Remove max_execution_time and max_execution_steps from ExecutionContext and GraphEngine since these limits are now handled by ExecutionLimitsLayer. This follows the separation of concerns principle by keeping execution limits as a cross-cutting concern handled by layers rather than embedded in core engine components.
Changes:
- Remove max_execution_time and max_execution_steps from ExecutionContext
- Remove these parameters from GraphEngine.__init__()
- Remove max_execution_time from Dispatcher
- Update workflow_entry.py to no longer pass these parameters
- Update all tests to remove these parameters
Remove worker idle/active callbacks that caused severe lock contention.
Instead, use sampling-based monitoring where worker states are queried
on-demand during scaling decisions. This eliminates the performance
bottleneck caused by workers acquiring locks 10+ times per second.
Changes:
- Remove callback parameters from Worker class
- Add properties to expose worker idle state directly
- Update WorkerPool to query worker states without callbacks
- Maintain scaling functionality with better performance
- Replace direct field access with private attributes and property decorators
- Implement deep copy protection for mutable objects (dict, LLMUsage)
- Add helper methods: set_output(), get_output(), update_outputs()
- Add increment_node_run_steps() and add_tokens() convenience methods
- Update loop_node and event_handlers to use new accessor methods
- Add comprehensive unit tests for immutability and validation
- Ensure backward compatibility with existing property access patterns
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.
-LAN-