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Update process_interview.py
Browse files- process_interview.py +224 -75
process_interview.py
CHANGED
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@@ -592,13 +592,11 @@ def calculate_acceptance_probability(analysis_data: Dict) -> float:
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def generate_report(analysis_data: Dict) -> str:
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try:
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voice = analysis_data.get('voice_analysis', {})
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voice_interpretation = generate_voice_interpretation(voice)
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interviewee_responses = [f"- {u['text']}" for u in analysis_data['transcript'] if u
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acceptance_prob = analysis_data.get('acceptance_probability', 50.0)
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acceptance_line = f"\n**Suitability Score: {acceptance_prob:.2f}%**\n"
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if acceptance_prob >= 80:
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@@ -609,71 +607,181 @@ def generate_report(analysis_data: Dict) -> str:
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acceptance_line += "HR Verdict: Moderate potential, needs additional assessment."
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else:
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acceptance_line += "HR Verdict: Limited fit, significant improvement required."
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prompt = f"""
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You are EvalBot, a senior HR consultant delivering a
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{acceptance_line}
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**1. Executive Summary**
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- Summarize performance, key
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- Participants: {', '.join(sorted(set(u['speaker'] for u in analysis_data['transcript'])))}
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**2. Communication and Vocal Dynamics**
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- Evaluate vocal delivery (rate, fluency, confidence).
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- Provide HR
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{voice_interpretation}
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**3. Competency and Content**
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- List
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- Sample responses:
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{chr(10).join(interviewee_responses)}
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**4. Role Fit and Potential**
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- Analyze cultural fit, role readiness, and growth potential.
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**5. Recommendations**
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- Provide
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-
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"""
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response = gemini_model.generate_content(prompt)
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-
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except Exception as e:
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logger.error(f"Report generation failed: {str(e)}")
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return f"Error generating report: {str(e)}"
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def create_pdf_report(analysis_data: Dict, output_path: str, gemini_report_text: str) -> bool:
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try:
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doc = SimpleDocTemplate(
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-
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styles = getSampleStyleSheet()
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story = []
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def header_footer(canvas, doc):
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canvas.saveState()
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canvas.setFont('Helvetica', 8)
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canvas.setFillColor(colors.HexColor('#666666'))
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canvas.drawString(doc.leftMargin, 0.5*inch, f"Page {doc.page} | EvalBot HR Interview Report | Confidential")
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canvas.setStrokeColor(colors.HexColor('#0050BC'))
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canvas.setLineWidth(0.8)
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canvas.line(doc.leftMargin, doc.height + 0.9*inch, doc.width + doc.leftMargin, doc.height + 0.9*inch)
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canvas.setFont('Helvetica-Bold', 9)
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canvas.drawString(doc.leftMargin, doc.height + 0.95*inch, "Candidate Interview Analysis")
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canvas.drawRightString(doc.width + doc.leftMargin, doc.height + 0.95*inch, time.strftime('%B %d, %Y'))
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canvas.restoreState()
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# Title Page
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story.append(Paragraph("
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story.append(
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acceptance_prob = analysis_data.get('acceptance_probability', 50.0)
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if acceptance_prob >= 80:
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story.append(Paragraph("<b>HR Verdict:</b> Outstanding candidate, recommended for immediate advancement.", body_text))
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elif acceptance_prob >= 60:
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story.append(Paragraph("<b>HR Verdict:</b> Moderate potential, needs additional assessment.", body_text))
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else:
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story.append(Paragraph("<b>HR Verdict:</b> Limited fit, significant improvement required.", body_text))
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story.append(Spacer(1, 0.
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table_data = [
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['Metric', 'Value'],
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['Interview Duration', f"{analysis_data['text_analysis']
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['Speaker Turns', f"{analysis_data['text_analysis']
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['
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]
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table = Table(table_data, colWidths=[2.3*inch, 3.7*inch])
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table.setStyle(TableStyle([
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('BOTTOMPADDING', (0,0), (-1,0), 8),
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('TOPPADDING', (0,0), (-1,0), 8),
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('BACKGROUND', (0,1), (-1,-1), colors.HexColor('#F5F6FA')),
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('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#
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]))
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story.append(table)
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story.append(Spacer(1, 0.
