# TimelineActivity migration to morph
- Creates `timelineActivities2` relations on Company, Dashboard, Note,
Opportunity, Person, Task, Workflow, WorkflowRun, and WorkflowVersion
entities with proper metadata and cascade delete behavior.
It was required to create standard fields as well since the
mapObjectMetadataByUniqueIdentifier needs it. otherwise the fields won't
be considered
- Feature Flag `IS_TIMELINE_ACTIVITY_MIGRATED` necessary to have the two
states in parallel. It is used as a stamp once the migration has been
run
- Migration is done using the coreDataSource. Why ?
even though is unsafe to use, the first implementation of the migration
took forever on each workspace. See [this
commit](https://github.com/twentyhq/twenty/pull/15652/commits/477011e8d7d4c580f79ba7ec4a8fb002a3ec86b2)
The plan for this complex migration is as follows :
Note: we will need to rename fields in the release 1.12 (there is no
easy way to do all this in one release)
## 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.
## Summary
This PR significantly simplifies the AI chat architecture by removing
complex routing/planning mechanisms and introduces clickable record
links in AI responses.
## Changes
### AI Chat Architecture Simplification
- **Removed** the entire `ai-chat-router` module (~850 lines) including:
- Strategy decider service
- Plan generator service
- Complex routing logic
- **Removed** agent execution planning services (~700 lines):
- `agent-execution.service.ts`
- `agent-plan-executor.service.ts`
- `agent-tool-generator.service.ts`
- **Added** centralized `ToolRegistryService` for tool management:
- Builds searchable tool index (database, action, workflow tools)
- Provides tool lookup by name
- Supports agent search for loading expertise
- **Added** `ChatExecutionService` as simple replacement:
- Includes full tool catalog in system prompt
- Pre-loads common tools (find/create/update for company, person,
opportunity, task, note)
- Uses `load_tools` mechanism for dynamic tool activation
- Enables native web search by default
### Record References in AI Responses
- Added `recordReferences` field to tool outputs for create, find, and
update operations
- Implemented `[[record:objectName:recordId:displayName]]` syntax for AI
to reference records
- Created `RecordLink` component that renders clickable chips with
object icons
- Integrated record link parsing into the markdown renderer
- Users can now click directly on created/found records in AI responses
### Workflow Agent Fixes
- Fixed cache invalidation issue when creating agents in workflows
- Added default prompt for workflow-created agents to prevent validation
errors
- Relaxed agent validation to only check properties being updated (not
all required properties)
### Code Quality Improvements
- Extracted `getRecordDisplayName` utility that mirrors frontend's
`getLabelIdentifierFieldValue` logic
- Uses object metadata to determine the correct label identifier field
- Handles `FULL_NAME` composite type for person/workspaceMember objects
- Shared across create, find, and update record services
## Net Impact
- **~1,200 lines deleted** (complex routing/planning code)
- **~500 lines added** (simpler tool registry + record links)
- Significantly reduced code complexity
- Better tool discovery through full catalog in system prompt
- Improved UX with clickable record references
## Testing
- Typecheck passes
- Lint passes
- Manual testing of AI chat with record creation and linking
Changes:
- as we store date in redis as serialized, let's make all flatEntity
dates as string. This requires changing FlatEntity types and making sure
that entity are converted to flatEntity and flatEntity to dtos
Fixes multiple issues with CRON schedule input validation and execution
time display.
### Issues Fixed
1. **UTC label placement** - Added "UTC" suffix to specific times (e.g.,
"at 09:30 UTC") but not to interval descriptions (e.g., "every hour")
2. **Upcoming execution time calculation** - Fixed incorrect execution
times for malformed CRON expressions by implementing auto-correction
### Changes
- Created `normalizeCronExpression` utility to standardize cron
expressions before parsing
- Updated `formatTime` to support optional UTC suffix
- Enhanced `getHoursDescription` to append UTC to specific times
- Added comprehensive test coverage (102 tests passing)
### Before
- `"1 /3 * * *"` showed daily executions at same time (incorrect)
- `"9 * * *"` showed same time repeated 3 times (incorrect)
- No UTC labels on schedule descriptions (confusing)
### After
- All malformed expressions auto-corrected and show correct execution
times
- UTC labels clearly indicate timezone for specific times
- User-friendly error messages for truly invalid patterns
Closes#15870
## Context
Deprecating TwentyORMManager in favor of TwentyORMGlobalManager
(temporarily, as this will simplify the ultimate goal to later replace
all usages with the new TwentyORMGlobalManagerV2 which will have a
similar signature)
This means this PR had to refactor a bit of code to pass down the
workspaceId when not available directly as it is now a requirement,
meaning we also deprecated scopedWorkspaceContextFactory to have a less
obscure way to fetch the workspaceId and have something more
declarative.
