DEV Community: NocoBase

Weekly Updates: Added Structured AI Usage Records

NocoBase — Mon, 13 Jul 2026 06:43:59 +0000

Summarize the weekly product update logs, and the latest releases can be checked on our blog.

NocoBase is currently updated across three branches: main, next, and develop.

main: The most stable version to date, recommended for installation.
next: Beta version, contains upcoming new features and has been preliminarily tested. There might be some known or unknown issues. It is mainly used to collect feedback from test users and further optimize features. Ideal for test users who want to experience new features early and provide feedback.
develop: Alpha version, contains the latest feature code, may be incomplete or unstable, and is mainly used for internal development and rapid iteration. Suited for technical users interested in cutting-edge product capabilities, but not recommended for production use.

main

v2.1.23

Release date: 2026-07-10

🐛 Bug Fixes

[client-v2]
- Fixed v2 ScanInput recognition for Safari QR images selected from the upload path. (#10011)by katherinehhh
- Fixed client runtime asset base URL normalization when __webpack_public_path__ is injected without a trailing slash, and added coverage for that edge case. (#10040)by chenos
- Fixed an issue where button linkage rule states in table blocks could become polluted after pagination. (#10038)by gchust
[app] Fix lazy-loaded assets using an external script URL when CDN_BASE_URL is empty. (#10052)by Molunerfinn
[flow-engine] Fixed an issue where overriding ctx.api in a JS block could cause a Maximum call stack size exceeded error. (#10051)by gchust
[Workflow: Delay node] Prevented delay nodes from accepting numeric durations less than 1 through the API (#10057)by mytharcher
[Form drafts] Fixed form drafts disappearing after consecutive page refreshes (#10059)by gchust
[Data source: Main] Prevented invalid many-to-many relationship field configurations from being saved (#10044)by 2013xile
[Collection: Tree] Fixed tree path collection creation to avoid passing internal field model metadata into collection options. (#10035)by cgyrock
[Workflow] Fixed subflow nodes remaining pending when the child workflow fails before creating an execution record (#10043)by mytharcher
[Flow engine]
- Fixed an issue where using a local AI agent to configure linkage rules could trigger rendering errors. (#10023)by gchust
- Fixed popup record variables failing to resolve from external NocoBase data sources (#10048)by gchust
[Template print] Fixed template print permission checks so hidden fields and records outside the current role's view scope are not rendered.by jiannx
[Workflow: Approval]
- Allow string type of assignee ID to be addedby mytharcher
- Fix approval form fields becoming single-column in print previewby zhangzhonghe
- Fix the issue where fields in disabled approval subtables can still be editedby zhangzhonghe

v2.1.22

Release date: 2026-07-09

🐛 Bug Fixes

[client-v2]
- Fix association fields showing the default operator setting in filter forms (#10025)by zhangzhonghe
- Fix mobile popup spacing for table quick edit and select fields (#10020)by zhangzhonghe
[cli] Fixed NocoBase CLI default value issues for image registry fallback, built-in database images, env info display, and prompt initialization. (#10027)by chenos
[Authentication] Fix the issue where reset password links open the sign-in page (#10006)by zhangzhonghe

v2.1.21

Release date: 2026-07-08

🎉 New Features

[AI employees] Add OrcaRouter as an LLM provider (#10003)by jinhaosong-source

🚀 Improvements

[Workflow] Remove arithmetic operators for condition node (#10019)by mytharcher

🐛 Bug Fixes

[client-v2]
- Fixed stale linkage field states when switching records in runtime edit popups. (#10010)by katherinehhh
- Fixed an issue where association field default values in filter forms could not be cleared. (#10022)by gchust
[File manager]
- Reject active-content filenames during file upload unless the configured storage MIME type rule explicitly allows them. (#10021)by mytharcher Reference: Local storage, Security guide
- Fixed missing Attachment field interface in v2 data table management, and fixed image upload preflight checks for public form file relationship fields. (#10012)by katherinehhh
[Data source manager] Hide the historical attachment field interface from the V2 data table Add field menu. (#10018)by katherinehhh
[Data visualization] Fixed chart click interactions that could stop working after chart rerendering (#10031)by 2013xile
[Migration manager] Fixed an issue where migration could leave an app stuck on the repair screenby 2013xile
[App supervisor] Fixed app JWT secret isolation so main app tokens are no longer accepted by sub apps after an independent secret is enabledby 2013xile

v2.1.20

Release date: 2026-07-07

🚀 Improvements

[cli]
- Improved the Docker CLI setup by supporting configurable default NocoBase image registry/variant, fixing proxy and no-nginx image port compatibility, and adding Docker Nginx/Caddy installation guides. (#9972)by chenos
- Refactor CLI setup startup to reuse nb app start, normalize API base path redirects, persist shared env proxy defaults, and rebuild Docker proxy containers when published ports change. (#9997)by chenos

🐛 Bug Fixes

[client-v2]
- Fixed Vditor asset loading in production by resolving plugin CDN paths from the effective webpack public path. (#10008)by chenos
- Fixed an issue where Quick Edit could fail to switch dropdown options when navigating between pages. (#10007)by gchust
[flow-engine] Fixed an issue where popup configuration became inconsistent when toggling design modes. (#10005)by gchust
[File manager] Reject active-content filenames during file upload unless the configured storage MIME type rule explicitly allows them. (#9994)by mytharcher
Reference: Local storage, Security guide
[Data source: External MariaDB] Fix Add all collections toggle in MySQL, MSSQL, and MariaDB external data source settings.by katherinehhh

v2.2.0-beta.13

Release date: 2026-07-12

🐛 Bug Fixes

[Redis worker ID allocator] Restored standalone startup without Redis worker ID configurationby 2013xile

v2.2.0-beta.12

Release date: 2026-07-11

🐛 Bug Fixes

[server] Fixed custom portals missing when multi-application plugins are disabled (#10055)by 2013xile
[app] Fixed Redis cache configuration ignoring the dedicated cache URL (#10065)by 2013xile
[Redis worker ID allocator] Improved Redis worker ID isolation and failure diagnosticsby 2013xile

v2.2.0-beta.11

Release date: 2026-07-11

🐛 Bug Fixes

[app] Fix lazy-loaded assets using an external script URL when CDN_BASE_URL is empty. (#10052)by Molunerfinn
[client-v2]
- Fixed v2 ScanInput recognition for Safari QR images selected from the upload path. (#10011)by katherinehhh
- Fixed an issue where button linkage rule states in table blocks could become polluted after pagination. (#10038)by gchust
- Fixed client runtime asset base URL normalization when __webpack_public_path__ is injected without a trailing slash, and added coverage for that edge case. (#10040)by chenos
[flow-engine] Fixed an issue where overriding ctx.api in a JS block could cause a Maximum call stack size exceeded error. (#10051)by gchust
[Workflow: Delay node] Prevented delay nodes from accepting numeric durations less than 1 through the API (#10057)by mytharcher
[Form drafts] Fixed form drafts disappearing after consecutive page refreshes (#10059)by gchust
[Workflow] Fixed subflow nodes remaining pending when the child workflow fails before creating an execution record (#10043)by mytharcher
[Flow engine]
- Fixed an issue where using a local AI agent to configure linkage rules could trigger rendering errors. (#10023)by gchust
- Fixed popup record variables failing to resolve from external NocoBase data sources (#10048)by gchust
[Data source: Main] Prevented invalid many-to-many relationship field configurations from being saved (#10044)by 2013xile
[Collection: Tree] Fixed tree path collection creation to avoid passing internal field model metadata into collection options. (#10035)by cgyrock
[Template print] Fixed template print permission checks so hidden fields and records outside the current role's view scope are not rendered.by jiannx
[Workflow: Approval]
- Allow string type of assignee ID to be addedby mytharcher
- Fix approval form fields becoming single-column in print previewby zhangzhonghe
- Fix the issue where fields in disabled approval subtables can still be editedby zhangzhonghe

v2.2.0-beta.10

Release date: 2026-07-09

🎉 New Features

[AI employees]
- Add OrcaRouter as an LLM provider (#10003)by jinhaosong-source
- Added structured AI usage records for usage statistics (#10004)by 2013xile

🚀 Improvements

[Workflow] Remove arithmetic operators for condition node (#10019)by mytharcher
[Data visualization] Improved chart event scripts so custom event handlers can clean up safely (#10034)by 2013xile
[Data source manager] Hide deprecated v2 main data source collection templates from the create collection menu. (#10009)by katherinehhh

🐛 Bug Fixes

[client-v2]
- Fix association fields showing the default operator setting in filter forms (#10025)by zhangzhonghe
- Fix mobile popup spacing for table quick edit and select fields (#10020)by zhangzhonghe
- Fixed an issue where association field default values in filter forms could not be cleared. (#10022)by gchust
- Fixed stale linkage field states when switching records in runtime edit popups. (#10010)by katherinehhh
- Fixed an issue where Quick Edit could fail to switch dropdown options when navigating between pages. (#10007)by gchust
- Fixed Vditor asset loading in production by resolving plugin CDN paths from the effective webpack public path. (#10008)by chenos
[cli] Fixed NocoBase CLI default value issues for image registry fallback, built-in database images, env info display, and prompt initialization. (#10027)by chenos
[flow-engine] Fixed an issue where popup configuration became inconsistent when toggling design modes. (#10005)by gchust
[Data visualization] Fixed chart click interactions that could stop working after chart rerendering (#10031)by 2013xile
[AI employees] Fix unnecessary login-required requests on V2 public form pages (#10013)by zhangzhonghe
[Authentication] Fix the issue where reset password links open the sign-in page (#10006)by zhangzhonghe
[Data source manager] Hide the historical attachment field interface from the V2 data table Add field menu. (#10018)by katherinehhh
[File manager]
- Reject active-content filenames during file upload unless the configured storage MIME type rule explicitly allows them. (#10021)by mytharcher Reference: Local storage, Security guide
- Fixed missing Attachment field interface in v2 data table management, and fixed image upload preflight checks for public form file relationship fields. (#10012)by katherinehhh
[Embed NocoBase] Fixed an issue where tokens could be polluted when embedding NocoBase pages. (#9948)by gchust
[Data source: External MariaDB] Fix Add all collections toggle in MySQL, MSSQL, and MariaDB external data source settings.by katherinehhh
[Migration manager] Fixed an issue where migration could leave an app stuck on the repair screenby 2013xile
[App supervisor] Fixed app JWT secret isolation so main app tokens are no longer accepted by sub apps after an independent secret is enabledby 2013xile

develop

v2.2.0-alpha.8

Release date: 2026-07-13

🎉 New Features

[Public forms] In the v1 public form, support creating v2 forms and prohibit creating v1 forms (#10045)by zhangzhonghe

🚀 Improvements

[Workflow] Unsupported workflow v2 canvas nodes now keep the normal node card actions while showing the node type as unsupported. (#10054)by mytharcher
[Flow engine] Support multi portals for ui build apis. (#10072)by gchust
[AI employees] Improved AI employee tool settings, data-query guardrails, relation field querying, and malformed tool call diagnostics. (#10042)by cgyrock
[Collection: SQL] Not user-facing; added client-v2 unit test coverage for migrated plugins. (#9967)by katherinehhh

🐛 Bug Fixes

[client-v2]
- Fix an error in v2 workflow value editors when a collection field is named nodeName. (#10067)by katherinehhh
- Fixed an issue where button linkage rule states in table blocks could become polluted after pagination. (#10038)by gchust
- Fixed workflow v2 variable editors to preserve saved variable pills, disabled states, and operator labels consistently across trigger, filter, and field assignment forms. (#10041)by Molunerfinn
[app]
- Fixed Redis cache configuration ignoring the dedicated cache URL (#10065)by 2013xile
- Fix lazy-loaded assets using an external script URL when CDN_BASE_URL is empty. (#10052)by Molunerfinn
[server] Fixed custom portals missing when multi-application plugins are disabled (#10055)by 2013xile
[flow-engine]
- Fixed an issue where users could type extra text after selecting a variable in single-value variable inputs. (#10050)by katherinehhh
- Fixed an issue where overriding ctx.api in a JS block could cause a Maximum call stack size exceeded error. (#10051)by gchust
[Workflow: Delay node]
- Fix delay node duration input and prevent values below the minimum from being saved. (#10056)by Molunerfinn
- Prevented delay nodes from accepting numeric durations less than 1 through the API (#10057)by mytharcher
[Workflow]
- Fixed subflow nodes remaining pending when the child workflow fails before creating an execution record (#10043)by mytharcher
- Fixed manual workflow execution returning an error when a valid request does not start an execution. (#10049)by mytharcher
[Data source: Main] Prevented invalid many-to-many relationship field configurations from being saved (#10044)by 2013xile
[Flow engine] Fixed popup record variables failing to resolve from external NocoBase data sources (#10048)by gchust
[Form drafts] Fixed form drafts disappearing after consecutive page refreshes (#10059)by gchust
[Workflow: Aggregate node] Fix validation rule to allow null filter (#10053)by mytharcher
[Redis worker ID allocator]
- Restored standalone startup without Redis worker ID configurationby 2013xile
- Improved Redis worker ID isolation and failure diagnosticsby 2013xile
[plugin-service-platform] Restored licensed plugin downloads from the service platform.by jiannx
[Template print] Fixed template print permission checks so hidden fields and records outside the current role's view scope are not rendered.by jiannx
[Workflow: Approval]
- Fix v2 approval subtables not displaying correctly in detailsby zhangzhonghe
- Fix empty approval interfaces and fixed assignee IDsby zhangzhonghe
- Fix the issue where fields in disabled approval subtables can still be editedby zhangzhonghe
- Allow string type of assignee ID to be addedby mytharcher
- Fix approval form fields becoming single-column in print previewby zhangzhonghe
- Close the Apply new drawer when opening an approval formby zhangzhonghe
- Fix missing approval data on approval task cardsby zhangzhonghe

v2.2.0-alpha.7

Release date: 2026-07-09

🎉 New Features

[AI employees]
- Add OrcaRouter as an LLM provider (#10003)by jinhaosong-source
- Added structured AI usage records for usage statistics (#10004)by 2013xile
[Workflow: Approval] Add approval initiation and todo blocks for v2 pagesby zhangzhonghe

🚀 Improvements

[client-v2]
- Refactor Markdown Vditor into a unified plugin-backed Markdown engine with compatibility bridges for existing Markdown block and Vditor field plugins. (#9998)by katherinehhh
[AI employees] Improved AI employee web search to reduce unnecessary model reasoning and better use provider-specific thinking controls. (#9996)by cgyrock
[Data visualization] Improved chart event scripts so custom event handlers can clean up safely (#10034)by 2013xile
[Workflow] Remove arithmetic operators for condition node (#10019)by mytharcher
[Data source manager] Hide deprecated v2 main data source collection templates from the create collection menu. (#10009)by katherinehhh
[Block: Comment] Improved comment submit actions and fixed related comment/user form submission issues. (#10002)by jiannx

🐛 Bug Fixes

[client-v2]
- Fixed client runtime asset base URL normalization when __webpack_public_path__ is injected without a trailing slash, and added coverage for that edge case. (#10040)by chenos
- Fixed v2 ScanInput recognition for Safari QR images selected from the upload path. (#10011)by katherinehhh
- Fix association fields showing the default operator setting in filter forms (#10025)by zhangzhonghe
- Fix mobile popup spacing for table quick edit and select fields (#10020)by zhangzhonghe
- Fixed an issue where Quick Edit could fail to switch dropdown options when navigating between pages. (#10007)by gchust
- Fixed Vditor asset loading in production by resolving plugin CDN paths from the effective webpack public path. (#10008)by chenos
- Fixed stale linkage field states when switching records in runtime edit popups. (#10010)by katherinehhh
- Fixed an issue where association field default values in filter forms could not be cleared. (#10022)by gchust
- Fixed an issue where v2 workflow assigned fields could still be edited in read-only executed workflow versions. (#10014)by katherinehhh
[cli] Fixed NocoBase CLI default value issues for image registry fallback, built-in database images, env info display, and prompt initialization. (#10027)by chenos
[flow-engine] Fixed an issue where popup configuration became inconsistent when toggling design modes. (#10005)by gchust
[Collection: Tree] Fixed tree path collection creation to avoid passing internal field model metadata into collection options. (#10035)by cgyrock
[Public forms] Fix the issue where public forms can still be configured when UI Editor is off (#10036)by zhangzhonghe
[Flow engine] Fixed an issue where using a local AI agent to configure linkage rules could trigger rendering errors. (#10023)by gchust
[Authentication] Fix the issue where reset password links open the sign-in page (#10006)by zhangzhonghe
[Data visualization] Fixed chart click interactions that could stop working after chart rerendering (#10031)by 2013xile
[Workflow]
- Fixed workflow v2 condition operands to stay on one row by default and wrap correctly when selected variable paths are too long. (#10033)by Molunerfinn
- Fix untranslated workflow result labels and oversized CC configuration dialogs (#9977)by zhangzhonghe
- Fix display and detail loading issues in the workflow v2 task center (#10001)by zhangzhonghe
[Data source manager] Hide the historical attachment field interface from the V2 data table Add field menu. (#10018)by katherinehhh
[File manager]
- Reject active-content filenames during file upload unless the configured storage MIME type rule explicitly allows them. (#10021)by mytharcher Reference: Local storage, Security guide
- Reject active-content filenames during file upload unless the configured storage MIME type rule explicitly allows them. (#9994)by mytharcher Reference: Local storage, Security guide
- Fixed missing Attachment field interface in v2 data table management, and fixed image upload preflight checks for public form file relationship fields. (#10012)by katherinehhh
[Embed NocoBase] Fixed an issue where tokens could be polluted when embedding NocoBase pages. (#9948)by gchust
[AI employees] Fix unnecessary login-required requests on V2 public form pages (#10013)by zhangzhonghe
[AI: Knowledge base] Added an overwrite option for AI knowledge base workflow document creation, allowing workflows to replace existing documents with the same key.by cgyrock
[Data source: External MariaDB] Fix Add all collections toggle in MySQL, MSSQL, and MariaDB external data source settings.by katherinehhh
[plugin-service-platform] Disabled the service platform plugin download endpoint.by jiannx
[Workflow: Subflow] Fixed workflow title search in the subflow node configuration selector.by mytharcher
[Migration manager] Fixed an issue where migration could leave an app stuck on the repair screenby 2013xile
[Workflow: Approval]
- Fix approval assignee sorting and hide unsupported legacy configuration entriesby zhangzhonghe
- Fix the error when configuring approval workflow conditionsby zhangzhonghe
- Fix missing processed approval details in v2 task detail popupsby zhangzhonghe
- Fix approval task form and action issues in the workflow v2 task centerby zhangzhonghe
[App supervisor] Fixed app JWT secret isolation so main app tokens are no longer accepted by sub apps after an independent secret is enabledby 2013xile

Build an Interactive Operations Dashboard with NocoBase

NocoBase — Fri, 10 Jul 2026 07:28:47 +0000

Originally published at https://www.nocobase.com/en/blog/build-interactive-operations-dashboard-with-nocobase

This article uses an operations dashboard for a ticketing system as an example. It shows how to combine NocoBase chart blocks, filter blocks, and JS blocks to build a data dashboard that supports linked filters, chart drilldowns, and custom styling.

Although the example comes from a ticketing scenario, the same approach also applies to CRM, equipment maintenance, project management, approval workflows, customer success, and other business systems.

💡 The point of this article is not to show how to write a large dashboard with a JS block. Instead, it explains how to combine NocoBase native blocks with JS blocks: native blocks handle standard capabilities, while JS blocks fill in the personalized experience.

💬 Hey, you're reading the NocoBase blog. NocoBase is the most extensible AI-powered no-code/low-code development platform for building enterprise applications, internal tools, and all kinds of systems. It’s fully self-hosted, plugin-based, and developer-friendly. → Explore NocoBase on GitHub

Scenario Goal

We want to build an Operations dashboard that helps operations or service teams quickly understand the current workload:

How many tickets are still open
Which tickets have SLA risks
How new ticket volume is trending
How tickets are distributed by status and priority
How to view matching records after clicking a chart

The page can be roughly divided into four layers:

Top filter area: time, service group, request type, priority, and SLA status
KPI area: Open backlog, Unassigned, SLA warning, and more
Chart analysis area: trends, status distribution, SLA distribution, and priority mix
Drilldown detail area: show matching records after a chart click

Start with the Right Building Approach

When building a data dashboard, it is easy to turn the problem into a binary choice.

Either you use only NocoBase native blocks, which are easy to configure but may feel less flexible in styling and interaction; or you write a large JS block and control queries, charts, filters, and drilldowns yourself, which means losing much of the convenience that low-code configuration provides.

A better approach is to combine the two.

In this Operations dashboard, we do not write the entire page as one large JS dashboard. Instead, we split responsibilities:

The top filters use NocoBase’s built-in filter block.
Trend charts, status distribution, and SLA distribution use native chart blocks.
KPI cards and drilldown details use JS blocks.
The filter block affects both chart blocks and JS blocks.
After a chart click, the drilldown condition is passed to the JS detail block below.

The benefit is clear: standard statistics and filtering still keep NocoBase’s configuration capabilities, while personalized display and complex interactions are handled by JS blocks. The page is neither “configuration only” nor “all code.” Configuration and code each handle what they are good at.

1. How to Customize Chart Block Styles

In a NocoBase chart block, you can first define the aggregation logic with Query builder, and then adjust the style with a custom ECharts option.

Using “ticket status statistics” as an example, Query builder can be configured as follows:

Data table: tickets
Metric: id count, alias ticketCount
Dimension: status

The key point is that when customizing the style, you do not need to rewrite the query. You only need to process the chart display based on ctx.data.objects.

const rows = Array.isArray(ctx.data?.objects) ? ctx.data.objects : [];

This line reads the chart query result. Then define the status labels and colors:

const labels = {
  new: ctx.t('New'),
  open: ctx.t('Open'),
  pending_customer: ctx.t('Pending customer'),
  resolved: ctx.t('Resolved'),
  closed: ctx.t('Closed'),
};

const colors = {
  new: '#1677ff',
  open: '#22a06b',
  pending_customer: '#f59f00',
  resolved: '#13c2c2',
  closed: '#8c8c8c',
};

It is recommended to use ctx.t() for all visible text so that multilingual support can be added later.

When generating chart data, you can attach drilldown information to each chart data point:

const data = rows.map((row) => ({
  value: Number(row.ticketCount || 0),
  itemStyle: {
    color: colors[row.status] || '#8c8c8c',
    borderRadius: [6, 6, 0, 0],
  },
  ticketingDrilldown: {
    label: ctx.t('Status') + ': ' + (labels[row.status] || row.status),
    filter: { status: { $eq: row.status } },
  },
}));

The most important part here is ticketingDrilldown. It is not a standard ECharts field. It is business context that we put into the data ourselves, and it will be used later when the user clicks the chart.

Finally, return the ECharts option:

return {
  grid: { top: 28, right: 22, bottom: 48, left: 42 },
  tooltip: { trigger: 'axis', axisPointer: { type: 'shadow' } },
  xAxis: {
    type: 'category',
    data: rows.map((row) => labels[row.status] || row.status),
  },
  yAxis: {
    type: 'value',
    minInterval: 1,
  },
  series: [
    {
      name: ctx.t('Tickets'),
      type: 'bar',
      barWidth: 36,
      data,
    },
  ],
};

The core idea of this part is:

Query builder is responsible for statistical data.
Custom option is responsible for visual expression.
Custom fields carry drilldown context.

2. Make the System Filter Block the Observation Scope for the Whole Page

The filter area in an operations dashboard should not be an isolated form. It represents the current observation scope of the entire page.

For example, when a user selects a service group, a request type, and a creation time range, the KPI cards, trend chart, status distribution, and drilldown details should all be displayed under the same conditions. Otherwise, numbers from different blocks may conflict with each other, making it hard for users to know which result belongs to the current scope.

Here, we directly use NocoBase’s built-in filter block instead of writing a custom filter component. The native filter block can be naturally bound to chart blocks, allowing the Chart block to continue using Query builder, permissions, refresh, and filtering mechanisms.

The top Dashboard scope can include these filter fields:

Created at
Service group
Request type
Priority
SLA status

For JS blocks, you only need to read the same set of filter conditions in code and convert them into a query filter. This allows KPI cards and drilldown details to stay consistent with native charts.

