#!/usr/bin/env python3
"""
Simple Performance Test for Curriculum Assistant
Tests core functionality without heavy dependencies
"""

import time
import os
from pathlib import Path
import fitz  # PyMuPDF
from PIL import Image
import io

class SimpleCurriculumTest:
    def __init__(self, slides_dir="Slides"):
        self.pdf_pages = {}
        self.pdf_files = {}
        self.response_cache = {}
        self._process_pdfs(slides_dir)
        print(f"✅ Loaded {len(self.pdf_files)} PDF files")
    
    def _process_pdfs(self, slides_dir):
        """Process PDFs and extract text"""
        slides_path = Path(slides_dir)
        pdf_files = list(slides_path.glob("*.pdf"))
        
        for pdf_file in pdf_files:
            self.pdf_files[pdf_file.name] = str(pdf_file)
            doc = fitz.open(str(pdf_file))
            pages = {}
            
            for page_num in range(len(doc)):
                page = doc[page_num]
                text = page.get_text()
                if text.strip():
                    pages[page_num + 1] = text.strip()
            
            self.pdf_pages[pdf_file.name] = pages
            doc.close()
    
    def simple_search(self, query):
        """Simple text-based search"""
        start_time = time.time()
        
        # Check cache
        if query in self.response_cache:
            print(f"✅ Cache hit! Response time: {time.time() - start_time:.3f}s")
            return self.response_cache[query]
        
        # Simple keyword search
        results = []
        query_lower = query.lower()
        
        for filename, pages in self.pdf_pages.items():
            for page_num, text in pages.items():
                if query_lower in text.lower():
                    results.append({
                        'filename': filename,
                        'page': page_num,
                        'content': text[:200] + "..." if len(text) > 200 else text
                    })
        
        # Sort by relevance (simple keyword count)
        for result in results:
            result['score'] = result['content'].lower().count(query_lower)
        
        results.sort(key=lambda x: x['score'], reverse=True)
        
        # Generate response
        if results:
            best_result = results[0]
            response = f"📄 Found in: {best_result['filename']} - Page {best_result['page']}\n\n"
            response += f"Content: {best_result['content']}\n\n"
            response += f"Found {len(results)} relevant pages"
        else:
            response = f"No relevant content found for '{query}'"
        
        # Cache result
        self.response_cache[query] = response
        
        response_time = time.time() - start_time
        print(f"✅ Response generated in {response_time:.3f} seconds")
        
        return response

def test_performance():
    """Run performance tests"""
    print("🚀 Starting Simple Performance Test...")
    
    # Initialize
    start_time = time.time()
    chatbot = SimpleCurriculumTest()
    init_time = time.time() - start_time
    print(f"✅ Initialization time: {init_time:.3f} seconds")
    
    # Test queries
    test_queries = [
        "loops",
        "variables", 
        "functions",
        "programming",
        "for loop",
        "while loop"
    ]
    
    print(f"\n🧪 Testing {len(test_queries)} queries...")
    
    total_time = 0
    for i, query in enumerate(test_queries, 1):
        print(f"\n--- Test {i}/{len(test_queries)}: '{query}' ---")
        
        start_time = time.time()
        response = chatbot.simple_search(query)
        query_time = time.time() - start_time
        total_time += query_time
        
        print(f"Response time: {query_time:.3f}s")
        print(f"Response length: {len(response)} characters")
        print(f"Cache size: {len(chatbot.response_cache)} entries")
        
        # Show first 200 chars of response
        print(f"Response preview: {response[:200]}...")
    
    # Summary
    avg_time = total_time / len(test_queries)
    print(f"\n📊 Performance Summary:")
    print(f"Total time: {total_time:.3f}s")
    print(f"Average response time: {avg_time:.3f}s")
    print(f"Initialization time: {init_time:.3f}s")
    print(f"Cache hits: {len([q for q in test_queries if q in chatbot.response_cache])}")
    
    # Performance rating
    if avg_time < 0.1:
        rating = "🚀 EXCELLENT (< 100ms)"
    elif avg_time < 0.5:
        rating = "✅ GOOD (< 500ms)"
    elif avg_time < 1.0:
        rating = "⚠️ ACCEPTABLE (< 1s)"
    else:
        rating = "❌ SLOW (> 1s)"
    
    print(f"Performance rating: {rating}")

if __name__ == "__main__":
    test_performance()