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story.append(Paragraph("Prepared by: EvalBot - AI-Powered HR Analysis", body_text))
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story.append(PageBreak())
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voice_analysis = analysis_data.get('voice_analysis', {})
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if voice_analysis and 'error' not in voice_analysis:
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table_data = [
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['Metric', 'Value', 'HR Insight'],
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['Speaking Rate', f"{voice_analysis.get('speaking_rate', 0):.2f} words/sec", 'Benchmark: 2.0-3.0 wps; impacts clarity'],
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['Filler Words', f"{voice_analysis.get('filler_ratio', 0) * 100:.1f}%", 'High usage
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['Anxiety', voice_analysis.get('interpretation', {}).get('anxiety_level', 'N/A'), f"Score: {voice_analysis.get('composite_scores', {}).get('anxiety', 0):.3f}"],
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['Confidence', voice_analysis.get('interpretation', {}).get('confidence_level', 'N/A'), f"Score: {voice_analysis.get('composite_scores', {}).get('confidence', 0):.3f}"],
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['Fluency', voice_analysis.get('interpretation', {}).get('fluency_level', 'N/A'), 'Drives engagement'],
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]
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table = Table(table_data, colWidths=[1.6*inch, 1.2*inch, 3.2*inch])
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table.setStyle(TableStyle([
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('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
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('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
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('FONTSIZE', (0,0), (-1,-1), 9),
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('BOTTOMPADDING', (0,0), (-1
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('TOPPADDING', (0,0), (-1
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('BACKGROUND', (0,1), (-1,-1), colors.HexColor('#F5F6FA')),
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('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#
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]))
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story.append(table)
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story.append(Spacer(1, 0.2*inch))
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img.hAlign = 'CENTER'
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story.append(img)
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else:
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story.append(Paragraph("Vocal analysis unavailable.", body_text))
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story.append(Spacer(1, 0.2*inch))
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# Parse Gemini Report
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sections = {
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"Executive Summary": [],
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"Communication": [],
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"Competency": {"Strengths": [], "
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"Recommendations": {"Development": [], "Next Steps": []},
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"Role Fit": [],
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}
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current_section = None
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current_subsection = None
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for line in lines:
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line = line.strip()
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if not line: continue
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if
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section_title =
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if section_title.startswith(('1.', '2.', '3.', '4.', '5.')):
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section_title = section_title[2:].strip()
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if 'Executive Summary' in section_title:
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current_section = 'Executive Summary'
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current_subsection = None
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elif 'Recommendations' in section_title:
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current_section = 'Recommendations'
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current_subsection = None
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elif
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clean_line =
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if not clean_line: continue
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clean_line = re.sub(r'[()]', '', clean_line)
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if current_section == 'Competency':
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if any(k in clean_line.lower() for k in ['leader', 'problem', 'commun', 'adapt', 'strength']):
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current_subsection = 'Strengths'
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elif any(k in clean_line.lower() for k in ['improv', 'grow', 'depth']):
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current_subsection = '
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if current_subsection:
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sections[current_section][current_subsection].append(clean_line)
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elif current_section == 'Recommendations':
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if any(k in clean_line.lower() for k in ['commun', 'tech', 'depth', 'pres']):
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current_subsection = 'Development'
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elif any(k in clean_line.lower() for k in ['adv', 'train', 'assess', 'next', 'mentor']):
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current_subsection = 'Next Steps'
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if current_subsection:
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sections[current_section][current_subsection].append(clean_line)
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else:
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sections[current_section].append(clean_line)
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# Executive Summary
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story.append(Paragraph("2. Executive Summary", h2))
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if sections['Executive Summary']:
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story.append(Paragraph("3. Competency & Evaluation", h2))
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story.append(Paragraph("Strengths", h3))
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if sections['Competency']['Strengths']:
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for line in sections['Competency']['Strengths']
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else:
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story.append(Paragraph("No strengths identified.", body_text))
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story.append(Spacer(1, 0.1*inch))
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story.append(Paragraph("
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if sections['Competency']['
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for line in sections['Competency']['
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else:
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story.append(Paragraph("No
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story.append(Spacer(1, 0.2*inch))
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# Role Fit
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story.append(Paragraph("5. Recommendations", h2))
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story.append(Paragraph("Development Priorities", h3))
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if sections['Recommendations']['Development']:
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for line in sections['Recommendations']['Development']
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else:
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story.append(Paragraph("No development priorities specified.", body_text))
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story.append(Spacer(1, 0.1*inch))
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return False
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def convert_to_serializable(obj):
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if isinstance(obj, np.generic):
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return obj.item()
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def generate_report(analysis_data: Dict) -> str:
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try:
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voice = analysis_data.get('voice_analysis', {})
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voice_interpretation = generate_voice_interpretation(voice)
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interviewee_responses = [f"- {u['text']}" for u in analysis_data['transcript'] if u.get('role') == 'Interviewee'][:5]
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acceptance_prob = analysis_data.get('acceptance_probability', 50.0)
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acceptance_line = f"\n**Suitability Score: {acceptance_prob:.2f}%**\n"
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if acceptance_prob >= 80:
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acceptance_line += "HR Verdict: Moderate potential, needs additional assessment."
