Bug fixes exposed by always-on direct execution
1. GraphQL spec compliance — data[field] = null on resolver error
direct-execution.service.ts — Changed from Promise.allSettled (which
lost the responseKey on rejection) to Promise.all with per-field
try/catch; errors now set data[responseKey] = null per spec
2. Empty object arguments skipped (extractArgumentsFromAst)
extract-arguments-from-ast.util.ts — Removed isEmptyObject check;
filter: {}, data: {} now correctly passed to resolvers instead of
silently dropped (which caused permissions to never be checked)
3. orderBy: {} factory default treated as "no ordering"
direct-execution.service.ts — Before calling the resolver, strips
orderBy: {} and orderByForRecords: {} (empty-object factory defaults
that mean "no ordering")
assert-find-many-args.util.ts / assert-group-by-args.util.ts — Accept {}
for orderBy without throwing
4. orderBy: { field: '...' } object auto-coerced to [{ field: '...' }]
array
direct-execution.service.ts — Applies GraphQL list coercion: a
non-array, non-empty orderBy object is wrapped in an array before
assertion and resolver call
5. totalCount and aggregate fields returned as strings from PostgreSQL
graphql-format-result-from-selected-fields.util.ts — Added
coerceAggregateValue that parses numeric strings to numbers for
totalCount, sum*, avg*, min*, max*, count*, percentageOf* fields
Test updates
nested-relation-queries.integration-spec.ts — Updated expected error
message from Yoga schema-validation message to direct execution resolver
message
~30 snapshot files — Updated to reflect direct execution's error
messages (different from Yoga schema-validation messages for input type
errors)
## Overview
This PR implements **generic many-to-many relation support** through
junction tables (also known as associative entities or join tables).
This replaces the need for hardcoded taskTarget/noteTarget logic and
provides a flexible foundation for modeling complex entity
relationships.
## Architecture
### Data Model
Many-to-many relationships are implemented using a **junction object
pattern**:
```
┌─────────┐ ┌──────────────────┐ ┌─────────┐
│ Pet │──────>│ PetRocket │<──────│ Rocket │
│ │ 1:N │ (junction) │ N:1 │ │
│ rockets ├───────┤ pet : Pet ├───────┤ │
└─────────┘ │ rocket : Rocket │ └─────────┘
└──────────────────┘
```
The junction object (PetRocket) has:
- A `MANY_TO_ONE` relation to **Pet** (the source)
- A `MANY_TO_ONE` relation to **Rocket** (the target)
The source object (Pet) has a `ONE_TO_MANY` relation pointing to the
junction, with **field settings** that specify which target field to
follow.
### Field Settings Schema
Junction configuration is stored in `FieldMetadataRelationSettings`:
```typescript
{
relationType: "ONE_TO_MANY",
// Points to the target field on the junction object
junctionTargetFieldId?: string; // For regular relations
junctionTargetMorphId?: string; // For polymorphic relations
}
```
**Two configuration modes:**
1. **`junctionTargetFieldId`** - References a specific `RELATION` field
on the junction
2. **`junctionTargetMorphId`** - References a `morphId` group for
polymorphic targets (e.g., link to Person OR Company)
### GraphQL Query Generation
When a junction relation is detected, the GraphQL fields are generated
to fetch the nested target:
```graphql
query GetPetWithRockets {
pet(id: "...") {
rockets { # ONE_TO_MANY to junction
id
rocket { # Target field on junction
id
name
__typename
}
}
}
}
```
For polymorphic junction targets:
```graphql
caretakerPerson { id, name }
caretakerCompany { id, name }
```
## Frontend Architecture
### Display Flow
1. **Detection**: `hasJunctionConfig()` checks if field has junction
settings
2. **Config Resolution**: `getJunctionConfig()` resolves junction object
metadata and target fields
3. **Record Extraction**: `extractTargetRecordsFromJunction()` extracts
target records from junction records
4. **Rendering**: Target records displayed as chips (not junction
records)
### Edit Flow
1. **Picker Opening**: Initializes the multi-record picker with:
- Searchable object types (derived from junction target fields)
- Pre-selected items (extracted from existing junction records)
2. **Selection Handling**: Manages create/delete of junction records:
- **Select**: Creates new junction record with source + target IDs
- **Deselect**: Finds and deletes the junction record
- **Optimistic Updates**: Manually updates Recoil store before API call
### Key Trade-offs
| Decision | Trade-off |
|----------|-----------|
| Junction records managed manually | More control over optimistic
updates, but requires manual cache management |
| Settings stored per-field | Flexible (same junction can power
different views), but requires UI to configure |
| Polymorphic via morphId groups | Supports N target types, but adds
query complexity |
| Feature flag gated | Safe rollout, but requires flag management |
## Backend Changes
- **Validation**: Junction target field must exist and be a valid
`MANY_TO_ONE` relation
- **Settings**: Extended `FieldMetadataRelationSettings` type with
junction fields
- **Dev Seeder**: Added sample junction objects (PetRocket,
EmploymentHistory, PetCareAgreement) for testing
## How to Test
1. Enable the `IS_JUNCTION_RELATIONS_ENABLED` feature flag
2. Create objects with junction pattern (Pet → PetRocket → Rocket)
3. Configure the junction target in field settings (advanced mode)
4. Verify:
- Display shows target objects (Rockets), not junction records
(PetRockets)
- Picker allows selecting/deselecting targets
- Changes persist correctly
https://github.com/user-attachments/assets/d04f057a-228c-4de8-af48-76bb2d72cac1
---------
Co-authored-by: Charles Bochet <charles@twenty.com>
# Introduction
In this pull-request we introduce a service dedicated to the
twenty-standard app installation, we will later be able to re-use
existing logic to be more generic and allow any app installation.
For the moment sticking to this usage
https://github.com/twentyhq/core-team-issues/issues/1995
## Encountered issues
- We decided not to migrate deprecated fields ( also they will become
custom field for any existing workspace having them in the future )
- duplicate criteria
- wrong search index declaration
- forgotten isSearchable
- Attachement seed
- Restored standardId
## Note
For the moment we're still searching through standardId for code that
run on both existing and new workspaces.
For code running on new workspace exclusively we're searching using
universalIdentifier
We will standardize universalIdentifier usage later when we've migratred
all the existing workspaces
## Workspace creation
Will handle workspace creation the same way in another PR
Related https://github.com/twentyhq/twenty/pull/15065
## TODO
- [ ] Double all frontend hardcoded queries to not refer to deprecated
fields especially attachments
## 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
Context :
Large PR with 600+ test files. Enable connect and disconnect logic in
createMany (upsert true) / updateOne / updateMany resolvers
- Add disconnect logic
- Gather disconnect and connect logic -> called relation nested queries
- Move logic to query builder (insert and update one) with a preparation
step in .set/.values and an execution step in .execute
- Add integration tests
Test :
- Test API call on updateMany, updateOne, createMany (upsert:true) with
connect/disconnect