The filter combination can be wrapped as a small function:

function combineFilters(...filters) {
  const parts = filters.filter(Boolean);
  if (!parts.length) return undefined;
  if (parts.length === 1) return parts[0];
  return { $and: parts };
}

Count records by filter condition:

async function countTickets(filter) {
  const resource = ctx.makeResource('MultiRecordResource');
  resource.setResourceName('tickets');
  resource.setPageSize(1);

  if (filter) {
    resource.setFilter(filter);
  }

  await resource.refresh();

  const meta = resource.getMeta?.() || {};
  return Number(meta.count || meta.total || 0);
}

The key lines are:

resource.setFilter(filter);
await resource.refresh();

JS blocks query business data through resource instead of directly writing SQL. This makes it easier to stay aligned with NocoBase permissions, data sources, and page runtime behavior.

3. Use JS Blocks to Display KPI Cards

KPI cards are better suited to JS blocks, because a KPI is usually not a single query. It is often a combination of several business metrics, such as unfinished tickets, unassigned tickets, SLA warning, SLA breached, new tickets, and resolved tickets.

A JS block can re-query data according to the current filter scope and render the results as statistic cards.

const { Card, Col, Row, Statistic, Tag } = ctx.libs.antd;

const scopeFilter = getDashboardScopeFilter();

const openBacklog = await countTickets(
  combineFilters(scopeFilter, {
    status: { $notIn: ['resolved', 'closed', 'cancelled'] },
  }),
);

ctx.render(
  <Row gutter={[12, 12]}>
    <Col span={6}>
      <Card size="small">
        <Tag color="blue">{ctx.t('Active')}</Tag>
        <Statistic title={ctx.t('Open backlog')} value={openBacklog} />
      </Card>
    </Col>
  </Row>,
);

The key points for JS blocks are:

Use ctx.makeResource() to query data.
Use ctx.libs.antd to render the UI.
Use ctx.render() to output content.
Re-render the JS block after filters change.

On a real page, filter and reset buttons can be configured with event flows. After they complete the native filter action, they can also refresh the KPI JS block and the drilldown JS block. This way, one click updates both the charts and the custom content under the same scope.

4. Link Chart Blocks with a JS Block for Drilldown

Chart drilldown is a very useful dashboard interaction.

In a ticketing scenario, when the user clicks the “Status: Open” bar, the detail area below shows all Open tickets. When the user clicks “SLA breached,” the detail area shows all overdue tickets.

The implementation idea is:

Attach ticketingDrilldown to chart data points.
Read the drilldown information from the chart event.
Write the drilldown information into the target JS block context.
Trigger the target JS block to re-render.

The key code in the chart event is shown below. First, locate the drilldown JS block:

const DRILLDOWN_TARGET_UID = 'v7mioopm6rm';

function getDrilldownTarget() {
  if (typeof ctx.getModel === 'function') {
    return ctx.getModel(DRILLDOWN_TARGET_UID);
  }

  const engine = ctx.model?.flowEngine || ctx.model?.context?.flowEngine || ctx.engine;
  return engine?.getModel?.(DRILLDOWN_TARGET_UID);
}

Then write the drilldown condition from the chart click into the target block:

function applyDrilldown(drilldown) {
  if (!drilldown?.filter) return;

  const target = getDrilldownTarget();
  if (!target?.context?.defineProperty) return;

  target.context.defineProperty('ticketingDashboardDrilldown', {
    value: drilldown,
  });

  target.rerender?.();
}

The most important lines are:

target.context.defineProperty('ticketingDashboardDrilldown', { value: drilldown });
target.rerender?.();

The first line passes the drilldown condition to the JS block, and the second line triggers the JS block to refresh.

Finally, bind the chart click event:

const clickHandler = (params) => {
  applyDrilldown(params?.data?.ticketingDrilldown);
};

chart.on('click', clickHandler);

return () => chart.off('click', clickHandler);

It is strongly recommended to return a cleanup function:

return () => chart.off('click', clickHandler);

This cleans up old events when the chart is reconfigured or re-rendered, avoiding duplicate event bindings.

The chart click event code above applies to v2.2.0-beta.10 and later. For earlier versions, refer to:

chart.off('click');
chart.on('click', clickHandler);

5. How the Drilldown JS Block Displays Details

The drilldown JS block reads the ticketingDashboardDrilldown written earlier, and then queries data based on its filter.

const drilldown = ctx.model?.context?.ticketingDashboardDrilldown;

if (!drilldown) {
  ctx.render(
    <Alert
      type="info"
      showIcon
      message={ctx.t('Select a chart segment to inspect matching tickets')}
    />,
  );
  return;
}

If the user has not clicked a chart yet, a prompt is displayed. After a click, tickets are queried according to drilldown.filter:

const resource = ctx.makeResource('MultiRecordResource');
resource.setResourceName('tickets');
resource.setFilter(drilldown.filter);
resource.setPageSize(10);
await resource.refresh();

const rows = resource.getData?.() || [];

Then render the table:

const { Table, Typography } = ctx.libs.antd;

ctx.render(
  <>
    <Typography.Title level={5}>
      {ctx.t('Drilldown')}: {drilldown.label}
    </Typography.Title>

    <Table
      size="small"
      rowKey="id"
      dataSource={rows}
      pagination={false}
      columns={[
        { title: ctx.t('Ticket No'), dataIndex: 'ticketNo' },
        { title: ctx.t('Title'), dataIndex: 'title' },
        { title: ctx.t('Status'), dataIndex: 'status' },
        { title: ctx.t('Priority'), dataIndex: 'priority' },
      ]}
    />
  </>,
);

To clear the drilldown condition, you can refer to:

function clearChartDrilldown() {
  if (ctx.model?.context?.defineProperty) {
    ctx.model.context.defineProperty('ticketingDashboardDrilldown', { value: null });
  }
  if (typeof ctx.model?.rerender === 'function') {
    ctx.model.rerender();
  }
}

The key points here are:

The chart only passes the filter.
The JS block is responsible for querying and displaying details.
The same drilldown block can be reused by clicks from different charts.

Practical Recommendations

1. Do Not Rush to Code the Whole Complex Page

The most important lesson from this page is: do not treat native capabilities and JS capabilities as opposites.

If a capability is already native to NocoBase, such as filtering, chart queries, table display, permission control, use the native block first. This allows you to continue configuring fields, filter conditions, and chart metrics in the interface later.

JS blocks are better for parts that native blocks are not good at, such as combining multiple metrics into KPI cards, applying special card styles, showing custom details after a chart click, or passing business context between different blocks.

In other words, native blocks handle “configurable standard capabilities,” while JS blocks handle “business-specific personalized experiences.” This is the most reusable building approach from this dashboard.

2. Use Chart Block Query Builder First for Simple Statistics

This preserves NocoBase’s standard query, permission, filtering, and refresh capabilities. Only use a custom ECharts option for visual optimization when the default chart style cannot express the business emphasis clearly.

3. Use JS Blocks First for KPI Cards

KPIs usually need multiple queries, condition combinations, and custom layouts, so JS blocks are more flexible. This is especially clear when KPIs need to respond to the same set of system filter conditions.

4. Return Cleanup for Chart Events

Recommended pattern:

const handler = (params) => {
  // handle click
};

chart.on('click', handler);

return () => chart.off('click', handler);

Do not directly use chart.off('click') to clear all click events, because this may accidentally remove listeners used by the chart block or configuration panel.

Let AI Help You Build It

This type of dashboard is very suitable for AI-assisted generation, because it involves data models, statistical definitions, chart styling, and page interactions at the same time. You can give this article to an AI tool and ask questions based on the prompt below.

You can ask:

I am building an operations dashboard for a ticketing system with NocoBase.
Please use the ticketing scenario as an example and help me design an Operations dashboard.

The tickets table contains:
ticketNo, title, status, priority, slaStatus,
requestType, serviceGroup, assignee, createdAt, updatedAt.

The page needs:
1. Top filters: Created at, Service group, Request type, Priority, SLA status.
2. KPI cards: Open backlog, Unassigned, SLA warning, SLA breached, New tickets, Resolved tickets.
3. Charts: Created tickets trend, Ticket status, SLA status, Priority mix.
4. After a chart click, the JS block below displays a matching Ticket drilldown table.
5. The chart style should fit an operations dashboard, with clear colors and a compact layout.
6. All JS text should use ctx.t().
7. Chart events should use chart.on and return a cleanup function.
8. Prefer NocoBase native filter blocks and chart blocks. Use JS blocks only for KPIs, drilldown details, special styling, and cross-block interactions. Do not write the whole page as one large JS block.

Please provide the configuration approach for each block and mark the key JS code.

If you already have a page, you can also ask AI to optimize it:

This is my current NocoBase dashboard design:
The top area is a filter block, the middle area has four charts, and the bottom area has a drilldown JS block.
Please help me optimize it from the perspective of operations staff:
1. Which KPIs should be displayed?
2. Do the charts need to be linked?
3. Which columns should be shown in drilldown details?
4. How should JS blocks and chart events be organized?
5. Which code should be placed in the chart custom option, and which code should be placed in the JS block?

This helps the AI generate content that is closer to real business scenarios instead of isolated code snippets.

If you choose to let AI help you build, back up the project with Backup Manager before you start.

Reference Documentation

What Is AI No-Code? A Practical Guide to No-Code Platforms in the AI Era

NocoBase — Thu, 09 Jul 2026 09:04:41 +0000

Originally published at https://www.nocobase.com/en/blog/what-is-ai-no-code

Introduction

Do you also think no-code belongs to the “pre-AI era”?

Now that AI can write code, generate applications, and automate workflows, do no-code platforms still need to exist?

The answer is yes.

Google Trends shows that search interest in “AI no code” has risen quickly over the past year.

People are not giving up on no-code. They are understanding it in a new way: not just dragging components to build pages, but using AI, natural language, and visual platforms to build applications, automate workflows, and create internal business systems faster.

The problem is that many products can now be called AI no-code.

Lovable, Zapier, and NocoBase all fall under the broader category of AI no-code, but they solve very different problems and suit very different users.

This article will answer two questions:

What is AI no-code?
How do you choose the right AI no-code tool?

What Is AI No-Code?

At the most basic level, AI no-code refers to tools or platforms that combine AI capabilities with no-code development methods. Users do not need to write code from scratch. Instead, they can use natural language, visual configuration, prebuilt components, workflow orchestration, and similar methods to build applications, automate processes, or let AI participate in specific business tasks.

But this definition only explains part of the picture.

Today, “AI no-code” is no longer a product category with clear boundaries. Many tools can be related to AI no-code, but their product logic can be completely different.

No-code platforms are adding AI to help users build pages, forms, data models, and business workflows faster.
Low-code platforms are using AI to help developers generate code, configure APIs, and extend systems.
AI app builders let users generate pages, components, or application prototypes directly from prompts.
AI automation tools connect multiple tools and use AI to summarize, classify, judge, and trigger actions.

These categories also continue to overlap. An AI app builder may offer a database. An automation tool may support simple pages. A no-code platform may connect to AI Agents and workflows.

It can get confusing.

A clearer way to think about it is this: stop asking whether a tool is truly AI no-code or where its category boundary sits.

Instead, ask what problem it helps you solve. Once you look at it this way, the choices become much easier.

Need 1: Build a Working Application Quickly

This is one of the most common needs.

AI can write code quickly and well. If you ask ChatGPT, Claude, or another AI coding tool to “build a customer management page,” they can generate HTML, React components, or even a full block of frontend code.

But the issue is that code is not the same as an application.

After AI generates code, you still need to handle many things yourself:

Put the code into a project.
Configure the development environment.
Manage dependencies and errors.
Connect a database.
Adjust page interactions.
Deploy the application.
Make it accessible for others to test.

For developers, these may be routine tasks. For product managers, designers, founders, and business users, they are still a lot of work.

This is where this type of AI no-code tool becomes valuable.

These tools do more than “generate code.” They combine generation, preview, editing, running, and deployment. Users only need to describe what they want, and the platform can generate the application interface, provide online preview, support interaction changes, and help with deployment.

Typical products include:

v0

UI and Frontend Interface Generation

You can describe the page you want in natural language, and v0 generates the corresponding interface and components. It is useful for quickly creating product interfaces, admin panels, landing pages, or interactive prototypes.

Lovable

Generate a Complete Web App From a Prompt

Lovable does not only focus on pages. It also tries to generate application structure, interaction logic, and basic features, making it suitable for turning a product idea into a working MVP quickly.

Bolt

Generate and Run Full-Stack Applications Online

Users can describe requirements, generate code, install dependencies, run projects, and debug applications in the browser, without first setting up a complex local development environment.

Replit

Develop and Deploy Applications Online

Replit is an online development environment. With AI, it can help users generate code, debug projects, and run and publish applications directly.

Need 2: Build Business Systems That Can Run Long Term

The second major need appears in enterprise scenarios.

The question becomes: Can I use AI and no-code to build a business system that a company can truly use over the long term?

For example:

I want to build a CRM to manage customers, contacts, opportunities, and follow-up records.
I want to build a ticketing system so customer issues can be submitted, assigned, handled, and tracked.
I want to build an approval system for leave requests, reimbursements, procurement, contracts, and other processes.
I want to build an inventory or asset management system where data, status, owners, and operation records are clear and traceable.
I want to build an internal operations system where different roles collaborate in the same system.

The core of this need is: how to combine data, pages, permissions, workflows, and AI capabilities into a business system that can keep running.

This is where enterprise business-system AI no-code platforms are needed.

They usually provide data modeling, page building, permission control, workflows, automation, audit logs, API integration, plugin extension, private deployment, and other capabilities. AI is not a standalone application here. It participates in system building and business operations.

NocoBase

An Open-Source, Self-Hosted, Extensible AI No-Code Platform for Enterprise Business Systems

NocoBase provides the core capabilities needed for enterprise business systems, including data models, page building, permission control, workflows, plugin extension, and private deployment. It gives AI a platform foundation for real business scenarios. AI understands requirements, assists generation, and improves efficiency. NocoBase carries the data, permissions, processes, audits, and long-term iteration.

This is why NocoBase is better suited as a first choice for applying AI in real enterprise scenarios. It does not only give AI a generation entry point. It gives AI a business system foundation that can run for the long term, continue to evolve, keep permissions under control, and protect business data.

Retool

An Internal Tool Builder for Development Teams

Retool can quickly connect databases, APIs, and internal services to build admin panels, data operation interfaces, and enterprise internal tools. It also provides AI-related capabilities for assisted building and automation.

Appsmith

An Open-Source Low-Code Platform for Internal Tools

Like NocoBase, Appsmith is also open source. It is suitable for developers and IT teams building dashboards, admin panels, and internal applications. It supports database and API connections and can also be self-hosted.

Budibase

An Open-Source Platform for Business Applications and Internal Tools

Budibase is suitable for building forms, approvals, operations systems, and internal management tools. It supports data source connections, automation, and self-hosting.

Need 3: Let Multiple Tools Work Together Automatically

After AI appeared, many people assumed automation would become simple.

For example, you can ask AI to summarize emails, extract form information, generate replies, and judge customer intent. Viewed separately, AI can indeed complete these tasks.

But in real work, tasks usually do not happen in isolation.

A customer lead may come from a website form, then need to be synced to a CRM, notify sales, and create a follow-up task.

A user feedback email may need to be summarized by AI, classified by issue type, and assigned to the right team.

A contract or invoice may need key information extracted, written into a spreadsheet or system, and then trigger an approval workflow.

Letting AI participate in a full business process, while different tools work together automatically, is the value of AI workflow automation tools.

These tools are not mainly for generating application pages. They connect different systems, place AI inside workflow nodes, and let data, messages, and tasks move automatically.

Typical products include:

Zapier

Automation Between SaaS Tools

Zapier supports a large number of common applications. It is suitable for connecting tools such as Gmail, Slack, HubSpot, Airtable, and Google Sheets to automate notifications, syncing, task creation, AI processing, and more.

Make

Visual Multi-Step Automation Workflows

Make is suitable for more complex conditional logic, data transformation, and multi-application collaboration. Users can design automation tasks in a flowchart-style interface.

n8n

Self-Hosted and Extensible Workflow Automation

As a popular GitHub project, n8n is suitable for technical teams and enterprise users who need to connect APIs, databases, internal systems, and AI services to build more controllable automation workflows.

Activepieces

Open-Source Automation and Business Process Connections

Activepieces is suitable for teams that want to use open-source solutions to build automation workflows. It can also handle data movement and AI tasks across common SaaS tools.

Need 4: Build AI Applications or AI Agents

The last type of need is to build an AI application directly.

For example:

I want to build an enterprise knowledge-base Q&A bot.
I want to build a RAG application that reads documents and answers questions.
I want to build a customer service Agent that understands user questions and calls tools.
I want to combine multiple models, prompts, knowledge bases, and workflows.

The core of this need is: how to package large model capabilities into a usable AI application.

This is where AI application building platforms and AI Agent platforms become valuable.

They usually provide prompt orchestration, model selection, knowledge base integration, RAG, tool calling, Agent workflows, API publishing, and similar capabilities. Users can build Chatbots, AI Workflows, or Agent applications without writing everything from scratch.

Typical products include:

Dify

LLM Application Development Platform

Dify is suitable for building Chatbots, RAG applications, Agent workflows, and enterprise knowledge-base Q&A. It provides model integration, prompt orchestration, knowledge bases, workflows, and application publishing.

Flowise

Visual Builder for LangChain Applications

Flowise is suitable for developers and AI application teams. It uses a node-based interface to orchestrate LLMs, tools, memory, vector databases, and Agent flows.

LangFlow

Visual AI Workflow and Agent Orchestration

LangFlow is suitable for building complex LLM call chains, RAG workflows, and Agent prototypes. Users can combine AI applications through a component-based approach.

Product Decision Table

The table below lists all products discussed in this article. You can quickly compare their characteristics, open-source status, and best-fit scenarios.

Product	Type	Open Source	Typical Use Cases	Target Users	Core Capabilities
NocoBase	Enterprise business-system AI no-code platform	✅ Open source	CRM, tickets, approvals, inventory, asset management, internal business systems	Enterprise IT, development teams, software agencies, business teams	Data models, page building, permissions, workflows, plugins, self-hosting, AI-assisted building
Retool	Enterprise business-system AI no-code platform	Closed source	Internal tools, admin panels, database operation interfaces	Development teams, enterprise IT	Internal tool building, database connections, component library, workflows, AI features
Appsmith	Enterprise business-system AI no-code platform	✅ Open source	Internal tools, admin panels, data operation apps	Developers, IT teams	Open-source low-code, UI components, database/API connections, self-hosting
Budibase	Enterprise business-system AI no-code platform	✅ Open source	Internal tools, approvals, forms, operations systems	IT teams, SMBs, developers	App building, data source connections, automation, self-hosting
Lovable	AI prototype generation tool	Closed source	MVPs, Web App prototypes, lightweight apps	Founders, product teams, indie developers	Prompt-based app generation, frontend/backend generation, fast deployment
Bolt	AI prototype generation tool	Closed source	Full-stack app generation, demos, small tools	Developers, founders, product teams	Natural-language code generation, online development environment, app preview
Zapier	AI workflow automation tool	Closed source	Cross-SaaS automation, lead routing, notifications, data sync	Operations, marketing, sales, business teams	SaaS integrations, triggers, automation workflows, AI steps
Make	AI workflow automation tool	Closed source	Multi-step automation, data processing, cross-tool workflows	Operations teams, automation specialists, growth teams	Visual workflow orchestration, API integration, conditional logic
n8n	AI workflow automation tool	✅ Open source	Self-hosted automation, AI workflows, system integration	Technical teams, automation engineers, enterprise IT	Workflow orchestration, self-hosting, API integration, AI nodes
Activepieces	AI workflow automation tool	✅ Open source	Open-source automation, business process connections, AI automation	Technical teams, operations teams, SMBs	Visual automation, open-source deployment, app connectors
Dify	AI application / Agent platform	✅ Open source	Chatbots, RAG applications, AI Agents, enterprise knowledge-base Q&A	AI application developers, technical teams, enterprise IT	LLM application development, prompt orchestration, RAG, Agent workflows
Flowise	AI application / Agent platform	✅ Open source	Visual LangChain orchestration, RAG, Agent prototypes	AI developers, technical teams	Visual AI flows, LangChain integration, node-based orchestration
LangFlow	AI application / Agent platform	✅ Open source	AI Workflow, RAG, model call flows	AI engineers, developers, research teams	Visual LLM orchestration, component-based flows, Agent building

FAQ

1. What Is the Difference Between AI No-Code and Traditional No-Code?

Traditional no-code mainly relies on drag-and-drop interfaces, forms, components, and visual configuration. AI no-code further introduces natural language, AI generation, intelligent automation, and AI Agent capabilities.

However, AI no-code is not simply adding an AI button to a traditional no-code platform. Valuable AI no-code tools need to bring AI into specific application building, business processes, and data processing scenarios.

2. What Is the Difference Between an AI App Builder and an AI No-Code Platform?

AI app builders focus more on quickly generating application prototypes, while AI no-code platforms focus more on building applications or business systems that can be used continuously.

AI app builders such as v0, Lovable, and Bolt are strong in generation speed, making them suitable for MVPs, demos, product prototypes, and lightweight applications.

AI no-code platforms such as NocoBase pay more attention to data models, pages, permissions, workflows, audit logs, plugin extension, and private deployment, making them more suitable for long-term enterprise use.

So the key is whether you need a prototype or a real system that supports business operations.

3. How Should Enterprises Choose AI No-Code Tools?

Enterprises should first clarify their goal: are they building a prototype, automation, an AI Agent, or a long-running business system?

If the goal is to build a system that the enterprise will use long term, focus on data models, permission control, workflows, audit logs, extensibility, private deployment, and security.

4. What Are the Advantages of Open-Source AI No-Code Tools?

Open-source AI no-code tools offer more control, extensibility, and self-hosting capabilities, especially for scenarios involving enterprise data, permissions, workflows, and long-term maintenance.

In AI scenarios, tools often touch customer data, business processes, internal knowledge bases, ticket content, approval records, and employee information. Enterprises care more about where data is stored, how models are called, whether the system can be privately deployed, and whether it can be extended or migrated in the future.

The closer a tool gets to core enterprise business systems, the more important open source, self-hosting, and extensibility become.

5. What Type of AI No-Code Tool Is NocoBase?

NocoBase is an enterprise business-system AI no-code platform, suitable for building long-running internal tools and business systems.

It can be used to build real business systems such as CRM, ticketing, approvals, inventory, asset management, expense reimbursement, and customer portals.

NocoBase is better suited for teams that want to apply AI to real enterprise scenarios.

Conclusion

Back to the question at the beginning: Does no-code still matter after AI?

The clearer answer is: no-code has not been replaced by AI. It has entered a new stage because of AI.

AI makes software building faster, but enterprises still need systems that are maintainable, extensible, permission-controlled, secure, and able to run over the long term.

That is the real value of no-code platforms in the AI era.

If this article helped you better understand AI no-code, feel free to share it with friends who are choosing AI tools, no-code platforms, or internal business system solutions.

Related reading:

Weekly Updates: Add Mistral AI as an LLM Provider

NocoBase — Tue, 07 Jul 2026 08:35:03 +0000

Summarize the weekly product update logs, and the latest releases can be checked on our blog.

