fix(LiteLlm): add fallback user message to prevent empty content error with include_contents='none'

src/google/adk/models/lite_llm.py

@@ -824,6 +824,17 @@ async def generate_content_async(
         _get_completion_inputs(llm_request)
     )
 
+    # Fix for include_contents='none' resulting in empty content error
+    # Ensure messages list is not empty (aligns with _maybe_append_user_content fallback)
+    if not messages:
+        messages = [
+            ChatCompletionUserMessage(
+                role="user",
+                content="Handle the requests as specified in the System Instruction."
+            )
+        ]
+
+
     if "functions" in self._additional_args:
       # LiteLLM does not support both tools and functions together.
       tools = None

tests/integration/models/test_lite_llm.py

@@ -0,0 +1,224 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Tests for LiteLlm model with include_contents='none'."""
+
+import pytest
+from unittest.mock import AsyncMock, patch
+
+from google.adk.models.lite_llm import LiteLlm
+from google.adk.models.llm_request import LlmRequest
+from google.genai import types
+from litellm import ChatCompletionMessageToolCall, Function
+
+
+@pytest.mark.asyncio
+async def test_include_contents_none_with_fallback():
+    """Test that LiteLlm handles include_contents='none' without empty content error."""
+
+    # Create a minimal LlmRequest with no contents
+    config = types.GenerateContentConfig(
+        system_instruction="Continue the phrase of the last agent with a short sentence"
+    )
+
+    llm_request = LlmRequest(
+        contents=[],  # Empty contents simulating include_contents='none'
+        config=config
+    )
+
+    # Use actual dict instead of MagicMock for proper serialization testing
+    mock_response = {
+        "choices": [{
+            "message": {
+                "content": "This is a test response.",
+                "tool_calls": None
+            },
+            "finish_reason": "stop"
+        }],
+        "usage": {
+            "prompt_tokens": 10,
+            "completion_tokens": 5,
+            "total_tokens": 15
+        }
+    }
+
+    # Initialize LiteLlm model
+    model = LiteLlm(model="gemini/gemini-2.0-flash")
+
+    # Mock the acompletion method
+    with patch.object(model.llm_client, 'acompletion', new_callable=AsyncMock) as mock_acompletion:
+        mock_acompletion.return_value = mock_response
+
+        # This should not raise an error about empty content
+        # Instead, it should add fallback content
+        response_generator = model.generate_content_async(llm_request, stream=False)
+
+        # Verify we can get a response without error
+        response = None
+        async for resp in response_generator:
+            response = resp
+            break
+
+        # Assert response is not None and has expected structure
+        assert response is not None
+        assert response.content is not None
+        assert response.content.role == "model"
+
+        # Verify that acompletion was called with non-empty messages
+        call_args = mock_acompletion.call_args
+        messages = call_args.kwargs.get('messages', [])
+        assert len(messages) > 0, "Messages should not be empty"
+
+        # Verify the fallback message is present
+        user_messages = [m for m in messages if m.get('role') == 'user']
+        assert len(user_messages) > 0, "Should have at least one user message"
+        assert "Handle the requests as specified in the System Instruction" in str(user_messages[0].get('content', ''))
+
+
+@pytest.mark.asyncio
+async def test_include_contents_none_with_tools():
+    """Test that LiteLlm handles include_contents='none' with tools."""
+
+    # Create a function declaration
+    function_decl = types.FunctionDeclaration(
+        name="get_weather",
+        description="Get weather for a city",
+        parameters=types.Schema(
+            type=types.Type.OBJECT,
+            properties={
+                "city": types.Schema(type=types.Type.STRING, description="City name")
+            },
+            required=["city"]
+        )
+    )
+
+    config = types.GenerateContentConfig(
+        system_instruction="You are a helpful assistant",
+        tools=[types.Tool(function_declarations=[function_decl])]
+    )
+
+    llm_request = LlmRequest(
+        contents=[],  # Empty contents
+        config=config
+    )
+
+    # Create proper tool call object for realistic testing
+    mock_tool_call = ChatCompletionMessageToolCall(
+        type="function",
+        id="call_123",
+        function=Function(
+            name="get_weather",
+            arguments='{"city": "New York"}'
+        )
+    )
+
+    # Use actual dict response structure
+    mock_response = {
+        "choices": [{
+            "message": {
+                "content": None,
+                "tool_calls": [mock_tool_call]
+            },
+            "finish_reason": "tool_calls"
+        }],
+        "usage": {
+            "prompt_tokens": 15,
+            "completion_tokens": 10,
+            "total_tokens": 25
+        }
+    }
+
+    model = LiteLlm(model="gemini/gemini-2.0-flash")
+
+    # Mock the acompletion method
+    with patch.object(model.llm_client, 'acompletion', new_callable=AsyncMock) as mock_acompletion:
+        mock_acompletion.return_value = mock_response
+
+        # Should handle empty contents gracefully
+        response_generator = model.generate_content_async(llm_request, stream=False)
+
+        response = None
+        async for resp in response_generator:
+            response = resp
+            break
+
+        assert response is not None
+        assert response.content is not None
+
+        # Verify that acompletion was called with non-empty messages
+        call_args = mock_acompletion.call_args
+        messages = call_args.kwargs.get('messages', [])
+        assert len(messages) > 0, "Messages should not be empty with tools"
+
+        # Verify tools were passed
+        tools = call_args.kwargs.get('tools', None)
+        assert tools is not None, "Tools should be passed to acompletion"
+        assert len(tools) > 0, "Should have at least one tool"
+
+
+@pytest.mark.asyncio
+async def test_include_contents_with_existing_content():
+    """Test that LiteLlm works normally when contents are provided."""
+
+    config = types.GenerateContentConfig(
+        system_instruction="You are a helpful assistant"
+    )
+
+    # Provide actual content
+    llm_request = LlmRequest(
+        contents=[
+            types.Content(
+                role="user",
+                parts=[types.Part(text="What is the weather in Paris?")]
+            )
+        ],
+        config=config
+    )
+
+    mock_response = {
+        "choices": [{
+            "message": {
+                "content": "The weather in Paris is sunny.",
+                "tool_calls": None
+            },
+            "finish_reason": "stop"
+        }],
+        "usage": {
+            "prompt_tokens": 20,
+            "completion_tokens": 8,
+            "total_tokens": 28
+        }
+    }
+
+    model = LiteLlm(model="gemini/gemini-2.0-flash")
+
+    with patch.object(model.llm_client, 'acompletion', new_callable=AsyncMock) as mock_acompletion:
+        mock_acompletion.return_value = mock_response
+
+        response_generator = model.generate_content_async(llm_request, stream=False)
+
+        response = None
+        async for resp in response_generator:
+            response = resp
+            break
+
+        assert response is not None
+        assert response.content is not None
+        assert response.content.role == "model"
+
+        # Verify that user's actual content was used
+        call_args = mock_acompletion.call_args
+        messages = call_args.kwargs.get('messages', [])
+        user_messages = [m for m in messages if m.get('role') == 'user']
+        assert any("Paris" in str(m.get('content', '')) for m in user_messages)