test: add comprehensive unit, integration, and e2e test suites

Introduce complete test coverage for the ARTEMIS platform across multiple layers: Unit tests: Add tests for agent nodes (Planner, Operator, Validator, Diagnoser, FlashRunner, Explorer), tools, utils (OCR/XML fusion, UI hierarchy), and data engine. Integration tests: Add live tool verification, reactive runner, IME, and standalone workflow tests. E2E tests: Add end-to-end scenario tests for media playback and failure recovery flows. Fixtures & mocks: Add mock inputs (audio, video, screenshot) and test utilities.
2026-08-13 12:18:32 -07:00
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commit 5d2283deaa
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+# 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 json
+from unittest.mock import MagicMock, Mock, patch
+from artemis.agents.summarizer.summarizer import SummarizerNode
+from artemis.context import ArtemisContext
+import pytest
+
+
+class DummyState:
+    def __init__(
+        self,
+        structured_decisions=None,
+        operator_raw_thinking=None,
+        operator_native_thinking=None,
+        last_execution_result=None,
+        current_step_id=None,
+    ):
+        self.structured_decisions = structured_decisions
+        self.operator_raw_thinking = operator_raw_thinking
+        self.operator_native_thinking = operator_native_thinking
+        self.last_execution_result = last_execution_result
+        self.current_step_id = current_step_id
+
+
+@pytest.fixture
+def mock_context():
+    ctx = Mock(spec=ArtemisContext)
+    ctx.device = None
+    ctx.data_engine = Mock()
+    ctx.background_tasks = []
+    return ctx
+
+
+@pytest.mark.asyncio
+async def test_summarizer_success(mock_context):
+    """Test that SummarizerNode successfully generates summary from raw thinking and execution result."""
+    decisions = json.dumps([{"action": "tap", "coordinates": [500, 600]}])
+    thinking = "The operator clicked the search button."
+    result = {
+        "status": "success",
+        "executed_actions": [{"action": "tap", "coordinates": [500, 600]}],
+    }
+
+    state = DummyState(
+        structured_decisions=decisions,
+        operator_raw_thinking=thinking,
+        last_execution_result=result,
+        current_step_id="12345678-1234-5678-1234-567812345678",
+    )
+
+    # Mock LLM response
+    mock_response = Mock()
+    mock_response.content = "Step completed successfully."
+    mock_llm = MagicMock()
+
+    async def mock_astream(*args, **kwargs):
+        yield mock_response
+
+    mock_llm.astream.side_effect = mock_astream
+
+    with (
+        patch(
+            "artemis.agents.summarizer.summarizer.get_llm", return_value=mock_llm
+        ) as mock_get_llm,
+        patch("asyncio.create_task") as mock_create_task,
+    ):
+        # Run the node call
+        node = SummarizerNode(mock_context)
+        await node(state)
+
+        # Verify task was registered in context
+        assert len(mock_context.background_tasks) == 1
+        assert mock_context.background_tasks[0] == mock_create_task.return_value
+
+        # Verify background task was spawned
+        assert mock_create_task.called
+        background_coroutine = mock_create_task.call_args[0][0]
+
+        # Await the background task synchronously for test verification
+        await background_coroutine
+
+    # Verify LLM was invoked with proper structured messages
+    assert mock_llm.astream.called
+    invoked_messages = mock_llm.astream.call_args[0][0]
+
+    system_msg = invoked_messages[0].content
+    human_msg = invoked_messages[1].content
+
+    assert "Summarizer Agent" in system_msg
+    assert "Decisions made" in human_msg
+    assert "The operator clicked the search button." in human_msg
+
+    # Verify Data Engine updated the step summary
+    from uuid import UUID
+
+    mock_context.data_engine.update_step_summary.assert_called_once_with(
+        UUID("12345678-1234-5678-1234-567812345678"),
+        "Step completed successfully.",
+    )
+
+
+@pytest.mark.asyncio
+async def test_summarizer_with_native_thinking(mock_context):
+    """Test that SummarizerNode successfully generates summary from both explicit and native thoughts."""
+    decisions = json.dumps([{"action": "tap", "coordinates": [500, 600]}])
+    raw_thinking = "Explicit monologue."
+    native_thinking = "Silent core reasoning."
+    result = {"status": "success"}
+
+    state = DummyState(
+        structured_decisions=decisions,
+        operator_raw_thinking=raw_thinking,
+        operator_native_thinking=native_thinking,
+        last_execution_result=result,
+        current_step_id="12345678-1234-5678-1234-567812345678",
+    )
+
+    mock_response = Mock()
+    mock_response.content = "Summary result."
+    mock_llm = MagicMock()
+
+    async def mock_astream(*args, **kwargs):
+        yield mock_response
+
+    mock_llm.astream.side_effect = mock_astream
+
+    with (
+        patch(
+            "artemis.agents.summarizer.summarizer.get_llm", return_value=mock_llm
+        ) as mock_get_llm,
+        patch("asyncio.create_task") as mock_create_task,
+    ):
+        node = SummarizerNode(mock_context)
+        await node(state)
+
+        # Verify task was registered in context
+        assert len(mock_context.background_tasks) == 1
+        assert mock_context.background_tasks[0] == mock_create_task.return_value
+
+        background_coroutine = mock_create_task.call_args[0][0]
+        await background_coroutine
+
+    assert mock_llm.astream.called
+    invoked_messages = mock_llm.astream.call_args[0][0]
+    human_msg = invoked_messages[1].content
+
+    assert "Operator explicit thoughts:" in human_msg
+    assert "Explicit monologue." in human_msg
+    assert "Operator native thoughts:" in human_msg
+    assert "Silent core reasoning." in human_msg
+
+
+@pytest.mark.asyncio
+async def test_summarizer_with_chronological_trace(mock_context):
+    """Test that SummarizerNode generates a prompt containing the chronological step trace when available."""
+    step_id = "12345678-1234-5678-1234-567812345678"
+    state = DummyState(
+        current_step_id=step_id,
+    )
+
+    mock_step_data = {
+        "step_id": step_id,
+        "step_number": 1,
+        "relative_time": "5.0s",
+        "action_taken": [{"action": "click", "target_text": "Search"}],
+        "last_execution_result": {"status": "success"},
+        "interleaved_events": [
+            {"type": "thought", "content": "Let's click search."},
+        ],
+    }
+
+    mock_context.data_engine.get_agent_friendly_steps.return_value = [mock_step_data]
+
+    # Mock LLM response
+    mock_response = Mock()
+    mock_response.content = "Summary using chronological trace."
+    mock_llm = MagicMock()
+
+    async def mock_astream(*args, **kwargs):
+        yield mock_response
+
+    mock_llm.astream.side_effect = mock_astream
+
+    with (
+        patch("artemis.agents.summarizer.summarizer.get_llm", return_value=mock_llm),
+        patch("asyncio.create_task") as mock_create_task,
+    ):
+        node = SummarizerNode(mock_context)
+        await node(state)
+
+        # Verify task was registered in context
+        assert len(mock_context.background_tasks) == 1
+        assert mock_context.background_tasks[0] == mock_create_task.return_value
+
+        background_coroutine = mock_create_task.call_args[0][0]
+        await background_coroutine
+
+    assert mock_llm.astream.called
+    invoked_messages = mock_llm.astream.call_args[0][0]
+    human_msg = invoked_messages[1].content
+
+    assert "--- Execution History ---" in human_msg
+    assert "Let's click search." in human_msg