NocoBase is currently updated across three branches: main, next, and develop.

main: The most stable version to date, recommended for installation.
next: Beta version, contains upcoming new features and has been preliminarily tested. There might be some known or unknown issues. It is mainly used to collect feedback from test users and further optimize features. Ideal for test users who want to experience new features early and provide feedback.
develop: Alpha version, contains the latest feature code, may be incomplete or unstable, and is mainly used for internal development and rapid iteration. Suited for technical users interested in cutting-edge product capabilities, but not recommended for production use.

main

v2.1.19

Release date: 2026-07-03

🐛 Bug Fixes

[cli] Fixed revision creation events failing on RabbitMQ brokers that reject : and @ in queue names. (#9989) by cgyrock
[client-v2]
- Fixed iframe sanitization for v2 Markdown rendering and editing. (#9986) by katherinehhh
- Fixed routed popup creation forms losing prefilled field values such as Calendar V2 start and end dates. (#9874) by jiannx
- Fixed V2 table data scope filters so missing URL query parameters no longer block table data queries. (#9869) by jiannx
- Fixed an issue where multiline text field values could not be set via ctx.setFormValues. (#9959) by gchust
[AI employees]
- Fixed AI checkpoint cleanup failures in underscored database environments. (#9982) by cgyrock
- Fixed AI employee workflow nodes failing to resume correctly in loops after a previous AI employee tool call. (#9980) by cgyrock
[File manager] Hidden the file manager attachments list API and return 404 when it is requested. (#9978) by mytharcher
[Workflow] Fixed an issue where workflow execution node results could remain stuck in a loading state. (#9991) by mytharcher
[Backup manager]
- Fixed PostgreSQL and Kingbase backup restore command execution when paths or arguments contain spaces or special characters. (#9946) by cgyrock
- Fixed an issue where newly created backup files could not be uploaded to cloud storage. (#9981) by gchust
[Data visualization] Fixed an issue where chart blocks would trigger unnecessary refreshes when closing a popup. (#9970) by gchust
[UI templates] Fixed an issue where the field template menu was incorrectly displayed in subforms. (#9960) by gchust
[Mobile (deprecated)] Fix responsive v1 admin pages so view actions open as subpages and select fields use mobile popups (#9974) by zhangzhonghe
[Version control] Fixed version-control revision creation on RabbitMQ brokers that reject : and @ in queue names. by cgyrock
[Workflow: Approval] Fix the error that may occur when opening approval details without configuration permissions by zhangzhonghe

v2.1.18

Release date: 2026-07-02

🚀 Improvements

[cli] Support manual Nginx/Caddy proxy config generation, allow Docker deployments without bundled Nginx, and align proxy and CDN-related runtime configuration. (#9943) by chenos
[undefined] Clarified the security guidance for PDF previews using external storage. (#9901) by mytharcher Reference: File Preview
[utils] Added warnings for server-side outbound requests that target potential SSRF-risk addresses when SERVER_REQUEST_WHITELIST is not configured. (#9966) by mytharcher Reference: Environment Variables, Global Environment Variables
[AI: Knowledge base] Added ZIP filename encoding options for knowledge base document uploads to avoid garbled filenames in ZIP archives created with non-UTF-8 encodings. by cgyrock

🐛 Bug Fixes

[client-v2] Fix the issue where route subpages are blank or use incorrect spacing after refresh (#9961) by zhangzhonghe
[Workflow] Reduced unnecessary workflow dispatcher DB fetch retries under concurrent queue processing. (#9953) by mytharcher
[Action: Export records] Fixed XLSX exports so text-like field values that start with formula characters are escaped before being opened in Excel. (#9973) by mytharcher
[AI employees] Fixed LLM providers falling back to their default Base URL when the custom Base URL field is cleared. (#9958) by cgyrock
[Data source: External NocoBase] Fixed external NocoBase attachment uploads and updates in attachment fields by 2013xile

v2.1.17

Release date: 2026-07-01

🐛 Bug Fixes

[flow-engine] Fixed an issue where ctx.auth.user would not update after switching users. (#9964) by gchust
[Mobile (deprecated)] Fix the issue where mobile pages and public forms cannot be scrolled on mobile devices (#9898) by zhangzhonghe

v2.1.15

Release date: 2026-06-30

🐛 Bug Fixes

[undefined] Fixed the Version control documentation in non-Chinese languages so the Professional Edition label is displayed. (#9944) by cgyrock
[AI employees] Fixed workflow AI employee tasks failing after repeated tool calls reached the graph recursion limit. (#9945) by cgyrock
[Action: Custom request] Fixed custom requests allowing runtime options to override the saved request target. (#9904) by mytharcher
[Data source manager] Fixed v2 collection field management so template-protected fields cannot be deleted and inherited fields support view / override behavior consistent with v1. (#9940) by katherinehhh
[Migration manager] Fixed garbled text that could occur when migrating MySQL data with non-ASCII content by 2013xile
[Workflow: Approval] Fix the error when adding Original application content to approval nodes by zhangzhonghe

v2.1.14

Release date: 2026-06-29

🎉 New Features

[AI employees] Added Mistral AI as an LLM provider for AI services. (#9925) by cgyrock

🚀 Improvements

[cli] support OAuth device authorization flow (#9922) by chenos

🐛 Bug Fixes

[client-v2]
- Fixed long selected labels in record select fields so they truncate cleanly without squeezing the select control. (#9939) by katherinehhh
- Fixed table datetime columns losing their configured time display after pagination or refresh. (#9935) by katherinehhh
[Users] Removed the default password from the add-user form in Users & Permissions. (#9915) by jiannx
[Data source: External NocoBase] Fixed NocoBase external data sources failing to load when connection options include runtime objects by 2013xile
[Record history] Fixed external NocoBase data source loading failure when record history is enabled by 2013xile
[App supervisor] Fixed the app supervisor Applications tab registration in Client V2 by 2013xile

v2.2.0-beta.8

Release date: 2026-06-29

🚀 Improvements

[cli] Support OAuth device authorization flow (#9922) by chenos
[client-v2] Support configure js block should be wrapped by block card. (#9897) by gchust
[flow-engine] Automatically refreshed related data blocks when RunJS closes a popup after updating data through resource APIs (#9873) by gchust
[Form drafts] Migrate plugin form drafts to client v2. (#9910) by gchust

🐛 Bug Fixes

[client-v2]
- Fixed link actions becoming invisible on mobile embedded pages when icon-only mode is enabled but no icon is configured. (#9921) by katherinehhh
- Fixed a brief no-pages prompt flash when refreshing in UI Editor mode. (#9918) by katherinehhh
- Fixed v2 form submit success redirects so they can reference the saved response record. (#9907) by katherinehhh
- Fixed link actions becoming invisible on mobile embedded pages when icon-only mode is enabled but no icon is configured. (#9919) by katherinehhh
- Fixed v2 table row action buttons changing row height. (#9866) by jiannx
- Fixed table blocks failing when a configured drag sorting field has been deleted, and allowed clearing the drag sorting field setting. (#9867) by jiannx
[flow-engine]
- Fix the issue where mobile popups with long content cannot scroll (#9871) by zhangzhonghe
- Fixed an issue where some parameters of ctx.openView in RunJS would not take effect. (#9883) by gchust
[cli] support pnpm and yarn global self update (#9912) by chenos
[client] Corrected several copy and typo issues across locales, related UI text, and documentation. (#9905) by Molunerfinn
[Flow engine] Fixed the issue where mobile page can't be created by flow surface api. (#9911) by gchust
[AI employees]
- Fixed the AI datasource card list so it adapts responsively to different viewport widths. (#9924) by cgyrock
- Fixed AI employee chat failures caused by replaying malformed tool calls. (#9900) by cgyrock
[Backup manager] Fixed inconsistent bold labels on the v2 Backup manager settings page. (#9908) by katherinehhh
[Block: iframe] Fixed 403 errors for normal users when viewing v2 iframe blocks in HTML mode. (#9889) by jiannx
[Data source: External NocoBase] Fixed NocoBase external data sources failing to load when connection options include runtime objects by 2013xile
[AI: Knowledge base] Fixed layout overflow in version control and knowledge base document lists when content or viewport size is constrained. by cgyrock
[Migration manager] Fixed migration rules for database-synced collections by 2013xile
[Record history]
- Fixed an issue where record history could fail to save changes for some collections by 2013xile
- Fixed external NocoBase data source loading failure when record history is enabled by 2013xile
[App supervisor] Fixed the app supervisor Applications tab registration in Client V2 by 2013xile
[WeCom] Fixed a blank flash when switching route menu items with the WeCom plugin enabled in Client V2 by 2013xile

develop

v2.2.0-alpha.6

Release date: 2026-07-05

🚀 Improvements

[cli] Refactor CLI setup startup to reuse nb app start, normalize API base path redirects, persist shared env proxy defaults, and rebuild Docker proxy containers when published ports change. (#9997) by chenos

v2.2.0-alpha.5

Release date: 2026-07-04

🎉 New Features

[client-v2] Added configurable App and Portal entry support for V2 action panels and the left-top app switcher. (#9893) by katherinehhh
[Portal manager] Added configurable App and Portal entries for the V2 action panel and app switcher. by katherinehhh

🚀 Improvements

[cli] Improved the Docker CLI setup by supporting configurable default NocoBase image registry/variant, fixing proxy and no-nginx image port compatibility, and adding Docker Nginx/Caddy installation guides. (#9972) by chenos
[undefined]
- Clarified the security guidance for PDF previews using external storage. (#9901) by mytharcher Reference: File Preview
- Refined Russian documentation translation for improved wording, readability, and terminology consistency. (#9942) by sembaev-a-a
[utils] Added warnings for server-side outbound requests that target potential SSRF-risk addresses when SERVER_REQUEST_WHITELIST is not configured. (#9966) by mytharcher
Reference: Environment Variables, Global Environment Variables
[AI employees]
- Removed the deprecated Datasource entry from AI employee settings and context selection in the v2 UI. (#9988) by cgyrock
- Migrated the AI employee plugin to client-v2. (#9794) by cgyrock
[Data source manager] Display unsupported external data source fields in V2 Configure fields, and align backup restore form label styles. (#9983) by katherinehhh
[Users] Improve client-v2 test coverage for the users plugin. (#9975) by jiannx
[AI: Knowledge base]
- Added ZIP filename encoding options for knowledge base document uploads to avoid garbled filenames in ZIP archives created with non-UTF-8 encodings. by cgyrock
- Migrated the AI knowledge base settings pages to the v2 client and fixed layout and loading issues in knowledge base and vector store pages. by cgyrock
[Email manager] Moved the department-based mail viewing option to the general mail settings page. by jiannx
[App supervisor] Hid the standalone V2 Applications block while keeping its settings page available internally. by katherinehhh

🐛 Bug Fixes

[cli] Fixed revision creation events failing on RabbitMQ brokers that reject : and @ in queue names. (#9989) by cgyrock
[client-v2]
- Fixed iframe sanitization for v2 Markdown rendering and editing. (#9986) by katherinehhh
- Fixed V2 table data scope filters so missing URL query parameters no longer block table data queries. (#9869) by jiannx
- Fix the issue where opening an empty V2 Group menu item shows 404 (#9896) by zhangzhonghe
- Fixed an issue where multiline text field values could not be set via ctx.setFormValues. (#9959) by gchust
- Fixed routed popup creation forms losing prefilled field values such as Calendar V2 start and end dates. (#9874) by jiannx
- Fix the issue where route subpages are blank or use incorrect spacing after refresh (#9961) by zhangzhonghe
[Action: Export records]
- Fixed a crash when dragging v2 exportable fields after selecting relation fields. (#9995) by katherinehhh
- Fixed XLSX exports so text-like field values that start with formula characters are escaped before being opened in Excel. (#9973) by mytharcher
[Workflow]
- Fixed an issue where workflow execution node results could remain stuck in a loading state. (#9991) by mytharcher
- Reduced unnecessary workflow dispatcher DB fetch retries under concurrent queue processing. (#9953) by mytharcher
[Backup manager]
- Fixed an issue where newly created backup files could not be uploaded to cloud storage. (#9981) by gchust
- Fixed PostgreSQL and Kingbase backup restore command execution when paths or arguments contain spaces or special characters. (#9946) by cgyrock
[AI employees]
- Fixed AI employee workflow nodes failing to resume correctly in loops after a previous AI employee tool call. (#9980) by cgyrock
- Fixed AI checkpoint cleanup failures in underscored database environments. (#9982) by cgyrock
[UI templates] Fixed an issue where the field template menu was incorrectly displayed in subforms. (#9960) by gchust
[File manager] Hidden the file manager attachments list API and return 404 when it is requested. (#9978) by mytharcher
[Block: Comment] Adjusted the default action order for new Comment blocks. (#9976) by jiannx
[Data visualization] Fixed an issue where chart blocks would trigger unnecessary refreshes when closing a popup. (#9970) by gchust
[Mobile (deprecated)] Fix responsive v1 admin pages so view actions open as subpages and select fields use mobile popups (#9974) by zhangzhonghe
[Version control] Fixed version-control revision creation on RabbitMQ brokers that reject : and @ in queue names. by cgyrock
[Data source: External NocoBase] Fixed external NocoBase attachment uploads and updates in attachment fields by 2013xile
[Workflow: Approval] Fix the error that may occur when opening approval details without configuration permissions by zhangzhonghe

v2.2.0-alpha.4

Release date: 2026-07-01

🎉 New Features

[Block: Comment]
- Improved comment block settings with data scope, default sorting, selectable page size, optional last-page jumping, and scalar owner field mapping. (#9954) by jiannx
- Added a comments block. (#9916) by jiannx
[AI employees] Added Mistral AI as an LLM provider for AI services. (#9925) by cgyrock
[Record history] Added client v2 support for the record history plugin. by jiannx

🚀 Improvements

[cli] Support manual Nginx/Caddy proxy config generation, allow Docker deployments without bundled Nginx, and align proxy and CDN-related runtime configuration. (#9943) by chenos
[Workflow: JavaScript] Aligned v2 workflow request and mailer node configuration fields with legacy layout and attachment variable behavior. (#9952) by jiannx
[UI layout] Improved the v2 mobile tab bar so crowded tabs scroll horizontally instead of overlapping. (#9949) by katherinehhh
[Workflow: Aggregate node] Improved v2 workflow field selection for update and aggregate query nodes, including safer associated collection selection in aggregate query nodes. (#9938) by katherinehhh
[Block: Comment] Added the new comment block plugin to the NocoBase preset and marked the legacy comments plugin as deprecated. (#9936) by jiannx
[Logger] Added the Logger settings page to the client v2 runtime. (#9933) by jiannx
[HTTP request encryption] Added v2 client support for HTTP request encryption so query parameters continue to be encrypted in the v2 client. by jiannx
[Workflow: Database transaction node] Improved the v2 workflow database transaction node layout so branch labels and the commit marker have better spacing. by katherinehhh

🐛 Bug Fixes

[flow-engine] Fixed an issue where ctx.auth.user would not update after switching users. (#9964) by gchust
[client-v2]
- Fix workflow execution revision navigation so creating a new version after manual execution opens the correct workflow page in both legacy and modern shells. (#9955) by Molunerfinn
- Fixed table datetime columns losing their configured time display after pagination or refresh. (#9935) by katherinehhh
- Fixed long selected labels in record select fields so they truncate cleanly without squeezing the select control. (#9939) by katherinehhh
- Fixed V2 admin group routes showing 404 when the group has no available child menu page. (#9932) by katherinehhh
[undefined] Fixed the Version control documentation in non-Chinese languages so the Professional Edition label is displayed. (#9944) by cgyrock
[AI employees]
- Fixed LLM providers falling back to their default Base URL when the custom Base URL field is cleared. (#9958) by cgyrock
- Fixed workflow AI employee tasks failing after repeated tool calls reached the graph recursion limit. (#9945) by cgyrock
[Action: Custom request] Fixed custom requests allowing runtime options to override the saved request target. (#9904) by mytharcher
[Mobile (deprecated)] Fix the issue where mobile pages and public forms cannot be scrolled on mobile devices (#9898) by zhangzhonghe
[Notification manager] Fix incorrect workflow variables shown in CC configuration (#9937) by zhangzhonghe
[Workflow]
- Fix workflow context mismatches across bundles so branches and some variable pickers work correctly in legacy workflow pages. (#9951) by Molunerfinn
- Fix issues after migrated client to v2 (#9929) by mytharcher
- Fix the issue where in-app message content cannot be configured in v2 workflows (#9885) by zhangzhonghe
[Data source manager] Fixed v2 collection field management so template-protected fields cannot be deleted and inherited fields support view / override behavior consistent with v1. (#9940) by katherinehhh
[Authentication] Fixed incorrect redirects after SSO login in v2 sub applications (#9927) by 2013xile
[Users] Removed the default password from the add-user form in Users & Permissions. (#9915) by jiannx
[Flow engine] Fixed the issue where mobile page can't be created by flow surface api. (#9911) by gchust
[App SSO] Fixed incorrect App SSO redirects in v2 sub applications by 2013xile
[AI: Knowledge base] Fixed layout overflow in version control and knowledge base document lists when content or viewport size is constrained. by cgyrock
[Data source: External NocoBase] Fixed NocoBase external data sources failing to load when connection options include runtime objects by 2013xile
[Migration manager] Fixed garbled text that could occur when migrating MySQL data with non-ASCII content by 2013xile
[Record history] Fixed external NocoBase data source loading failure when record history is enabled by 2013xile
[Workflow: Approval]
- Fix the error when opening CC node settings by zhangzhonghe
- Fix the error when adding Original application content to approval nodes by zhangzhonghe
- Fix the issue where approval tables appear in the block data source list by zhangzhonghe
- Fix issues involved by migrating to client v2 by mytharcher
[App supervisor]
- Fixed app visit links losing the v2 path in sub applications by 2013xile
- Fixed the app supervisor Applications tab registration in Client V2 by 2013xile

From Paperwork to Digital Public Services in France

NocoBase — Mon, 06 Jul 2026 09:45:24 +0000

Originally published at https://www.nocobase.com/en/blog/astrolab-nocobase

Introduction

Astrolab is one of NocoBase's partners in Europe, Africa, and the Middle East. The company specialises in technology strategy, intelligent automation, AI, and digital solution delivery.

Using NocoBase, Astrolab delivered three production-grade digital public-service platforms for one of France's 13 metropolitan regional governments.

The platforms were delivered under a unified framework approach. They were not isolated tools, but a set of digital public-service systems built on a shared modular architecture. Together, they helped the client move critical administrative processes from paper forms, spreadsheets, and fragmented email workflows to flexible, controlled, and traceable digital services.

Challenge

A major French metropolitan regional government manages environmental policy, education, economic development, transport, and territorial planning for several million inhabitants. It faced a recurring operational challenge: multiple critical administrative processes were still handled through paper forms, spreadsheets, and fragmented email workflows.

Three high-priority public services required urgent digital transformation.

Environmental Impact Assessment Platform (GIE)

Companies applying for regional economic-development aid were required to complete a multi-dimensional environmental self-assessment covering carbon impact, energy usage, water consumption, waste management, land usage, and ecological indicators.

The legacy workflow relied heavily on manual validation and duplicate data entry. This created delays, inconsistent evaluations, and limited operational visibility.

Fleet Vehicle Pooling Management Platform (SID)

The regional administration operated a shared fleet across multiple departments using manual reservation workflows and spreadsheet tracking. This resulted in reservation conflicts, low vehicle utilisation, poor visibility on fleet performance, uncontrolled fuel and mileage reporting, and limited operational governance.

Annual Boarding-School Census Platform (EIT)

The regional education department conducted an annual census across more than 190 public and private institutions.

The previous email-and-paper process led to low response rates, significant manual consolidation work, delayed reporting cycles, and inconsistent or incomplete datasets, directly impacting regional planning.

Astrolab's Solution

Astrolab delivered three production-grade digital public-service platforms under a unified framework approach, designed around a shared modular architecture and low-code extensibility model powered by NocoBase.

The platforms shared a common foundation including:

Unified authentication and role management
Shared workflow orchestration layer
Centralised audit and logging infrastructure
Notification and reminder engine
Dynamic form and data-model management
API integration framework
Modular low-code administration capabilities enabling rapid evolution by functional teams

This approach avoided rebuilding the same common capabilities for each system. Instead, the delivery team could extend NocoBase's existing capabilities and focus on business processes, data rules, permission boundaries, and system integrations.

The architecture was intentionally designed to accelerate delivery cycles while maintaining enterprise-grade governance, security, scalability, and maintainability. It also allowed functional teams to continue evolving forms, workflows, and management rules after launch.

All deliverables complied with:

French DINUM digital-service standards
GDPR requirements
French RGAA accessibility standards, equivalent to WCAG
ANSSI-aligned security baselines for public-sector systems
Data hosted on sovereign infrastructure within French territory

Platform 1: Environmental Impact Assessment Platform (GIE)

The Environmental Impact Assessment Platform supports the environmental self-assessment workflow for companies applying for regional economic-development aid.

Astrolab used NocoBase to build dynamic adaptive survey workflows. The questionnaire adapts to company size and industry, while SIRET-based company-data auto-population retrieves company information through French public-service APIs, reducing duplicate data entry and manual verification.

After submission, the platform supports multi-role submission and validation routing. The workflow is connected to regional grant-processing systems, so validated assessment results can be routed into the financial-aid process.

The platform also provides immutable audit history, save-and-resume functionality, and low-code administrative interfaces. Functional teams can rapidly evolve forms and workflows without requiring full redevelopment.

Platform 2: Fleet Vehicle Pooling Management Platform (SID)

The Fleet Vehicle Pooling Management Platform manages shared vehicle usage across multiple departments of the regional administration.

Astrolab transformed a process previously based on manual reservations and spreadsheet tracking into a real-time vehicle reservation and approval system. Drivers can view available vehicles and submit reservations, while managers and administrators handle approval, notifications, and operational oversight.

The platform provides automated conflict detection, mileage and fuel-consumption tracking, department-level reporting dashboards, Excel and PDF exports, and a mobile-responsive booking experience.

It was built using the modular workflow and data-management capabilities provided through the NocoBase-based architecture. This enables administrators to quickly adjust vehicle rules, approval flows, and reporting logic as operational needs change.

Platform 3: Annual Boarding-School Census Platform (EIT)

The Annual Boarding-School Census Platform supports the regional education department's yearly census across public and private institutions.

Astrolab used NocoBase to transform the process into an online census platform with dual-stream survey workflows for public and private institutions, smart branching logic, pre-filled historical data, automated reminder notifications, and real-time completion dashboards.

Administrators can monitor progress, validate submitted data through centralised data validation workflows, and use executive reporting and analytics integration to support regional education planning.

Because census questionnaires and reporting structures may change every year, the low-code architecture enables rapid yearly adjustments without major redevelopment cycles.

Results

After the three platforms entered production, the client achieved significant improvements in operational efficiency, data quality, administrative visibility, governance, and compliance.

The most direct improvement came from the Environmental Impact Assessment Platform. Manual environmental-review cycles were reduced from multiple days to less than 24 hours median processing time. Through 12+ live integrations with public-sector registries and open-data systems, the platform can automatically populate more than 95% of company profile information, eliminating duplicate data entry and significantly reducing manual verification workload. Assessment results are also automatically routed into financial-aid processing systems.

In the Fleet Vehicle Pooling Management Platform, real-time reservations, automated conflict detection, and department-level reporting improved daily operations. Reservation conflicts were reduced by approximately 80%, and vehicle utilisation improved by approximately 25%. The platform also provides full operational visibility on mileage and fuel consumption by department.

The Annual Boarding-School Census Platform also improved the data collection process. During the first operational cycle, the response rate increased to more than 90%, and data consolidation was reduced from several weeks to less than 48 hours. The improved completeness and consistency of the data created a stronger foundation for educational planning.

Beyond efficiency gains, the three platforms strengthened governance and compliance across all targeted processes. The systems provide full traceability across workflows, centralised audit logging, and compliance reporting. There were zero reported data-breach incidents, annual penetration testing was successfully completed, and full GDPR compliance was validated by the client governance teams.

In terms of reliability, the platforms achieved measured service availability exceeding 99.8% across all platforms over a 24-month period. Under active support and evolution contracts, Astrolab maintained a quarterly feature-release cadence, and all three services continued to be used in production.

Technical Architecture Overview

Astrolab used NocoBase as the shared foundation for all three platforms, providing core capabilities such as data models, dynamic forms, access control, workflows, audit logs, and administration interfaces.

Around this foundation, the team integrated React.js, NestJS, PostgreSQL, PostGIS, Power BI, custom reporting, government APIs, Docker, CI/CD, and private cloud deployment to meet public-sector production requirements.

The architecture supports data sovereignty, RGPD/GDPR compliance, RBAC, AES-256 encryption, immutable audit history, and zero-downtime deployment, enabling the three platforms to run reliably over the long term.

During delivery, Astrolab also explored AI-assisted development with Claude for custom plugin code. With NocoBase 2.1, AI Agents can now work more naturally with NocoBase documentation and extension mechanisms to build plugins, JS Blocks, and complex business logic.

Summary

Astrolab used NocoBase to reuse foundational capabilities across multiple public-service systems, then extended each platform for its specific operational scenario. The result was a set of production-grade systems designed for long-term use, continuous evolution, and public-sector governance requirements.

This is also the kind of system development approach that deserves more attention in the AI era.

AI can accelerate code generation and development, but real business systems cannot rely on one-time generation alone. They need stable data models, clear permission boundaries, traceable workflows, auditable history, and an architecture that can keep evolving.

This is where NocoBase delivers its value: it allows both AI and delivery teams to avoid starting from scratch, and instead build, extend, and maintain real applications on a platform that already provides the foundational capabilities required by business systems.

