mirror of
https://github.com/NicolasBohn/NexQuant.git
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196 lines
8.5 KiB
Python
196 lines
8.5 KiB
Python
"""Tests for LLM-dependent components with mock backends."""
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from __future__ import annotations
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import sys
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from pathlib import Path
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from unittest.mock import MagicMock, patch
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import numpy as np
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import pytest
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PROJECT_ROOT = Path(__file__).parent.parent.parent
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sys.path.insert(0, str(PROJECT_ROOT))
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# =============================================================================
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# ModelCoSTEEREvaluator (model_coder/evaluators.py)
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# =============================================================================
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class TestModelCoSTEEREvaluator:
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def test_init(self):
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from rdagent.components.coder.model_coder.evaluators import ModelCoSTEEREvaluator
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eva = ModelCoSTEEREvaluator(scen=MagicMock())
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assert eva.scen is not None
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def test_returns_cached_feedback(self):
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from rdagent.components.coder.model_coder.evaluators import ModelCoSTEEREvaluator
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eva = ModelCoSTEEREvaluator(scen=MagicMock())
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qk = MagicMock()
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qk.success_task_to_knowledge_dict = {
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"info_task": MagicMock(feedback="cached_fb"),
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}
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t = MagicMock()
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t.get_task_information.return_value = "info_task"
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fb = eva.evaluate(target_task=t, implementation=None, gt_implementation=None, queried_knowledge=qk)
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assert fb == "cached_fb"
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def test_returns_failed_feedback(self):
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from rdagent.components.coder.model_coder.evaluators import ModelCoSTEEREvaluator
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eva = ModelCoSTEEREvaluator(scen=MagicMock())
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qk = MagicMock()
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qk.success_task_to_knowledge_dict = {}
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qk.failed_task_info_set = {"info_task"}
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t = MagicMock()
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t.get_task_information.return_value = "info_task"
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fb = eva.evaluate(target_task=t, implementation=None, gt_implementation=None, queried_knowledge=qk)
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assert fb.final_decision is False
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assert "failed too many times" in fb.execution_feedback
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def test_raises_on_wrong_task_type(self):
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from rdagent.components.coder.model_coder.evaluators import ModelCoSTEEREvaluator
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eva = ModelCoSTEEREvaluator(scen=MagicMock())
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qk = MagicMock()
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qk.success_task_to_knowledge_dict = {}
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qk.failed_task_info_set = set()
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t = MagicMock()
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t.get_task_information.return_value = "new_task"
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with pytest.raises(TypeError, match="Expected ModelTask"):
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eva.evaluate(target_task=t, implementation=None, gt_implementation=None, queried_knowledge=qk)
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def test_raises_on_wrong_workspace_type(self):
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from rdagent.components.coder.model_coder.evaluators import ModelCoSTEEREvaluator
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from rdagent.components.coder.model_coder.model import ModelTask
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eva = ModelCoSTEEREvaluator(scen=MagicMock())
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qk = MagicMock()
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qk.success_task_to_knowledge_dict = {}
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qk.failed_task_info_set = set()
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t = ModelTask(
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name="m1", description="d", architecture="LSTM",
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hyperparameters={}, training_hyperparameters={},
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)
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t.get_task_information = MagicMock(return_value="new")
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with pytest.raises(TypeError, match="Expected ModelFBWorkspace"):
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eva.evaluate(target_task=t, implementation="not_a_workspace", gt_implementation=None, queried_knowledge=qk)
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# =============================================================================
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# FactorMultiProcessEvolvingStrategy (factor_coder/evolving_strategy.py)
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# =============================================================================
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class TestFactorEvolvingStrategy:
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def test_init_sets_fields(self):
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from rdagent.components.coder.factor_coder.evolving_strategy import FactorMultiProcessEvolvingStrategy
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strat = FactorMultiProcessEvolvingStrategy(scen=MagicMock(), settings=MagicMock())
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assert strat.num_loop == 0
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assert strat.haveSelected is False
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assert strat.improve_mode is False
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def test_assign_code_list_to_evo_str_input(self):
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"""assign_code_list_to_evo handles string code (not dict)."""
