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#!/usr/bin/env python3
"""
Simple test script to verify adaptive learning imports work correctly.
"""
import sys
from pathlib import Path
# Add the project root to the Python path
project_root = Path(__file__).parent
sys.path.insert(0, str(project_root))
def test_imports():
"""Test all adaptive learning imports."""
print("🧪 Testing Adaptive Learning System Imports")
print("=" * 50)
try:
print("1. Testing analytics imports...")
from mcp_server.analytics.performance_tracker import PerformanceTracker
from mcp_server.analytics.learning_analytics import LearningAnalytics
from mcp_server.analytics.progress_monitor import ProgressMonitor
print(" ✅ Analytics imports successful")
print("2. Testing algorithms imports...")
from mcp_server.algorithms.adaptive_engine import AdaptiveLearningEngine
from mcp_server.algorithms.difficulty_adjuster import DifficultyAdjuster
from mcp_server.algorithms.path_optimizer import PathOptimizer
from mcp_server.algorithms.mastery_detector import MasteryDetector
print(" ✅ Algorithms imports successful")
print("3. Testing models imports...")
from mcp_server.models.student_profile import StudentProfile
print(" ✅ Models imports successful")
print("4. Testing storage imports...")
from mcp_server.storage.memory_store import MemoryStore
print(" ✅ Storage imports successful")
print("5. Testing component initialization...")
performance_tracker = PerformanceTracker()
learning_analytics = LearningAnalytics(performance_tracker)
progress_monitor = ProgressMonitor(performance_tracker, learning_analytics)
adaptive_engine = AdaptiveLearningEngine(performance_tracker, learning_analytics)
difficulty_adjuster = DifficultyAdjuster(performance_tracker)
path_optimizer = PathOptimizer(performance_tracker, learning_analytics)
mastery_detector = MasteryDetector(performance_tracker)
print(" ✅ Component initialization successful")
print("6. Testing adaptive learning tools import...")
import mcp_server.tools.adaptive_learning_tools
print(" ✅ Adaptive learning tools import successful")
print("\n🎉 All imports successful!")
print("The adaptive learning system is ready to use.")
return True
except Exception as e:
print(f"\n❌ Import failed: {e}")
import traceback
traceback.print_exc()
return False
def test_basic_functionality():
"""Test basic functionality without async."""
print("\n🔧 Testing Basic Functionality")
print("=" * 50)
try:
from mcp_server.analytics.performance_tracker import PerformanceTracker
from mcp_server.models.student_profile import StudentProfile
from mcp_server.storage.memory_store import MemoryStore
# Test performance tracker
print("1. Testing PerformanceTracker...")
tracker = PerformanceTracker()
print(f" ✅ Created tracker with {len(tracker.student_performances)} students")
# Test student profile
print("2. Testing StudentProfile...")
profile = StudentProfile(student_id="test_001", name="Test Student")
print(f" ✅ Created profile for {profile.name}")
# Test memory store
print("3. Testing MemoryStore...")
store = MemoryStore()
store.save_student_profile(profile)
retrieved = store.get_student_profile("test_001")
print(f" ✅ Stored and retrieved profile: {retrieved.name if retrieved else 'None'}")
print("\n🎉 Basic functionality test successful!")
return True
except Exception as e:
print(f"\n❌ Functionality test failed: {e}")
import traceback
traceback.print_exc()
return False
if __name__ == "__main__":
print("🧠 TutorX-MCP Adaptive Learning System - Import Test")
print("=" * 60)
# Test imports
imports_ok = test_imports()
if imports_ok:
# Test basic functionality
functionality_ok = test_basic_functionality()
if functionality_ok:
print("\n✅ All tests passed! The system is ready.")
sys.exit(0)
else:
print("\n❌ Functionality tests failed.")
sys.exit(1)
else:
print("\n❌ Import tests failed.")
sys.exit(1)
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