Step 3 will be to update TwentyORMGlobalManager to use a featureFlag
toggling and use the new GlobalWorkspaceOrmManager internally using the
new cache service
Step 4 will be to remove the feature flag and pg_pool patch
## Summary
Consolidates the AI tool provider architecture by creating a single
`ToolProviderService` as the entry point for all tool generation. This
removes multiple intermediate services and simplifies the codebase.
## Changes
### New Architecture
- **`ToolProviderService`**: Single service for all tool generation
with:
- `getTools(spec)` - Get tools by category with permissions
- `getToolByType(type)` - Get specific tool for workflow execution
- **`ToolCategory` enum**: Declarative specification of tool types:
- `DATABASE_CRUD` - Record CRUD operations
- `ACTION` - HTTP requests, email sending, article search
- `WORKFLOW` - Workflow management tools
- `METADATA` - Object/field metadata tools
- `NATIVE_MODEL` - Model-specific tools (e.g., web search)
- **`ToolSpecification` type**: Clean API for requesting tools with
permissions
### Removed
- `AiToolsModule` - No longer needed
- `ToolService` - Logic inlined into ToolProviderService
- `ToolAdapterService` - Logic inlined into ToolProviderService
- `ToolRegistryService` - Logic inlined into ToolProviderService
### Updated
- All consumers (agents, chat, MCP, workflows) now use
`ToolProviderService`
- Test files updated accordingly
## Stats
- **547 insertions, 1146 deletions** (net ~600 lines removed)
- 4 services deleted
- 1 module deleted
## Testing
- [x] Typecheck passes
- [x] Lint passes
This is a temporary fix that needs to be revisited.
It seems that with the new enqueue system we are enqueuing jobs multiple
times due to race condition. We likely want to only consider job that
have been created more than x secs ago
2025-12-03 20:49:33 +01:00
Thomas TrompetteGitHubgreptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
- if >5000 workflows per hour, new ones should failed
- if >100 workflow per min, new ones should be set as not started.
Except manual trigger
- when enqueued, we check if there a not started workflows that may be
queued. If yes, we call the associated job
---------
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
## 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
## Summary
This PR introduces a comprehensive agent evaluation system and refactors
the AI module structure for better organization.
