import gradio as gr
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from datetime import datetime
import io
import base64
from transformers import pipeline
from reportlab.lib.pagesizes import letter, A4
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Image, Table, TableStyle, PageBreak
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import inch
from reportlab.lib import colors
from reportlab.lib.enums import TA_CENTER, TA_JUSTIFY, TA_LEFT
import tempfile
import os
import warnings
warnings.filterwarnings("ignore")

# Initialize the AI model for text generation
try:
    # Using a smaller, efficient model that works well on HF Spaces
    generator = pipeline(
        "text-generation",
        model="microsoft/DialoGPT-medium",
        pad_token_id=50256
    )
except Exception as e:
    print(f"Model loading error: {e}")
    generator = None

def calculate_metrics(quiz_scores, assignment_scores, participation_score):
    """Calculate key performance metrics"""
    quiz_avg = np.mean(quiz_scores) if quiz_scores else 0
    assignment_avg = np.mean(assignment_scores) if assignment_scores else 0
    overall_avg = (quiz_avg * 0.4 + assignment_avg * 0.4 + participation_score * 0.2)
    
    # Determine grade letter
    if overall_avg >= 97: grade = "A+"
    elif overall_avg >= 93: grade = "A"
    elif overall_avg >= 90: grade = "A-"
    elif overall_avg >= 87: grade = "B+"
    elif overall_avg >= 83: grade = "B"
    elif overall_avg >= 80: grade = "B-"
    elif overall_avg >= 77: grade = "C+"
    elif overall_avg >= 73: grade = "C"
    elif overall_avg >= 70: grade = "C-"
    elif overall_avg >= 67: grade = "D+"
    elif overall_avg >= 65: grade = "D"
    else: grade = "F"
    
    return {
        'quiz_avg': round(quiz_avg, 1),
        'assignment_avg': round(assignment_avg, 1),
        'overall_avg': round(overall_avg, 1),
        'grade': grade
    }

def analyze_performance(metrics, quiz_scores, assignment_scores):
    """Analyze performance patterns and generate insights"""
    strengths = []
    improvements = []
    
    # Analyze quiz vs assignment performance
    if metrics['assignment_avg'] > metrics['quiz_avg'] + 5:
        improvements.append("Quiz performance under timed conditions")
        strengths.append("Consistent assignment quality and preparation")
    elif metrics['quiz_avg'] > metrics['assignment_avg'] + 5:
        strengths.append("Strong performance under pressure")
        improvements.append("Assignment completion and thoroughness")
    
    # Analyze score consistency
    if quiz_scores:
        quiz_std = np.std(quiz_scores)
        if quiz_std < 5:
            strengths.append("Consistent quiz performance")
        elif quiz_std > 15:
            improvements.append("Score consistency and preparation routine")
    
    # Overall performance analysis
    if metrics['overall_avg'] >= 90:
        strengths.append("Excellent overall academic performance")
    elif metrics['overall_avg'] >= 80:
        strengths.append("Strong understanding of course material")
    else:
        improvements.append("Fundamental concept mastery")
    
    return strengths[:3], improvements[:3]  # Limit to top 3 each

def generate_ai_insights(student_name, subject, metrics, strengths, improvements):
    """Generate AI-powered insights and recommendations"""
    
    # Fallback insights if AI model fails
    fallback_insights = {
        'strengths_text': f"{student_name} demonstrates solid academic foundation with a {metrics['grade']} average. Strong areas include consistent study habits and course engagement.",
        'recommendations': [
            "Continue maintaining current study schedule and habits",
            "Focus on areas showing lower performance for improvement",
            "Seek additional help or resources for challenging topics",
            "Practice active recall and spaced repetition techniques"
        ]
    }
    
    if not generator:
        return fallback_insights
    
    try:
        # Create prompts for AI generation
        strengths_prompt = f"Student {student_name} in {subject} shows strengths in: {', '.join(strengths)}. Explain these strengths briefly:"
        
