chore: import upstream snapshot with attribution

tests/unittests/tools/retrieval/test_files_retrieval.py

@@ -0,0 +1,150 @@
+# Copyright 2026 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 FilesRetrieval tool."""
+
+import unittest.mock as mock
+
+from google.adk.tools.retrieval.files_retrieval import _get_default_embedding_model
+from google.adk.tools.retrieval.files_retrieval import FilesRetrieval
+from llama_index.core.base.embeddings.base import BaseEmbedding
+import pytest
+
+
+class MockEmbedding(BaseEmbedding):
+  """Mock embedding model for testing."""
+
+  def _get_query_embedding(self, query):
+    return [0.1] * 384
+
+  def _get_text_embedding(self, text):
+    return [0.1] * 384
+
+  async def _aget_query_embedding(self, query):
+    return [0.1] * 384
+
+  async def _aget_text_embedding(self, text):
+    return [0.1] * 384
+
+
+class TestFilesRetrieval:
+
+  def test_files_retrieval_with_custom_embedding(self, tmp_path):
+    """Test FilesRetrieval with custom embedding model."""
+    # Create test file
+    test_file = tmp_path / "test.txt"
+    test_file.write_text("This is a test document for retrieval testing.")
+
+    custom_embedding = MockEmbedding()
+    retrieval = FilesRetrieval(
+        name="test_retrieval",
+        description="Test retrieval tool",
+        input_dir=str(tmp_path),
+        embedding_model=custom_embedding,
+    )
+
+    assert retrieval.name == "test_retrieval"
+    assert retrieval.input_dir == str(tmp_path)
+    assert retrieval.retriever is not None
+
+  @mock.patch(
+      "google.adk.tools.retrieval.files_retrieval._get_default_embedding_model"
+  )
+  def test_files_retrieval_uses_default_embedding(
+      self, mock_get_default_embedding, tmp_path
+  ):
+    """Test FilesRetrieval uses default embedding when none provided."""
+    # Create test file
+    test_file = tmp_path / "test.txt"
+    test_file.write_text("This is a test document for retrieval testing.")
+
+    mock_embedding = MockEmbedding()
+    mock_get_default_embedding.return_value = mock_embedding
+
+    retrieval = FilesRetrieval(
+        name="test_retrieval",
+        description="Test retrieval tool",
+        input_dir=str(tmp_path),
+    )
+
+    mock_get_default_embedding.assert_called_once()
+    assert retrieval.name == "test_retrieval"
+    assert retrieval.input_dir == str(tmp_path)
+
+  def test_get_default_embedding_model_import_error(self):
+    """Test _get_default_embedding_model handles ImportError correctly."""
+    # Simulate the package not being installed by making import fail
+    import builtins
+
+    original_import = builtins.__import__
+
+    def mock_import(name, *args, **kwargs):
+      if name == "llama_index.embeddings.google_genai":
+        raise ImportError(
+            "No module named 'llama_index.embeddings.google_genai'"
+        )
+      return original_import(name, *args, **kwargs)
+
+    with mock.patch("builtins.__import__", side_effect=mock_import):
+      with pytest.raises(ImportError) as exc_info:
+        _get_default_embedding_model()
+
+      # The exception should be re-raised as our custom ImportError with helpful message
+      assert "llama-index-embeddings-google-genai package not found" in str(
+          exc_info.value
+      )
+      assert "pip install llama-index-embeddings-google-genai" in str(
+          exc_info.value
+      )
+
+  def test_get_default_embedding_model_success(self):
+    """Test _get_default_embedding_model returns Google embedding when available."""
+
+    # Mock the module creation to avoid import issues
+    mock_module = mock.MagicMock()
+    mock_embedding_instance = MockEmbedding()
+    mock_module.GoogleGenAIEmbedding.return_value = mock_embedding_instance
+
+    with mock.patch.dict(
+        "sys.modules", {"llama_index.embeddings.google_genai": mock_module}
+    ):
+      result = _get_default_embedding_model()
+
+      mock_module.GoogleGenAIEmbedding.assert_called_once_with(
+          model_name="gemini-embedding-2-preview",
+          embed_batch_size=1,
+      )
+      assert result == mock_embedding_instance
+
+  def test_backward_compatibility(self, tmp_path):
+    """Test that existing code without embedding_model parameter still works."""
+    # Create test file
+    test_file = tmp_path / "test.txt"
+    test_file.write_text("This is a test document for retrieval testing.")
+
+    with mock.patch(
+        "google.adk.tools.retrieval.files_retrieval._get_default_embedding_model"
+    ) as mock_get_default:
+      mock_get_default.return_value = MockEmbedding()
+
+      # This should work exactly like before - no embedding_model parameter
+      retrieval = FilesRetrieval(
+          name="test_retrieval",
+          description="Test retrieval tool",
+          input_dir=str(tmp_path),
+      )
+
+      assert retrieval.name == "test_retrieval"
+      assert retrieval.input_dir == str(tmp_path)
+      mock_get_default.assert_called_once()