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else:
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acceptance_line += "HR Verdict: Limited fit, significant improvement required."
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# Enhanced prompt with detailed recommendations
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prompt = f"""
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You are EvalBot, a senior HR consultant delivering a comprehensive, professional interview analysis report.
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Use clear headings, bullet points ('-'), and avoid redundancy.
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Ensure text is clean, professional, and free of special characters that could break formatting.
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The interview involves two roles: Interviewer and Interviewee, assigned alternately to utterances.
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{acceptance_line}
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**1. Executive Summary**
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- Summarize the candidate's overall performance, key strengths, and hiring potential in 2-3 bullets.
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- Include metrics: Duration ({analysis_data['text_analysis']['total_duration']:.2f} seconds), Speaker Turns ({analysis_data['text_analysis']['speaker_turns']}).
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- Mention roles: Interviewer and Interviewee.
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**2. Communication and Vocal Dynamics**
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- Evaluate the Interviewee's vocal delivery (speaking rate, fluency, confidence, anxiety) in 2-3 bullets.
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- Provide one HR insight on workplace communication alignment.
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- Voice Analysis: {voice_interpretation}
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**3. Competency and Content**
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- List 2-3 key strengths (e.g., leadership, problem-solving, communication) with specific examples from responses.
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- List 1-2 weaknesses (growth areas) with actionable feedback to address them.
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- Sample Interviewee responses (for context):
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{chr(10).join(interviewee_responses)}
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**4. Role Fit and Potential**
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- Analyze the Interviewee's cultural fit, role readiness, and long-term growth potential in 2-3 bullets.
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**5. Recommendations**
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- Provide 3-4 specific suggestions for improvement focusing on:
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- Communication skills (e.g., clarity, fluency, reducing filler words).
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- Content delivery (e.g., structuring responses, emphasizing key points).
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- Professional presentation (e.g., confidence, tone, engagement).
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- Include practical strategies or examples for each suggestion.
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- Suggest 2-3 specific next steps for hiring managers (e.g., advance to technical round, provide training, conduct behavioral assessment).
