## Context
The previous WorkspaceAuthContext was a single interface with many
optional fields, making it unclear which fields are available in
different authentication scenarios. This made the code harder to reason
about and required runtime checks scattered throughout the codebase.
## Changes
- Introduced a discriminated union type for WorkspaceAuthContext with
four specific variants:
-> UserWorkspaceAuthContext - for authenticated users
-> ApiKeyWorkspaceAuthContext - for API key authentication
-> ApplicationWorkspaceAuthContext - for application-based auth
-> SystemWorkspaceAuthContext - for system/internal operations
- Added type guard functions (isUserAuthContext, isApiKeyAuthContext,
etc.) for safe type narrowing
- Added builder utilities (buildUserAuthContext, buildApiKeyAuthContext,
etc.) to construct each context variant with proper type safety
- Refactored WorkspaceAuthContextMiddleware to use the new builders
instead of constructing a loosely-typed object
- Moved the type definition from twenty-orm/interfaces/ to
core-modules/auth/types/ for better organization
- Updated all consumers across query runners, tool providers, and
modules to use the new type location
## Notes
- I had to query User and WorkspaceMember in some parts of tool module
that were expecting userWorkspaceId but not the rest of
UserWorkspaceAuthContext (that should be required with the new proper
type otherwise it would break a lot of logic and mostly permissions with
the newly added RLS -> This is what we expect from
UserWorkspaceAuthContext and how it's done in the "normal" path in HTTP
middleware)
- WorkspaceMember is in the cache already but ideally we should move
User (And Workspace?) in the cache as well to avoid querying the DB
after each request (this is also valid for HTTP middleware when we
hydrate the Request object btw)
## Context
Introduces a middleware that automatically sets the workspace auth
context in AsyncLocalStorage for HTTP requests, making it available
throughout the request lifecycle without explicit parameter passing.
The motivation behind this change is to reduce boilerplate and simplify
the developer experience when working with workspace data in HTTP
request handlers.
The Problem (Before)
Every HTTP request handler that needed to access workspace data had to:
- Extract auth-related info from decorators (@AuthWorkspace(),
@AuthUserWorkspaceId(), etc.) in controller/resolver and pass down to
services
- Build or pass the authContext explicitly (sometimes with type
assertion which was flaky)
Then call executeInWorkspaceContext(authContext, async () => { ... })
## Changes
- Add WorkspaceAuthContextMiddleware that extracts auth context from the
request and stores it in AsyncLocalStorage
- Register middleware for GraphQL, metadata, and REST routes (runs after
hydration middlewares)
- Simplify executeInWorkspaceContext signature: fn is now the first
parameter, authContext is optional second
- If authContext is not provided, it's automatically retrieved from the
storage (set by middleware)
- Update all callers (~120 files) to use the new parameter order
- Fixes a bug in search where system auth context was used, bypassing
RLS feature.
# Introduction
In this PR we're introducing mainly two branded type signatures for both
`JsonbProperty` entities properties and `SerializedRelation` (jsonb
serialized property storing another entity id).
Allowing to dynamically map over them later in order to build universal
`jsonb` `serialized` relations.
## `JsonbProperty`
A branded wrapper type that marks entity properties stored as PostgreSQL
JSONB columns. It adds a phantom brand `__JsonbPropertyBrand__` to
object types while leaving primitives unchanged. The branded key is
optional and typed as never, also omitted when transpiled to
`UniversalFlat`
**Should be used at entities lvl only:**
```typescript
@Column({ type: 'jsonb', nullable: false })
gridPosition: JsonbProperty<GridPosition>;
@Column({ nullable: false, type: 'jsonb', default: [] })
publishedVersions: JsonbProperty<string[]>;
```
## `SerializedRelation`
A branded string type that marks foreign key IDs stored inside JSONB
objects. These are entity references serialized within a JSONB column
rather than being a regular database foreign key.
