fix(gemini): map any count_tokens translation failure to a 400 error response

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

litellm/llms/gemini/count_tokens/transformation.py

@@ -442,7 +442,7 @@ def build_count_tokens_payload(
         if _has_anthropic_shape(system=system, tools=tools, messages=messages):
             return _build_anthropic_payload(model=model, messages=messages, system=system, tools=tools)
         return _build_openai_payload(model=model, messages=messages, system=system, tools=tools)
-    except (KeyError, TypeError, ValueError) as e:
+    except Exception as e:  # noqa: BLE001  # translation is pure; any failure is untranslatable input
         return InvalidCountTokensRequest(message=f"Invalid token count request: {e!r}")
 
 

tests/test_litellm/llms/gemini/test_gemini_common_utils.py

@@ -259,14 +259,21 @@ class TestGoogleAIStudioTokenCounter:
         assert result.error_message is not None
 
     @pytest.mark.asyncio
-    async def test_count_tokens_translation_error_falls_back(self):
+    @pytest.mark.parametrize(
+        "bad_messages",
+        [
+            [{"role": "tool", "content": "orphaned result", "tool_call_id": "missing-call"}],
+            [{"role": "user", "content": [{"type": "text", "text": 123}]}],
+        ],
+    )
+    async def test_count_tokens_translation_error_falls_back(self, bad_messages):
         """Malformed message shapes surface as a 400 error TokenCountResponse so
         the proxy falls back instead of 500ing."""
         token_counter = GoogleAIStudioTokenCounter()
 
         result = await token_counter.count_tokens(
             model_to_use="gemini-2.5-flash",
-            messages=[{"role": "user", "content": [{"type": "text", "text": 123}]}],
+            messages=bad_messages,
             contents=None,
             deployment={"litellm_params": {"api_key": "test-key"}},
             request_model="gemini/gemini-2.5-flash",