fix(vertex_ai): convert messages to contents in gemini count_tokens

acount_tokens passed contents=None to the Vertex Gemini countTokens
endpoint when called with messages=, causing a silent zero token count.
The Gemini branch of VertexAITokenCounter.count_tokens never read the
messages parameter, so the request body was {"contents": null}, which
Vertex accepts with HTTP 200 and no totalTokens field.

Convert messages to Gemini contents format using the existing
_gemini_convert_messages_with_history helper when contents is None.
Treat a response without totalTokens as a failure so the caller falls
back to local token counting instead of returning a silent zero.

Fixes #36921

litellm/llms/vertex_ai/common_utils.py

@@ -1164,21 +1164,29 @@ class VertexAITokenCounter(BaseTokenCounter):
                     original_response=result,
                 )
         else:
-            # Use standard Vertex AI (Gemini) token counter
             from litellm.llms.vertex_ai.count_tokens.handler import VertexAITokenCounter
+            from litellm.llms.vertex_ai.gemini.transformation import (
+                _gemini_convert_messages_with_history,
+            )
+
+            resolved_contents: Final = (
+                contents
+                if contents is not None
+                else _gemini_convert_messages_with_history(messages=messages or [])
+            )
 
             count_tokens_params: Final = {
                 "model": model_to_use,
-                "contents": contents,
+                "contents": resolved_contents,
             }
             count_tokens_params_request.update(count_tokens_params)
             result = await VertexAITokenCounter().acount_tokens(
                 **count_tokens_params_request,
             )
 
-            if result is not None:
+            if result is not None and "totalTokens" in result:
                 return TokenCountResponse(
-                    total_tokens=result.get("totalTokens", 0),
+                    total_tokens=result["totalTokens"],
                     request_model=request_model,
                     model_used=model_to_use,
                     tokenizer_type=result.get("tokenizer_used", ""),

tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py

@@ -1275,6 +1275,85 @@ async def test_vertex_ai_token_counter_routes_gemini_models():
         assert result.total_tokens == 50
 
 
+@pytest.mark.asyncio
+async def test_vertex_ai_token_counter_converts_messages_to_contents_for_gemini():
+    """
+    Regression test for #36921: acount_tokens passed contents=None to the
+    Gemini countTokens endpoint when called with messages=, causing a
+    silent zero token count. Verify messages are converted to Gemini
+    contents format when contents is None.
+    """
+    from unittest.mock import patch
+
+    from litellm.llms.vertex_ai.common_utils import VertexAITokenCounter
+
+    token_counter = VertexAITokenCounter()
+
+    with patch(
+        "litellm.llms.vertex_ai.count_tokens.handler.VertexAITokenCounter.acount_tokens"
+    ) as mock_acount_tokens:
+        mock_acount_tokens.return_value = {
+            "totalTokens": 42,
+            "tokenizer_used": "gemini",
+        }
+
+        await token_counter.count_tokens(
+            model_to_use="gemini-2.5-flash",
+            messages=[{"role": "user", "content": "Hello, how are you?"}],
+            contents=None,
+            deployment={
+                "litellm_params": {
+                    "vertex_project": "test-project",
+                    "vertex_location": "us-central1",
+                }
+            },
+            request_model="vertex_ai/gemini-2.5-flash",
+        )
+
+        mock_acount_tokens.assert_called_once()
+        call_kwargs = mock_acount_tokens.call_args.kwargs
+        passed_contents = call_kwargs["contents"]
+        assert passed_contents is not None
+        assert isinstance(passed_contents, list)
+        assert len(passed_contents) >= 1
+        assert "parts" in passed_contents[0]
+
+
+@pytest.mark.asyncio
+async def test_vertex_ai_token_counter_returns_none_when_api_omits_total_tokens():
+    """
+    Regression test for #36921: Vertex returns HTTP 200 with no totalTokens
+    when contents is null. The old code read totalTokens with a default of 0
+    and returned a silent zero. Verify we now return None so the caller falls
+    back to local token counting.
+    """
+    from unittest.mock import patch
+
+    from litellm.llms.vertex_ai.common_utils import VertexAITokenCounter
+
+    token_counter = VertexAITokenCounter()
+
+    with patch(
+        "litellm.llms.vertex_ai.count_tokens.handler.VertexAITokenCounter.acount_tokens"
+    ) as mock_acount_tokens:
+        mock_acount_tokens.return_value = {"tokenizer_used": "gemini"}
+
+        result = await token_counter.count_tokens(
+            model_to_use="gemini-2.5-flash",
+            messages=[{"role": "user", "content": "Hello"}],
+            contents=None,
+            deployment={
+                "litellm_params": {
+                    "vertex_project": "test-project",
+                    "vertex_location": "us-central1",
+                }
+            },
+            request_model="vertex_ai/gemini-2.5-flash",
+        )
+
+        assert result is None
+
+
 @pytest.mark.asyncio
 async def test_vertex_ai_partner_model_detection():
     """