO_ENGAGE = "likely_to_engage"
+    UNAVAILABLE = "unavailable"
+
+
+class RuleConfigStatus(BaseModel):
+    """A rule config status in Apollo"""
+
+    _id: str
+    created_at: str
+    rule_action_config_id: str
+    rule_config_id: str
+    status_cd: str
+    updated_at: str
+    id: str
+    key: str
+
+
+class ContactCampaignStatus(BaseModel):
+    """A contact campaign status in Apollo"""
+
+    id: str
+    emailer_campaign_id: str
+    send_email_from_user_id: str
+    inactive_reason: str
+    status: str
+    added_at: str
+    added_by_user_id: str
+    finished_at: str
+    paused_at: str
+    auto_unpause_at: str
+    send_email_from_email_address: str
+    send_email_from_email_account_id: str
+    manually_set_unpause: str
+    failure_reason: str
+    current_step_id: str
+    in_response_to_emailer_message_id: str
+    cc_emails: str
+    bcc_emails: str
+    to_emails: str
+
+
+class Account(BaseModel):
+    """An account in Apollo"""
+
+    id: str
+    name: str
+    website_url: str
+    blog_url: str
+    angellist_url: str
+    linkedin_url: str
+    twitter_url: str
+    facebook_url: str
+    primary_phone: PrimaryPhone
+    languages: list[str]
+    alexa_ranking: int
+    phone: str
+    linkedin_uid: str
+    founded_year: int
+    publicly_traded_symbol: str
+    publicly_traded_exchange: str
+    logo_url: str
+    chrunchbase_url: str
+    primary_domain: str
+    domain: str
+    team_id: str
+    organization_id: str
+    account_stage_id: str
+    source: str
+    original_source: str
+    creator_id: str
+    owner_id: str
+    created_at: str
+    phone_status: str
+    hubspot_id: str
+    salesforce_id: str
+    crm_owner_id: str
+    parent_account_id: str
+    sanitized_phone: str
+    # no listed type on the API docs
+    account_playbook_statues: list[Any]
+    account_rule_config_statuses: list[RuleConfigStatus]
+    existence_level: str
+    label_ids: list[str]
+    typed_custom_fields: Any
+    custom_field_errors: Any
+    modality: str
+    source_display_name: str
+    salesforce_record_id: str
+    crm_record_url: str
+
+
+class ContactEmail(BaseModel):
+    """A contact email in Apollo"""
+
+    email: str = ""
+    email_md5: str = ""
+    email_sha256: str = ""
+    email_status: str = ""
+    email_source: str = ""
+    extrapolated_email_confidence: str = ""
+    position: int = 0
+    email_from_customer: str = ""
+    free_domain: bool = True
+
+
+class EmploymentHistory(BaseModel):
+    """An employment history in Apollo"""
+
+    model_config = ConfigDict(
+        extra="allow",
+        arbitrary_types_allowed=True,
+        from_attributes=True,
+        populate_by_name=True,
+    )
+
+    _id: Optional[str] = None
+    created_at: Optional[str] = None
+    current: Optional[bool] = None
+    degree: Optional[str] = None
+    description: Optional[str] = None
+    emails: Optional[str] = None
+    end_date: Optional[str] = None
+    grade_level: Optional[str] = None
+    kind: Optional[str] = None
+    major: Optional[str] = None
+    organization_id: Optional[str] = None
+    organization_name: Optional[str] = None
+    raw_address: Optional[str] = None
+    start_date: Optional[str] = None
+    title: Optional[str] = None
+    updated_at: Optional[str] = None
+    id: Optional[str] = None
+    key: Optional[str] = None
+
+
+class Breadcrumb(BaseModel):
+    """A breadcrumb in Apollo"""
+
+    label: Optional[str] = "N/A"
+    signal_field_name: Optional[str] = "N/A"
+    value: str | list | None = "N/A"
+    display_name: Optional[str] = "N/A"
+
+
+class TypedCustomField(BaseModel):
+    """A typed custom field in Apollo"""
+
+    id: Optional[str] = "N/A"
+    value: Optional[str] = "N/A"
+
+
+class Pagination(BaseModel):
+    """Pagination in Apollo"""
+
+    model_config = ConfigDict(
+        extra="allow",
+        arbitrary_types_allowed=True,
+        from_attributes=True,
+        populate_by_name=True,
+    )
+
+    page: int = 0
+    per_page: int = 0
+    total_entries: int = 0
+    total_pages: int = 0
+
+
+class DialerFlags(BaseModel):
+    """A dialer flags in Apollo"""
+
+    country_name: str
+    country_enabled: bool
+    high_risk_calling_enabled: bool
+    potential_high_risk_number: bool
+
+
+class PhoneNumber(BaseModel):
+    """A phone number in Apollo"""
+
+    raw_number: str = ""
+    sanitized_number: str = ""
+    type: str = ""
+    position: int = 0
+    status: str = ""
+    dnc_status: str = ""
+    dnc_other_info: str = ""
+    dailer_flags: DialerFlags = DialerFlags(
+        country_name="",
+        country_enabled=True,
+        high_risk_calling_enabled=True,
+        potential_high_risk_number=True,
+    )
+
+
+class Organization(BaseModel):
+    """An organization in Apollo"""
+
+    model_config = ConfigDict(
+        extra="allow",
+        arbitrary_types_allowed=True,
+        from_attributes=True,
+        populate_by_name=True,
+    )
+
+    id: Optional[str] = "N/A"
+    name: Optional[str] = "N/A"
+    website_url: Optional[str] = "N/A"
+    blog_url: Optional[str] = "N/A"
+    angellist_url: Optional[str] = "N/A"
+    linkedin_url: Optional[str] = "N/A"
+    twitter_url: Optional[str] = "N/A"
+    facebook_url: Optional[str] = "N/A"
+    primary_phone: Optional[PrimaryPhone] = PrimaryPhone(
+        number="N/A", source="N/A", sanitized_number="N/A"
+    )
+    languages: list[str] = []
+    alexa_ranking: Optional[int] = 0
+    phone: Optional[str] = "N/A"
+    linkedin_uid: Optional[str] = "N/A"
+    founded_year: Optional[int] = 0
+    publicly_traded_symbol: Optional[str] = "N/A"
+    publicly_traded_exchange: Optional[str] = "N/A"
+    logo_url: Optional[str] = "N/A"
+    chrunchbase_url: Optional[str] = "N/A"
+    primary_domain: Optional[str] = "N/A"
+    sanitized_phone: Optional[str] = "N/A"
+    owned_by_organization_id: Optional[str] = "N/A"
+    intent_strength: Optional[str] = "N/A"
+    show_intent: bool = True
+    has_intent_signal_account: Optional[bool] = True
+    intent_signal_account: Optional[str] = "N/A"
+
+
+class Contact(BaseModel):
+    """A contact in Apollo"""
+
+    model_config = ConfigDict(
+        extra="allow",
+        arbitrary_types_allowed=True,
+        from_attributes=True,
+        populate_by_name=True,
+    )
+
+    contact_roles: list[Any] = []
+    id: Optional[str] = None
+    first_name: Optional[str] = None
+    last_name: Optional[str] = None
+    name: Optional[str] = None
+    linkedin_url: Optional[str] = None
+    title: Optional[str] = None
+    contact_stage_id: Optional[str] = None
+    owner_id: Optional[str] = None
+    creator_id: Optional[str] = None
+    person_id: Optional[str] = None
+    email_needs_tickling: bool = True
+    organization_name: Optional[str] = None
+    source: Optional[str] = None
+    original_source: Optional[str] = None
+    organization_id: Optional[str] = None
+    headline: Optional[str] = None
+    photo_url: Optional[str] = None
+    present_raw_address: Optional[str] = None
+    linkededin_uid: Optional[str] = None
+    extrapolated_email_confidence: Optional[float] = None
+    salesforce_id: Optional[str] = None
+    salesforce_lead_id: Optional[str] = None
+    salesforce_contact_id: Optional[str] = None
+    saleforce_account_id: Optional[str] = None
+    crm_owner_id: Optional[str] = None
+    created_at: Optional[str] = None
+    emailer_campaign_ids: list[str] = []
+    direct_dial_status: Optional[str] = None
+    direct_dial_enrichment_failed_at: Optional[str] = None
+    email_status: Optional[str] = None
+    email_source: Optional[str] = None
+    account_id: Optional[str] = None
+    last_activity_date: Optional[str] = None
+    hubspot_vid: Optional[str] = None
+    hubspot_company_id: Optional[str] = None
+    crm_id: Optional[str] = None
+    sanitized_phone: Optional[str] = None
+    merged_crm_ids: Optional[str] = None
+    updated_at: Optional[str] = None
+    queued_for_crm_push: bool = True
+    suggested_from_rule_engine_config_id: Optional[str] = None
+    email_unsubscribed: Optional[str] = None
+    label_ids: list[Any] = []
+    has_pending_email_arcgate_request: bool = True
+    has_email_arcgate_request: bool = True
+    existence_level: Optional[str] = None
+    email: Optional[str] = None
+    email_from_customer: Optional[str] = None
+    typed_custom_fields: list[TypedCustomField] = []
+    custom_field_errors: Any = None
+    salesforce_record_id: Optional[str] = None
+    crm_record_url: Optional[str] = None
+    email_status_unavailable_reason: Optional[str] = None
+    email_true_status: Optional[str] = None
+    updated_email_true_status: bool = True
+    contact_rule_config_statuses: list[RuleConfigStatus] = []
+    source_display_name: Optional[str] = None
+    twitter_url: Optional[str] = None
+    contact_campaign_statuses: list[ContactCampaignStatus] = []
+    state: Optional[str] = None
+    city: Optional[str] = None
+    country: Optional[str] = None
+    account: Optional[Account] = None
+    contact_emails: list[ContactEmail] = []
+    organization: Optional[Organization] = None
+    employment_history: list[EmploymentHistory] = []
+    time_zone: Optional[str] = None
+    intent_strength: Optional[str] = None
+    show_intent: bool = True
+    phone_numbers: list[PhoneNumber] = []
+    account_phone_note: Optional[str] = None
+    free_domain: bool = True
+    is_likely_to_engage: bool = True
+    email_domain_catchall: bool = True
+    contact_job_change_event: Optional[str] = None
+
+
+class SearchOrganizationsRequest(BaseModel):
+    """Request for Apollo's search organizations API"""
+
+    organization_num_empoloyees_range: list[int] = SchemaField(
+        description="""The number range of employees working for the company. This enables you to find companies based on headcount. You can add multiple ranges to expand your search results.
+
+Each range you add needs to be a string, with the upper and lower numbers of the range separated only by a comma.""",
+        default=[0, 1000000],
+    )
+
+    organization_locations: list[str] = SchemaField(
+        description="""The location of the company headquarters. You can search across cities, US states, and countries.
+
+If a company has several office locations, results are still based on the headquarters location. For example, if you search chicago but a company's HQ location is in boston, any Boston-based companies will not appearch in your search results, even if they match other parameters.
+
+To exclude companies based on location, use the organization_not_locations parameter.
+""",
+        default_factory=list,
+    )
+    organizations_not_locations: list[str] = SchemaField(
+        description="""Exclude companies from search results based on the location of the company headquarters. You can use cities, US states, and countries as locations to exclude.
+
+This parameter is useful for ensuring you do not prospect in an undesirable territory. For example, if you use ireland as a value, no Ireland-based companies will appear in your search results.
+""",
+        default_factory=list,
+    )
+    q_organization_keyword_tags: list[str] = SchemaField(
+        description="""Filter search results based on keywords associated with companies. For example, you can enter mining as a value to return only companies that have an association with the mining industry."""
+    )
+    q_organization_name: str = SchemaField(
+        description="""Filter search results to include a specific company name.
+
+If the value you enter for this parameter does not match with a company's name, the company will not appear in search results, even if it matches other parameters. Partial matches are accepted. For example, if you filter by the value marketing, a company called NY Marketing Unlimited would still be eligible as a search result, but NY Market Analysis would not be eligible."""
+    )
+    organization_ids: list[str] = SchemaField(
+        description="""The Apollo IDs for the companies you want to include in your search results. Each company in the Apollo database is assigned a unique ID.
+
+To find IDs, identify the values for organization_id when you call this endpoint.""",
+        default_factory=list,
+    )
+    max_results: int = SchemaField(
+        description="""The maximum number of results to return. If you don't specify this parameter, the default is 100.""",
+        default=100,
+        ge=1,
+        le=50000,
+        advanced=True,
+    )
+
+    page: int = SchemaField(
+        description="""The page number of the Apollo data that you want to retrieve.
+
+Use this parameter in combination with the per_page parameter to make search results for navigable and improve the performance of the endpoint.""",
+        default=1,
+    )
+    per_page: int = SchemaField(
+        description="""The number of search results that should be returned for each page. Limited the number of results per page improves the endpoint's performance.
+
+Use the page parameter to search the different pages of data.""",
+        default=100,
+    )
+
+
+class SearchOrganizationsResponse(BaseModel):
+    """Response from Apollo's search organizations API"""
+
+    breadcrumbs: list[Breadcrumb] = []
+    partial_results_only: bool = True
+    has_join: bool = True
+    disable_eu_prospecting: bool = True
+    partial_results_limit: int = 0
+    pagination: Pagination = Pagination(
+        page=0, per_page=0, total_entries=0, total_pages=0
+    )
+    # no listed type on the API docs
+    accounts: list[Any] = []
+    organizations: list[Organization] = []
+    models_ids: list[str] = []
+    num_fetch_result: Optional[str] = "N/A"
+    derived_params: Optional[str] = "N/A"
+
+
+class SearchPeopleRequest(BaseModel):
+    """Request for Apollo's search people API"""
+
+    person_titles: list[str] = SchemaField(
+        description="""Job titles held by the people you want to find. For a person to be included in search results, they only need to match 1 of the job titles you add. Adding more job titles expands your search results.
+
+Results also include job titles with the same terms, even if they are not exact matches. For example, searching for marketing manager might return people with the job title content marketing manager.
+
+Use this parameter in combination with the person_seniorities[] parameter to find people based on specific job functions and seniority levels.
+""",
+        default_factory=list,
+        placeholder="marketing manager",
+    )
+    person_locations: list[str] = SchemaField(
+        description="""The location where people live. You can search across cities, US states, and countries.
+
+To find people based on the headquarters locations of their current employer, use the organization_locations parameter.""",
+        default_factory=list,
+    )
+    person_seniorities: list[SenorityLevels] = SchemaField(
+        description="""The job seniority that people hold within their current employer. This enables you to find people that currently hold positions at certain reporting levels, such as Director level or senior IC level.
+
+For a person to be included in search results, they only need to match 1 of the seniorities you add. Adding more seniorities expands your search results.
+
+Searches only return results based on their current job title, so searching for Director-level employees only returns people that currently hold a Director-level title. If someone was previously a Director, but is currently a VP, they would not be included in your search results.
+
+Use this parameter in combination with the person_titles[] parameter to find people based on specific job functions and seniority levels.""",
+        default_factory=list,
+    )
+    organization_locations: list[str] = SchemaField(
+        description="""The location of the company headquarters for a person's current employer. You can search across cities, US states, and countries.
+
+If a company has several office locations, results are still based on the headquarters location. For example, if you search chicago but a company's HQ location is in boston, people that work for the Boston-based company will not appear in your results, even if they match other parameters.
+
+To find people based on their personal location, use the person_locations parameter.""",
+        default_factory=list,
+    )
+    q_organization_domains: list[str] = SchemaField(
+        description="""The domain name for the person's employer. This can be the current employer or a previous employer. Do not include www., the @ symbol, or similar.
+
+You can add multiple domains to search across companies.
+
+  Examples: apollo.io and microsoft.com""",
+        default_factory=list,
+    )
+    contact_email_statuses: list[ContactEmailStatuses] = SchemaField(
+        description="""The email statuses for the people you want to find. You can add multiple statuses to expand your search.""",
+        default_factory=list,
+    )
+    organization_ids: list[str] = SchemaField(
+        description="""The Apollo IDs for the companies (employers) you want to include in your search results. Each company in the Apollo database is assigned a unique ID.
+
+To find IDs, call the Organization Search endpoint and identify the values for organization_id.""",
+        default_factory=list,
+    )
+    organization_num_empoloyees_range: list[int] = SchemaField(
+        description="""The number range of employees working for the company. This enables you to find companies based on headcount. You can add multiple ranges to expand your search results.
+
+Each range you add needs to be a string, with the upper and lower numbers of the range separated only by a comma.""",
+        default_factory=list,
+    )
+    q_keywords: str = SchemaField(
+        description="""A string of words over which we want to filter the results""",
+        default="",
+    )
+    page: int = SchemaField(
+        description="""The page number of the Apollo data that you want to retrieve.
+
+Use this parameter in combination with the per_page parameter to make search results for navigable and improve the performance of the endpoint.""",
+        default=1,
+    )
+    per_page: int = SchemaField(
+        description="""The number of search results that should be returned for each page. Limited the number of results per page improves the endpoint's performance.
+
+Use the page parameter to search the different pages of data.""",
+        default=100,
+    )
+    max_results: int = SchemaField(
+        description="""The maximum number of results to return. If you don't specify this parameter, the default is 100.""",
+        default=100,
+        ge=1,
+        le=50000,
+        advanced=True,
+    )
+
+
+class SearchPeopleResponse(BaseModel):
+    """Response from Apollo's search people API"""
+
+    model_config = ConfigDict(
+        extra="allow",
+        arbitrary_types_allowed=True,
+        from_attributes=True,
+        populate_by_name=True,
+    )
+
+    breadcrumbs: list[Breadcrumb] = []
+    partial_results_only: bool = True
+    has_join: bool = True
+    disable_eu_prospecting: bool = True
+    partial_results_limit: int = 0
+    pagination: Pagination = Pagination(
+        page=0, per_page=0, total_entries=0, total_pages=0
+    )
+    contacts: list[Contact] = []
+    people: list[Contact] = []
+    model_ids: list[str] = []
+    num_fetch_result: Optional[str] = "N/A"
+    derived_params: Optional[str] = "N/A"

autogpt_platform/backend/backend/blocks/apollo/organization.py

@@ -0,0 +1,219 @@
+from backend.blocks.apollo._api import ApolloClient
+from backend.blocks.apollo._auth import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    ApolloCredentials,
+    ApolloCredentialsInput,
+)
+from backend.blocks.apollo.models import (
+    Organization,
+    PrimaryPhone,
+    SearchOrganizationsRequest,
+)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+
+
+class SearchOrganizationsBlock(Block):
+    """Search for organizations in Apollo"""
+
+    class Input(BlockSchema):
+        organization_num_empoloyees_range: list[int] = SchemaField(
+            description="""The number range of employees working for the company. This enables you to find companies based on headcount. You can add multiple ranges to expand your search results.
+
+Each range you add needs to be a string, with the upper and lower numbers of the range separated only by a comma.""",
+            default=[0, 1000000],
+        )
+
+        organization_locations: list[str] = SchemaField(
+            description="""The location of the company headquarters. You can search across cities, US states, and countries.
+
+If a company has several office locations, results are still based on the headquarters location. For example, if you search chicago but a company's HQ location is in boston, any Boston-based companies will not appearch in your search results, even if they match other parameters.
+
+To exclude companies based on location, use the organization_not_locations parameter.
+""",
+            default_factory=list,
+        )
+        organizations_not_locations: list[str] = SchemaField(
+            description="""Exclude companies from search results based on the location of the company headquarters. You can use cities, US states, and countries as locations to exclude.
+
+This parameter is useful for ensuring you do not prospect in an undesirable territory. For example, if you use ireland as a value, no Ireland-based companies will appear in your search results.
+""",
+            default_factory=list,
+        )
+        q_organization_keyword_tags: list[str] = SchemaField(
+            description="""Filter search results based on keywords associated with companies. For example, you can enter mining as a value to return only companies that have an association with the mining industry.""",
+            default_factory=list,
+        )
+        q_organization_name: str = SchemaField(
+            description="""Filter search results to include a specific company name.
+
+If the value you enter for this parameter does not match with a company's name, the company will not appear in search results, even if it matches other parameters. Partial matches are accepted. For example, if you filter by the value marketing, a company called NY Marketing Unlimited would still be eligible as a search result, but NY Market Analysis would not be eligible.""",
+            default="",
+            advanced=False,
+        )
+        organization_ids: list[str] = SchemaField(
+            description="""The Apollo IDs for the companies you want to include in your search results. Each company in the Apollo database is assigned a unique ID.
+
+To find IDs, identify the values for organization_id when you call this endpoint.""",
+            default_factory=list,
+        )
+        max_results: int = SchemaField(
+            description="""The maximum number of results to return. If you don't specify this parameter, the default is 100.""",
+            default=100,
+            ge=1,
+            le=50000,
+            advanced=True,
+        )
+        credentials: ApolloCredentialsInput = SchemaField(
+            description="Apollo credentials",
+        )
+
+    class Output(BlockSchema):
+        organizations: list[Organization] = SchemaField(
+            description="List of organizations found",
+            default_factory=list,
+        )
+        organization: Organization = SchemaField(
+            description="Each found organization, one at a time",
+        )
+        error: str = SchemaField(
+            description="Error message if the search failed",
+            default="",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="3d71270d-599e-4148-9b95-71b35d2f44f0",
+            description="Search for organizations in Apollo",
+            categories={BlockCategory.SEARCH},
+            input_schema=SearchOrganizationsBlock.Input,
+            output_schema=SearchOrganizationsBlock.Output,
+            test_credentials=TEST_CREDENTIALS,
+            test_input={"query": "Google", "credentials": TEST_CREDENTIALS_INPUT},
+            test_output=[
+                (
+                    "organization",
+                    Organization(
+                        id="1",
+                        name="Google",
+                        website_url="https://google.com",
+                        blog_url="https://google.com/blog",
+                        angellist_url="https://angel.co/google",
+                        linkedin_url="https://linkedin.com/company/google",
+                        twitter_url="https://twitter.com/google",
+                        facebook_url="https://facebook.com/google",
+                        primary_phone=PrimaryPhone(
+                            source="google",
+                            number="1234567890",
+                            sanitized_number="1234567890",
+                        ),
+                        languages=["en"],
+                        alexa_ranking=1000,
+                        phone="1234567890",
+                        linkedin_uid="1234567890",
+                        founded_year=2000,
+                        publicly_traded_symbol="GOOGL",
+                        publicly_traded_exchange="NASDAQ",
+                        logo_url="https://google.com/logo.png",
+                        chrunchbase_url="https://chrunchbase.com/google",
+                        primary_domain="google.com",
+                        sanitized_phone="1234567890",
+                        owned_by_organization_id="1",
+                        intent_strength="strong",
+                        show_intent=True,
+                        has_intent_signal_account=True,
+                        intent_signal_account="1",
+                    ),
+                ),
+                (
+                    "organizations",
+                    [
+                        Organization(
+                            id="1",
+                            name="Google",
+                            website_url="https://google.com",
+                            blog_url="https://google.com/blog",
+                            angellist_url="https://angel.co/google",
+                            linkedin_url="https://linkedin.com/company/google",
+                            twitter_url="https://twitter.com/google",
+                            facebook_url="https://facebook.com/google",
+                            primary_phone=PrimaryPhone(
+                                source="google",
+                                number="1234567890",
+                                sanitized_number="1234567890",
+                            ),
+                            languages=["en"],
+                            alexa_ranking=1000,
+                            phone="1234567890",
+                            linkedin_uid="1234567890",
+                            founded_year=2000,
+                            publicly_traded_symbol="GOOGL",
+                            publicly_traded_exchange="NASDAQ",
+                            logo_url="https://google.com/logo.png",
+                            chrunchbase_url="https://chrunchbase.com/google",
+                            primary_domain="google.com",
+                            sanitized_phone="1234567890",
+                            owned_by_organization_id="1",
+                            intent_strength="strong",
+                            show_intent=True,
+                            has_intent_signal_account=True,
+                            intent_signal_account="1",
+                        ),
+                    ],
+                ),
+            ],
+            test_mock={
+                "search_organizations": lambda *args, **kwargs: [
+                    Organization(
+                        id="1",
+                        name="Google",
+                        website_url="https://google.com",
+                        blog_url="https://google.com/blog",
+                        angellist_url="https://angel.co/google",
+                        linkedin_url="https://linkedin.com/company/google",
+                        twitter_url="https://twitter.com/google",
+                        facebook_url="https://facebook.com/google",
+                        primary_phone=PrimaryPhone(
+                            source="google",
+                            number="1234567890",
+                            sanitized_number="1234567890",
+                        ),
+                        languages=["en"],
+                        alexa_ranking=1000,
+                        phone="1234567890",
+                        linkedin_uid="1234567890",
+                        founded_year=2000,
+                        publicly_traded_symbol="GOOGL",
+                        publicly_traded_exchange="NASDAQ",
+                        logo_url="https://google.com/logo.png",
+                        chrunchbase_url="https://chrunchbase.com/google",
+                        primary_domain="google.com",
+                        sanitized_phone="1234567890",
+                        owned_by_organization_id="1",
+                        intent_strength="strong",
+                        show_intent=True,
+                        has_intent_signal_account=True,
+                        intent_signal_account="1",
+                    )
+                ]
+            },
+        )
+
+    @staticmethod
+    def search_organizations(
+        query: SearchOrganizationsRequest, credentials: ApolloCredentials
+    ) -> list[Organization]:
+        client = ApolloClient(credentials)
+        return client.search_organizations(query)
+
+    def run(
+        self, input_data: Input, *, credentials: ApolloCredentials, **kwargs
+    ) -> BlockOutput:
+        query = SearchOrganizationsRequest(
+            **input_data.model_dump(exclude={"credentials"})
+        )
+        organizations = self.search_organizations(query, credentials)
+        for organization in organizations:
+            yield "organization", organization
+        yield "organizations", organizations

