#!/usr/bin/env python3
"""
Create a test PDF for testing the PDF Analysis & Orchestrator
"""

from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
from reportlab.lib.styles import getSampleStyleSheet
from reportlab.lib.units import inch

def create_test_pdf():
    """Create a test PDF with sample content"""
    
    # Create PDF document
    doc = SimpleDocTemplate("test_document.pdf", pagesize=letter)
    styles = getSampleStyleSheet()
    
    # Sample content
    content = [
        Paragraph("PDF Analysis & Orchestrator - Test Document", styles['Title']),
        Spacer(1, 12),
        
        Paragraph("Executive Summary", styles['Heading1']),
        Paragraph("""
        This document serves as a test case for the PDF Analysis & Orchestrator application. 
        It contains various sections that can be used to test different analysis capabilities 
        including summarization, technical explanation, and content segmentation.
        """, styles['Normal']),
        Spacer(1, 12),
        
        Paragraph("Introduction", styles['Heading1']),
        Paragraph("""
        The PDF Analysis & Orchestrator is a powerful tool that leverages artificial intelligence 
        to provide comprehensive document analysis. It uses advanced natural language processing 
        techniques to understand, summarize, and explain complex documents across various domains.
        """, styles['Normal']),
        Spacer(1, 12),
        
        Paragraph("Key Features", styles['Heading1']),
        Paragraph("""
        The system offers several key features that make it particularly useful for document analysis:
        """, styles['Normal']),
        
        Paragraph("1. Intelligent Analysis", styles['Heading2']),
        Paragraph("""
        The AI-powered analysis engine can understand context and provide meaningful insights 
        from complex documents. It adapts its language and complexity based on the target audience.
        """, styles['Normal']),
        
        Paragraph("2. Document Chunking", styles['Heading2']),
        Paragraph("""
        For large documents, the system automatically breaks them into manageable chunks while 
        maintaining context through intelligent sentence boundary detection and overlap handling.
        """, styles['Normal']),
        
        Paragraph("3. Batch Processing", styles['Heading2']),
        Paragraph("""
        Users can process multiple documents simultaneously, with comprehensive reporting that 
        includes individual results and batch summaries.
        """, styles['Normal']),
        
        Paragraph("4. Custom Prompts", styles['Heading2']),
        Paragraph("""
        The system supports custom prompt templates that can be saved, organized, and reused 
        across different analysis sessions.
        """, styles['Normal']),
        
        Paragraph("Technical Implementation", styles['Heading1']),
        Paragraph("""
        The application is built using modern Python technologies including Gradio for the user 
        interface, OpenAI's GPT models for analysis, and pdfplumber for PDF processing. The 
        architecture follows a multi-agent pattern with specialized agents for different aspects 
        of analysis.
        """, styles['Normal']),
        Spacer(1, 12),
        
        Paragraph("Performance Considerations", styles['Heading1']),
        Paragraph("""
        The system includes several performance optimizations including PDF text extraction caching, 
        configurable chunk sizes, and streaming responses for better user experience. These features 
        ensure efficient processing even for large documents and multiple concurrent users.
        """, styles['Normal']),
        Spacer(1, 12),
        
        Paragraph("Use Cases", styles['Heading1']),
        Paragraph("""
        The PDF Analysis & Orchestrator is suitable for a wide range of use cases including:
        """, styles['Normal']),
        
        Paragraph("• Research Paper Analysis", styles['Normal']),
        Paragraph("• Business Document Summarization", styles['Normal']),
        Paragraph("• Technical Documentation Explanation", styles['Normal']),
        Paragraph("• Legal Document Review", styles['Normal']),
        Paragraph("• Educational Content Processing", styles['Normal']),
        Paragraph("• Report Generation and Analysis", styles['Normal']),
        Spacer(1, 12),
        
        Paragraph("Conclusion", styles['Heading1']),
        Paragraph("""
        The PDF Analysis & Orchestrator represents a significant advancement in document analysis 
        technology. By combining artificial intelligence with user-friendly interfaces and powerful 
        processing capabilities, it provides a comprehensive solution for document understanding 
        and analysis across various domains and use cases.
        """, styles['Normal']),
        Spacer(1, 12),
        
        Paragraph("Contact Information", styles['Heading1']),
        Paragraph("""
        For more information about the PDF Analysis & Orchestrator, please refer to the 
        project documentation or contact the development team. The application is designed 
        to be continuously improved based on user feedback and technological advancements.
        """, styles['Normal']),
    ]
    
    # Build PDF
    doc.build(content)
    print("✅ Test PDF created: test_document.pdf")

if __name__ == "__main__":
    create_test_pdf()