**Usage in jsonb property generic***
```ts
type FieldMetadataRelationSettings = {
relationType: RelationType;
onDelete?: RelationOnDeleteAction;
joinColumnName?: string | null;
junctionTargetFieldId?: SerializedRelation;
};
```
## `FormatJsonbSerializedRelation<T>`
A transformation type that processes JSONB properties for universal
entity mapping. It:
1. Detects properties with the `JsonbProperty` brand
2. Finds `SerializedRelation` properties
3. Renames them from `*Id` to `*UniversalIdentifier`
4. Removes the brand from the output type ( optional though )
```typescript
// Input: JsonbProperty<{ targetFieldMetadataId: SerializedRelation }>
// Output: { targetFieldMetadataUniversalIdentifier: SerializedRelation }
```
## Result
An example of the dynamic type mapping, through a type-test example
```ts
type SettingsTestCase = UniversalFlatFieldMetadata<
| FieldMetadataType.RELATION
| FieldMetadataType.NUMBER
| FieldMetadataType.TEXT
>['settings']
type SettingsExpectedResult =
| {
relationType: RelationType;
onDelete?: RelationOnDeleteAction | undefined;
joinColumnName?: string | null | undefined;
junctionTargetFieldUniversalIdentifier?: SerializedRelation | undefined;
}
| {
dataType?: NumberDataType | undefined;
decimals?: number | undefined;
type?: FieldNumberVariant | undefined;
}
| {
displayedMaxRows?: number | undefined;
}
| null;
type Assertions = [
Expect<Equal<SettingsTestCase, SettingsExpectedResult>>,
]
```
## Remarks
- Removed duplicated twenty-server and twenty-shared typed
- Removed class validator instances for default value that were not used
at runtime, we will refactor that to add validation across all entities
following a same pattern
# Introduction
Currently refactoring `flatEntity` typing, encountering some tsc errors
due to this fk aggregator custom override
It shall now follow generic pattern leading to be named `fieldIds`
Needs to flush object cache when released
## Summary
- The `createMany` API was returning records in arbitrary order because
`fetchUpsertedRecords` used `WHERE id IN (...)` without `ORDER BY`
- This caused flaky tests that assumed input order was preserved (e.g.,
`people-merge-many.integration-spec.ts`)
- Fixed by reordering the fetched records to match the original input
order from `generatedMaps`
## Root Cause
```typescript
// Before: No ORDER BY, so SQL returns in arbitrary order
const upsertedRecords = await queryBuilder
.where({ id: In(objectRecords.generatedMaps.map((record) => record.id)) })
.getMany(); // Returns in arbitrary order!
```
## Fix
```typescript
// After: Reorder results to match original input order
const orderedIds = objectRecords.generatedMaps.map((record) => record.id);
const upsertedRecords = await queryBuilder
.where({ id: In(orderedIds) })
.getMany();
// Preserve original input order
const recordsById = new Map(upsertedRecords.map((record) => [record.id, record]));
return orderedIds
.map((id) => recordsById.get(id))
.filter((record) => record !== undefined);
```
## Test plan
- [x] Run `people-merge-many.integration-spec.ts` multiple times -
passes consistently
- [x] Lint passes
In this PR :
- New field type FieldMetadataType.FILES added (as jsonb in DB)
- Backend: GraphQL types, validation, REST API schema, data processor
handling
- Frontend: field configuration in settings
- Feature flag IS_FILES_FIELD_ENABLED to gate the feature
- Integration tests for create/filter validation
- Dev seed: Feature flag enabled + FILES field on survey result object
To do in next PRs :
- Backend :
-- new workspaceFile controller (for download) & new workspaceFile
upload resolver (for upload)
-- pre-hook/post-hook to ensure fileId existence + listener to ensure
cleaning
- Frontend : FILES field display/edit in table view, record, ...
## Description
Fixes a bug where queries with relation field + scalar field ordering
would fail with:
```
column distinctAlias.person_position does not exist
```
## Root Cause
When a GraphQL query orders by columns that are **not in the selected
fields**, TypeORM's DISTINCT subquery fails because it expects those
columns in the inner SELECT with alias format (e.g., `person_position`).
The issue only manifests when:
1. A filter is applied (triggers DISTINCT path in TypeORM)
2. OrderBy includes columns NOT in the GraphQL selection
3. Example: query selects only `id`, but orders by `position`
## The Fix
`addRelationOrderColumnsToBuilder` now accepts `columnsToSelect` and
adds orderBy columns via `addSelect()` only if they're **NOT** already
in the selected columns:
- **Relation orderBy columns**: Always added (never in columnsToSelect)
- **Main entity orderBy columns**: Added only when not already selected
This ensures all orderBy columns are present in TypeORM's inner SELECT
for the DISTINCT subquery.
## Test Plan
Added integration test for the exact failing scenario:
- Filter with `neq` (triggers DISTINCT path)
- Multiple orderBy: relation field + scalar field
- Minimal field selection (only `id`, not `position`)
## Related
Regression introduced in #17021 which added nested sort support.
## Summary
This PR enables sorting records by fields of related objects. For
example, sorting **People by their Company's name**.
### Before
Only scalar and composite fields could be sorted. Relation fields showed
in the sort dropdown but produced errors.
### After
Many-to-One relation fields can now be sorted using the related object's
**label identifier field** (e.g., Company's `name`).
---
## Changes
### Frontend
- Added `RELATION` to sortable field types (restricted to `MANY_TO_ONE`
relations)
- New `getOrderByForRelationField()` generates nested orderBy structures
using the related object's label identifier
- Updated `turnSortsIntoOrderBy()` to handle relation fields by looking
up related object metadata
### Backend
- Extended `GraphqlQueryOrderFieldParser.parse()` to detect nested
relation ordering like `{ company: { name: 'AscNullsLast' } }`
- Returns `ParseOrderByResult` containing both `orderBy` conditions and
`relationJoins` info
- Added LEFT JOINs for relation ordering in `applyOrderToBuilder()`
- Added `addRelationOrderColumnsToBuilder()` for TypeORM DISTINCT
compatibility
### Tests
- Added unit tests for `filterSortableFieldMetadataItems`,
`getOrderByForRelationField`, and `turnSortsIntoOrderBy`
- Added integration tests covering ascending/descending order and
composite label identifiers
---
## TypeORM Bug Workaround
We encountered a significant TypeORM limitation when implementing this
feature. When using `getMany()` with `ORDER BY` on joined relation
columns, TypeORM generates a DISTINCT subquery that has specific
requirements:
### Issue 1: Alias Parsing
TypeORM's `orderBy()` method fails with **"alias not found"** when using
quoted SQL identifiers like `"company"."name"`. TypeORM internally
expects unquoted property paths (e.g., `company.name`) for its alias
resolution mechanism.