autogpt_platform/backend/backend/blocks/apollo/people.py

@@ -0,0 +1,394 @@
+from backend.blocks.apollo._api import ApolloClient
+from backend.blocks.apollo._auth import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    ApolloCredentials,
+    ApolloCredentialsInput,
+)
+from backend.blocks.apollo.models import (
+    Contact,
+    ContactEmailStatuses,
+    SearchPeopleRequest,
+    SenorityLevels,
+)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+
+
+class SearchPeopleBlock(Block):
+    """Search for people in Apollo"""
+
+    class Input(BlockSchema):
+        person_titles: list[str] = SchemaField(
+            description="""Job titles held by the people you want to find. For a person to be included in search results, they only need to match 1 of the job titles you add. Adding more job titles expands your search results.
+
+        Results also include job titles with the same terms, even if they are not exact matches. For example, searching for marketing manager might return people with the job title content marketing manager.
+
+        Use this parameter in combination with the person_seniorities[] parameter to find people based on specific job functions and seniority levels.
+        """,
+            default_factory=list,
+            advanced=False,
+        )
+        person_locations: list[str] = SchemaField(
+            description="""The location where people live. You can search across cities, US states, and countries.
+
+        To find people based on the headquarters locations of their current employer, use the organization_locations parameter.""",
+            default_factory=list,
+            advanced=False,
+        )
+        person_seniorities: list[SenorityLevels] = SchemaField(
+            description="""The job seniority that people hold within their current employer. This enables you to find people that currently hold positions at certain reporting levels, such as Director level or senior IC level.
+
+        For a person to be included in search results, they only need to match 1 of the seniorities you add. Adding more seniorities expands your search results.
+
+        Searches only return results based on their current job title, so searching for Director-level employees only returns people that currently hold a Director-level title. If someone was previously a Director, but is currently a VP, they would not be included in your search results.
+
+        Use this parameter in combination with the person_titles[] parameter to find people based on specific job functions and seniority levels.""",
+            default_factory=list,
+            advanced=False,
+        )
+        organization_locations: list[str] = SchemaField(
+            description="""The location of the company headquarters for a person's current employer. You can search across cities, US states, and countries.
+
+        If a company has several office locations, results are still based on the headquarters location. For example, if you search chicago but a company's HQ location is in boston, people that work for the Boston-based company will not appear in your results, even if they match other parameters.
+
+        To find people based on their personal location, use the person_locations parameter.""",
+            default_factory=list,
+            advanced=False,
+        )
+        q_organization_domains: list[str] = SchemaField(
+            description="""The domain name for the person's employer. This can be the current employer or a previous employer. Do not include www., the @ symbol, or similar.
+
+        You can add multiple domains to search across companies.
+
+          Examples: apollo.io and microsoft.com""",
+            default_factory=list,
+            advanced=False,
+        )
+        contact_email_statuses: list[ContactEmailStatuses] = SchemaField(
+            description="""The email statuses for the people you want to find. You can add multiple statuses to expand your search.""",
+            default_factory=list,
+            advanced=False,
+        )
+        organization_ids: list[str] = SchemaField(
+            description="""The Apollo IDs for the companies (employers) you want to include in your search results. Each company in the Apollo database is assigned a unique ID.
+
+        To find IDs, call the Organization Search endpoint and identify the values for organization_id.""",
+            default_factory=list,
+            advanced=False,
+        )
+        organization_num_empoloyees_range: list[int] = SchemaField(
+            description="""The number range of employees working for the company. This enables you to find companies based on headcount. You can add multiple ranges to expand your search results.
+
+        Each range you add needs to be a string, with the upper and lower numbers of the range separated only by a comma.""",
+            default_factory=list,
+            advanced=False,
+        )
+        q_keywords: str = SchemaField(
+            description="""A string of words over which we want to filter the results""",
+            default="",
+            advanced=False,
+        )
+        max_results: int = SchemaField(
+            description="""The maximum number of results to return. If you don't specify this parameter, the default is 100.""",
+            default=100,
+            ge=1,
+            le=50000,
+            advanced=True,
+        )
+
+        credentials: ApolloCredentialsInput = SchemaField(
+            description="Apollo credentials",
+        )
+
+    class Output(BlockSchema):
+        people: list[Contact] = SchemaField(
+            description="List of people found",
+            default_factory=list,
+        )
+        person: Contact = SchemaField(
+            description="Each found person, one at a time",
+        )
+        error: str = SchemaField(
+            description="Error message if the search failed",
+            default="",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="c2adb3aa-5aae-488d-8a6e-4eb8c23e2ed6",
+            description="Search for people in Apollo",
+            categories={BlockCategory.SEARCH},
+            input_schema=SearchPeopleBlock.Input,
+            output_schema=SearchPeopleBlock.Output,
+            test_credentials=TEST_CREDENTIALS,
+            test_input={"credentials": TEST_CREDENTIALS_INPUT},
+            test_output=[
+                (
+                    "person",
+                    Contact(
+                        contact_roles=[],
+                        id="1",
+                        name="John Doe",
+                        first_name="John",
+                        last_name="Doe",
+                        linkedin_url="https://www.linkedin.com/in/johndoe",
+                        title="Software Engineer",
+                        organization_name="Google",
+                        organization_id="123456",
+                        contact_stage_id="1",
+                        owner_id="1",
+                        creator_id="1",
+                        person_id="1",
+                        email_needs_tickling=True,
+                        source="apollo",
+                        original_source="apollo",
+                        headline="Software Engineer",
+                        photo_url="https://www.linkedin.com/in/johndoe",
+                        present_raw_address="123 Main St, Anytown, USA",
+                        linkededin_uid="123456",
+                        extrapolated_email_confidence=0.8,
+                        salesforce_id="123456",
+                        salesforce_lead_id="123456",
+                        salesforce_contact_id="123456",
+                        saleforce_account_id="123456",
+                        crm_owner_id="123456",
+                        created_at="2021-01-01",
+                        emailer_campaign_ids=[],
+                        direct_dial_status="active",
+                        direct_dial_enrichment_failed_at="2021-01-01",
+                        email_status="active",
+                        email_source="apollo",
+                        account_id="123456",
+                        last_activity_date="2021-01-01",
+                        hubspot_vid="123456",
+                        hubspot_company_id="123456",
+                        crm_id="123456",
+                        sanitized_phone="123456",
+                        merged_crm_ids="123456",
+                        updated_at="2021-01-01",
+                        queued_for_crm_push=True,
+                        suggested_from_rule_engine_config_id="123456",
+                        email_unsubscribed=None,
+                        label_ids=[],
+                        has_pending_email_arcgate_request=True,
+                        has_email_arcgate_request=True,
+                        existence_level=None,
+                        email=None,
+                        email_from_customer=None,
+                        typed_custom_fields=[],
+                        custom_field_errors=None,
+                        salesforce_record_id=None,
+                        crm_record_url=None,
+                        email_status_unavailable_reason=None,
+                        email_true_status=None,
+                        updated_email_true_status=True,
+                        contact_rule_config_statuses=[],
+                        source_display_name=None,
+                        twitter_url=None,
+                        contact_campaign_statuses=[],
+                        state=None,
+                        city=None,
+                        country=None,
+                        account=None,
+                        contact_emails=[],
+                        organization=None,
+                        employment_history=[],
+                        time_zone=None,
+                        intent_strength=None,
+                        show_intent=True,
+                        phone_numbers=[],
+                        account_phone_note=None,
+                        free_domain=True,
+                        is_likely_to_engage=True,
+                        email_domain_catchall=True,
+                        contact_job_change_event=None,
+                    ),
+                ),
+                (
+                    "people",
+                    [
+                        Contact(
+                            contact_roles=[],
+                            id="1",
+                            name="John Doe",
+                            first_name="John",
+                            last_name="Doe",
+                            linkedin_url="https://www.linkedin.com/in/johndoe",
+                            title="Software Engineer",
+                            organization_name="Google",
+                            organization_id="123456",
+                            contact_stage_id="1",
+                            owner_id="1",
+                            creator_id="1",
+                            person_id="1",
+                            email_needs_tickling=True,
+                            source="apollo",
+                            original_source="apollo",
+                            headline="Software Engineer",
+                            photo_url="https://www.linkedin.com/in/johndoe",
+                            present_raw_address="123 Main St, Anytown, USA",
+                            linkededin_uid="123456",
+                            extrapolated_email_confidence=0.8,
+                            salesforce_id="123456",
+                            salesforce_lead_id="123456",
+                            salesforce_contact_id="123456",
+                            saleforce_account_id="123456",
+                            crm_owner_id="123456",
+                            created_at="2021-01-01",
+                            emailer_campaign_ids=[],
+                            direct_dial_status="active",
+                            direct_dial_enrichment_failed_at="2021-01-01",
+                            email_status="active",
+                            email_source="apollo",
+                            account_id="123456",
+                            last_activity_date="2021-01-01",
+                            hubspot_vid="123456",
+                            hubspot_company_id="123456",
+                            crm_id="123456",
+                            sanitized_phone="123456",
+                            merged_crm_ids="123456",
+                            updated_at="2021-01-01",
+                            queued_for_crm_push=True,
+                            suggested_from_rule_engine_config_id="123456",
+                            email_unsubscribed=None,
+                            label_ids=[],
+                            has_pending_email_arcgate_request=True,
+                            has_email_arcgate_request=True,
+                            existence_level=None,
+                            email=None,
+                            email_from_customer=None,
+                            typed_custom_fields=[],
+                            custom_field_errors=None,
+                            salesforce_record_id=None,
+                            crm_record_url=None,
+                            email_status_unavailable_reason=None,
+                            email_true_status=None,
+                            updated_email_true_status=True,
+                            contact_rule_config_statuses=[],
+                            source_display_name=None,
+                            twitter_url=None,
+                            contact_campaign_statuses=[],
+                            state=None,
+                            city=None,
+                            country=None,
+                            account=None,
+                            contact_emails=[],
+                            organization=None,
+                            employment_history=[],
+                            time_zone=None,
+                            intent_strength=None,
+                            show_intent=True,
+                            phone_numbers=[],
+                            account_phone_note=None,
+                            free_domain=True,
+                            is_likely_to_engage=True,
+                            email_domain_catchall=True,
+                            contact_job_change_event=None,
+                        ),
+                    ],
+                ),
+            ],
+            test_mock={
+                "search_people": lambda query, credentials: [
+                    Contact(
+                        id="1",
+                        name="John Doe",
+                        first_name="John",
+                        last_name="Doe",
+                        linkedin_url="https://www.linkedin.com/in/johndoe",
+                        title="Software Engineer",
+                        organization_name="Google",
+                        organization_id="123456",
+                        contact_stage_id="1",
+                        owner_id="1",
+                        creator_id="1",
+                        person_id="1",
+                        email_needs_tickling=True,
+                        source="apollo",
+                        original_source="apollo",
+                        headline="Software Engineer",
+                        photo_url="https://www.linkedin.com/in/johndoe",
+                        present_raw_address="123 Main St, Anytown, USA",
+                        linkededin_uid="123456",
+                        extrapolated_email_confidence=0.8,
+                        salesforce_id="123456",
+                        salesforce_lead_id="123456",
+                        salesforce_contact_id="123456",
+                        saleforce_account_id="123456",
+                        crm_owner_id="123456",
+                        created_at="2021-01-01",
+                        emailer_campaign_ids=[],
+                        direct_dial_status="active",
+                        direct_dial_enrichment_failed_at="2021-01-01",
+                        email_status="active",
+                        email_source="apollo",
+                        account_id="123456",
+                        last_activity_date="2021-01-01",
+                        hubspot_vid="123456",
+                        hubspot_company_id="123456",
+                        crm_id="123456",
+                        sanitized_phone="123456",
+                        merged_crm_ids="123456",
+                        updated_at="2021-01-01",
+                        queued_for_crm_push=True,
+                        suggested_from_rule_engine_config_id="123456",
+                        email_unsubscribed=None,
+                        label_ids=[],
+                        has_pending_email_arcgate_request=True,
+                        has_email_arcgate_request=True,
+                        existence_level=None,
+                        email=None,
+                        email_from_customer=None,
+                        typed_custom_fields=[],
+                        custom_field_errors=None,
+                        salesforce_record_id=None,
+                        crm_record_url=None,
+                        email_status_unavailable_reason=None,
+                        email_true_status=None,
+                        updated_email_true_status=True,
+                        contact_rule_config_statuses=[],
+                        source_display_name=None,
+                        twitter_url=None,
+                        contact_campaign_statuses=[],
+                        state=None,
+                        city=None,
+                        country=None,
+                        account=None,
+                        contact_emails=[],
+                        organization=None,
+                        employment_history=[],
+                        time_zone=None,
+                        intent_strength=None,
+                        show_intent=True,
+                        phone_numbers=[],
+                        account_phone_note=None,
+                        free_domain=True,
+                        is_likely_to_engage=True,
+                        email_domain_catchall=True,
+                        contact_job_change_event=None,
+                    ),
+                ]
+            },
+        )
+
+    @staticmethod
+    def search_people(
+        query: SearchPeopleRequest, credentials: ApolloCredentials
+    ) -> list[Contact]:
+        client = ApolloClient(credentials)
+        return client.search_people(query)
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: ApolloCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+
+        query = SearchPeopleRequest(**input_data.model_dump(exclude={"credentials"}))
+        people = self.search_people(query, credentials)
+        for person in people:
+            yield "person", person
+        yield "people", people

autogpt_platform/backend/backend/blocks/basic.py

@@ -3,22 +3,20 @@ from typing import Any, List
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema, BlockType
 from backend.data.model import SchemaField
-from backend.util.file import MediaFile, store_media_file
+from backend.util import json
+from backend.util.file import store_media_file
 from backend.util.mock import MockObject
-from backend.util.text import TextFormatter
-from backend.util.type import convert
-
-formatter = TextFormatter()
+from backend.util.type import MediaFileType, convert
 
 
 class FileStoreBlock(Block):
     class Input(BlockSchema):
-        file_in: MediaFile = SchemaField(
+        file_in: MediaFileType = SchemaField(
             description="The file to store in the temporary directory, it can be a URL, data URI, or local path."
         )
 
     class Output(BlockSchema):
-        file_out: MediaFile = SchemaField(
+        file_out: MediaFileType = SchemaField(
             description="The relative path to the stored file in the temporary directory."
         )
 
@@ -92,9 +90,10 @@ class StoreValueBlock(Block):
 
 class PrintToConsoleBlock(Block):
     class Input(BlockSchema):
-        text: str = SchemaField(description="The text to print to the console.")
+        text: Any = SchemaField(description="The data to print to the console.")
 
     class Output(BlockSchema):
+        output: Any = SchemaField(description="The data printed to the console.")
         status: str = SchemaField(description="The status of the print operation.")
 
     def __init__(self):
@@ -105,11 +104,14 @@ class PrintToConsoleBlock(Block):
             input_schema=PrintToConsoleBlock.Input,
             output_schema=PrintToConsoleBlock.Output,
             test_input={"text": "Hello, World!"},
-            test_output=("status", "printed"),
+            test_output=[
+                ("output", "Hello, World!"),
+                ("status", "printed"),
+            ],
         )
 
     def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        print(">>>>> Print: ", input_data.text)
+        yield "output", input_data.text
         yield "status", "printed"
 
 
@@ -153,6 +155,9 @@ class FindInDictionaryBlock(Block):
         obj = input_data.input
         key = input_data.key
 
+        if isinstance(obj, str):
+            obj = json.loads(obj)
+
         if isinstance(obj, dict) and key in obj:
             yield "output", obj[key]
         elif isinstance(obj, list) and isinstance(key, int) and 0 <= key < len(obj):
@@ -170,192 +175,10 @@ class FindInDictionaryBlock(Block):
             yield "missing", input_data.input
 
 
-class AgentInputBlock(Block):
-    """
-    This block is used to provide input to the graph.
-
-    It takes in a value, name, description, default values list and bool to limit selection to default values.
-
-    It Outputs the value passed as input.
-    """
-
-    class Input(BlockSchema):
-        name: str = SchemaField(description="The name of the input.")
-        value: Any = SchemaField(
-            description="The value to be passed as input.",
-            default=None,
-        )
-        title: str | None = SchemaField(
-            description="The title of the input.", default=None, advanced=True
-        )
-        description: str | None = SchemaField(
-            description="The description of the input.",
-            default=None,
-            advanced=True,
-        )
-        placeholder_values: List[Any] = SchemaField(
-            description="The placeholder values to be passed as input.",
-            default=[],
-            advanced=True,
-        )
-        limit_to_placeholder_values: bool = SchemaField(
-            description="Whether to limit the selection to placeholder values.",
-            default=False,
-            advanced=True,
-        )
-        advanced: bool = SchemaField(
-            description="Whether to show the input in the advanced section, if the field is not required.",
-            default=False,
-            advanced=True,
-        )
-        secret: bool = SchemaField(
-            description="Whether the input should be treated as a secret.",
-            default=False,
-            advanced=True,
-        )
-
-    class Output(BlockSchema):
-        result: Any = SchemaField(description="The value passed as input.")
-
-    def __init__(self):
-        super().__init__(
-            id="c0a8e994-ebf1-4a9c-a4d8-89d09c86741b",
-            description="This block is used to provide input to the graph.",
-            input_schema=AgentInputBlock.Input,
-            output_schema=AgentInputBlock.Output,
-            test_input=[
-                {
-                    "value": "Hello, World!",
-                    "name": "input_1",
-                    "description": "This is a test input.",
-                    "placeholder_values": [],
-                    "limit_to_placeholder_values": False,
-                },
-                {
-                    "value": "Hello, World!",
-                    "name": "input_2",
-                    "description": "This is a test input.",
-                    "placeholder_values": ["Hello, World!"],
-                    "limit_to_placeholder_values": True,
-                },
-            ],
-            test_output=[
-                ("result", "Hello, World!"),
-                ("result", "Hello, World!"),
-            ],
-            categories={BlockCategory.INPUT, BlockCategory.BASIC},
-            block_type=BlockType.INPUT,
-            static_output=True,
-        )
-
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        yield "result", input_data.value
-
-
-class AgentOutputBlock(Block):
-    """
-    Records the output of the graph for users to see.
-
-    Behavior:
-        If `format` is provided and the `value` is of a type that can be formatted,
-        the block attempts to format the recorded_value using the `format`.
-        If formatting fails or no `format` is provided, the raw `value` is output.
-    """
-
-    class Input(BlockSchema):
-        value: Any = SchemaField(
-            description="The value to be recorded as output.",
-            default=None,
-            advanced=False,
-        )
-        name: str = SchemaField(description="The name of the output.")
-        title: str | None = SchemaField(
-            description="The title of the output.",
-            default=None,
-            advanced=True,
-        )
-        description: str | None = SchemaField(
-            description="The description of the output.",
-            default=None,
-            advanced=True,
-        )
-        format: str = SchemaField(
-            description="The format string to be used to format the recorded_value. Use Jinja2 syntax.",
-            default="",
-            advanced=True,
-        )
-        advanced: bool = SchemaField(
-            description="Whether to treat the output as advanced.",
-            default=False,
-            advanced=True,
-        )
-        secret: bool = SchemaField(
-            description="Whether the output should be treated as a secret.",
-            default=False,
-            advanced=True,
-        )
-
-    class Output(BlockSchema):
-        output: Any = SchemaField(description="The value recorded as output.")
-        name: Any = SchemaField(description="The name of the value recorded as output.")
-
-    def __init__(self):
-        super().__init__(
-            id="363ae599-353e-4804-937e-b2ee3cef3da4",
-            description="Stores the output of the graph for users to see.",
-            input_schema=AgentOutputBlock.Input,
-            output_schema=AgentOutputBlock.Output,
-            test_input=[
-                {
-                    "value": "Hello, World!",
-                    "name": "output_1",
-                    "description": "This is a test output.",
-                    "format": "{{ output_1 }}!!",
-                },
-                {
-                    "value": "42",
-                    "name": "output_2",
-                    "description": "This is another test output.",
-                    "format": "{{ output_2 }}",
-                },
-                {
-                    "value": MockObject(value="!!", key="key"),
-                    "name": "output_3",
-                    "description": "This is a test output with a mock object.",
-                    "format": "{{ output_3 }}",
-                },
-            ],
-            test_output=[
-                ("output", "Hello, World!!!"),
-                ("output", "42"),
-                ("output", MockObject(value="!!", key="key")),
-            ],
-            categories={BlockCategory.OUTPUT, BlockCategory.BASIC},
-            block_type=BlockType.OUTPUT,
-            static_output=True,
-        )
-
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        """
-        Attempts to format the recorded_value using the fmt_string if provided.
-        If formatting fails or no fmt_string is given, returns the original recorded_value.
-        """
-        if input_data.format:
-            try:
-                yield "output", formatter.format_string(
-                    input_data.format, {input_data.name: input_data.value}
-                )
-            except Exception as e:
-                yield "output", f"Error: {e}, {input_data.value}"
-        else:
-            yield "output", input_data.value
-            yield "name", input_data.name
-
-
 class AddToDictionaryBlock(Block):
     class Input(BlockSchema):
         dictionary: dict[Any, Any] = SchemaField(
-            default={},
+            default_factory=dict,
             description="The dictionary to add the entry to. If not provided, a new dictionary will be created.",
         )
         key: str = SchemaField(
@@ -371,7 +194,7 @@ class AddToDictionaryBlock(Block):
             advanced=False,
         )
         entries: dict[Any, Any] = SchemaField(
-            default={},
+            default_factory=dict,
             description="The entries to add to the dictionary. This is the batch version of the `key` and `value` fields.",
             advanced=True,
         )
@@ -433,7 +256,7 @@ class AddToDictionaryBlock(Block):
 class AddToListBlock(Block):
     class Input(BlockSchema):
         list: List[Any] = SchemaField(
-            default=[],
+            default_factory=list,
             advanced=False,
             description="The list to add the entry to. If not provided, a new list will be created.",
         )
@@ -443,7 +266,7 @@ class AddToListBlock(Block):
             default=None,
         )
         entries: List[Any] = SchemaField(
-            default=[],
+            default_factory=lambda: list(),
             description="The entries to add to the list. This is the batch version of the `entry` field.",
             advanced=True,
         )

autogpt_platform/backend/backend/blocks/code_executor.py

@@ -55,7 +55,7 @@ class CodeExecutionBlock(Block):
                 "These commands are executed with `sh`, in the foreground."
             ),
             placeholder="pip install cowsay",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
 
@@ -207,7 +207,7 @@ class InstantiationBlock(Block):
                 "These commands are executed with `sh`, in the foreground."
             ),
             placeholder="pip install cowsay",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
 

autogpt_platform/backend/backend/blocks/compass/triggers.py

@@ -8,6 +8,7 @@ from backend.data.block import (
     BlockSchema,
 )
 from backend.data.model import SchemaField
+from backend.integrations.providers import ProviderName
 from backend.integrations.webhooks.compass import CompassWebhookType
 
 
@@ -42,7 +43,7 @@ class CompassAITriggerBlock(Block):
             input_schema=CompassAITriggerBlock.Input,
             output_schema=CompassAITriggerBlock.Output,
             webhook_config=BlockManualWebhookConfig(
-                provider="compass",
+                provider=ProviderName.COMPASS,
                 webhook_type=CompassWebhookType.TRANSCRIPTION,
             ),
             test_input=[

autogpt_platform/backend/backend/blocks/csv.py

@@ -34,7 +34,7 @@ class ReadCsvBlock(Block):
         )
         skip_columns: list[str] = SchemaField(
             description="The columns to skip from the start of the row",
-            default=[],
+            default_factory=list,
         )
 
     class Output(BlockSchema):

autogpt_platform/backend/backend/blocks/exa/contents.py

@@ -1,6 +1,6 @@
 from typing import List
 
-from pydantic import BaseModel
+
 
 from backend.blocks.exa._auth import (
     ExaCredentials,
@@ -9,29 +9,14 @@ from backend.blocks.exa._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
+from .helpers import ContentSettings
 from backend.util.request import requests
 
 
-class ContentRetrievalSettings(BaseModel):
-    text: dict = SchemaField(
-        description="Text content settings",
-        default={"maxCharacters": 1000, "includeHtmlTags": False},
-        advanced=True,
-    )
-    highlights: dict = SchemaField(
-        description="Highlight settings",
-        default={
-            "numSentences": 3,
-            "highlightsPerUrl": 3,
-            "query": "",
-        },
-        advanced=True,
-    )
-    summary: dict = SchemaField(
-        description="Summary settings",
-        default={"query": ""},
-        advanced=True,
-    )
+# Use the fully-typed ``ContentSettings`` model from ``helpers`` instead of
+# anonymous ``dict`` fields so that the generated JSON schema contains proper
+# object properties. Without this, the frontend crashes when rendering the
+# advanced settings for this block.
 
 
 class ExaContentsBlock(Block):
@@ -40,17 +25,18 @@ class ExaContentsBlock(Block):
         ids: List[str] = SchemaField(
             description="Array of document IDs obtained from searches",
         )
-        contents: ContentRetrievalSettings = SchemaField(
+        contents: ContentSettings = SchemaField(
             description="Content retrieval settings",
-            default=ContentRetrievalSettings(),
+            default=ContentSettings(),
             advanced=True,
         )
 
     class Output(BlockSchema):
         results: list = SchemaField(
             description="List of document contents",
-            default=[],
+            default_factory=list,
         )
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/exa/search.py

@@ -38,11 +38,11 @@ class ExaSearchBlock(Block):
         )
         include_domains: List[str] = SchemaField(
             description="Domains to include in search",
-            default=[],
+            default_factory=list,
         )
         exclude_domains: List[str] = SchemaField(
             description="Domains to exclude from search",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         start_crawl_date: datetime = SchemaField(
@@ -59,12 +59,12 @@ class ExaSearchBlock(Block):
         )
         include_text: List[str] = SchemaField(
             description="Text patterns to include",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         exclude_text: List[str] = SchemaField(
             description="Text patterns to exclude",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         contents: ContentSettings = SchemaField(
@@ -76,7 +76,7 @@ class ExaSearchBlock(Block):
     class Output(BlockSchema):
         results: list = SchemaField(
             description="List of search results",
-            default=[],
+            default_factory=list,
         )
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/exa/similar.py

@@ -26,12 +26,12 @@ class ExaFindSimilarBlock(Block):
         )
         include_domains: List[str] = SchemaField(
             description="Domains to include in search",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         exclude_domains: List[str] = SchemaField(
             description="Domains to exclude from search",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         start_crawl_date: datetime = SchemaField(
@@ -48,12 +48,12 @@ class ExaFindSimilarBlock(Block):
         )
         include_text: List[str] = SchemaField(
             description="Text patterns to include (max 1 string, up to 5 words)",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         exclude_text: List[str] = SchemaField(
             description="Text patterns to exclude (max 1 string, up to 5 words)",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         contents: ContentSettings = SchemaField(
@@ -65,7 +65,7 @@ class ExaFindSimilarBlock(Block):
     class Output(BlockSchema):
         results: List[Any] = SchemaField(
             description="List of similar documents with title, URL, published date, author, and score",
-            default=[],
+            default_factory=list,
         )
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/fal/ai_video_generator.py

@@ -42,7 +42,7 @@ class AIVideoGeneratorBlock(Block):
             description="Error message if video generation failed."
         )
         logs: list[str] = SchemaField(
-            description="Generation progress logs.", optional=True
+            description="Generation progress logs.",
         )
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/generic_webhook/triggers.py

