fix: Refactor LiteLlm check to avoid ImportError

The `can_use_output_schema_with_tools` function now checks if a model is a LiteLlm instance by inspecting its type's Method Resolution Order, rather than directly importing `LiteLlm`

Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 882253446

src/google/adk/utils/output_schema_utils.py

@@ -36,10 +36,14 @@ def can_use_output_schema_with_tools(model: Union[str, BaseLlm]) -> bool:
   #   tool_choice enforcement
   # This is strictly more reliable than the SetModelResponseTool
   # prompt-based workaround.
-  from ..models.lite_llm import LiteLlm
+  if not isinstance(model, str):
+    try:
+      from ..models.lite_llm import LiteLlm
+    except ImportError:
+      LiteLlm = None
 
-  if isinstance(model, LiteLlm):
-    return True
+    if LiteLlm is not None and isinstance(model, LiteLlm):
+      return True
 
   model_string = model if isinstance(model, str) else model.model
 

tests/unittests/utils/test_output_schema_utils.py

@@ -12,10 +12,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from __future__ import annotations
+
+import builtins
+import importlib.util
+import sys
+from typing import Any
 
 from google.adk.models.anthropic_llm import Claude
+from google.adk.models.base_llm import BaseLlm
 from google.adk.models.google_llm import Gemini
-from google.adk.models.lite_llm import LiteLlm
 from google.adk.utils.output_schema_utils import can_use_output_schema_with_tools
 import pytest
 
@@ -38,19 +44,51 @@ import pytest
         (Claude(model="claude-3.7-sonnet"), "1", False),
         (Claude(model="claude-3.7-sonnet"), "0", False),
         (Claude(model="claude-3.7-sonnet"), None, False),
-        (LiteLlm(model="openai/gpt-4o"), "1", True),
-        (LiteLlm(model="openai/gpt-4o"), "0", True),
-        (LiteLlm(model="openai/gpt-4o"), None, True),
-        (LiteLlm(model="anthropic/claude-3.7-sonnet"), None, True),
-        (LiteLlm(model="fireworks_ai/llama-v3p1-70b"), None, True),
     ],
 )
 def test_can_use_output_schema_with_tools(
-    monkeypatch, model, env_value, expected
-):
+    monkeypatch: pytest.MonkeyPatch,
+    model: str | BaseLlm,
+    env_value: str | None,
+    expected: bool,
+) -> None:
   """Test can_use_output_schema_with_tools."""
   if env_value is not None:
     monkeypatch.setenv("GOOGLE_GENAI_USE_VERTEXAI", env_value)
   else:
     monkeypatch.delenv("GOOGLE_GENAI_USE_VERTEXAI", raising=False)
   assert can_use_output_schema_with_tools(model) == expected
+
+
+def test_can_use_output_schema_with_tools_with_litellm_model() -> None:
+  """Test LiteLlm detection when the optional module is available."""
+  if importlib.util.find_spec("litellm") is None:
+    pytest.skip("litellm is not installed")
+
+  from google.adk.models.lite_llm import LiteLlm
+
+  assert can_use_output_schema_with_tools(LiteLlm(model="openai/gpt-4o"))
+
+
+def test_can_use_output_schema_with_tools_without_litellm_module(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+  """Test optional LiteLlm import failures do not affect other models."""
+  original_import = builtins.__import__
+
+  def _failing_import(
+      name: str,
+      globals_dict: dict[str, Any] | None = None,
+      locals_dict: dict[str, Any] | None = None,
+      fromlist: tuple[str, ...] = (),
+      level: int = 0,
+  ) -> Any:
+    if name.endswith("lite_llm"):
+      raise ImportError("litellm not installed")
+    return original_import(name, globals_dict, locals_dict, fromlist, level)
+
+  monkeypatch.delenv("GOOGLE_GENAI_USE_VERTEXAI", raising=False)
+  monkeypatch.delitem(sys.modules, "google.adk.models.lite_llm", raising=False)
+  monkeypatch.setattr(builtins, "__import__", _failing_import)
+
+  assert not can_use_output_schema_with_tools(Claude(model="claude-3.7-sonnet"))