### Issue 2: setFindOptions Clears addSelect
`setFindOptions({ select })` **clears any previously added `addSelect()`
columns**. This caused `"column distinctAlias.company_name does not
exist"` errors because the relation columns needed for ORDER BY were
being removed.
### Solution
We split the logic into two methods:
1. `applyOrderToBuilder()` - adds JOINs and ORDER BY (before
`setFindOptions`)
2. `addRelationOrderColumnsToBuilder()` - adds relation columns for
SELECT (AFTER `setFindOptions`)
This ensures the relation columns are present in the final SQL query's
SELECT clause with the proper underscore aliases (`company_name`) that
TypeORM's DISTINCT subquery expects.
**Related TypeORM issue**:
https://github.com/typeorm/typeorm/issues/9921
---
## Screenshots/Demo
_Add screenshots if applicable_
## Context
This PR adds the core structure for RLS implementation:
- RLS data model
- RLS service layer
- RLS WorkspaceMigration and Syncable Entity + cache + Validations
- RLS resolver layer
- ORM layer with RLS Predicate to ORM WHERE clause conversion with
workspaceMember record transposition
Tests are missing though
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Establishes core row-level permissions infrastructure and enforcement
across the stack.
>
> - Backend: new `rowLevelPermissionPredicate` and
`rowLevelPermissionPredicateGroup` entities, TypeORM migration, feature
flag `IS_ROW_LEVEL_PERMISSION_PREDICATES_ENABLED`, flat-entity
maps/cache wiring, services and GraphQL resolvers for CRUD, and
inclusion of `workspaceMember` in auth context
> - ORM: applies row-level permission predicates to SELECT, DELETE, and
SOFT DELETE query builders; propagates context through
GlobalWorkspaceOrmManager/EntityManager
> - GraphQL: generated schema/types/queries/mutations for
creating/updating/deleting/fetching predicates and groups
> - Frontend: settings page adds a gated "Record-level" section
(placeholder) and metadata error handler labels for new entities
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
fe955cc4588a92157afa6795fb574189a4be1e93. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
---------
Co-authored-by: Félix Malfait <felix.malfait@gmail.com>
Two challenges with error messages
- always provide a useful/meaningful error message for the end user
instead of the generic one. eg: show "Wrong password" and not "An error
occured"
- avoid technical details unless error regards a technical feature. eg:
show "An error occured" and not "Invalid post-hook payload."; but do
show "Invalid issuer URL." as it occurs while configuring SSO
What this PR does
- Make userFriendlyMessage mandatory for widely used
GraphqlQueryRunnerException and CommonQueryRunnerException, so that
developers are forced to ask themselves what the error message should
be, and as it contains very wide error codes (eg: "Bad request") which
should not be mapped to just one default message
- Keep userFriendlyMessage optional for service-specific exceptions (eg:
workflowStepExecutorException), but convert the error code to
userFriendlyMessage mapper to a switch case function with a typecheck
ensuring that all codes are mapped to a message. These default messages
are still overridable where they are thrown.
Fixes https://github.com/twentyhq/twenty/issues/16110
This PR implements Temporal to replace the legacy Date object, in all
features that are time zone sensitive. (around 80% of the app)
Here we define a few utils to handle Temporal primitives and obtain an
easier DX for timezone manipulation, front end and back end.
This PR deactivates the usage of timezone from the graph configuration,
because for now it's always UTC and is not really relevant, let's handle
that later.
Workflows code and backend only code that don't take user input are
using UTC time zone, the affected utils have not been refactored yet
because this PR is big enough.
# New way of filtering on date intervals
As we'll progressively rollup Temporal everywhere in the codebase and
remove `Date` JS object everywhere possible, we'll use the way to filter
that is recommended by Temporal.
This way of filtering on date intervals involves half-open intervals,
and is the preferred way to avoid edge-cases with DST and smallest time
increment edge-case.
## Filtering endOfX with DST edge-cases
Some day-light save time shifts involve having no existing hour, or even
day on certain days, for example Samoa Islands have no 30th of December
2011 : https://www.timeanddate.com/news/time/samoa-dateline.html, it
jumps from 29th to 31st, so filtering on `< next period start` makes it
easier to let the date library handle the strict inferior comparison,
than filtering on `≤ end of period` and trying to compute manually the
end of the period.
For example for Samoa Islands, is end of day `2011-12-29T23:59:59.999`
or is it `2011-12-30T23:59:59.999` ? If you say I don't need to know and
compute it, because I want everything strictly before
`2011-12-29T00:00:00 + start of next day (according to the library which
knows those edge-cases)`, then you have a 100% deterministic way of
computing date intervals in any timezone, for any day of any year.