## Key Changes
### 🎯 Agent Evaluation System
- Added **Agent Turn Evaluation** entities, DTOs, and database schema
- New GraphQL mutations: `evaluateAgentTurn` and `runEvaluationInput`
- Added `evaluationInputs` field to Agent entity for storing test inputs
- New `AgentTurnGraderService` for automatic turn evaluation
- Added evaluation UI with new **Evals** and **Logs** tabs in agent
detail pages
### 🏗️ Entity & Module Refactoring
- Renamed `AgentChatMessage` → `AgentMessage` for clarity
- Consolidated chat entities: `AgentMessage`, `AgentTurn`, and
`AgentChatThread`
- Reorganized AI modules under `ai/` subdirectory structure
- Updated imports across codebase to reflect new module paths
### 🤖 New Agents & Roles
- Added **Dashboard Builder Agent** for dashboard creation and
management
- Added **Dashboard Manager Role** with appropriate permissions
- Updated role permissions to be more granular (users vs agents vs API
keys)
### 🔐 Permission System Updates
- Added `HTTP_REQUEST_TOOL` permission flag
- Updated Workflow Manager role permissions (restricted tool access)
- Enhanced permission flag types to differentiate between user/agent/API
key contexts
- Added `isRelevantForAgents`, `isRelevantForApiKeys`,
`isRelevantForUsers` to permission flags
### 📨 Message Role Enhancement
- Added `system` role to `AgentMessageRole` enum (alongside
user/assistant)
- Updated message handling to support system prompts
### 🎨 UI/UX Improvements
- New tabs in agent detail: **Evals** and **Logs**
- Added turn detail page: `/ai/agents/:agentId/turns/:turnId`
- Fixed text overflow in `SettingsListItemCardContent`
- Updated role applicability labels ("Assignable to Workspace Members")
### 🛠️ Technical Improvements
- Fixed Zod schema validation for UUID and Date fields (use string
validators)
- Updated `ToolRegistryService` to properly register HTTP tool with
permission flag
- Enhanced error handling in agent execution services
- Updated database migrations for new entity schema
## Database Migrations
- `1764210000000-add-system-role-to-agent-message.ts`
- `1764220000000-add-evaluation-inputs-to-agent.ts`
- `1764200000000-add-agent-turn-evaluation.ts`
- `1764100000000-refactor-agent-chat-entities.ts`
## Testing
- [ ] Agent evaluation flow tested
- [ ] Dashboard Builder agent tested
- [ ] Permission system validated
- [ ] UI tabs and navigation tested
- [ ] Database migrations run successfully
## Breaking Changes
⚠️ **Entity Rename**: `AgentChatMessage` renamed to `AgentMessage` -
GraphQL queries need updating
## Related Issues
<!-- Link any related issues here -->
## Screenshots
<!-- Add screenshots if applicable -->
# Introduction
We need to be able to create custom workspace application on all
workspaces, even pending and ongoing etc
Right now the upgrade devx only allows and expect active or suspended
workspace to be passed to runOnWorkspace.
## WorkspacesMigrationRunner
Created an intermediate class `WorkspacesMigrationRunner` that expect an
array `WorkspaceStatus` to be fetched for the current command to be run
on
The `ActiveOrSuspendedCommandRunner` statically passes both `SUSPENDED`
and `ACTIVE`, whereas the create workspace custom application passed all
the enum values
## DataSource
Workspace that are not fully init don't have a `workspace_schema` so
they don't have `dataSource`
Made a not very elegant check to see if current workspace we're about to
create dataSource on has one historically
Which means that dataSource is now optional, it had only one impact on
an existing command and the desired devx will become consuming existing
services that do not expect dataSource ( or at least yet )
@charlesBochet
In workflow codebase, NULL (instead of empty object) is expected on
workflow version object step field, when a new workflow is created for
example.
(packages/twenty-front/src/modules/workflow/workflow-diagram/utils/generateWorkflowDiagram.ts
- 42)
This case is not isolated and it creates many issues.
We decided to format NULL value to equivalent (empty string for text
field, empty object for raw_json) but it seems it complicates the dev x.
To unlock @Devessier I prefer revert the logic, the time we discuss how
to solve this cases.
## Overview
This PR replaces the dynamic agent handoff system with a more
predictable planning-based router that decides upfront how to handle
multi-agent coordination.