        # Generate insights (simplified for demo)
        strengths_response = generator(
            strengths_prompt,
            max_length=150,
            num_return_sequences=1,
            temperature=0.7,
            pad_token_id=50256
        )
        
        recommendations = [
            f"Focus on improving {improvements[0] if improvements else 'fundamental concepts'}",
            f"Build upon strength in {strengths[0] if strengths else 'current performance level'}",
            "Establish regular study schedule with consistent review sessions",
            "Seek additional practice in areas showing room for growth"
        ]
        
        return {
            'strengths_text': strengths_response[0]['generated_text'][:200] + "...",
            'recommendations': recommendations
        }
        
    except Exception as e:
        print(f"AI generation error: {e}")
        return fallback_insights

def create_performance_chart(metrics, save_path=None):
    """Create a simple performance visualization"""
    categories = ['Quiz Average', 'Assignment Average', 'Participation', 'Overall']
    scores = [metrics['quiz_avg'], metrics['assignment_avg'], 
              metrics.get('participation', 0), metrics['overall_avg']]
    
    fig, ax = plt.subplots(figsize=(10, 6))
    bars = ax.bar(categories, scores, color=['#FF6B6B', '#4ECDC4', '#45B7D1', '#96CEB4'])
    
    # Add value labels on bars
    for bar, score in zip(bars, scores):
        height = bar.get_height()
        ax.text(bar.get_x() + bar.get_width()/2., height + 1,
                f'{score:.1f}%', ha='center', va='bottom', fontweight='bold')
    
    ax.set_ylim(0, 100)
    ax.set_ylabel('Score (%)', fontweight='bold')
    ax.set_title('Performance Overview', fontsize=16, fontweight='bold', pad=20)
    ax.grid(axis='y', alpha=0.3)
    
    # Color code based on performance
    for i, (bar, score) in enumerate(zip(bars, scores)):
        if score >= 90:
            bar.set_color('#2ECC71')  # Green
        elif score >= 80:
            bar.set_color('#F39C12')  # Orange
        else:
            bar.set_color('#E74C3C')  # Red
    
    plt.tight_layout()
    
    # Save chart if path provided
    if save_path:
        plt.savefig(save_path, dpi=300, bbox_inches='tight')
    
    return fig

def create_pdf_report(student_name, subject, time_period, metrics, strengths, improvements, 
                     insights, participation_score, additional_notes="", chart_path=None):
    """Generate a comprehensive PDF report"""
    
    # Create temporary PDF file
    temp_pdf = tempfile.NamedTemporaryFile(delete=False, suffix='.pdf')
    pdf_path = temp_pdf.name
    temp_pdf.close()
    
    # Create PDF document
    doc = SimpleDocTemplate(pdf_path, pagesize=A4, rightMargin=72, leftMargin=72,
                           topMargin=72, bottomMargin=18)
    
    # Get styles
    styles = getSampleStyleSheet()
    
    # Custom styles
    title_style = ParagraphStyle(
        'CustomTitle',
        parent=styles['Heading1'],
        fontSize=24,
        spaceAfter=30,
        alignment=TA_CENTER,
        textColor=colors.darkblue
    )
    
    heading_style = ParagraphStyle(
        'CustomHeading',
        parent=styles['Heading2'],
        fontSize=16,
        spaceAfter=12,
        spaceBefore=20,
        textColor=colors.darkblue
    )
    
    subheading_style = ParagraphStyle(
        'CustomSubheading',
        parent=styles['Heading3'],
        fontSize=14,
        spaceAfter=8,
        spaceBefore=12,
        textColor=colors.darkgreen
    )
    
    body_style = ParagraphStyle(
        'CustomBody',
        parent=styles['Normal'],
        fontSize=11,
        spaceAfter=6,
        alignment=TA_JUSTIFY
    )
    
    # Build PDF content
    story = []
    
    # Title
    story.append(Paragraph("📊 Student Performance Report", title_style))
    story.append(Spacer(1, 12))
    
    # Student Information Table
    student_data = [
        ['Student Name:', student_name],
        ['Subject/Course:', subject],
        ['Reporting Period:', time_period],
        ['Report Generated:', datetime.now().strftime('%B %d, %Y')],
        ['Generated By:', 'Scoreazy AI Agent']
    ]
    
    student_table = Table(student_data, colWidths=[2*inch, 4*inch])
    student_table.setStyle(TableStyle([
        ('BACKGROUND', (0, 0), (0, -1), colors.lightblue),
        ('TEXTCOLOR', (0, 0), (0, -1), colors.darkblue),
        ('ALIGN', (0, 0), (-1, -1), 'LEFT'),
        ('FONTNAME', (0, 0), (0, -1), 'Helvetica-Bold'),
        ('FONTNAME', (1, 0), (1, -1), 'Helvetica'),
        ('FONTSIZE', (0, 0), (-1, -1), 12),
        ('GRID', (0, 0), (-1, -1), 1, colors.black),
        ('VALIGN', (0, 0), (-1, -1), 'MIDDLE'),
    ]))
    
    story.append(student_table)
    story.append(Spacer(1, 20))
    