@@ -0,0 +1,51 @@
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockManualWebhookConfig,
+    BlockOutput,
+    BlockSchema,
+)
+from backend.data.model import SchemaField
+from backend.integrations.providers import ProviderName
+from backend.integrations.webhooks.generic import GenericWebhookType
+
+
+class GenericWebhookTriggerBlock(Block):
+    class Input(BlockSchema):
+        payload: dict = SchemaField(hidden=True, default_factory=dict)
+        constants: dict = SchemaField(
+            description="The constants to be set when the block is put on the graph",
+            default_factory=dict,
+        )
+
+    class Output(BlockSchema):
+        payload: dict = SchemaField(
+            description="The complete webhook payload that was received from the generic webhook."
+        )
+        constants: dict = SchemaField(
+            description="The constants to be set when the block is put on the graph"
+        )
+
+    example_payload = {"message": "Hello, World!"}
+
+    def __init__(self):
+        super().__init__(
+            id="8fa8c167-2002-47ce-aba8-97572fc5d387",
+            description="This block will output the contents of the generic input for the webhook.",
+            categories={BlockCategory.INPUT},
+            input_schema=GenericWebhookTriggerBlock.Input,
+            output_schema=GenericWebhookTriggerBlock.Output,
+            webhook_config=BlockManualWebhookConfig(
+                provider=ProviderName.GENERIC_WEBHOOK,
+                webhook_type=GenericWebhookType.PLAIN,
+            ),
+            test_input={"constants": {"key": "value"}, "payload": self.example_payload},
+            test_output=[
+                ("constants", {"key": "value"}),
+                ("payload", self.example_payload),
+            ],
+        )
+
+    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        yield "constants", input_data.constants
+        yield "payload", input_data.payload

autogpt_platform/backend/backend/blocks/github/_api.py

@@ -38,6 +38,59 @@ def _get_headers(credentials: GithubCredentials) -> dict[str, str]:
     }
 
 
+def convert_comment_url_to_api_endpoint(comment_url: str) -> str:
+    """
+    Converts a GitHub comment URL (web interface) to the appropriate API endpoint URL.
+
+    Handles:
+    1. Issue/PR comments: #issuecomment-{id}
+    2. PR review comments: #discussion_r{id}
+
+    Returns the appropriate API endpoint path for the comment.
+    """
+    # First, check if this is already an API URL
+    parsed_url = urlparse(comment_url)
+    if parsed_url.hostname == "api.github.com":
+        return comment_url
+
+    # Replace pull with issues for comment endpoints
+    if "/pull/" in comment_url:
+        comment_url = comment_url.replace("/pull/", "/issues/")
+
+    # Handle issue/PR comments (#issuecomment-xxx)
+    if "#issuecomment-" in comment_url:
+        base_url, comment_part = comment_url.split("#issuecomment-")
+        comment_id = comment_part
+
+        # Extract repo information from base URL
+        parsed_url = urlparse(base_url)
+        path_parts = parsed_url.path.strip("/").split("/")
+        owner, repo = path_parts[0], path_parts[1]
+
+        # Construct API URL for issue comments
+        return (
+            f"https://api.github.com/repos/{owner}/{repo}/issues/comments/{comment_id}"
+        )
+
+    # Handle PR review comments (#discussion_r)
+    elif "#discussion_r" in comment_url:
+        base_url, comment_part = comment_url.split("#discussion_r")
+        comment_id = comment_part
+
+        # Extract repo information from base URL
+        parsed_url = urlparse(base_url)
+        path_parts = parsed_url.path.strip("/").split("/")
+        owner, repo = path_parts[0], path_parts[1]
+
+        # Construct API URL for PR review comments
+        return (
+            f"https://api.github.com/repos/{owner}/{repo}/pulls/comments/{comment_id}"
+        )
+
+    # If no specific comment identifiers are found, use the general URL conversion
+    return _convert_to_api_url(comment_url)
+
+
 def get_api(
     credentials: GithubCredentials | GithubFineGrainedAPICredentials,
     convert_urls: bool = True,

autogpt_platform/backend/backend/blocks/github/checks.py

@@ -172,7 +172,9 @@ class GithubCreateCheckRunBlock(Block):
             data.output = output_data
 
         check_runs_url = f"{repo_url}/check-runs"
-        response = api.post(check_runs_url)
+        response = api.post(
+            check_runs_url, data=data.model_dump_json(exclude_none=True)
+        )
         result = response.json()
 
         return {
@@ -323,7 +325,9 @@ class GithubUpdateCheckRunBlock(Block):
             data.output = output_data
 
         check_run_url = f"{repo_url}/check-runs/{check_run_id}"
-        response = api.patch(check_run_url)
+        response = api.patch(
+            check_run_url, data=data.model_dump_json(exclude_none=True)
+        )
         result = response.json()
 
         return {

autogpt_platform/backend/backend/blocks/github/issues.py

@@ -1,3 +1,4 @@
+import logging
 from urllib.parse import urlparse
 
 from typing_extensions import TypedDict
@@ -5,7 +6,7 @@ from typing_extensions import TypedDict
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
 
-from ._api import get_api
+from ._api import convert_comment_url_to_api_endpoint, get_api
 from ._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
@@ -14,6 +15,8 @@ from ._auth import (
     GithubCredentialsInput,
 )
 
+logger = logging.getLogger(__name__)
+
 
 def is_github_url(url: str) -> bool:
     return urlparse(url).netloc == "github.com"
@@ -108,6 +111,228 @@ class GithubCommentBlock(Block):
 # --8<-- [end:GithubCommentBlockExample]
 
 
+class GithubUpdateCommentBlock(Block):
+    class Input(BlockSchema):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        comment_url: str = SchemaField(
+            description="URL of the GitHub comment",
+            placeholder="https://github.com/owner/repo/issues/1#issuecomment-123456789",
+            default="",
+            advanced=False,
+        )
+        issue_url: str = SchemaField(
+            description="URL of the GitHub issue or pull request",
+            placeholder="https://github.com/owner/repo/issues/1",
+            default="",
+        )
+        comment_id: str = SchemaField(
+            description="ID of the GitHub comment",
+            placeholder="123456789",
+            default="",
+        )
+        comment: str = SchemaField(
+            description="Comment to update",
+            placeholder="Enter your comment",
+        )
+
+    class Output(BlockSchema):
+        id: int = SchemaField(description="ID of the updated comment")
+        url: str = SchemaField(description="URL to the comment on GitHub")
+        error: str = SchemaField(
+            description="Error message if the comment update failed"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="b3f4d747-10e3-4e69-8c51-f2be1d99c9a7",
+            description="This block updates a comment on a specified GitHub issue or pull request.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubUpdateCommentBlock.Input,
+            output_schema=GithubUpdateCommentBlock.Output,
+            test_input={
+                "comment_url": "https://github.com/owner/repo/issues/1#issuecomment-123456789",
+                "comment": "This is an updated comment.",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("id", 123456789),
+                (
+                    "url",
+                    "https://github.com/owner/repo/issues/1#issuecomment-123456789",
+                ),
+            ],
+            test_mock={
+                "update_comment": lambda *args, **kwargs: (
+                    123456789,
+                    "https://github.com/owner/repo/issues/1#issuecomment-123456789",
+                )
+            },
+        )
+
+    @staticmethod
+    def update_comment(
+        credentials: GithubCredentials, comment_url: str, body_text: str
+    ) -> tuple[int, str]:
+        api = get_api(credentials, convert_urls=False)
+        data = {"body": body_text}
+        url = convert_comment_url_to_api_endpoint(comment_url)
+
+        logger.info(url)
+        response = api.patch(url, json=data)
+        comment = response.json()
+        return comment["id"], comment["html_url"]
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        if (
+            not input_data.comment_url
+            and input_data.comment_id
+            and input_data.issue_url
+        ):
+            parsed_url = urlparse(input_data.issue_url)
+            path_parts = parsed_url.path.strip("/").split("/")
+            owner, repo = path_parts[0], path_parts[1]
+
+            input_data.comment_url = f"https://api.github.com/repos/{owner}/{repo}/issues/comments/{input_data.comment_id}"
+
+        elif (
+            not input_data.comment_url
+            and not input_data.comment_id
+            and input_data.issue_url
+        ):
+            raise ValueError(
+                "Must provide either comment_url or comment_id and issue_url"
+            )
+        id, url = self.update_comment(
+            credentials,
+            input_data.comment_url,
+            input_data.comment,
+        )
+        yield "id", id
+        yield "url", url
+
+
+class GithubListCommentsBlock(Block):
+    class Input(BlockSchema):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        issue_url: str = SchemaField(
+            description="URL of the GitHub issue or pull request",
+            placeholder="https://github.com/owner/repo/issues/1",
+        )
+
+    class Output(BlockSchema):
+        class CommentItem(TypedDict):
+            id: int
+            body: str
+            user: str
+            url: str
+
+        comment: CommentItem = SchemaField(
+            title="Comment", description="Comments with their ID, body, user, and URL"
+        )
+        comments: list[CommentItem] = SchemaField(
+            description="List of comments with their ID, body, user, and URL"
+        )
+        error: str = SchemaField(description="Error message if listing comments failed")
+
+    def __init__(self):
+        super().__init__(
+            id="c4b5fb63-0005-4a11-b35a-0c2467bd6b59",
+            description="This block lists all comments for a specified GitHub issue or pull request.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubListCommentsBlock.Input,
+            output_schema=GithubListCommentsBlock.Output,
+            test_input={
+                "issue_url": "https://github.com/owner/repo/issues/1",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                (
+                    "comment",
+                    {
+                        "id": 123456789,
+                        "body": "This is a test comment.",
+                        "user": "test_user",
+                        "url": "https://github.com/owner/repo/issues/1#issuecomment-123456789",
+                    },
+                ),
+                (
+                    "comments",
+                    [
+                        {
+                            "id": 123456789,
+                            "body": "This is a test comment.",
+                            "user": "test_user",
+                            "url": "https://github.com/owner/repo/issues/1#issuecomment-123456789",
+                        }
+                    ],
+                ),
+            ],
+            test_mock={
+                "list_comments": lambda *args, **kwargs: [
+                    {
+                        "id": 123456789,
+                        "body": "This is a test comment.",
+                        "user": "test_user",
+                        "url": "https://github.com/owner/repo/issues/1#issuecomment-123456789",
+                    }
+                ]
+            },
+        )
+
+    @staticmethod
+    def list_comments(
+        credentials: GithubCredentials, issue_url: str
+    ) -> list[Output.CommentItem]:
+        parsed_url = urlparse(issue_url)
+        path_parts = parsed_url.path.strip("/").split("/")
+
+        owner = path_parts[0]
+        repo = path_parts[1]
+
+        # GitHub API uses 'issues' for both issues and pull requests when it comes to comments
+        issue_number = path_parts[3]  # Whether 'issues/123' or 'pull/123'
+
+        # Construct the proper API URL directly
+        api_url = f"https://api.github.com/repos/{owner}/{repo}/issues/{issue_number}/comments"
+
+        # Set convert_urls=False since we're already providing an API URL
+        api = get_api(credentials, convert_urls=False)
+        response = api.get(api_url)
+        comments = response.json()
+        parsed_comments: list[GithubListCommentsBlock.Output.CommentItem] = [
+            {
+                "id": comment["id"],
+                "body": comment["body"],
+                "user": comment["user"]["login"],
+                "url": comment["html_url"],
+            }
+            for comment in comments
+        ]
+        return parsed_comments
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        comments = self.list_comments(
+            credentials,
+            input_data.issue_url,
+        )
+        yield from (("comment", comment) for comment in comments)
+        yield "comments", comments
+
+
 class GithubMakeIssueBlock(Block):
     class Input(BlockSchema):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")

autogpt_platform/backend/backend/blocks/github/statuses.py

@@ -144,7 +144,7 @@ class GithubCreateStatusBlock(Block):
             data.description = description
 
         status_url = f"{repo_url}/statuses/{sha}"
-        response = api.post(status_url, json=data)
+        response = api.post(status_url, data=data.model_dump_json(exclude_none=True))
         result = response.json()
 
         return {

autogpt_platform/backend/backend/blocks/github/triggers.py

@@ -12,6 +12,7 @@ from backend.data.block import (
     BlockWebhookConfig,
 )
 from backend.data.model import SchemaField
+from backend.integrations.providers import ProviderName
 
 from ._auth import (
     TEST_CREDENTIALS,
@@ -36,7 +37,7 @@ class GitHubTriggerBase:
             placeholder="{owner}/{repo}",
         )
         # --8<-- [start:example-payload-field]
-        payload: dict = SchemaField(hidden=True, default={})
+        payload: dict = SchemaField(hidden=True, default_factory=dict)
         # --8<-- [end:example-payload-field]
 
     class Output(BlockSchema):
@@ -123,7 +124,7 @@ class GithubPullRequestTriggerBlock(GitHubTriggerBase, Block):
             output_schema=GithubPullRequestTriggerBlock.Output,
             # --8<-- [start:example-webhook_config]
             webhook_config=BlockWebhookConfig(
-                provider="github",
+                provider=ProviderName.GITHUB,
                 webhook_type=GithubWebhookType.REPO,
                 resource_format="{repo}",
                 event_filter_input="events",

autogpt_platform/backend/backend/blocks/google/calendar.py

@@ -0,0 +1,598 @@
+import enum
+import uuid
+from datetime import datetime, timedelta, timezone
+from typing import Literal
+
+from google.oauth2.credentials import Credentials
+from googleapiclient.discovery import build
+from pydantic import BaseModel
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+from backend.util.settings import AppEnvironment, Settings
+
+from ._auth import (
+    GOOGLE_OAUTH_IS_CONFIGURED,
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    GoogleCredentials,
+    GoogleCredentialsField,
+    GoogleCredentialsInput,
+)
+
+
+class CalendarEvent(BaseModel):
+    """Structured representation of a Google Calendar event."""
+
+    id: str
+    title: str
+    start_time: str
+    end_time: str
+    is_all_day: bool
+    location: str | None
+    description: str | None
+    organizer: str | None
+    attendees: list[str]
+    has_video_call: bool
+    video_link: str | None
+    calendar_link: str
+    is_recurring: bool
+
+
+class GoogleCalendarReadEventsBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/calendar.readonly"]
+        )
+        calendar_id: str = SchemaField(
+            description="Calendar ID (use 'primary' for your main calendar)",
+            default="primary",
+        )
+        max_events: int = SchemaField(
+            description="Maximum number of events to retrieve", default=10
+        )
+        start_time: datetime = SchemaField(
+            description="Retrieve events starting from this time",
+            default_factory=lambda: datetime.now(tz=timezone.utc),
+        )
+        time_range_days: int = SchemaField(
+            description="Number of days to look ahead for events", default=30
+        )
+        search_term: str | None = SchemaField(
+            description="Optional search term to filter events by", default=None
+        )
+
+        page_token: str | None = SchemaField(
+            description="Page token from previous request to get the next batch of events. You can use this if you have lots of events you want to process in a loop",
+            default=None,
+        )
+        include_declined_events: bool = SchemaField(
+            description="Include events you've declined", default=False
+        )
+
+    class Output(BlockSchema):
+        events: list[CalendarEvent] = SchemaField(
+            description="List of calendar events in the requested time range",
+            default_factory=list,
+        )
+        event: CalendarEvent = SchemaField(
+            description="One of the calendar events in the requested time range"
+        )
+        next_page_token: str | None = SchemaField(
+            description="Token for retrieving the next page of events if more exist",
+            default=None,
+        )
+        error: str = SchemaField(
+            description="Error message if the request failed",
+        )
+
+    def __init__(self):
+        settings = Settings()
+
+        # Create realistic test data for events
+        test_now = datetime.now(tz=timezone.utc)
+        test_tomorrow = test_now + timedelta(days=1)
+
+        test_event_dict = {
+            "id": "event1id",
+            "title": "Team Meeting",
+            "start_time": test_tomorrow.strftime("%Y-%m-%d %H:%M"),
+            "end_time": (test_tomorrow + timedelta(hours=1)).strftime("%Y-%m-%d %H:%M"),
+            "is_all_day": False,
+            "location": "Conference Room A",
+            "description": "Weekly team sync",
+            "organizer": "manager@example.com",
+            "attendees": ["colleague1@example.com", "colleague2@example.com"],
+            "has_video_call": True,
+            "video_link": "https://meet.google.com/abc-defg-hij",
+            "calendar_link": "https://calendar.google.com/calendar/event?eid=event1id",
+            "is_recurring": True,
+        }
+
+        super().__init__(
+            id="80bc3ed1-e9a4-449e-8163-a8fc86f74f6a",
+            description="Retrieves upcoming events from a Google Calendar with filtering options",
+            categories={BlockCategory.PRODUCTIVITY, BlockCategory.DATA},
+            input_schema=GoogleCalendarReadEventsBlock.Input,
+            output_schema=GoogleCalendarReadEventsBlock.Output,
+            disabled=not GOOGLE_OAUTH_IS_CONFIGURED
+            or settings.config.app_env == AppEnvironment.PRODUCTION,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "calendar_id": "primary",
+                "max_events": 5,
+                "start_time": test_now.isoformat(),
+                "time_range_days": 7,
+                "search_term": None,
+                "include_declined_events": False,
+                "page_token": None,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("event", test_event_dict),
+                ("events", [test_event_dict]),
+            ],
+            test_mock={
+                "_read_calendar": lambda *args, **kwargs: {
+                    "items": [
+                        {
+                            "id": "event1id",
+                            "summary": "Team Meeting",
+                            "start": {
+                                "dateTime": test_tomorrow.isoformat(),
+                                "timeZone": "UTC",
+                            },
+                            "end": {
+                                "dateTime": (
+                                    test_tomorrow + timedelta(hours=1)
+                                ).isoformat(),
+                                "timeZone": "UTC",
+                            },
+                            "location": "Conference Room A",
+                            "description": "Weekly team sync",
+                            "organizer": {"email": "manager@example.com"},
+                            "attendees": [
+                                {"email": "colleague1@example.com"},
+                                {"email": "colleague2@example.com"},
+                            ],
+                            "conferenceData": {
+                                "conferenceUrl": "https://meet.google.com/abc-defg-hij"
+                            },
+                            "htmlLink": "https://calendar.google.com/calendar/event?eid=event1id",
+                            "recurrence": ["RRULE:FREQ=WEEKLY;COUNT=10"],
+                        }
+                    ],
+                    "nextPageToken": None,
+                },
+                "_format_events": lambda *args, **kwargs: [test_event_dict],
+            },
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            service = self._build_service(credentials, **kwargs)
+
+            # Calculate end time based on start time and time range
+            end_time = input_data.start_time + timedelta(
+                days=input_data.time_range_days
+            )
+
+            # Call Google Calendar API
+            result = self._read_calendar(
+                service=service,
+                calendarId=input_data.calendar_id,
+                time_min=input_data.start_time.isoformat(),
+                time_max=end_time.isoformat(),
+                max_results=input_data.max_events,
+                single_events=True,
+                search_term=input_data.search_term,
+                show_deleted=False,
+                show_hidden=input_data.include_declined_events,
+                page_token=input_data.page_token,
+            )
+
+            # Format events into a user-friendly structure
+            formatted_events = self._format_events(result.get("items", []))
+
+            # Include next page token if available
+            if next_page_token := result.get("nextPageToken"):
+                yield "next_page_token", next_page_token
+
+            for event in formatted_events:
+                yield "event", event
+
+            yield "events", formatted_events
+
+        except Exception as e:
+            yield "error", str(e)
+
+    @staticmethod
+    def _build_service(credentials: GoogleCredentials, **kwargs):
+        creds = Credentials(
+            token=(
+                credentials.access_token.get_secret_value()
+                if credentials.access_token
+                else None
+            ),
+            refresh_token=(
+                credentials.refresh_token.get_secret_value()
+                if credentials.refresh_token
+                else None
+            ),
+            token_uri="https://oauth2.googleapis.com/token",
+            client_id=Settings().secrets.google_client_id,
+            client_secret=Settings().secrets.google_client_secret,
+            scopes=credentials.scopes,
+        )
+        return build("calendar", "v3", credentials=creds)
+
+    def _read_calendar(
+        self,
+        service,
+        calendarId: str,
+        time_min: str,
+        time_max: str,
+        max_results: int,
+        single_events: bool,
+        search_term: str | None = None,
+        show_deleted: bool = False,
+        show_hidden: bool = False,
+        page_token: str | None = None,
+    ) -> dict:
+        """Read calendar events with optional filtering."""
+        calendar = service.events()
+
+        # Build query parameters
+        params = {
+            "calendarId": calendarId,
+            "timeMin": time_min,
+            "timeMax": time_max,
+            "maxResults": max_results,
+            "singleEvents": single_events,
+            "orderBy": "startTime",
+            "showDeleted": show_deleted,
+            "showHiddenInvitations": show_hidden,
+            **({"pageToken": page_token} if page_token else {}),
+        }
+
+        # Add search term if provided
+        if search_term:
+            params["q"] = search_term
+
+        result = calendar.list(**params).execute()
+        return result
+
+    def _format_events(self, events: list[dict]) -> list[CalendarEvent]:
+        """Format Google Calendar API events into user-friendly structure."""
+        formatted_events = []
+
+        for event in events:
+            # Determine if all-day event
+            is_all_day = "date" in event.get("start", {})
+
+            # Format start and end times
+            if is_all_day:
+                start_time = event.get("start", {}).get("date", "")
+                end_time = event.get("end", {}).get("date", "")
+            else:
+                # Convert ISO format to more readable format
+                start_datetime = datetime.fromisoformat(
+                    event.get("start", {}).get("dateTime", "").replace("Z", "+00:00")
+                )
+                end_datetime = datetime.fromisoformat(
+                    event.get("end", {}).get("dateTime", "").replace("Z", "+00:00")
+                )
+                start_time = start_datetime.strftime("%Y-%m-%d %H:%M")
+                end_time = end_datetime.strftime("%Y-%m-%d %H:%M")
+
+            # Extract attendees
+            attendees = []
+            for attendee in event.get("attendees", []):
+                if email := attendee.get("email"):
+                    attendees.append(email)
+
+            # Check for video call link
+            has_video_call = False
+            video_link = None
+            if conf_data := event.get("conferenceData"):
+                if conf_url := conf_data.get("conferenceUrl"):
+                    has_video_call = True
+                    video_link = conf_url
+                elif entry_points := conf_data.get("entryPoints", []):
+                    for entry in entry_points:
+                        if entry.get("entryPointType") == "video":
+                            has_video_call = True
+                            video_link = entry.get("uri")
+                            break
+
+            # Create formatted event
+            formatted_event = CalendarEvent(
+                id=event.get("id", ""),
+                title=event.get("summary", "Untitled Event"),
+                start_time=start_time,
+                end_time=end_time,
+                is_all_day=is_all_day,
+                location=event.get("location"),
+                description=event.get("description"),
+                organizer=event.get("organizer", {}).get("email"),
+                attendees=attendees,
+                has_video_call=has_video_call,
+                video_link=video_link,
+                calendar_link=event.get("htmlLink", ""),
+                is_recurring=bool(event.get("recurrence")),
+            )
+
+            formatted_events.append(formatted_event)
+
+        return formatted_events
+
+
+class ReminderPreset(enum.Enum):
+    """Common reminder times before an event."""
+
+    TEN_MINUTES = 10
+    THIRTY_MINUTES = 30
+    ONE_HOUR = 60
+    ONE_DAY = 1440  # 24 hours in minutes
+
+
+class RecurrenceFrequency(enum.Enum):
+    """Frequency options for recurring events."""
+
+    DAILY = "DAILY"
+    WEEKLY = "WEEKLY"
+    MONTHLY = "MONTHLY"
+    YEARLY = "YEARLY"
+
+
+class ExactTiming(BaseModel):
+    """Model for specifying start and end times."""
+
+    discriminator: Literal["exact_timing"]
+    start_datetime: datetime
+    end_datetime: datetime
+
+
+class DurationTiming(BaseModel):
+    """Model for specifying start time and duration."""
+
+    discriminator: Literal["duration_timing"]
+    start_datetime: datetime
+    duration_minutes: int
+
+
+class OneTimeEvent(BaseModel):
+    """Model for a one-time event."""
+
+    discriminator: Literal["one_time"]
+
+
+class RecurringEvent(BaseModel):
+    """Model for a recurring event."""
+
+    discriminator: Literal["recurring"]
+    frequency: RecurrenceFrequency
+    count: int
+
+
+class GoogleCalendarCreateEventBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/calendar"]
+        )
+        # Event Details
+        event_title: str = SchemaField(description="Title of the event")
+        location: str | None = SchemaField(
+            description="Location of the event", default=None
+        )
+        description: str | None = SchemaField(
+            description="Description of the event", default=None
+        )
+
+        # Timing
+        timing: ExactTiming | DurationTiming = SchemaField(
+            discriminator="discriminator",
+            advanced=False,
+            description="Specify when the event starts and ends",
+            default_factory=lambda: DurationTiming(
+                discriminator="duration_timing",
+                start_datetime=datetime.now().replace(microsecond=0, second=0, minute=0)
+                + timedelta(hours=1),
+                duration_minutes=60,
+            ),
+        )
+
+        # Calendar selection
+        calendar_id: str = SchemaField(
+            description="Calendar ID (use 'primary' for your main calendar)",
+            default="primary",
+        )
+
+        # Guests
+        guest_emails: list[str] = SchemaField(
+            description="Email addresses of guests to invite", default_factory=list
+        )
+        send_notifications: bool = SchemaField(
+            description="Send email notifications to guests", default=True
+        )
+
+        # Extras
+        add_google_meet: bool = SchemaField(
+            description="Include a Google Meet video conference link", default=False
+        )
+        recurrence: OneTimeEvent | RecurringEvent = SchemaField(
+            discriminator="discriminator",
+            description="Whether the event repeats",
+            default_factory=lambda: OneTimeEvent(discriminator="one_time"),
+        )
+        reminder_minutes: list[ReminderPreset] = SchemaField(
+            description="When to send reminders before the event",
+            default_factory=lambda: [ReminderPreset.TEN_MINUTES],
+        )
+
+    class Output(BlockSchema):
+        event_id: str = SchemaField(description="ID of the created event")
+        event_link: str = SchemaField(
+            description="Link to view the event in Google Calendar"
+        )
+        error: str = SchemaField(description="Error message if event creation failed")
+
+    def __init__(self):
+        settings = Settings()
+
+        super().__init__(
+            id="ed2ec950-fbff-4204-94c0-023fb1d625e0",
+            description="This block creates a new event in Google Calendar with customizable parameters.",
+            categories={BlockCategory.PRODUCTIVITY},
+            input_schema=GoogleCalendarCreateEventBlock.Input,
+            output_schema=GoogleCalendarCreateEventBlock.Output,
+            disabled=not GOOGLE_OAUTH_IS_CONFIGURED
+            or settings.config.app_env == AppEnvironment.PRODUCTION,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "event_title": "Team Meeting",
+                "location": "Conference Room A",
+                "description": "Weekly team sync-up",
+                "calendar_id": "primary",
+                "guest_emails": ["colleague1@example.com", "colleague2@example.com"],
+                "add_google_meet": True,
+                "send_notifications": True,
+                "reminder_minutes": [
+                    ReminderPreset.TEN_MINUTES.value,
+                    ReminderPreset.ONE_HOUR.value,
+                ],
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("event_id", "abc123event_id"),
+                ("event_link", "https://calendar.google.com/calendar/event?eid=abc123"),
+            ],
+            test_mock={
+                "_create_event": lambda *args, **kwargs: {
+                    "id": "abc123event_id",
+                    "htmlLink": "https://calendar.google.com/calendar/event?eid=abc123",
+                }
+            },
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            service = self._build_service(credentials, **kwargs)
+
+            # Get start and end times based on the timing option
+            if input_data.timing.discriminator == "exact_timing":
+                start_datetime = input_data.timing.start_datetime
+                end_datetime = input_data.timing.end_datetime
+            else:  # duration_timing
+                start_datetime = input_data.timing.start_datetime
+                end_datetime = start_datetime + timedelta(
+                    minutes=input_data.timing.duration_minutes
+                )
+
+            # Format datetimes for Google Calendar API
+            start_time_str = start_datetime.isoformat()
+            end_time_str = end_datetime.isoformat()
+
+            # Build the event body
+            event_body = {
+                "summary": input_data.event_title,
+                "start": {"dateTime": start_time_str},
+                "end": {"dateTime": end_time_str},
+            }
+
+            # Add optional fields
+            if input_data.location:
+                event_body["location"] = input_data.location
+
+            if input_data.description:
+                event_body["description"] = input_data.description
+
+            # Add guests
+            if input_data.guest_emails:
+                event_body["attendees"] = [
+                    {"email": email} for email in input_data.guest_emails
+                ]
+
+            # Add reminders
+            if input_data.reminder_minutes:
+                event_body["reminders"] = {
+                    "useDefault": False,
+                    "overrides": [
+                        {"method": "popup", "minutes": reminder.value}
+                        for reminder in input_data.reminder_minutes
+                    ],
+                }
+
+            # Add Google Meet
+            if input_data.add_google_meet:
+                event_body["conferenceData"] = {
+                    "createRequest": {
+                        "requestId": f"meet-{uuid.uuid4()}",
+                        "conferenceSolutionKey": {"type": "hangoutsMeet"},
+                    }
+                }
+
+            # Add recurrence
+            if input_data.recurrence.discriminator == "recurring":
+                rule = f"RRULE:FREQ={input_data.recurrence.frequency.value}"
+                rule += f";COUNT={input_data.recurrence.count}"
+                event_body["recurrence"] = [rule]
+
+            # Create the event
+            result = self._create_event(
+                service=service,
+                calendar_id=input_data.calendar_id,
+                event_body=event_body,
+                send_notifications=input_data.send_notifications,
+                conference_data_version=1 if input_data.add_google_meet else 0,
+            )
+
+            yield "event_id", result.get("id", "")
+            yield "event_link", result.get("htmlLink", "")
+        except Exception as e:
+            yield "error", str(e)
+
+    @staticmethod
+    def _build_service(credentials: GoogleCredentials, **kwargs):
+        creds = Credentials(
+            token=(
+                credentials.access_token.get_secret_value()
+                if credentials.access_token
+                else None
+            ),
+            refresh_token=(
+                credentials.refresh_token.get_secret_value()
+                if credentials.refresh_token
+                else None
+            ),
+            token_uri="https://oauth2.googleapis.com/token",
+            client_id=Settings().secrets.google_client_id,
+            client_secret=Settings().secrets.google_client_secret,
+            scopes=credentials.scopes,
+        )
+        return build("calendar", "v3", credentials=creds)
+
+    def _create_event(
+        self,
+        service,
+        calendar_id: str,
+        event_body: dict,
+        send_notifications: bool = False,
+        conference_data_version: int = 0,
+    ) -> dict:
+        """Create a new event in Google Calendar."""
+        calendar = service.events()
+
+        # Make the API call
+        result = calendar.insert(
+            calendarId=calendar_id,
+            body=event_body,
+            sendNotifications=send_notifications,
+            conferenceDataVersion=conference_data_version,
+        ).execute()
+
+        return result

