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#!/usr/bin/env python3
"""
Test script for the new AI integration features in TutorX-MCP.
Tests the contextualized AI tutoring and automated content generation.
"""
import asyncio
import json
import sys
import os
# Add the current directory to the Python path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from mcp_server.tools.ai_tutor_tools import (
start_tutoring_session,
ai_tutor_chat,
get_step_by_step_guidance,
get_alternative_explanations,
end_tutoring_session
)
from mcp_server.tools.content_generation_tools import (
generate_interactive_exercise,
generate_scenario_based_learning,
generate_gamified_content
)
async def test_ai_tutoring():
"""Test the AI tutoring functionality"""
print("🤖 Testing AI Tutoring Features...")
# Test 1: Start a tutoring session
print("\n1. Starting tutoring session...")
session_result = await start_tutoring_session(
student_id="test_student_001",
subject="Mathematics",
learning_objectives=["Understand quadratic equations", "Learn factoring methods"]
)
print(f"Session started: {session_result.get('success', False)}")
if not session_result.get('success'):
print(f"❌ Failed to start session: {session_result.get('error')}")
return
session_id = session_result.get('session_id')
print(f"Session ID: {session_id}")
# Test 2: Chat with AI tutor
print("\n2. Chatting with AI tutor...")
chat_result = await ai_tutor_chat(
session_id=session_id,
student_query="How do I solve quadratic equations?",
request_type="explanation"
)
print(f"Chat response received: {chat_result.get('success', False)}")
# Test 3: Get step-by-step guidance
print("\n3. Getting step-by-step guidance...")
steps_result = await get_step_by_step_guidance(
session_id=session_id,
concept="Solving quadratic equations",
current_step=1
)
print(f"Step-by-step guidance received: {steps_result.get('success', False)}")
# Test 4: Get alternative explanations
print("\n4. Getting alternative explanations...")
alt_result = await get_alternative_explanations(
session_id=session_id,
concept="Quadratic formula",
explanation_types=["visual", "analogy", "real_world"]
)
print(f"Alternative explanations received: {alt_result.get('success', False)}")
# Test 5: End session
print("\n5. Ending tutoring session...")
end_result = await end_tutoring_session(
session_id=session_id,
session_summary="Learned about quadratic equations and different solving methods"
)
print(f"Session ended: {end_result.get('success', False)}")
print("✅ AI Tutoring tests completed!")
async def test_content_generation():
"""Test the content generation functionality"""
print("\n🎨 Testing Content Generation Features...")
# Test 1: Generate interactive exercise
print("\n1. Generating interactive exercise...")
exercise_result = await generate_interactive_exercise(
concept="Photosynthesis",
exercise_type="simulation",
difficulty_level=0.6,
student_level="intermediate"
)
print(f"Interactive exercise generated: {exercise_result.get('success', False)}")
# Test 2: Generate scenario-based learning
print("\n2. Generating scenario-based learning...")
scenario_result = await generate_scenario_based_learning(
concept="Climate Change",
scenario_type="real_world",
complexity_level="moderate"
)
print(f"Scenario-based learning generated: {scenario_result.get('success', False)}")
# Test 3: Generate gamified content
print("\n3. Generating gamified content...")
game_result = await generate_gamified_content(
concept="Fractions",
game_type="quest",
target_age_group="teen"
)
print(f"Gamified content generated: {game_result.get('success', False)}")
print("✅ Content Generation tests completed!")
async def main():
"""Run all tests"""
print("🚀 Starting TutorX AI Integration Tests...")
print("=" * 50)
try:
# Test AI Tutoring
await test_ai_tutoring()
# Test Content Generation
await test_content_generation()
print("\n" + "=" * 50)
print("🎉 All tests completed successfully!")
except Exception as e:
print(f"\n❌ Test failed with error: {str(e)}")
import traceback
traceback.print_exc()
if __name__ == "__main__":
asyncio.run(main())
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