The `ChatMessageApi` (`POST /console/api/apps/{app_id}/chat-messages`) and
`ModelConfigResource` (`POST /console/api/apps/{app_id}/model-config`)
endpoints do not properly validate user permissions, allowing users without `editor`
permission to access restricted functionality.
This PR addresses this issue by adding proper permission check.
- Remove triggered_by field from WorkflowWebhookTrigger model
- Replace manual webhook creation/deletion APIs with automatic sync via WebhookService
- Keep only GET API for retrieving webhook information
- Use same webhook ID for both debug and production environments (differentiated by endpoint)
- Add sync_webhook_relationships to automatically manage webhook lifecycle
- Update tests to remove triggered_by references
- Clean up unused imports and fix type checking issues
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Modified `PluginTriggerApi` to accept `trigger_name` as a JSON argument and return encoded plugin triggers.
- Updated `WorkflowPluginTrigger` model to replace `trigger_id` with `trigger_name` for better clarity.
- Adjusted `WorkflowPluginTriggerService` to handle the new `trigger_name` field and ensure proper error handling for subscriptions.
- Enhanced `workflow_trigger_fields` to include `trigger_name` in the plugin trigger schema.
This change improves the API's clarity and aligns the model with the updated naming conventions.
- Renamed `TriggerSubscriptionBuilderRequestLogsApi` to `TriggerSubscriptionBuilderLogsApi` for clarity.
- Updated the API endpoint to retrieve logs for subscription builders.
- Enhanced logging functionality in `TriggerSubscriptionBuilderService` to append and list logs more effectively.
- Refactored trigger processing tasks to improve naming consistency and clarity in logging.
🤖 Generated with [Claude Code](https://claude.ai/code)
- Add new workflow plugin trigger service for managing plugin-based triggers
- Implement trigger provider encryption utilities for secure credential storage
- Add custom trigger errors module for better error handling
- Refactor trigger provider and manager classes for improved plugin integration
- Update API endpoints to support plugin trigger workflows
- Add database migration for plugin trigger workflow support
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Deleted the plugin_trigger migration file as it is no longer needed in the codebase.
- Updated model imports in `__init__.py` to include new trigger-related classes for better organization.
- Remove the debug endpoint for cleaner API structure
- Add support for TRIGGER_PLUGIN in NodeType enumeration
- Implement WorkflowPluginTrigger model to map plugin triggers to workflow nodes
- Enhance TriggerService to process plugin triggers and store trigger data in Redis
- Update node mapping to include TriggerPluginNode for workflow execution
Co-authored-by: Claude <noreply@anthropic.com>
- Refactor trigger provider classes to improve naming consistency, including renaming classes for subscription management
- Implement new TriggerSubscriptionBuilderService for creating and verifying subscription builders
- Update API endpoints to support subscription builder creation and verification
- Enhance data models to include new attributes for subscription builders
- Remove the deprecated TriggerSubscriptionValidationService to streamline the codebase
Co-authored-by: Claude <noreply@anthropic.com>
- Remove unused imports in trigger-related files for better clarity and maintainability
- Streamline import statements across various modules to enhance code quality
Co-authored-by: Claude <noreply@anthropic.com>
- Refactor trigger provider classes to improve naming consistency and clarity
- Introduce new methods for managing trigger subscriptions, including validation and dispatching
- Update API endpoints to reflect changes in subscription handling
- Implement logging and request management for endpoint interactions
- Enhance data models to support subscription attributes and lifecycle management
Co-authored-by: Claude <noreply@anthropic.com>
- Rename classes and methods to reflect the transition from credentials to subscriptions
- Update API endpoints for managing trigger subscriptions
- Modify data models and entities to support subscription attributes
- Enhance service methods for listing, adding, updating, and deleting subscriptions
- Adjust encryption utilities to handle subscription data
Co-authored-by: Claude <noreply@anthropic.com>
- Remove unused classes and imports in encryption utilities
- Simplify method signatures for better readability
- Enhance code quality by adding newlines for clarity
- Update tests to reflect changes in import paths
Co-authored-by: Claude <noreply@anthropic.com>
The `Account._current_tenant` object is loaded by a database session (typically `db.session`) whose lifetime
is not aligned with the Account model instance. This misalignment causes a `DetachedInstanceError` to be raised
when accessing attributes of `Account._current_tenant` after the original session has been closed.
To resolve this issue, we now reload the tenant object with `expire_on_commit=False`, ensuring the tenant remains
accessible even after the session is closed.
refactor(api): Separate SegmentType for Integer/Float to Enable Pydantic Serialization (#22025)
This PR addresses serialization issues in the VariablePool model by separating the `value_type` tags for `IntegerSegment`/`FloatSegment` and `IntegerVariable`/`FloatVariable`. Previously, both Integer and Float types shared the same `SegmentType.NUMBER` tag, causing conflicts during serialization.
Key changes:
- Introduce distinct `value_type` tags for Integer and Float segments/variables
- Add `VariableUnion` and `SegmentUnion` types for proper type discrimination
- Leverage Pydantic's discriminated union feature for seamless serialization/deserialization
- Enable accurate serialization of data structures containing these types
Closes#22024.
This pull request introduces a feature aimed at improving the debugging experience during workflow editing. With the addition of variable persistence, the system will automatically retain the output variables from previously executed nodes. These persisted variables can then be reused when debugging subsequent nodes, eliminating the need for repetitive manual input.
By streamlining this aspect of the workflow, the feature minimizes user errors and significantly reduces debugging effort, offering a smoother and more efficient experience.
Key highlights of this change:
- Automatic persistence of output variables for executed nodes.
- Reuse of persisted variables to simplify input steps for nodes requiring them (e.g., `code`, `template`, `variable_assigner`).
- Enhanced debugging experience with reduced friction.
Closes#19735.
- Add `node_execution_id` column to `WorkflowDraftVariable`, allowing efficient implementation of
the "Reset to last run value" feature.
- Add additional index for `WorkflowNodeExecutionModel` to improve the performance of last run lookup.
Closes#20745.
Currently, `WorkflowNodeExecution.execution_metadata_dict` returns `None` when metadata is absent in the database. This requires all callers to perform `None` checks when processing metadata, leading to more complex caller-side logic.
This pull request updates the `execution_metadata_dict` method to return an empty dictionary instead of `None` when metadata is absent. This change would simplify the caller logic, as it removes the need for explicit `None` checks and provides a more consistent data structure to work with.
- Introduce `WorkflowDraftVariable` model and the corresponding migration.
- Implement `EnumText`, a custom column type for SQLAlchemy designed
to work seamlessly with enumeration classes based on `StrEnum`.
Alembic's offline mode generates SQL from SQLAlchemy migration operations,
providing developers with a clear view of database schema changes without
requiring an active database connection.
However, some migration versions (specifically bbadea11becb and d7999dfa4aae)
were performing database schema introspection, which fails in offline mode
since it requires an actual database connection.
This commit:
- Adds offline mode support by detecting context.is_offline_mode()
- Skips introspection steps when in offline mode
- Adds warning messages in SQL output to inform users that assumptions were made
- Prompts users to review the generated SQL for accuracy
These changes ensure migrations work consistently in both online and offline modes.
Close#19284.
QuantumGhost