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| import streamlit as st | |
| from utils.parser import parse_cv, extract_education_level, identify_cv_type | |
| from utils.cv_scoring import calculate_cv_score | |
| from utils.suggestions import ( | |
| get_certification_suggestions, | |
| get_higher_education_suggestions, | |
| get_visa_recommendations, | |
| get_career_advice, | |
| get_job_listings, | |
| ) | |
| from utils.visualizer import generate_timeline | |
| from PIL import Image | |
| from fpdf import FPDF | |
| import matplotlib.pyplot as plt | |
| import tempfile | |
| import io | |
| # ------------------ PDF Generation Function ------------------ | |
| def generate_pdf_report(cv_type, education_level, score, score_breakdown, certs, edu, visa, advice, jobs, fig): | |
| pdf = FPDF() | |
| pdf.add_page() | |
| pdf.set_font("Arial", size=12) | |
| pdf.cell(200, 10, txt="CV Analysis Report", ln=True, align="C") | |
| pdf.ln(10) | |
| pdf.cell(200, 10, txt=f"CV Type: {cv_type}", ln=True) | |
| pdf.cell(200, 10, txt=f"Education Level: {education_level}", ln=True) | |
| pdf.cell(200, 10, txt=f"CV Score: {score}/100", ln=True) | |
| pdf.ln(5) | |
| pdf.set_font("Arial", style="B", size=12) | |
| pdf.cell(200, 10, txt="Score Breakdown:", ln=True) | |
| pdf.set_font("Arial", size=12) | |
| for k, v in score_breakdown.items(): | |
| pdf.cell(200, 10, txt=f"- {k}: {v}", ln=True) | |
| pdf.ln(5) | |
| def add_list_to_pdf(title, items): | |
| pdf.set_font("Arial", style="B", size=12) | |
| pdf.cell(200, 10, txt=title, ln=True) | |
| pdf.set_font("Arial", size=12) | |
| if isinstance(items, list): | |
| for item in items: | |
| pdf.multi_cell(0, 10, f"- {item}") | |
| else: | |
| pdf.multi_cell(0, 10, str(items)) | |
| pdf.ln(5) | |
| add_list_to_pdf("Certification Suggestions:", certs) | |
| add_list_to_pdf("Higher Education Suggestions:", edu) | |
| add_list_to_pdf("Visa Recommendations:", visa) | |
| add_list_to_pdf("Career Advice:", advice) | |
| add_list_to_pdf("Job Listings:", jobs) | |
| # Save the figure as an image and insert into PDF | |
| with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmpfile: | |
| fig.savefig(tmpfile.name, bbox_inches='tight') | |
| pdf.add_page() | |
| pdf.image(tmpfile.name, x=10, y=20, w=pdf.w - 20) | |
| return pdf | |
| # ------------------ Streamlit App ------------------ | |
| st.title("Smart CV Analyzer & Career Roadmap") | |
| uploaded_file = st.file_uploader("Upload your CV in PDF format", type=["pdf"]) | |
| if uploaded_file is not None: | |
| with open("temp_cv.pdf", "wb") as f: | |
| f.write(uploaded_file.getbuffer()) | |
| parsed_text = parse_cv("temp_cv.pdf") | |
| education_level = extract_education_level(parsed_text) | |
| cv_type = identify_cv_type(parsed_text) | |
| score, score_breakdown = calculate_cv_score(parsed_text, education_level) | |
| st.header("CV Analysis Results") | |
| st.write(f"**CV Type:** {cv_type}") | |
| st.write(f"**Education Level:** {education_level}") | |
| st.write(f"### Overall CV Score: {score} / 100") | |
| st.write("### Score Breakdown:") | |
| for k, v in score_breakdown.items(): | |
| st.write(f"- {k}: {v}") | |
| with st.expander("Certification Suggestions"): | |
| certs = get_certification_suggestions(parsed_text) | |
| st.write(certs) | |
| with st.expander("Higher Education Suggestions"): | |
| edu = get_higher_education_suggestions(parsed_text) | |
| st.write(edu) | |
| with st.expander("Visa Recommendations"): | |
| visa = get_visa_recommendations(parsed_text) | |
| st.write(visa) | |
| with st.expander("Career Advice"): | |
| advice = get_career_advice(parsed_text) | |
| st.write(advice) | |
| with st.expander("Job Listings"): | |
| jobs = get_job_listings(parsed_text) | |
| for job in jobs: | |
| st.write(f"- {job}") | |
| st.header("📈 Career Roadmap Timeline") | |
| fig = generate_timeline(cv_type, education_level, score) | |
| st.pyplot(fig) | |
| # --- PDF Download Button --- | |
| # --- PDF Download Button --- | |
| st.subheader("Download Report") | |
| # Generate the PDF as a string | |
| pdf_bytes = generate_pdf_report(cv_type, education_level, score, score_breakdown, certs, edu, visa, advice, jobs, fig).output(dest='S').encode('latin1') | |
| # Display a single download button | |
| st.download_button( | |
| label="📄 Download CV Analysis Report (PDF)", | |
| data=pdf_bytes, | |
| file_name="cv_analysis_report.pdf", | |
| mime="application/pdf" | |
| ) | |