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"""
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response = gemini_model.generate_content(prompt)
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# Robust sanitization
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clean_text = re.sub(r'[^\x20-\x7E\n]+', '', response.text)
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return clean_text
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except Exception as e:
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logger.error(f"Report generation failed: {str(e)}")
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return f"Error generating report: {str(e)}"
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def create_pdf_report(analysis_data: Dict, output_path: str, gemini_report_text: str) -> bool:
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try:
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doc = SimpleDocTemplate(
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output_path,
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pagesize=letter,
|
| 654 |
+
rightMargin=0.75*inch,
|
| 655 |
+
leftMargin=0.75*inch,
|
| 656 |
+
topMargin=1*inch,
|
| 657 |
+
bottomMargin=1*inch
|
| 658 |
+
)
|
| 659 |
styles = getSampleStyleSheet()
|
| 660 |
+
|
| 661 |
+
# Custom styles
|
| 662 |
+
cover_title = ParagraphStyle(
|
| 663 |
+
name='CoverTitle',
|
| 664 |
+
fontSize=24,
|
| 665 |
+
leading=28,
|
| 666 |
+
spaceAfter=20,
|
| 667 |
+
alignment=1,
|
| 668 |
+
textColor=colors.HexColor('#003087'),
|
| 669 |
+
fontName='Helvetica-Bold'
|
| 670 |
+
)
|
| 671 |
+
h1 = ParagraphStyle(
|
| 672 |
+
name='Heading1',
|
| 673 |
+
fontSize=16,
|
| 674 |
+
leading=20,
|
| 675 |
+
spaceAfter=14,
|
| 676 |
+
alignment=1,
|
| 677 |
+
textColor=colors.HexColor('#003087'),
|
| 678 |
+
fontName='Helvetica-Bold'
|
| 679 |
+
)
|
| 680 |
+
h2 = ParagraphStyle(
|
| 681 |
+
name='Heading2',
|
| 682 |
+
fontSize=12,
|
| 683 |
+
leading=15,
|
| 684 |
+
spaceBefore=10,
|
| 685 |
+
spaceAfter=8,
|
| 686 |
+
textColor=colors.HexColor('#0050BC'),
|
| 687 |
+
fontName='Helvetica-Bold'
|
| 688 |
+
)
|
| 689 |
+
h3 = ParagraphStyle(
|
| 690 |
+
name='Heading3',
|
| 691 |
+
fontSize=10,
|
| 692 |
+
leading=12,
|
| 693 |
+
spaceBefore=8,
|
| 694 |
+
spaceAfter=6,
|
| 695 |
+
textColor=colors.HexColor('#3F7CFF'),
|
| 696 |
+
fontName='Helvetica-Bold'
|
| 697 |
+
)
|
| 698 |
+
body_text = ParagraphStyle(
|
| 699 |
+
name='BodyText',
|
| 700 |
+
fontSize=9,
|
| 701 |
+
leading=12,
|
| 702 |
+
spaceAfter=6,
|
| 703 |
+
fontName='Helvetica',
|
| 704 |
+
textColor=colors.HexColor('#333333')
|
| 705 |
+
)
|
| 706 |
+
bullet_style = ParagraphStyle(
|
| 707 |
+
name='Bullet',
|
| 708 |
+
parent=body_text,
|
| 709 |
+
leftIndent=18,
|
| 710 |
+
bulletIndent=8,
|
| 711 |
+
fontName='Helvetica',
|
| 712 |
+
bulletFontName='Helvetica',
|
| 713 |
+
bulletFontSize=9
|
| 714 |
+
)
|
| 715 |
+
table_header = ParagraphStyle(
|
| 716 |
+
name='TableHeader',
|
| 717 |
+
fontSize=9,
|
| 718 |
+
leading=11,
|
| 719 |
+
textColor=colors.white,
|
| 720 |
+
fontName='Helvetica-Bold'
|
| 721 |
+
)
|
| 722 |
+
table_body = ParagraphStyle(
|
| 723 |
+
name='TableBody',
|
| 724 |
+
fontSize=9,
|
| 725 |
+
