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"""Utilities for assembling and exporting interview reports.

This module provides two primary helpers used by the recruiter dashboard:

``generate_llm_interview_report(application)``
    Given a candidate's ``Application`` record, assemble a plain‑text report
    summarising the interview.  Because the interview process currently
    executes entirely client‑side and does not persist questions or answers
    to the database, this report focuses on the information available on
    the server: the candidate's profile, the job requirements and a skills
    match score.  Should future iterations store richer interview data
    server‑side, this function can be extended to include question/answer
    transcripts, per‑question scores and LLM‑generated feedback.

``create_pdf_report(report_text)``
    Convert a multi‑line string into a simple PDF.  The implementation
    leverages Matplotlib's PDF backend (available by default) to avoid
    heavyweight dependencies such as ReportLab or WeasyPrint, which are
    absent from the runtime environment.  Text is wrapped and split
    across multiple pages as necessary.
"""

from __future__ import annotations

import json
from io import BytesIO
import textwrap
from typing import List

import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages

def generate_llm_interview_report(application) -> str:
    """Generate a human‑readable interview report for a candidate.

    The report includes the candidate's name and email, job details,
    application date, a computed skills match summary and placeholder
    sections for future enhancements.  If server‑side storage of
    question/answer pairs is added later, this function can be updated
    to incorporate those details.

    Parameters
    ----------
    application : backend.models.database.Application
        The SQLAlchemy Application instance representing the candidate's
        job application.  Assumed to have related ``job`` and
        ``date_applied`` attributes available.

    Returns
    -------
    str
        A multi‑line string containing the report contents.
    """
    # Defensive imports to avoid circular dependencies at import time
    try:
        from datetime import datetime  # noqa: F401
    except Exception:
        pass

    # Extract candidate skills and job skills
    try:
        candidate_features = json.loads(application.extracted_features) if application.extracted_features else {}
    except Exception:
        candidate_features = {}
    candidate_skills: List[str] = candidate_features.get('skills', []) or []

    job_skills: List[str] = []
    try:
        job_skills = json.loads(application.job.skills) if application.job and application.job.skills else []
    except Exception:
        job_skills = []

    # Compute skills match ratio and label.  Normalise to lower case for
    # comparison and avoid dividing by zero when ``job_skills`` is empty.
    candidate_set = {s.strip().lower() for s in candidate_skills}
    job_set = {s.strip().lower() for s in job_skills}
    common = candidate_set & job_set
    ratio = len(common) / len(job_set) if job_set else 0.0

    if ratio >= 0.75:
        score_label = 'Excellent'
    elif ratio >= 0.5:
        score_label = 'Good'
    elif ratio >= 0.25:
        score_label = 'Medium'
    else:
        score_label = 'Poor'

    # Assemble report lines
    lines: List[str] = []
    lines.append('Interview Report')
    lines.append('=================')
    lines.append('')
    lines.append(f'Candidate Name: {application.name}')
    lines.append(f'Candidate Email: {application.email}')
    if application.job:
        lines.append(f'Job Applied: {application.job.role}')
        lines.append(f'Company: {application.job.company}')
    else:
        lines.append('Job Applied: N/A')
        lines.append('Company: N/A')
    # Format date_applied if available
    try:
        date_str = application.date_applied.strftime('%Y-%m-%d') if application.date_applied else 'N/A'
    except Exception:
        date_str = 'N/A'
    lines.append(f'Date Applied: {date_str}')
    lines.append('')
    lines.append('Skills Match Summary:')
    # Represent required and candidate skills as comma‑separated lists.  Use
    # title‑case for presentation and handle empty lists gracefully.
    formatted_job_skills = ', '.join(job_skills) if job_skills else 'N/A'
    formatted_candidate_skills = ', '.join(candidate_skills) if candidate_skills else 'N/A'
    formatted_common = ', '.join(sorted(common)) if common else 'None'
    lines.append(f'  Required Skills: {formatted_job_skills}')
    lines.append(f'  Candidate Skills: {formatted_candidate_skills}')
    lines.append(f'  Skills in Common: {formatted_common}')
    lines.append(f'  Match Ratio: {ratio * 100:.0f}%')
    lines.append(f'  Score: {score_label}')
    lines.append('')
    lines.append('Interview Transcript & Evaluation:')
    try:
        if application.interview_log:
            try:
                qa_log = json.loads(application.interview_log)
            except Exception:
                qa_log = []