More Customer Stories:

9 Open-Source AI No-Code Tools on GitHub Worth Watching

NocoBase — Tue, 30 Jun 2026 03:59:24 +0000

Originally published at https://www.nocobase.com/en/blog/open-source-ai-no-code-tools-github-9

AI coding is getting a lot of attention. Many tools can already generate code, pages, and application prototypes very quickly. At first glance, it may seem like AI is weakening the value of no-code.

But real business applications need more than speed. Once user permissions, data structures, business workflows, handover, and long-term maintenance are involved, a system needs clearer structure and more stable governance.

A similar point appears in this Reddit discussion: AI app-building tools are fast for prototypes, but when they enter real business environments, the value of no-code platforms becomes even more visible.

AI coding is not replacing no-code. Instead, it is making the boundary between the two increasingly blurred. AI is moving into app building, workflow automation, knowledge bases, and business systems, while no-code platforms are also adding stronger AI-assisted capabilities.

This article is based on open-source projects under the GitHub no-code topic. We selected 9 no-code tools where AI has already become part of the core positioning. We will focus on their AI highlights and suitable use cases, and look at how AI is entering application building, workflow automation, knowledge bases, agent orchestration, design generation, and enterprise business system development.

Before going into the details, here is a quick overview of the 9 tools covered in this article.

No.	Tool	GitHub Stars	Positioning	AI Highlights	Suitable Use Cases
9	NocoBase	23.1k	AI no-code platform for enterprise business systems	AI employees, AI-assisted building, knowledge base, plugin extension	CRM, ERP, approvals, ticketing, inventory, project management, and other internal enterprise systems and tools
8	Budibase	28.1k	AI-powered internal operations app platform	AI agents, process execution, automation, internal apps	IT service desk, approval workflows, employee services, operations processes
7	Sim	28.9k	Multi-agent collaboration workspace	Agent orchestration, task decomposition, tool calling, multi-agent collaboration	Sales operations, customer support, data processing, research and analysis
6	ToolJet	38.1k	AI platform for building internal enterprise tools	AI app generation, query assistance, debugging, workflows	Admin panels, dashboards, approval systems, order processing
5	Flowise	54.1k	Visual builder for AI agents and model workflows	Visual workflows, RAG, knowledge-base Q&A, human-in-the-loop review	AI app prototypes, document Q&A, customer support assistants
4	AnythingLLM	62.2k	Private AI knowledge base and local assistant	Private document Q&A, RAG, self-hosting, AI agents	Enterprise knowledge bases, internal document search, local AI assistants
3	open-design	72.3k	AI design prototype generation tool	Natural-language design generation, design systems, multi-format export	Product prototypes, landing pages, presentations, visual assets
2	Dify	147k	Production-grade AI application development platform	AI workflows, RAG, tool calling, model management	AI customer service, AI assistants, enterprise RAG, AI applications
1	n8n	194k	AI workflow automation platform	AI agent workflows, system integration, automated execution, self-hosting	Sales operations, customer support automation, data synchronization, ticket routing

9. NocoBase

Official site: https://www.nocobase.com/

GitHub: https://github.com/nocobase/nocobase

GitHub Stars: 23.1k

NocoBase is an AI-powered open-source no-code/low-code development platform for building enterprise applications, internal tools, and business systems. It supports self-hosting and uses a plugin-based architecture, making it suitable for teams that need to build CRM, ERP, approval systems, ticketing systems, inventory systems, project management tools, operations back offices, and other systems around their own business processes.

NocoBase is closer to a development framework and business system infrastructure for enterprise applications. It includes common foundational capabilities required by enterprise systems, such as data modeling, page configuration, user permissions, workflows, security audit, and plugin extension. This gives AI a clear system architecture and permission boundary to work within. Instead of generating a hard-to-maintain codebase from scratch, AI can help create data tables, configure pages, orchestrate workflows, set permissions, and continue supporting later extensions within the NocoBase framework. For enterprises, this approach is better suited to real business systems: it improves building efficiency with AI while keeping the stability, security, and maintainability required for long-term operation.

AI Highlights

AI-assisted business system building: Users can describe business requirements in natural language and let AI help with data model design, page configuration, workflow orchestration, permission setup, and plugin management. For example, when building a customer management system, ticketing system, contract approval system, or project dashboard, AI can generate the basic system first. The team can then review fields, relationships, pages, action buttons, and permission settings in the no-code interface to ensure they match the actual business process.

AI employees entering system operations: NocoBase AI employees can act as intelligent assistants inside the system. They can work with page data, business context, tools, and knowledge bases to complete tasks such as data queries, content summaries, report generation, translation, unstructured content extraction, form filling, and workflow node processing. This means AI does not only help during system building; it can also continue participating in system operation.

AI Skills, CLI, and MCP support external Agent collaboration: NocoBase also provides AI Skills, CLI, and MCP capabilities. AI Skills help external Agents understand how NocoBase is configured and what operation boundaries they should follow. CLI allows Agents to execute commands for installation, creation, and modification. MCP provides a more standardized entry point for external AI tools to connect with NocoBase.

🎉 Related resources

AI documentation: https://docs.nocobase.com/en/ai/

CLI: https://docs.nocobase.com/en/api/cli/

Skills: https://docs.nocobase.com/en/ai-builder#nocobase-skills

MCP: https://docs.nocobase.com/en/ai/mcp/

No-code capabilities reduce long-term maintenance costs: Many AI generation tools can quickly create code, but later maintenance often depends on developers. NocoBase is different because after AI generates the initial system, users can still modify fields, pages, menus, action buttons, permissions, and workflows in the no-code interface. For business teams, the system does not stop at a one-off demo. It can keep evolving as the business changes.

Suitable Use Cases

Internal business systems: NocoBase is suitable for CRM, approval systems, ticketing systems, project management systems, operations back offices, admin panels, and similar systems. These systems need stable data structures, clear permission boundaries, and continuously adjustable workflow rules, so they are not well suited to one-off generation tools alone.

Lightweight ERP and business management modules: Procurement management, inventory management, order management, equipment management, asset management, archive management, and customer follow-up scenarios are also suitable for NocoBase. Teams can start from specific business modules, use AI to generate the basic structure, and then gradually improve fields, pages, permissions, and workflows through no-code configuration.

🎉 NocoBase AI Blueprints are now available. Try them out!

These are small, focused business solutions built with NocoBase. They are open-source, controllable, and easy to extend or modify around your own process.

Each solution comes with a standard prompt. Give it to the AI Agent connected to your NocoBase instance, and you can recreate the same type of system in minutes.

https://www.nocobase.com/en/ai-blueprints

Extending and enhancing existing systems: For enterprises that already have databases, ERP, CRM, or other business systems, NocoBase can also be used as an extension layer to integrate data, configure pages, manage permissions, and orchestrate workflows. When an AI Agent needs to enter real business processes, NocoBase can provide a structured, governable, and maintainable business system environment.

8. Budibase

Official site: https://budibase.com/

GitHub: https://github.com/Budibase/budibase

GitHub Stars: 28.1k

Budibase brings internal applications, automated workflows, and AI agents into one platform. It is suitable for handling high-frequency, repetitive internal operations that require process routing. Its focus is not single-turn Q&A, but enabling AI to enter everyday business steps such as request handling, approval routing, notification distribution, and record updates.

For IT, HR, administration, operations, and support teams, Budibase is more like a platform for productizing internal processes. Teams can first build forms, data tables, and internal applications, and then let AI agents participate in judgment, assignment, and execution. Processes that used to depend on manual communication can become traceable and reusable systems.

AI Highlights

AI agents participate in process handling: Budibase AI agents can understand employee requests, approval items, feedback, and operational tasks, then decide what should happen next. They can classify requests, assign them to the right owner, and enter automated workflows to reduce manual triage and repeated communication.

Automation and internal apps work together: Budibase connects forms, databases, permissions, automation, and AI agents. After a request enters the system, AI can make the first judgment, automation continues the following steps, and the result becomes a traceable business record.

Suitable Use Cases

Internal service requests and approval flows: Budibase is suitable for IT service desks, equipment requests, HR support, administrative approvals, support routing, and operational task flows. For example, after an employee submits an account permission request, AI can identify the request type, create a ticket, and assign the task to the right owner.

7. Sim

Official site: https://www.sim.ai/

GitHub: https://github.com/simstudioai/sim

GitHub Stars: 28.9k

Sim is mainly used to build, deploy, and manage AI agents. It organizes large models, external tools, integration capabilities, and task flows so teams can place multiple AI agents into the same workflow and handle more complex business tasks.

In real work, a task is often not completed in one step. Sales lead handling, for example, may involve information collection, customer qualification, email drafting, CRM updates, and follow-up reminders. Sim helps split these steps and coordinate them through different agents or workflow stages, making AI feel closer to an execution team that can participate in real work.

AI Highlights

AI agent building and orchestration: Sim helps teams build multiple AI agents and organize them into the same task flow. Each agent can take responsibility for a different step, such as information organization, judgment, execution, or result writing, making it suitable for multi-step tasks.

Connecting models, tools, and business workflows: Sim can connect mainstream large models and external tools, allowing AI agents to read information, call tools, and perform actions. Agents are therefore not limited to generating text; they can enter real tool environments and complete tasks closer to business execution.

Suitable Use Cases

Multi-step business tasks: Sim is suitable for sales operations, data processing, customer support, research, and analysis. For example, a sales team can let different AI agents handle lead organization, email drafting, CRM updates, and follow-up reminders.

6. ToolJet

Official site: https://tooljet.com/

GitHub: https://github.com/ToolJet/ToolJet

GitHub Stars: 38.1k

ToolJet is used to build internal enterprise applications, dashboards, admin panels, and business tools. It combines app building, data connection, workflows, and AI capabilities, making it suitable for teams that want to generate internal apps quickly and then continue connecting real data, adjusting pages, and refining business logic.

For many internal tools, the hard part is not only the interface. Data source connections, API calls, query configuration, and permission rules are often more difficult. ToolJet's AI capabilities focus on these practical building steps: first helping generate an app skeleton, then assisting with queries, debugging, and workflow automation.

AI Highlights

AI-generated internal applications: ToolJet can generate the basic structure of an internal tool based on requirements, including pages, components, fields, and interaction logic. Teams do not need to start from a blank canvas. They can get an initial version first and then continue adjusting it around real business needs.

AI-assisted data queries and debugging: Internal tools often need to connect to databases, APIs, and business systems. Incorrect queries, API errors, and mismatched field mapping can all slow down implementation. ToolJet's AI capabilities can help generate queries and locate configuration issues, reducing the cost of data connection and debugging.

Suitable Use Cases

Internal enterprise tools: ToolJet is suitable for admin panels, dashboards, approval systems, supplier management, employee directories, order processing back offices, and similar scenarios. For example, an operations team building an order exception handling back office can first generate the app skeleton with AI and then connect databases and APIs for further refinement.

5. Flowise

Official site: https://flowiseai.com/

GitHub: https://github.com/FlowiseAI/Flowise

GitHub Stars: 54.1k

Flowise breaks large language model applications into visual nodes, allowing users to build AI agents and model workflows through drag-and-drop. Models, prompts, memory, tool calls, knowledge bases, and retrievers—parts that usually require code orchestration—can all be combined into runnable AI application flows in Flowise.

For teams that want to validate AI applications quickly, Flowise is valuable because it is intuitive to build with and inexpensive to iterate on. Teams can first connect the nodes and make the flow run, then adjust retrieval methods, prompts, tool calls, and output logic based on the results.

AI Highlights

Visual building for AI agents and model workflows: Flowise can build AI agents through a node-based interface and orchestrate multi-step model workflows. Users can connect models, prompts, tool calls, memory, and output logic to quickly create a runnable and adjustable AI application.

RAG and knowledge-base Q&A: Flowise is suitable for connecting documents, vector databases, retrievers, and large language models to build enterprise knowledge-base Q&A, document assistants, or customer support Q&A. It lowers the barrier from “we have a set of documents” to “we can ask questions directly about those documents.”

Suitable Use Cases

AI application prototypes and enterprise document Q&A: Flowise is suitable for quickly validating AI chatbots, knowledge-base Q&A, RAG applications, and multi-step agent workflows. Product teams can first build a Q&A assistant based on product documentation, test the results, and then decide whether to move into formal development.

4. AnythingLLM

Official site: https://anythingllm.com/

GitHub: https://github.com/Mintplex-Labs/anything-llm

GitHub Stars: 62.2k

AnythingLLM starts from how teams use enterprise knowledge. It brings document Q&A, RAG, AI agents, multi-user management, and model access into one workspace. For many teams, the first step in using AI is not building a complex application right away. Instead, they want AI to understand internal materials and answer questions in a controlled environment.

Its key characteristics are local-first usage and private deployment. For teams with data security requirements, deployment method and data control are very important when connecting internal documents, project materials, customer records, or codebases to AI. AnythingLLM is suitable for starting with a private knowledge base and gradually extending into agent tasks.

AI Highlights

Private document Q&A and RAG: AnythingLLM allows users to upload PDFs, Word documents, CSVs, codebases, and internal documentation, then ask questions around those materials in natural language. It is not general chat; it lets AI answer based on the team's own knowledge and files.

AI agents: AnythingLLM is not only used for document Q&A. It also supports AI agent configuration. Teams can build on the knowledge base and let agents continue completing tasks such as information organization, content generation, and document lookup.

Suitable Use Cases

Private enterprise knowledge bases: AnythingLLM is suitable for consulting firms, R&D teams, customer support teams, and operations teams building internal knowledge Q&A systems. For example, teams can upload project documents, product manuals, and FAQs so employees can query them quickly in natural language.

3. open-design

Official site: https://open-design.ai/

GitHub: https://github.com/nexu-io/open-design

GitHub Stars: 72.3k

open-design turns natural-language design generation into an open-source, local-first AI design workspace. It does not focus on business processes or knowledge bases, but on the path from ideas to visual outputs: pages, prototypes, dashboards, slides, images, and videos can all start from a text description.

For product managers, designers, startup teams, and growth teams, open-design can reduce the cost of early-stage expression. Often, teams are not short of ideas; they struggle to quickly turn ideas into visual materials that can be discussed, modified, and delivered. open-design helps requirements descriptions become prototypes and design drafts faster.

AI Highlights

Generating design outputs from natural language: Users can describe the pages, dashboards, landing pages, presentations, or prototypes they want, and open-design generates an initial design result based on the description. It is suitable for turning early ideas into visual content quickly and helping product, design, and business teams align on direction. open-design includes many design systems, making AI-generated results easier to keep visually consistent. Compared with general image generation tools, it focuses more on interface structure, component style, brand guidelines, and reusability.

Multi-type outputs and format export: open-design can generate web, desktop, and mobile prototypes, dashboards, decks, images, and videos, and supports exports in formats such as HTML, PDF, PPTX, and MP4. This makes it more than an inspiration tool; it is closer to an AI design tool that can enter the delivery process.

Suitable Use Cases

Product prototypes and presentation materials: open-design is suitable for product managers, designers, startup teams, and growth teams that need to quickly generate product prototypes, landing pages, dashboard mockups, pitch decks, and brand visual assets.

2. Dify

Official site: https://dify.ai/

GitHub: https://github.com/langgenius/dify

GitHub Stars: 147k

Dify covers the full process of building, orchestrating, and managing AI applications after launch. It brings AI workflows, RAG, agents, model management, and observability together, making it suitable for building AI applications closer to production environments rather than simple chat windows.

For teams that already know they want to build an AI product or AI feature, Dify's value is that it productizes many foundational tasks: how models are connected, how knowledge bases are managed, how workflows are orchestrated, how tools are called, and how application performance is observed after launch. If all of these are built from code, development and maintenance costs can be high.

AI Highlights

AI workflow orchestration: Dify can visually orchestrate AI workflows. Complex AI applications are usually not just “user asks, model answers.” They need to identify intent, retrieve information, call tools, evaluate conditions, and generate responses. Dify can organize these steps into maintainable workflows.

RAG and knowledge-base applications: Dify provides RAG capabilities and is suitable for building AI Q&A systems based on enterprise documents, product materials, help centers, or internal knowledge bases. For enterprises, RAG is a key capability for making AI answers closer to business content.

Agents and tool calling: Dify supports building agents and enabling them to call tools, APIs, or external services. This allows AI to do more than answer questions; it can perform searches, queries, calculations, and calls to business systems.

Model management and observability: After an AI application goes live, teams need to continuously monitor answer quality, call cost, response speed, and user feedback. Dify provides model management and observability features so teams can keep optimizing during real use.

Suitable Use Cases

Production-grade AI applications: Dify is suitable for building AI chatbots, intelligent customer service, AI assistants, enterprise RAG, and agent applications. If a team wants to deploy an AI application into real business scenarios rather than build a demo only, Dify's workflow, model management, and observability capabilities become more valuable.

1. n8n

Official site: https://n8n.io/

GitHub: https://github.com/n8n-io/n8n

GitHub Stars: 194k

n8n's most direct value is letting AI enter existing business processes. Many companies do not lack tools. The real problem is that tools are fragmented: CRM, forms, databases, ticketing systems, email, messaging tools, and marketing platforms all run separately. n8n connects these systems and places AI into workflow nodes, allowing AI to read data, judge conditions, generate content, call APIs, and trigger actions.

It is not only for building an AI application. It is more suitable as an AI automation execution layer. When AI needs to truly enter business systems and complete actions such as updating records, sending notifications, synchronizing data, processing leads, or assigning tasks, n8n's workflow capability becomes valuable.

AI Highlights

AI agent workflows: n8n can build AI agent workflows that allow AI to participate in judgment and execution inside automation flows. For example, it can read customer information, decide the next action, generate follow-up content, and write the result back to a CRM or notify the sales team.

Business system integration and automated execution: n8n can connect a large number of SaaS tools, databases, APIs, and internal systems. AI-generated results can directly enter business workflows, such as triggering processes, updating data, calling APIs, and sending messages, rather than stopping at a text response.

Suitable Use Cases

Cross-system automation: n8n is suitable for sales operations, customer support automation, marketing automation, data synchronization, and ticket routing. For example, after a sales lead enters a form, AI can first identify the customer type, generate follow-up suggestions, then automatically update the CRM and notify sales.

FAQ

1. What Are AI No-Code Tools?

AI no-code tools are platforms that combine AI capabilities with visual building. Users do not need to start from code. They can build AI applications, agents, knowledge bases, internal tools, or business systems through natural language, drag-and-drop configuration, and workflow orchestration.

The point of these tools is not only to “write less code.” They also let AI participate in app building, data processing, workflow execution, and content generation, such as generating pages, orchestrating workflows, calling tools, retrieving knowledge bases, or assisting in the building of enterprise internal systems.

2. Why Pay Attention to AI No-Code Tools Now?

AI is changing how no-code tools are used. In the past, no-code mainly solved the problem of “building applications without writing code.” Now, AI makes application generation, process configuration, knowledge retrieval, and agent execution faster.

But real business applications still need data structures, permission control, workflow rules, deployment options, and long-term maintenance. That is why the combination of AI and no-code is becoming more important: AI improves building efficiency, while no-code platforms provide visual structure and maintainable frameworks.

3. Which Open-Source AI No-Code Tools on GitHub Are Worth Watching?

This article selected 9 open-source AI no-code tools worth watching on GitHub: n8n, Dify, open-design, AnythingLLM, Flowise, ToolJet, Sim, Budibase, and NocoBase.

They cover different directions. n8n focuses more on workflow automation; Dify focuses on AI application development; Flowise focuses on visual AI workflows; AnythingLLM focuses on private knowledge bases; open-design focuses on design generation; ToolJet and Budibase focus more on internal tools and operational processes; NocoBase is more suitable for building enterprise business systems.

4. Which AI No-Code Tool Is Suitable for Building Enterprise Business Systems?

If the goal is to build enterprise business systems such as CRM, approvals, ticketing, project management, inventory management, or operations back offices, NocoBase is a better fit.

These systems need more than a page or a chat entry. They need data models, permissions, pages, workflows, operation records, and later extension capabilities. NocoBase is itself an open-source AI no-code/low-code platform for internal enterprise business systems, admin panels, and continuously evolving business applications. It also supports AI participation in data modeling, page configuration, workflow, and plugin development.

5. Which AI No-Code Tools Are Suitable for Building AI Agents?

If the focus is building AI agents, Dify, Flowise, Sim, n8n, and Budibase are worth looking at first.

Dify is better for AI applications and agent workflows. Flowise is suitable for visually building large language model flows and agents. Sim focuses more on collaboration across multiple agents. n8n is suitable for letting agents enter cross-system automation workflows. Budibase is more suitable for agents participating in internal requests, approvals, and operations workflows.

6. Which Tools Are Better for RAG Knowledge Bases?

AnythingLLM, Dify, and Flowise are all suitable for RAG, or retrieval-augmented generation.

AnythingLLM is better for private knowledge bases and local AI assistants. Dify is better for putting RAG into production-grade AI applications. Flowise is better for visually building and debugging RAG flows. If a knowledge base also needs to connect with enterprise business data, permissions, pages, and workflows, NocoBase can also serve as the business system layer.

7. How Is NocoBase Different from Dify and Flowise?

Dify and Flowise focus more on AI applications themselves. They are suitable for building chat assistants, RAG applications, agent workflows, and large language model flows.

NocoBase focuses more on enterprise business systems. It looks at how AI enters enterprise application infrastructure such as data models, page configuration, permission management, workflows, and plugin extension. In other words, if you want to build an AI application, Dify or Flowise is worth considering. If you want to build a business system that can run for the long term and remain maintainable, NocoBase deserves closer attention.

8. Are AI No-Code Tools Suitable for Non-Technical Teams?

Yes, but the learning curve varies by tool.

NocoBase, Budibase, ToolJet, and AnythingLLM are friendlier to business teams and are suitable for starting from internal tools, business processes, knowledge bases, or enterprise systems. Dify, Flowise, n8n, and Sim are more powerful, but users usually need to understand some models, workflows, APIs, data sources, or automation logic.

For non-technical teams, a safer approach is to start from a clear scenario, such as knowledge-base Q&A, approval workflows, internal back offices, or customer management systems, and then gradually add AI capabilities.

9. Are Open-Source AI No-Code Tools Suitable for Enterprises?

Yes, but enterprises should not choose tools only based on how many AI features they have. Deployment method, permission control, data security, model access, team collaboration, and long-term maintenance also matter.

If an enterprise cares more about business systems, tools such as NocoBase, ToolJet, and Budibase are closer to internal application scenarios. If the focus is workflow automation, n8n is worth considering. If the focus is AI applications and knowledge bases, Dify, Flowise, or AnythingLLM may be more suitable. What enterprises really need is a tool that can be implemented, maintained, and connected to real business processes.

We look forward to seeing AI and no-code platforms integrate more deeply in the future—not only to improve building efficiency, but also to help teams expand into more real business scenarios and make application building, workflow automation, and system maintenance more flexible.

If you found this article helpful, feel free to share it with friends who are following AI, no-code tools, or enterprise application development.

Related reading:

Weekly Updates: Add Support for Mobile Layout

NocoBase — Fri, 26 Jun 2026 16:49:29 +0000

Originally published at https://www.nocobase.com/en/blog/weekly-updates-20260626

Summarize the weekly product update logs, and the latest releases can be checked on our blog.