autogpt_platform/backend/backend/blocks/google/gmail.py

@@ -8,6 +8,7 @@ from pydantic import BaseModel
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
+from backend.util.settings import Settings
 
 from ._auth import (
     GOOGLE_OAUTH_IS_CONFIGURED,
@@ -150,8 +151,8 @@ class GmailReadBlock(Block):
                 else None
             ),
             token_uri="https://oauth2.googleapis.com/token",
-            client_id=kwargs.get("client_id"),
-            client_secret=kwargs.get("client_secret"),
+            client_id=Settings().secrets.google_client_id,
+            client_secret=Settings().secrets.google_client_secret,
             scopes=credentials.scopes,
         )
         return build("gmail", "v1", credentials=creds)

autogpt_platform/backend/backend/blocks/google/sheets.py

@@ -3,6 +3,7 @@ from googleapiclient.discovery import build
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
+from backend.util.settings import AppEnvironment, Settings
 
 from ._auth import (
     GOOGLE_OAUTH_IS_CONFIGURED,
@@ -35,13 +36,15 @@ class GoogleSheetsReadBlock(Block):
         )
 
     def __init__(self):
+        settings = Settings()
         super().__init__(
             id="5724e902-3635-47e9-a108-aaa0263a4988",
             description="This block reads data from a Google Sheets spreadsheet.",
             categories={BlockCategory.DATA},
             input_schema=GoogleSheetsReadBlock.Input,
             output_schema=GoogleSheetsReadBlock.Output,
-            disabled=not GOOGLE_OAUTH_IS_CONFIGURED,
+            disabled=not GOOGLE_OAUTH_IS_CONFIGURED
+            or settings.config.app_env == AppEnvironment.PRODUCTION,
             test_input={
                 "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
                 "range": "Sheet1!A1:B2",
@@ -86,8 +89,8 @@ class GoogleSheetsReadBlock(Block):
                 else None
             ),
             token_uri="https://oauth2.googleapis.com/token",
-            client_id=kwargs.get("client_id"),
-            client_secret=kwargs.get("client_secret"),
+            client_id=Settings().secrets.google_client_id,
+            client_secret=Settings().secrets.google_client_secret,
             scopes=credentials.scopes,
         )
         return build("sheets", "v4", credentials=creds)

autogpt_platform/backend/backend/blocks/http.py

@@ -1,11 +1,16 @@
 import json
+import logging
 from enum import Enum
 from typing import Any
 
+from requests.exceptions import HTTPError, RequestException
+
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
 from backend.util.request import requests
 
+logger = logging.getLogger(name=__name__)
+
 
 class HttpMethod(Enum):
     GET = "GET"
@@ -29,7 +34,7 @@ class SendWebRequestBlock(Block):
         )
         headers: dict[str, str] = SchemaField(
             description="The headers to include in the request",
-            default={},
+            default_factory=dict,
         )
         json_format: bool = SchemaField(
             title="JSON format",
@@ -43,8 +48,9 @@ class SendWebRequestBlock(Block):
 
     class Output(BlockSchema):
         response: object = SchemaField(description="The response from the server")
-        client_error: object = SchemaField(description="The error on 4xx status codes")
-        server_error: object = SchemaField(description="The error on 5xx status codes")
+        client_error: object = SchemaField(description="Errors on 4xx status codes")
+        server_error: object = SchemaField(description="Errors on 5xx status codes")
+        error: str = SchemaField(description="Errors for all other exceptions")
 
     def __init__(self):
         super().__init__(
@@ -68,20 +74,48 @@ class SendWebRequestBlock(Block):
                     # we should send it as plain text instead
                     input_data.json_format = False
 
-        response = requests.request(
-            input_data.method.value,
-            input_data.url,
-            headers=input_data.headers,
-            json=body if input_data.json_format else None,
-            data=body if not input_data.json_format else None,
-        )
-        result = response.json() if input_data.json_format else response.text
+        try:
+            response = requests.request(
+                input_data.method.value,
+                input_data.url,
+                headers=input_data.headers,
+                json=body if input_data.json_format else None,
+                data=body if not input_data.json_format else None,
+            )
+
+            if input_data.json_format:
+                if response.status_code == 204 or not response.content.strip():
+                    result = None
+                else:
+                    result = response.json()
+            else:
+                result = response.text
 
-        if response.status_code // 100 == 2:
             yield "response", result
-        elif response.status_code // 100 == 4:
-            yield "client_error", result
-        elif response.status_code // 100 == 5:
-            yield "server_error", result
-        else:
-            raise ValueError(f"Unexpected status code: {response.status_code}")
+
+        except HTTPError as e:
+            # Handle error responses
+            try:
+                result = e.response.json() if input_data.json_format else str(e)
+            except json.JSONDecodeError:
+                result = str(e)
+
+            if 400 <= e.response.status_code < 500:
+                yield "client_error", result
+            elif 500 <= e.response.status_code < 600:
+                yield "server_error", result
+            else:
+                error_msg = (
+                    "Unexpected status code "
+                    f"{e.response.status_code} '{e.response.reason}'"
+                )
+                logger.warning(error_msg)
+                yield "error", error_msg
+
+        except RequestException as e:
+            # Handle other request-related exceptions
+            yield "error", str(e)
+
+        except Exception as e:
+            # Catch any other unexpected exceptions
+            yield "error", str(e)

autogpt_platform/backend/backend/blocks/hubspot/company.py

@@ -15,7 +15,8 @@ class HubSpotCompanyBlock(Block):
             description="Operation to perform (create, update, get)", default="get"
         )
         company_data: dict = SchemaField(
-            description="Company data for create/update operations", default={}
+            description="Company data for create/update operations",
+            default_factory=dict,
         )
         domain: str = SchemaField(
             description="Company domain for get/update operations", default=""

autogpt_platform/backend/backend/blocks/hubspot/contact.py

@@ -15,7 +15,8 @@ class HubSpotContactBlock(Block):
             description="Operation to perform (create, update, get)", default="get"
         )
         contact_data: dict = SchemaField(
-            description="Contact data for create/update operations", default={}
+            description="Contact data for create/update operations",
+            default_factory=dict,
         )
         email: str = SchemaField(
             description="Email address for get/update operations", default=""

autogpt_platform/backend/backend/blocks/hubspot/engagement.py

@@ -19,7 +19,7 @@ class HubSpotEngagementBlock(Block):
         )
         email_data: dict = SchemaField(
             description="Email data including recipient, subject, content",
-            default={},
+            default_factory=dict,
         )
         contact_id: str = SchemaField(
             description="Contact ID for engagement tracking", default=""
@@ -27,7 +27,6 @@ class HubSpotEngagementBlock(Block):
         timeframe_days: int = SchemaField(
             description="Number of days to look back for engagement",
             default=30,
-            optional=True,
         )
 
     class Output(BlockSchema):

autogpt_platform/backend/backend/blocks/ideogram.py

@@ -142,6 +142,16 @@ class IdeogramModelBlock(Block):
             title="Color Palette Preset",
             advanced=True,
         )
+        custom_color_palette: Optional[list[str]] = SchemaField(
+            description=(
+                "Only available for model version V_2 or V_2_TURBO. Provide one or more color hex codes "
+                "(e.g., ['#000030', '#1C0C47', '#9900FF', '#4285F4', '#FFFFFF']) to define a custom color "
+                "palette. Only used if 'color_palette_name' is 'NONE'."
+            ),
+            default=None,
+            title="Custom Color Palette",
+            advanced=True,
+        )
 
     class Output(BlockSchema):
         result: str = SchemaField(description="Generated image URL")
@@ -164,6 +174,13 @@ class IdeogramModelBlock(Block):
                 "style_type": StyleType.AUTO,
                 "negative_prompt": None,
                 "color_palette_name": ColorPalettePreset.NONE,
+                "custom_color_palette": [
+                    "#000030",
+                    "#1C0C47",
+                    "#9900FF",
+                    "#4285F4",
+                    "#FFFFFF",
+                ],
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
             test_output=[
@@ -173,7 +190,7 @@ class IdeogramModelBlock(Block):
                 ),
             ],
             test_mock={
-                "run_model": lambda api_key, model_name, prompt, seed, aspect_ratio, magic_prompt_option, style_type, negative_prompt, color_palette_name: "https://ideogram.ai/api/images/test-generated-image-url.png",
+                "run_model": lambda api_key, model_name, prompt, seed, aspect_ratio, magic_prompt_option, style_type, negative_prompt, color_palette_name, custom_colors: "https://ideogram.ai/api/images/test-generated-image-url.png",
                 "upscale_image": lambda api_key, image_url: "https://ideogram.ai/api/images/test-upscaled-image-url.png",
             },
             test_credentials=TEST_CREDENTIALS,
@@ -195,6 +212,7 @@ class IdeogramModelBlock(Block):
             style_type=input_data.style_type.value,
             negative_prompt=input_data.negative_prompt,
             color_palette_name=input_data.color_palette_name.value,
+            custom_colors=input_data.custom_color_palette,
         )
 
         # Step 2: Upscale the image if requested
@@ -217,6 +235,7 @@ class IdeogramModelBlock(Block):
         style_type: str,
         negative_prompt: Optional[str],
         color_palette_name: str,
+        custom_colors: Optional[list[str]],
     ):
         url = "https://api.ideogram.ai/generate"
         headers = {
@@ -241,7 +260,11 @@ class IdeogramModelBlock(Block):
             data["image_request"]["negative_prompt"] = negative_prompt
 
         if color_palette_name != "NONE":
-            data["image_request"]["color_palette"] = {"name": color_palette_name}
+            data["color_palette"] = {"name": color_palette_name}
+        elif custom_colors:
+            data["color_palette"] = {
+                "members": [{"color_hex": color} for color in custom_colors]
+            }
 
         try:
             response = requests.post(url, json=data, headers=headers)
@@ -267,9 +290,7 @@ class IdeogramModelBlock(Block):
             response = requests.post(
                 url,
                 headers=headers,
-                data={
-                    "image_request": "{}",  # Empty JSON object
-                },
+                data={"image_request": "{}"},
                 files=files,
             )
 

autogpt_platform/backend/backend/blocks/io.py

@@ -0,0 +1,556 @@
+import copy
+from datetime import date, time
+from typing import Any, Optional
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema, BlockType
+from backend.data.model import SchemaField
+from backend.util.file import store_media_file
+from backend.util.mock import MockObject
+from backend.util.settings import Config
+from backend.util.text import TextFormatter
+from backend.util.type import LongTextType, MediaFileType, ShortTextType
+
+formatter = TextFormatter()
+config = Config()
+
+
+class AgentInputBlock(Block):
+    """
+    This block is used to provide input to the graph.
+
+    It takes in a value, name, description, default values list and bool to limit selection to default values.
+
+    It Outputs the value passed as input.
+    """
+
+    class Input(BlockSchema):
+        name: str = SchemaField(description="The name of the input.")
+        value: Any = SchemaField(
+            description="The value to be passed as input.",
+            default=None,
+        )
+        title: str | None = SchemaField(
+            description="The title of the input.", default=None, advanced=True
+        )
+        description: str | None = SchemaField(
+            description="The description of the input.",
+            default=None,
+            advanced=True,
+        )
+        placeholder_values: list = SchemaField(
+            description="The placeholder values to be passed as input.",
+            default_factory=list,
+            advanced=True,
+            hidden=True,
+        )
+        advanced: bool = SchemaField(
+            description="Whether to show the input in the advanced section, if the field is not required.",
+            default=False,
+            advanced=True,
+        )
+        secret: bool = SchemaField(
+            description="Whether the input should be treated as a secret.",
+            default=False,
+            advanced=True,
+        )
+
+        def generate_schema(self):
+            schema = copy.deepcopy(self.get_field_schema("value"))
+            if possible_values := self.placeholder_values:
+                schema["enum"] = possible_values
+            return schema
+
+    class Output(BlockSchema):
+        result: Any = SchemaField(description="The value passed as input.")
+
+    def __init__(self, **kwargs):
+        super().__init__(
+            **{
+                "id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b",
+                "description": "Base block for user inputs.",
+                "input_schema": AgentInputBlock.Input,
+                "output_schema": AgentInputBlock.Output,
+                "test_input": [
+                    {
+                        "value": "Hello, World!",
+                        "name": "input_1",
+                        "description": "Example test input.",
+                        "placeholder_values": [],
+                    },
+                    {
+                        "value": "Hello, World!",
+                        "name": "input_2",
+                        "description": "Example test input with placeholders.",
+                        "placeholder_values": ["Hello, World!"],
+                    },
+                ],
+                "test_output": [
+                    ("result", "Hello, World!"),
+                    ("result", "Hello, World!"),
+                ],
+                "categories": {BlockCategory.INPUT, BlockCategory.BASIC},
+                "block_type": BlockType.INPUT,
+                "static_output": True,
+                **kwargs,
+            }
+        )
+
+    def run(self, input_data: Input, *args, **kwargs) -> BlockOutput:
+        if input_data.value is not None:
+            yield "result", input_data.value
+
+
+class AgentOutputBlock(Block):
+    """
+    Records the output of the graph for users to see.
+
+    Behavior:
+        If `format` is provided and the `value` is of a type that can be formatted,
+        the block attempts to format the recorded_value using the `format`.
+        If formatting fails or no `format` is provided, the raw `value` is output.
+    """
+
+    class Input(BlockSchema):
+        value: Any = SchemaField(
+            description="The value to be recorded as output.",
+            default=None,
+            advanced=False,
+        )
+        name: str = SchemaField(description="The name of the output.")
+        title: str | None = SchemaField(
+            description="The title of the output.",
+            default=None,
+            advanced=True,
+        )
+        description: str | None = SchemaField(
+            description="The description of the output.",
+            default=None,
+            advanced=True,
+        )
+        format: str = SchemaField(
+            description="The format string to be used to format the recorded_value. Use Jinja2 syntax.",
+            default="",
+            advanced=True,
+        )
+        advanced: bool = SchemaField(
+            description="Whether to treat the output as advanced.",
+            default=False,
+            advanced=True,
+        )
+        secret: bool = SchemaField(
+            description="Whether the output should be treated as a secret.",
+            default=False,
+            advanced=True,
+        )
+
+        def generate_schema(self):
+            return self.get_field_schema("value")
+
+    class Output(BlockSchema):
+        output: Any = SchemaField(description="The value recorded as output.")
+        name: Any = SchemaField(description="The name of the value recorded as output.")
+
+    def __init__(self):
+        super().__init__(
+            id="363ae599-353e-4804-937e-b2ee3cef3da4",
+            description="Stores the output of the graph for users to see.",
+            input_schema=AgentOutputBlock.Input,
+            output_schema=AgentOutputBlock.Output,
+            test_input=[
+                {
+                    "value": "Hello, World!",
+                    "name": "output_1",
+                    "description": "This is a test output.",
+                    "format": "{{ output_1 }}!!",
+                },
+                {
+                    "value": "42",
+                    "name": "output_2",
+                    "description": "This is another test output.",
+                    "format": "{{ output_2 }}",
+                },
+                {
+                    "value": MockObject(value="!!", key="key"),
+                    "name": "output_3",
+                    "description": "This is a test output with a mock object.",
+                    "format": "{{ output_3 }}",
+                },
+            ],
+            test_output=[
+                ("output", "Hello, World!!!"),
+                ("output", "42"),
+                ("output", MockObject(value="!!", key="key")),
+            ],
+            categories={BlockCategory.OUTPUT, BlockCategory.BASIC},
+            block_type=BlockType.OUTPUT,
+            static_output=True,
+        )
+
+    def run(self, input_data: Input, *args, **kwargs) -> BlockOutput:
+        """
+        Attempts to format the recorded_value using the fmt_string if provided.
+        If formatting fails or no fmt_string is given, returns the original recorded_value.
+        """
+        if input_data.format:
+            try:
+                yield "output", formatter.format_string(
+                    input_data.format, {input_data.name: input_data.value}
+                )
+            except Exception as e:
+                yield "output", f"Error: {e}, {input_data.value}"
+        else:
+            yield "output", input_data.value
+            yield "name", input_data.name
+
+
+class AgentShortTextInputBlock(AgentInputBlock):
+    class Input(AgentInputBlock.Input):
+        value: Optional[ShortTextType] = SchemaField(
+            description="Short text input.",
+            default=None,
+            advanced=False,
+            title="Default Value",
+        )
+
+    class Output(AgentInputBlock.Output):
+        result: str = SchemaField(description="Short text result.")
+
+    def __init__(self):
+        super().__init__(
+            id="7fcd3bcb-8e1b-4e69-903d-32d3d4a92158",
+            description="Block for short text input (single-line).",
+            disabled=not config.enable_agent_input_subtype_blocks,
+            input_schema=AgentShortTextInputBlock.Input,
+            output_schema=AgentShortTextInputBlock.Output,
+            test_input=[
+                {
+                    "value": "Hello",
+                    "name": "short_text_1",
+                    "description": "Short text example 1",
+                    "placeholder_values": [],
+                },
+                {
+                    "value": "Quick test",
+                    "name": "short_text_2",
+                    "description": "Short text example 2",
+                    "placeholder_values": ["Quick test", "Another option"],
+                },
+            ],
+            test_output=[
+                ("result", "Hello"),
+                ("result", "Quick test"),
+            ],
+        )
+
+
+class AgentLongTextInputBlock(AgentInputBlock):
+    class Input(AgentInputBlock.Input):
+        value: Optional[LongTextType] = SchemaField(
+            description="Long text input (potentially multi-line).",
+            default=None,
+            advanced=False,
+            title="Default Value",
+        )
+
+    class Output(AgentInputBlock.Output):
+        result: str = SchemaField(description="Long text result.")
+
+    def __init__(self):
+        super().__init__(
+            id="90a56ffb-7024-4b2b-ab50-e26c5e5ab8ba",
+            description="Block for long text input (multi-line).",
+            disabled=not config.enable_agent_input_subtype_blocks,
+            input_schema=AgentLongTextInputBlock.Input,
+            output_schema=AgentLongTextInputBlock.Output,
+            test_input=[
+                {
+                    "value": "Lorem ipsum dolor sit amet...",
+                    "name": "long_text_1",
+                    "description": "Long text example 1",
+                    "placeholder_values": [],
+                },
+                {
+                    "value": "Another multiline text input.",
+                    "name": "long_text_2",
+                    "description": "Long text example 2",
+                    "placeholder_values": ["Another multiline text input."],
+                },
+            ],
+            test_output=[
+                ("result", "Lorem ipsum dolor sit amet..."),
+                ("result", "Another multiline text input."),
+            ],
+        )
+
+
+class AgentNumberInputBlock(AgentInputBlock):
+    class Input(AgentInputBlock.Input):
+        value: Optional[int] = SchemaField(
+            description="Number input.",
+            default=None,
+            advanced=False,
+            title="Default Value",
+        )
+
+    class Output(AgentInputBlock.Output):
+        result: int = SchemaField(description="Number result.")
+
+    def __init__(self):
+        super().__init__(
+            id="96dae2bb-97a2-41c2-bd2f-13a3b5a8ea98",
+            description="Block for number input.",
+            disabled=not config.enable_agent_input_subtype_blocks,
+            input_schema=AgentNumberInputBlock.Input,
+            output_schema=AgentNumberInputBlock.Output,
+            test_input=[
+                {
+                    "value": 42,
+                    "name": "number_input_1",
+                    "description": "Number example 1",
+                    "placeholder_values": [],
+                },
+                {
+                    "value": 314,
+                    "name": "number_input_2",
+                    "description": "Number example 2",
+                    "placeholder_values": [314, 2718],
+                },
+            ],
+            test_output=[
+                ("result", 42),
+                ("result", 314),
+            ],
+        )
+
+
+class AgentDateInputBlock(AgentInputBlock):
+    class Input(AgentInputBlock.Input):
+        value: Optional[date] = SchemaField(
+            description="Date input (YYYY-MM-DD).",
+            default=None,
+            advanced=False,
+            title="Default Value",
+        )
+
+    class Output(AgentInputBlock.Output):
+        result: date = SchemaField(description="Date result.")
+
+    def __init__(self):
+        super().__init__(
+            id="7e198b09-4994-47db-8b4d-952d98241817",
+            description="Block for date input.",
+            disabled=not config.enable_agent_input_subtype_blocks,
+            input_schema=AgentDateInputBlock.Input,
+            output_schema=AgentDateInputBlock.Output,
+            test_input=[
+                {
+                    # If your system can parse JSON date strings to date objects
+                    "value": str(date(2025, 3, 19)),
+                    "name": "date_input_1",
+                    "description": "Example date input 1",
+                },
+                {
+                    "value": str(date(2023, 12, 31)),
+                    "name": "date_input_2",
+                    "description": "Example date input 2",
+                },
+            ],
+            test_output=[
+                ("result", date(2025, 3, 19)),
+                ("result", date(2023, 12, 31)),
+            ],
+        )
+
+
+class AgentTimeInputBlock(AgentInputBlock):
+    class Input(AgentInputBlock.Input):
+        value: Optional[time] = SchemaField(
+            description="Time input (HH:MM:SS).",
+            default=None,
+            advanced=False,
+            title="Default Value",
+        )
+
+    class Output(AgentInputBlock.Output):
+        result: time = SchemaField(description="Time result.")
+
+    def __init__(self):
+        super().__init__(
+            id="2a1c757e-86cf-4c7e-aacf-060dc382e434",
+            description="Block for time input.",
+            disabled=not config.enable_agent_input_subtype_blocks,
+            input_schema=AgentTimeInputBlock.Input,
+            output_schema=AgentTimeInputBlock.Output,
+            test_input=[
+                {
+                    "value": str(time(9, 30, 0)),
+                    "name": "time_input_1",
+                    "description": "Time example 1",
+                },
+                {
+                    "value": str(time(23, 59, 59)),
+                    "name": "time_input_2",
+                    "description": "Time example 2",
+                },
+            ],
+            test_output=[
+                ("result", time(9, 30, 0)),
+                ("result", time(23, 59, 59)),
+            ],
+        )
+
+
+class AgentFileInputBlock(AgentInputBlock):
+    """
+    A simplified file-upload block. In real usage, you might have a custom
+    file type or handle binary data. Here, we'll store a string path as the example.
+    """
+
+    class Input(AgentInputBlock.Input):
+        value: Optional[MediaFileType] = SchemaField(
+            description="Path or reference to an uploaded file.",
+            default=None,
+            advanced=False,
+            title="Default Value",
+        )
+
+    class Output(AgentInputBlock.Output):
+        result: str = SchemaField(description="File reference/path result.")
+
+    def __init__(self):
+        super().__init__(
+            id="95ead23f-8283-4654-aef3-10c053b74a31",
+            description="Block for file upload input (string path for example).",
+            disabled=not config.enable_agent_input_subtype_blocks,
+            input_schema=AgentFileInputBlock.Input,
+            output_schema=AgentFileInputBlock.Output,
+            test_input=[
+                {
+                    "value": "data:image/png;base64,MQ==",
+                    "name": "file_upload_1",
+                    "description": "Example file upload 1",
+                },
+            ],
+            test_output=[
+                ("result", str),
+            ],
+        )
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        graph_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        if not input_data.value:
+            return
+
+        file_path = store_media_file(
+            graph_exec_id=graph_exec_id,
+            file=input_data.value,
+            return_content=False,
+        )
+        yield "result", file_path
+
+
+class AgentDropdownInputBlock(AgentInputBlock):
+    """
+    A specialized text input block that relies on placeholder_values to present a dropdown.
+    """
+
+    class Input(AgentInputBlock.Input):
+        value: Optional[str] = SchemaField(
+            description="Text selected from a dropdown.",
+            default=None,
+            advanced=False,
+            title="Default Value",
+        )
+        placeholder_values: list = SchemaField(
+            description="Possible values for the dropdown.",
+            default_factory=list,
+            advanced=False,
+            title="Dropdown Options",
+        )
+
+    class Output(AgentInputBlock.Output):
+        result: str = SchemaField(description="Selected dropdown value.")
+
+    def __init__(self):
+        super().__init__(
+            id="655d6fdf-a334-421c-b733-520549c07cd1",
+            description="Block for dropdown text selection.",
+            disabled=not config.enable_agent_input_subtype_blocks,
+            input_schema=AgentDropdownInputBlock.Input,
+            output_schema=AgentDropdownInputBlock.Output,
+            test_input=[
+                {
+                    "value": "Option A",
+                    "name": "dropdown_1",
+                    "placeholder_values": ["Option A", "Option B", "Option C"],
+                    "description": "Dropdown example 1",
+                },
+                {
+                    "value": "Option C",
+                    "name": "dropdown_2",
+                    "placeholder_values": ["Option A", "Option B", "Option C"],
+                    "description": "Dropdown example 2",
+                },
+            ],
+            test_output=[
+                ("result", "Option A"),
+                ("result", "Option C"),
+            ],
+        )
+
+
+class AgentToggleInputBlock(AgentInputBlock):
+    class Input(AgentInputBlock.Input):
+        value: bool = SchemaField(
+            description="Boolean toggle input.",
+            default=False,
+            advanced=False,
+            title="Default Value",
+        )
+
+    class Output(AgentInputBlock.Output):
+        result: bool = SchemaField(description="Boolean toggle result.")
+
+    def __init__(self):
+        super().__init__(
+            id="cbf36ab5-df4a-43b6-8a7f-f7ed8652116e",
+            description="Block for boolean toggle input.",
+            disabled=not config.enable_agent_input_subtype_blocks,
+            input_schema=AgentToggleInputBlock.Input,
+            output_schema=AgentToggleInputBlock.Output,
+            test_input=[
+                {
+                    "value": True,
+                    "name": "toggle_1",
+                    "description": "Toggle example 1",
+                },
+                {
+                    "value": False,
+                    "name": "toggle_2",
+                    "description": "Toggle example 2",
+                },
+            ],
+            test_output=[
+                ("result", True),
+                ("result", False),
+            ],
+        )
+
+
+IO_BLOCK_IDs = [
+    AgentInputBlock().id,
+    AgentOutputBlock().id,
+    AgentShortTextInputBlock().id,
+    AgentLongTextInputBlock().id,
+    AgentNumberInputBlock().id,
+    AgentDateInputBlock().id,
+    AgentTimeInputBlock().id,
+    AgentFileInputBlock().id,
+    AgentDropdownInputBlock().id,
+    AgentToggleInputBlock().id,
+]