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from rdagent.components.coder.factor_coder.evolving_strategy import FactorMultiProcessEvolvingStrategy
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from rdagent.components.coder.CoSTEER.evolvable_subjects import EvolvingItem
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from rdagent.components.coder.factor_coder.factor import FactorTask, FactorFBWorkspace
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strat = FactorMultiProcessEvolvingStrategy(scen=MagicMock(), settings=MagicMock())
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evo = EvolvingItem(sub_tasks=[FactorTask("f1", "desc", "formula")])
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evo.sub_workspace_list = [None]
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with patch(
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"rdagent.components.coder.factor_coder.evolving_strategy.auto_fix_factor_code",
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return_value="fixed_code",
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):
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strat.assign_code_list_to_evo(["raw_code"], evo)
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assert evo.sub_workspace_list[0] is not None
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# Should be a FactorFBWorkspace
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from rdagent.components.coder.factor_coder.factor import FactorFBWorkspace
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assert isinstance(evo.sub_workspace_list[0], FactorFBWorkspace)
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def test_assign_code_list_to_evo_dict_input(self):
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"""assign_code_list_to_evo handles dict code."""
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from rdagent.components.coder.factor_coder.evolving_strategy import FactorMultiProcessEvolvingStrategy
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from rdagent.components.coder.CoSTEER.evolvable_subjects import EvolvingItem
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from rdagent.components.coder.factor_coder.factor import FactorTask
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strat = FactorMultiProcessEvolvingStrategy(scen=MagicMock(), settings=MagicMock())
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evo = EvolvingItem(sub_tasks=[FactorTask("f1", "desc", "formula")])
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evo.sub_workspace_list = [None]
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with patch(
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"rdagent.components.coder.factor_coder.evolving_strategy.auto_fix_factor_code",
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return_value="fixed",
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):
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strat.assign_code_list_to_evo([{"factor.py": "code", "utils.py": "util_code"}], evo)
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assert evo.sub_workspace_list[0] is not None
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def test_assign_code_list_skips_none(self):
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from rdagent.components.coder.factor_coder.evolving_strategy import FactorMultiProcessEvolvingStrategy
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from rdagent.components.coder.CoSTEER.evolvable_subjects import EvolvingItem
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from rdagent.components.coder.factor_coder.factor import FactorTask
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strat = FactorMultiProcessEvolvingStrategy(scen=MagicMock(), settings=MagicMock())
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evo = EvolvingItem(sub_tasks=[FactorTask("f1", "desc", "formula")])
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evo.sub_workspace_list = [None]
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strat.assign_code_list_to_evo([None], evo)
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assert evo.sub_workspace_list[0] is None # unchanged
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# =============================================================================
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# Eurusd_llm prompt class (eurusd_llm.py)
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# =============================================================================
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class TestEurusdLLM:
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def test_eurusd_llm_importable(self):
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from rdagent.components.coder.factor_coder import eurusd_llm
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assert eurusd_llm is not None
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def test_eurusd_risk_importable(self):
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from rdagent.components.coder.factor_coder import eurusd_risk
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assert eurusd_risk is not None
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def test_eurusd_regime_importable(self):
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from rdagent.components.coder.factor_coder import eurusd_regime
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assert eurusd_regime is not None
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def test_eurusd_debate_importable(self):
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from rdagent.components.coder.factor_coder import eurusd_debate
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assert eurusd_debate is not None
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# eurusd_macro needs yfinance (optional)
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# eurusd_memory needs rank_bm25 (optional)
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# eurusd_reflection needs eurusd_memory (chain dependency)
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# =============================================================================
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# model_coder/evolving_strategy.py import
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# =============================================================================
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class TestModelEvolvingStrategy:
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def test_model_evolving_strategy_importable(self):
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from rdagent.components.coder.model_coder import evolving_strategy
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assert evolving_strategy is not None
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# =============================================================================
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# model_coder/eva_utils.py ModelCodeEvaluator + ModelFinalEvaluator
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# =============================================================================
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class TestModelCodeFinalEvaluators:
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def test_model_code_evaluator_init(self):
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from rdagent.components.coder.model_coder.eva_utils import ModelCodeEvaluator
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eva = ModelCodeEvaluator(scen=MagicMock())
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assert eva.scen is not None
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def test_model_final_evaluator_init(self):
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from rdagent.components.coder.model_coder.eva_utils import ModelFinalEvaluator
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eva = ModelFinalEvaluator(scen=MagicMock())
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assert eva.scen is not None
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