NocoBase is currently updated across three branches: main, next, and develop.

main: The most stable version to date, recommended for installation.
next: Beta version, contains upcoming new features and has been preliminarily tested. There might be some known or unknown issues. It is mainly used to collect feedback from test users and further optimize features. Ideal for test users who want to experience new features early and provide feedback.
develop: Alpha version, contains the latest feature code, may be incomplete or unstable, and is mainly used for internal development and rapid iteration. Suited for technical users interested in cutting-edge product capabilities, but not recommended for production use.

main

v2.1.11

Release date: 2026-06-25

🚀 Improvements

[Backup Manager] Fixed version-control restore failures when selected-collection backups contain database views or related database objects. (#9827) by cgyrock

🐛 Bug Fixes

[Flow Engine]
- Fix the issue where the block toolbar may not reappear after dragging a field (#9848) by zhangzhonghe
- Fix the issue where resizing fields closes the detail popup (#9850) by zhangzhonghe
[Client V2]
- Fix assigning values to display association fields in filter forms (#9875) by zhangzhonghe
- Fixed an issue where union roles could not be correctly resolved by variables in v2. (#9611) by gchust
[AI] Added support for using NocoBase request variables in user-bound MCP configurations and prevented user-bound MCP connection failures from interrupting AI employee conversations. (#9888) by cgyrock
[CLI] Prepare npm source dev dependencies (#9882) by chenos
[UI Templates] Fixed an issue where association field block templates could not be used. (#9406) by gchust
[AI: Knowledge Base] Fixed AI knowledge base document table and hit-test result cards overflowing on narrow screens or with long filenames. by cgyrock
[Version Control] Fixed version-control restore failures when selected-collection backups contain database views or related database objects. by cgyrock
[Multi-Space] Fixed the spaces settings page so it can load spaces beyond the first 20 records. by jiannx

v2.1.10

Release date: 2026-06-23

🎉 New Features

[AI] Added support for using current user variables in remote MCP client URLs and headers. (#9828) by cgyrock
[CLI] Support install hook scripts (#9824) by chenos

🚀 Improvements

[Client V2] Show field-level validation rules as read-only inherited rules in UI field validation settings. (#9819) by katherinehhh
[Flow Engine] Added the current block to the user context by default when building AI employees using the Flow Surface API. (#9840) by gchust

🐛 Bug Fixes

[Client V2] Fixed block did not refresh after blocks settings updated. (#9843) by gchust
[Workflow: Custom Action Event]
- Fixed custom-context trigger workflow actions so frontend variables in request payloads are resolved before submission in v2 action buttons (#9853) by mytharcher
- Fixed the v2 custom action workflow binding selector so enabled workflows are filtered with boolean values and can be listed correctly. (#9865) by mytharcher
[Block: Gantt] Fixed Gantt task popup template settings not applying or clearing correctly. (#9835) by jiannx
[Workflow: Approval]
- Fixed approval action node validation to allow null for applyDetail or approvalUid and skip processing unless a string reference is provided by mytharcher
- Fix the issue where related approvals do not load or refresh correctly by zhangzhonghe

v2.2.0-beta.7

Release date: 2026-06-25

🎉 New Features

[AI] Added support for using current user variables in remote MCP client URLs and headers. (#9828) by cgyrock

🚀 Improvements

[Client V2]
- Fixed missing Settings entries for Client V2 plugin manager cards when a plugin uses a shared or legacy settings path. (#9852) by katherinehhh
- Adjusted the v2 System settings menu order and page panel height to match the standard settings layout. (#9849) by katherinehhh
[Backup Manager]
- Fixed version-control restore failures when selected-collection backups contain database views or related database objects. (#9827) by cgyrock
- Improved backup manager table styling and long file name display. (#9864) by katherinehhh
[Public Forms] Separated v1 and v2 public form lists and fixed the v2 Configure page to open a configurable form detail page. (#9851) by katherinehhh
[User Data Synchronization] Added modern UI support for user data synchronization settings (#9837) by 2013xile
[WeCom] Added modern UI support for WeCom authentication, sync, and notification settings by 2013xile
[DingTalk] Added modern UI support for DingTalk authentication, sync, and notification settings by 2013xile

🐛 Bug Fixes

[Flow Engine]
- Fix the issue where resizing fields closes the detail popup (#9850) by zhangzhonghe
- Fix the issue where the block toolbar may not reappear after dragging a field (#9848) by zhangzhonghe
[Client V2]
- Fixed an issue where union roles could not be correctly resolved by variables in v2. (#9611) by gchust
- Fix assigning values to display association fields in filter forms (#9875) by zhangzhonghe
[CLI] Prepare npm source dev dependencies (#9882) by chenos
[AI] Added support for using NocoBase request variables in user-bound MCP configurations and prevented user-bound MCP connection failures from interrupting AI employee conversations. (#9888) by cgyrock
[UI Templates] Fixed an issue where association field block templates could not be used. (#9406) by gchust
[Data Source Manager] Added a warning and quick setup for v2 data source collections without a primary key or record unique key. (#9872) by katherinehhh
[Embed NocoBase] Fixed v2 embed pages losing token-based access after the URL token is removed and the page is refreshed. (#9857) by katherinehhh
[Workflow: Custom Action Event]
- Fixed the v2 custom action workflow binding selector so enabled workflows are filtered with boolean values and can be listed correctly. (#9865) by mytharcher
- Fixed custom-context trigger workflow actions so frontend variables in request payloads are resolved before submission in v2 action buttons (#9853) by mytharcher
[Multi-Space] Fixed the spaces settings page so it can load spaces beyond the first 20 records. by jiannx
[Version Control] Fixed version-control restore failures when selected-collection backups contain database views or related database objects. by cgyrock
[AI: Knowledge Base] Fixed AI knowledge base document table and hit-test result cards overflowing on narrow screens or with long filenames. by cgyrock
[Workflow: Approval] Fixed approval action node validation to allow null for applyDetail or approvalUid and skip processing unless a string reference is provided by mytharcher

v2.2.0-beta.6

Release date: 2026-06-22

🎉 New Features

[CLI] Support install hook scripts (#9824) by chenos
[UI Layout] Add support for mobile layout (#9641) by zhangzhonghe
[Backup Manager] Support backup and restore for KingBase as the primary database (#9791) by 2013xile
[Multi-Portal] Add Multi-Portal plugin by zhangzhonghe
[Migration Manager] Support migrations for KingBase as the primary database. by 2013xile

🚀 Improvements

[Client V2]
- Show field-level validation rules as read-only inherited rules in UI field validation settings. (#9819) by katherinehhh
- Add override value option for field value settings. (#9578) by gchust
[General] Improved AI knowledge base retrieval and documentation. (#9765) by cgyrock
[Flow Engine]
- Added the current block to the user context by default when building AI employees using the Flow Surface API. (#9840) by gchust
- Open RunJS browser globals. (#9841) by gchust
[Workflow] Stabilize update options test (#9773) by mytharcher
[Access Control] Aligned the v2 Users & Permissions settings pages with v1 behavior, including pagination totals, department tree behavior, selected styles, and internal permissions-panel scrolling. (#9810) by jiannx
[Backup Manager] Tables whose collection dataCategory is marked as 'runtime' are now excluded from backups automatically. (#9804) by cgyrock
[AI: Knowledge Base] Improved AI knowledge base document segmentation, segment management, hit tests, and document workflow node support. by cgyrock

🐛 Bug Fixes

[Client V2]
- Fixed block did not refresh after blocks settings updated. (#9843) by gchust
- Fixed custom action workflow trigger buttons sending custom context JSON under an extra values property or as a serialized string. (#9815) by mytharcher
- Fixed an issue where configuring an association field value as a fixed value or default value would not take effect. (#9820) by gchust
- Fixed an issue where event flows on sub-table columns would execute incorrectly. (#9821) by gchust
- Remove unexpected updateAssociationValues from association fields (#9812) by katherinehhh
- Fixed an issue where form submission would show incorrect message when a subform contained a sub-table. (#9807) by gchust
[AI]
- Fixed incompatible LangChain dependency resolutions for AI plugins. (#9831) by cgyrock
- Locked @langchain/openai to patch-level updates for AI packages. (#9829) by cgyrock
[App] Ignore unrelated currentScript when inferring plugin public path (#9839) by chenos
[Auth] Encrypted password data is no longer included in sign-in status responses (#9836) by 2013xile
[Block: Gantt] Fixed Gantt task popup template settings not applying or clearing correctly. (#9835) by jiannx
[Action: Print] Fixed v2 detail block printing so empty detail blocks no longer print the whole page. (#9832) by katherinehhh
[UI Templates] Fixed incorrect default context for ctx.openView. (#9811) by gchust
[File Manager] Fixed 404 errors when uploading files to attachment URL fields in external data sources (#9809) by 2013xile
[Action: Custom Request] Fixed v2 custom request actions showing an extra error when request settings are not configured. (#9802) by katherinehhh
[Workflow] Fixed workflow dispatcher recovery after unexpected dispatch errors. (#9783) by mytharcher
[AI Employees] Fixed AI employee shortcut task triggers so attachments from the current work context are included when running a task from the shortcut profile. (#9808) by cgyrock
[Data Source: External NocoBase] Proxy NocoBase external data source file upload and storage actions by upload data source by 2013xile
[AI: Knowledge Base]
- Fixed incompatible LangChain dependency resolutions for the AI knowledge base plugin. by cgyrock
- Fixed unclear failures when enabling the AI knowledge base plugin without the AI plugin available. by cgyrock
[Multi-Space] Fixed authentication recovery requests being blocked by stale multi-space headers. by jiannx
[Workflow: Subflow] Fixed asynchronous subflows so parent workflows can resume after worker restart or in-memory event mapping loss. by mytharcher
[Workflow: Approval] Fix the issue where related approvals do not load or refresh correctly by zhangzhonghe
[App Supervisor] Fixed a crash when remote WebSocket proxy responses fail by 2013xile

develop

v2.2.0-alpha.2

Release date: 2026-06-26

🎉 New Features

[Client V2] Add an environment variable to configure legacy and modern route entry modes. (#9891) by Molunerfinn
[AI] Added support for using current user variables in remote MCP client URLs and headers. (#9828) by cgyrock
[CLI] Support install hook scripts (#9824) by chenos
[Notification: Email] Migrated the workflow notification node client to v2, restored channel-specific notification forms, and kept legacy workflow route compatibility for migrated notification configuration. (#9817) by jiannx
[Workflow: Mailer Node]
- Added v2 client support for configuring the workflow mailer node. (#9825) by jiannx
- Add attachment support to the workflow mailer node. (#9724) by mytharcher
[UI Layout] Add support for mobile layout (#9641) by zhangzhonghe
[Backup Manager] Support backup and restore for KingBase as the primary database (#9791) by 2013xile
[Workflow]
- Migrate the Workflow settings page to the v2 client and share a reusable draggable category-tabs component via @nocobase/client-v2. (#9645) by Molunerfinn
- Added workflow database transaction scope support. (#9742) by mytharcher Reference: Database Transaction
[AI Employees]
- Added an external vector store configuration form for AI knowledge bases. (#9723) by cgyrock
[Multi-Portal] Add Multi-Portal plugin by zhangzhonghe
[Workflow: Database Transaction Node]
- Added a client-v2 implementation for the workflow database transaction node while preserving the legacy client entry. by katherinehhh
- Added the database transaction workflow node plugin. by mytharcher
[AI: Knowledge Base] Added an external vector store configuration form for AI knowledge bases. by cgyrock
[Migration Manager] Support migrations for KingBase as the primary database. by 2013xile
[Email Manager] Migrated the email manager client to v2. by jiannx

🚀 Improvements

[General]
- Refined Russian documentation translation for improved wording, readability, and terminology consistency. (#9816) by sembaev-a-a
- Improved AI knowledge base retrieval and documentation. (#9765) by cgyrock
- Updated the Chinese documentation label for the Version Control plugin. (#9776) by cgyrock
- Added Russian translations for new UI strings. (#9771) by sembaev-a-a
- Refined Russian documentation translation for improved wording, readability, and terminology consistency. (#9754) by sembaev-a-a
- Add a version control scenario to the AI builder quick start (#9748) by Molunerfinn Reference: AI Builder Quick Start
- Improved the version control documentation with AI Builder automatic revision guidance. (#9745) by cgyrock
[Flow Engine] Automatically refreshed related data blocks when RunJS closes a popup after updating data through resource APIs (#9873) by gchust
[Client V2]
- Fixed missing Settings entries for Client V2 plugin manager cards when a plugin uses a shared or legacy settings path. (#9852) by katherinehhh
- Adjusted the v2 System settings menu order and page panel height to match the standard settings layout. (#9849) by katherinehhh
- Show field-level validation rules as read-only inherited rules in UI field validation settings. (#9819) by katherinehhh
- Add override value option for field value settings. (#9578) by gchust
- Supported current item variables in the data scope of association field columns within form sub-tables. (#9444) by gchust
[CLI]
- Add env config schema version (#9782) by chenos
- Normalize app compat build versions (#9763) by chenos
- Support updating skills to a specified version (#9760) by chenos
- Clarify init setup wording (#9750) by chenos
[Workflow: JSON Calculation] Migrated the workflow JSON calculation node configuration UI to the v2 workflow canvas while preserving v1 canvas compatibility. (#9902) by mytharcher
[Workflow]
- Simplified workflow v2 create/update field assignment, improved selected variable display, and avoided generating unused assign-form model data. (#9887) by katherinehhh
- Exported workflow v2 canvas extension APIs for downstream workflow node plugins. (#9834) by katherinehhh
- Stabilize update options test (#9773) by mytharcher
- Migrate the workflow output node configuration to v2 and align v2 workflow result viewers with the legacy display behavior for string results. (#9813) by Molunerfinn
- Migrate the workflow end node to the v2 implementation. (#9795) by Molunerfinn
- Improved workflow metadata editing by allowing descriptions to be edited from the details modal and pre-filling duplicate workflow metadata. (#9766) by mytharcher
[Backup Manager]
- Fixed version-control restore failures when selected-collection backups contain database views or related database objects. (#9827) by cgyrock
- Improved backup manager table styling and long file name display. (#9864) by katherinehhh
- Tables whose collection dataCategory is marked as 'runtime' are now excluded from backups automatically. (#9804) by cgyrock
[Public Forms] Separated v1 and v2 public form lists and fixed the v2 Configure page to open a configurable form detail page. (#9851) by katherinehhh
[Workflow: Custom Action Event] Migrated workflow triggers and bind-workflow settings to client-v2, including action trigger, custom action trigger, request interception trigger, and submit/update action workflow binding settings. (#9845) by mytharcher
[User Data Synchronization] Added modern UI support for user data synchronization settings (#9837) by 2013xile
[Flow Engine]
- Open RunJS browser globals. (#9841) by gchust
- Added the current block to the user context by default when building AI employees using the Flow Surface API. (#9840) by gchust
[Workflow: HTTP Request Node] Migrated the workflow HTTP request node to client-v2. (#9806) by jiannx
[Access Control] Aligned the v2 Users & Permissions settings pages with v1 behavior, including pagination totals, department tree behavior, selected styles, and internal permissions-panel scrolling. (#9810) by jiannx
[Workflow: JavaScript] Migrated the JavaScript workflow node to client-v2 (#9805) by jiannx
[File Manager]
- Improved PDF previews by using the browser-native viewer for cross-origin PDF files while keeping same-origin PDF files rendered with PDF.js. (#9796) by mytharcher
- Added selectable text support to the file manager PDF preview when the PDF contains embedded text. (#9781) by mytharcher
[Users] Improved the Users & Permissions v2 page layout and department tree behavior. (#9780) by jiannx
[Action: Batch Edit] Improved v2 action plugin loading and kept migrated action buttons in a stable order. (#9778) by katherinehhh
[Action: Import Records] Improved import and async task error dialogs so long error messages can be fully read without breaking the layout. (#9746) by katherinehhh
[Locale Tester] Added a client v2 settings page for the locale tester. (#9744) by jiannx
[Version Control] Updated the Chinese display name of the Version Control plugin. by cgyrock
[Action: Import Records Pro] Improved import dialogs so long error messages remain readable and v2 processing mode can be selected directly from the settings menu. by katherinehhh
[AI: Knowledge Base] Improved AI knowledge base document segmentation, segment management, hit tests, and document workflow node support. by cgyrock
[WeCom] Added modern UI support for WeCom authentication, sync, and notification settings by 2013xile
[DingTalk] Added modern UI support for DingTalk authentication, sync, and notification settings by 2013xile

🐛 Bug Fixes

[Client V2]
- Fixed a brief no-pages prompt flash when refreshing in UI Editor mode. (#9918) by katherinehhh
- Fixed v2 form submit success redirects so they can reference the saved response record. (#9907) by katherinehhh
- Fixed table blocks failing when a configured drag sorting field has been deleted, and allowed clearing the drag sorting field setting. (#9867) by jiannx
- Fixed v2 table row action buttons changing row height. (#9866) by jiannx
- Fix assigning values to display association fields in filter forms (#9875) by zhangzhonghe
- Fixed an issue where union roles could not be correctly resolved by variables in v2. (#9611) by gchust
- Fixed block did not refresh after blocks settings updated. (#9843) by gchust
- Fixed custom action workflow trigger buttons sending custom context JSON under an extra values property or as a serialized string. (#9815) by mytharcher
- Fixed an issue where configuring an association field value as a fixed value or default value would not take effect. (#9820) by gchust
- Fixed an issue where event flows on sub-table columns would execute incorrectly. (#9821) by gchust
- Remove unexpected updateAssociationValues from association fields (#9812) by katherinehhh
- Fixed an issue where form submission would show incorrect message when a subform contained a sub-table. (#9807) by gchust
- Fixed untranslated Yes/No options in v2 filter form checkbox dropdowns. (#9792) by katherinehhh
- Fixed incorrect display and format settings when v2 table association title fields use time, date-only, or datetime fields. (#9785) by katherinehhh
- Fixed the issue that not able to update event flow settings after saving block as template. (#9585) by gchust
- Fixed migration progress not showing its dedicated progress view (#9761) by 2013xile
- Fix the issue where v2 pages could keep loading after signing in (#9738) by zhangzhonghe
[CLI]
- Support pnpm and yarn global self update (#9912) by chenos
- Prepare npm source dev dependencies (#9882) by chenos
- Require Node.js 22 for nb (#9749) by chenos
[Client]
- Corrected several copy and typo issues across locales, related UI text, and documentation. (#9905) by Molunerfinn
- Fix the issue where fields in horizontal subforms are too narrow to display data (#9755) by zhangzhonghe
[Flow Engine]
- Fixed an issue where some parameters of ctx.openView in RunJS would not take effect. (#9883) by gchust
- Fix the issue where resizing fields closes the detail popup (#9850) by zhangzhonghe
- Fix the issue where the block toolbar may not reappear after dragging a field (#9848) by zhangzhonghe
- Fixed Vietnamese and Chinese IME input handling in v2 single-line text and textarea fields. (#9764) by katherinehhh
[AI]
- Added support for using NocoBase request variables in user-bound MCP configurations and prevented user-bound MCP connection failures from interrupting AI employee conversations. (#9888) by cgyrock
- Fixed incompatible LangChain dependency resolutions for AI plugins. (#9831) by cgyrock
- Locked @langchain/openai to patch-level updates for AI packages. (#9829) by cgyrock
[App] Ignore unrelated currentScript when inferring plugin public path (#9839) by chenos
[Auth] Encrypted password data is no longer included in sign-in status responses (#9836) by 2013xile
[CLI v1] Fix the yarn dev error after upgrading projects created by create-nocobase-app from 2.0 to 2.1. (#9775) by Molunerfinn
[Server] Fixed unsafe plugin name handling in pm:enable to prevent local file inclusion through plugin resolution. (#9701) by mytharcher
[Backup Manager]
- Fixed inconsistent bold labels on the v2 Backup manager settings page. (#9908) by katherinehhh
- Fixed a security issue where unsafe PostgreSQL schema names could be accepted during backup restore (#9758) by 2013xile
[AI Employees]
- Fixed AI employee chat failures caused by replaying malformed tool calls. (#9900) by cgyrock
- Fixed AI employee shortcut task triggers so attachments from the current work context are included when running a task from the shortcut profile. (#9808) by cgyrock
- Fixed an issue where AI employees could not correctly fill sub-table data. (#9801) by gchust
- Fixed loss of message configuration in workflow LLM nodes. (#9743) by cgyrock
- Fixed an issue where attachments pasted into the AI employee dialog could not be removed. (#9753) by cgyrock
[Workflow]
- Fixed the workflow v2 add-node menu so unavailable node types are disabled according to workflow and branch rules (#9855) by mytharcher
- Restored debounced remote search for workflow collection trigger manual execution and aligned the selector with the v1 200-record fetch behavior. (#9870) by Molunerfinn
- Fixed workflow dispatcher recovery after unexpected dispatch errors. (#9783) by mytharcher
- Fixed workflow last modifier tracking after workflow nodes are changed. (#9769) by mytharcher
- Fixed workflow timeout handling so aborted executions and their pending jobs are updated atomically. (#9768) by mytharcher
[Block: iframe] Fixed 403 errors for normal users when viewing v2 iframe blocks in HTML mode. (#9889) by jiannx
[UI Templates]
- Fixed an issue where association field block templates could not be used. (#9406) by gchust
- Fixed incorrect default context for ctx.openView. (#9811) by gchust
[Workflow: Custom Action Event]
- Fixed the v2 custom action workflow binding selector so enabled workflows are filtered with boolean values and can be listed correctly. (#9865) by mytharcher
- Fixed custom-context trigger workflow actions so frontend variables in request payloads are resolved before submission in v2 action buttons (#9853) by mytharcher
- Fixed action panel v2 trigger workflow buttons showing success and sending a request when no workflow is bound. (#9798) by mytharcher
[Data Source Manager]
- Added a warning and quick setup for v2 data source collections without a primary key or record unique key. (#9872) by katherinehhh
- Fixed an issue where deleting the active collection category in the v1 data source manager could leave the All collections tab empty. (#9757) by katherinehhh
- Fixed the blank edit field drawer caused by repeated rerenders on the v1 external data source Configure fields page. (#9759) by katherinehhh
[Workflow: Mailer Node] Fixed workflow v2 test failures caused by missing mocks for trigger workflow action registration. (#9863) by jiannx
[Embed NocoBase] Fixed v2 embed pages losing token-based access after the URL token is removed and the page is refreshed. (#9857) by katherinehhh
[Workflow: Response Message] Migrated the workflow response message node to the v2 canvas and fixed unsupported workflow types being able to add it. (#9830) by jiannx
[Block: Gantt] Fixed Gantt task popup template settings not applying or clearing correctly. (#9835) by jiannx
[Action: Print] Fixed v2 detail block printing so empty detail blocks no longer print the whole page. (#9832) by katherinehhh
[Workflow: JavaScript] Fixed JavaScript workflow node registration failure in the legacy workflow client. (#9826) by jiannx
[File Manager]
- Fixed 404 errors when uploading files to attachment URL fields in external data sources (#9809) by 2013xile
- Fixed PDF preview failures caused by the PDF.js worker module not loading correctly. (#9779) by mytharcher
- Fix PDF previews missing CJK/CID font text after switching to pdf.js. (#9737) by mytharcher
[Action: Custom Request] Fixed v2 custom request actions showing an extra error when request settings are not configured. (#9802) by katherinehhh
[Flow Engine] Fixed an issue where current record forms and details in popup could contain incorrect data if built by AI. (#9788) by gchust
[Async Task Manager]
- Fixed async task file download errors when the task id is missing from filterByTk. (#9705) by mytharcher
- Fixed incorrect request IDs in async task worker logs (#9686) by 2013xile
[Action: Import Records] Store import uploads on disk to reduce memory pressure during large imports. (#9739) by mytharcher
[Workflow: SQL Node] Fixed SQL workflow legacy template-variable migration being skipped for some beta-version users. (#9762) by mytharcher
[Block: Kanban]
- Fixed unexpected hidden popup action persistence and repeated destroy requests when opening calendar, gantt, and kanban blocks outside edit mode. (#9772) by jiannx
- Fixed URL support for calendar and related popups. (#9751) by jiannx
[API Documentation] Fixed the API documentation package declaration build failure. (#9752) by katherinehhh
[Version Control]
- Fixed version-control restore failures when selected-collection backups contain database views or related database objects. by cgyrock
- Adjusted the Version control topbar shortcut to appear next to the UI editor in both legacy and v2 admin layouts. by cgyrock
[AI: Knowledge Base]
- Fixed AI knowledge base document table and hit-test result cards overflowing on narrow screens or with long filenames. by cgyrock
- Fixed incompatible LangChain dependency resolutions for the AI knowledge base plugin. by cgyrock
- Fixed unclear failures when enabling the AI knowledge base plugin without the AI plugin available. by cgyrock
[Multi-Space]
- Fixed the spaces settings page so it can load spaces beyond the first 20 records. by jiannx
- Fixed authentication recovery requests being blocked by stale multi-space headers. by jiannx
- Fixed permission errors when space managers add users without access to the users email field. by jiannx
[Data Source: External NocoBase] Proxy NocoBase external data source file upload and storage actions by upload data source by 2013xile
[Action: Export Records Pro] Improved v2 import/export pro Processing mode settings and tooltip descriptions. by katherinehhh
[Action: Import Records Pro] Avoid parsing large pro import files on the request node before async task creation. by mytharcher
[Workflow: Subflow] Fixed asynchronous subflows so parent workflows can resume after worker restart or in-memory event mapping loss. by mytharcher
[Migration Manager] Fixed failures when importing large migration data files by 2013xile
[Template Print] Rejected unsupported template file types before template printing starts by 2013xile
[Workflow: Approval]
- Fixed approval action node validation to allow null for applyDetail or approvalUid and skip processing unless a string reference is provided by mytharcher
- Fix the issue where related approvals do not load or refresh correctly by zhangzhonghe
- Fix the issue where related data is not displayed in v2 approval forms by zhangzhonghe
[App Supervisor] Fixed a crash when remote WebSocket proxy responses fail by 2013xile

Weekly Updates : Add External Vector Store Configuration Form for AI Knowledge Bases

NocoBase — Sun, 21 Jun 2026 07:39:13 +0000

Originally published at https://www.nocobase.com/en/blog/weekly-updates-20260619

Summarize the weekly product update logs, and the latest releases can be checked on our blog.