## Major Changes
### 🔄 Architecture Shift: Handoffs → Planning
**Removed:**
- `AgentHandoffEntity` and handoff tracking system
- `AgentHandoffService` and `AgentHandoffExecutorService`
- Dynamic agent-to-agent transfers during execution
- Handoff tool generation and description templates
**Added:**
- `AiRouterService` with two strategies: `simple` (single agent) and
`planned` (multi-agent)
- `AgentPlanExecutorService` for executing multi-step plans
- Plan validation (cycle detection, dependency resolution)
- `UnifiedRouterResult` type with discriminated union
### 🤖 New Standard Agents
Added two new specialized agents:
- **Researcher Agent**: Web search, fact-finding, competitive
intelligence
- **Code Agent**: TypeScript function generation for serverless
workflows
### 🏗️ Router Refactoring (Latest)
Split router responsibilities into focused services:
- `AiRouterStrategyDeciderService`: Decides simple vs planned strategy
- `AiRouterPlanGeneratorService`: Generates and validates execution
plans
- `AiRouterService`: Coordinates between services (reduced from 426→275
lines)
### ⚙️ Configuration Improvements
- Added `outputStrategy` to agent definitions (`direct` vs `synthesize`)
- Removed hardcoded special cases for workflow-builder
- Added `plannerModel` field to workspace entity
- Increased `MAX_STEPS` from 10 to 25 for complex workflows
### 📝 Agent Prompt Refinements
Significantly simplified prompts for better clarity:
- Workflow Builder: 51→36 lines
- Helper: 49→28 lines
- Data Manipulator: Enhanced with sorting guidance
### 🔍 Enhanced Debugging
- Plan reasoning and step count in data message parts
- Router debug info with token usage tracking
- Better logging throughout execution pipeline
## Benefits
1. **Simpler Mental Model**: Router decides upfront vs dynamic transfers
2. **Better Predictability**: Users see the plan before execution
3. **Cleaner Architecture**: SRP with focused services
4. **Configuration Over Code**: Agent behavior via config, not hardcoded
logic
5. **Plan Validation**: Catches invalid dependencies and cycles
## Migration Notes
- Database migration removes `agentHandoff` table
- Adds `plannerModel` column to workspace table
- No API breaking changes (agent endpoints unchanged)
## Testing
- Integration tests updated to remove handoff dependencies
- Agent tool test utilities simplified
- Plan validation covered by new logic
## Next Steps (Future PRs)
- Parallel execution of independent plan steps
- Dynamic re-planning based on results
- Plan caching for common routing patterns
- Error recovery strategies in plan executor
## Context
Deprecating legacy ObjectMetadata from cache in favor of flat entities.
Introducing utils to build byName/byNameSingular/byNamePlural in
isolated cases
## Next
- I had to introduce a util to build from flat to legacy
objectMetadataMaps, we should instead use flat maps directly when needed
(datasource, schema generation, etc)
- Deprecate metadata version in the cache
- Use the new cache strategy for flat entities with permissions and
feature flags and inject in the global datasource context
## Summary
This PR adds configurable response format support for AI agents,
allowing them to return either plain text or structured JSON data based
on a defined schema.
## Key Features
### 1. Agent Response Format Configuration
- Added `AgentResponseFormat` type supporting:
- `text`: Returns plain text responses (default)
- `json`: Returns structured JSON based on defined schema
- New `AgentResponseSchema` type moved to `twenty-shared/ai` for sharing
between frontend/backend
### 2. Settings UI
- New `SettingsAgentResponseFormat` component for configuring response
format
- Visual schema builder for defining JSON output structure
- Real-time validation and preview
- Integrated into agent settings tab
### 3. Workflow Integration
- AI Agent workflow action automatically uses agent's configured
response format
- Output schema dynamically generated from agent's response format
- Workflow variable picker shows structured fields for JSON responses
- Backward compatible with existing text-only agents
### 4. Backend Implementation
- Added `convertAgentSchemaToZod` utility to validate JSON responses
- Agent executor service handles both text and JSON generation
- Automatic agent creation/cloning when adding AI agent steps to
workflows
- Unique agent naming with conflict resolution
### 5. Database Migration
- Migration `1763622159656-update-agent-response-format.ts`
- Sets default `responseFormat` to `{"type":"text"}` for existing agents
- Updated all standard agents with proper response format
## Changes by Module
### Frontend (`twenty-front`)
- 🆕 `AgentResponseFormat` type
- 🆕 `SettingsAgentResponseFormat` component
- ✏️ Updated `WorkflowEditActionAiAgent` to support response format
configuration
- 🗑️ Removed deprecated `useAiAgentOutputSchema` hook and
`AiAgentOutputSchema` type
### Backend (`twenty-server`)
- 🆕 `AgentResponseFormat` type in agent entity
- 🆕 `convertAgentSchemaToZod` utility for schema validation
- ✏️ Updated `AiAgentExecutorService` to handle both text and JSON
generation
- ✏️ Updated `WorkflowSchemaWorkspaceService` to generate output schema
from agent config
- ✏️ Enhanced `WorkflowVersionStepOperationsWorkspaceService` with agent
creation/cloning
- 🆕 Agent naming constants for conflict resolution
### Shared (`twenty-shared`)
- 🆕 `AgentResponseSchema` type
- 🆕 `ModelConfiguration` type moved to shared package
- Updated exports in `ai/index.ts`
## Code Quality
- Removed useless comments following code style guidelines
- All linter checks passed
- Type-safe implementation with proper TypeScript types
## Testing
- ✅ Database migration tested
- ✅ Agent creation/cloning in workflows verified
- ✅ Response format switching (text ↔ JSON) validated
- ✅ Backward compatibility with existing agents confirmed
## Migration Notes
- Existing agents will have `responseFormat: {type: 'text'}` set
automatically
- No breaking changes - all existing functionality preserved
- Agents can be updated to use JSON format through settings UI
## Summary
This PR replaces the Active/Inactive accordion sections with a modern
filter dropdown button and enables full access to system objects in
advanced mode.