Of course the Samoa example is an extreme one, but more common ones
involve DST shifts of 1 hour, which are still problematic on certain
days of the year.
## Computing the exact _end of period_
Having an open interval filtering, with `[included - included]` instead
of half-open `[included - excluded)`, forces to compute the open end of
an interval, which often involves taking an arbitrary unit like minute,
second, microsecond or nanosecond, which will lead to edge-case of
unhandled values.
For example, let's say my code computes endOfDay by setting the time to
`23:59:59.999`, if another library, API, or anything else, ends up
giving me a date-time with another time precision `23:59:59.999999999`
(down to the nanosecond), then this date-time will be filtered out,
while it should not.
The good deterministic way to avoid 100% of those complex bugs is to
create a half-open filter :
`≥ start of period` to `< start of next period`
For example :
`≥ 2025-01-01T00:00:00` to `< 2025-01-02T00:00:00` instead of `≥
2025-01-01T00:00:00` to `≤ 2025-01-01T23:59:59.999`
Because, `2025-01-01T00:00:00` = `2025-01-01T00:00:00.000` =
`2025-01-01T00:00:00.000000` = `2025-01-01T00:00:00.000000000` => no
risk of error in computing start of period
But `2025-01-01T23:59:59` ≠ `2025-01-01T23:59:59.999` ≠
`2025-01-01T23:59:59.999999` ≠ `2025-01-01T23:59:59.999999999` =>
existing risk of error in computing end of period
This is why an half-open interval has no risk of error in computing a
date-time interval filter.
Here is a link to this debate :
https://github.com/tc39/proposal-temporal/issues/2568
> For this reason, we recommend not calculating the exact nanosecond at
the end of the day if it's not absolutely necessary. For example, if
it's needed for <= comparisons, we recommend just changing the
comparison code. So instead of <= zdtEndOfDay your code could be <
zdtStartOfNextDay which is easier to calculate and not subject to the
issue of not knowing which unit is the right one.
>
> [Justin Grant](https://github.com/justingrant), top contributor of
Temporal
## Application to our codebase
Applying this half-open filtering paradigm to our codebase means we
would have to rename `IS_AFTER` to `IS_AFTER_OR_EQUAL` and to keep
`IS_BEFORE` (or even `IS_STRICTLY_BEFORE`) to make this half-open
interval self-explanatory everywhere in the codebase, this will avoid
any confusion.
See the relevant issue :
https://github.com/twentyhq/core-team-issues/issues/2010
In the mean time, we'll keep this operand and add this semantic in the
naming everywhere possible.
## Example with a different user timezone
Example on a graph grouped by week in timezone Pacific/Samoa, on a
computer running on Europe/Paris :
<img width="342" height="511" alt="image"
src="https://github.com/user-attachments/assets/9e7d5121-ecc4-4233-835b-f59293fbd8c8"
/>
Then the associated data in the table view, with our **half-open
date-time filter** :
<img width="804" height="262" alt="image"
src="https://github.com/user-attachments/assets/28efe1d7-d2fc-4aec-b521-bada7f980447"
/>
And the associated SQL query result to see how DATE_TRUNC in Postgres
applies its internal start of week logic :
<img width="709" height="220" alt="image"
src="https://github.com/user-attachments/assets/4d0542e1-eaae-4b4b-afa9-5005f48ffdca"
/>
The associated SQL query without parameters to test in your SQL client :
```SQL
SELECT "opportunity"."closeDate" as "close_date", TO_CHAR(DATE_TRUNC('week', "opportunity"."closeDate", 'Pacific/Samoa') AT TIME ZONE 'Pacific/Samoa', 'YYYY-MM-DD') AS "DATE_TRUNC by week start in timezone Pacific/Samoa", "opportunity"."name" FROM "workspace_1wgvd1injqtife6y4rvfbu3h5"."opportunity" "opportunity" ORDER BY "opportunity"."closeDate" ASC NULLS LAST
```
# Date picker simplification (not in this PR)
Our DatePicker component, which is wrapping `react-datepicker` library
component, is now exposing plain dates as string instead of Date object.
The Date object is still used internally to manage the library
component, but since the date picker calendar is only manipulating plain
dates, there is no need to add timezone management to it, and no need to
expose a handleChange with Date object.
The timezone management relies on date time inputs now.
The modification has been made in a previous PR :
https://github.com/twentyhq/twenty/issues/15377 but it's good to
reference it here.
# Calendar feature refactor
Calendar feature has been refactored to rely on Temporal.PlainDate as
much as possible, while leaving some date-fns utils to avoid re-coding
them.
Since the trick is to use utils to convert back and from Date object in
exec env reliably, we can do it everywhere we need to interface legacy
Date object utils and Temporal related code.
## TimeZone is now shown on Calendar :
<img width="894" height="958" alt="image"
src="https://github.com/user-attachments/assets/231f8107-fad6-4786-b532-456692c20f1d"
/>
## Month picker has been refactored
<img width="503" height="266" alt="image"
src="https://github.com/user-attachments/assets/cb90bc34-6c4d-436d-93bc-4b6fb00de7f5"
/>
Since the days weren't useful, the picker has been refactored to remove
the days.
