## 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>