## Changes
### UI Improvements
- ✅ Replaced accordion sections with a filter button dropdown (matching
the design pattern from the Group filter)
- ✅ Added 'Deactivated' toggle filter (hidden by default, uses
IconArchive)
- ✅ Added 'System objects' toggle filter (only visible in advanced mode,
uses IconSettings)
- ✅ Fixed search input width to properly fill available space
- ✅ Proper button sizing and alignment
### System Objects Support
- ✅ Made system objects visible when 'System objects' filter is toggled
on
- ✅ System objects are now fully clickable and accessible
- ✅ Updated object detail page to support system objects
- ✅ Updated field creation/edit pages to support system objects
- ✅ System objects can now have custom fields added
### Architecture
- ✅ Implemented scalable filter architecture using a single filtered
list
- ✅ Easy to add more filters in the future (e.g., show remote objects)
- ✅ All filters work independently and can be combined
## Testing
- [x] Tested deactivated objects toggle
- [x] Tested system objects toggle (only shows in advanced mode)
- [x] Tested clicking on system objects
- [x] Tested adding custom fields to system objects
- [x] No linter errors
## Screenshots
See attached screenshots in the conversation for the new filter UI.
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Adds a filter dropdown to the Settings Objects table (incl.
deactivated/system toggles), enables system objects across
settings/field flows, seeds core views (workspace members, messages,
threads, calendar events), and adds actions for Workspace Members.
>
> - **Settings UI**
> - **Objects Table**: Replaces Active/Inactive sections with a single
filterable list and dropdown (`Deactivated`, `System objects` in
advanced mode); updates props to `objectMetadataItems` and removes
accordion sections.
> - **Search/UX**: Search input fills available space; inactive rows
show activation/delete menu; active rows remain navigable.
> - **Pages Updated**: `SettingsObjects`,
`SettingsApplicationDetailContentTab` switch to new table API; object
detail and new-field flows use `findObjectMetadataItemByNamePlural`
(works with system objects).
> - **Action Menu**
> - **Workspace Members**: Adds `WORKSPACE_MEMBERS_ACTIONS_CONFIG` with
"Manage members in settings" action; wired into `getActionConfig` for
`WorkspaceMember`.
> - **Server (Core Views Seed)**
> - Adds default views: `workspaceMembersAllView`, `messagesAllView`,
`messageThreadsAllView`, `calendarEventsAllView`; included in
`prefillCoreViews`.
> - Marks workflow entities as system (`WorkflowRun`,
`WorkflowVersion`).
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
6a2856df85. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
# Introduction
related to https://github.com/twentyhq/core-team-issues/issues/1833
In this PR we're starting the sync-metadata and standardIds deprecation
by introducing `twenty-standard` application that will regroup every
standard object such as company and opportunities. But also the
`custom-workspace-application` which is an app created at the same time
as a workspace and that will regroup everything configure within the
workspace ( custom objects fields etc )
## What's done
On both new workspace and seeded workspace creation:
- Creating a custom workspace app
- Creating a twenty standard app
- Refactored the seed core schema and workspace creation to be run
within a transaction in order to handle circular dependency foreignkey
requirements ( which is deferred for app toward workspace )
- Updated workspace entity to have a custom workspace relation (
nullable for the moment until we implem an upgrade command to handle
retro comp )
- Integration testing on user, workspace creation deletion and expected
default apps creation
- ~~Soft deleted user on `deleteUser`~~ Done by marie and rebased on it
## What's next
- Update seeder to propagate the `twenty-standard` workspace
`applicationId` to every standard synchronized entities ( cheap and fast
iteration through the about to be deprecated sync-metadata as an easy
way to synchronize standards metadata entities ).