# Miscellaneous
- Fixed a bug with drag and drop edge-case with 2 items in a list.
# Improvements
## Lots of chained operations
It would be nice to create small utils to avoid repeated chained
operations, but that is how Temporal is designed, a very small set of
primitive operations that allow to compose everything needed. Maybe
we'll have wrappers on top of Temporal in the coming years.
## Creation of Temporal objects is throwing errors
If the input is badly formatted Temporal will throw, we might want to
adopt a global strategy to avoid that.
Example :
```ts
const newPlainDate = Temporal.PlainDate.from('bad-string'); // Will throw
```
Removing the feature flag to enable read on replica for all workspaces.
It will still be possible to toggle off the feature by removing the env
variable `PG_DATABASE_REPLICA_URL`.
## Summary
This PR enforces that all custom exceptions must provide a
`userFriendlyMessage`, ensuring end users always see readable error
messages.
## Changes
### Core Changes
- **`CustomException` simplified**: Removed the `ForceFriendlyMessage`
generic parameter - `userFriendlyMessage` is now always required
- **Type safety**: The constructor now requires `{ userFriendlyMessage:
MessageDescriptor }` (no longer optional)
### Updated Files
- **74+ exception classes** updated to provide default user-friendly
messages using Lingui `msg` macro
- Each exception class has a sensible fallback message (e.g., `msg\`An
authentication error occurred.\``)
- Exception classes that had code-specific message maps retain their
behavior
## Benefits
- **Compile-time enforcement**: Forgetting to add a user-friendly
message now causes a TypeScript error
- **Better UX**: End users always see a localized, human-readable error
message
- **Simpler API**: No more boolean generic parameter to think about
## Testing
- `npx nx run twenty-server:typecheck` passes
- `npx nx run twenty-server:lint` passes
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Enforces `userFriendlyMessage` on `CustomException` and updates all
exception classes to supply localized default messages, with
filters/tests adjusted accordingly.
>
> - **Core**:
> - Enforce required `userFriendlyMessage` in `CustomException` (remove
optional generic; constructor now requires `{ userFriendlyMessage:
MessageDescriptor }`).
> - **Exceptions**:
> - Update ~70+ exception classes to set default localized messages via
Lingui `msg` maps and pass them in constructors (e.g., `AuthException`,
`ObjectMetadataException`, `FieldMetadataException`, etc.).
> - Add fallback messages where needed (e.g., `INTERNAL_SERVER_ERROR` or
domain-specific defaults).
> - **HTTP/GraphQL Filters**:
> - Ensure fallbacks create `UnknownException` with `msg` for
user-friendly text in REST/GraphQL exception filters.
> - **Tests**:
> - Adjust unit tests to pass `userFriendlyMessage` to exceptions.
> - Update Jest snapshots to include `extensions.userFriendlyMessage` or
message objects where applicable.
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
221004fdfc0d97b7d152a258b347bf571e70f10e. This will update automatically
on new commits. Configure
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<!-- /CURSOR_SUMMARY -->
- moves applicationRoleId to application entity
- add new `APPLICATION` FieldActorSource and `APPLICATION`
JwtTokenTypeEnum value
- create a new token with applicationId when executing a function
- when applicationId is in token, check for application.defaultRole
permissions
-use twenty-shared types in `twenty-sdk/application`
- create a new import from generate called "Twenty" that you can use
directly without having to set TWENTY_API_KEY AND TWENTY_API_URL (keep
metadata or core parameter only)
- provide to serverless unique one time BEARER TOKEN to run it
Result
<img width="977" height="566" alt="image"
src="https://github.com/user-attachments/assets/e78428a0-5b13-4975-aa13-58ee3b32450c"
/>
<img width="910" height="596" alt="image"
src="https://github.com/user-attachments/assets/6ec72bf5-7655-4093-a45e-ad269595a324"
/>
<img width="741" height="568" alt="image"
src="https://github.com/user-attachments/assets/7683944c-fd79-4417-8fb2-8e4815cc112f"
/>
## Context
Following https://github.com/twentyhq/twenty/pull/16399
Now using the new global orm manager everywhere and returning a
GlobalDatasource/WorkspaceDatasource based on a feature flag.
This means we now need to wrap all our ORM calls within
executeInWorkspaceContext callback (at least for now) so the global
datasource can dynamically hydrate its context via the new store (the
global datasource does not store anything related to workspaces as it is
now a unique singleton). If feature flag is off it still uses local data
stored in the workspace datasource.
First PR to implement application tokens
- add new application role in twenty-server
- move duplicated constants and types to twenty-shared
- will add role configuration utils into twenty-sdk in another PR
Validations :
- relations count (in common api)
- oneToMany relation nested count (in common)
- requested fields count (in gql)
- root resolver count (in gql)
- root resolver duplicates (in gql)
- specific complexity for metadata / nesting count (in gql)
## Problem
buildEntityMetadatas in GlobalWorkspaceOrmManager is computationally
expensive and was running on every executeInWorkspaceContext call. This
method uses
TypeORM's EntitySchemaTransformer and EntityMetadataBuilder to build
metadata for all workspace entities (30-50+ objects with many fields
each).