leading=11,
|
| 726 |
+
fontName='Helvetica'
|
| 727 |
+
)
|
| 728 |
|
| 729 |
story = []
|
| 730 |
|
| 731 |
def header_footer(canvas, doc):
|
| 732 |
canvas.saveState()
|
| 733 |
+
# Footer
|
| 734 |
canvas.setFont('Helvetica', 8)
|
| 735 |
canvas.setFillColor(colors.HexColor('#666666'))
|
| 736 |
canvas.drawString(doc.leftMargin, 0.5*inch, f"Page {doc.page} | EvalBot HR Interview Report | Confidential")
|
| 737 |
+
canvas.drawRightString(doc.width + doc.leftMargin, 0.5*inch, time.strftime('%B %d, %Y'))
|
| 738 |
+
# Header
|
| 739 |
canvas.setStrokeColor(colors.HexColor('#0050BC'))
|
| 740 |
canvas.setLineWidth(0.8)
|
| 741 |
canvas.line(doc.leftMargin, doc.height + 0.9*inch, doc.width + doc.leftMargin, doc.height + 0.9*inch)
|
| 742 |
canvas.setFont('Helvetica-Bold', 9)
|
| 743 |
canvas.drawString(doc.leftMargin, doc.height + 0.95*inch, "Candidate Interview Analysis")
|
|
|
|
| 744 |
canvas.restoreState()
|
| 745 |
|
| 746 |
+
# Cover Page
|
| 747 |
+
story.append(Spacer(1, 2*inch))
|
| 748 |
+
logo_path = 'logo.png'
|
| 749 |
+
if os.path.exists(logo_path):
|
| 750 |
+
story.append(Image(logo_path, width=2*inch, height=0.75*inch))
|
| 751 |
+
story.append(Spacer(1, 0.3*inch))
|
| 752 |
+
story.append(Paragraph("Candidate Interview Analysis Report", cover_title))
|
| 753 |
+
story.append(Spacer(1, 0.2*inch))
|
| 754 |
+
story.append(Paragraph(f"Candidate ID: {analysis_data.get('user_id', 'N/A')}", body_text))
|
| 755 |
+
story.append(Paragraph(f"Generated: {time.strftime('%B %d, %Y')}", body_text))
|
| 756 |
+
story.append(Spacer(1, 0.5*inch))
|
| 757 |
+
story.append(Paragraph("Confidential", ParagraphStyle(
|
| 758 |
+
name='Confidential',
|
| 759 |
+
fontSize=10,
|
| 760 |
+
alignment=1,
|
| 761 |
+
textColor=colors.HexColor('#D32F2F'),
|
| 762 |
+
fontName='Helvetica-Bold'
|
| 763 |
+
)))
|
| 764 |
+
story.append(PageBreak())
|
| 765 |
+
|
| 766 |
# Title Page
|
| 767 |
+
story.append(Paragraph("Interview Evaluation Summary", h1))
|
| 768 |
+
story.append(Spacer(1, 0.3*inch))
|
| 769 |
+
# Suitability Score
|
| 770 |
acceptance_prob = analysis_data.get('acceptance_probability', 50.0)
|
| 771 |
+
prob_color = colors.HexColor('#2E7D32') if acceptance_prob >= 80 else (
|
| 772 |
+
colors.HexColor('#F57C00') if acceptance_prob >= 60 else colors.HexColor('#D32F2F')
|
| 773 |
+
)
|
| 774 |
+
story.append(Paragraph(
|
| 775 |
+
f"Suitability Score: <font size=14 color='{prob_color.hexval()}'><b>{acceptance_prob:.2f}%</b></font>",
|
| 776 |
+
ParagraphStyle(
|
| 777 |
+
name='Score',
|
| 778 |
+
fontSize=14,
|
| 779 |
+
spaceAfter=12,
|
| 780 |
+
alignment=1,
|
| 781 |
+
fontName='Helvetica-Bold'
|
| 782 |
+
)
|
| 783 |
+
))
|
| 784 |
+
# HR Verdict
|
| 785 |
if acceptance_prob >= 80:
|
| 786 |
story.append(Paragraph("<b>HR Verdict:</b> Outstanding candidate, recommended for immediate advancement.", body_text))
|
| 787 |
elif acceptance_prob >= 60:
|
|
|
|
| 790 |
story.append(Paragraph("<b>HR Verdict:</b> Moderate potential, needs additional assessment.", body_text))
|
| 791 |
else:
|
| 792 |
story.append(Paragraph("<b>HR Verdict:</b> Limited fit, significant improvement required.", body_text))
|
| 793 |
+
story.append(Spacer(1, 0.2*inch))
|
| 794 |
+
|
| 795 |
+
# Summary Table with Roles
|