- Update seeder to propagate the `custom-workspace-application`
workspace `applicationId` to anything custom ( `pets` and `rockets` )
- Prepend `custom-workspace-application` `applicationId` to every
metadata API operations ( create a specific cache etc )
- Upgrade command on all existing workspace to create a custom app and
associate its applicationId to any existing custom entities
- Make `universalIdentifier` and `applicationId` required for any
syncable entity
As title
- adds decorators in twenty-sdk
- update twenty-cli load-manifest to it gets @FieldMetadata infos +
testing
- update twenty-server so it CRUD fields properly, using
universalIdentifier
- Fix UI so we can update managed objects records
- move FieldMetadata items from twenty-server to twenty-shared
- on draft creation, do not fetch the full version. Avoid the fetch of
steps and trigger
- on activation, we were performing 8 queries/mutations synchronously +
2 additional for automated triggers. I refacto the call it it gets
reduced to 4 queries/mutations + 2 additional for automated triggers
This PR implements the necessary tools to have `react-datepicker`
calendar and our date picker components work reliably no matter the
timezone difference between the user execution environment and the user
application timezone.
Fixes https://github.com/twentyhq/core-team-issues/issues/1781
This PR won't cover everything needed to have Twenty handle timezone
properly, here is the follow-up issue :
https://github.com/twentyhq/core-team-issues/issues/1807
# Features in this PR
This PR brings a lot of features that have to be merged together.
- DATE field type is now handled as string only, because it shouldn't
involve timezone nor the JS Date object at all, since it is a day like a
birthday date, and not an absolute point in time.
- DATE_TIME field wasn't properly handled when the user settings
timezone was different from the system one
- A timezone abbreviation suffix has been added to most DATE_TIME
display component, only when the timezone is different from the system
one in the settings.
- A lot of bugs, small features and improvements have been made here :
https://github.com/twentyhq/core-team-issues/issues/1781
# Handling of timezones
## Essential concepts
This topic is so complex and easy to misunderstand that it is necessary
to define the precise terms and concepts first. It resembles character
encoding and should be treated with the same care.
- Wall-clock time : the time expressed in the timezone of a user, it is
distinct from the absolute point in time it points to, much like a
pointer being a different value than the value that it points to.
- Absolute time : a point in time, regardless of the timezone, it is an
objective point in time, of course it has to be expressed in a given
timezone, because we have to talk about when it is located in time
between humans, but it is in fact distinct from any wall clock time, it
exists in itself without any clock running on earth. However, by
convention the low-level way to store an absolute point in time is in
UTC, which is a timezone, because there is no way to store an absolute
point in time without a referential, much like a point in space cannot
be stored without a referential.
- DST : Daylight Save Time, makes the timezone shift in a specific
period every year in a given timezone, to make better use of longer days
for various reasons, not all timezones have DST. DST can be 1 hour or 30
min, 45 min, which makes computation difficult.
- UTC : It is NOT an “absolute timezone”, it is the wall-clock time at
0° longitude without DST, which is an arbitrary and shared human
convention. UTC is often used as the standard reference wall-clock time
for talking about absolute point in time without having to do timezone
and DST arithmetic. PostgreSQL stores everything in UTC by convention,
but outputs everything in the server’s SESSION TIMEZONE.
## How should an absolute point in time be stored ?
Since an absolute point in time is essentially distinct from its
timezone it could be stored in an absolute way, but in practice it is
impossible to store an absolute point in time without a referential. We
have to say that a rocket launched at X given time, in UTC, EST, CET,
etc. And of course, someone in China will say that it launched at 10:30,
while in San Francisco it will have launched at 19:30, but it is THE
SAME absolute point in time.