The resulting EntityMetadata[] is not serialisable which means it cannot
be cached in Redis because they contain:
- Circular references
- Functions/methods
- References to the DataSource instance
## Solution
Extended the workspace cache system to support local-only caching, then
created a cache provider for entityMetadatas.
## Implementation details
Updated @WorkspaceCache decorator (workspace-cache.decorator.ts)
- Added localOnly?: boolean option to skip Redis storage for
non-serializable data
Created WorkspaceEntityMetadatasCacheService
- Computes entity metadatas from DB to avoid race condition, this is
acceptable
Simplified GlobalWorkspaceOrmManager
- Now fetches entityMetadatas from cache instead of rebuilding on every
call
Updated Workspace migration runner - the only entry point where metadata
can change
- Now invalidate the new 'entityMetadata' local cache when
shouldIncrementMetadataGraphqlSchemaVersion is true (== field/object
mutations)
This PR improves the general UX and DX of boards, by modifying the query
effect to only use paged group by queries.
In this PR we implement two more things in the backend for group by
queries :
- Fixed ORDER BY in the PARTITION BY sub-query (this wasn't working
because it was applied in the main query, so it sorted randomly picked
records, which was a correct sort on an incorrect dataset returned by
the sub-query)
- Added offset paging in PARTITION BY
Miscellaneous, various bug fixes and improvements along the way :
- Throttled loading of cards to avoid React freeze
- Handling of drag & drop
- Handling of create / delete / update
- Reworked skeleton (the library slows down a lot with hundreds of
skeleton for a spinning effect that is hardly noticed)
- Fixed refetch of aggregate queries (I included the new group by
aggregates query we use in the existing refetch mechanism)
- Re-trigger queries on filters and sorts changes
- Unselect all record ids when deleting / restoring / detroying
- Fetch only groups that still have records to lighten the group by
query.
# What remains to be done
This is still a naïve fetch more implementation that will work for a few
fetch more rounds, but if you scroll and load say 200 cards per column
on a board, React will re-render all 200 cards of each column each time.
We would probably need to virtualize the board with paged queries as we
did for the table, this could be done after this PR but seems less
urgent.
What's nice is that this new query pattern is well designed for
virtualization also, drawing from our experience with table
virtualization, and adapted to a multi-column request pattern, like a
2:2 matrix of records, for our boards.
So the remaining work would be to design a UI solution for virtualizing
this matrix of records, which could be quite different from our table
virtualization mechanism.
## Context
We've recently introduced a new workspace cache service which now acts
as a cache access and local storage for all workspace related data,
deprecating the individual specific services.
- Better performance through multiple caching/fetching strategies
- Consistent data access patterns across the codebase
- Reduced redis queries through MGET/MSET/PIPELINE with multiple cache
keys
## Context
Deprecating the old objectMetadataMap type in favour of split flat
entities to match with our new caching.
In the long run, trying to achieve:
- Better performance through caching
- Consistent data access patterns across the codebase
- Reduced database queries
Now that everything is based on flat entities, which are cached, we can
finish the refactoring of workspace context cache which should already
improve performances.
Then the last step will be to consume that new cache in the new global
datasource to get rid of the many workspace datasources stored in the
server
closes https://github.com/twentyhq/core-team-issues/issues/1629
To do before requesting review :
- filter update
Migration to come in an other PR
Strat :
1/ Null transformation
- [x] Transform NULL equivalent value to NULL in field validation in
common api - pre-query - with feature flag
- [ ] Same logic in ORM (Not done, complex to handle feature flag here)
- [x] Transform NULL value to equivalent in data formatting in ORM -
post-query
2/ Migration (in other PR) for fieldMetadata not nullable with default
defaultValue (empty string, ...)
- [ ] Remove NOT NULL db constraint
- [ ] Update record value to NULL
- [ ] Update field metadata : isNullable:true
- [ ] Update uniqueIndex whereClause (also for standard uniqueIndex)
- [ ] Activate feature flag
3/ Update metadata creation
- [x] No more default default value
- [x] Update standard field nullability
- [x] Remove index default whereClause for standard field
4/ Update filter
- [x] When filtering on NULL or empty string, be sure all records are
returned (the one with NULL + the one with "")
5/ Test
- [ ] Strat. to do
While investigating the issue a customer was facing, I discovered that
before records and after records could be in different order, making the
orm event and timeline activity engine mix records
Fixes https://github.com/twentyhq/private-issues/issues/362
**How to reproduce**
Link a person that has a duplicate to an opportunity. (you can create a
duplicate by giving two people the same linkedin link).
Open the opportunity record from opportunity table.
Click on the related person (in "Point of contact").
In front of "Duplicates", click on the merge button (two arrows becoming
one).
You should here see an empty "Merge preview" and an error when clicking
"First" tab.