            if qa_log:
                for idx, entry in enumerate(qa_log, 1):
                    q = entry.get("question", "N/A")
                    a = entry.get("answer", "N/A")
                    eval_score = entry.get("evaluation", {}).get("score", "N/A")
                    eval_feedback = entry.get("evaluation", {}).get("feedback", "N/A")

                    lines.append(f"\nQuestion {idx}: {q}")
                    lines.append(f"Answer: {a}")
                    lines.append(f"Score: {eval_score}")
                    lines.append(f"Feedback: {eval_feedback}")
            else:
                lines.append("No interview log data recorded.")
        else:
            lines.append("No interview log data recorded.")
    except Exception as e:
        lines.append(f"Error loading interview log: {e}")

    return '\n'.join(lines)
from io import BytesIO
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from typing import List, Tuple
import textwrap

def create_pdf_report(report_text: str) -> BytesIO:
    """Convert a formatted report into a clean, well-organized PDF."""
    from matplotlib.backends.backend_pdf import PdfPages
    import matplotlib.pyplot as plt
    import matplotlib.patches as mpatches
    from io import BytesIO
    import textwrap
    
    buffer = BytesIO()
    
    # Page configuration - A4 size
    PAGE_WIDTH = 8.27  # A4 width in inches
    PAGE_HEIGHT = 11.69  # A4 height in inches
    MARGIN = 0.75  # Uniform margins
    
    # Text configuration
    CHARS_PER_LINE = 80  # Characters per line for wrapping
    LINES_PER_PAGE = 45  # Lines that fit on one page
    
    # Colors
    COLORS = {
        'question': '#1e3a8a',  # Dark blue
        'answer': '#374151',    # Dark gray
        'score': '#059669',     # Green
        'feedback': '#dc2626',  # Red
        'header': '#111827',    # Almost black
        'normal': '#374151'     # Gray
    }
    
    # Process the text
    lines = report_text.split('\n')
    processed_lines = []
    wrapper = textwrap.TextWrapper(width=CHARS_PER_LINE, break_long_words=False)
    
    for line in lines:
        if not line.strip():
            processed_lines.append({'text': '', 'type': 'blank'})
            continue
            
        # Identify line type
        if line.strip().startswith('Question'):
            # Add spacing before questions (except first)
            if processed_lines and processed_lines[-1]['type'] != 'blank':
                processed_lines.append({'text': '', 'type': 'blank'})
            processed_lines.append({
                'text': line.strip(),
                'type': 'question',
                'size': 11,
                'bold': True
            })
        elif line.strip().startswith('Answer:'):
            wrapped = wrapper.wrap(line.strip())
            for i, wrapped_line in enumerate(wrapped):
                processed_lines.append({
                    'text': ('  ' + wrapped_line) if i == 0 else ('         ' + wrapped_line),
                    'type': 'answer',
                    'size': 10
                })
        elif line.strip().startswith('Score:'):
            processed_lines.append({
                'text': '  ' + line.strip(),
                'type': 'score',
                'size': 10,
                'bold': True
            })
        elif line.strip().startswith('Feedback:'):
            wrapped = wrapper.wrap(line.strip())
            for i, wrapped_line in enumerate(wrapped):
                processed_lines.append({
                    'text': ('  ' + wrapped_line) if i == 0 else ('           ' + wrapped_line),
                    'type': 'feedback',
                    'size': 10
                })
        elif any(line.strip().startswith(x) for x in ['Interview Report', 'Candidate Name:', 'Candidate Email:', 
                                                       'Job Applied:', 'Company:', 'Date Applied:', 
                                                       'Skills Match Summary:', 'Interview Transcript']):
            # Headers and metadata
            if 'Interview Report' in line:
                processed_lines.append({
                    'text': line.strip(),
                    'type': 'header',
                    'size': 14,
                    'bold': True
                })
                processed_lines.append({'text': '=' * 50, 'type': 'header', 'size': 10})
            else:
                wrapped = wrapper.wrap(line.strip())
                for wrapped_line in enumerate(wrapped):
                    processed_lines.append({
                        'text': wrapped_line[1],
                        'type': 'header',
                        'size': 10,
                        'bold': True if ':' in wrapped_line[1] and wrapped_line[0] == 0 else False
                    })
        else:
            # Regular text
            wrapped = wrapper.wrap(line)
            for wrapped_line in wrapped:
                processed_lines.append({
                    'text': wrapped_line,
                    'type': 'normal',
                    'size': 10
                })
    
