Address PR feedback: Add _is_gemini_model helper, improve error handling, and add comprehensive tests

Co-Authored-By: Joe Moura <joao@crewai.com>

tests/test_gemini_html_template.py

@@ -51,3 +51,79 @@ def test_openrouter_gemini_empty_response_handling():
         # Verify that our fix works - empty string should be replaced with placeholder
         assert "Response processed successfully" in result
         assert "HTML template" in result
+
+
+def test_gemini_none_response_handling():
+    """Test that None responses are properly handled."""
+    llm = LLM(model="gemini/gemini-pro")
+    
+    # Create a mock response with None content
+    mock_response = MagicMock()
+    mock_response.choices = [MagicMock()]
+    mock_response.choices[0].message = MagicMock()
+    mock_response.choices[0].message.content = None
+    
+    # Mock litellm.completion to return our mock response
+    with patch('litellm.completion', return_value=mock_response):
+        # Call the non-streaming response handler directly
+        # None content should be converted to empty string and then handled
+        result = llm._handle_non_streaming_response({"model": "gemini/gemini-pro"})
+        
+        # Verify that our fix works - None should be converted to empty string
+        # and then handled as an empty string for Gemini models
+        assert "Response processed successfully" in result
+        assert "HTML template" in result
+
+
+@pytest.mark.parametrize("model_name,base_url", [
+    ("gemini/gemini-pro", None),
+    ("gemini-pro", None),
+    ("google/gemini-pro", None),
+    ("openrouter/google/gemini-pro", "https://openrouter.ai/api/v1"),
+    ("openrouter/gemini-pro", "https://openrouter.ai/api/v1"),
+])
+def test_various_gemini_configurations(model_name, base_url):
+    """Test different Gemini model configurations with the _is_gemini_model helper."""
+    # Create a mock LLM instance with the specified model and base URL
+    llm = LLM(model=model_name, base_url=base_url)
+    
+    # Verify that _is_gemini_model correctly identifies all these configurations
+    assert llm._is_gemini_model() is True
+    
+    # Create a mock response with empty content
+    mock_response = MagicMock()
+    mock_response.choices = [MagicMock()]
+    mock_response.choices[0].message = MagicMock()
+    mock_response.choices[0].message.content = ""
+    
+    # Mock litellm.completion to return our mock response
+    with patch('litellm.completion', return_value=mock_response):
+        # Call the non-streaming response handler directly
+        result = llm._handle_non_streaming_response({"model": model_name})
+        
+        # Verify that our fix works for all Gemini configurations
+        assert "Response processed successfully" in result
+        assert "HTML template" in result
+
+
+def test_non_gemini_model():
+    """Test that non-Gemini models don't get special handling for empty responses."""
+    # Create a mock LLM instance with a non-Gemini model
+    llm = LLM(model="gpt-4")
+    
+    # Verify that _is_gemini_model correctly identifies this as not a Gemini model
+    assert llm._is_gemini_model() is False
+    
+    # Create a mock response with empty content
+    mock_response = MagicMock()
+    mock_response.choices = [MagicMock()]
+    mock_response.choices[0].message = MagicMock()
+    mock_response.choices[0].message.content = ""
+    
+    # Mock litellm.completion to return our mock response
+    with patch('litellm.completion', return_value=mock_response):
+        # Call the non-streaming response handler directly
+        result = llm._handle_non_streaming_response({"model": "gpt-4"})
+        
+        # Verify that non-Gemini models just return the empty string
+        assert result == ""