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"""Unit tests for Teacher Agent system."""
import sys
from pathlib import Path
# Add parent directory to path for imports
sys.path.insert(0, str(Path(__file__).parent))
from mock_student import MockStudentAgent
from mock_task_generator import MockTaskGenerator
from teacher_agent import TeacherAgent
from interfaces import TeacherAction
def test_mock_student_learning():
"""Test that mock student learns."""
print("Testing student learning...", end=" ")
student = MockStudentAgent(learning_rate=0.15, forgetting_rate=0.05)
generator = MockTaskGenerator()
# Test learning
topic = 'history'
tasks = [generator.generate_task(topic, 'easy') for _ in range(20)]
accuracies = []
for task in tasks:
eval_tasks = [generator.generate_task(topic, 'easy') for _ in range(10)]
acc = student.evaluate(eval_tasks)
accuracies.append(acc)
student.learn(task)
# Student should improve
improvement = accuracies[-1] - accuracies[0]
assert improvement > 0.1, f"Student should improve! Improvement: {improvement:.3f}"
print("✅ PASSED")
print(f" Initial accuracy: {accuracies[0]:.3f}")
print(f" Final accuracy: {accuracies[-1]:.3f}")
print(f" Improvement: {improvement:.3f}")
def test_mock_student_forgetting():
"""Test that mock student forgets over time."""
print("Testing student forgetting...", end=" ")
student = MockStudentAgent(learning_rate=0.15, forgetting_rate=0.1)
generator = MockTaskGenerator()
# Train on one topic
topic = 'science'
for _ in range(30):
task = generator.generate_task(topic, 'easy')
student.learn(task)
# Measure accuracy
eval_tasks = [generator.generate_task(topic, 'easy') for _ in range(10)]
acc_before = student.evaluate(eval_tasks)
# Time passes without practice
student.advance_time(50.0)
acc_after = student.evaluate(eval_tasks)
# Student should forget
assert acc_after < acc_before - 0.05, f"Student should forget! Before: {acc_before:.3f}, After: {acc_after:.3f}"
print("✅ PASSED")
print(f" Accuracy before forgetting: {acc_before:.3f}")
print(f" Accuracy after 50 time units: {acc_after:.3f}")
print(f" Forgetting: {acc_before - acc_after:.3f}")
def test_mock_student_initial_accuracy():
"""Test that student starts at ~25% accuracy (random guessing)."""
print("Testing initial student accuracy...", end=" ")
student = MockStudentAgent()
generator = MockTaskGenerator()
# Evaluate on many tasks
eval_tasks = [generator.generate_task('history', 'easy') for _ in range(100)]
initial_acc = student.evaluate(eval_tasks)
# Should be around 25% (random guessing on 4-choice MCQ)
assert 0.15 < initial_acc < 0.35, f"Initial accuracy should be ~25%! Got: {initial_acc:.3f}"
print("✅ PASSED")
print(f" Initial accuracy: {initial_acc:.3f} (~25% expected)")
def test_teacher_exploration():
"""Test that teacher explores all actions."""
print("Testing teacher exploration...", end=" ")
teacher = TeacherAgent(exploration_bonus=5.0) # High exploration
from mock_student import MockStudentAgent
from interfaces import StudentState
# Create minimal student state
student = MockStudentAgent()
actions_tried = set()
for _ in range(100):
student_state = student.get_state()
action = teacher.select_action(student_state)
actions_tried.add((action.topic, action.difficulty, action.is_review))
teacher.update(action, 0.0) # Neutral reward
# Teacher should explore many actions (now has 15 topics × 7 difficulties × 2 = 210 actions)
expected_actions = 15 * 7 * 2 # topics × difficulties × review options
assert len(actions_tried) > 20, f"Teacher should explore many actions! Only tried: {len(actions_tried)}"
print("✅ PASSED")
print(f" Unique actions tried: {len(actions_tried)}/{expected_actions}")
def test_teacher_exploitation():
"""Test that teacher exploits good actions."""
print("Testing teacher exploitation...", end=" ")
teacher = TeacherAgent(exploration_bonus=0.1) # Very low exploration
from mock_student import MockStudentAgent
student = MockStudentAgent()
# Manually set one action to be very good
best_action = TeacherAction(topic='history', difficulty='easy', is_review=False)
best_action_idx = teacher._action_to_index(best_action)
# First, try all actions once (cold start)
for i in range(teacher.num_actions):
test_action = teacher._index_to_action(i)
if i == best_action_idx:
teacher.update(test_action, 100.0) # Very high reward
else:
teacher.update(test_action, 0.0) # Low reward
# Now teacher should prefer the best action
selections = []
for _ in range(50): # More samples for better statistics
student_state = student.get_state()
action = teacher.select_action(student_state)
idx = teacher._action_to_index(action)
selections.append(idx == best_action_idx)
# Should select best action frequently
exploit_rate = sum(selections) / len(selections)
assert exploit_rate > 0.3, f"Teacher should exploit good actions! Exploit rate: {exploit_rate:.2f}"
print("✅ PASSED")
print(f" Best action selection rate: {exploit_rate:.2f}")
def test_teacher_action_encoding():
"""Test that action encoding/decoding works correctly."""
print("Testing action encoding/decoding...", end=" ")
teacher = TeacherAgent()
# Test all actions
for idx in range(teacher.num_actions):
action1 = teacher._index_to_action(idx)
idx2 = teacher._action_to_index(action1)
action2 = teacher._index_to_action(idx2)
assert idx == idx2, f"Encoding mismatch! {idx} != {idx2}"
assert action1.topic == action2.topic, "Topic mismatch"
assert action1.difficulty == action2.difficulty, "Difficulty mismatch"
assert action1.is_review == action2.is_review, "Review flag mismatch"
print("✅ PASSED")
print(f" Tested {teacher.num_actions} actions")
def test_task_generator():
"""Test that task generator creates valid tasks."""
print("Testing task generator...", end=" ")
generator = MockTaskGenerator()
topics = generator.get_available_topics()
difficulties = generator.get_available_difficulties()
# Check that we have topics and difficulties (exact count may vary after expansion)
assert len(topics) >= 5, f"Should have at least 5 topics, got {len(topics)}"
assert len(difficulties) >= 3, f"Should have at least 3 difficulties, got {len(difficulties)}"
# Generate tasks for all combinations
for topic in topics:
for difficulty in difficulties:
task = generator.generate_task(topic, difficulty)
assert len(task.choices) == 4, "Should have 4 choices"
assert 0 <= task.answer < 4, "Answer should be valid index"
assert task.topic == topic, "Topic should match"
assert task.difficulty == difficulty, "Difficulty should match"
print("✅ PASSED")
print(f" Generated tasks for {len(topics)} topics × {len(difficulties)} difficulties")
def run_all_tests():
"""Run all tests."""
print("=" * 70)
print("RUNNING TESTS")
print("=" * 70)
print()
tests = [
test_task_generator,
test_mock_student_initial_accuracy,
test_mock_student_learning,
test_mock_student_forgetting,
test_teacher_action_encoding,
test_teacher_exploration,
test_teacher_exploitation,
]
passed = 0
failed = 0
for test_func in tests:
try:
test_func()
passed += 1
except AssertionError as e:
print(f"❌ FAILED: {e}")
failed += 1
except Exception as e:
print(f"❌ ERROR: {e}")
import traceback
traceback.print_exc()
failed += 1
print()
print("=" * 70)
print(f"TESTS COMPLETE: {passed} passed, {failed} failed")
print("=" * 70)
return failed == 0
if __name__ == "__main__":
success = run_all_tests()
sys.exit(0 if success else 1)
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