chore: import upstream snapshot with attribution

tests/unittests/agents/test_run_config.py

@@ -0,0 +1,139 @@
+# 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.
+
+import sys
+from unittest.mock import ANY
+from unittest.mock import patch
+import warnings
+
+from google.adk.agents.run_config import RunConfig
+from google.genai import types
+import pytest
+
+
+def test_validate_max_llm_calls_valid():
+  value = RunConfig.validate_max_llm_calls(100)
+  assert value == 100
+
+
+def test_validate_max_llm_calls_negative():
+  with patch("google.adk.agents.run_config.logger.warning") as mock_warning:
+    value = RunConfig.validate_max_llm_calls(-1)
+    mock_warning.assert_called_once_with(ANY)
+    assert value == -1
+
+
+def test_validate_max_llm_calls_warns_on_zero():
+  with patch("google.adk.agents.run_config.logger.warning") as mock_warning:
+    value = RunConfig.validate_max_llm_calls(0)
+    mock_warning.assert_called_once_with(ANY)
+    assert value == 0
+
+
+def test_validate_max_llm_calls_too_large():
+  with pytest.raises(
+      ValueError, match=f"max_llm_calls should be less than {sys.maxsize}."
+  ):
+    RunConfig.validate_max_llm_calls(sys.maxsize)
+
+
+def test_audio_transcription_configs_are_not_shared_between_instances():
+  config1 = RunConfig()
+  config2 = RunConfig()
+
+  # Validate output_audio_transcription
+  assert config1.output_audio_transcription is not None
+  assert config2.output_audio_transcription is not None
+  assert (
+      config1.output_audio_transcription
+      is not config2.output_audio_transcription
+  )
+
+  # Validate input_audio_transcription
+  assert config1.input_audio_transcription is not None
+  assert config2.input_audio_transcription is not None
+  assert (
+      config1.input_audio_transcription is not config2.input_audio_transcription
+  )
+
+
+def test_response_modalities_accepts_enum():
+  config = RunConfig(response_modalities=[types.Modality.AUDIO])
+  assert config.response_modalities == [types.Modality.AUDIO]
+  assert isinstance(config.response_modalities[0], types.Modality)
+
+
+def test_response_modalities_coerces_string_to_enum():
+  config = RunConfig(response_modalities=["AUDIO"])
+  assert config.response_modalities == [types.Modality.AUDIO]
+  assert isinstance(config.response_modalities[0], types.Modality)
+
+
+def test_response_modalities_coerces_lowercase_string_to_enum():
+  config = RunConfig(response_modalities=["audio"])
+  assert config.response_modalities == [types.Modality.AUDIO]
+  assert isinstance(config.response_modalities[0], types.Modality)
+
+
+def test_response_modalities_serialization_no_warning():
+  config = RunConfig(response_modalities=[types.Modality.AUDIO])
+  live_config = types.LiveConnectConfig()
+  live_config.response_modalities = config.response_modalities
+  with warnings.catch_warnings(record=True) as w:
+    warnings.simplefilter("always")
+    live_config.model_dump()
+    pydantic_warnings = [
+        x for x in w if "PydanticSerializationUnexpectedValue" in str(x.message)
+    ]
+    assert len(pydantic_warnings) == 0
+
+
+def test_avatar_config_initialization():
+  custom_avatar = types.CustomizedAvatar(
+      image_mime_type="image/jpeg", image_data=b"image_bytes"
+  )
+  avatar_config = types.AvatarConfig(
+      audio_bitrate_bps=128000,
+      video_bitrate_bps=1000000,
+      customized_avatar=custom_avatar,
+  )
+  run_config = RunConfig(avatar_config=avatar_config)
+
+  assert run_config.avatar_config == avatar_config
+  assert run_config.avatar_config.customized_avatar == custom_avatar
+  assert (
+      run_config.avatar_config.customized_avatar.image_mime_type == "image/jpeg"
+  )
+  assert run_config.avatar_config.customized_avatar.image_data == b"image_bytes"
+
+
+def test_avatar_config_with_name():
+  avatar_config = types.AvatarConfig(
+      audio_bitrate_bps=128000,
+      video_bitrate_bps=1000000,
+      avatar_name="test_avatar",
+  )
+  run_config = RunConfig(avatar_config=avatar_config)
+
+  assert run_config.avatar_config == avatar_config
+  assert run_config.avatar_config.avatar_name == "test_avatar"
+  assert run_config.avatar_config.customized_avatar is None
+
+
+def test_model_input_context_accepts_transient_contents():
+  context_content = types.UserContent("Relevant context for this turn")
+
+  run_config = RunConfig(model_input_context=[context_content])
+
+  assert run_config.model_input_context == [context_content]