feat: support nullable named function outputs (#4123)

Supports fully nullable named Function outputs while preserving the
distinction between a valid all-null struct and a null/unassigned
result.

## Concrete example

This UDF contract is now valid:

```python
@udf(
    input_schema=pa.schema([
        pa.field("text", pa.string(), nullable=False),
    ]),
    output_schema=pa.schema([
        pa.field(
            "embedding",
            pa.list_(pa.float32(), list_size=1024),
            nullable=True,
        ),
        pa.field("embedding_failure_reason", pa.string(), nullable=True),
        pa.field("embedding_failure_code", pa.int32(), nullable=True),
    ]),
)
def embed(text):
    ...
```

A successful row can return:

```text
embedding = [0.12, ...]
embedding_failure_reason = NULL
embedding_failure_code = NULL
```

If remote inference still fails after retries, it can return:

```text
embedding = NULL
embedding_failure_reason = "HTTP 429: rate limited"
embedding_failure_code = 429
```

An all-null but valid result struct is also assigned; it is not mistaken
for unfinished work.

## Binding shapes

- Mapping the result to one output column stores the `StructArray`
directly, including its parent validity bitmap.
- Flattening the result into top-level columns stores the parent
validity in a reserved internal nullable Boolean assignment column that
is not part of the UDF result mapping.
- An outer null struct remains unassigned/skipped. A valid struct
remains assigned regardless of which child fields are null.
- Scalar Function outputs remain non-nullable.

The contract is preserved through Python registration, Rust application
planning, persisted `FunctionBinding` metadata, schema revalidation, and
Enterprise execution.

python/python/tests/test_first_class_function_slice2.py

@@ -850,6 +850,43 @@ def test_named_struct_function_can_include_a_blob_result_field():
     ]
 
 
+def test_named_struct_function_preserves_nullable_result_fields():
+    @udf(
+        input_schema=pa.schema([pa.field("value", pa.int64(), nullable=False)]),
+        output_schema=pa.schema(
+            [
+                pa.field("result", pa.int64(), nullable=True),
+                pa.field("failure_code", pa.int32(), nullable=False),
+            ]
+        ),
+    )
+    def nullable_result(value):
+        return {"result": value, "failure_code": 0}
+
+    output = nullable_result.registration_request.signature.output
+    assert [(field.name, field.nullable) for field in output.fields] == [
+        ("result", True),
+        ("failure_code", False),
+    ]
+
+    @udf(
+        input_schema=pa.schema([pa.field("value", pa.int64(), nullable=False)]),
+        output_schema=pa.schema(
+            [
+                pa.field("result", pa.int64(), nullable=True),
+                pa.field("failure_code", pa.int32(), nullable=True),
+            ]
+        ),
+    )
+    def all_nullable(value):
+        return {"result": value, "failure_code": None}
+
+    assert all(
+        field.nullable
+        for field in all_nullable.registration_request.signature.output.fields
+    )
+
+
 def test_metadata_marked_blob_field_uses_the_semantic_type():
     extension = lancedb.blob("image", nullable=False).type
     storage = (