| 796 |
+
roles = sorted(set(u.get('role', 'Unknown') for u in analysis_data.get('transcript', [])))
|
| 797 |
table_data = [
|
| 798 |
+
[Paragraph('Metric', table_header), Paragraph('Value', table_header)],
|
| 799 |
+
[Paragraph('Interview Duration', table_body), Paragraph(f"{analysis_data['text_analysis'].get('total_duration', 0):.2f} seconds", table_body)],
|
| 800 |
+
[Paragraph('Speaker Turns', table_body), Paragraph(f"{analysis_data['text_analysis'].get('speaker_turns', 0)}", table_body)],
|
| 801 |
+
[Paragraph('Roles', table_body), Paragraph(', '.join(roles), table_body)],
|
| 802 |
]
|
| 803 |
table = Table(table_data, colWidths=[2.3*inch, 3.7*inch])
|
| 804 |
table.setStyle(TableStyle([
|
|
|
|
| 811 |
('BOTTOMPADDING', (0,0), (-1,0), 8),
|
| 812 |
('TOPPADDING', (0,0), (-1,0), 8),
|
| 813 |
('BACKGROUND', (0,1), (-1,-1), colors.HexColor('#F5F6FA')),
|
| 814 |
+
('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#DDE4EE')),
|
| 815 |
]))
|
| 816 |
story.append(table)
|
| 817 |
+
story.append(Spacer(1, 0.3*inch))
|
| 818 |
story.append(Paragraph("Prepared by: EvalBot - AI-Powered HR Analysis", body_text))
|
| 819 |
story.append(PageBreak())
|
| 820 |
|
|
|
|
| 826 |
voice_analysis = analysis_data.get('voice_analysis', {})
|
| 827 |
if voice_analysis and 'error' not in voice_analysis:
|
| 828 |
table_data = [
|
| 829 |
+
[Paragraph('Metric', table_header), Paragraph('Value', table_header), Paragraph('HR Insight', table_header)],
|
| 830 |
+
[Paragraph('Speaking Rate', table_body), Paragraph(f"{voice_analysis.get('speaking_rate', 0):.2f} words/sec", table_body), Paragraph('Benchmark: 2.0-3.0 wps; impacts clarity', table_body)],
|
| 831 |
+
[Paragraph('Filler Words', table_body), Paragraph(f"{voice_analysis.get('filler_ratio', 0) * 100:.1f}%", table_body), Paragraph('High usage may reduce credibility', table_body)],
|
| 832 |
+
[Paragraph('Anxiety', table_body), Paragraph(voice_analysis.get('interpretation', {}).get('anxiety_level', 'N/A').title(), table_body), Paragraph(f"Score: {voice_analysis.get('composite_scores', {}).get('anxiety', 0):.3f}", table_body)],
|
| 833 |
+
[Paragraph('Confidence', table_body), Paragraph(voice_analysis.get('interpretation', {}).get('confidence_level', 'N/A').title(), table_body), Paragraph(f"Score: {voice_analysis.get('composite_scores', {}).get('confidence', 0):.3f}", table_body)],
|
| 834 |
+
[Paragraph('Fluency', table_body), Paragraph(voice_analysis.get('interpretation', {}).get('fluency_level', 'N/A').title(), table_body), Paragraph('Drives engagement', table_body)],
|
| 835 |
]
|
| 836 |
table = Table(table_data, colWidths=[1.6*inch, 1.2*inch, 3.2*inch])
|
| 837 |
table.setStyle(TableStyle([
|
|
|
|
| 841 |
('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
|
| 842 |
('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
|
| 843 |
('FONTSIZE', (0,0), (-1,-1), 9),
|
| 844 |
+
('BOTTOMPADDING', (0,0), (-1,-1), 8),
|
| 845 |
+
('TOPPADDING', (0,0), (-1,-1), 8),
|
| 846 |
('BACKGROUND', (0,1), (-1,-1), colors.HexColor('#F5F6FA')),
|
| 847 |
+
('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#DDE4EE')),
|
| 848 |
]))
|
| 849 |
story.append(table)
|
| 850 |
story.append(Spacer(1, 0.2*inch))
|
|
|
|
| 855 |
img.hAlign = 'CENTER'
|