**Issue**
The issue is that CommandMenuMergeRecordPage is getting the referenced
objectMetadataItem from useContextStoreObjectMetadataItemOrThrow without
an instance id. contextStoreObjectMetadataItem is still "opportunity" as
it should be, being on an opportunity view.
So further down it attempts to display the record page according the
label identifier field from opportunity, which is a text field, "name",
and it breaks because the record is actually a person for who the "name"
field is not a text but a full_name type.
**Fix**
I suggested a fix that offers the possibility to find the referenced
objectMetadataItem from the MergeRecords instanceId. But I still gave
flexibility to avoid having to set that state everytime we open the
merge tab, by falling back to the default
contextStoreObjectMetadataItem. (this is used when we merge records from
ticking two records from a view and open the command menu).
Im not sure this is the best option. Open to suggestions !
---------
Co-authored-by: Charles Bochet <charles@twenty.com>
Closes https://github.com/twentyhq/core-team-issues/issues/1600.
Two remarks
- This `limit` variable does not reduce postgre's work at it still needs
to scan the whole table. It did not seem possible to me to optimize this
as we cannot foresee which dimensions will be used by the user, and an
optimization could only result from an index on the dimension(s) (e.g.:
group companies by addressCity limit 50 can be optimized if we have an
index on companies.addressCity + we had a default orderBy on
adressCity). But this will still optimize the FE which at the moment
receives all groups and truncates the result.
- I have not done the work on the FE as the addition of limit is a
breaking change, and will break until the workspaces' schema is rebuilt,
so we need to flush the cache. I think this could be acceptable as the
feature is in the lab but I preferred not doing it yet as it would have
no impact since in the BE I added a default limit to 50 groups, and I
expect more FE work will be done to allow the user to choose their own
limit
Fixes https://github.com/twentyhq/twenty/issues/15809
## Context
We recently introduced a global datasource now consuming workspace
context from ALS store however the authContext was missing (only the
workspaceId was there) which "broke" event emission, now missing the
workspaceMemberId
This PR adds the missing authContext so we can access from anywhere in
the datasource. We are still passing it as a parameters on repository
level for legacy but in theory we should be able to remove it from
everywhere and consume the context
<img width="929" height="253" alt="Screenshot 2025-11-13 at 18 58 16"
src="https://github.com/user-attachments/assets/3e04f264-95e6-4831-94f3-fc01603f19bd"
/>
## Context
This PR introduces a Global Workspace DataSource that consolidates
workspace-specific database access through a single TypeORM DataSource
instance with AsyncLocalStorage-based context management instead of N
workspace datasources.
- Created GlobalWorkspaceDataSource extending TypeORM's DataSource to
manage multiple workspaces with entity metadata caching (1-hour TTL)
- Implemented AsyncLocalStorage for workspace context propagation
(WorkspaceContextForStorage) containing workspace ID, metadata,
permissions, and feature flags
- Modified query execution flow to wrap operations in workspace context
via GlobalWorkspaceOrmManager.executeInWorkspaceContext()
- Added schema name to entity schemas for proper multi-tenant database
separation
Next:
- use the new global workspace datasource everywhere and deprecate
workspace datasource factory
- improve metadata caching using a short TTL to avoid multiple calls to
redis
- Leverage the new WorkspaceContextALS and put it higher in the request
hierarchy to have access to permission, metadata and featureflag
everywhere --- build it manually for commands --- find a way to
propagate it in jobs?
- Remove PG_POOL patch once we have a unique datasource and increase
global datasource pool size
## Implementation
Why ALS:
1. Automatic Per-Request Isolation
With schema-based multi-tenancy, each workspace has its own PostgreSQL
schema
(e.g. workspace_20202020-1c25-4d02-bf25-6aeccf7ea419).
The critical challenge is ensuring that concurrent requests from
different tenants don't interfere with each other.
```typescript
// Request A (Workspace 1) and Request B (Workspace 2) executing concurrently
// Without ALS: Race condition — they'd share the same global state!
// With ALS: Each request has isolated context ✓
```
ALS automatically isolates context per async execution chain, so:
- Request from Tenant A → ALS stores workspaceId: "tenant-a" → Queries
hit workspace_tenant_a schema
- Request from Tenant B → ALS stores workspaceId: "tenant-b" → Queries
hit workspace_tenant_b schema
✅ No interference, even when executing simultaneously on the same
Node.js event loop.
