sdks/python: address gemini comments

Author: moawnallah

CHANGES.md

@@ -75,9 +75,8 @@
 * X feature added (Java/Python) ([#X](https://github.com/apache/beam/issues/X)).
 * Python examples added for Milvus search enrichment handler on [Beam Website](https://beam.apache.org/documentation/transforms/python/elementwise/enrichment-milvus/)
   including jupyter notebook example (Python) ([#36176](https://github.com/apache/beam/issues/36176)).
-* Milvus sink I/O connector added (Python) ([#36702](
-  https://github.com/apache/beam/issues/36702)). Now Beam has full support for
-  Milvus integration including Milvus enrichment and sink operations.
+* Milvus sink I/O connector added (Python) ([#36702](https://github.com/apache/beam/issues/36702)).
+Now Beam has full support for Milvus integration including Milvus enrichment and sink operations.
 
 ## Breaking Changes
 

sdks/python/apache_beam/ml/rag/ingestion/milvus_search_it_test.py

@@ -370,10 +370,7 @@ def test_write_on_existent_collection_with_default_schema(self):
     for chunk in test_chunks:
       self.assertIn(chunk.id, result_by_id)
       result_item = result_by_id[chunk.id]
-      self.assertEqual(
-          result_item["content"],
-          chunk.content.text
-          if hasattr(chunk.content, 'text') else chunk.content)
+      self.assertEqual(result_item["content"], chunk.content.text)
       self.assertEqual(result_item["metadata"], chunk.metadata)
 
       # Verify embedding is present and has correct length.
@@ -388,11 +385,7 @@ def test_write_with_custom_column_specifications(self):
 
     custom_column_specs = [
         ColumnSpec("id", int, lambda chunk: int(chunk.id) if chunk.id else 0),
-        ColumnSpec(
-            "content",
-            str, lambda chunk: (
-                chunk.content.text
-                if hasattr(chunk.content, 'text') else chunk.content)),
+        ColumnSpec("content", str, lambda chunk: chunk.content.text),
         ColumnSpec("metadata", dict, lambda chunk: chunk.metadata or {}),
         ColumnSpec(
             "embedding",