| 856 |
story.append(img)
|
| 857 |
else:
|
| 858 |
+
story.append(Paragraph(f"Vocal analysis unavailable: {voice_analysis.get('error', 'No data available')}", body_text))
|
| 859 |
story.append(Spacer(1, 0.2*inch))
|
| 860 |
|
| 861 |
# Parse Gemini Report
|
| 862 |
sections = {
|
| 863 |
"Executive Summary": [],
|
| 864 |
"Communication": [],
|
| 865 |
+
"Competency": {"Strengths": [], "Weaknesses": []},
|
|
|
|
| 866 |
"Role Fit": [],
|
| 867 |
+
"Recommendations": {"Development": [], "Next Steps": []},
|
| 868 |
}
|
| 869 |
current_section = None
|
| 870 |
current_subsection = None
|
|
|
|
| 872 |
for line in lines:
|
| 873 |
line = line.strip()
|
| 874 |
if not line: continue
|
| 875 |
+
heading_match = re.match(r'^\**(\d+\.\s+)?([^\*]+)\**$', line)
|
| 876 |
+
if heading_match:
|
| 877 |
+
section_title = heading_match.group(2).strip()
|
|
|
|
|
|
|
| 878 |
if 'Executive Summary' in section_title:
|
| 879 |
current_section = 'Executive Summary'
|
| 880 |
current_subsection = None
|
|
|
|
| 890 |
elif 'Recommendations' in section_title:
|
| 891 |
current_section = 'Recommendations'
|
| 892 |
current_subsection = None
|
| 893 |
+
elif re.match(r'^[-*•]\s+', line) and current_section:
|
| 894 |
+
clean_line = re.sub(r'^[-*•]\s+', '', line).strip()
|
| 895 |
if not clean_line: continue
|
| 896 |
+
clean_line = re.sub(r'[()\[\]{}]', '', clean_line)
|
| 897 |
if current_section == 'Competency':
|
| 898 |
+
if any(k in clean_line.lower() for k in ['leader', 'problem', 'commun', 'adapt', 'strength', 'effective', 'skill']):
|
| 899 |
current_subsection = 'Strengths'
|
| 900 |
+
elif any(k in clean_line.lower() for k in ['improv', 'grow', 'weak', 'depth', 'challenge']):
|
| 901 |
+
current_subsection = 'Weaknesses'
|
| 902 |
if current_subsection:
|
| 903 |
sections[current_section][current_subsection].append(clean_line)
|
| 904 |
elif current_section == 'Recommendations':
|
| 905 |
+
if any(k in clean_line.lower() for k in ['commun', 'tech', 'depth', 'pres', 'improve', 'enhance', 'clarity', 'structur', 'tone']):
|
| 906 |
current_subsection = 'Development'
|
| 907 |
+
elif any(k in clean_line.lower() for k in ['adv', 'train', 'assess', 'next', 'mentor', 'round']):
|
| 908 |
current_subsection = 'Next Steps'
|
| 909 |
if current_subsection:
|
| 910 |
sections[current_section][current_subsection].append(clean_line)
|
| 911 |
else:
|
| 912 |
sections[current_section].append(clean_line)
|
| 913 |
|
| 914 |
+
# Summary Box
|
| 915 |
+
story.append(Paragraph("Key Highlights", h2))
|
| 916 |
+
summary_data = [
|
| 917 |
+
[Paragraph("Category", table_header), Paragraph("Detail", table_header)],
|
| 918 |
+
[Paragraph("Top Strength", table_body), Paragraph(sections['Competency']['Strengths'][0] if sections['Competency']['Strengths'] else "N/A", table_body)],
|
| 919 |
+
[Paragraph("Key Weakness", table_body), Paragraph(sections['Competency']['Weaknesses'][0] if sections['Competency']['Weaknesses'] else "N/A", table_body)],
|
| 920 |
+
[Paragraph("Top Recommendation", table_body), Paragraph(sections['Recommendations']['Development'][0] if sections['Recommendations']['Development'] else "N/A", table_body)],
|
| 921 |
+
]
|
| 922 |
+
summary_table = Table(summary_data, colWidths=[2*inch, 4*inch])
|
