fix: Refine Ollama content flattening and provider checks

- Stripping whitespace from custom LLM provider and model names when checking for "ollama_chat".
- Enhancing `_flatten_ollama_content` to correctly handle content that is None, a string, a dictionary, or an iterable (like a tuple) of content blocks, not just lists. This aligns with LiteLLM's `OpenAIMessageContent` type being an `Iterable`.

Close #3928

Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 845848017

src/google/adk/models/lite_llm.py

@@ -628,9 +628,12 @@ def _is_ollama_chat_provider(
     model: Optional[str], custom_llm_provider: Optional[str]
 ) -> bool:
   """Returns True when requests should be normalized for ollama_chat."""
-  if custom_llm_provider and custom_llm_provider.lower() == "ollama_chat":
+  if (
+      custom_llm_provider
+      and custom_llm_provider.strip().lower() == "ollama_chat"
+  ):
     return True
-  if model and model.lower().startswith("ollama_chat"):
+  if model and model.strip().lower().startswith("ollama_chat"):
     return True
   return False
 
@@ -644,11 +647,24 @@ def _flatten_ollama_content(
   join them with newlines, and fall back to a JSON string for non-text content.
   If both text and non-text parts are present, only the text parts are kept.
   """
-  if not isinstance(content, list):
+  if content is None or isinstance(content, str):
     return content
 
+  # `OpenAIMessageContent` is typed as `Iterable[...]` in LiteLLM. Some
+  # providers or LiteLLM versions may hand back tuples or other iterables.
+  if isinstance(content, dict):
+    try:
+      return json.dumps(content)
+    except TypeError:
+      return str(content)
+
+  try:
+    blocks = list(content)
+  except TypeError:
+    return str(content)
+
   text_parts = []
-  for block in content:
+  for block in blocks:
     if isinstance(block, dict) and block.get("type") == "text":
       text_value = block.get("text")
       if text_value:
@@ -658,9 +674,9 @@ def _flatten_ollama_content(
     return _NEW_LINE.join(text_parts)
 
   try:
-    return json.dumps(content)
+    return json.dumps(blocks)
   except TypeError:
-    return str(content)
+    return str(blocks)
 
 
 def _normalize_ollama_chat_messages(

tests/unittests/models/test_litellm.py

@@ -1549,6 +1549,17 @@ async def test_generate_content_async_custom_provider_flattens_content(
   assert "Describe this image." in message_content
 
 
+def test_flatten_ollama_content_accepts_tuple_blocks():
+  from google.adk.models.lite_llm import _flatten_ollama_content
+
+  content = (
+      {"type": "text", "text": "first"},
+      {"type": "text", "text": "second"},
+  )
+  flattened = _flatten_ollama_content(content)
+  assert flattened == "first\nsecond"
+
+
 @pytest.mark.asyncio
 async def test_content_to_message_param_user_message():
   content = types.Content(