refactor(api): Separate SegmentType for Integer/Float to Enable Pydantic Serialization (#22025)
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.
feat(api): Explicitly define version method for all BaseNode subclasses (#21443)
This PR addresses issue #21441 by implementing explicit `version` method definitions for all `BaseNode` subclasses to improve code maintainability.
### Changes
Added explicit `version` method definitions for all `BaseNode` subclasses:
- `QuestionClassifierNode`
- `KnowledgeRetrievalNode`
- `AgentNode`
Added comprehensive test suite to validate:
1. All subclasses of `BaseNode` have explicitly defined `version` method
2. All subclasses have required `_node_type` property
3. The `(node_type, node_version)` combination is unique across all subclasses
feat: Persist Variables for Enhanced Debugging Workflow (#20699)
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.
liujin-patsnap
baonudesifeizhai
Yongtao Huang
kenwoodjw
znn
NeatGuyCoding
呆萌闷油瓶
little_huang
Asuka Minato
Yeuoly
jiangbo721
crazywoola
Will
quicksand
Novice
-LAN-
Kalo Chin
Maries
Chieh Wang
QuantumGhost
湛露先生
Jacky Wu
Davide Delbianco
Ganondorf
Novice
efrey kong
Han