Let’s take a related example in computer science with character
encoding. If a text is stored without the associated encoding table, the
correct meaning associated to the bits stored in memory can be lost
forever. It can become impossible for a program to guess what encoding
table should be used for a given text stored as bits, thus the glitches
that appeared a lot back in the early days of internet and document
processing.
The same can happen with date time storing, if we don’t have the
timezone associated with the absolute point in time, the information of
when it absolutely happened is lost.
It is NOT necessary to store an absolute point in time in UTC, it is
more of a standard and practical wall-clock time to be associated with
an absolute point in time. But an absolute point in time MUST be store
with a timezone, with its time referential, otherwise the information of
when it absolutely happened is lost.
For example, it is easier to pass around a date as a string in UTC, like
`2024-01-02T00:00:00Z` because it allows front-end and back-end code to
“talk” in the same standard and DST-free wall-clock time, BUT it is not
necessary. Because we have date libraries that operate on the standard
ISO timezone tables, we can talk in different timezone and let the
libraries handle the conversion internally.
It is false to say that UTC is an absolute timezone or an absolute point
in time, it is just the standard, conventional time referential, because
one can perfectly store every absolute points in time in UTC+10 with a
complex DST table and have the exactly correct absolute points in time,
without any loss of information, without having any UTC+0 dates
involved.
Thus storing an absolute point in time without a timezone associated,
for example with `timestamp` PostgreSQL data type, is equivalent to
storing a wall-clock time and then throwing away voluntarily the
information that allows to know when it absolutely happened, which is a
voluntary data-loss if the code that stores and retrieves those
wall-clock points in time don’t store the associated timezone somewhere.
This is why we use `timestamptz` type in PostgreSQL, so that we make
sure that the correct absolute point in time is stored at the exact time
we send it to PostgreSQL server, no matter the front-end, back-end and
SQL server's timezone differences.
## The JavaScript Date object
The native JavaScript Date object is now officially considered legacy
([source](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Date)),
the Date object stores an absolute point in time BUT it forces the
storage to use its execution environment timezone, and one CANNOT modify
this timezone, this is a legacy behavior.
To obtain the desired result and store an absolute point in time with an
arbitrary timezone there are several options :
- The new Temporal API that is the successor of the legacy Date object.
- Moment / Luxon / @date-fns/tz that expose objects that allow to use
any timezone to store an absolute point in time.
## How PostgreSQL stores absolute point in times
PostgreSQL stores absolute points in time internally in UTC
([source](https://www.postgresql.org/docs/current/datatype-datetime.html#DATATYPE-DATETIME-INPUT-TIME-STAMPS)),
but the output date is expressed in the server’s session timezone
([source](https://www.postgresql.org/docs/current/sql-set.html)) which
can be different from UTC.
Example with the object companies in Twenty seed database, on a local
instance, with a new “datetime” custom column :
<img width="374" height="554" alt="image"
src="https://github.com/user-attachments/assets/4394cb43-d97e-4479-801d-ca068f800e39"
/>
<img width="516" height="524" alt="image"
src="https://github.com/user-attachments/assets/b652f36a-d2e2-47a4-8950-647ca688cbbd"
/>
## Why can’t I just use the JavaScript native Date object with some
manual logic ?
Because the JavaScript Date object does not allow to change its internal
timezone, the libraries that are based on it will behave on the
execution environment timezone, thus leading to bugs that appear only on
the computers of users in a timezone but not for other in another
timezone.
In our case the `react-datepicker` library forces to use the `Date`
object, thus forcing the calendar to behave in the execution environment
system timezone, which causes a lot of problems when we decide to
display the Twenty application DATE_TIME values in another timezone than
the user system one, the bugs that appear will be of the off-by-one date
class, for example clicking on 23 will select 24, thus creating an
unreliable feature for some system / application timezone combinations.
A solution could be to manually compute the difference of minutes
between the application user and the system timezones, but that’s not
reliable because of DST which makes this computation unreliable when DST
are applied at different period of the year for the two timezones.