2. No Manual Context Passing
Before ALS, you'd need to pass workspaceId through every function call:
```typescript
// ❌ Without ALS - Context threading nightmare
getRepository(workspaceId, entity)
→ createEntityManager(workspaceId)
→ getMetadata(workspaceId, target)
→ findInCache(workspaceId, cacheKey)
```
With ALS:
```typescript
// ✅ With ALS - Clean, implicit context
getRepository(entity) // Reads workspaceId from ALS
→ createEntityManager() // Reads workspaceId from ALS
→ getMetadata(target) // Reads workspaceId from ALS
→ findInCache(cacheKey) // Reads workspaceId from ALS
```
example
```typescript
override findMetadata(target: EntityTarget<ObjectLiteral>): EntityMetadata | undefined {
const context = getWorkspaceContext(); // 👈 Automatically gets the right workspace!
const { workspaceId, metadataVersion } = context;
const cacheKey = `${workspaceId}-${metadataVersion}`;
// ... returns metadata for THIS workspace's schema
}
```
3. Async Chain Propagation
Node.js operations are heavily async. ALS automatically propagates
context through:
- async/await chains
- Promise chains
- Callbacks
```typescript
executeInWorkspaceContext(workspaceId, async () => {
await prepareContext(); // Has context ✓
const results = await run(); // Has context ✓
await enrichResults(); // Has context ✓
// Even nested async operations maintain context!
await Promise.all([
saveToCache(), // Has context ✓
emitEvent(), // Has context ✓
logMetrics(), // Has context ✓
]);
});
```
5. Schema-Specific Metadata Caching
The implementation caches entity metadata per workspace + version:
```typescript
// Cache key format: "workspaceId-metadataVersion"
const cacheKey = `${workspaceId}-${metadataVersion}`;
```
Why this matters with schemas:
- Each workspace has different table structures (custom fields, objects)
- EntitySchema includes schema: "workspace_xxx" property
- Each cached metadata points to the correct schema
ALS ensures getWorkspaceContext() returns the right workspaceId,
so you always get the correct schema's metadata from cache.
6. Single DataSource for All Tenants
The key change here:
```typescript
// ❌ Old approach: One DataSource per tenant
const dataSourceTenantA = new DataSource({ schema: 'workspace_a' });
const dataSourceTenantB = new DataSource({ schema: 'workspace_b' });
// Problem: Hundreds of DB connection pools!
```
```typescript
// ✅ New approach: One shared DataSource + ALS context
const globalDataSource = new GlobalWorkspaceDataSource();
// ALS determines which schema to use at runtime
```
When you call:
```typescript
globalDataSource.getRepository('person');
```
It internally does:
```typescript
const context = getWorkspaceContext(); // Gets current tenant from ALS
const metadata = this.findMetadata('person'); // Finds metadata for THIS tenant's schema
// EntityMetadata includes: schema: "workspace_20202020-1c25..."
// TypeORM automatically queries: SELECT * FROM "workspace_20202020-1c25...".person
```
7. Request Lifecycle Example
```typescript
// 1. GraphQL request arrives: "query people { ... }"
// 2. Middleware extracts authContext.workspace.id = "tenant-a"
// 3. Query runner wraps execution in ALS:
executeInWorkspaceContext("tenant-a", async () => {
// 4. Everything inside has access to workspace context:
const repo = getRepository('person'); // ALS → tenant-a
const metadata = getMetadata('person'); // ALS → tenant-a → cache["tenant-a-v5"]
// 5. TypeORM builds query with correct schema:
// SELECT * FROM "workspace_tenant_a"."person" WHERE ...
// 6. Even nested calls work:
await saveAuditLog(); // ALS → tenant-a → correct audit schema
await emitWebhook(); // ALS → tenant-a → correct tenant webhook
});
// 7. Request completes, ALS context automatically cleaned up
```
8. Safety & Error Prevention
```typescript
// If you forget to set context:
const context = getWorkspaceContext();
// ❌ Throws: "Workspace context not set..."
// Fails fast rather than querying wrong schema!
// Can't accidentally query wrong tenant:
// Context is immutable within execution scope
```
**Before**
- any user with workpace_members permission was able to remove a user
from their workspace. This triggered the deletion of workspaceMember +
of userWorkspace, but did not delete the user (even if they had no
workspace left) nor the roleTarget (acts as junction between role and
userWorkspace) which was left with a userWorkspaceId pointing to
nothing. This is because roleTarget points to userWorkspaceId but the
foreign key constraint was not implemented
- any user could delete their own account. This triggered the deletion
of all their workspaceMembers, but not of their userWorkspace nor their
user nor the roleTarget --> we have orphaned userWorkspace, not
technically but product wise - a userWorkspace without a workspaceMember
does not make sense
So the problems are
- we have some roleTargets pointing to non-existing userWorkspaceId
(which caused https://github.com/twentyhq/twenty/issues/14608 )
- we have userWorkspaces that should not exist and that have no
workspaceMember counterpart
- it is not possible for a user to leave a workspace by themselves, they
can only leave all workspaces at once, except if they are being removed
from the workspace by another user
**Now**
- if a user has multiple workspaces, they are given the possibility to
leave one workspace while remaining in the others (we show two buttons:
Leave workspace and Delete account buttons). if a user has just one
workspace, they only see Delete account
- when a user leaves a workspace, we delete their workspaceMember,
userWorkspace and roleTarget. If they don't belong to any other
workspace we also soft-delete their user
- soft-deleted users get hard deleted after 30 days thanks to a cron
- we have two commands to clean the orphans roleTarget and userWorkspace
(TODO: query db to see how many must be run)
**Next**
- once the commands have been run, we can implement and introduce the
foreign key constraint on roleTarget
Fixes https://github.com/twentyhq/twenty/issues/14608
martmull