NocoBase is currently updated with three branches: main , next and develop.

main：The most stable version to date, recommended for installation;
next：Beta version, contains upcoming new features and has been preliminarily tested. There might be some known or unknown issues. It's mainly for test users to collect feedback and optimize functions further. Ideal for test users who want to experience new features early and give feedback;
develop：Alpha version, contains the latest feature code, may be incomplete or unstable, mainly for internal dev and rapid iteration. Suited for tech users interested in product's cutting-edge, but with potential issues and incomplete functions. Not for production use.

main

v2.1.9

🚀 Improvements

[client-v2] Add override value option for field value settings. (#9578) by gchust

🐛 Bug Fixes

[client-v2]
- Fixed custom action workflow trigger buttons sending custom context JSON under an extra values property or as a serialized string. (#9815) by mytharcher
- Fixed an issue where configuring an association field value as a fixed value or default value would not take effect. (#9820) by gchust
[auth] Encrypted password data is no longer included in sign-in status responses (#9836) by 2013xile
[app] Ignore unrelated currentScript when inferring plugin public path (#9839) by chenos
[UI templates] Fixed incorrect default context for ctx.openview. (#9811) by gchust

v2.1.8

Release date: 2026-06-18

🐛 Bug Fixes

[ai]
- Locked @langchain/openai to patch-level updates for AI packages. (#9829) by cgyrock
- Fixed incompatible LangChain dependency resolution for AI plugins. (#9831) by cgyrock
[AI: Knowledge base]
- Fixed unclear error messages when enabling the AI knowledge base plugin without the AI plugin available. by cgyrock
- Fixed incompatible LangChain dependency resolution for the AI knowledge base plugin. by cgyrock

v2.1.7

Release date: 2026-06-18

🎉 New Features

[Backup manager] Support backup and restore for KingBase as the primary database (#9791) by 2013xile
[Migration manager] Support migrations for KingBase as the primary database. by 2013xile

🚀 Improvements

[AI: Knowledge base] Improved AI knowledge base retrieval and documentation. (#9765) by cgyrock
[cli] Add env config schema version (#9782) by chenos
[Workflow] Stabilize update options test (#9773) by mytharcher
[File manager] Improved PDF previews: cross-origin PDF files now use the browser-native viewer, while same-origin PDF files continue to use PDF.js. (#9796) by mytharcher
[Backup manager] Tables whose collection dataCategory is marked as 'runtime' are now automatically excluded from backups. (#9804) by cgyrock
[AI: Knowledge base] Improved AI knowledge base document segmentation, segment management, hit tests, and document workflow node support. by cgyrock

🐛 Bug Fixes

[client-v2]
- Fixed an issue where form submission would show an incorrect message when a subform contained a sub-table. (#9807) by gchust
- Fixed an issue where event flows on sub-table columns would execute incorrectly. (#9821) by gchust
- Removed unexpected updateAssociationValues from association fields (#9812) by katherinehhh
- Fixed untranslated Yes/No options in v2 filter form checkbox dropdowns. (#9792) by katherinehhh
- Fixed the issue where event flow settings could not be updated after saving a block as a template. (#9585) by gchust
- Fixed incorrect display and format settings when v2 table association title fields use time, date-only, or datetime fields. (#9785) by katherinehhh
[Workflow] Fixed workflow dispatcher recovery after unexpected dispatch errors. (#9783) by mytharcher
[File manager] Fixed 404 errors when uploading files to attachment URL fields in external data sources (#9809) by 2013xile
[Action: Custom request] Fixed V2 custom request actions showing an unnecessary error when request settings are not configured. (#9802) by katherinehhh
[AI employees]
- Fixed an issue where AI employees could not correctly fill sub-table data. (#9801) by gchust
- Fixed AI employee shortcut task triggers so that attachments from the current work context are included when running a task from the shortcut profile. (#9808) by cgyrock
[Workflow: Custom action event] Fixed action panel v2 trigger workflow buttons showing success and sending a request when no workflow is bound. (#9798) by mytharcher
[Flow engine] Fixed an issue where current record forms and details in popup could contain incorrect data when built by AI. (#9788) by gchust
[Async task manager] Fixed async task file download errors when the task id is missing from filterByTk. (#9705) by mytharcher
[Data source: External NocoBase] Proxy NocoBase external data source file upload and storage actions by upload data source by 2013xile
[Multi-space] Fixed permission errors when space managers add users without access to the user email field. by jiannx
[Workflow: Subflow] Fixed asynchronous subflows so that parent workflows can resume after worker restart or in-memory event mapping loss. by mytharcher
[App supervisor] Fixed a crash when remote WebSocket proxy responses fail by 2013xile

v2.1.5

Release date: 2026-06-15

🎉 New Features

[Workflow: Mailer node] Added support for sending attachments in workflow mailer nodes. (#9724) by mytharcher

🚀 Improvements

[client-v2] Relation field column data scopes in form subtables now support current item variables. (#9444) by gchust
[undefined] Unified the Chinese documentation name of the version control plugin as “版本控制”. (#9776) by cgyrock
[File manager] Added selectable text support to PDF previews in the file manager for PDFs with embedded text. (#9781) by mytharcher
[Action: Bulk edit] Optimized the loading method for v2 action plugins and kept the order of migrated action buttons stable. (#9778) by katherinehhh
[Version control] Changed the Chinese display name of the version control plugin to “版本控制”. by cgyrock

🐛 Bug Fixes

[cli-v1] Fixed an error when running yarn dev after upgrading projects created with create-nocobase-app from 2.0 to 2.1. (#9775) by Molunerfinn
[client-v2] Fixed the issue where migration progress did not show the dedicated progress view. (#9761) by 2013xile
[flow-engine] Fixed Vietnamese and Chinese IME input issues in v2 single-line text and multiline text fields. (#9764) by katherinehhh
[server] Fixed unsafe plugin name handling in pm:enable to prevent local file inclusion risks during plugin resolution. (#9701) by mytharcher
[File manager] Fixed PDF preview failures caused by abnormal pdf.js worker module loading. (#9779) by mytharcher
[Block: Kanban] Fixed the issue where opening Calendar, Gantt, and Kanban blocks outside edit mode unexpectedly persisted hidden popup actions and repeatedly sent delete requests. (#9772) by jiannx
[Action: Export records Pro] Improved processing mode settings and explanatory prompts for v2 Import/Export Pro. by katherinehhh
[Migration manager] Fixed possible failures when importing large migration data files. by 2013xile
[Template print] Rejected unsupported template file types before template printing starts. by 2013xile

v2.1.4

Release date: 2026-06-13

🚀 Improvements

[Workflow] Improved the workflow metadata editing experience by supporting description editing in the details popup and automatically filling source workflow metadata when duplicating workflows. (#9766) by mytharcher

🐛 Bug Fixes

[Action: Import records] Changed uploaded import files to disk storage to reduce memory pressure during large data imports. (#9739) by mytharcher
[Backup manager] Fixed a security issue where unsafe PostgreSQL schema names could be accepted during backup restoration. (#9758) by 2013xile
[Workflow]
- Fixed workflow timeout handling so aborted executions and their pending tasks can be updated atomically. (#9768) by mytharcher
- Fixed the issue where the workflow’s last updated by field was not updated after workflow node changes. (#9769) by mytharcher
[Action: Import records Pro] Avoided parsing large files in the request node before Pro import creates an async task. by mytharcher
[Version control] Adjusted the position of the version control top shortcut entry so it appears next to the UI editor in both legacy and v2 admin layouts. by cgyrock

v2.1.3

Release date: 2026-06-12

🚀 Improvements

[cli]
- normalize app compat build versions (#9763) by chenos
- support updating skills to a specified version (#9760) by chenos

🐛 Bug Fixes

[client] Fixed the issue where fields in horizontal subforms are too narrow to display data (#9755) by zhangzhonghe
[Data source manager]
- Fixed the blank edit field drawer caused by repeated rerenders on the v1 external data source Configure fields page. (#9759) by katherinehhh
- Fixed an issue where deleting the active collection category in the v1 data source manager could leave the All collections tab empty. (#9757) by katherinehhh
[Async task manager] Fixed incorrect request IDs in async task worker logs (#9686) by 2013xile
[Workflow: SQL node] Fixed SQL workflow legacy template-variable migration being skipped for some beta-version users. (#9762) by mytharcher
[AI employees]
- Fixed loss of message configuration in workflow LLM nodes. (#9743) by cgyrock
- Fixed an issue where attachments pasted into the AI employee dialog could not be removed. (#9753) by cgyrock
[Block: Kanban] Fixed URL support for calendar and related popups. (#9751) by jiannx
[Workflow: Approval] Fixed the issue where related data is not displayed in v2 approval forms by zhangzhonghe

v2.1.2

Release date: 2026-06-12

🎉 New Features

[AI employees] Added an external vector store configuration form for AI knowledge bases. (#9723) by cgyrock
[AI: Knowledge base] Added an external vector store configuration form for AI knowledge bases. by cgyrock

🚀 Improvements

[undefined]
- Added a version control scenario to the AI builder quick start (#9748) by Molunerfinn Reference: AI Builder Quick Start
- Improved the version control documentation with AI Builder automatic revision guidance. (#9745) by cgyrock
[cli] clarify init setup wording (#9750) by chenos
[Action: Import records] Improved import and async task error dialogs so long error messages can be fully read without breaking the layout. (#9746) by katherinehhh
[Action: Import records Pro] Improved import dialogs so long error messages remain readable and v2 processing mode can be selected directly from the settings menu. by katherinehhh

🐛 Bug Fixes

[client-v2] Fixed the issue where v2 pages could keep loading after signing in (#9738) by zhangzhonghe
[cli] require Node.js 22 for nb (#9749) by chenos
[File manager] Fix PDF previews missing CJK/CID font text after switching to pdf.js. (#9737) by mytharcher

v2.2.0-beta.5

Release date: 2026-06-16

🚀 Improvements

[cli] Added schema version records for env configuration. (#9782) by chenos
[File manager] Improved PDF previews: cross-origin PDF files now use the browser-native preview, while same-origin PDF files continue to be rendered with PDF.js. (#9796) by mytharcher

🐛 Bug Fixes

[client-v2]
- Fixed the issue where event flow settings could no longer be modified after a block was converted into a template. (#9585) by gchust
- Fixed the issue where checkbox dropdown options in v2 filter forms did not display translated text. (#9792) by katherinehhh
- Fixed incorrect display and format settings when the title field of a v2 table relation field used a time, date, or datetime field. (#9785) by katherinehhh
[Flow engine] Fixed incorrect data in current record forms and detail data inside popups during AI building. (#9788) by gchust
[Workflow: Custom action event] Fixed the issue where action panel v2 trigger workflow buttons still showed success and sent requests when no workflow was bound. (#9798) by mytharcher
[AI employees] Fixed the issue where AI employees could not correctly fill sub-table data. (#9801) by gchust

v2.2.0-beta.3

Release date: 2026-06-15

🎉 New Features

[Workflow: Mailer node] Added support for sending attachments in workflow mailer nodes. (#9724) by mytharcher
[Workflow] Added support for database transaction scopes in workflows. (#9742) by mytharcher Reference: Database transactions
[Workflow: Database transaction node] Added a database transaction workflow node plugin. by mytharcher

🚀 Improvements

[client-v2] Relation field columns in form subtables now support current item variables in data scopes. (#9444) by gchust
[undefined] Unified the Chinese documentation name of the Version control plugin as “版本控制”. (#9776) by cgyrock
[File manager] Added selectable text support to PDF previews in File manager for PDFs with embedded text. (#9781) by mytharcher
[Users] Improved the layout of the v2 Users and Permissions pages and optimized department tree behavior. (#9780) by jiannx
[Action: Bulk edit] Optimized how v2 action plugins are loaded and kept the order of migrated action buttons stable. (#9778) by katherinehhh
[Version control] Renamed the Chinese display name of the Version control plugin to “版本控制”. by cgyrock

🐛 Bug Fixes

[cli-v1] Fixed an error when running yarn dev after upgrading projects created with create-nocobase-app from 2.0 to 2.1. (#9775) by Molunerfinn
[flow-engine] Fixed Vietnamese and Chinese IME input issues in v2 single-line text and multiline text fields. (#9764) by katherinehhh
[client-v2] Fixed the issue where migration progress did not display the dedicated progress view. (#9761) by 2013xile
[server] Fixed unsafe plugin name handling in pm:enable to avoid local file inclusion risks during plugin resolution. (#9701) by mytharcher
[Async task manager] Fixed database query errors caused by missing filterByTk when downloading async task files. (#9705) by mytharcher
[File manager] Fixed PDF preview failures caused by abnormal loading of the pdf.js worker module. (#9779) by mytharcher
[Block: Kanban] Fixed the issue where opening Calendar, Gantt, and Kanban blocks in non-edit mode unexpectedly persisted hidden popup actions and repeatedly sent delete requests. (#9772) by jiannx
[Action: Export records Pro] Improved the processing mode settings and help text for v2 Import/Export Pro. by katherinehhh
[Multi-space] Fixed the issue where space administrators could not add space users when they did not have permission for the user email field. by jiannx
[Migration manager] Fixed possible failures when importing large migration data files. by 2013xile
[Template print] Rejected unsupported template file types before template printing starts. by 2013xile

v2.2.0-beta.2

Release date: 2026-06-13*

🎉 New Features

[AI employees] Added an external vector store configuration form for AI knowledge bases. (#9723) by cgyrock
[AI: Knowledge base] Added an external vector store configuration form for AI knowledge bases. by cgyrock
[Email manager] Migrated the Email manager client to v2. by jiannx

🚀 Improvements

[cli]
- Optimized compatibility checks for different version number formats. (#9763) by chenos
- Added support for updating skills to a specified version. (#9760) by chenos
- Improved the wording of initialization setup prompts. (#9750) by chenos
[undefined]
- Added a version control conversation scenario to the AI Builder overview page. (#9748) by Molunerfinn Reference: AI Builder Quick Start
- Improved version control documentation with notes on automatic version saving in AI Builder. (#9745) by cgyrock Reference: Version control
[Workflow] Improved the workflow metadata editing experience by supporting description editing in the details popup and automatically filling source workflow metadata when duplicating workflows. (#9766) by mytharcher
[Action: Import records] Improved import and async task error detail dialogs so long error messages can be fully viewed without breaking the layout. (#9746) by katherinehhh
[Translation test tool] Added a client-v2 settings page for the translation test tool. (#9744) by jiannx
[Action: Import records Pro] Improved import dialogs so long error messages can be fully viewed, and processing mode can be selected directly from the v2 settings menu. by katherinehhh

🐛 Bug Fixes

[client] Fixed the issue where fields in horizontal subforms were too narrow to display data. (#9755) by zhangzhonghe
[client-v2] Fixed the issue where v2 pages could keep loading after signing in. (#9738) by zhangzhonghe
[cli] Added Node.js version detection for the nb runtime environment. (#9749) by chenos
[Action: Import records] Changed uploaded import files to disk storage to reduce memory pressure during large data imports. (#9739) by mytharcher
[Async task manager] Fixed incorrect request IDs in async task worker logs. (#9686) by 2013xile
[Workflow]
- Fixed workflow timeout handling so aborted executions and their pending tasks can be updated atomically. (#9768) by mytharcher
- Fixed the issue where the workflow’s last updated by field was not updated after workflow node changes. (#9769) by mytharcher
[Data source manager]
- Fixed the blank field edit drawer caused by repeated rerenders on the v1 external data source Configure fields page. (#9759) by katherinehhh
- Fixed the issue where deleting the current collection category in the v1 data source manager could leave the All collections tab empty. (#9757) by katherinehhh
[Backup manager] Fixed a security issue where unsafe PostgreSQL schema names could be accepted during backup restoration. (#9758) by 2013xile
[Workflow: SQL node] Fixed the issue where SQL workflow legacy template variable migration was skipped for some beta-version users. (#9762) by mytharcher
[Block: Kanban] Fixed URL support for Calendar and other popups. (#9751) by jiannx
[AI employees]
- Fixed the issue where attachments pasted into the AI employee dialog could not be removed. (#9753) by cgyrock
- Fixed loss of message configuration in workflow LLM nodes. (#9743) by cgyrock
[File manager] Fixed missing Chinese/CID font text in some PDF previews after switching to pdf.js. (#9737) by mytharcher
[API documentation] Fixed the build failure of the API documentation plugin declaration file. (#9752) by katherinehhh
[Action: Import records Pro] Avoided parsing large files in the request node before Pro import creates an async task. by mytharcher
[Version control] Adjusted the position of the version control top shortcut entry so it appears next to the UI editor in both legacy and v2 admin layouts. by cgyrock
[Workflow: Approval] Fixed the issue where related data was not displayed in v2 approval forms. by zhangzhonghe

Do Software and Programmers Still Have a Future?

NocoBase — Tue, 16 Jun 2026 03:54:47 +0000

Originally published at https://www.nocobase.com/en/blog/future-of-software-programmers-revenue-doubled

Background

Six months ago, when we released NocoBase 2.0, we published our second recap: No AI, No VC, Just 17K Stars and Real Revenue. At that point, NocoBase had already reached around $1.4 million in annual revenue.

The plan had been simple: one recap a year, sharing NocoBase's growth as it happened. This third piece was supposed to wait until the end of this year, when NocoBase 3.0 comes out. But the world is changing too fast. AI is hitting this industry with a new shock wave almost every day. In a jolt like this, NocoBase was never going to remain untouched. We have been pulled, over and over, into all kinds of uncertainty.

So we had to move faster. We had to stay nimble enough to answer the shock as it came.

That is why this recap is arriving half a year early, together with NocoBase 2.1. Better to write it now than wait another six months and wonder whether this industry will still look the same by then. Or whether anyone will still care about an open-source product like this. Or whether anyone will still care about software, or programmers, at all.

Where We Are

It has now been five years since we committed the first line of code on GitHub.

Compared with six months ago, our team size has not changed. We are still 14 people. We still do not have a dedicated sales team. For the most part, users still find us, not the other way around. But beyond SEO, we have also started paying serious attention to generative engine optimization, and we already have quite a few paying users who discovered NocoBase through ChatGPT and Claude.

Here are a few other numbers:

GitHub stars: 22.7k
Contributors: 115
Git clones: 3K/day

Revenue

Now that the revenue figure is becoming more substantial, we will stop disclosing exact numbers in future recap articles. But we will keep sharing the trend lines, and the shape of what is happening underneath them.

In the first five months of 2026, our revenue was exactly double what it was in the same period of 2025. In our best month so far, monthly revenue alone had already reached our entire revenue for all of 2024.

But if I am being honest about how it felt from the inside, this was not the result of some smooth, graceful curve upward. It came after a major turn.

Were We About to Be Killed?

Before 2025, NocoBase was positioned as a no-code platform. It was a direction plenty of companies had already proven to be valuable and commercially viable, even if it was not the kind of business that usually leads to spectacular fortunes. The familiar products in this category can become solid businesses, even if they rarely produce outsized outcomes. With differentiated positioning, a standardized product, and a global market, we believed we had a chance to build a durable business around a focused product and a lean team.

Starting in 2025, we began introducing AI features into the product. That opened up a new imaginative horizon for the traditional no-code platform. AI could play a supporting role in business workflows and help people get certain kinds of work done more efficiently. At the same time, our revenue was climbing quickly, which seemed to validate the decision.

Then, at the end of 2025, things changed.

When Opus 4.5 was released, it felt as though the weather turned overnight. Social media was suddenly full of awe at the revolutionary changes it seemed to be bringing to programming. Then came the wave of layoff news, followed by all the loud voices declaring that traditional software was about to be killed. And just like that, the whole industry seemed to be living inside the same split reality, one half panic, one half exhilaration.

That mood spread through our team almost immediately.

More than one colleague started to feel that what we were building no longer had any meaning. And once that feeling takes hold, it does real damage. We had spent years building something we were proud of. Now AI appeared able to produce something similar in a few hours. And AI was still evolving at a frightening pace. So what were we still here for? Only a month earlier, I had believed that the stronger AI became, the better it would be for us, unless it planned to take over the entire world. Was that day really about to arrive this quickly?

At the same time, NocoBase's revenue also entered a weaker stretch. I could not tell whether that was just because of the Christmas and New Year holiday season, or because a flood of AI news had genuinely affected how enterprises were making purchasing decisions.

For two full months, I read obsessively. I tried product after product. Every day I discussed, argued, and compared notes with the more radical people on our team, while also trying to keep everyone grounded. I spoke with NocoBase users about how they viewed AI and how it was actually being used inside their companies.

And while I was doing all that, I sank into a serious state of anxiety, the kind I had not experienced in many years. When I was resting, I could hear my own heartbeat. I would fall asleep, wake up quickly, and find it hard to sleep again. The muscles in my abdomen were often so tight that I could feel them beating with my pulse.

NocoBase has not made us a huge amount of money. But everyone on this team has tied some part of their ideals to it, along with some part of their hope for a better life. If it were killed, it would hurt. A lot.

It was not until after February, after many rounds of intense discussion inside the team and many conversations with users, that I felt we had finally thought it through. We then held three all-hands alignment sessions in a row and shared a presentation called The Twilight of the Old Version, the Dawn of the New One. It laid out why NocoBase still deserves to exist, and where it should go next. We made sure everyone understood the reasoning behind the direction and felt confident moving forward.

Looking for What Does Not Change

The day before I started writing this piece, one of the three largest life sciences companies in the world contacted us. They wanted to explore using NocoBase as infrastructure, layering AI capabilities on top of traditional systems like SAP, and rebuilding certain parts of their supply chain on that basis.

For example, they want to identify and structure large volumes of orders arriving from different countries through fax, paper, handwriting, websites, and other channels. They want to plan shipping in batches based on warehouse locations and delivery destinations. They want to process accounts receivable, bills, and invoices more efficiently depending on different payment methods.

This is a giant enterprise with tens of thousands of employees spread across dozens of countries. They have no shortage of technical expertise and access to the most advanced models. So why would they still consider a product like NocoBase, instead of simply instructing an LLM to write the whole thing from scratch?

That was exactly the question we had been discussing and thinking through over the past few months.

Large models and agents are advancing at astonishing speed. They are making code itself incredibly cheap. They are making programmers as a group feel deeply uneasy. But once that same wave reaches traditional enterprises, it loses a lot of force.

The furniture company is still making furniture. The supply chain team is still doing supply chain work. Processes that never even made it to digitalization are still running on A4 paper and fax. These things are not going to undergo some revolutionary transformation just because LLMs can generate code. LLMs are not wish-granting machines. You cannot wave a magic wand and expect an entire enterprise to remake itself.

The bar is still very high. Solving real problems in production, sales, logistics, finance, and the rest of the business means building systems that are solid, secure, able to run for years, able to evolve, and able to absorb AI in ways that genuinely improve efficiency.

Code generation lowers the barrier to generating code. That is all. And in practice, if you use it badly, it may lead you straight into more traps.

In The Twilight of the Old Version, the Dawn of the New One, we listed several things that we believe will remain unchanged for quite a long time. Those are also the reasons we believe NocoBase still needs to exist.

If AI is going to truly land inside business, a chat window is not enough. AI needs a real operating environment. NocoBase gives it one, along with a ready-made toolbox. We turn data, workflows, and functional modules into interfaces AI can actually use, while surrounding that access with strict permissions and full logging. That is what allows AI to query data safely, identify risks, carry out complex tasks, and gradually move enterprise software from the old logic of "people looking for data" to a new logic of "tasks finding people."
An enterprise-grade system must have standardized data structures, rigorous permissions, strict business workflows, audit logs for every action, and historical records for key data. This layer is complex, and it cannot afford to be wrong. And no matter how much AI improves, it will not make these things disappear, because this is not really a problem of intelligence. It is a problem of people and organizations. Rather than asking AI to rewrite a fresh, half-proven version of this every time, it makes far more sense to build on top of standardized foundational modules that have already been thoroughly tested.
Enterprise applications contain a great deal of basic functionality that gets reused over and over again. User systems, authentication, email and SMS delivery, notification centers, data import and export, backend asynchronous jobs, almost every system needs them. As AI develops, these building blocks will keep changing too, and more AI-oriented tools will appear with them. But asking AI to rewrite them from scratch every single time is a massive waste. Reusing mature capabilities that already exist in the platform still creates enormous value.
WYSIWYG no-code visual configuration still matters. Its value is no longer just that it reduces the amount of code people need to write. It also gives AI output a visible surface that humans can adjust directly. If AI generates an interface or a workflow, people should be able to understand it at a glance, then refine it with their own hands. That kind of directness preserves transparency in human-AI collaboration. It keeps the system from turning into a black box that only AI understands and no one else can really move.
Without truly strong architectural design, the more code AI generates, the harder it becomes to maintain. NocoBase uses architecture to impose a set of physical rules on the system. It keeps interfaces and interaction styles highly consistent. It keeps automation under shared standards. It keeps plugins under shared standards too. That is what makes long-term, stable iteration possible.

