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.

api/core/workflow/graph_engine/entities/graph_runtime_state.py

@@ -17,8 +17,12 @@ class GraphRuntimeState(BaseModel):
     """total tokens"""
     llm_usage: LLMUsage = LLMUsage.empty_usage()
     """llm usage info"""
+
+    # The `outputs` field stores the final output values generated by executing workflows or chatflows.
+    #
+    # Note: Since the type of this field is `dict[str, Any]`, its values may not remain consistent
+    # after a serialization and deserialization round trip.
     outputs: dict[str, Any] = {}
-    """outputs"""
 
     node_run_steps: int = 0
     """node run steps"""