Python: Fix build_model_schema using pydantic constraint as field description

python/semantic_kernel/schema/kernel_json_schema_builder.py

@@ -92,9 +92,9 @@ def build_model_schema(
                 if isinstance(field_info.metadata, dict):
                     field_description = field_info.metadata.get("description")
                 elif isinstance(field_info.metadata, list) and field_info.metadata:
-                    field_description = field_info.metadata[0]
-                elif hasattr(field_info, "description"):
-                    field_description = field_info.description
+                    field_description = next((item for item in field_info.metadata if isinstance(item, str)), None)
+                if field_description is None:
+                    field_description = getattr(field_info, "description", None)
             if not cls._is_optional(field_type):
                 required.append(field_name)
             properties[field_name] = cls.build(field_type, field_description, structured_output)

python/tests/unit/schema/test_schema_builder.py

@@ -8,7 +8,7 @@
 import pytest
 
 from semantic_kernel.connectors.utils.structured_output_schema import generate_structured_output_response_format_schema
-from semantic_kernel.kernel_pydantic import KernelBaseModel
+from semantic_kernel.kernel_pydantic import Field, KernelBaseModel
 from semantic_kernel.schema.kernel_json_schema_builder import KernelJsonSchemaBuilder
 
 
@@ -156,6 +156,26 @@ def test_build_model_schema():
     assert result == expected_schema
 
 
+def test_build_model_schema_with_constrained_field_with_description():
+    class Params(KernelBaseModel):
+        top_p: float = Field(default=0.9, ge=0.0, le=1.0, description="nucleus sampling")
+
+    schema = KernelJsonSchemaBuilder.build_model_schema(Params)
+
+    assert schema["properties"]["top_p"] == {"type": "number", "description": "nucleus sampling"}
+    json.dumps(schema)
+
+
+def test_build_model_schema_with_constrained_field_without_description():
+    class Params(KernelBaseModel):
+        top_p: float = Field(default=0.9, ge=0.0, le=1.0)
+
+    schema = KernelJsonSchemaBuilder.build_model_schema(Params)
+
+    assert schema["properties"]["top_p"] == {"type": "number"}
+    json.dumps(schema)
+
+
 def test_build_from_type_name():
     expected_schema = {"type": "string", "description": "A simple string"}
     result = KernelJsonSchemaBuilder.build_from_type_name("str", description="A simple string")