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app.py
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import streamlit as st
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from cv_analyzer import analyze_cv
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st.set_page_config(page_title="CV Analyzer", layout="wide")
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st.title('CV Analyzer')
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uploaded_file = st.file_uploader("Choose a CV file", type=['pdf', 'docx', 'txt'])
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if uploaded_file is not None:
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with st.spinner('Analyzing CV...'):
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result = analyze_cv(uploaded_file)
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if "error" in result:
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st.error(result["error"])
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else:
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st.header("Detected Sections")
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st.write(result["detected_sections"])
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st.header("Section Detection Score")
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st.write(f"Score: {result['section_detection_score']}")
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st.header("Overall Content Quality Score")
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st.write(f"Score: {result['overall_score']:.2f} / 10")
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st.header("Content Quality Analysis")
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for section, evaluation in result['content_analysis'].items():
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st.subheader(section.capitalize())
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st.json(evaluation)
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st.header("Spelling and Grammar")
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st.write(f"Score: {result['spelling_grammar_score']}")
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st.header("Personal Information")
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st.json(result['personal_info'])
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st.header("Completeness Analysis")
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st.json(result['completeness_analysis'])
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if __name__ == "__main__":
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st.sidebar.title("About")
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st.sidebar.info(
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"This CV Analyzer detects sections, calculates section detection and content quality scores, "
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"checks spelling and grammar, analyzes personal information, assesses completeness, "
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"and provides a detailed content analysis."
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)
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