How yogesh-pandey090/ai-resume-analyzer works
This is a Flask resume analyzer. A user submits a PDF and selects a target role; the application extracts text, identifies skills, compares them with role requirements, and gathers job recommendations, keyword matches, and feedback before rendering a result. The tree and sampled source support this workflow, but the README is empty and template contents were not sampled, so template-to-browser wiring and the dashboard’s role are uncertain.
Main entry points: app.py Flask application · job_recommender.py Job recommendation · skills.py Skill and role data · index.html Upload page
Components 16
Web workflow
- Flask application
app.py - Upload page
templates/index.html - Analysis results
templates/result.html - Dashboard template
templates/dashboard.html - Score chart
static/chart.js
Resume analysis
- PDF text extraction
app.py - PyPDF2 reader
- Skill extraction
app.py - Skill and role data
skills.py - Role skill comparison
app.py - ATS score helper
ats.py - Keyword analysis
keyword_analyzer.py
Career guidance
- Job recommendation
job_recommender.py - Recommendation role data
job_recommender.py - Skill feedback
ai_feedback.py
Other components
- Resume user
Connections 13
- Resume user → Flask application: submits resume
- Flask application → Upload page: renders page
- Flask application → PDF text extraction: extracts text
- PDF text extraction → PyPDF2 reader: reads PDF
- Flask application → Skill extraction: finds skills
- Skill extraction → Skill and role data: checks terms
- Flask application → Role skill comparison: compares skills
- Role skill comparison → Skill and role data: reads requirements
- Flask application → Keyword analysis: finds keywords
- Flask application → Job recommendation: requests recommendation
- Job recommendation → Recommendation role data: checks roles
- Flask application → Skill feedback: requests tips
- Flask application → Analysis results: renders analysis