autogpt_platform/backend/backend/blocks/iteration.py

@@ -11,13 +11,13 @@ class StepThroughItemsBlock(Block):
             advanced=False,
             description="The list or dictionary of items to iterate over",
             placeholder="[1, 2, 3, 4, 5] or {'key1': 'value1', 'key2': 'value2'}",
-            default=[],
+            default_factory=list,
         )
         items_object: dict = SchemaField(
             advanced=False,
             description="The list or dictionary of items to iterate over",
             placeholder="[1, 2, 3, 4, 5] or {'key1': 'value1', 'key2': 'value2'}",
-            default={},
+            default_factory=dict,
         )
         items_str: str = SchemaField(
             advanced=False,

autogpt_platform/backend/backend/blocks/jina/chunking.py

@@ -23,7 +23,7 @@ class JinaChunkingBlock(Block):
     class Output(BlockSchema):
         chunks: list = SchemaField(description="List of chunked texts")
         tokens: list = SchemaField(
-            description="List of token information for each chunk", optional=True
+            description="List of token information for each chunk",
         )
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/jina/search.py

@@ -1,4 +1,4 @@
-from groq._utils._utils import quote
+from urllib.parse import quote
 
 from backend.blocks.jina._auth import (
     TEST_CREDENTIALS,

autogpt_platform/backend/backend/blocks/linear/issues.py

@@ -28,8 +28,8 @@ class LinearCreateIssueBlock(Block):
         priority: int | None = SchemaField(
             description="Priority of the issue",
             default=None,
-            minimum=0,
-            maximum=4,
+            ge=0,
+            le=4,
         )
         project_name: str | None = SchemaField(
             description="Name of the project to create the issue on",

autogpt_platform/backend/backend/blocks/llm.py

@@ -4,32 +4,30 @@ from abc import ABC
 from enum import Enum, EnumMeta
 from json import JSONDecodeError
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, List, Literal, NamedTuple
-
-from pydantic import SecretStr
-
-from backend.integrations.providers import ProviderName
-
-if TYPE_CHECKING:
-    from enum import _EnumMemberT
+from typing import Any, Iterable, List, Literal, NamedTuple, Optional
 
 import anthropic
 import ollama
 import openai
+from anthropic.types import ToolParam
 from groq import Groq
+from pydantic import BaseModel, SecretStr
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
     CredentialsMetaInput,
+    NodeExecutionStats,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 from backend.util import json
+from backend.util.logging import TruncatedLogger
 from backend.util.settings import BehaveAs, Settings
 from backend.util.text import TextFormatter
 
-logger = logging.getLogger(__name__)
+logger = TruncatedLogger(logging.getLogger(__name__), "[LLM-Block]")
 fmt = TextFormatter()
 
 LLMProviderName = Literal[
@@ -38,6 +36,7 @@ LLMProviderName = Literal[
     ProviderName.OLLAMA,
     ProviderName.OPENAI,
     ProviderName.OPEN_ROUTER,
+    ProviderName.LLAMA_API,
 ]
 AICredentials = CredentialsMetaInput[LLMProviderName, Literal["api_key"]]
 
@@ -74,12 +73,10 @@ class ModelMetadata(NamedTuple):
 
 class LlmModelMeta(EnumMeta):
     @property
-    def __members__(
-        self: type["_EnumMemberT"],
-    ) -> MappingProxyType[str, "_EnumMemberT"]:
+    def __members__(self) -> MappingProxyType:
         if Settings().config.behave_as == BehaveAs.LOCAL:
             members = super().__members__
-            return members
+            return MappingProxyType(members)
         else:
             removed_providers = ["ollama"]
             existing_members = super().__members__
@@ -94,14 +91,17 @@ class LlmModelMeta(EnumMeta):
 class LlmModel(str, Enum, metaclass=LlmModelMeta):
     # OpenAI models
     O3_MINI = "o3-mini"
+    O3 = "o3-2025-04-16"
     O1 = "o1"
     O1_PREVIEW = "o1-preview"
     O1_MINI = "o1-mini"
+    GPT41 = "gpt-4.1-2025-04-14"
     GPT4O_MINI = "gpt-4o-mini"
     GPT4O = "gpt-4o"
     GPT4_TURBO = "gpt-4-turbo"
     GPT3_5_TURBO = "gpt-3.5-turbo"
     # Anthropic models
+    CLAUDE_3_7_SONNET = "claude-3-7-sonnet-20250219"
     CLAUDE_3_5_SONNET = "claude-3-5-sonnet-latest"
     CLAUDE_3_5_HAIKU = "claude-3-5-haiku-latest"
     CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
@@ -122,6 +122,7 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     OLLAMA_DOLPHIN = "dolphin-mistral:latest"
     # OpenRouter models
     GEMINI_FLASH_1_5 = "google/gemini-flash-1.5"
+    GEMINI_2_5_PRO = "google/gemini-2.5-pro-preview-03-25"
     GROK_BETA = "x-ai/grok-beta"
     MISTRAL_NEMO = "mistralai/mistral-nemo"
     COHERE_COMMAND_R_08_2024 = "cohere/command-r-08-2024"
@@ -139,6 +140,13 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     AMAZON_NOVA_PRO_V1 = "amazon/nova-pro-v1"
     MICROSOFT_WIZARDLM_2_8X22B = "microsoft/wizardlm-2-8x22b"
     GRYPHE_MYTHOMAX_L2_13B = "gryphe/mythomax-l2-13b"
+    META_LLAMA_4_SCOUT = "meta-llama/llama-4-scout"
+    META_LLAMA_4_MAVERICK = "meta-llama/llama-4-maverick"
+    # Llama API models
+    LLAMA_API_LLAMA_4_SCOUT = "Llama-4-Scout-17B-16E-Instruct-FP8"
+    LLAMA_API_LLAMA4_MAVERICK = "Llama-4-Maverick-17B-128E-Instruct-FP8"
+    LLAMA_API_LLAMA3_3_8B = "Llama-3.3-8B-Instruct"
+    LLAMA_API_LLAMA3_3_70B = "Llama-3.3-70B-Instruct"
 
     @property
     def metadata(self) -> ModelMetadata:
@@ -159,12 +167,14 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
 
 MODEL_METADATA = {
     # https://platform.openai.com/docs/models
+    LlmModel.O3: ModelMetadata("openai", 200000, 100000),
     LlmModel.O3_MINI: ModelMetadata("openai", 200000, 100000),  # o3-mini-2025-01-31
     LlmModel.O1: ModelMetadata("openai", 200000, 100000),  # o1-2024-12-17
     LlmModel.O1_PREVIEW: ModelMetadata(
         "openai", 128000, 32768
     ),  # o1-preview-2024-09-12
     LlmModel.O1_MINI: ModelMetadata("openai", 128000, 65536),  # o1-mini-2024-09-12
+    LlmModel.GPT41: ModelMetadata("openai", 1047576, 32768),
     LlmModel.GPT4O_MINI: ModelMetadata(
         "openai", 128000, 16384
     ),  # gpt-4o-mini-2024-07-18
@@ -174,6 +184,9 @@ MODEL_METADATA = {
     ),  # gpt-4-turbo-2024-04-09
     LlmModel.GPT3_5_TURBO: ModelMetadata("openai", 16385, 4096),  # gpt-3.5-turbo-0125
     # https://docs.anthropic.com/en/docs/about-claude/models
+    LlmModel.CLAUDE_3_7_SONNET: ModelMetadata(
+        "anthropic", 200000, 8192
+    ),  # claude-3-7-sonnet-20250219
     LlmModel.CLAUDE_3_5_SONNET: ModelMetadata(
         "anthropic", 200000, 8192
     ),  # claude-3-5-sonnet-20241022
@@ -199,6 +212,7 @@ MODEL_METADATA = {
     LlmModel.OLLAMA_DOLPHIN: ModelMetadata("ollama", 32768, None),
     # https://openrouter.ai/models
     LlmModel.GEMINI_FLASH_1_5: ModelMetadata("open_router", 1000000, 8192),
+    LlmModel.GEMINI_2_5_PRO: ModelMetadata("open_router", 1050000, 8192),
     LlmModel.GROK_BETA: ModelMetadata("open_router", 131072, 131072),
     LlmModel.MISTRAL_NEMO: ModelMetadata("open_router", 128000, 4096),
     LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata("open_router", 128000, 4096),
@@ -220,6 +234,13 @@ MODEL_METADATA = {
     LlmModel.AMAZON_NOVA_PRO_V1: ModelMetadata("open_router", 300000, 5120),
     LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata("open_router", 65536, 4096),
     LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata("open_router", 4096, 4096),
+    LlmModel.META_LLAMA_4_SCOUT: ModelMetadata("open_router", 131072, 131072),
+    LlmModel.META_LLAMA_4_MAVERICK: ModelMetadata("open_router", 1048576, 1000000),
+    # Llama API models
+    LlmModel.LLAMA_API_LLAMA_4_SCOUT: ModelMetadata("llama_api", 128000, 4028),
+    LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata("llama_api", 128000, 4028),
+    LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata("llama_api", 128000, 4028),
+    LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata("llama_api", 128000, 4028),
 }
 
 for model in LlmModel:
@@ -227,21 +248,374 @@ for model in LlmModel:
         raise ValueError(f"Missing MODEL_METADATA metadata for model: {model}")
 
 
-class MessageRole(str, Enum):
-    SYSTEM = "system"
-    USER = "user"
-    ASSISTANT = "assistant"
+class ToolCall(BaseModel):
+    name: str
+    arguments: str
 
 
-class Message(BlockSchema):
-    role: MessageRole
-    content: str
+class ToolContentBlock(BaseModel):
+    id: str
+    type: str
+    function: ToolCall
+
+
+class LLMResponse(BaseModel):
+    raw_response: Any
+    prompt: List[Any]
+    response: str
+    tool_calls: Optional[List[ToolContentBlock]] | None
+    prompt_tokens: int
+    completion_tokens: int
+
+
+def convert_openai_tool_fmt_to_anthropic(
+    openai_tools: list[dict] | None = None,
+) -> Iterable[ToolParam] | anthropic.NotGiven:
+    """
+    Convert OpenAI tool format to Anthropic tool format.
+    """
+    if not openai_tools or len(openai_tools) == 0:
+        return anthropic.NOT_GIVEN
+
+    anthropic_tools = []
+    for tool in openai_tools:
+        if "function" in tool:
+            # Handle case where tool is already in OpenAI format with "type" and "function"
+            function_data = tool["function"]
+        else:
+            # Handle case where tool is just the function definition
+            function_data = tool
+
+        anthropic_tool: anthropic.types.ToolParam = {
+            "name": function_data["name"],
+            "description": function_data.get("description", ""),
+            "input_schema": {
+                "type": "object",
+                "properties": function_data.get("parameters", {}).get("properties", {}),
+                "required": function_data.get("parameters", {}).get("required", []),
+            },
+        }
+        anthropic_tools.append(anthropic_tool)
+
+    return anthropic_tools
+
+
+def estimate_token_count(prompt_messages: list[dict]) -> int:
+    char_count = sum(len(str(msg.get("content", ""))) for msg in prompt_messages)
+    message_overhead = len(prompt_messages) * 4
+    estimated_tokens = (char_count // 4) + message_overhead
+    return int(estimated_tokens * 1.2)
+
+
+def llm_call(
+    credentials: APIKeyCredentials,
+    llm_model: LlmModel,
+    prompt: list[dict],
+    json_format: bool,
+    max_tokens: int | None,
+    tools: list[dict] | None = None,
+    ollama_host: str = "localhost:11434",
+    parallel_tool_calls: bool | None = None,
+) -> LLMResponse:
+    """
+    Make a call to a language model.
+
+    Args:
+        credentials: The API key credentials to use.
+        llm_model: The LLM model to use.
+        prompt: The prompt to send to the LLM.
+        json_format: Whether the response should be in JSON format.
+        max_tokens: The maximum number of tokens to generate in the chat completion.
+        tools: The tools to use in the chat completion.
+        ollama_host: The host for ollama to use.
+
+    Returns:
+        LLMResponse object containing:
+            - prompt: The prompt sent to the LLM.
+            - response: The text response from the LLM.
+            - tool_calls: Any tool calls the model made, if applicable.
+            - prompt_tokens: The number of tokens used in the prompt.
+            - completion_tokens: The number of tokens used in the completion.
+    """
+    provider = llm_model.metadata.provider
+
+    # Calculate available tokens based on context window and input length
+    estimated_input_tokens = estimate_token_count(prompt)
+    context_window = llm_model.context_window
+    model_max_output = llm_model.max_output_tokens or 4096
+    user_max = max_tokens or model_max_output
+    available_tokens = max(context_window - estimated_input_tokens, 0)
+    max_tokens = max(min(available_tokens, model_max_output, user_max), 0)
+
+    if provider == "openai":
+        tools_param = tools if tools else openai.NOT_GIVEN
+        oai_client = openai.OpenAI(api_key=credentials.api_key.get_secret_value())
+        response_format = None
+
+        if llm_model in [LlmModel.O1_MINI, LlmModel.O1_PREVIEW]:
+            sys_messages = [p["content"] for p in prompt if p["role"] == "system"]
+            usr_messages = [p["content"] for p in prompt if p["role"] != "system"]
+            prompt = [
+                {"role": "user", "content": "\n".join(sys_messages)},
+                {"role": "user", "content": "\n".join(usr_messages)},
+            ]
+        elif json_format:
+            response_format = {"type": "json_object"}
+
+        response = oai_client.chat.completions.create(
+            model=llm_model.value,
+            messages=prompt,  # type: ignore
+            response_format=response_format,  # type: ignore
+            max_completion_tokens=max_tokens,
+            tools=tools_param,  # type: ignore
+            parallel_tool_calls=(
+                openai.NOT_GIVEN if parallel_tool_calls is None else parallel_tool_calls
+            ),
+        )
+
+        if response.choices[0].message.tool_calls:
+            tool_calls = [
+                ToolContentBlock(
+                    id=tool.id,
+                    type=tool.type,
+                    function=ToolCall(
+                        name=tool.function.name,
+                        arguments=tool.function.arguments,
+                    ),
+                )
+                for tool in response.choices[0].message.tool_calls
+            ]
+        else:
+            tool_calls = None
+
+        return LLMResponse(
+            raw_response=response.choices[0].message,
+            prompt=prompt,
+            response=response.choices[0].message.content or "",
+            tool_calls=tool_calls,
+            prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
+            completion_tokens=response.usage.completion_tokens if response.usage else 0,
+        )
+    elif provider == "anthropic":
+
+        an_tools = convert_openai_tool_fmt_to_anthropic(tools)
+
+        system_messages = [p["content"] for p in prompt if p["role"] == "system"]
+        sysprompt = " ".join(system_messages)
+
+        messages = []
+        last_role = None
+        for p in prompt:
+            if p["role"] in ["user", "assistant"]:
+                if (
+                    p["role"] == last_role
+                    and isinstance(messages[-1]["content"], str)
+                    and isinstance(p["content"], str)
+                ):
+                    # If the role is the same as the last one, combine the content
+                    messages[-1]["content"] += p["content"]
+                else:
+                    messages.append({"role": p["role"], "content": p["content"]})
+                    last_role = p["role"]
+
+        client = anthropic.Anthropic(api_key=credentials.api_key.get_secret_value())
+        try:
+            resp = client.messages.create(
+                model=llm_model.value,
+                system=sysprompt,
+                messages=messages,
+                max_tokens=max_tokens,
+                tools=an_tools,
+            )
+
+            if not resp.content:
+                raise ValueError("No content returned from Anthropic.")
+
+            tool_calls = None
+            for content_block in resp.content:
+                # Antropic is different to openai, need to iterate through
+                # the content blocks to find the tool calls
+                if content_block.type == "tool_use":
+                    if tool_calls is None:
+                        tool_calls = []
+                    tool_calls.append(
+                        ToolContentBlock(
+                            id=content_block.id,
+                            type=content_block.type,
+                            function=ToolCall(
+                                name=content_block.name,
+                                arguments=json.dumps(content_block.input),
+                            ),
+                        )
+                    )
+
+            if not tool_calls and resp.stop_reason == "tool_use":
+                logger.warning(
+                    f"Tool use stop reason but no tool calls found in content. {resp}"
+                )
+
+            return LLMResponse(
+                raw_response=resp,
+                prompt=prompt,
+                response=(
+                    resp.content[0].name
+                    if isinstance(resp.content[0], anthropic.types.ToolUseBlock)
+                    else getattr(resp.content[0], "text", "")
+                ),
+                tool_calls=tool_calls,
+                prompt_tokens=resp.usage.input_tokens,
+                completion_tokens=resp.usage.output_tokens,
+            )
+        except anthropic.APIError as e:
+            error_message = f"Anthropic API error: {str(e)}"
+            logger.error(error_message)
+            raise ValueError(error_message)
+    elif provider == "groq":
+        if tools:
+            raise ValueError("Groq does not support tools.")
+
+        client = Groq(api_key=credentials.api_key.get_secret_value())
+        response_format = {"type": "json_object"} if json_format else None
+        response = client.chat.completions.create(
+            model=llm_model.value,
+            messages=prompt,  # type: ignore
+            response_format=response_format,  # type: ignore
+            max_tokens=max_tokens,
+        )
+        return LLMResponse(
+            raw_response=response.choices[0].message,
+            prompt=prompt,
+            response=response.choices[0].message.content or "",
+            tool_calls=None,
+            prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
+            completion_tokens=response.usage.completion_tokens if response.usage else 0,
+        )
+    elif provider == "ollama":
+        if tools:
+            raise ValueError("Ollama does not support tools.")
+
+        client = ollama.Client(host=ollama_host)
+        sys_messages = [p["content"] for p in prompt if p["role"] == "system"]
+        usr_messages = [p["content"] for p in prompt if p["role"] != "system"]
+        response = client.generate(
+            model=llm_model.value,
+            prompt=f"{sys_messages}\n\n{usr_messages}",
+            stream=False,
+            options={"num_ctx": max_tokens},
+        )
+        return LLMResponse(
+            raw_response=response.get("response") or "",
+            prompt=prompt,
+            response=response.get("response") or "",
+            tool_calls=None,
+            prompt_tokens=response.get("prompt_eval_count") or 0,
+            completion_tokens=response.get("eval_count") or 0,
+        )
+    elif provider == "open_router":
+        tools_param = tools if tools else openai.NOT_GIVEN
+        client = openai.OpenAI(
+            base_url="https://openrouter.ai/api/v1",
+            api_key=credentials.api_key.get_secret_value(),
+        )
+
+        response = client.chat.completions.create(
+            extra_headers={
+                "HTTP-Referer": "https://agpt.co",
+                "X-Title": "AutoGPT",
+            },
+            model=llm_model.value,
+            messages=prompt,  # type: ignore
+            max_tokens=max_tokens,
+            tools=tools_param,  # type: ignore
+        )
+
+        # If there's no response, raise an error
+        if not response.choices:
+            if response:
+                raise ValueError(f"OpenRouter error: {response}")
+            else:
+                raise ValueError("No response from OpenRouter.")
+
+        if response.choices[0].message.tool_calls:
+            tool_calls = [
+                ToolContentBlock(
+                    id=tool.id,
+                    type=tool.type,
+                    function=ToolCall(
+                        name=tool.function.name, arguments=tool.function.arguments
+                    ),
+                )
+                for tool in response.choices[0].message.tool_calls
+            ]
+        else:
+            tool_calls = None
+
+        return LLMResponse(
+            raw_response=response.choices[0].message,
+            prompt=prompt,
+            response=response.choices[0].message.content or "",
+            tool_calls=tool_calls,
+            prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
+            completion_tokens=response.usage.completion_tokens if response.usage else 0,
+        )
+    elif provider == "llama_api":
+        tools_param = tools if tools else openai.NOT_GIVEN
+        client = openai.OpenAI(
+            base_url="https://api.llama.com/compat/v1/",
+            api_key=credentials.api_key.get_secret_value(),
+        )
+
+        response = client.chat.completions.create(
+            extra_headers={
+                "HTTP-Referer": "https://agpt.co",
+                "X-Title": "AutoGPT",
+            },
+            model=llm_model.value,
+            messages=prompt,  # type: ignore
+            max_tokens=max_tokens,
+            tools=tools_param,  # type: ignore
+            parallel_tool_calls=(
+                openai.NOT_GIVEN if parallel_tool_calls is None else parallel_tool_calls
+            ),
+        )
+
+        # If there's no response, raise an error
+        if not response.choices:
+            if response:
+                raise ValueError(f"Llama API error: {response}")
+            else:
+                raise ValueError("No response from Llama API.")
+
+        if response.choices[0].message.tool_calls:
+            tool_calls = [
+                ToolContentBlock(
+                    id=tool.id,
+                    type=tool.type,
+                    function=ToolCall(
+                        name=tool.function.name, arguments=tool.function.arguments
+                    ),
+                )
+                for tool in response.choices[0].message.tool_calls
+            ]
+        else:
+            tool_calls = None
+
+        return LLMResponse(
+            raw_response=response.choices[0].message,
+            prompt=prompt,
+            response=response.choices[0].message.content or "",
+            tool_calls=tool_calls,
+            prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
+            completion_tokens=response.usage.completion_tokens if response.usage else 0,
+        )
+    else:
+        raise ValueError(f"Unsupported LLM provider: {provider}")
 
 
 class AIBlockBase(Block, ABC):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        self.prompt = ""
+        self.prompt = []
 
     def merge_llm_stats(self, block: "AIBlockBase"):
         self.merge_stats(block.execution_stats)
@@ -260,7 +634,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4_TURBO,
+            default=LlmModel.GPT4O,
             description="The language model to use for answering the prompt.",
             advanced=False,
         )
@@ -270,8 +644,8 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             default="",
             description="The system prompt to provide additional context to the model.",
         )
-        conversation_history: list[Message] = SchemaField(
-            default=[],
+        conversation_history: list[dict] = SchemaField(
+            default_factory=list,
             description="The conversation history to provide context for the prompt.",
         )
         retry: int = SchemaField(
@@ -281,7 +655,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         )
         prompt_values: dict[str, str] = SchemaField(
             advanced=False,
-            default={},
+            default_factory=dict,
             description="Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}.",
         )
         max_tokens: int | None = SchemaField(
@@ -300,7 +674,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         response: dict[str, Any] = SchemaField(
             description="The response object generated by the language model."
         )
-        prompt: str = SchemaField(description="The prompt sent to the language model.")
+        prompt: list = SchemaField(description="The prompt sent to the language model.")
         error: str = SchemaField(description="Error message if the API call failed.")
 