| 923 |
+
summary_table.setStyle(TableStyle([
|
| 924 |
+
('BACKGROUND', (0,0), (-1,0), colors.HexColor('#0050BC')),
|
| 925 |
+
('TEXTCOLOR', (0,0), (-1,0), colors.white),
|
| 926 |
+
('ALIGN', (0,0), (-1,-1), 'LEFT'),
|
| 927 |
+
('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
|
| 928 |
+
('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
|
| 929 |
+
('FONTSIZE', (0,0), (-1,-1), 9),
|
| 930 |
+
('BOTTOMPADDING', (0,0), (-1,-1), 6),
|
| 931 |
+
('TOPPADDING', (0,0), (-1,-1), 6),
|
| 932 |
+
('BACKGROUND', (0,1), (-1,-1), colors.HexColor('#E8F0FE')),
|
| 933 |
+
('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#DDE4EE')),
|
| 934 |
+
]))
|
| 935 |
+
story.append(summary_table)
|
| 936 |
+
story.append(Spacer(1, 0.3*inch))
|
| 937 |
+
|
| 938 |
# Executive Summary
|
| 939 |
story.append(Paragraph("2. Executive Summary", h2))
|
| 940 |
if sections['Executive Summary']:
|
|
|
|
| 948 |
story.append(Paragraph("3. Competency & Evaluation", h2))
|
| 949 |
story.append(Paragraph("Strengths", h3))
|
| 950 |
if sections['Competency']['Strengths']:
|
| 951 |
+
strength_table = Table([[Paragraph(line, bullet_style)] for line in sections['Competency']['Strengths']], colWidths=[6*inch])
|
| 952 |
+
strength_table.setStyle(TableStyle([
|
| 953 |
+
('BACKGROUND', (0,0), (-1,-1), colors.HexColor('#E6FFE6')),
|
| 954 |
+
('VALIGN', (0,0), (-1,-1), 'TOP'),
|
| 955 |
+
('LEFTPADDING', (0,0), (-1,-1), 6),
|
| 956 |
+
]))
|
| 957 |
+
story.append(strength_table)
|
| 958 |
else:
|
| 959 |
story.append(Paragraph("No strengths identified.", body_text))
|
| 960 |
story.append(Spacer(1, 0.1*inch))
|
| 961 |
+
story.append(Paragraph("Weaknesses", h3))
|
| 962 |
+
if sections['Competency']['Weaknesses']:
|
| 963 |
+
weakness_table = Table([[Paragraph(line, bullet_style)] for line in sections['Competency']['Weaknesses']], colWidths=[6*inch])
|
| 964 |
+
weakness_table.setStyle(TableStyle([
|
| 965 |
+
('BACKGROUND', (0,0), (-1,-1), colors.HexColor('#FFF0F0')),
|
| 966 |
+
('VALIGN', (0,0), (-1,-1), 'TOP'),
|
| 967 |
+
('LEFTPADDING', (0,0), (-1,-1), 6),
|
| 968 |
+
]))
|
| 969 |
+
story.append(weakness_table)
|
| 970 |
else:
|
| 971 |
+
story.append(Paragraph("No weaknesses identified; maintain current strengths.", body_text))
|
| 972 |
story.append(Spacer(1, 0.2*inch))
|
| 973 |
|
| 974 |
# Role Fit
|
|
|
|
| 984 |
story.append(Paragraph("5. Recommendations", h2))
|
| 985 |
story.append(Paragraph("Development Priorities", h3))
|
| 986 |
if sections['Recommendations']['Development']:
|
| 987 |
+
dev_table = Table([[Paragraph(line, bullet_style)] for line in sections['Recommendations']['Development']], colWidths=[6*inch])
|
| 988 |
+
dev_table.setStyle(TableStyle([
|
| 989 |
+
('BACKGROUND', (0,0), (-1,-1), colors.HexColor('#E8F0FE')),
|
| 990 |
+
('VALIGN', (0,0), (-1,-1), 'TOP'),
|
| 991 |
+
('LEFTPADDING', (0,0), (-1,-1), 6),
|
| 992 |
+
]))
|
| 993 |
+
story.append(dev_table)
|
| 994 |
else:
|
| 995 |
story.append(Paragraph("No development priorities specified.", body_text))
|
| 996 |
story.append(Spacer(1, 0.1*inch))
|
|
|
|
| 1010 |
return False
|
| 1011 |
|
| 1012 |
|
| 1013 |
+
|
| 1014 |
def convert_to_serializable(obj):
|
| 1015 |
if isinstance(obj, np.generic):
|
| 1016 |
return obj.item()
|