    # Create PDF with consistent pages
    with PdfPages(buffer) as pdf:
        page_count = 0
        line_index = 0
        
        while line_index < len(processed_lines):
            # Create new page
            fig = plt.figure(figsize=(PAGE_WIDTH, PAGE_HEIGHT))
            fig.patch.set_facecolor('white')
            ax = fig.add_subplot(111)
            ax.axis('off')
            ax.set_xlim(0, 1)
            ax.set_ylim(0, 1)
            
            # Add subtle page border
            border = mpatches.Rectangle(
                (MARGIN/PAGE_WIDTH, MARGIN/PAGE_HEIGHT), 
                1 - 2*MARGIN/PAGE_WIDTH, 
                1 - 2*MARGIN/PAGE_HEIGHT,
                fill=False, 
                edgecolor='#e5e7eb', 
                linewidth=1
            )
            ax.add_patch(border)
            
            # Current y position (start from top)
            y_pos = 1 - MARGIN/PAGE_HEIGHT - 0.05
            lines_on_page = 0
            
            # Add content to page
            while line_index < len(processed_lines) and lines_on_page < LINES_PER_PAGE:
                line_data = processed_lines[line_index]
                
                # Skip if too close to bottom
                if y_pos < MARGIN/PAGE_HEIGHT + 0.05:
                    break
                
                # Set text properties
                color = COLORS.get(line_data['type'], COLORS['normal'])
                size = line_data.get('size', 10)
                weight = 'bold' if line_data.get('bold', False) else 'normal'
                
                # Add text
                ax.text(
                    MARGIN/PAGE_WIDTH + 0.02,
                    y_pos,
                    line_data['text'],
                    transform=ax.transAxes,
                    fontsize=size,
                    fontweight=weight,
                    color=color,
                    fontfamily='sans-serif',
                    verticalalignment='top'
                )
                
                # Move to next line
                line_height = 0.018 if line_data['type'] == 'blank' else 0.022
                y_pos -= line_height
                lines_on_page += 1
                line_index += 1
            
            # Add page number at bottom
            page_count += 1
            ax.text(
                0.5,
                MARGIN/PAGE_HEIGHT - 0.03,
                f'Page {page_count}',
                transform=ax.transAxes,
                fontsize=9,
                color='#9ca3af',
                horizontalalignment='center'
            )
            
            # Save page
            pdf.savefig(fig, bbox_inches='tight', pad_inches=0.1)
            plt.close(fig)
    
    buffer.seek(0)
    return buffer


def create_pdf_report_advanced(report_text: str) -> BytesIO:
    """
    Alternative implementation using reportlab for professional PDF generation.
    This creates cleaner, more consistent PDFs with better text handling.
    Install with: pip install reportlab
    """
    try:
        from reportlab.lib.pagesizes import A4
        from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
        from reportlab.lib.units import inch
        from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, PageBreak
        from reportlab.lib.colors import HexColor
        from reportlab.lib.enums import TA_LEFT, TA_CENTER
        
        buffer = BytesIO()
        