     def __init__(self):
@@ -311,7 +685,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             input_schema=AIStructuredResponseGeneratorBlock.Input,
             output_schema=AIStructuredResponseGeneratorBlock.Output,
             test_input={
-                "model": LlmModel.GPT4_TURBO,
+                "model": LlmModel.GPT4O,
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "expected_format": {
                     "key1": "value1",
@@ -322,22 +696,24 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             test_credentials=TEST_CREDENTIALS,
             test_output=[
                 ("response", {"key1": "key1Value", "key2": "key2Value"}),
-                ("prompt", str),
+                ("prompt", list),
             ],
             test_mock={
-                "llm_call": lambda *args, **kwargs: (
-                    json.dumps(
+                "llm_call": lambda *args, **kwargs: LLMResponse(
+                    raw_response="",
+                    prompt=[""],
+                    response=json.dumps(
                         {
                             "key1": "key1Value",
                             "key2": "key2Value",
                         }
                     ),
-                    0,
-                    0,
+                    tool_calls=None,
+                    prompt_tokens=0,
+                    completion_tokens=0,
                 )
             },
         )
-        self.prompt = ""
 
     def llm_call(
         self,
@@ -346,160 +722,29 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         prompt: list[dict],
         json_format: bool,
         max_tokens: int | None,
+        tools: list[dict] | None = None,
         ollama_host: str = "localhost:11434",
-    ) -> tuple[str, int, int]:
+    ) -> LLMResponse:
         """
-        Args:
-            credentials: The API key credentials to use.
-            llm_model: The LLM model to use.
-            prompt: The prompt to send to the LLM.
-            json_format: Whether the response should be in JSON format.
-            max_tokens: The maximum number of tokens to generate in the chat completion.
-            ollama_host: The host for ollama to use
-
-        Returns:
-            The response from the LLM.
-            The number of tokens used in the prompt.
-            The number of tokens used in the completion.
+        Test mocks work only on class functions, this wraps the llm_call function
+        so that it can be mocked withing the block testing framework.
         """
-        provider = llm_model.metadata.provider
-        max_tokens = max_tokens or llm_model.max_output_tokens or 4096
-
-        if provider == "openai":
-            oai_client = openai.OpenAI(api_key=credentials.api_key.get_secret_value())
-            response_format = None
-
-            if llm_model in [LlmModel.O1_MINI, LlmModel.O1_PREVIEW]:
-                sys_messages = [p["content"] for p in prompt if p["role"] == "system"]
-                usr_messages = [p["content"] for p in prompt if p["role"] != "system"]
-                prompt = [
-                    {"role": "user", "content": "\n".join(sys_messages)},
-                    {"role": "user", "content": "\n".join(usr_messages)},
-                ]
-            elif json_format:
-                response_format = {"type": "json_object"}
-
-            response = oai_client.chat.completions.create(
-                model=llm_model.value,
-                messages=prompt,  # type: ignore
-                response_format=response_format,  # type: ignore
-                max_completion_tokens=max_tokens,
-            )
-            self.prompt = json.dumps(prompt)
-
-            return (
-                response.choices[0].message.content or "",
-                response.usage.prompt_tokens if response.usage else 0,
-                response.usage.completion_tokens if response.usage else 0,
-            )
-        elif provider == "anthropic":
-            system_messages = [p["content"] for p in prompt if p["role"] == "system"]
-            sysprompt = " ".join(system_messages)
-
-            messages = []
-            last_role = None
-            for p in prompt:
-                if p["role"] in ["user", "assistant"]:
-                    if p["role"] != last_role:
-                        messages.append({"role": p["role"], "content": p["content"]})
-                        last_role = p["role"]
-                    else:
-                        # If the role is the same as the last one, combine the content
-                        messages[-1]["content"] += "\n" + p["content"]
-
-            client = anthropic.Anthropic(api_key=credentials.api_key.get_secret_value())
-            try:
-                resp = client.messages.create(
-                    model=llm_model.value,
-                    system=sysprompt,
-                    messages=messages,
-                    max_tokens=max_tokens,
-                )
-                self.prompt = json.dumps(prompt)
-
-                if not resp.content:
-                    raise ValueError("No content returned from Anthropic.")
-
-                return (
-                    (
-                        resp.content[0].name
-                        if isinstance(resp.content[0], anthropic.types.ToolUseBlock)
-                        else resp.content[0].text
-                    ),
-                    resp.usage.input_tokens,
-                    resp.usage.output_tokens,
-                )
-            except anthropic.APIError as e:
-                error_message = f"Anthropic API error: {str(e)}"
-                logger.error(error_message)
-                raise ValueError(error_message)
-        elif provider == "groq":
-            client = Groq(api_key=credentials.api_key.get_secret_value())
-            response_format = {"type": "json_object"} if json_format else None
-            response = client.chat.completions.create(
-                model=llm_model.value,
-                messages=prompt,  # type: ignore
-                response_format=response_format,  # type: ignore
-                max_tokens=max_tokens,
-            )
-            self.prompt = json.dumps(prompt)
-            return (
-                response.choices[0].message.content or "",
-                response.usage.prompt_tokens if response.usage else 0,
-                response.usage.completion_tokens if response.usage else 0,
-            )
-        elif provider == "ollama":
-            client = ollama.Client(host=ollama_host)
-            sys_messages = [p["content"] for p in prompt if p["role"] == "system"]
-            usr_messages = [p["content"] for p in prompt if p["role"] != "system"]
-            response = client.generate(
-                model=llm_model.value,
-                prompt=f"{sys_messages}\n\n{usr_messages}",
-                stream=False,
-            )
-            self.prompt = json.dumps(prompt)
-            return (
-                response.get("response") or "",
-                response.get("prompt_eval_count") or 0,
-                response.get("eval_count") or 0,
-            )
-        elif provider == "open_router":
-            client = openai.OpenAI(
-                base_url="https://openrouter.ai/api/v1",
-                api_key=credentials.api_key.get_secret_value(),
-            )
-
-            response = client.chat.completions.create(
-                extra_headers={
-                    "HTTP-Referer": "https://agpt.co",
-                    "X-Title": "AutoGPT",
-                },
-                model=llm_model.value,
-                messages=prompt,  # type: ignore
-                max_tokens=max_tokens,
-            )
-            self.prompt = json.dumps(prompt)
-
-            # If there's no response, raise an error
-            if not response.choices:
-                if response:
-                    raise ValueError(f"OpenRouter error: {response}")
-                else:
-                    raise ValueError("No response from OpenRouter.")
-
-            return (
-                response.choices[0].message.content or "",
-                response.usage.prompt_tokens if response.usage else 0,
-                response.usage.completion_tokens if response.usage else 0,
-            )
-        else:
-            raise ValueError(f"Unsupported LLM provider: {provider}")
+        self.prompt = prompt
+        return llm_call(
+            credentials=credentials,
+            llm_model=llm_model,
+            prompt=prompt,
+            json_format=json_format,
+            max_tokens=max_tokens,
+            tools=tools,
+            ollama_host=ollama_host,
+        )
 
     def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         logger.debug(f"Calling LLM with input data: {input_data}")
-        prompt = [p.model_dump() for p in input_data.conversation_history]
+        prompt = [json.to_dict(p) for p in input_data.conversation_history]
 
         def trim_prompt(s: str) -> str:
             lines = s.strip().split("\n")
@@ -549,7 +794,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
 
         for retry_count in range(input_data.retry):
             try:
-                response_text, input_token, output_token = self.llm_call(
+                llm_response = self.llm_call(
                     credentials=credentials,
                     llm_model=llm_model,
                     prompt=prompt,
@@ -557,11 +802,12 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                     ollama_host=input_data.ollama_host,
                     max_tokens=input_data.max_tokens,
                 )
+                response_text = llm_response.response
                 self.merge_stats(
-                    {
-                        "input_token_count": input_token,
-                        "output_token_count": output_token,
-                    }
+                    NodeExecutionStats(
+                        input_token_count=llm_response.prompt_tokens,
+                        output_token_count=llm_response.completion_tokens,
+                    )
                 )
                 logger.info(f"LLM attempt-{retry_count} response: {response_text}")
 
@@ -601,13 +847,23 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                 prompt.append({"role": "user", "content": retry_prompt})
             except Exception as e:
                 logger.exception(f"Error calling LLM: {e}")
+                if (
+                    "maximum context length" in str(e).lower()
+                    or "token limit" in str(e).lower()
+                ):
+                    if input_data.max_tokens is None:
+                        input_data.max_tokens = llm_model.max_output_tokens or 4096
+                    input_data.max_tokens = int(input_data.max_tokens * 0.85)
+                    logger.debug(
+                        f"Reducing max_tokens to {input_data.max_tokens} for next attempt"
+                    )
                 retry_prompt = f"Error calling LLM: {e}"
             finally:
                 self.merge_stats(
-                    {
-                        "llm_call_count": retry_count + 1,
-                        "llm_retry_count": retry_count,
-                    }
+                    NodeExecutionStats(
+                        llm_call_count=retry_count + 1,
+                        llm_retry_count=retry_count,
+                    )
                 )
 
         raise RuntimeError(retry_prompt)
@@ -621,7 +877,7 @@ class AITextGeneratorBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4_TURBO,
+            default=LlmModel.GPT4O,
             description="The language model to use for answering the prompt.",
             advanced=False,
         )
@@ -638,7 +894,7 @@ class AITextGeneratorBlock(AIBlockBase):
         )
         prompt_values: dict[str, str] = SchemaField(
             advanced=False,
-            default={},
+            default_factory=dict,
             description="Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}.",
         )
         ollama_host: str = SchemaField(
@@ -656,7 +912,7 @@ class AITextGeneratorBlock(AIBlockBase):
         response: str = SchemaField(
             description="The response generated by the language model."
         )
-        prompt: str = SchemaField(description="The prompt sent to the language model.")
+        prompt: list = SchemaField(description="The prompt sent to the language model.")
         error: str = SchemaField(description="Error message if the API call failed.")
 
     def __init__(self):
@@ -673,7 +929,7 @@ class AITextGeneratorBlock(AIBlockBase):
             test_credentials=TEST_CREDENTIALS,
             test_output=[
                 ("response", "Response text"),
-                ("prompt", str),
+                ("prompt", list),
             ],
             test_mock={"llm_call": lambda *args, **kwargs: "Response text"},
         )
@@ -692,7 +948,10 @@ class AITextGeneratorBlock(AIBlockBase):
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         object_input_data = AIStructuredResponseGeneratorBlock.Input(
-            **{attr: getattr(input_data, attr) for attr in input_data.model_fields},
+            **{
+                attr: getattr(input_data, attr)
+                for attr in AITextGeneratorBlock.Input.model_fields
+            },
             expected_format={},
         )
         yield "response", self.llm_call(object_input_data, credentials)
@@ -714,7 +973,7 @@ class AITextSummarizerBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4_TURBO,
+            default=LlmModel.GPT4O,
             description="The language model to use for summarizing the text.",
         )
         focus: str = SchemaField(
@@ -749,7 +1008,7 @@ class AITextSummarizerBlock(AIBlockBase):
 
     class Output(BlockSchema):
         summary: str = SchemaField(description="The final summary of the text.")
-        prompt: str = SchemaField(description="The prompt sent to the language model.")
+        prompt: list = SchemaField(description="The prompt sent to the language model.")
         error: str = SchemaField(description="Error message if the API call failed.")
 
     def __init__(self):
@@ -766,7 +1025,7 @@ class AITextSummarizerBlock(AIBlockBase):
             test_credentials=TEST_CREDENTIALS,
             test_output=[
                 ("summary", "Final summary of a long text"),
-                ("prompt", str),
+                ("prompt", list),
             ],
             test_mock={
                 "llm_call": lambda input_data, credentials: (
@@ -875,12 +1134,18 @@ class AITextSummarizerBlock(AIBlockBase):
 
 class AIConversationBlock(AIBlockBase):
     class Input(BlockSchema):
-        messages: List[Message] = SchemaField(
-            description="List of messages in the conversation.", min_length=1
+        prompt: str = SchemaField(
+            description="The prompt to send to the language model.",
+            placeholder="Enter your prompt here...",
+            default="",
+            advanced=False,
+        )
+        messages: List[Any] = SchemaField(
+            description="List of messages in the conversation.",
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4_TURBO,
+            default=LlmModel.GPT4O,
             description="The language model to use for the conversation.",
         )
         credentials: AICredentials = AICredentialsField()
@@ -899,7 +1164,7 @@ class AIConversationBlock(AIBlockBase):
         response: str = SchemaField(
             description="The model's response to the conversation."
         )
-        prompt: str = SchemaField(description="The prompt sent to the language model.")
+        prompt: list = SchemaField(description="The prompt sent to the language model.")
         error: str = SchemaField(description="Error message if the API call failed.")
 
     def __init__(self):
@@ -919,7 +1184,7 @@ class AIConversationBlock(AIBlockBase):
                     },
                     {"role": "user", "content": "Where was it played?"},
                 ],
-                "model": LlmModel.GPT4_TURBO,
+                "model": LlmModel.GPT4O,
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
             test_credentials=TEST_CREDENTIALS,
@@ -928,7 +1193,7 @@ class AIConversationBlock(AIBlockBase):
                     "response",
                     "The 2020 World Series was played at Globe Life Field in Arlington, Texas.",
                 ),
-                ("prompt", str),
+                ("prompt", list),
             ],
             test_mock={
                 "llm_call": lambda *args, **kwargs: "The 2020 World Series was played at Globe Life Field in Arlington, Texas."
@@ -950,7 +1215,7 @@ class AIConversationBlock(AIBlockBase):
     ) -> BlockOutput:
         response = self.llm_call(
             AIStructuredResponseGeneratorBlock.Input(
-                prompt="",
+                prompt=input_data.prompt,
                 credentials=input_data.credentials,
                 model=input_data.model,
                 conversation_history=input_data.messages,
@@ -981,7 +1246,7 @@ class AIListGeneratorBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4_TURBO,
+            default=LlmModel.GPT4O,
             description="The language model to use for generating the list.",
             advanced=True,
         )
@@ -1008,7 +1273,7 @@ class AIListGeneratorBlock(AIBlockBase):
         list_item: str = SchemaField(
             description="Each individual item in the list.",
         )
-        prompt: str = SchemaField(description="The prompt sent to the language model.")
+        prompt: list = SchemaField(description="The prompt sent to the language model.")
         error: str = SchemaField(
             description="Error message if the list generation failed."
         )
@@ -1030,7 +1295,7 @@ class AIListGeneratorBlock(AIBlockBase):
                     "drawing explorers to uncover its mysteries. Each planet showcases the limitless possibilities of "
                     "fictional worlds."
                 ),
-                "model": LlmModel.GPT4_TURBO,
+                "model": LlmModel.GPT4O,
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "max_retries": 3,
             },
@@ -1040,7 +1305,7 @@ class AIListGeneratorBlock(AIBlockBase):
                     "generated_list",
                     ["Zylora Prime", "Kharon-9", "Vortexia", "Oceara", "Draknos"],
                 ),
-                ("prompt", str),
+                ("prompt", list),
                 ("list_item", "Zylora Prime"),
                 ("list_item", "Kharon-9"),
                 ("list_item", "Vortexia"),

autogpt_platform/backend/backend/blocks/media.py

@@ -8,13 +8,13 @@ from moviepy.video.io.VideoFileClip import VideoFileClip
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.file import MediaFile, get_exec_file_path, store_media_file
+from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
 
 
 class MediaDurationBlock(Block):
 
     class Input(BlockSchema):
-        media_in: MediaFile = SchemaField(
+        media_in: MediaFileType = SchemaField(
             description="Media input (URL, data URI, or local path)."
         )
         is_video: bool = SchemaField(
@@ -69,7 +69,7 @@ class LoopVideoBlock(Block):
     """
 
     class Input(BlockSchema):
-        video_in: MediaFile = SchemaField(
+        video_in: MediaFileType = SchemaField(
             description="The input video (can be a URL, data URI, or local path)."
         )
         # Provide EITHER a `duration` or `n_loops` or both. We'll demonstrate `duration`.
@@ -137,7 +137,7 @@ class LoopVideoBlock(Block):
         assert isinstance(looped_clip, VideoFileClip)
 
         # 4) Save the looped output
-        output_filename = MediaFile(
+        output_filename = MediaFileType(
             f"{node_exec_id}_looped_{os.path.basename(local_video_path)}"
         )
         output_abspath = get_exec_file_path(graph_exec_id, output_filename)
@@ -162,10 +162,10 @@ class AddAudioToVideoBlock(Block):
     """
 
     class Input(BlockSchema):
-        video_in: MediaFile = SchemaField(
+        video_in: MediaFileType = SchemaField(
             description="Video input (URL, data URI, or local path)."
         )
-        audio_in: MediaFile = SchemaField(
+        audio_in: MediaFileType = SchemaField(
             description="Audio input (URL, data URI, or local path)."
         )
         volume: float = SchemaField(
@@ -178,7 +178,7 @@ class AddAudioToVideoBlock(Block):
         )
 
     class Output(BlockSchema):
-        video_out: MediaFile = SchemaField(
+        video_out: MediaFileType = SchemaField(
             description="Final video (with attached audio), as a path or data URI."
         )
         error: str = SchemaField(
@@ -229,7 +229,7 @@ class AddAudioToVideoBlock(Block):
         final_clip = video_clip.with_audio(audio_clip)
 
         # 4) Write to output file
-        output_filename = MediaFile(
+        output_filename = MediaFileType(
             f"{node_exec_id}_audio_attached_{os.path.basename(local_video_path)}"
         )
         output_abspath = os.path.join(abs_temp_dir, output_filename)

autogpt_platform/backend/backend/blocks/mem0.py

@@ -65,7 +65,7 @@ class AddMemoryBlock(Block, Mem0Base):
             default=Content(discriminator="content", content="I'm a vegetarian"),
         )
         metadata: dict[str, Any] = SchemaField(
-            description="Optional metadata for the memory", default={}
+            description="Optional metadata for the memory", default_factory=dict
         )
 
         limit_memory_to_run: bool = SchemaField(
@@ -173,7 +173,7 @@ class SearchMemoryBlock(Block, Mem0Base):
         )
         categories_filter: list[str] = SchemaField(
             description="Categories to filter by",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         limit_memory_to_run: bool = SchemaField(

autogpt_platform/backend/backend/blocks/nvidia/deepfake.py

@@ -6,13 +6,14 @@ from backend.blocks.nvidia._auth import (
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
 from backend.util.request import requests
+from backend.util.type import MediaFileType
 
 
 class NvidiaDeepfakeDetectBlock(Block):
     class Input(BlockSchema):
         credentials: NvidiaCredentialsInput = NvidiaCredentialsField()
-        image_base64: str = SchemaField(
-            description="Image to analyze for deepfakes", image_upload=True
+        image_base64: MediaFileType = SchemaField(
+            description="Image to analyze for deepfakes",
         )
         return_image: bool = SchemaField(
             description="Whether to return the processed image with markings",
@@ -22,16 +23,12 @@ class NvidiaDeepfakeDetectBlock(Block):
     class Output(BlockSchema):
         status: str = SchemaField(
             description="Detection status (SUCCESS, ERROR, CONTENT_FILTERED)",
-            default="",
         )
-        image: str = SchemaField(
+        image: MediaFileType = SchemaField(
             description="Processed image with detection markings (if return_image=True)",
-            default="",
-            image_output=True,
         )
         is_deepfake: float = SchemaField(
             description="Probability that the image is a deepfake (0-1)",
-            default=0.0,
         )
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/pinecone.py

@@ -177,7 +177,8 @@ class PineconeInsertBlock(Block):
             description="Namespace to use in Pinecone", default=""
         )
         metadata: dict = SchemaField(
-            description="Additional metadata to store with each vector", default={}
+            description="Additional metadata to store with each vector",
+            default_factory=dict,
         )
 
     class Output(BlockSchema):

autogpt_platform/backend/backend/blocks/replicate_flux_advanced.py

@@ -2,8 +2,8 @@ import os
 from enum import Enum
 from typing import Literal
 
-import replicate
 from pydantic import SecretStr
+from replicate.client import Client as ReplicateClient
 from replicate.helpers import FileOutput
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
@@ -198,7 +198,7 @@ class ReplicateFluxAdvancedModelBlock(Block):
         safety_tolerance,
     ):
         # Initialize Replicate client with the API key
-        client = replicate.Client(api_token=api_key.get_secret_value())
+        client = ReplicateClient(api_token=api_key.get_secret_value())
 
         # Run the model with additional parameters
         output: FileOutput | list[FileOutput] = client.run(  # type: ignore This is because they changed the return type, and didn't update the type hint! It should be overloaded depending on the value of `use_file_output` to `FileOutput | list[FileOutput]` but it's `Any | Iterator[Any]`

autogpt_platform/backend/backend/blocks/screenshotone.py

@@ -12,7 +12,7 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
-from backend.util.file import MediaFile, store_media_file
+from backend.util.file import MediaFileType, store_media_file
 from backend.util.request import Requests
 
 
@@ -57,7 +57,7 @@ class ScreenshotWebPageBlock(Block):
         )
 
     class Output(BlockSchema):
-        image: MediaFile = SchemaField(description="The screenshot image data")
+        image: MediaFileType = SchemaField(description="The screenshot image data")
         error: str = SchemaField(description="Error message if the screenshot failed")
 
     def __init__(self):
@@ -142,7 +142,9 @@ class ScreenshotWebPageBlock(Block):
         return {
             "image": store_media_file(
                 graph_exec_id=graph_exec_id,
-                file=f"data:image/{format.value};base64,{b64encode(response.content).decode('utf-8')}",
+                file=MediaFileType(
+                    f"data:image/{format.value};base64,{b64encode(response.content).decode('utf-8')}"
+                ),
                 return_content=True,
             )
         }

autogpt_platform/backend/backend/blocks/slant3d/webhook.py

@@ -8,6 +8,7 @@ from backend.data.block import (
     BlockWebhookConfig,
 )
 from backend.data.model import SchemaField
+from backend.integrations.providers import ProviderName
 from backend.util import settings
 from backend.util.settings import AppEnvironment, BehaveAs
 
@@ -25,7 +26,7 @@ class Slant3DTriggerBase:
     class Input(BlockSchema):
         credentials: Slant3DCredentialsInput = Slant3DCredentialsField()
         # Webhook URL is handled by the webhook system
-        payload: dict = SchemaField(hidden=True, default={})
+        payload: dict = SchemaField(hidden=True, default_factory=dict)
 
     class Output(BlockSchema):
         payload: dict = SchemaField(
@@ -82,7 +83,7 @@ class Slant3DOrderWebhookBlock(Slant3DTriggerBase, Block):
             input_schema=self.Input,
             output_schema=self.Output,
             webhook_config=BlockWebhookConfig(
-                provider="slant3d",
+                provider=ProviderName.SLANT3D,
                 webhook_type="orders",  # Only one type for now
                 resource_format="",  # No resource format needed
                 event_filter_input="events",

