fix: #3065 LiteLLM Model Override Not Working with llm_request.model

tests/unittests/models/test_litellm.py

@@ -19,7 +19,6 @@
 import warnings
 
 from google.adk.models.lite_llm import _content_to_message_param
-from google.adk.models.lite_llm import _FINISH_REASON_MAPPING
 from google.adk.models.lite_llm import _function_declaration_to_tool_param
 from google.adk.models.lite_llm import _get_content
 from google.adk.models.lite_llm import _message_to_generate_content_response
@@ -2019,114 +2018,4 @@ def test_non_gemini_litellm_no_warning():
     warnings.simplefilter("always")
     # Test with non-Gemini model
     LiteLlm(model="openai/gpt-4o")
-    assert len(w) == 0
-
-
-@pytest.mark.parametrize(
-    "finish_reason,response_content,expected_content,has_tool_calls",
-    [
-        ("length", "Test response", "Test response", False),
-        ("stop", "Complete response", "Complete response", False),
-        (
-            "tool_calls",
-            "",
-            "",
-            True,
-        ),
-        ("content_filter", "", "", False),
-    ],
-    ids=["length", "stop", "tool_calls", "content_filter"],
-)
-@pytest.mark.asyncio
-async def test_finish_reason_propagation(
-    mock_acompletion,
-    lite_llm_instance,
-    finish_reason,
-    response_content,
-    expected_content,
-    has_tool_calls,
-):
-  """Test that finish_reason is properly propagated from LiteLLM response."""
-  tool_calls = None
-  if has_tool_calls:
-    tool_calls = [
-        ChatCompletionMessageToolCall(
-            type="function",
-            id="test_id",
-            function=Function(
-                name="test_function",
-                arguments='{"arg": "value"}',
-            ),
-        )
-    ]
-
-  mock_response = ModelResponse(
-      choices=[
-          Choices(
-              message=ChatCompletionAssistantMessage(
-                  role="assistant",
-                  content=response_content,
-                  tool_calls=tool_calls,
-              ),
-              finish_reason=finish_reason,
-          )
-      ]
-  )
-  mock_acompletion.return_value = mock_response
-
-  llm_request = LlmRequest(
-      contents=[
-          types.Content(
-              role="user", parts=[types.Part.from_text(text="Test prompt")]
-          )
-      ],
-  )
-
-  async for response in lite_llm_instance.generate_content_async(llm_request):
-    assert response.content.role == "model"
-    # Verify finish_reason is mapped to FinishReason enum
-    assert isinstance(response.finish_reason, types.FinishReason)
-    # Verify correct enum mapping using the actual mapping from lite_llm
-    assert response.finish_reason == _FINISH_REASON_MAPPING[finish_reason]
-    if expected_content:
-      assert response.content.parts[0].text == expected_content
-    if has_tool_calls:
-      assert len(response.content.parts) > 0
-      assert response.content.parts[-1].function_call.name == "test_function"
-
-  mock_acompletion.assert_called_once()
-
-
-@pytest.mark.asyncio
-async def test_finish_reason_unknown_maps_to_other(
-    mock_acompletion, lite_llm_instance
-):
-  """Test that unknown finish_reason values map to FinishReason.OTHER."""
-  mock_response = ModelResponse(
-      choices=[
-          Choices(
-              message=ChatCompletionAssistantMessage(
-                  role="assistant",
-                  content="Test response",
-              ),
-              finish_reason="unknown_reason_type",
-          )
-      ]
-  )
-  mock_acompletion.return_value = mock_response
-
-  llm_request = LlmRequest(
-      contents=[
-          types.Content(
-              role="user", parts=[types.Part.from_text(text="Test prompt")]
-          )
-      ],
-  )
-
-  async for response in lite_llm_instance.generate_content_async(llm_request):
-    assert response.content.role == "model"
-    # Unknown finish_reason should map to OTHER
-    assert isinstance(response.finish_reason, types.FinishReason)
-    assert response.finish_reason == types.FinishReason.OTHER
-
-  mock_acompletion.assert_called_once()
+    assert len(w) == 0