chore: import upstream snapshot with attribution

test/qlib/test_model_factor_proposal.py

@@ -0,0 +1,112 @@
+from unittest.mock import Mock, patch
+
+import pytest
+
+from rdagent.core.proposal import Hypothesis, Trace
+from rdagent.scenarios.qlib.proposal.factor_proposal import (
+    QlibFactorHypothesis2Experiment,
+)
+from rdagent.scenarios.qlib.proposal.model_proposal import (
+    QlibModelHypothesis2Experiment,
+)
+
+
+@pytest.fixture
+def mixed_model_trace():
+    trace = Trace(scen=Mock())
+    model_task = Mock()
+    model_task.name = "model_task_1"
+    factor_task = Mock()
+    factor_task.name = "factor_task_1"
+    trace.hist = [
+        (Mock(sub_tasks=[model_task], hypothesis=Mock(action="model")), Mock()),
+        (Mock(sub_tasks=[factor_task], hypothesis=Mock(action="factor")), Mock()),
+    ]
+    return trace
+
+
+@pytest.fixture
+def mixed_factor_trace():
+    trace = Trace(scen=Mock())
+    factor_task = Mock()
+    factor_task.factor_name = "factor_task_1"
+    model_task = Mock()
+    model_task.name = "model_task_1"
+    trace.hist = [
+        (Mock(sub_tasks=[factor_task], hypothesis=Mock(action="factor")), Mock()),
+        (Mock(sub_tasks=[model_task], hypothesis=Mock(action="model")), Mock()),
+    ]
+    return trace
+
+
+def test_model_proposal_import():
+    assert QlibModelHypothesis2Experiment is not None
+
+
+def test_factor_proposal_import():
+    assert QlibFactorHypothesis2Experiment is not None
+
+
+def test_model_filtering(mixed_model_trace):
+    converter = QlibModelHypothesis2Experiment()
+    hypothesis = Hypothesis(
+        hypothesis="test",
+        reason="r",
+        concise_reason="cr",
+        concise_observation="co",
+        concise_justification="cj",
+        concise_knowledge="ck",
+    )
+    with patch("rdagent.utils.agent.tpl.T.r", return_value="mocked"):
+        context, ok = converter.prepare_context(hypothesis, mixed_model_trace)
+
+    target_list = context.get("target_list", [])
+    assert ok is True
+    names = [getattr(task, "name", "") for task in target_list]
+    assert all("model" in name for name in names)
+
+
+def test_factor_filtering(mixed_factor_trace):
+    converter = QlibFactorHypothesis2Experiment()
+    hypothesis = Hypothesis(
+        hypothesis="test",
+        reason="r",
+        concise_reason="cr",
+        concise_observation="co",
+        concise_justification="cj",
+        concise_knowledge="ck",
+    )
+    with patch("rdagent.utils.agent.tpl.T.r", return_value="mocked"):
+        context, ok = converter.prepare_context(hypothesis, mixed_factor_trace)
+
+    target_list = context.get("target_list", [])
+    assert ok is True
+    factor_names = [getattr(task, "factor_name", "") for task in target_list]
+    assert all("factor" in name for name in factor_names)
+
+
+@pytest.mark.parametrize(
+    "converter_class, trace_fixture, expected_type",
+    [
+        (QlibModelHypothesis2Experiment, "mixed_model_trace", "ModelExperiment"),
+        (QlibFactorHypothesis2Experiment, "mixed_factor_trace", "FactorExperiment"),
+    ],
+)
+def test_code_inspection(converter_class, trace_fixture, request, expected_type):
+    converter = converter_class()
+    trace = request.getfixturevalue(trace_fixture)
+    hypothesis = Hypothesis(
+        hypothesis="test",
+        reason="r",
+        concise_reason="cr",
+        concise_observation="co",
+        concise_justification="cj",
+        concise_knowledge="ck",
+    )
+    with patch("rdagent.utils.agent.tpl.T.r", return_value="mocked"):
+        context, ok = converter.prepare_context(hypothesis, trace)
+
+    target_list = context.get("target_list", [])
+    assert ok is True
+    if target_list:
+        assert target_list[0].__class__.__name__ == expected_type