autogpt_platform/backend/backend/blocks/smart_decision_maker.py

@@ -0,0 +1,513 @@
+import logging
+import re
+from collections import Counter
+from typing import TYPE_CHECKING, Any
+
+from autogpt_libs.utils.cache import thread_cached
+
+import backend.blocks.llm as llm
+from backend.blocks.agent import AgentExecutorBlock
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockInput,
+    BlockOutput,
+    BlockSchema,
+    BlockType,
+)
+from backend.data.model import SchemaField
+from backend.util import json
+
+if TYPE_CHECKING:
+    from backend.data.graph import Link, Node
+
+logger = logging.getLogger(__name__)
+
+
+@thread_cached
+def get_database_manager_client():
+    from backend.executor import DatabaseManagerClient
+    from backend.util.service import get_service_client
+
+    return get_service_client(DatabaseManagerClient)
+
+
+def _get_tool_requests(entry: dict[str, Any]) -> list[str]:
+    """
+    Return a list of tool_call_ids if the entry is a tool request.
+    Supports both OpenAI and Anthropics formats.
+    """
+    tool_call_ids = []
+    if entry.get("role") != "assistant":
+        return tool_call_ids
+
+    # OpenAI: check for tool_calls in the entry.
+    calls = entry.get("tool_calls")
+    if isinstance(calls, list):
+        for call in calls:
+            if tool_id := call.get("id"):
+                tool_call_ids.append(tool_id)
+
+    # Anthropics: check content items for tool_use type.
+    content = entry.get("content")
+    if isinstance(content, list):
+        for item in content:
+            if item.get("type") != "tool_use":
+                continue
+            if tool_id := item.get("id"):
+                tool_call_ids.append(tool_id)
+
+    return tool_call_ids
+
+
+def _get_tool_responses(entry: dict[str, Any]) -> list[str]:
+    """
+    Return a list of tool_call_ids if the entry is a tool response.
+    Supports both OpenAI and Anthropics formats.
+    """
+    tool_call_ids: list[str] = []
+
+    # OpenAI: a tool response message with role "tool" and key "tool_call_id".
+    if entry.get("role") == "tool":
+        if tool_call_id := entry.get("tool_call_id"):
+            tool_call_ids.append(str(tool_call_id))
+
+    # Anthropics: check content items for tool_result type.
+    if entry.get("role") == "user":
+        content = entry.get("content")
+        if isinstance(content, list):
+            for item in content:
+                if item.get("type") != "tool_result":
+                    continue
+                if tool_call_id := item.get("tool_use_id"):
+                    tool_call_ids.append(tool_call_id)
+
+    return tool_call_ids
+
+
+def _create_tool_response(call_id: str, output: dict[str, Any]) -> dict[str, Any]:
+    """
+    Create a tool response message for either OpenAI or Anthropics,
+    based on the tool_id format.
+    """
+    content = output if isinstance(output, str) else json.dumps(output)
+
+    # Anthropics format: tool IDs typically start with "toolu_"
+    if call_id.startswith("toolu_"):
+        return {
+            "role": "user",
+            "type": "message",
+            "content": [
+                {"tool_use_id": call_id, "type": "tool_result", "content": content}
+            ],
+        }
+
+    # OpenAI format: tool IDs typically start with "call_".
+    # Or default fallback (if the tool_id doesn't match any known prefix)
+    return {"role": "tool", "tool_call_id": call_id, "content": content}
+
+
+def get_pending_tool_calls(conversation_history: list[Any]) -> dict[str, int]:
+    """
+    All the tool calls entry in the conversation history requires a response.
+    This function returns the pending tool calls that has not generated an output yet.
+
+    Return: dict[str, int] - A dictionary of pending tool call IDs with their count.
+    """
+    pending_calls = Counter()
+    for history in conversation_history:
+        for call_id in _get_tool_requests(history):
+            pending_calls[call_id] += 1
+
+        for call_id in _get_tool_responses(history):
+            pending_calls[call_id] -= 1
+
+    return {call_id: count for call_id, count in pending_calls.items() if count > 0}
+
+
+class SmartDecisionMakerBlock(Block):
+    """
+    A block that uses a language model to make smart decisions based on a given prompt.
+    """
+
+    class Input(BlockSchema):
+        prompt: str = SchemaField(
+            description="The prompt to send to the language model.",
+            placeholder="Enter your prompt here...",
+        )
+        model: llm.LlmModel = SchemaField(
+            title="LLM Model",
+            default=llm.LlmModel.GPT4O,
+            description="The language model to use for answering the prompt.",
+            advanced=False,
+        )
+        credentials: llm.AICredentials = llm.AICredentialsField()
+        sys_prompt: str = SchemaField(
+            title="System Prompt",
+            default="Thinking carefully step by step decide which function to call. "
+            "Always choose a function call from the list of function signatures, "
+            "and always provide the complete argument provided with the type "
+            "matching the required jsonschema signature, no missing argument is allowed. "
+            "If you have already completed the task objective, you can end the task "
+            "by providing the end result of your work as a finish message. "
+            "Only provide EXACTLY one function call, multiple tool calls is strictly prohibited.",
+            description="The system prompt to provide additional context to the model.",
+        )
+        conversation_history: list[dict] = SchemaField(
+            default_factory=list,
+            description="The conversation history to provide context for the prompt.",
+        )
+        last_tool_output: Any = SchemaField(
+            default=None,
+            description="The output of the last tool that was called.",
+        )
+        retry: int = SchemaField(
+            title="Retry Count",
+            default=3,
+            description="Number of times to retry the LLM call if the response does not match the expected format.",
+        )
+        prompt_values: dict[str, str] = SchemaField(
+            advanced=False,
+            default_factory=dict,
+            description="Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}.",
+        )
+        max_tokens: int | None = SchemaField(
+            advanced=True,
+            default=None,
+            description="The maximum number of tokens to generate in the chat completion.",
+        )
+        ollama_host: str = SchemaField(
+            advanced=True,
+            default="localhost:11434",
+            description="Ollama host for local  models",
+        )
+
+        @classmethod
+        def get_missing_links(cls, data: BlockInput, links: list["Link"]) -> set[str]:
+            # conversation_history & last_tool_output validation is handled differently
+            missing_links = super().get_missing_links(
+                data,
+                [
+                    link
+                    for link in links
+                    if link.sink_name
+                    not in ["conversation_history", "last_tool_output"]
+                ],
+            )
+
+            # Avoid executing the block if the last_tool_output is connected to a static
+            # link, like StoreValueBlock or AgentInputBlock.
+            if any(link.sink_name == "conversation_history" for link in links) and any(
+                link.sink_name == "last_tool_output" and link.is_static
+                for link in links
+            ):
+                raise ValueError(
+                    "Last Tool Output can't be connected to a static (dashed line) "
+                    "link like the output of `StoreValue` or `AgentInput` block"
+                )
+
+            return missing_links
+
+        @classmethod
+        def get_missing_input(cls, data: BlockInput) -> set[str]:
+            if missing_input := super().get_missing_input(data):
+                return missing_input
+
+            conversation_history = data.get("conversation_history", [])
+            pending_tool_calls = get_pending_tool_calls(conversation_history)
+            last_tool_output = data.get("last_tool_output")
+            if not last_tool_output and pending_tool_calls:
+                return {"last_tool_output"}
+            return set()
+
+    class Output(BlockSchema):
+        error: str = SchemaField(description="Error message if the API call failed.")
+        tools: Any = SchemaField(description="The tools that are available to use.")
+        finished: str = SchemaField(
+            description="The finished message to display to the user."
+        )
+        conversations: list[Any] = SchemaField(
+            description="The conversation history to provide context for the prompt."
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="3b191d9f-356f-482d-8238-ba04b6d18381",
+            description="Uses AI to intelligently decide what tool to use.",
+            categories={BlockCategory.AI},
+            block_type=BlockType.AI,
+            input_schema=SmartDecisionMakerBlock.Input,
+            output_schema=SmartDecisionMakerBlock.Output,
+            test_input={
+                "prompt": "Hello, World!",
+                "credentials": llm.TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[],
+            test_credentials=llm.TEST_CREDENTIALS,
+        )
+
+    @staticmethod
+    def cleanup(s: str):
+        return re.sub(r"[^a-zA-Z0-9_-]", "_", s).lower()
+
+    @staticmethod
+    def _create_block_function_signature(
+        sink_node: "Node", links: list["Link"]
+    ) -> dict[str, Any]:
+        """
+        Creates a function signature for a block node.
+
+        Args:
+            sink_node: The node for which to create a function signature.
+            links: The list of links connected to the sink node.
+
+        Returns:
+            A dictionary representing the function signature in the format expected by LLM tools.
+
+        Raises:
+            ValueError: If the block specified by sink_node.block_id is not found.
+        """
+        block = sink_node.block
+
+        tool_function: dict[str, Any] = {
+            "name": SmartDecisionMakerBlock.cleanup(block.name),
+            "description": block.description,
+        }
+
+        properties = {}
+        required = []
+
+        for link in links:
+            sink_block_input_schema = block.input_schema
+            description = (
+                sink_block_input_schema.model_fields[link.sink_name].description
+                if link.sink_name in sink_block_input_schema.model_fields
+                and sink_block_input_schema.model_fields[link.sink_name].description
+                else f"The {link.sink_name} of the tool"
+            )
+            properties[SmartDecisionMakerBlock.cleanup(link.sink_name)] = {
+                "type": "string",
+                "description": description,
+            }
+
+        tool_function["parameters"] = {
+            "type": "object",
+            "properties": properties,
+            "required": required,
+            "additionalProperties": False,
+            "strict": True,
+        }
+
+        return {"type": "function", "function": tool_function}
+
+    @staticmethod
+    def _create_agent_function_signature(
+        sink_node: "Node", links: list["Link"]
+    ) -> dict[str, Any]:
+        """
+        Creates a function signature for an agent node.
+
+        Args:
+            sink_node: The agent node for which to create a function signature.
+            links: The list of links connected to the sink node.
+
+        Returns:
+            A dictionary representing the function signature in the format expected by LLM tools.
+
+        Raises:
+            ValueError: If the graph metadata for the specified graph_id and graph_version is not found.
+        """
+        graph_id = sink_node.input_default.get("graph_id")
+        graph_version = sink_node.input_default.get("graph_version")
+        if not graph_id or not graph_version:
+            raise ValueError("Graph ID or Graph Version not found in sink node.")
+
+        db_client = get_database_manager_client()
+        sink_graph_meta = db_client.get_graph_metadata(graph_id, graph_version)
+        if not sink_graph_meta:
+            raise ValueError(
+                f"Sink graph metadata not found: {graph_id} {graph_version}"
+            )
+
+        tool_function: dict[str, Any] = {
+            "name": SmartDecisionMakerBlock.cleanup(sink_graph_meta.name),
+            "description": sink_graph_meta.description,
+        }
+
+        properties = {}
+        required = []
+
+        for link in links:
+            sink_block_input_schema = sink_node.input_default["input_schema"]
+            description = (
+                sink_block_input_schema["properties"][link.sink_name]["description"]
+                if "description"
+                in sink_block_input_schema["properties"][link.sink_name]
+                else f"The {link.sink_name} of the tool"
+            )
+            properties[SmartDecisionMakerBlock.cleanup(link.sink_name)] = {
+                "type": "string",
+                "description": description,
+            }
+
+        tool_function["parameters"] = {
+            "type": "object",
+            "properties": properties,
+            "required": required,
+            "additionalProperties": False,
+            "strict": True,
+        }
+
+        return {"type": "function", "function": tool_function}
+
+    @staticmethod
+    def _create_function_signature(node_id: str) -> list[dict[str, Any]]:
+        """
+        Creates function signatures for tools linked to a specified node within a graph.
+
+        This method filters the graph links to identify those that are tools and are
+        connected to the given node_id. It then constructs function signatures for each
+        tool based on the metadata and input schema of the linked nodes.
+
+        Args:
+            node_id: The node_id for which to create function signatures.
+
+        Returns:
+            list[dict[str, Any]]: A list of dictionaries, each representing a function signature
+                                  for a tool, including its name, description, and parameters.
+
+        Raises:
+            ValueError: If no tool links are found for the specified node_id, or if a sink node
+                        or its metadata cannot be found.
+        """
+        db_client = get_database_manager_client()
+        tools = [
+            (link, node)
+            for link, node in db_client.get_connected_output_nodes(node_id)
+            if link.source_name.startswith("tools_^_") and link.source_id == node_id
+        ]
+        if not tools:
+            raise ValueError("There is no next node to execute.")
+
+        return_tool_functions = []
+
+        grouped_tool_links: dict[str, tuple["Node", list["Link"]]] = {}
+        for link, node in tools:
+            if link.sink_id not in grouped_tool_links:
+                grouped_tool_links[link.sink_id] = (node, [link])
+            else:
+                grouped_tool_links[link.sink_id][1].append(link)
+
+        for sink_node, links in grouped_tool_links.values():
+            if not sink_node:
+                raise ValueError(f"Sink node not found: {links[0].sink_id}")
+
+            if sink_node.block_id == AgentExecutorBlock().id:
+                return_tool_functions.append(
+                    SmartDecisionMakerBlock._create_agent_function_signature(
+                        sink_node, links
+                    )
+                )
+            else:
+                return_tool_functions.append(
+                    SmartDecisionMakerBlock._create_block_function_signature(
+                        sink_node, links
+                    )
+                )
+
+        return return_tool_functions
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: llm.APIKeyCredentials,
+        graph_id: str,
+        node_id: str,
+        graph_exec_id: str,
+        node_exec_id: str,
+        user_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        tool_functions = self._create_function_signature(node_id)
+
+        input_data.conversation_history = input_data.conversation_history or []
+        prompt = [json.to_dict(p) for p in input_data.conversation_history if p]
+
+        pending_tool_calls = get_pending_tool_calls(input_data.conversation_history)
+        if pending_tool_calls and not input_data.last_tool_output:
+            raise ValueError(f"Tool call requires an output for {pending_tool_calls}")
+
+        # Prefill all missing tool calls with the last tool output/
+        # TODO: we need a better way to handle this.
+        tool_output = [
+            _create_tool_response(pending_call_id, input_data.last_tool_output)
+            for pending_call_id, count in pending_tool_calls.items()
+            for _ in range(count)
+        ]
+
+        # If the SDM block only calls 1 tool at a time, this should not happen.
+        if len(tool_output) > 1:
+            logger.warning(
+                f"[SmartDecisionMakerBlock-node_exec_id={node_exec_id}] "
+                f"Multiple pending tool calls are prefilled using a single output. "
+                f"Execution may not be accurate."
+            )
+
+        # Fallback on adding tool output in the conversation history as user prompt.
+        if len(tool_output) == 0 and input_data.last_tool_output:
+            logger.warning(
+                f"[SmartDecisionMakerBlock-node_exec_id={node_exec_id}] "
+                f"No pending tool calls found. This may indicate an issue with the "
+                f"conversation history, or an LLM calling two tools at the same time."
+            )
+            tool_output.append(
+                {
+                    "role": "user",
+                    "content": f"Last tool output: {json.dumps(input_data.last_tool_output)}",
+                }
+            )
+
+        prompt.extend(tool_output)
+
+        values = input_data.prompt_values
+        if values:
+            input_data.prompt = llm.fmt.format_string(input_data.prompt, values)
+            input_data.sys_prompt = llm.fmt.format_string(input_data.sys_prompt, values)
+
+        prefix = "[Main Objective Prompt]: "
+
+        if input_data.sys_prompt and not any(
+            p["role"] == "system" and p["content"].startswith(prefix) for p in prompt
+        ):
+            prompt.append({"role": "system", "content": prefix + input_data.sys_prompt})
+
+        if input_data.prompt and not any(
+            p["role"] == "user" and p["content"].startswith(prefix) for p in prompt
+        ):
+            prompt.append({"role": "user", "content": prefix + input_data.prompt})
+
+        response = llm.llm_call(
+            credentials=credentials,
+            llm_model=input_data.model,
+            prompt=prompt,
+            json_format=False,
+            max_tokens=input_data.max_tokens,
+            tools=tool_functions,
+            ollama_host=input_data.ollama_host,
+            parallel_tool_calls=False,
+        )
+
+        if not response.tool_calls:
+            yield "finished", response.response
+            return
+
+        for tool_call in response.tool_calls:
+            tool_name = tool_call.function.name
+            tool_args = json.loads(tool_call.function.arguments)
+
+            for arg_name, arg_value in tool_args.items():
+                yield f"tools_^_{tool_name}_~_{arg_name}", arg_value
+
+        response.prompt.append(response.raw_response)
+        yield "conversations", response.prompt

autogpt_platform/backend/backend/blocks/smartlead/_api.py

@@ -0,0 +1,97 @@
+from backend.blocks.smartlead.models import (
+    AddLeadsRequest,
+    AddLeadsToCampaignResponse,
+    CreateCampaignRequest,
+    CreateCampaignResponse,
+    SaveSequencesRequest,
+    SaveSequencesResponse,
+)
+from backend.util.request import Requests
+
+
+class SmartLeadClient:
+    """Client for the SmartLead API"""
+
+    # This api is stupid and requires your api key in the url. DO NOT RAISE ERRORS FOR BAD REQUESTS.
+    # FILTER OUT THE API KEY FROM THE ERROR MESSAGE.
+
+    API_URL = "https://server.smartlead.ai/api/v1"
+
+    def __init__(self, api_key: str):
+        self.api_key = api_key
+        self.requests = Requests()
+
+    def _add_auth_to_url(self, url: str) -> str:
+        return f"{url}?api_key={self.api_key}"
+
+    def _handle_error(self, e: Exception) -> str:
+        return e.__str__().replace(self.api_key, "API KEY")
+
+    def create_campaign(self, request: CreateCampaignRequest) -> CreateCampaignResponse:
+        try:
+            response = self.requests.post(
+                self._add_auth_to_url(f"{self.API_URL}/campaigns/create"),
+                json=request.model_dump(),
+            )
+            response_data = response.json()
+            return CreateCampaignResponse(**response_data)
+        except ValueError as e:
+            raise ValueError(f"Invalid response format: {str(e)}")
+        except Exception as e:
+            raise ValueError(f"Failed to create campaign: {self._handle_error(e)}")
+
+    def add_leads_to_campaign(
+        self, request: AddLeadsRequest
+    ) -> AddLeadsToCampaignResponse:
+        try:
+            response = self.requests.post(
+                self._add_auth_to_url(
+                    f"{self.API_URL}/campaigns/{request.campaign_id}/leads"
+                ),
+                json=request.model_dump(exclude={"campaign_id"}),
+            )
+            response_data = response.json()
+            response_parsed = AddLeadsToCampaignResponse(**response_data)
+            if not response_parsed.ok:
+                raise ValueError(
+                    f"Failed to add leads to campaign: {response_parsed.error}"
+                )
+            return response_parsed
+        except ValueError as e:
+            raise ValueError(f"Invalid response format: {str(e)}")
+        except Exception as e:
+            raise ValueError(
+                f"Failed to add leads to campaign: {self._handle_error(e)}"
+            )
+
+    def save_campaign_sequences(
+        self, campaign_id: int, request: SaveSequencesRequest
+    ) -> SaveSequencesResponse:
+        """
+        Save sequences within a campaign.
+
+        Args:
+            campaign_id: ID of the campaign to save sequences for
+            request: SaveSequencesRequest containing the sequences configuration
+
+        Returns:
+            SaveSequencesResponse with the result of the operation
+
+        Note:
+            For variant_distribution_type:
+            - MANUAL_EQUAL: Equally distributes variants across leads
+            - AI_EQUAL: Requires winning_metric_property and lead_distribution_percentage
+            - MANUAL_PERCENTAGE: Requires variant_distribution_percentage in seq_variants
+        """
+        try:
+            response = self.requests.post(
+                self._add_auth_to_url(
+                    f"{self.API_URL}/campaigns/{campaign_id}/sequences"
+                ),
+                json=request.model_dump(exclude_none=True),
+            )
+            return SaveSequencesResponse(**response.json())
+        except Exception as e:
+            raise ValueError(
+                f"Failed to save campaign sequences: {e.__str__().replace(self.api_key, 'API KEY')}"
+            )

autogpt_platform/backend/backend/blocks/smartlead/_auth.py

@@ -0,0 +1,35 @@
+from typing import Literal
+
+from pydantic import SecretStr
+
+from backend.data.model import APIKeyCredentials, CredentialsField, CredentialsMetaInput
+from backend.integrations.providers import ProviderName
+
+SmartLeadCredentials = APIKeyCredentials
+SmartLeadCredentialsInput = CredentialsMetaInput[
+    Literal[ProviderName.SMARTLEAD],
+    Literal["api_key"],
+]
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="smartlead",
+    api_key=SecretStr("mock-smartlead-api-key"),
+    title="Mock SmartLead API key",
+    expires_at=None,
+)
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}
+
+
+def SmartLeadCredentialsField() -> SmartLeadCredentialsInput:
+    """
+    Creates a SmartLead credentials input on a block.
+    """
+    return CredentialsField(
+        description="The SmartLead integration can be used with an API Key.",
+    )

autogpt_platform/backend/backend/blocks/smartlead/campaign.py

@@ -0,0 +1,326 @@
+from backend.blocks.smartlead._api import SmartLeadClient
+from backend.blocks.smartlead._auth import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    SmartLeadCredentials,
+    SmartLeadCredentialsInput,
+)
+from backend.blocks.smartlead.models import (
+    AddLeadsRequest,
+    AddLeadsToCampaignResponse,
+    CreateCampaignRequest,
+    CreateCampaignResponse,
+    LeadInput,
+    LeadUploadSettings,
+    SaveSequencesRequest,
+    SaveSequencesResponse,
+    Sequence,
+)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+
+
+class CreateCampaignBlock(Block):
+    """Create a campaign in SmartLead"""
+
+    class Input(BlockSchema):
+        name: str = SchemaField(
+            description="The name of the campaign",
+        )
+        credentials: SmartLeadCredentialsInput = SchemaField(
+            description="SmartLead credentials",
+        )
+
+    class Output(BlockSchema):
+        id: int = SchemaField(
+            description="The ID of the created campaign",
+        )
+        name: str = SchemaField(
+            description="The name of the created campaign",
+        )
+        created_at: str = SchemaField(
+            description="The date and time the campaign was created",
+        )
+        error: str = SchemaField(
+            description="Error message if the search failed",
+            default="",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="8865699f-9188-43c4-89b0-79c84cfaa03e",
+            description="Create a campaign in SmartLead",
+            categories={BlockCategory.CRM},
+            input_schema=CreateCampaignBlock.Input,
+            output_schema=CreateCampaignBlock.Output,
+            test_credentials=TEST_CREDENTIALS,
+            test_input={"name": "Test Campaign", "credentials": TEST_CREDENTIALS_INPUT},
+            test_output=[
+                (
+                    "id",
+                    1,
+                ),
+                (
+                    "name",
+                    "Test Campaign",
+                ),
+                (
+                    "created_at",
+                    "2024-01-01T00:00:00Z",
+                ),
+            ],
+            test_mock={
+                "create_campaign": lambda name, credentials: CreateCampaignResponse(
+                    ok=True,
+                    id=1,
+                    name=name,
+                    created_at="2024-01-01T00:00:00Z",
+                )
+            },
+        )
+
+    @staticmethod
+    def create_campaign(
+        name: str, credentials: SmartLeadCredentials
+    ) -> CreateCampaignResponse:
+        client = SmartLeadClient(credentials.api_key.get_secret_value())
+        return client.create_campaign(CreateCampaignRequest(name=name))
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: SmartLeadCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        response = self.create_campaign(input_data.name, credentials)
+
+        yield "id", response.id
+        yield "name", response.name
+        yield "created_at", response.created_at
+        if not response.ok:
+            yield "error", "Failed to create campaign"
+
+
+class AddLeadToCampaignBlock(Block):
+    """Add a lead to a campaign in SmartLead"""
+
+    class Input(BlockSchema):
+        campaign_id: int = SchemaField(
+            description="The ID of the campaign to add the lead to",
+        )
+        lead_list: list[LeadInput] = SchemaField(
+            description="An array of JSON objects, each representing a lead's details. Can hold max 100 leads.",
+            max_length=100,
+            default_factory=list,
+            advanced=False,
+        )
+        settings: LeadUploadSettings = SchemaField(
+            description="Settings for lead upload",
+            default=LeadUploadSettings(),
+        )
+        credentials: SmartLeadCredentialsInput = SchemaField(
+            description="SmartLead credentials",
+        )
+
+    class Output(BlockSchema):
+        campaign_id: int = SchemaField(
+            description="The ID of the campaign the lead was added to (passed through)",
+        )
+        upload_count: int = SchemaField(
+            description="The number of leads added to the campaign",
+        )
+        already_added_to_campaign: int = SchemaField(
+            description="The number of leads that were already added to the campaign",
+        )
+        duplicate_count: int = SchemaField(
+            description="The number of emails that were duplicates",
+        )
+        invalid_email_count: int = SchemaField(
+            description="The number of emails that were invalidly formatted",
+        )
+        is_lead_limit_exhausted: bool = SchemaField(
+            description="Whether the lead limit was exhausted",
+        )
+        lead_import_stopped_count: int = SchemaField(
+            description="The number of leads that were not added to the campaign because the lead import was stopped",
+        )
+        error: str = SchemaField(
+            description="Error message if the lead was not added to the campaign",
+            default="",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="fb8106a4-1a8f-42f9-a502-f6d07e6fe0ec",
+            description="Add a lead to a campaign in SmartLead",
+            categories={BlockCategory.CRM},
+            input_schema=AddLeadToCampaignBlock.Input,
+            output_schema=AddLeadToCampaignBlock.Output,
+            test_credentials=TEST_CREDENTIALS,
+            test_input={
+                "campaign_id": 1,
+                "lead_list": [],
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[
+                (
+                    "campaign_id",
+                    1,
+                ),
+                (
+                    "upload_count",
+                    1,
+                ),
+            ],
+            test_mock={
+                "add_leads_to_campaign": lambda campaign_id, lead_list, credentials: AddLeadsToCampaignResponse(
+                    ok=True,
+                    upload_count=1,
+                    already_added_to_campaign=0,
+                    duplicate_count=0,
+                    invalid_email_count=0,
+                    is_lead_limit_exhausted=False,
+                    lead_import_stopped_count=0,
+                    error="",
+                    total_leads=1,
+                    block_count=0,
+                    invalid_emails=[],
+                    unsubscribed_leads=[],
+                    bounce_count=0,
+                )
+            },
+        )
+
+    @staticmethod
+    def add_leads_to_campaign(
+        campaign_id: int, lead_list: list[LeadInput], credentials: SmartLeadCredentials
+    ) -> AddLeadsToCampaignResponse:
+        client = SmartLeadClient(credentials.api_key.get_secret_value())
+        return client.add_leads_to_campaign(
+            AddLeadsRequest(
+                campaign_id=campaign_id,
+                lead_list=lead_list,
+                settings=LeadUploadSettings(
+                    ignore_global_block_list=False,
+                    ignore_unsubscribe_list=False,
+                    ignore_community_bounce_list=False,
+                    ignore_duplicate_leads_in_other_campaign=False,
+                ),
+            ),
+        )
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: SmartLeadCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        response = self.add_leads_to_campaign(
+            input_data.campaign_id, input_data.lead_list, credentials
+        )
+
+        yield "campaign_id", input_data.campaign_id
+        yield "upload_count", response.upload_count
+        if response.already_added_to_campaign:
+            yield "already_added_to_campaign", response.already_added_to_campaign
+        if response.duplicate_count:
+            yield "duplicate_count", response.duplicate_count
+        if response.invalid_email_count:
+            yield "invalid_email_count", response.invalid_email_count
+        if response.is_lead_limit_exhausted:
+            yield "is_lead_limit_exhausted", response.is_lead_limit_exhausted
+        if response.lead_import_stopped_count:
+            yield "lead_import_stopped_count", response.lead_import_stopped_count
+        if response.error:
+            yield "error", response.error
+        if not response.ok:
+            yield "error", "Failed to add leads to campaign"
+
+
+class SaveCampaignSequencesBlock(Block):
+    """Save sequences within a campaign"""
+
+    class Input(BlockSchema):
+        campaign_id: int = SchemaField(
+            description="The ID of the campaign to save sequences for",
+        )
+        sequences: list[Sequence] = SchemaField(
+            description="The sequences to save",
+            default_factory=list,
+            advanced=False,
+        )
+        credentials: SmartLeadCredentialsInput = SchemaField(
+            description="SmartLead credentials",
+        )
+
+    class Output(BlockSchema):
+        data: dict | str | None = SchemaField(
+            description="Data from the API",
+            default=None,
+        )
+        message: str = SchemaField(
+            description="Message from the API",
+            default="",
+        )
+        error: str = SchemaField(
+            description="Error message if the sequences were not saved",
+            default="",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="e7d9f41c-dc10-4f39-98ba-a432abd128c0",
+            description="Save sequences within a campaign",
+            categories={BlockCategory.CRM},
+            input_schema=SaveCampaignSequencesBlock.Input,
+            output_schema=SaveCampaignSequencesBlock.Output,
+            test_credentials=TEST_CREDENTIALS,
+            test_input={
+                "campaign_id": 1,
+                "sequences": [],
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[
+                (
+                    "message",
+                    "Sequences saved successfully",
+                ),
+            ],
+            test_mock={
+                "save_campaign_sequences": lambda campaign_id, sequences, credentials: SaveSequencesResponse(
+                    ok=True,
+                    message="Sequences saved successfully",
+                )
+            },
+        )
+
+    @staticmethod
+    def save_campaign_sequences(
+        campaign_id: int, sequences: list[Sequence], credentials: SmartLeadCredentials
+    ) -> SaveSequencesResponse:
+        client = SmartLeadClient(credentials.api_key.get_secret_value())
+        return client.save_campaign_sequences(
+            campaign_id=campaign_id, request=SaveSequencesRequest(sequences=sequences)
+        )
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: SmartLeadCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        response = self.save_campaign_sequences(
+            input_data.campaign_id, input_data.sequences, credentials
+        )
+
+        if response.data:
+            yield "data", response.data
+        if response.message:
+            yield "message", response.message
+        if response.error:
+            yield "error", response.error
+        if not response.ok:
+            yield "error", "Failed to save sequences"

