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Update app.py
Browse files
app.py
CHANGED
@@ -4,6 +4,40 @@ import pdfplumber
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import re
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from collections import Counter
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# Function to extract text from PDF
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def extract_text_from_pdf(pdf_file):
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with pdfplumber.open(pdf_file) as pdf:
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@@ -83,15 +117,19 @@ def calculate_job_fit_score(resume_text, job_description):
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# Main App
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def main():
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st.write(
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"Upload your resume to check its ATS-friendliness and compare it with a job description for keyword matching."
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)
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uploaded_resume = st.file_uploader(
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"Upload your Resume (PDF or Word):", type=["pdf", "docx"]
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)
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job_description = st.text_area("Paste the Job Description:")
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if uploaded_resume:
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# Extract text based on file type
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@@ -104,46 +142,41 @@ def main():
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return
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# Analyze ATS-friendliness
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st.
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ats_score, ats_suggestions = check_ats_friendly(resume_text)
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st.metric("ATS Score", f"{ats_score}/100")
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if ats_score >= 80:
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st.success("Your resume is ATS-friendly!")
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else:
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st.warning("Your resume needs improvement to be ATS-friendly.")
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# Display ATS suggestions
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st.
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if ats_suggestions:
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for idx, suggestion in enumerate(ats_suggestions, 1):
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st.
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else:
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st.write("
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# Analyze Job Fit
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if job_description.strip():
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st.
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job_fit_score, job_fit_suggestions, missing_keywords = calculate_job_fit_score(
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resume_text, job_description
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)
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st.metric("Job Fit Score", f"{job_fit_score:.2f}%")
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if job_fit_score >= 70:
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st.success("Your resume matches well with the job description!")
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else:
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st.warning("Your resume could be tailored better to match the job description.")
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# Display job fit suggestions
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st.
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if job_fit_suggestions:
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for idx, suggestion in enumerate(job_fit_suggestions, 1):
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st.write(f"{idx}. {suggestion}")
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else:
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st.write("No specific suggestions. Great match!")
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# Recommend missing keywords
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if missing_keywords:
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st.
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st.
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else:
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st.write("Your resume already includes all the required keywords!")
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import re
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from collections import Counter
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# Custom CSS for UI enhancements
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def apply_custom_css():
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st.markdown("""
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<style>
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.title {
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font-size: 2.5rem;
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color: #4CAF50;
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text-align: center;
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margin-bottom: 20px;
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}
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.subtitle {
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font-size: 1.5rem;
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color: #FF5722;
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margin-top: 20px;
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margin-bottom: 10px;
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}
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.metric {
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font-size: 1.2rem;
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text-align: center;
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}
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.separator {
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border-top: 2px solid #eee;
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margin-top: 30px;
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margin-bottom: 30px;
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}
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.suggestions {
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background-color: #f9f9f9;
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border-left: 4px solid #2196F3;
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padding: 10px;
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margin: 10px 0;
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}
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</style>
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""", unsafe_allow_html=True)
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# Function to extract text from PDF
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def extract_text_from_pdf(pdf_file):
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with pdfplumber.open(pdf_file) as pdf:
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# Main App
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def main():
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apply_custom_css()
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st.markdown("<div class='title'>ATS Resume Checker</div>", unsafe_allow_html=True)
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st.write(
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"Upload your resume to check its ATS-friendliness and compare it with a job description for keyword matching."
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)
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st.markdown("<hr class='separator'>", unsafe_allow_html=True)
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uploaded_resume = st.file_uploader(
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"π Upload your Resume (PDF or Word):", type=["pdf", "docx"]
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)
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job_description = st.text_area("π Paste the Job Description:")
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if uploaded_resume:
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# Extract text based on file type
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return
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# Analyze ATS-friendliness
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st.markdown("<div class='subtitle'>π οΈ ATS Analysis</div>", unsafe_allow_html=True)
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ats_score, ats_suggestions = check_ats_friendly(resume_text)
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st.metric("ATS Score", f"{ats_score}/100")
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if ats_score >= 80:
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st.success("β
Your resume is ATS-friendly!")
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else:
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st.warning("β οΈ Your resume needs improvement to be ATS-friendly.")
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# Display ATS suggestions
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st.markdown("<div class='subtitle'>π Suggestions for ATS Improvement</div>", unsafe_allow_html=True)
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if ats_suggestions:
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for idx, suggestion in enumerate(ats_suggestions, 1):
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st.markdown(f"<div class='suggestions'>{idx}. {suggestion}</div>", unsafe_allow_html=True)
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else:
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st.write("Your resume is well-optimized for ATS!")
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st.markdown("<hr class='separator'>", unsafe_allow_html=True)
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# Analyze Job Fit
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if job_description.strip():
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st.markdown("<div class='subtitle'>π Job Description Matching</div>", unsafe_allow_html=True)
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job_fit_score, job_fit_suggestions, missing_keywords = calculate_job_fit_score(
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resume_text, job_description
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)
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st.metric("Job Fit Score", f"{job_fit_score:.2f}%")
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if job_fit_score >= 70:
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st.success("β
Your resume matches well with the job description!")
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else:
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st.warning("β οΈ Your resume could be tailored better to match the job description.")
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# Display job fit suggestions
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st.markdown("<div class='subtitle'>π Missing Keywords</div>", unsafe_allow_html=True)
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if missing_keywords:
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st.write("To improve matching, consider including these keywords:")
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st.markdown(f"<div class='suggestions'>{', '.join(missing_keywords)}</div>", unsafe_allow_html=True)
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else:
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st.write("Your resume already includes all the required keywords!")
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