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.
- Added 'type' field to all node data configurations in test files
- Fixed test_code.py: added 'type: code' to all code node configs
- Fixed test_http.py: added 'type: http-request' to all HTTP node configs
- Fixed test_template_transform.py: added 'type: template-transform' to template node config
- Fixed test_tool.py: added 'type: tool' to all tool node configs
- Added setup_code_executor_mock fixture to test_execute_code_scientific_notation
These changes fix the ValueError: 'Node X missing or invalid type information' errors
that were occurring due to changes in the node factory validation requirements.
- Fixed isinstance() checks to properly handle None values by checking None separately
- Fixed typo in STRING type validation where 'output_name' was hardcoded as string instead of variable
- Updated error message format to be consistent and more informative
- Updated test assertion to match new error message format
This commit introduces a background task that automatically deletes `WorkflowDraftVariable` records when
their associated workflow apps are deleted.
Additionally, it adds a new cleanup script
`cleanup-orphaned-draft-variables` to remove existing orphaned draft variables from the database.
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.
- Extract methods used by `ParameterExtractorNode` from `LLMNode` into a separate file.
- Convert `ParameterExtractorNode` into a subclass of `BaseNode`.
- Refactor code referencing the extracted methods to ensure functionality and clarity.
- Fixes the issue that `ParameterExtractorNode` returns error when executed.
- Fix relevant test cases.
Closes#20840.