autogpt_platform/backend/backend/blocks/smartlead/models.py

@@ -0,0 +1,147 @@
+from enum import Enum
+
+from pydantic import BaseModel
+
+from backend.data.model import SchemaField
+
+
+class CreateCampaignResponse(BaseModel):
+    ok: bool
+    id: int
+    name: str
+    created_at: str
+
+
+class CreateCampaignRequest(BaseModel):
+    name: str
+    client_id: str | None = None
+
+
+class AddLeadsToCampaignResponse(BaseModel):
+    ok: bool
+    upload_count: int
+    total_leads: int
+    block_count: int
+    duplicate_count: int
+    invalid_email_count: int
+    invalid_emails: list[str]
+    already_added_to_campaign: int
+    unsubscribed_leads: list[str]
+    is_lead_limit_exhausted: bool
+    lead_import_stopped_count: int
+    bounce_count: int
+    error: str | None = None
+
+
+class LeadCustomFields(BaseModel):
+    """Custom fields for a lead (max 20 fields)"""
+
+    fields: dict[str, str] = SchemaField(
+        description="Custom fields for a lead (max 20 fields)",
+        max_length=20,
+        default_factory=dict,
+    )
+
+
+class LeadInput(BaseModel):
+    """Single lead input data"""
+
+    first_name: str
+    last_name: str
+    email: str
+    phone_number: str | None = None  # Changed from int to str for phone numbers
+    company_name: str | None = None
+    website: str | None = None
+    location: str | None = None
+    custom_fields: LeadCustomFields | None = None
+    linkedin_profile: str | None = None
+    company_url: str | None = None
+
+
+class LeadUploadSettings(BaseModel):
+    """Settings for lead upload"""
+
+    ignore_global_block_list: bool = SchemaField(
+        description="Ignore the global block list",
+        default=False,
+    )
+    ignore_unsubscribe_list: bool = SchemaField(
+        description="Ignore the unsubscribe list",
+        default=False,
+    )
+    ignore_community_bounce_list: bool = SchemaField(
+        description="Ignore the community bounce list",
+        default=False,
+    )
+    ignore_duplicate_leads_in_other_campaign: bool = SchemaField(
+        description="Ignore duplicate leads in other campaigns",
+        default=False,
+    )
+
+
+class AddLeadsRequest(BaseModel):
+    """Request body for adding leads to a campaign"""
+
+    lead_list: list[LeadInput] = SchemaField(
+        description="List of leads to add to the campaign",
+        max_length=100,
+        default_factory=list,
+    )
+    settings: LeadUploadSettings
+    campaign_id: int
+
+
+class VariantDistributionType(str, Enum):
+    MANUAL_EQUAL = "MANUAL_EQUAL"
+    MANUAL_PERCENTAGE = "MANUAL_PERCENTAGE"
+    AI_EQUAL = "AI_EQUAL"
+
+
+class WinningMetricProperty(str, Enum):
+    OPEN_RATE = "OPEN_RATE"
+    CLICK_RATE = "CLICK_RATE"
+    REPLY_RATE = "REPLY_RATE"
+    POSITIVE_REPLY_RATE = "POSITIVE_REPLY_RATE"
+
+
+class SequenceDelayDetails(BaseModel):
+    delay_in_days: int
+
+
+class SequenceVariant(BaseModel):
+    subject: str
+    email_body: str
+    variant_label: str
+    id: int | None = None  # Optional for creation, required for updates
+    variant_distribution_percentage: int | None = None
+
+
+class Sequence(BaseModel):
+    seq_number: int = SchemaField(
+        description="The sequence number",
+        default=1,
+    )
+    seq_delay_details: SequenceDelayDetails
+    id: int | None = None
+    variant_distribution_type: VariantDistributionType | None = None
+    lead_distribution_percentage: int | None = SchemaField(
+        None, ge=20, le=100
+    )  # >= 20% for fair calculation
+    winning_metric_property: WinningMetricProperty | None = None
+    seq_variants: list[SequenceVariant] | None = None
+    subject: str = ""  # blank makes the follow up in the same thread
+    email_body: str | None = None
+
+
+class SaveSequencesRequest(BaseModel):
+    sequences: list[Sequence]
+
+
+class SaveSequencesResponse(BaseModel):
+    ok: bool
+    message: str = SchemaField(
+        description="Message from the API",
+        default="",
+    )
+    data: dict | str | None = None
+    error: str | None = None

autogpt_platform/backend/backend/blocks/time_blocks.py

@@ -156,6 +156,10 @@ class CountdownTimerBlock(Block):
         days: Union[int, str] = SchemaField(
             advanced=False, description="Duration in days", default=0
         )
+        repeat: int = SchemaField(
+            description="Number of times to repeat the timer",
+            default=1,
+        )
 
     class Output(BlockSchema):
         output_message: Any = SchemaField(
@@ -187,5 +191,6 @@ class CountdownTimerBlock(Block):
 
         total_seconds = seconds + minutes * 60 + hours * 3600 + days * 86400
 
-        time.sleep(total_seconds)
-        yield "output_message", input_data.input_message
+        for _ in range(input_data.repeat):
+            time.sleep(total_seconds)
+            yield "output_message", input_data.input_message

autogpt_platform/backend/backend/blocks/todoist/comments.py

@@ -7,6 +7,7 @@ from typing_extensions import Optional
 from backend.blocks.todoist._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TODOIST_OAUTH_IS_CONFIGURED,
     TodoistCredentials,
     TodoistCredentialsField,
     TodoistCredentialsInput,
@@ -61,6 +62,7 @@ class TodoistCreateCommentBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistCreateCommentBlock.Input,
             output_schema=TodoistCreateCommentBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "content": "Test comment",
@@ -164,6 +166,7 @@ class TodoistGetCommentsBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistGetCommentsBlock.Input,
             output_schema=TodoistGetCommentsBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "id_type": {"discriminator": "task", "task_id": "2995104339"},
@@ -268,6 +271,7 @@ class TodoistGetCommentBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistGetCommentBlock.Input,
             output_schema=TodoistGetCommentBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "comment_id": "2992679862",
@@ -346,6 +350,7 @@ class TodoistUpdateCommentBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistUpdateCommentBlock.Input,
             output_schema=TodoistUpdateCommentBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "comment_id": "2992679862",
@@ -404,6 +409,7 @@ class TodoistDeleteCommentBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistDeleteCommentBlock.Input,
             output_schema=TodoistDeleteCommentBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "comment_id": "2992679862",

autogpt_platform/backend/backend/blocks/todoist/labels.py

@@ -4,6 +4,7 @@ from typing_extensions import Optional
 from backend.blocks.todoist._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TODOIST_OAUTH_IS_CONFIGURED,
     TodoistCredentials,
     TodoistCredentialsField,
     TodoistCredentialsInput,
@@ -42,6 +43,7 @@ class TodoistCreateLabelBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistCreateLabelBlock.Input,
             output_schema=TodoistCreateLabelBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "name": "Test Label",
@@ -130,6 +132,7 @@ class TodoistListLabelsBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistListLabelsBlock.Input,
             output_schema=TodoistListLabelsBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={"credentials": TEST_CREDENTIALS_INPUT},
             test_credentials=TEST_CREDENTIALS,
             test_output=[
@@ -211,6 +214,7 @@ class TodoistGetLabelBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistGetLabelBlock.Input,
             output_schema=TodoistGetLabelBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "label_id": "2156154810",
@@ -293,6 +297,7 @@ class TodoistUpdateLabelBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistUpdateLabelBlock.Input,
             output_schema=TodoistUpdateLabelBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "label_id": "2156154810",
@@ -364,6 +369,7 @@ class TodoistDeleteLabelBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistDeleteLabelBlock.Input,
             output_schema=TodoistDeleteLabelBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "label_id": "2156154810",
@@ -415,6 +421,7 @@ class TodoistGetSharedLabelsBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistGetSharedLabelsBlock.Input,
             output_schema=TodoistGetSharedLabelsBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={"credentials": TEST_CREDENTIALS_INPUT},
             test_credentials=TEST_CREDENTIALS,
             test_output=[("labels", ["Label1", "Label2", "Label3"])],
@@ -471,6 +478,7 @@ class TodoistRenameSharedLabelsBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistRenameSharedLabelsBlock.Input,
             output_schema=TodoistRenameSharedLabelsBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "name": "OldLabel",
@@ -526,6 +534,7 @@ class TodoistRemoveSharedLabelsBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistRemoveSharedLabelsBlock.Input,
             output_schema=TodoistRemoveSharedLabelsBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={"credentials": TEST_CREDENTIALS_INPUT, "name": "LabelToRemove"},
             test_credentials=TEST_CREDENTIALS,
             test_output=[("success", True)],

autogpt_platform/backend/backend/blocks/todoist/projects.py

@@ -4,6 +4,7 @@ from typing_extensions import Optional
 from backend.blocks.todoist._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TODOIST_OAUTH_IS_CONFIGURED,
     TodoistCredentials,
     TodoistCredentialsField,
     TodoistCredentialsInput,
@@ -35,6 +36,7 @@ class TodoistListProjectsBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistListProjectsBlock.Input,
             output_schema=TodoistListProjectsBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
@@ -150,6 +152,7 @@ class TodoistCreateProjectBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistCreateProjectBlock.Input,
             output_schema=TodoistCreateProjectBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={"credentials": TEST_CREDENTIALS_INPUT, "name": "Test Project"},
             test_credentials=TEST_CREDENTIALS,
             test_output=[("success", True)],
@@ -230,6 +233,7 @@ class TodoistGetProjectBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistGetProjectBlock.Input,
             output_schema=TodoistGetProjectBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "project_id": "2203306141",
@@ -332,6 +336,7 @@ class TodoistUpdateProjectBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistUpdateProjectBlock.Input,
             output_schema=TodoistUpdateProjectBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "project_id": "2203306141",
@@ -413,6 +418,7 @@ class TodoistDeleteProjectBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistDeleteProjectBlock.Input,
             output_schema=TodoistDeleteProjectBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "project_id": "2203306141",
@@ -481,6 +487,7 @@ class TodoistListCollaboratorsBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistListCollaboratorsBlock.Input,
             output_schema=TodoistListCollaboratorsBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "project_id": "2203306141",

autogpt_platform/backend/backend/blocks/todoist/sections.py

@@ -4,6 +4,7 @@ from typing_extensions import Optional
 from backend.blocks.todoist._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TODOIST_OAUTH_IS_CONFIGURED,
     TodoistCredentials,
     TodoistCredentialsField,
     TodoistCredentialsInput,
@@ -36,6 +37,7 @@ class TodoistListSectionsBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistListSectionsBlock.Input,
             output_schema=TodoistListSectionsBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "project_id": "2203306141",
@@ -207,6 +209,7 @@ class TodoistGetSectionBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistGetSectionBlock.Input,
             output_schema=TodoistGetSectionBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={"credentials": TEST_CREDENTIALS_INPUT, "section_id": "7025"},
             test_credentials=TEST_CREDENTIALS,
             test_output=[
@@ -275,6 +278,7 @@ class TodoistDeleteSectionBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistDeleteSectionBlock.Input,
             output_schema=TodoistDeleteSectionBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={"credentials": TEST_CREDENTIALS_INPUT, "section_id": "7025"},
             test_credentials=TEST_CREDENTIALS,
             test_output=[("success", True)],

autogpt_platform/backend/backend/blocks/todoist/tasks.py

@@ -7,6 +7,7 @@ from typing_extensions import Optional
 from backend.blocks.todoist._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TODOIST_OAUTH_IS_CONFIGURED,
     TodoistCredentials,
     TodoistCredentialsField,
     TodoistCredentialsInput,
@@ -86,6 +87,7 @@ class TodoistCreateTaskBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistCreateTaskBlock.Input,
             output_schema=TodoistCreateTaskBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "content": "Buy groceries",
@@ -217,6 +219,7 @@ class TodoistGetTasksBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistGetTasksBlock.Input,
             output_schema=TodoistGetTasksBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "project_id": "2203306141",
@@ -309,6 +312,7 @@ class TodoistGetTaskBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistGetTaskBlock.Input,
             output_schema=TodoistGetTaskBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={"credentials": TEST_CREDENTIALS_INPUT, "task_id": "2995104339"},
             test_credentials=TEST_CREDENTIALS,
             test_output=[
@@ -428,6 +432,7 @@ class TodoistUpdateTaskBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistUpdateTaskBlock.Input,
             output_schema=TodoistUpdateTaskBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "task_id": "2995104339",
@@ -467,32 +472,24 @@ class TodoistUpdateTaskBlock(Block):
             )
 
             task_updates = {}
-            if input_data.content is not None:
-                task_updates["content"] = input_data.content
-            if input_data.description is not None:
-                task_updates["description"] = input_data.description
-            if input_data.project_id is not None:
-                task_updates["project_id"] = input_data.project_id
-            if input_data.section_id is not None:
-                task_updates["section_id"] = input_data.section_id
-            if input_data.parent_id is not None:
-                task_updates["parent_id"] = input_data.parent_id
-            if input_data.order is not None:
-                task_updates["order"] = input_data.order
-            if input_data.labels is not None:
-                task_updates["labels"] = input_data.labels
-            if input_data.priority is not None:
-                task_updates["priority"] = input_data.priority
-            if due_date is not None:
-                task_updates["due_date"] = due_date
-            if deadline_date is not None:
-                task_updates["deadline_date"] = deadline_date
-            if input_data.assignee_id is not None:
-                task_updates["assignee_id"] = input_data.assignee_id
-            if input_data.duration is not None:
-                task_updates["duration"] = input_data.duration
-            if input_data.duration_unit is not None:
-                task_updates["duration_unit"] = input_data.duration_unit
+            update_fields = {
+                "content": input_data.content,
+                "description": input_data.description,
+                "project_id": input_data.project_id,
+                "section_id": input_data.section_id,
+                "parent_id": input_data.parent_id,
+                "order": input_data.order,
+                "labels": input_data.labels,
+                "priority": input_data.priority,
+                "due_date": due_date,
+                "deadline_date": deadline_date,
+                "assignee_id": input_data.assignee_id,
+                "duration": input_data.duration,
+                "duration_unit": input_data.duration_unit,
+            }
+
+            # Filter out None values
+            task_updates = {k: v for k, v in update_fields.items() if v is not None}
 
             self.update_task(
                 credentials,
@@ -526,6 +523,7 @@ class TodoistCloseTaskBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistCloseTaskBlock.Input,
             output_schema=TodoistCloseTaskBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={"credentials": TEST_CREDENTIALS_INPUT, "task_id": "2995104339"},
             test_credentials=TEST_CREDENTIALS,
             test_output=[("success", True)],
@@ -576,6 +574,7 @@ class TodoistReopenTaskBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistReopenTaskBlock.Input,
             output_schema=TodoistReopenTaskBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={"credentials": TEST_CREDENTIALS_INPUT, "task_id": "2995104339"},
             test_credentials=TEST_CREDENTIALS,
             test_output=[
@@ -628,6 +627,7 @@ class TodoistDeleteTaskBlock(Block):
             categories={BlockCategory.PRODUCTIVITY},
             input_schema=TodoistDeleteTaskBlock.Input,
             output_schema=TodoistDeleteTaskBlock.Output,
+            disabled=not TODOIST_OAUTH_IS_CONFIGURED,
             test_input={"credentials": TEST_CREDENTIALS_INPUT, "task_id": "2995104339"},
             test_credentials=TEST_CREDENTIALS,
             test_output=[

autogpt_platform/backend/backend/blocks/twitter/direct_message/direct_message_lookup.py

@@ -1,4 +1,4 @@
-# Todo : Add new Type support
+# Todo : Add new Type support, and disable block if it's Oauth is not configured
 
 # from typing import cast
 # import tweepy

autogpt_platform/backend/backend/blocks/twitter/direct_message/manage_direct_message.py

@@ -1,4 +1,4 @@
-# Todo : Add new Type support
+# Todo : Add new Type support, and disable block if it's Oauth is not configured
 
 # from typing import cast
 
@@ -156,7 +156,7 @@
 #         participant_ids: list[str] = SchemaField(
 #             description="Array of User IDs to create conversation with (max 50)",
 #             placeholder="Enter participant user IDs",
-#             default=[],
+#             default_factory=list,
 #             advanced=False
 #         )
 

autogpt_platform/backend/backend/blocks/twitter/lists/list_follows.py

@@ -4,6 +4,7 @@ import tweepy
 from backend.blocks.twitter._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TWITTER_OAUTH_IS_CONFIGURED,
     TwitterCredentials,
     TwitterCredentialsField,
     TwitterCredentialsInput,
@@ -44,6 +45,7 @@ class TwitterUnfollowListBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterUnfollowListBlock.Input,
             output_schema=TwitterUnfollowListBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={"list_id": "123456789", "credentials": TEST_CREDENTIALS_INPUT},
             test_credentials=TEST_CREDENTIALS,
             test_output=[
@@ -106,6 +108,7 @@ class TwitterFollowListBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterFollowListBlock.Input,
             output_schema=TwitterFollowListBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={"list_id": "123456789", "credentials": TEST_CREDENTIALS_INPUT},
             test_credentials=TEST_CREDENTIALS,
             test_output=[

autogpt_platform/backend/backend/blocks/twitter/lists/list_lookup.py

@@ -6,6 +6,7 @@ from tweepy.client import Response
 from backend.blocks.twitter._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TWITTER_OAUTH_IS_CONFIGURED,
     TwitterCredentials,
     TwitterCredentialsField,
     TwitterCredentialsInput,
@@ -39,7 +40,6 @@ class TwitterGetListBlock(Block):
         list_id: str = SchemaField(
             description="The ID of the List to lookup",
             placeholder="Enter list ID",
-            required=True,
         )
 
     class Output(BlockSchema):
@@ -64,6 +64,7 @@ class TwitterGetListBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterGetListBlock.Input,
             output_schema=TwitterGetListBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "list_id": "84839422",
                 "credentials": TEST_CREDENTIALS_INPUT,
@@ -184,7 +185,6 @@ class TwitterGetOwnedListsBlock(Block):
         user_id: str = SchemaField(
             description="The user ID whose owned Lists to retrieve",
             placeholder="Enter user ID",
-            required=True,
         )
 
         max_results: int | None = SchemaField(
@@ -222,6 +222,7 @@ class TwitterGetOwnedListsBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterGetOwnedListsBlock.Input,
             output_schema=TwitterGetOwnedListsBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "user_id": "2244994945",
                 "max_results": 10,

autogpt_platform/backend/backend/blocks/twitter/lists/list_members.py

@@ -6,6 +6,7 @@ from tweepy.client import Response
 from backend.blocks.twitter._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TWITTER_OAUTH_IS_CONFIGURED,
     TwitterCredentials,
     TwitterCredentialsField,
     TwitterCredentialsInput,
@@ -45,13 +46,11 @@ class TwitterRemoveListMemberBlock(Block):
         list_id: str = SchemaField(
             description="The ID of the List to remove the member from",
             placeholder="Enter list ID",
-            required=True,
         )
 
         user_id: str = SchemaField(
             description="The ID of the user to remove from the List",
             placeholder="Enter user ID to remove",
-            required=True,
         )
 
     class Output(BlockSchema):
@@ -67,6 +66,7 @@ class TwitterRemoveListMemberBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterRemoveListMemberBlock.Input,
             output_schema=TwitterRemoveListMemberBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "list_id": "123456789",
                 "user_id": "987654321",
@@ -120,13 +120,11 @@ class TwitterAddListMemberBlock(Block):
         list_id: str = SchemaField(
             description="The ID of the List to add the member to",
             placeholder="Enter list ID",
-            required=True,
         )
 
         user_id: str = SchemaField(
             description="The ID of the user to add to the List",
             placeholder="Enter user ID to add",
-            required=True,
         )
 
     class Output(BlockSchema):
@@ -142,6 +140,7 @@ class TwitterAddListMemberBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterAddListMemberBlock.Input,
             output_schema=TwitterAddListMemberBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "list_id": "123456789",
                 "user_id": "987654321",
@@ -195,7 +194,6 @@ class TwitterGetListMembersBlock(Block):
         list_id: str = SchemaField(
             description="The ID of the List to get members from",
             placeholder="Enter list ID",
-            required=True,
         )
 
         max_results: int | None = SchemaField(
@@ -234,6 +232,7 @@ class TwitterGetListMembersBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterGetListMembersBlock.Input,
             output_schema=TwitterGetListMembersBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "list_id": "123456789",
                 "max_results": 2,
@@ -376,7 +375,6 @@ class TwitterGetListMembershipsBlock(Block):
         user_id: str = SchemaField(
             description="The ID of the user whose List memberships to retrieve",
             placeholder="Enter user ID",
-            required=True,
         )
 
         max_results: int | None = SchemaField(
@@ -411,6 +409,7 @@ class TwitterGetListMembershipsBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterGetListMembershipsBlock.Input,
             output_schema=TwitterGetListMembershipsBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "user_id": "123456789",
                 "max_results": 1,

autogpt_platform/backend/backend/blocks/twitter/lists/list_tweets_lookup.py

@@ -6,6 +6,7 @@ from tweepy.client import Response
 from backend.blocks.twitter._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TWITTER_OAUTH_IS_CONFIGURED,
     TwitterCredentials,
     TwitterCredentialsField,
     TwitterCredentialsInput,
@@ -42,7 +43,6 @@ class TwitterGetListTweetsBlock(Block):
         list_id: str = SchemaField(
             description="The ID of the List whose Tweets you would like to retrieve",
             placeholder="Enter list ID",
-            required=True,
         )
 
         max_results: int | None = SchemaField(
@@ -82,6 +82,7 @@ class TwitterGetListTweetsBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterGetListTweetsBlock.Input,
             output_schema=TwitterGetListTweetsBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "list_id": "84839422",
                 "max_results": 1,

autogpt_platform/backend/backend/blocks/twitter/lists/manage_lists.py

@@ -6,6 +6,7 @@ from tweepy.client import Response
 from backend.blocks.twitter._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TWITTER_OAUTH_IS_CONFIGURED,
     TwitterCredentials,
     TwitterCredentialsField,
     TwitterCredentialsInput,
@@ -28,7 +29,6 @@ class TwitterDeleteListBlock(Block):
         list_id: str = SchemaField(
             description="The ID of the List to be deleted",
             placeholder="Enter list ID",
-            required=True,
         )
 
     class Output(BlockSchema):
@@ -42,6 +42,7 @@ class TwitterDeleteListBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterDeleteListBlock.Input,
             output_schema=TwitterDeleteListBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={"list_id": "1234567890", "credentials": TEST_CREDENTIALS_INPUT},
             test_credentials=TEST_CREDENTIALS,
             test_output=[("success", True)],
@@ -119,6 +120,7 @@ class TwitterUpdateListBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterUpdateListBlock.Input,
             output_schema=TwitterUpdateListBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "list_id": "1234567890",
                 "name": "Updated List Name",
@@ -215,6 +217,7 @@ class TwitterCreateListBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterCreateListBlock.Input,
             output_schema=TwitterCreateListBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "name": "New List Name",
                 "description": "New List Description",

autogpt_platform/backend/backend/blocks/twitter/lists/pinned_lists.py

@@ -6,6 +6,7 @@ from tweepy.client import Response
 from backend.blocks.twitter._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TWITTER_OAUTH_IS_CONFIGURED,
     TwitterCredentials,
     TwitterCredentialsField,
     TwitterCredentialsInput,
@@ -39,7 +40,6 @@ class TwitterUnpinListBlock(Block):
         list_id: str = SchemaField(
             description="The ID of the List to unpin",
             placeholder="Enter list ID",
-            required=True,
         )
 
     class Output(BlockSchema):
@@ -53,6 +53,7 @@ class TwitterUnpinListBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterUnpinListBlock.Input,
             output_schema=TwitterUnpinListBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={"list_id": "123456789", "credentials": TEST_CREDENTIALS_INPUT},
             test_credentials=TEST_CREDENTIALS,
             test_output=[("success", True)],
@@ -103,7 +104,6 @@ class TwitterPinListBlock(Block):
         list_id: str = SchemaField(
             description="The ID of the List to pin",
             placeholder="Enter list ID",
-            required=True,
         )
 
     class Output(BlockSchema):
@@ -117,6 +117,7 @@ class TwitterPinListBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterPinListBlock.Input,
             output_schema=TwitterPinListBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={"list_id": "123456789", "credentials": TEST_CREDENTIALS_INPUT},
             test_credentials=TEST_CREDENTIALS,
             test_output=[("success", True)],
@@ -186,6 +187,7 @@ class TwitterGetPinnedListsBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterGetPinnedListsBlock.Input,
             output_schema=TwitterGetPinnedListsBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "expansions": None,
                 "list_fields": None,

autogpt_platform/backend/backend/blocks/twitter/spaces/search_spaces.py

@@ -6,6 +6,7 @@ from tweepy.client import Response
 from backend.blocks.twitter._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TWITTER_OAUTH_IS_CONFIGURED,
     TwitterCredentials,
     TwitterCredentialsField,
     TwitterCredentialsInput,
@@ -78,6 +79,7 @@ class TwitterSearchSpacesBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterSearchSpacesBlock.Input,
             output_schema=TwitterSearchSpacesBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "query": "tech",
                 "max_results": 1,

autogpt_platform/backend/backend/blocks/twitter/spaces/spaces_lookup.py

@@ -7,6 +7,7 @@ from tweepy.client import Response
 from backend.blocks.twitter._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
+    TWITTER_OAUTH_IS_CONFIGURED,
     TwitterCredentials,
     TwitterCredentialsField,
     TwitterCredentialsInput,
@@ -44,7 +45,7 @@ class SpaceList(BaseModel):
     space_ids: list[str] = SchemaField(
         description="List of Space IDs to lookup (up to 100)",
         placeholder="Enter Space IDs",
-        default=[],
+        default_factory=list,
         advanced=False,
     )
 
@@ -54,7 +55,7 @@ class UserList(BaseModel):
     user_ids: list[str] = SchemaField(
         description="List of user IDs to lookup their Spaces (up to 100)",
         placeholder="Enter user IDs",
-        default=[],
+        default_factory=list,
         advanced=False,
     )
 
@@ -94,6 +95,7 @@ class TwitterGetSpacesBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterGetSpacesBlock.Input,
             output_schema=TwitterGetSpacesBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "identifier": {
                     "discriminator": "space_list",
@@ -227,7 +229,6 @@ class TwitterGetSpaceByIdBlock(Block):
         space_id: str = SchemaField(
             description="Space ID to lookup",
             placeholder="Enter Space ID",
-            required=True,
         )
 
     class Output(BlockSchema):
@@ -250,6 +251,7 @@ class TwitterGetSpaceByIdBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterGetSpaceByIdBlock.Input,
             output_schema=TwitterGetSpaceByIdBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "space_id": "1DXxyRYNejbKM",
                 "credentials": TEST_CREDENTIALS_INPUT,
@@ -389,7 +391,6 @@ class TwitterGetSpaceBuyersBlock(Block):
         space_id: str = SchemaField(
             description="Space ID to lookup buyers for",
             placeholder="Enter Space ID",
-            required=True,
         )
 
     class Output(BlockSchema):
@@ -411,6 +412,7 @@ class TwitterGetSpaceBuyersBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterGetSpaceBuyersBlock.Input,
             output_schema=TwitterGetSpaceBuyersBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "space_id": "1DXxyRYNejbKM",
                 "credentials": TEST_CREDENTIALS_INPUT,
@@ -517,7 +519,6 @@ class TwitterGetSpaceTweetsBlock(Block):
         space_id: str = SchemaField(
             description="Space ID to lookup tweets for",
             placeholder="Enter Space ID",
-            required=True,
         )
 
     class Output(BlockSchema):
@@ -540,6 +541,7 @@ class TwitterGetSpaceTweetsBlock(Block):
             categories={BlockCategory.SOCIAL},
             input_schema=TwitterGetSpaceTweetsBlock.Input,
             output_schema=TwitterGetSpaceTweetsBlock.Output,
+            disabled=not TWITTER_OAUTH_IS_CONFIGURED,
             test_input={
                 "space_id": "1DXxyRYNejbKM",
                 "credentials": TEST_CREDENTIALS_INPUT,