## Why can’t I compute the timezone difference manually ?
Because of DST, the work to compute the timezone difference reliably,
not just for the usual happy path, is equivalent to developing the
internal mechanism of a date timezone library, which is equivalent to
use a library that handles timezones.
## Using `@date-fns/tz` to solve this problem
We could have used `luxon` but it has a heavy bundle size, so instead we
rely here on `@date-fns/tz` (~1kB) which gives us a `TZDate` object that
allows to use any given timezone to store an absolute point-in-time.
The solution here is to trick `react-datepicker` by shifting a Date
object by the difference of timezone between the user application
timezone and the system timezone.
Let’s take a concerte example.
System timezone : Midway, ⇒ UTC-11:00, has no DST.
User application timezone : Auckland, NZ ⇒ UTC+13:00, has a DST.
We’ll take the NZ daylight time, so that will make a timezone difference
of 24 hours !
Let’s take an error-prone date : `2025-01-01T00:00:00` . This date is
usually a good test-case because it can generate three classes of bugs :
off-by-one day bugs, off-by-one month bugs and off-by-one year bugs, at
the same time.
Here is the absolute point in time we take expressed in the different
wall-clock time points we manipulate
Case | In system timezone ⇒ UTC-11 | In UTC | In user application
timezone ⇒ UTC+13
-- | -- | -- | --
Original date | `2024-12-31T00:00:00-11:00` | `2024-12-31T11:00:00Z` |
`2025-01-01T00:00:00+13:00`
Date shifted for react-datepicker | `2025-01-01T00:00:00-11:00` |
`2025-01-01T11:00:00Z` | `2025-01-02T00:00:00+13:00`
We can see with this table that we have the number part of the date that
is the same (`2025-01-01T00:00:00`) but with a different timezone to
“trick” `react-datepicker` and have it display the correct day in its
calendar.
You can find the code in the hooks
`useTurnPointInTimeIntoReactDatePickerShiftedDate` and
`useTurnReactDatePickerShiftedDateBackIntoPointInTime` that contain the
logic that produces the above table internally.
## Miscellaneous
Removed FormDateFieldInput and FormDateTimeFieldInput stories as they do
not behave the same depending of the execution environment and it would
be easier to put them back after having refactored FormDateFieldInput
and FormDateTimeFieldInput
---------
Co-authored-by: Charles Bochet <charles@twenty.com>
We do not want the fields to update multiselect for upsert record
action. We want all available fields displayed by default.
This makes upsert record action closer to create record than update
record.
This PR:
- deletes WorkflowUpdateRecordBody that was common between update and
upsert and put back content into update
- creates WorkflowCreateRecordBody that is now common between create and
upsert
- simplifies shouldDisplayFormField
Before - using fields to update as update record action
<img width="546" height="823" alt="Capture d’écran 2025-10-30 à 10 00
24"
src="https://github.com/user-attachments/assets/9206bc8b-75c2-40fa-a8de-e708b6b2cd05"
/>
After - displaying all fields as create record action
<img width="546" height="823" alt="Capture d’écran 2025-10-30 à 10 00
04"
src="https://github.com/user-attachments/assets/87141a47-946f-4604-be55-f4c21ff4a3d8"
/>
2025-10-30 13:36:16 +01:00
Thomas TrompetteGitHubgreptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
When using primitive types such as array, number and boolean, we display
a text field in filters because fieldmetadataId is empty. We should
instead support these as we would do for our own fields.
Adding also a fix for https://github.com/twentyhq/twenty/issues/15282
---------
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
This PR implements Sentry's AI agent monitoring by:
- Configuring vercelAIIntegration with recordInputs and recordOutputs
options
- Adding sendDefaultPii to Sentry.init() for better debugging
- Creating a shared AI_TELEMETRY_CONFIG constant to DRY up the telemetry
configuration
- Adding experimental_telemetry to all AI SDK calls (generateText,
generateObject, streamText)
All AI operations are now fully monitored in Sentry with complete
input/output recording for debugging and performance analysis.
Note: Currently on Sentry v9.26.0, which is compatible with this
implementation. No breaking changes from the v9-to-v10 migration guide
were found in the codebase.