Based on these things that do not change, we immediately adjusted our product positioning. We moved from "no-code platform" to "AI + no-code" infrastructure, and within a matter of weeks we completed the corresponding product changes. Of course, AI itself helped enormously, pushing our efficiency to more than twice what it was before. The no-code platform that had originally been built for people formally became a platform built for collaboration between people and AI.

And soon after that, we started receiving strong positive feedback from several large enterprises.

One pharmaceutical company, with more than 20,000 employees and dozens of subsidiaries, had begun promoting AI coding across the whole company months earlier. In the process, they had done a great deal of engineering work to deal with hallucinations, limited context windows, and architectural drift, all the problems that make long-term stable iteration so difficult. Even then, the results were not encouraging. Eventually, they concluded that a more sensible approach was to develop on top of a scaffold suited to AI, one that would preserve efficiency and flexibility while also placing strong constraints on AI behavior. After spending several weeks testing NocoBase, they concluded that NocoBase was exactly that kind of infrastructure.

Another top-tier renewable energy company in the wind power sector used NocoBase inside a single team for several months, then formally rolled it out across the entire company, to tens of thousands of employees, as an AI development platform. It has since gone into production in key scenarios such as review workflows, project management, and AI portals, allowing AI to create dependable value in those areas. They also have more than enough technical and business experts, the most advanced models, and essentially unlimited tokens. But spending time and resources on low-level infrastructure that does not generate returns is simply not worth it. Once they adopted NocoBase, they were able to focus most of their energy on the business itself.

What We Do Next

No matter what we think, AI is still moving very fast. If we want to stay alive for longer, and if we want to keep finding a sense of fulfillment true to our original intentions, then we need to keep reminding ourselves not to forget a few simple facts.

Stand on What Lasts

Under AI's impact, the pace of the world seems to have accelerated dramatically. And with social platforms, industry hype, and recommendation algorithms amplifying everything, we are bombarded by new concepts every day. But from what we have seen in real life, the world of AI vendors and online commentary is very different from the world of actual enterprises.

No matter how intense the conceptual bombardment becomes, real businesses are still making their pharmaceuticals, their cars, their bottled water. Many companies still have not even completed basic digitalization. They still rely heavily on paper and Excel, let alone any AI revolution. If we anchor ourselves in the things we can identify as lasting, and take those real businesses as the people we serve, that will be the foundation of our healthy survival.

Embrace What Changes Fast

Since the company was founded, we had been adding one or two new people to the product and engineering team every year. But starting this year, we decided to stop expanding the engineering team. Instead, we would give the existing team access to the most advanced models and plenty of tokens. In practice, the result is clear: people's output has already increased by at least a factor of two.

Using frontier models every day also keeps the team highly sensitive. It helps us really understand the boundaries of what these models can do, where they fit, and where they do not. Once we understand those things, we can fold them into NocoBase as part of the product itself.

Live in the Present

I have written so much above about "what lasts." But how long is "long-term," really? Six months? One year? Three years? To be honest, we ourselves cannot judge that with confidence.

But there is no need to let that become a source of anxiety. We are a bridge between AI and enterprises. AI is moving fast, so fast that it is hard to say what things will look like this time next year. But between the speed of AI and the speed of most enterprises in the real world, there is still a gap of many months, if not years. As long as we stay grounded in the actual conditions and needs of those businesses, there will always be time for us to adjust, and perhaps even discover more opportunities along the way.

What we most need to avoid in this process is end-state thinking: the belief that if AI can generate code, then it can do anything; the belief that if AI will eventually take over everything, then whatever we do now is meaningless. The real world in front of us does not look like that.

From a Vast Ocean, We Only Need One Drop

If the needs of enterprises around the world are a vast ocean, then we do not need a bucketful. We only need one drop. That is enough for a team our size to move at our own pace, stay focused on what we love, create value for the users inside that one drop, and find a sense of achievement there.

NocoBase has to stay focused on a precise kind of user. We are not trying to make every enterprise our target customer. Many people may not agree with the things we have listed here as long-term constants. That is fine. As long as the users in this one drop agree, that is enough.

So, Do Programmers and Software Still Have a Future?

I think the answer depends mostly on what we want, and on what we are willing to do.

If the ambition is to build another Salesforce, form a monopoly, and change the world, that is beyond our ability to judge. But for a product like NocoBase, built by a team of fourteen people, I believe there is absolutely a future. Not only are we not going to be killed, we may well have more opportunities ahead of us than before.

NocoBase used to live only inside the no-code crowd, and that crowd was very small. Today, NocoBase has also started attracting attention from AI users. More and more enterprises want to bring AI capability into real business operations. As long as we avoid end-state thinking, and do not assume that the leading model companies are capable of doing everything across every industry, every scenario, and every link in the chain, we will see how diverse enterprise demand really is. On the road to adopting AI, companies will need all kinds of infrastructure layers, along with the services that make them usable.

From that point of view, I believe some programmers, and some kinds of software, have a better future ahead of them than they did before.

Final Note

NocoBase 2.1 was released last week. Try connecting your AI agent to NocoBase and experience it for yourself.

GitHub: https://github.com/nocobase/nocobase

Announcing NocoBase 2.1.0

NocoBase — Mon, 15 Jun 2026 14:20:52 +0000

Originally published at https://www.nocobase.com/en/blog/2.1.0

NocoBase 2.1 is a major upgrade to AI capabilities, multi-app, and 2.0 adaptation. We've introduced the NocoBase CLI, making it easy for both people and AI Agents to connect to and manage NocoBase applications. From creating applications and AI-assisted building to enhanced AI Employees and an AI development plugin, it covers the full flow from environment onboarding to system building and business collaboration. We've also enhanced multi-app capabilities to make interaction and collaboration across apps easier. At the same time, we've added version control and continued to substantially round out 2.0 page support and core capabilities — more blocks, fields, actions, and plugins now support 2.0.

What's New

Introducing the NocoBase CLI

In this release, the NocoBase CLI (nb) is the core entry point for both regular users and AI Agents to connect to NocoBase.

The CLI is used to initialize, connect, and manage NocoBase applications in a local workspace. It covers several scenarios:

Install a new NocoBase application via Docker, npm, or Git, then save it as a CLI env
Connect to an existing NocoBase application and save it as a CLI env
Install, create, and activate plugins
Operate, back up, and manage NocoBase applications

Whether you want to plug AI into an existing system or spin up a new application from scratch, you can handle initialization and ongoing management through the CLI.

For teams, the CLI provides a standard entry point that AI Agents can understand and operate on — environment initialization, connection configuration, and runtime management all share the same flow.

The official release also adds a set of operations-related commands:

nb api: Call the NocoBase API through the CLI.
nb app: Manage application runtime state: start, stop, restart, logs, and upgrade.
nb backup: Create a backup and download it locally, or restore a local backup file to a target env.
nb config: Manage CLI default configuration.
nb db: Manage the built-in database of the selected env.
nb env: Manage NocoBase project environments, the current env, status, details, and runtime commands.
nb license: Manage commercial licenses and licensed plugins.
nb plugin: Manage plugins of the selected NocoBase env.
nb scaffold: Generate a NocoBase plugin development scaffold.
nb self: Check or update the NocoBase CLI itself.
nb source: Manage local source projects: download, develop, build, and test.

Related documentation:

AI-assisted building: replace manual configuration with conversation

AI-assisted building is one of the core experiences in this release. You can describe your business needs in natural language, and the AI helps complete data modeling, page configuration, permission setup, and workflow orchestration.

Compared with traditional low-code building, AI-assisted building has several clear advantages:

A lower barrier to entry — you don't need to be familiar with every configuration concept up front
A shorter path from requirement description to working prototype
Data, UI, and workflow configuration can be completed by the AI continuously

For example: "design a CRM data model for me", "create a customer management page for me", or "orchestrate a workflow that automatically deducts inventory after an order is created" — all of these can be handled by the AI within the scope of NocoBase's capabilities.

Related documentation:

AI-assisted building quick start

NocoBase Skills cover the full building flow

To help the AI truly understand NocoBase's configuration system, this release ships a set of domain knowledge packs that can be installed into AI Agents — NocoBase Skills.

Skills are standardized knowledge and operation wrappers organized around NocoBase's key capability domains, helping the AI more accurately understand object models, configuration structures, and execution boundaries.

We currently provide 8 Skills that cover the full building flow:

Environment management — environment checks, install/deploy, upgrade, and troubleshooting
Data modeling — create and manage tables, fields, and relations
UI building — create and edit pages, blocks, popups, and interaction reactions
Workflow management — create, edit, enable, and diagnose workflows
Permission configuration — manage roles, permission policies, user bindings, and risk assessment
Solutions — bulk-build entire business systems from YAML (still in beta, with limited stability)
Plugin management — view, enable, and disable plugins
Publish management — cross-environment publishing, backup/restore, and migration

With Skills, the AI can more accurately understand NocoBase's configuration system and provide smarter assistance when building and managing systems.

Note: NocoBase Skills are still being actively improved. NocoBase Skills are also installed automatically when you install and initialize the NocoBase CLI, so in most cases you don't need to install them separately.

Related documentation:

NocoBase Skills

AI development plugin

This release fills in the foundational capabilities needed for AI plugin development, so the AI can take part not only in application building but also in custom plugin development.

This shows up in three main areas:

A unified rsbuild/rspack build pipeline, consolidating plugin development and the frontend build system
A client-v2 capability and /v/ routing system aimed at AI development, preparing for the next-generation client plugin development
AI plugin development Skills that help the AI better understand plugin structure, code organization, and implementation patterns

Preparation around client-v2 includes:

@nocobase/app exposes the client-v2 entry
The kernel ships a @nocobase/client-v2 package with base components, utilities, and type definitions
Each plugin gets a /src/client-v2 directory
A new /v/ route is added — still being actively improved, available for early adopters
The kernel is gradually migrating to V2
Plugins are gradually migrating to V2

A unified build pipeline lowers the cost of frontend plugin development and debugging. The gradual rollout of client-v2 also gives the AI a more stable target structure for generating and maintaining plugin code.

In practice: you can describe a plugin requirement in natural language, and the AI helps generate the frontend and backend code, data tables, APIs, permission configuration, and i18n content.

Note: AI plugin development is only for client-v2-style new plugins. We will follow up with migration documentation and Skills for moving from client-v1 plugins to client-v2, to help you bring existing plugins into the new system.

Related documentation:

AI Employees enhancements

AI-assisted building answers "how do I use AI to build a system"; AI Employees answer "how do I let AI work inside the system to solve concrete business problems".

AI Employees existed in earlier releases, but in this release the related capabilities have been enhanced and the AI kernel has been rounded out:

MCP support
New AI Employee Atlas, playing a team-leader role and dispatching other AI Employees to complete tasks based on user intent
AI Employee workflow node
LLM-based web search tool
New aggregation query tool and report generation tool for producing business analysis reports
New localization engineer Lina, a built-in AI Employee from the localization plugin used for system localization translation, supporting incremental, selected, and full translation scopes

These improvements take AI Employees' extensibility, orchestration, and execution capabilities inside business systems to the next level. AI Employees can understand the current business context, invoke skills to execute specific tasks, participate in automated workflows, and combine external information to deliver analysis and output.

The official release also adds support for AI Employees to load files from workflow attachment fields and to handle multiple conversations in parallel, further improving the usability of AI Employees in real business processes.

Related documentation:

Version control

Version control helps you better manage your application's version iterations and change history. You can create, view, and restore different versions of an application, making it easy to switch versions and recover from issues during development and operations. Note: This feature requires the Professional edition or above.

Related documentation:

Multi-app enhancements

In this release, we have made some important enhancements to multi-app deployments, mainly in three areas:

New app block and app switcher, which let you surface entry points to other sub-applications on a page, making it easy for users to switch between the main app and sub-apps.

New app single sign-on. When a user enters a sub-app from the main app, or switches between sub-apps, the system attempts to automatically sign them in to the target sub-app using the currently logged-in user. Users no longer need to re-enter their credentials in each sub-app.

Calling sub-app APIs. In multi-app scenarios, each sub-app has its own independent API, distinguished by path prefix, parameters, and so on, making it easy to call a sub-app's API.

These enhancements are very practical for users running multi-app deployments, making it easier to exchange data and operate across multiple applications and improving the overall collaboration efficiency of multi-app systems.

Related documentation:

Workflow enhancements

This release enhances the controllability and observability of workflows:

Added timeout control — workflows that run too long are automatically terminated (subflows also support timeout configuration)
Added created-by and updated-by fields
Added a log field to node jobs, making it easier to view node logs while debugging
The Webhook trigger (synchronous mode) returns a 408 response status on timeout

Related documentation:

Workflow

Handwritten signature field

Added a handwritten signature field that lets you draw and save a signature in a form, suitable for approvals, confirmation sheets, receipts, and similar scenarios.

Related documentation:

Handwritten signature field

JS Item action

Added the JS Item action, which lets you run custom logic in an action by writing JS, working together with event flows to meet more flexible interaction needs.

Related documentation:

JS Item action

2.0 adaptation and new features

Beyond AI, this release continues to migrate key feature modules to 2.0, while also rolling out new features for real-world business scenarios.

New features

2.0 adaptation

Multilingual documentation

Added Indonesian and Vietnamese documentation

14 Open Source AI Agent Tools with the Most GitHub Stars

NocoBase — Fri, 12 Jun 2026 17:36:21 +0000

Originally published at https://www.nocobase.com/en/blog/github-open-source-ai-agent-tools-16

Recently, we have published several recommendation articles about open source AI Agent projects, and they have received attention, saves, and feedback from many developers. Many readers also mentioned that they would like to see more roundups of AI Agent tools across different directions and use cases.

In Reddit’s AI Agent community, developers have raised similar questions: there are more and more AI Agent tools and frameworks, but the hard part is figuring out which projects are suitable for real use cases and which ones are mostly hype.

This time, we focus on GitHub’s official ai-agent topic. We selected projects from the most-starred results and organized them in the order they appear on the topic page. Since the projects under this topic cover a wide range of types, we excluded some projects that are only loosely related to AI Agent tools, are too vertical in use case, or are closer to resource collections or single-purpose content generation. In the end, we selected 14 open source projects that are more suitable for this article.

AI Agent-related projects cover a broad range of areas, so ranking purely by Star count does not fully explain their practical value. Therefore, this article first lists the basic information for each project, including official website, GitHub repository, Star count, and more. Then, each project is introduced from two angles:

Positioning: What type of AI Agent tool it mainly is, whether it focuses more on personal productivity, development assistance, web automation, knowledge management, or enterprise business systems.
Use cases: What specific problems it is better suited to solve, and whether it is more suitable for individual developers, team collaboration, or implementation inside enterprises.

Below are the 14 open source AI Agent projects we selected. Before the detailed introduction, you can quickly scan their positioning through the table.

Rank	Tool	GitHub Stars	Positioning
14	NocoBase	22.7k	AI-powered no-code business systems
13	OpenCLI	24.1k	Website-to-CLI / browser automation
12	Agent-Reach	26.3k	AI Agent web access / information retrieval
11	Google Workspace CLI	27k	Productivity suite CLI / Agent Skills
10	AionUi	28.1k	Local AI coworking workspace / multi-Agent management
9	OpenClaude	28.6k	AI Coding Agent / CLI tool
8	CopilotKit	34.7k	Agent frontend framework / Generative UI
7	Nanobot	44.1k	Lightweight AI Agent
6	Siyuan	44.4k	Self-hosted knowledge management / personal knowledge base
5	CowAgent	45.2k	AI Assistant / Agent Harness
4	Cherry Studio	47.2k	AI Productivity Studio
3	career-ops	52.7k	AI job search automation system
2	learn-claude-code	66.1k	Claude Code-like Agent Harness
1	Hermes Agent	191k	General AI Agent / Agent Harness

14. NocoBase

Official website: https://www.nocobase.com

GitHub: https://github.com/nocobase/nocobase

GitHub Stars: 22.7k

Project introduction

NocoBase is an open source AI-powered no-code / low-code platform for quickly building enterprise internal business systems, admin panels, and business applications that need continuous iteration.

As AI Agents gradually enter both development and business scenarios, enterprises need more than single-task automation. They need a system environment that can support data, permissions, pages, workflows, and activity logs. This is exactly the foundation NocoBase provides.

In NocoBase, AI can participate in application building. Users can describe business requirements in natural language, and AI can help create data models, configure pages, orchestrate workflows, and even assist with plugin development. After the system is generated, teams can continue checking and adjusting fields, relationships, pages, permissions, and workflows through the no-code interface.

NocoBase also supports configuring AI Employees inside business systems. AI Employees can work with page data, business context, tools, and knowledge bases to handle data analysis, content summaries, report generation, translation, unstructured content extraction, form filling, workflow node processing, and more. In this way, AI does not only help build the system. It can also continue participating in system operations.

Suitable scenarios

NocoBase is suitable for building enterprise internal systems that require data models, permission control, workflow orchestration, and long-term maintenance, especially in the following scenarios:

Enterprise internal business systems: CRM customer management, approval systems, ticketing systems, project management systems, operations backends, admin backends, and more.

Lightweight ERP and business management modules: procurement management, inventory management, order management, equipment management, asset management, archive management, customer follow-up, and more.
Extension and enhancement of existing systems: For enterprises that already have databases, ERP, CRM, or other business systems, NocoBase can help integrate data, configure pages, manage permissions, and orchestrate workflows.
A foundation for AI Agents to enter business workflows: NocoBase provides AI Agents with a clear business system environment, where business data has models, user operations have permissions, workflow transitions have rules, and later maintenance can continue through no-code configuration and plugin extensions.

🔎Related resources:

CLI: https://docs.nocobase.com/en/api/cli/

Skills: https://docs.nocobase.com/en/ai-builder#nocobase-skills

MCP: https://docs.nocobase.com/en/ai/mcp/

Official solution library: https://www.nocobase.com/en/solutions

13. OpenCLI

Official website: https://opencli.info

GitHub: https://github.com/jackwener/OpenCLI

GitHub Stars: 24.1k

Project introduction

OpenCLI converts websites, browser sessions, Electron apps, and local tools into CLI interfaces. Operations that originally required graphical interfaces can be wrapped as commands, allowing humans or AI Agents to call web capabilities, reuse logged-in browser sessions, and perform automated actions such as navigation, clicking, form filling, and data extraction.

Suitable scenarios

OpenCLI is suitable for scenarios where tasks need to be completed through webpages but no standard API is available:

Web automation: Read backend pages, query information, fill out forms, and extract platform data.
Agent tool interface: Wrap browser sessions and web capabilities as commands that AI Agents can call.

12. Agent-Reach

GitHub: https://github.com/Panniantong/Agent-Reach

GitHub Stars: 26.3k

Project introduction

Agent-Reach focuses on external information access for AI Agents. Through a CLI tool, it allows Agents to read and search content from platforms such as Twitter, Reddit, YouTube, GitHub, Bilibili, and Xiaohongshu, solving the access problem in information retrieval, content reading, and cross-platform research.

Suitable scenarios

Agent-Reach can be used for technology trend tracking, competitor research, social media sentiment analysis, content topic research, GitHub project organization, and cross-platform material collection. It is not a complete Agent platform by itself. Instead, it adds external information access capabilities to Agents, giving later analysis, summarization, and organization a richer information base.

11. Google Workspace CLI

GitHub: https://github.com/googleworkspace/cli

GitHub Stars: 27k

Project introduction

Google Workspace CLI is a command-line tool for Google Workspace. It covers Drive, Gmail, Calendar, Sheets, Docs, Chat, Admin, and more. Through command-line operations and structured JSON output, it turns capabilities scattered across different productivity apps into interfaces that are easier to call.

Suitable scenarios

For teams that heavily use Google Workspace, this type of tool makes it easier for AI Agents to enter daily office workflows, such as reading emails, managing calendars, organizing Drive files, operating Sheets, generating Docs, or processing Chat messages. Since it involves workplace data and account authorization, actual use should pay special attention to OAuth scopes, access boundaries, and data security.

🔎Related resources:

Agent Skills: https://github.com/googleworkspace/cli/blob/main/docs/skills.md

10. AionUi

Official website: https://www.aionui.com

GitHub: https://github.com/iOfficeAI/AionUi

GitHub Stars: 28.1k

Project introduction

AionUi is a local open source AI coworking app for AI CLI tools such as OpenClaw, Hermes Agent, Claude Code, Codex, OpenCode, and Gemini CLI. It provides built-in Agents, multi-Agent management, remote access, cross-platform use, and automation tasks, making it more like a desktop workbench for managing AI Agents and local work in one place.

Suitable scenarios

AionUi is suitable for people who use multiple AI Coding or Agent tools at the same time:

Multi-Agent management: Manage tools such as Claude Code, Codex, Hermes Agent, OpenCode, and Gemini CLI in one place.
Local workbench: Handle local files, coding tasks, web operations, and remote access in one workspace, reducing the need to switch between multiple tools.

9. OpenClaude

Official website: https://openclaude.gitlawb.com

GitHub: https://github.com/Gitlawb/openclaude

GitHub Stars: 28.6k

Project introduction

OpenClaude is an open source AI Coding Agent CLI that supports both cloud and local model providers, including OpenAI-compatible APIs, Gemini, GitHub Models, Codex, Ollama, Atomic Chat, and more. It brings prompts, tools, agents, MCP, slash commands, and streaming output into a terminal-first workflow.

Suitable scenarios

OpenClaude is mainly used in terminal development environments, such as code explanation, file modification, test generation, refactoring suggestions, and tool calling. It is flexible, composable, and supports many model choices, but it also requires users to have some development experience and manage model configuration, execution permissions, and code change review themselves.

8. CopilotKit

Official website: https://docs.copilotkit.ai

GitHub: https://github.com/CopilotKit/CopilotKit

GitHub Stars: 34.7k

Project introduction

CopilotKit is a frontend framework for Agents and Generative UI, supporting React, Angular, mobile, Slack, and other interfaces and platforms. It helps developers build AI Copilots, Agent interactions, shared state, and human-AI collaboration workflows inside their own products, rather than providing a standalone application for end users.

Suitable scenarios

When a product needs to embed an AI Copilot into its interface, CopilotKit provides a relatively complete frontend foundation. For example, it can let AI understand the current page state, assist with form filling, trigger in-app actions, generate UI content, or participate in a business workflow. It is more of a development framework, suitable for teams building AI products, SaaS applications, or internal systems.

🔎Related resources:

Build with Agents: https://docs.showcase.copilotkit.ai/build-with-agents

7. Nanobot

Official website: https://nanobot.wiki

GitHub: https://github.com/HKUDS/nanobot

GitHub Stars: 44.1k

Project introduction

Nanobot is a lightweight open source personal AI Agent that emphasizes real user ownership. It keeps the Agent core relatively simple while providing WebUI, chat channels, tools, memory, MCP, model routing, automation, deployment, and other capabilities.

Suitable scenarios

It is suitable for individual developers, small teams, or users who want to build lightweight AI Agents:

Personal AI Agent: Connect to Telegram, Discord, Slack, Email, and other entry points to handle daily tasks and automation workflows.
Agent prototype development: Quickly build a runnable Agent with tools, memory, MCP, model routing, and WebUI.

6. SiYuan

Official website: https://b3log.org/siyuan

GitHub: https://github.com/siyuan-note/siyuan

GitHub Stars: 44.4k

Project introduction

SiYuan is a privacy-first, self-hosted, fully open source personal knowledge management tool written in TypeScript and Go. It supports block references, backlinks, Markdown WYSIWYG editing, embedded SQL queries, web clipping, PDF annotation, databases, flashcards, AI writing, Q&A, and more.