    # Performance Summary
    story.append(Paragraph("📈 Performance Summary", heading_style))
    
    performance_data = [
        ['Metric', 'Score', 'Grade'],
        ['Overall Performance', f"{metrics['overall_avg']}%", metrics['grade']],
        ['Quiz Average', f"{metrics['quiz_avg']}%", ''],
        ['Assignment Average', f"{metrics['assignment_avg']}%", ''],
        ['Participation Score', f"{participation_score}%", '']
    ]
    
    performance_table = Table(performance_data, colWidths=[2.5*inch, 1.5*inch, 1*inch])
    performance_table.setStyle(TableStyle([
        ('BACKGROUND', (0, 0), (-1, 0), colors.darkblue),
        ('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
        ('ALIGN', (0, 0), (-1, -1), 'CENTER'),
        ('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
        ('FONTNAME', (0, 1), (-1, -1), 'Helvetica'),
        ('FONTSIZE', (0, 0), (-1, -1), 11),
        ('GRID', (0, 0), (-1, -1), 1, colors.black),
        ('VALIGN', (0, 0), (-1, -1), 'MIDDLE'),
        ('BACKGROUND', (0, 1), (-1, -1), colors.beige),
    ]))
    
    story.append(performance_table)
    story.append(Spacer(1, 20))
    
    # Add chart if available
    if chart_path and os.path.exists(chart_path):
        story.append(Paragraph("📊 Performance Visualization", heading_style))
        chart_img = Image(chart_path, width=6*inch, height=3.6*inch)
        story.append(chart_img)
        story.append(Spacer(1, 20))
    
    # Strengths Section
    story.append(Paragraph("✅ Identified Strengths", heading_style))
    
    for i, strength in enumerate(strengths, 1):
        story.append(Paragraph(f"<b>{i}. {strength.title()}</b>", subheading_style))
        story.append(Paragraph(f"Student demonstrates consistent performance and understanding in this area, "
                             f"showing mastery of key concepts and skills.", body_style))
        story.append(Spacer(1, 8))
    
    # Areas for Improvement
    story.append(Paragraph("⚠️ Areas for Improvement", heading_style))
    
    for i, improvement in enumerate(improvements, 1):
        story.append(Paragraph(f"<b>{i}. {improvement.title()}</b>", subheading_style))
        story.append(Paragraph(f"This area presents opportunities for growth and enhanced learning outcomes. "
                             f"Focused attention in this area will yield significant improvements.", body_style))
        story.append(Spacer(1, 8))
    
    # Recommendations
    story.append(Paragraph("🎯 Personalized Recommendations", heading_style))
    
    for i, rec in enumerate(insights['recommendations'], 1):
        story.append(Paragraph(f"<b>{i}.</b> {rec}", body_style))
        story.append(Spacer(1, 6))
    
    # Additional Notes
    if additional_notes:
        story.append(Spacer(1, 20))
        story.append(Paragraph("📝 Additional Notes", heading_style))
        story.append(Paragraph(additional_notes, body_style))
    
    # Next Steps
    story.append(Spacer(1, 20))
    story.append(Paragraph("📅 Next Steps", heading_style))
    next_steps = [
        "Review this report with student and parent/guardian",
        "Monitor progress on recommended improvement areas over the next 2-3 weeks",
        "Schedule follow-up assessment to track improvement",
        "Continue building on identified strengths through advanced challenges",
        "Implement suggested study strategies and learning techniques"
    ]
    
    for step in next_steps:
        story.append(Paragraph(f"• {step}", body_style))
        story.append(Spacer(1, 4))
    
