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168 lines
4.7 KiB
Python
168 lines
4.7 KiB
Python
#!/usr/bin/env python3
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"""
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Basic test to verify all components work correctly.
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"""
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import sys
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from pathlib import Path
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PROJECT_ROOT = Path(__file__).resolve().parents[1]
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if str(PROJECT_ROOT) not in sys.path:
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sys.path.insert(0, str(PROJECT_ROOT))
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def test_game_environment():
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"""Test that the game environment works."""
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print("Testing game environment...")
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from game_environment import TreasureHuntGame
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game = TreasureHuntGame(seed=42)
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# Test initial state
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state = game.get_state_description()
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assert "entrance" in state.lower()
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print(" ✓ Game initialization works")
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# Test actions
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actions = game.get_available_actions()
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assert len(actions) > 0
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print(" ✓ Actions generation works")
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# Test action execution
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feedback, reward, done = game.execute_action("look around")
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assert isinstance(feedback, str)
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assert isinstance(reward, float)
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assert isinstance(done, bool)
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print(" ✓ Action execution works")
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# Test reset
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game.reset()
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assert game.moves == 0
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print(" ✓ Game reset works")
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print("✅ Game environment tests passed!\n")
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def test_rl_agent():
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"""Test that the RL agent works."""
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print("Testing RL agent...")
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from game_environment import TreasureHuntGame
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from rl_agent import QLearningAgent
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game = TreasureHuntGame(seed=42)
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agent = QLearningAgent()
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# Test action selection
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action = agent.choose_action(game, training=True)
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assert isinstance(action, str)
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print(" ✓ Action selection works")
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# Test Q-value update
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state = agent._get_state_hash(game)
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feedback, reward, done = game.execute_action(action)
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next_state = agent._get_state_hash(game)
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next_actions = game.get_available_actions()
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agent.update_q_value(state, action, reward, next_state, next_actions, done)
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print(" ✓ Q-value update works")
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# Test training (just 10 episodes for speed)
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results = agent.train(num_episodes=10, verbose=False)
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assert "total_episodes" in results
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print(" ✓ Training works")
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print("✅ RL agent tests passed!\n")
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def test_llm_agent():
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"""Test that the LLM agent works (without API calls)."""
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print("Testing LLM agent structure...")
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from game_environment import TreasureHuntGame
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from llm_agent import LLMAgent, GameExperience
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# Test experience storage
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exp = GameExperience(
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state_description="test state",
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action="test action",
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feedback="test feedback",
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reward=1.0,
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success=True
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)
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assert exp.action == "test action"
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print(" ✓ Experience dataclass works")
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# Test context building (without API)
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try:
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# This will fail without API key, but we can test the structure
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agent = LLMAgent(api_key="dummy-key-for-testing")
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game = TreasureHuntGame()
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state = game.get_state_description()
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actions = game.get_available_actions()
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context = agent._build_context(state, actions)
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assert "treasure hunt" in context.lower()
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print(" ✓ Context building works")
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# Test experience update
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agent.update_experience(state, "test action", "test feedback", 1.0)
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assert len(agent.experiences) == 1
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print(" ✓ Experience storage works")
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except ValueError as e:
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if "MOONSHOT_API_KEY" in str(e):
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print(" ⚠ LLM agent requires API key for full testing")
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else:
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raise
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print("✅ LLM agent structure tests passed!\n")
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def test_experiment_runner():
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"""Test that the experiment runner works."""
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print("Testing experiment runner...")
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from experiment import ExperimentRunner
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runner = ExperimentRunner(results_dir="test_results")
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assert runner.results_dir.exists()
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print(" ✓ Experiment runner initialization works")
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# Clean up test directory
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import shutil
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if runner.results_dir.exists():
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shutil.rmtree(runner.results_dir)
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print("✅ Experiment runner tests passed!\n")
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def main():
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"""Run all tests."""
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print("\n" + "="*60)
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print("RUNNING BASIC TESTS")
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print("="*60 + "\n")
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try:
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test_game_environment()
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test_rl_agent()
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test_llm_agent()
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test_experiment_runner()
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print("="*60)
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print("ALL TESTS PASSED! ✅")
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print("="*60)
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print("\nThe experiment is ready to run.")
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print("To run the full experiment: python experiment.py")
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print("To play interactively: python demo.py")
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except Exception as e:
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print(f"\n❌ Test failed: {e}")
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import traceback
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traceback.print_exc()
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return 1
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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