Join Byte Sparkle, a curious young programmer, on an exciting adventure to build a clever AI Resume Analyzer! This delightful story brings the world of coding to life with vibrant illustrations, showing how Byte uses Python and Flask to create a helpful tool that matches resumes to dream jobs. Discover the magic of problem-solving and creation in a tale that's both educational and full of heart.
Build a Flask-based AI Resume Analyzer and Job Matcher web application using Python. Project Requirements: 1. Create a Flask web app with two pages: - Home page with: • Resume upload (PDF only) • Text area to paste job description • Submit button - Result page showing: • Resume vs Job match percentage • Missing skills list • Keyword overlap 2. Backend (Flask): - app.py as main Flask file - Route '/' for resume upload and job description input - Route '/analyze' to process resume and job description - Use PyPDF2 to extract text from uploaded resume - Clean and preprocess text (lowercase, remove symbols) 3. AI / NLP Logic: - Use TF-IDF Vectorizer from scikit-learn - Calculate cosine similarity between resume text and job description - Convert similarity score into percentage - Extract keywords from both resume and job description - Identify missing skills (job keywords not found in resume) 4. Frontend: - Simple HTML templates using Jinja2 - index.html: • Resume upload form • Job description textarea - result.html: • Display match percentage • Display missing skills • Display keyword overlap 5. Project Structure: resume-analyzer/ ├── app.py ├── resume_parser.py ├── matcher.py ├── requirements.txt ├── templates/ │ ├── index.html │ └── result.html └── static/ 6. requirements.txt should include: flask scikit-learn PyPDF2 7. The project should run locally using: python app.py Focus on functionality over UI. Keep the implementation simple, clean, and beginner-friendly.