    # Footer
    story.append(Spacer(1, 30))
    footer_style = ParagraphStyle(
        'Footer',
        parent=styles['Normal'],
        fontSize=10,
        alignment=TA_CENTER,
        textColor=colors.grey
    )
    story.append(Paragraph("Report generated by Scoreazy AI Agent | Educational Technology Solutions", footer_style))
    story.append(Paragraph("For questions or support, please contact your instructor", footer_style))
    
    # Build PDF
    doc.build(story)
    
    return pdf_path

def generate_report(student_name, subject, quiz_scores_str, assignment_scores_str, 
                   participation_score, time_period, additional_notes=""):
    """Main function to generate the complete student report"""
    
    try:
        # Parse input scores
        quiz_scores = [float(x.strip()) for x in quiz_scores_str.split(',') if x.strip()]
        assignment_scores = [float(x.strip()) for x in assignment_scores_str.split(',') if x.strip()]
        
        # Validate scores
        all_scores = quiz_scores + assignment_scores + [participation_score]
        if any(score < 0 or score > 100 for score in all_scores):
            return "Error: All scores must be between 0 and 100.", None, None
        
        # Calculate metrics
        metrics = calculate_metrics(quiz_scores, assignment_scores, participation_score)
        metrics['participation'] = participation_score
        
        # Analyze performance
        strengths, improvements = analyze_performance(metrics, quiz_scores, assignment_scores)
        
        # Generate AI insights
        insights = generate_ai_insights(student_name, subject, metrics, strengths, improvements)
        
        # Create temporary file for chart
        chart_temp = tempfile.NamedTemporaryFile(delete=False, suffix='.png')
        chart_path = chart_temp.name
        chart_temp.close()
        
        # Create visualization
        chart = create_performance_chart(metrics, save_path=chart_path)
        
        # Generate PDF report
        pdf_path = create_pdf_report(
            student_name, subject, time_period, metrics, strengths, improvements,
            insights, participation_score, additional_notes, chart_path
        )
        
        # Generate report text for display
        report = f"""
# 📊 Student Performance Report

**Student Name:** {student_name}  
**Subject:** {subject}  
**Reporting Period:** {time_period}  
**Generated Date:** {datetime.now().strftime('%B %d, %Y')}

---

## 📈 Performance Summary
- **Overall Grade:** {metrics['grade']} ({metrics['overall_avg']}%)
- **Quiz Average:** {metrics['quiz_avg']}%
- **Assignment Average:** {metrics['assignment_avg']}%
- **Participation Score:** {participation_score}%

---

## ✅ Identified Strengths
"""
        
        for i, strength in enumerate(strengths, 1):
            report += f"{i}. **{strength.title()}**: Demonstrates consistent performance and understanding in this area.\n"
        
        report += "\n## ⚠️ Areas for Improvement\n"
        
        for i, improvement in enumerate(improvements, 1):
            report += f"{i}. **{improvement.title()}**: Focus area for enhanced learning outcomes.\n"
        
        report += f"""
---

## 🎯 Recommendations

"""
        for i, rec in enumerate(insights['recommendations'], 1):
            report += f"{i}. {rec}\n"
        
        if additional_notes:
            report += f"""
---

## 📝 Additional Notes
{additional_notes}
"""
        
        report += """
---

## 📅 Next Steps
- Review this report with student and parent/guardian
- Monitor progress on recommended improvement areas
- Schedule follow-up assessment in 2-3 weeks
- Continue building on identified strengths

---

*Report generated by Scoreazy AI Agent | Educational Technology Solutions*
"""
        
        # Clean up temporary chart file
        try:
            os.unlink(chart_path)
        except:
            pass
        
        return report, chart, pdf_path
        
    except ValueError as e:
        return f"Error parsing scores: {str(e)}. Please ensure scores are numbers separated by commas.", None, None
    except Exception as e:
        return f"Error generating report: {str(e)}", None, None

# Create Gradio interface
def create_interface():
    with gr.Blocks(title="📊 Report Generator Bot", theme=gr.themes.Soft()) as app:
        gr.Markdown("""
        # 🤖 Student Report Generator Bot
        ### Powered by AI | Built for Scoreazy Assignment
        