Suitable scenarios

In the AI Agent context, SiYuan can be understood as a layer of knowledge infrastructure rather than a typical Agent framework. It is mainly used for personal knowledge management, research material organization, team knowledge accumulation, and local-first knowledge base building. When users want AI to better read, organize, and reuse long-term knowledge, this type of structured knowledge environment becomes especially important.

5. CowAgent

Official website: https://cowagent.ai

GitHub: https://github.com/zhayujie/CowAgent

GitHub Stars: 45.2k

Project introduction

CowAgent is an open source AI Assistant and Agent Harness. It supports task planning, tool and Skills calling, memory and knowledge, self-evolution, multi-model access, and multi-channel access. It also builds on the foundation of chatgpt-on-wechat in IM access and personal assistant scenarios.

Suitable scenarios

CowAgent focuses on connecting AI Assistants to multiple entry points and tool environments, such as webpages, servers, personal computers, the WeChat ecosystem, and other IM platforms. It is not just a chatbot. Instead, it aims to become a long-running personal assistant or automation assistant through task planning, tool calling, memory, and Skills extensions.

4. Cherry Studio

Official website: https://cherryai.com

GitHub: https://github.com/CherryHQ/cherry-studio

GitHub Stars: 47.2k

Project introduction

Cherry Studio is an AI Productivity Studio that supports intelligent chat, Autonomous Agents, 300+ assistants, and unified access to multiple frontier large language models. It is closer to a complete AI workbench for centrally managing models, assistants, knowledge bases, and daily AI workflows.

Suitable scenarios

Cherry Studio is designed for high-frequency AI use in daily work:

Multi-model workbench: Manage different large language models, assistants, knowledge bases, and daily AI workflows in one place.
AI productivity tool: Use it for writing, material organization, knowledge base Q&A, Agent usage, and team collaboration.

3. career-ops

Official website: https://career-ops.org

GitHub: https://github.com/santifer/career-ops

GitHub Stars: 52.7k

Project introduction

career-ops is an AI job search automation system based on Claude Code. It can turn an AI Coding CLI into a job search management center for job evaluation, resume generation, job portal scanning, batch processing, interview preparation, and opportunity tracking.

Suitable scenarios

career-ops is highly vertical and mainly focuses on personal job search workflows. Its value is not only in providing a “job search tool,” but also in showing how AI Agents can enter a clearly defined workflow and break job filtering, material generation, opportunity tracking, interview preparation, and batch processing into executable task chains.

2. learn-claude-code

Official website: https://learn.shareai.run

GitHub: https://github.com/shareAI-lab/learn-claude-code

GitHub Stars: 66.1k

Project introduction

learn-claude-code is an open source project for learning Claude Code-like Agent Harnesses. Built around the idea that “Agent product = Model + Harness,” it explains tools, knowledge, observation, action interfaces, permission boundaries, context management, multi-Agent collaboration, and more.

Suitable scenarios

learn-claude-code is more like systematic learning material for developers, helping users understand the mechanisms behind AI Coding Agents. It covers agent loop, tool use, permissions, hooks, memory, task systems, MCP, and multi-agent collaboration. It is suitable for individual learning and can also serve as internal training material for teams building Agent engineering capabilities.

1. Hermes Agent

Official website: https://hermes-agent.nousresearch.com

GitHub: https://github.com/NousResearch/hermes-agent

GitHub Stars: 191k

Project introduction

Hermes Agent is a self-improving AI Agent built by Nous Research. It is officially described as “The agent that grows with you.” It emphasizes that Agents can create and improve skills during continuous use, record and search past conversations, and gradually understand users’ long-term preferences and context.

Suitable scenarios

Hermes Agent is suitable for Agent scenarios that require long-term operation, long-term memory, and Skills accumulation:

Self-hosted Agent: Build a personal or team Agent that can run continuously, record historical conversations, and reuse skills.
Long-term collaboration assistant: Through memory, skills, and tool calling, the Agent can gradually accumulate context and working methods across repeated use.

🔎Related resources:

Skills System: https://hermes-agent.nousresearch.com/docs/user-guide/features/skills Skills Catalog: https://github.com/NousResearch/hermes-agent/blob/main/website/docs/reference/skills-catalog.md

FAQ

Q1: How should I choose between these tools?

A: You can first identify what type of problem you want to solve. If you want to improve personal productivity, you can prioritize Cherry Studio, Nanobot, Hermes Agent, and SiYuan. If you are developing AI Agents or AI Copilots, you can look at OpenClaude, CopilotKit, and learn-claude-code. If you want Agents to call external tools and web capabilities, you can look at OpenCLI, Agent-Reach, and Google Workspace CLI. If you are building enterprise business systems and implementing workflows, NocoBase is worth focusing on.

Goal	Recommended tools
Build enterprise internal systems	NocoBase
Web automation and tool calling	OpenCLI, Agent-Reach
Office system automation	Google Workspace CLI
AI Coding / terminal Agent	OpenClaude, learn-claude-code
In-product AI Copilot	CopilotKit
Personal AI assistant	Nanobot, Hermes Agent, CowAgent
Multi-model workbench	Cherry Studio
Knowledge management	SiYuan
Vertical Agent application reference	career-ops

Q2: Can non-technical teams use these AI Agent tools?

Yes, but it depends on the type of tool.

Projects such as OpenCLI, Agent-Reach, Google Workspace CLI, OpenClaude, CopilotKit, and learn-claude-code are more like CLI tools, development frameworks, or Agent engineering learning materials. They require some technical foundation.

Tools such as Cherry Studio and SiYuan have friendlier interfaces and are easier for business users to get started with directly.

NocoBase sits between the two. Non-technical users can use systems and AI Employees that have already been built. Users with some technical background can better configure data models, pages, permissions, and workflows. With development resources, teams can also extend it more deeply through plugins, APIs, Skills, and MCP.

Q3: What should enterprises pay the most attention to when using AI Agents?

When enterprises use AI Agents, they should not focus only on model capabilities. They also need to consider data, permissions, workflows, and auditing. Once an Agent enters a business system, it may access customer data, order information, approval workflows, contract content, or internal documents. Clear boundaries are required.

Key issue	Capabilities to focus on
Is data controllable?	Self-hosting, database permissions, data access scope
Are operations traceable?	Audit logs, activity logs, workflow records
Are permissions clear?	Role permissions, field permissions, data scope control
Do key actions require confirmation?	Human confirmation nodes, approval workflows, trigger conditions
Is Agent output stable?	Structured output, retry mechanisms, human review

The value of business system platforms such as NocoBase is that they place AI inside a system environment with permissions, workflows, and data models, rather than letting Agents directly face scattered data and uncontrolled operations. For scenarios such as approvals, customer service, data entry, and report generation, human confirmation and audit records remain very important.

Q4: Can multiple tools be combined?

Yes. The AI Agent ecosystem cannot be covered by a single tool. Many teams use different tools at different layers: some are responsible for building systems, some for calling webpages, some for writing code, some for knowledge management, and some for frontend AI interaction.

Combination scenario	Reference combination
Business system + AI Employee	NocoBase + AI Employee
Business system + external Coding Agent	NocoBase + Claude Code / Codex / OpenCode
Web operation + information organization	OpenCLI + Agent-Reach
In-product AI Copilot	CopilotKit + business system API
Knowledge base + Agent	SiYuan + Nanobot / Hermes Agent
Multi-model daily workbench	Cherry Studio + various model services

Conclusion

AI Agent tools are rapidly branching into different directions. Some tools focus on model calling and task execution, some focus on web automation and external information access, some focus on AI Coding and Agent Harnesses, and some are beginning to enter enterprise business systems and long-term process management.

For individual users, it is better to start with lightweight scenarios such as knowledge management, personal assistants, AI Coding, or browser automation. For enterprise teams, the more important question is whether an Agent can enter real business workflows and run stably under the constraints of data, permissions, workflows, and audit mechanisms.

If this article is helpful to you, feel free to share it with friends who are following open source AI Agent tools, AI automation, and enterprise internal system building.

Related reading:

Top 8 Open Source AI Assistant Tools by GitHub Stars

NocoBase — Wed, 10 Jun 2026 15:58:18 +0000

Originally published at https://www.nocobase.com/en/blog/top-open-source-ai-assistant-tools-github-stars

Over the past few weeks, we have organized several open source tools that work well with popular AI Agents:

💡After using Claude Code, you need these 6 open source tools

💡Do not let Codex generate apps from scratch: 6 composable open source projects

Recently, while browsing Reddit, we noticed that besides AI Agents, AI Assistants are still a topic many users actively discuss. Compared with Agents, which emphasize autonomous planning and task execution, Assistants are more like everyday work entry points. They can serve individuals, small teams, and enterprises.

In a discussion on r/AI_Agents, one user was looking for a personal AI Assistant that is actually worth using long term. They hoped it could help manage daily information such as notes, tasks, calendars, emails, reminders, and contacts.

Another discussion was more focused on enterprise and team scenarios. The user runs a service agency and needs to handle website content, emails, and social media work for small business clients, so they wanted to know which AI Assistants or AI tools would fit their needs.

From these discussions, we can see that AI Assistant needs roughly fall into two categories: personal use and enterprise or team use.

Personal AI Assistants: mainly help individual users manage daily information and improve productivity, such as organizing notes, following up on tasks, managing calendars, processing emails, setting reminders, calling local tools, or providing support in desktop and development environments.

Enterprise AI Assistants: better suited for teams and enterprises. They can connect to business systems, be embedded into application interfaces, handle customer communication, support content operations, automate workflows, and provide support around data, permissions, and task collaboration.

Based on this idea, we collected high-star projects ranked near the top under GitHub’s ai-assistant topic and selected 8 open source projects that are worth introducing in more detail.

Below, we will review them in two categories: enterprise AI Assistants and personal AI Assistants. Since personal AI Assistants usually have more direct use cases around desktops, development tools, and daily productivity, while enterprise AI Assistants often involve business systems, permission workflows, data management, application embedding, and team collaboration, this article will focus more on enterprise AI Assistants.

Category	Project	GitHub Stars	Positioning
Enterprise AI Assistant	NocoBase	22.7k	AI-powered no-code platform for building and maintaining business systems
Enterprise AI Assistant	NanoClaw	29.8k	AI Assistant with chat-based entry points and containerized runtime
Enterprise AI Assistant	CopilotKit	34.3k	Frontend framework for in-app AI Copilots and generative UI
Enterprise AI Assistant	Ruflo	58.6k	Multi-Agent collaboration and automation workflow assistant
Personal AI Assistant	DeepChat	6k	Desktop assistant that connects models, tools, and personal context
Personal AI Assistant	Everywhere	6k	Desktop context-aware AI Assistant
Personal AI Assistant	CopilotForXcode	6.1k	AI coding assistant for Xcode
Personal AI Assistant	Leon	17.3k	Open source personal AI Assistant

Enterprise AI Assistant

NocoBase

Website: https://www.nocobase.com/

Online Demo: https://demo.nocobase.com/new

Documentation: https://docs.nocobase.com/

GitHub: https://github.com/nocobase/nocobase

Stars: 22.7k

Introduction

NocoBase is an open source AI-powered no-code platform for quickly building enterprise internal business systems. In NocoBase, users can describe business requirements in natural language and let AI help with data model design, page configuration, workflow orchestration, permission setup, plugin management, and more. NocoBase also supports AI Employees, AI Skills, CLI, and other capabilities, allowing AI to continue working around existing business systems instead of stopping at one-off app generation.

This is especially important for enterprise internal systems. Many business applications are not finished after being generated once. They often need continuous adjustments to fields, permissions, workflows, pages, and data relationships. The value of NocoBase is that it provides AI with a structured system environment, allowing AI to work within existing data models, permissions, workflows, and plugin systems.

Core features

AI participates in business system building

NocoBase supports describing business requirements in natural language and letting AI help with the initial creation of data tables, fields, relationships, pages, and workflows. For example, users can describe a customer management, ticket management, contract approval, or project dashboard scenario. AI can first generate the system foundation, and the team can then review and adjust it.

This approach is better suited for enterprise internal systems, because business systems usually require clear data structures, role permissions, and workflow rules. AI improves building efficiency, while humans confirm business logic and control system boundaries.

🔎Related resources:

CLI: https://docs.nocobase.com/en/api/cli/

Skills: https://docs.nocobase.com/en/ai-builder#nocobase-skills

MCP: https://docs.nocobase.com/en/ai/mcp/

AI Employees can continue participating in system operations

NocoBase’s AI Employees can automatically use page data and structure as context, understand business scenarios, and directly execute tasks. They can summarize emails, analyze data, organize unstructured content and automatically fill forms, design data models, and even write JavaScript code. Each AI Employee has independent Skills, tools, and knowledge bases. Enterprises can create any number of AI Employees to build their own AI team.

No-code capabilities reduce later maintenance costs

Many AI generation tools can quickly generate code, but later maintenance often depends on developers. NocoBase is different. After AI generates the system, users can still enter the no-code interface to continue modifying fields, pages, menus, action buttons, permissions, and workflows.

For business teams, this means the system does not remain a one-off demo. Whenever the business changes, teams can continue adjusting it inside the platform, without needing to return to the code development process every time.

Suitable for enterprise-level data, permissions, and workflows

When enterprise AI Assistants are actually implemented, data, permissions, and workflows are unavoidable. NocoBase has capabilities such as data models, role permissions, workflows, plugin extensions, and multiple data sources, making it a strong foundation for AI Assistants to work inside business systems.

For example, AI can work around business objects such as customers, orders, tickets, projects, inventory, and contracts. At the same time, different roles can have different data access scopes and operation permissions, preventing everyone from seeing the same information or performing the same actions.

Suitable for starting from specific scenarios

When using NocoBase, it is not recommended to ask AI to build a complete ERP or complex enterprise system from the beginning. A better approach is to start with a clear small scenario, such as customer management, purchase requests, equipment ledgers, after-sales tickets, contract approval, project dashboards, or inventory records.

After one specific scenario works well, you can gradually expand fields, pages, workflows, and permissions. This makes it easier for AI-generated results to match the business and makes later review and maintenance easier for the team.

Suitable scenarios

CRM customer management system
Approval systems
Ticketing systems
Project management systems
Lightweight ERP modules such as procurement, inventory, and orders
Operations backends and admin backends
Equipment management, asset management, and archive management
Customer follow-up and service management
Enterprise internal systems that require private deployment
Business applications that require permissions, workflows, data models, and continuous adjustment
Teams that want to combine AI and no-code capabilities to build internal systems

NanoClaw

GitHub: https://github.com/nanocoai/nanoclaw

Official website: https://nanoclaw.dev

Stars: 29.8k

Introduction

NanoClaw is a lightweight AI Assistant project focused on running Agents in containers and connecting to messaging channels such as WhatsApp, Telegram, Slack, Discord, and Gmail. It is more like an enterprise-focused AI Assistant with chat-based entry points and container isolation, making it suitable for users who want to call Agents, handle tasks, and arrange automation workflows through chat tools.

Compared with ordinary chat assistants, NanoClaw places more emphasis on security isolation and controllable runtime environments. Each Agent can run in an independent container, reducing its impact on the host system and other tasks.

Core features

Containerized runtime: Agents run in independent containers, making it easier to isolate the file system and runtime environment.
Rich messaging channels: Supports Telegram, Discord, WhatsApp, Slack, Gmail, and other entry points, making it suitable for connecting AI Assistants to daily collaboration tools.
Lightweight and customizable: Compared with large Agent systems, NanoClaw emphasizes clear code structure, easy understanding, and convenient customization.

Suitable scenarios

Calling AI Assistants through messaging tools such as Telegram, Discord, and Slack.
Building a self-hosted task processing entry point for individuals or teams.
Running Agent tasks in a safer and isolated environment.

CopilotKit

GitHub: https://github.com/CopilotKit/CopilotKit

Official website: https://docs.copilotkit.ai

Stars: 34.4k

Introduction

CopilotKit is a frontend framework for building AI Copilots, generative UI, and Agent applications. It is better understood as a development framework for in-app AI Assistants. It can embed Agent capabilities into interfaces users already use, such as Web, mobile apps, Slack, and Teams.

Its focus is not only providing a chat window. It also supports generative UI, shared state, and human confirmation workflows, making it suitable for teams that need to deeply integrate AI Assistants into product interactions.

Core features

In-app Copilot: Embed AI Assistants directly into existing applications, instead of asking users to switch to a separate chat tool.
Generative UI: Agents can generate or update UI components based on task status and user intent.
Human confirmation workflows: Supports human-in-the-loop, allowing users to confirm, modify, or take over tasks at key steps.

Suitable scenarios

Embedding an AI Copilot into SaaS products.
Building AI Assistants that can read application state, call tools, and generate interfaces.
Teams that need to integrate Agent workflows into Slack, Teams, or Web applications.

Ruflo

GitHub: https://github.com/ruvnet/ruflo

Official website: https://flo.ruv.io

Stars: 58.6k

Introduction

Ruflo is a multi-Agent collaboration platform for Claude Code and Codex, used to coordinate multiple specialized Agents, automated workflows, and team-level tasks. It is more like the Agent collaboration foundation behind enterprise AI Assistants, and is suitable for complex development, testing, security, documentation, architecture, and DevOps scenarios.

Its core value is expanding the capability of a single Agent into multi-Agent collaboration, allowing tasks to be split, routed, executed, and remembered.

Core features

Multi-Agent collaboration: Supports multiple specialized Agents working together on development, testing, security, documentation, and other tasks.
Designed for complex workflows: Can work with Claude Code / Codex to handle coding, testing, auditing, documentation generation, and other workflows.
Plugin and memory capabilities: Provides a plugin system, vector memory, and task coordination capabilities, making it suitable for more complex Agent working environments.

Suitable scenarios

Multiple Agents need to collaborate on development tasks.
Teams want to automate code review, test generation, documentation maintenance, security scanning, and similar workflows.
Teams need to extend more complex Agent collaboration capabilities on top of Claude Code or Codex.

Personal AI Assistant

DeepChat

GitHub: https://github.com/ThinkInAIXYZ/deepchat

Official website: https://deepchat.thinkinai.xyz

Stars: 6k

Introduction

DeepChat is an open source desktop AI Assistant platform that supports multiple cloud and local large language models, and integrates MCP tool calling, Skills, ACP Agent integration, and remote control capabilities. It is more like a desktop assistant that connects models, tools, and personal context.

For individual users, DeepChat’s advantage is that it brings multi-model chat, local models, tool calling, search enhancement, and skill workflows into one desktop application.

Core features

Unified multi-model management: Supports multiple model providers, including OpenAI, Gemini, Anthropic, DeepSeek, and Ollama.
Tool and skill support: Built-in MCP, Skills, and ACP Agent integrations can extend task capabilities for code review, document processing, PDFs, PPTs, spreadsheets, and more.
Remote control: Supports controlling DeepChat sessions through Telegram, Feishu, QQBot, Discord, WeChat iLink, and other channels.

Everywhere

GitHub: https://github.com/Sylinko/Everywhere

Official website: https://everywhere.sylinko.com

Stars: 6k

Introduction

Everywhere is a desktop AI Assistant focused on screen context awareness and contextual understanding. It can perceive the current application and screen content, allowing users to call AI for help in the current work environment without frequently taking screenshots, copying content, or switching windows.

It is more like a desktop context-aware assistant, suitable for individual users when reading, translating, troubleshooting, summarizing, and working across applications.

Core features

Screen context awareness: Understands the current screen and application environment, reducing copy-paste and window switching.
Quick invocation: Uses shortcuts to call the AI Assistant in the current scenario, making it closer to desktop workflows.
Supports multiple models and MCP tools: Can combine different LLMs and MCP tools to complete more operations in the desktop environment.

GitHub Copilot for Xcode

GitHub: https://github.com/github/CopilotForXcode

Official website: https://github.com/github/CopilotForXcode

Stars: 6.1k

Introduction

GitHub Copilot for Xcode is an AI coding assistant for Xcode, mainly serving Swift, Objective-C, iOS, and macOS development scenarios. It is more like a developer assistant embedded directly into Xcode, providing code completion, chat, code review, Agent Mode, and other capabilities.

For developers in the Apple ecosystem, its value is bringing AI programming assistance into the native development environment and reducing the need to switch back and forth between Xcode and other AI tools.

Core features

Native Xcode integration: Built for Swift, Objective-C, iOS, and macOS development, and used directly in Xcode.
Code completion and chat: Supports code suggestions, Copilot Chat, code review, and other features.
Agent Mode: Can understand and modify codebases, search related files, create files, and run MCP tools.

Leon

GitHub: https://github.com/leon-ai/leon

Official website: https://getleon.ai

Stars: 17.3k

Introduction

Leon is an open source personal AI Assistant built around tools, context, memory, and Agent-style execution. It is more like a personal assistant that can run locally or on a server, suitable for users who value privacy, control, and extensibility.

Compared with ordinary chat assistants, Leon emphasizes completing tasks through real tools and combining memory with context, making its answers and actions closer to the user’s real environment.

Core features

Clear personal assistant positioning: Designed for personal tasks, voice, automation, memory, and local environments.
Supports tools, skills, and memory: Can use local tools, skills, and hierarchical memory to complete more specific tasks.
Balances local and remote models: Supports local and remote AI providers, making it easier to choose between privacy and capability.

FAQ

1. What should you consider when choosing an open source AI Assistant?

When choosing an open source AI Assistant, you can focus on five aspects: whether the project is actively maintained, whether it supports your use case, whether it can connect to existing tools or systems, whether it supports self-hosting or private deployment, and whether it has clear documentation and an active community.

Individual users can prioritize ease of use, model support, local tool calling, and desktop experience. Enterprise users should focus more on permissions, data structures, workflow automation, system integration, and long-term maintenance capabilities.

2. If I want to build internal business systems for an enterprise, which AI Assistant project should I choose?

If your goal is to build enterprise internal business systems such as CRM, approval systems, ticketing systems, project management, inventory management, and operations backends, you can look at NocoBase first.

NocoBase is better suited for supporting enterprise business data, permissions, workflows, and page configuration. It can not only help build systems with AI, but also continue adjusting fields, pages, permissions, and workflows through a no-code interface after generation. For enterprise internal systems that require long-term maintenance, this type of structured platform is more reliable.

3. If I only need a desktop AI Assistant for personal use, which one should I choose?

If you mainly use it personally and want to use multiple models, process files, call tools, and organize information from one desktop app, you can first look at DeepChat or Everywhere.

DeepChat is better suited for bringing multiple models, MCP, Skills, and remote control capabilities into one desktop application. Everywhere emphasizes screen context awareness and contextual understanding, making it suitable for reading, translating, troubleshooting, and summarizing webpages or documents.

4. If I am a developer and want to use an AI Assistant inside development tools, which one should I choose?

If you are a developer in the Apple ecosystem and mainly use Xcode to build iOS, macOS, Swift, or Objective-C projects, you can look at GitHub Copilot for Xcode.

It is better suited as a developer assistant embedded directly into Xcode, providing code completion, chat, code review, Agent Mode, and other capabilities. If your needs lean more toward multi-Agent collaboration, code review, test generation, documentation maintenance, and DevOps workflows, you can also look at Ruflo.

5. If I want to embed an AI Assistant into my own product interface, which one should I choose?

If you are building a SaaS product, Web application, or internal product and want to embed an AI Assistant directly into the application interface, you can first look at CopilotKit.

CopilotKit is better suited for building in-app Copilots. It allows AI Assistants to read application state, call tools, generate interfaces, and add human confirmation workflows at key steps. For teams that want to add AI Copilots, generative UI, or Agent workflows to products, it is a better fit.

6. How should I choose if I want to build an open source personal AI Assistant?

Leon leans more toward the personal assistant direction and is suitable for personal tasks, voice interaction, tool calling, memory, and automation scenarios. It is suitable for users who value privacy, self-hosting, long-term memory, and extensibility. If you want an assistant that can gradually connect to your local environment and personal workflows, Leon is closer to that direction than a simple chat tool.

7. Is NocoBase only for enterprises? Can individual users use it?

NocoBase is not only for enterprises. Individual users can also use it to build their own management systems or knowledge bases. Its open source edition is free and friendly to individual users.

For example, individuals can use NocoBase to build knowledge bases, reading logs, task management systems, resource libraries, project dashboards, customer follow-up tables, content topic libraries, and other systems. As long as your needs involve data tables, fields, relationships, pages, and long-term organization, NocoBase can serve as a lightweight personal management platform.

⭐ If this article inspired you, feel free to share it with friends who are also interested in open source AI tools and productivity improvement.

Related reading