        # Create document with consistent margins
        doc = SimpleDocTemplate(
            buffer,
            pagesize=A4,
            rightMargin=0.75*inch,
            leftMargin=0.75*inch,
            topMargin=1*inch,
            bottomMargin=1*inch
        )
        
        # Define consistent styles
        styles = getSampleStyleSheet()
        
        # Title style
        title_style = ParagraphStyle(
            'CustomTitle',
            parent=styles['Heading1'],
            fontSize=16,
            textColor=HexColor('#111827'),
            spaceAfter=12,
            alignment=TA_CENTER
        )
        
        # Header style for metadata
        header_style = ParagraphStyle(
            'Header',
            parent=styles['Normal'],
            fontSize=10,
            textColor=HexColor('#111827'),
            spaceAfter=4
        )
        
        # Question style
        question_style = ParagraphStyle(
            'Question',
            parent=styles['Heading2'],
            fontSize=11,
            textColor=HexColor('#1e3a8a'),
            spaceBefore=12,
            spaceAfter=6,
            fontName='Helvetica-Bold'
        )
        
        # Answer style
        answer_style = ParagraphStyle(
            'Answer',
            parent=styles['Normal'],
            fontSize=10,
            textColor=HexColor('#374151'),
            leftIndent=20,
            spaceAfter=4
        )
        
        # Score style
        score_style = ParagraphStyle(
            'Score',
            parent=styles['Normal'],
            fontSize=10,
            textColor=HexColor('#059669'),
            leftIndent=20,
            fontName='Helvetica-Bold',
            spaceAfter=4
        )
        
        # Feedback style
        feedback_style = ParagraphStyle(
            'Feedback',
            parent=styles['Normal'],
            fontSize=10,
            textColor=HexColor('#dc2626'),
            leftIndent=20,
            spaceAfter=8
        )
        
        # Build document content
        story = []
        lines = report_text.split('\n')
        
        for line in lines:
            stripped = line.strip()
            
            if not stripped:
                story.append(Spacer(1, 6))
            elif 'Interview Report' in stripped:
                story.append(Paragraph(stripped, title_style))
                story.append(Spacer(1, 12))
            elif any(stripped.startswith(x) for x in ['Candidate Name:', 'Candidate Email:', 
                                                      'Job Applied:', 'Company:', 'Date Applied:']):
                story.append(Paragraph(stripped, header_style))
            elif stripped.startswith('Skills Match Summary:') or stripped.startswith('Interview Transcript'):
                story.append(Spacer(1, 12))
                story.append(Paragraph(f"<b>{stripped}</b>", header_style))
                story.append(Spacer(1, 6))
            elif stripped.startswith('Question'):
                story.append(Paragraph(stripped, question_style))
            elif stripped.startswith('Answer:'):
                story.append(Paragraph(stripped, answer_style))
            elif stripped.startswith('Score:'):
                story.append(Paragraph(stripped, score_style))
            elif stripped.startswith('Feedback:'):
                story.append(Paragraph(stripped, feedback_style))
            else:
                # Regular text with proper indentation for sub-items
                if stripped.startswith(' '):
                    indent_style = ParagraphStyle(
                        'Indented',
                        parent=styles['Normal'],
                        fontSize=10,
                        leftIndent=20,
                        spaceAfter=2
                    )
                    story.append(Paragraph(stripped, indent_style))
                else:
                    story.append(Paragraph(stripped, styles['Normal']))
        
        # Build PDF
        doc.build(story)
        buffer.seek(0)
        return buffer
        
    except ImportError:
        # Fallback to matplotlib version if reportlab not available
        print("Reportlab not installed. Using matplotlib version.")
        return create_pdf_report(report_text)
    
__all__ = ['generate_llm_interview_report', 'create_pdf_report']