        Generate comprehensive student performance reports with AI-powered insights and recommendations.
        """)
        
        with gr.Row():
            with gr.Column(scale=1):
                gr.Markdown("## 📝 Student Information")
                student_name = gr.Textbox(
                    label="Student Name",
                    placeholder="Enter student's full name",
                    value="Sarah Johnson"
                )
                subject = gr.Textbox(
                    label="Subject/Course",
                    placeholder="e.g., Mathematics, Science, English",
                    value="Mathematics"
                )
                time_period = gr.Textbox(
                    label="Time Period",
                    placeholder="e.g., Quarter 1, Week 1-4, Month 1",
                    value="Quarter 1"
                )
                
            with gr.Column(scale=1):
                gr.Markdown("## 📊 Performance Data")
                quiz_scores = gr.Textbox(
                    label="Quiz Scores (comma-separated)",
                    placeholder="85, 78, 92, 88",
                    value="85, 78, 92, 88, 90"
                )
                assignment_scores = gr.Textbox(
                    label="Assignment Scores (comma-separated)",
                    placeholder="90, 87, 93, 89",
                    value="90, 87, 93, 89, 91"
                )
                participation_score = gr.Slider(
                    label="Participation Score",
                    minimum=0,
                    maximum=100,
                    value=88,
                    step=1
                )
        
        additional_notes = gr.Textbox(
            label="Additional Notes (Optional)",
            placeholder="Any specific observations or concerns...",
            lines=3
        )
        
        generate_btn = gr.Button("🚀 Generate Report", variant="primary", size="lg")
        
        with gr.Row():
            with gr.Column(scale=2):
                report_output = gr.Markdown(label="Generated Report")
            with gr.Column(scale=1):
                chart_output = gr.Plot(label="Performance Chart")
        
        # PDF Download Section
        with gr.Row():
            pdf_output = gr.File(label="📄 Download PDF Report", visible=False)
            download_status = gr.Markdown("", visible=False)
        
        # Example button
        def load_example():
            return (
                "Alex Rodriguez",
                "Computer Science", 
                "95, 87, 91, 89, 93",
                "88, 92, 86, 94, 90",
                85,
                "Semester 1",
                "Student shows strong technical aptitude but could benefit from more consistent participation in class discussions."
            )
        
        def generate_and_update(student_name, subject, quiz_scores, assignment_scores, 
                               participation_score, time_period, additional_notes):
            """Generate report and update interface with PDF"""
            report, chart, pdf_path = generate_report(
                student_name, subject, quiz_scores, assignment_scores,
                participation_score, time_period, additional_notes
            )
            
            if pdf_path and os.path.exists(pdf_path):
                return (
                    report, 
                    chart, 
                    gr.update(value=pdf_path, visible=True),
                    gr.update(value="✅ **PDF Report Generated Successfully!** Click the download button above to save your report.", visible=True)
                )
            else:
                return (
                    report, 
                    chart, 
                    gr.update(visible=False),
                    gr.update(value="❌ Error generating PDF report." if pdf_path is None else "", visible=bool(report))
                )
        
        example_btn = gr.Button("📋 Load Example Data", variant="secondary")
        example_btn.click(
            fn=load_example,
            outputs=[student_name, subject, quiz_scores, assignment_scores, 
                    participation_score, time_period, additional_notes]
        )
        
        generate_btn.click(
            fn=generate_and_update,
            inputs=[student_name, subject, quiz_scores, assignment_scores, 
                   participation_score, time_period, additional_notes],
            outputs=[report_output, chart_output, pdf_output, download_status]
        )
        
        gr.Markdown("""
        ---
        ### 💡 How to Use:
        1. **Enter student information** and course details
        2. **Input performance data** - use comma-separated values for multiple scores
        3. **Add participation score** using the slider
        4. **Click "Generate Report"** to create AI-powered analysis
        5. **Review the comprehensive report** with strengths, improvements, and recommendations
        6. **Download PDF version** for offline viewing and sharing
        
        ### 🔧 Features:
        - ✅ Automated performance analysis
        - ✅ AI-generated insights and recommendations  
        - ✅ Visual performance charts
        - ✅ Professional report formatting
        - ✅ **PDF download with embedded charts**
        - ✅ Customizable input parameters
        
        ### 📄 PDF Report Includes:
        - Complete performance analysis with charts
        - Professional formatting for printing
        - All recommendations and insights
        - Visual performance graphs
        - Ready for sharing with parents/educators
        """)
    
    return app

# Launch the app
if __name__ == "__main__":
    app = create_interface()
    app.launch(share=True)