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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 visually appealing PDF with enhanced formatting."""
buffer = BytesIO()
# Configuration
PAGE_WIDTH = 8.27 # A4 width in inches
PAGE_HEIGHT = 11.69 # A4 height in inches
MARGIN_LEFT = 0.75
MARGIN_RIGHT = 0.75
MARGIN_TOP = 1.0
MARGIN_BOTTOM = 1.0
# Calculate usable width for text
usable_width = PAGE_WIDTH - MARGIN_LEFT - MARGIN_RIGHT
chars_per_inch = 12 # Approximate for 10pt font
wrap_width = int(usable_width * chars_per_inch)
# Text styling
FONT_SIZE_NORMAL = 10
FONT_SIZE_HEADING = 12
LINE_HEIGHT = 0.02 # Relative to page height
QUESTION_COLOR = '#2C3E50' # Dark blue-gray
ANSWER_COLOR = '#34495E' # Slightly lighter
SCORE_COLOR = '#27AE60' # Green
FEEDBACK_COLOR = '#E74C3C' # Red
# Prepare formatted content
raw_lines = report_text.split("\n")
wrapper = textwrap.TextWrapper(width=wrap_width, break_long_words=False, replace_whitespace=False)
formatted_content = []
for line in raw_lines:
stripped = line.strip()
if stripped.startswith("Question"):
# Add spacing before questions (except the first one)
if formatted_content:
formatted_content.append({"text": "", "style": "normal"})
# Question with special formatting
formatted_content.append({
"text": stripped,
"style": "question",
"color": QUESTION_COLOR,
"bold": True,
"size": FONT_SIZE_HEADING
})
elif stripped.startswith("Answer:"):
# Extract and wrap answer text
answer_text = stripped.replace("Answer:", "", 1).strip()
wrapped_lines = wrapper.wrap(f"Answer: {answer_text}") if answer_text else ["Answer:"]
for idx, wrapped_line in enumerate(wrapped_lines):
formatted_content.append({
"text": " " + wrapped_line if idx == 0 else " " + wrapped_line,
"style": "answer",
"color": ANSWER_COLOR,
"size": FONT_SIZE_NORMAL
})
elif stripped.startswith("Score:"):
formatted_content.append({
"text": f" {stripped}",
"style": "score",
"color": SCORE_COLOR,
"bold": True,
"size": FONT_SIZE_NORMAL
})
elif stripped.startswith("Feedback:"):
# Wrap feedback text
feedback_text = stripped.replace("Feedback:", "", 1).strip()
wrapped_lines = wrapper.wrap(f"Feedback: {feedback_text}") if feedback_text else ["Feedback:"]
for idx, wrapped_line in enumerate(wrapped_lines):
formatted_content.append({
"text": " " + wrapped_line if idx == 0 else " " + wrapped_line,
"style": "feedback",
"color": FEEDBACK_COLOR,
"size": FONT_SIZE_NORMAL
})
else:
# Regular text
if stripped:
wrapped_lines = wrapper.wrap(line)
for wrapped_line in wrapped_lines:
formatted_content.append({
"text": wrapped_line,
"style": "normal",
"color": "black",
"size": FONT_SIZE_NORMAL
})
else:
formatted_content.append({"text": "", "style": "normal"})
# Calculate lines per page based on actual line height
usable_height = PAGE_HEIGHT - MARGIN_TOP - MARGIN_BOTTOM
lines_per_page = int(usable_height / (LINE_HEIGHT * PAGE_HEIGHT))
# Create PDF
with PdfPages(buffer) as pdf:
page_start = 0
page_num = 1
while page_start < len(formatted_content):
# Create figure
fig = plt.figure(figsize=(PAGE_WIDTH, PAGE_HEIGHT))
fig.patch.set_facecolor('white')
ax = fig.add_subplot(111)
ax.axis('off')
# Add subtle page border
border = mpatches.Rectangle(
(0.5, 0.5), PAGE_WIDTH - 1, PAGE_HEIGHT - 1,
fill=False, edgecolor='#BDC3C7', linewidth=0.5
)
ax.add_patch(border)
# Add page content
y_position = 1 - MARGIN_TOP / PAGE_HEIGHT
lines_on_page = 0
for idx in range(page_start, min(page_start + lines_per_page, len(formatted_content))):
item = formatted_content[idx]
# Apply text styling
weight = 'bold' if item.get('bold', False) else 'normal'
size = item.get('size', FONT_SIZE_NORMAL)
color = item.get('color', 'black')
# Add text to page
ax.text(
MARGIN_LEFT / PAGE_WIDTH,
y_position,
item['text'],
transform=ax.transAxes,
fontsize=size,
fontweight=weight,
color=color,
fontfamily='DejaVu Sans',
verticalalignment='top'
)
# Move to next line
y_position -= LINE_HEIGHT
lines_on_page += 1
# Check if we need a new page (with some buffer)
if y_position < MARGIN_BOTTOM / PAGE_HEIGHT + 0.05:
break
# Add page number
ax.text(
0.5,
MARGIN_BOTTOM / PAGE_HEIGHT / 2,
f"Page {page_num}",
transform=ax.transAxes,
fontsize=9,
color='#7F8C8D',
horizontalalignment='center'
)
# Save page
pdf.savefig(fig, bbox_inches='tight', pad_inches=0)
plt.close(fig)
# Move to next page
page_start += lines_on_page
page_num += 1
buffer.seek(0)
return buffer
def create_pdf_report_advanced(report_text: str) -> BytesIO:
"""
Alternative implementation using reportlab for better PDF generation.
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
buffer = BytesIO()
doc = SimpleDocTemplate(
buffer,
pagesize=A4,
rightMargin=0.75*inch,
leftMargin=0.75*inch,
topMargin=1*inch,
bottomMargin=1*inch
)
# Create custom styles
styles = getSampleStyleSheet()
question_style = ParagraphStyle(
'Question',
parent=styles['Heading2'],
fontSize=12,
textColor=HexColor('#2C3E50'),
spaceAfter=6,
spaceBefore=12
)
answer_style = ParagraphStyle(
'Answer',
parent=styles['Normal'],
fontSize=10,
textColor=HexColor('#34495E'),
leftIndent=20,
spaceAfter=3
)
score_style = ParagraphStyle(
'Score',
parent=styles['Normal'],
fontSize=10,
textColor=HexColor('#27AE60'),
leftIndent=20,
fontName='Helvetica-Bold'
)
feedback_style = ParagraphStyle(
'Feedback',
parent=styles['Normal'],
fontSize=10,
textColor=HexColor('#E74C3C'),
leftIndent=20,
spaceAfter=6
)
# Build document content
story = []
lines = report_text.split('\n')
for line in lines:
stripped = line.strip()
if 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))
elif stripped:
story.append(Paragraph(stripped, styles['Normal']))
else:
story.append(Spacer(1, 12))
# Build PDF
doc.build(story)
buffer.seek(0)
return buffer
except ImportError:
# Fallback to matplotlib version
return create_pdf_report(report_text)
__all__ = ['generate_llm_interview_report', 'create_pdf_report'] |