whatisgithub

What is ai-resume-analyzer-and-enhancer?

adii-git/ai-resume-analyzer-and-enhancer — explained in plain English

Analysis updated 2026-05-18

0PythonAudience · general

In one sentence

A full-stack app that scores your resume against a job description like an ATS system would, then uses AI to improve it.

Mindmap

mindmap
  root((AI Resume Analyzer))
    What it does
      ATS score your resume
      AI resume enhancement
    Tech stack
      React
      FastAPI
      spaCy
    Use cases
      Job seekers
      Recruiter ranking mode
    Audience
      Job seekers
      Recruiters

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Check how well your resume matches a job description before applying.

USE CASE 2

See which keywords from the job posting are missing from your resume.

USE CASE 3

Generate an AI-improved version of your resume with a before-and-after score comparison.

USE CASE 4

Rank multiple candidate resumes against one job posting in recruiter mode.

What is it built with?

ReactFastAPIPythonspaCysentence-transformers

How does it compare?

adii-git/ai-resume-analyzer-and-enhancer0xhassaan/nn-from-scratch3ks/embedoc
Stars00
LanguagePythonPythonPython
Last pushed2023-06-08
MaintenanceDormant
Setup difficultymoderatehard
Complexity4/51/5
Audiencegeneraldeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

So what is it?

AI-Resume-Analyzer-and-Enhancer is a full-stack web application that helps job seekers understand how well their resume matches a specific job listing, and then automatically improves it. The core problem it addresses is that many employers use ATS software (Applicant Tracking Systems, automated filters that scan resumes for relevant keywords before a human ever reads them). This app lets you see your ATS score before you apply and fix gaps before they cost you an interview. You upload your resume (PDF or DOCX) and paste in a job description. The backend parses your resume using NLP (natural language processing) to extract skills and experience, then compares it against the job description using a weighted scoring formula: 40% keyword match, 20% skills relevance, 20% experience quality, and 20% formatting. It shows you exactly which keywords are present and which are missing. You can then use the AI enhancement feature, powered by OpenAI GPT-4o-mini, with a rule-based fallback if no API key is set, to generate an improved version of your resume, with a side-by-side before-and-after score comparison. The app also exports the enhanced resume as a downloadable PDF. There is a recruiter mode too: upload multiple resumes at once against a single job description to rank candidates by ATS score. The tech stack listed in the README is React 18 on the frontend, FastAPI and Python on the backend, spaCy for NLP processing, sentence-transformers for measuring semantic similarity between resume and job description text, and ReportLab for generating the output PDF. This is aimed at job seekers who want an objective, data-driven view of their resume before submitting it.

Copy-paste prompts

Prompt 1
Explain how the ATS score is calculated in this app.
Prompt 2
Walk me through setting up the backend and frontend to run this locally.
Prompt 3
What happens if I don't have an OpenAI API key for the AI enhancement feature?
Prompt 4
How does recruiter mode rank multiple resumes against one job description?

Frequently asked questions

What is ai-resume-analyzer-and-enhancer?

A full-stack app that scores your resume against a job description like an ATS system would, then uses AI to improve it.

What language is ai-resume-analyzer-and-enhancer written in?

Mainly Python. The stack also includes React, FastAPI, Python.

Who is ai-resume-analyzer-and-enhancer for?

Mainly general.

Open on GitHub → Ask about another repo

This repo across BitVibe Labs

Verify against the repo before relying on details.