ResumeAI — AI Resume Analyzer

ResumeAI is a full-stack AI-powered resume analysis platform built with Next.js. Users can upload their resume PDF, choose a target role, optionally paste a job description, and receive an AI-generated report with ATS score, job match score, skill gaps, missing keywords, strengths, weaknesses, and improvement suggestions.

Features

• Secure authentication with Clerk
• Protected routes and user-specific data
• Resume PDF upload using UploadThing
• Resume metadata storage in MongoDB Atlas
• AI resume analysis using Gemini API
• ATS score generation
• Resume vs job description match analysis
• Skill gaps and missing job keywords
• AI-generated strengths, weaknesses, and suggestions
• Dashboard with analytics and charts
• Previous analysis history
• Delete resume/report with confirmation dialog
• Toast notifications for better UX
• Responsive and modern UI with Tailwind CSS and shadcn/ui
• PDF report download support

Tech Stack

Area	Technology
Framework	Next.js App Router
Language	JavaScript
Styling	Tailwind CSS
UI Components	shadcn/ui
Authentication	Clerk
Database	MongoDB Atlas
ODM	Mongoose
File Upload	UploadThing
AI	Gemini API
Charts	Recharts
Notifications	Sonner
Deployment	Vercel

Pages

/                  Landing page
/sign-in           Clerk sign-in page
/sign-up           Clerk sign-up page
/analyze           Resume upload and analysis form
/report/[id]       AI-generated resume report
/dashboard         User dashboard and report history

Project Workflow

User signs in
↓
Uploads resume PDF
↓
Adds target role and optional job description
↓
Resume is uploaded to UploadThing
↓
Resume details are saved in MongoDB
↓
Gemini analyzes the resume PDF
↓
Report is saved in MongoDB
↓
User views ATS score, job match score, skills, keywords, and suggestions

Environment Variables

Create a .env.local file in the project root and add:

MONGODB_URI=your_mongodb_atlas_connection_string
UPLOADTHING_TOKEN=your_uploadthing_token
GEMINI_API_KEY=your_gemini_api_key
NEXT_PUBLIC_APP_URL=http://localhost:3000

NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY=your_clerk_publishable_key
CLERK_SECRET_KEY=your_clerk_secret_key
NEXT_PUBLIC_CLERK_SIGN_IN_URL=/sign-in
NEXT_PUBLIC_CLERK_SIGN_UP_URL=/sign-up
NEXT_PUBLIC_CLERK_SIGN_IN_FALLBACK_REDIRECT_URL=/dashboard
NEXT_PUBLIC_CLERK_SIGN_UP_FALLBACK_REDIRECT_URL=/dashboard

For production deployment, use Clerk live keys instead of development keys.

Installation

Clone the repository:

git clone https://github.com/your-username/ai-resume-analyzer.git
cd ai-resume-analyzer

Install dependencies:

npm install

Run the development server:

npm run dev

Open the app:

http://localhost:3000

Main Functional Modules

Authentication

Clerk is used for login, signup, session management, and protected routes. Each resume and report is linked to the authenticated user's Clerk user ID.

Resume Upload

UploadThing handles secure PDF upload. After upload completion, the file URL and metadata are saved in MongoDB.

AI Analysis

Gemini API analyzes the uploaded PDF and returns structured JSON including:

ATS score
Job match score
Summary
Strengths
Weaknesses
Skill gaps
Recommended keywords
Matching skills
Missing job keywords
Improvement suggestions
Project suggestions
Formatting issues

Dashboard

The dashboard shows:

Total analyses
Completed reports
Average ATS score
Best ATS score
Recent analyses table
ATS score charts

Folder Structure

src/
  app/
    api/
      dashboard/
      reports/
      resumes/
      uploadthing/
    analyze/
    dashboard/
    report/[id]/
    sign-in/
    sign-up/
    layout.js
    page.js
  components/
    dashboard/
    report/
    shared/
    ui/
  lib/
    db.js
    gemini.js
    uploadthing.js
  models/
    Resume.js
    Report.js
  proxy.js

API Routes

Route	Method	Description
/api/resumes	POST	Save uploaded resume details
/api/resumes/[id]	GET	Get single resume for logged-in user
/api/resumes/[id]	DELETE	Delete resume and related report
/api/reports/generate	POST	Generate AI report using Gemini
/api/reports/[resumeId]	GET	Get report by resume ID
/api/dashboard	GET	Get dashboard stats and recent analyses
/api/uploadthing	GET/POST	UploadThing file upload route

Deployment

This project can be deployed on Vercel.

Deployment checklist:

Add all environment variables in Vercel
Use Clerk production/live keys
Update NEXT_PUBLIC_APP_URL with deployed URL
Allow production domain in Clerk dashboard
Allow production domain in UploadThing if required
Test login, upload, analysis, dashboard, and report pages

Author

Meet Vora

• GitHub: https://github.com/MeetVora79
• LinkedIn: https://linkedin.com/in/meetvora79
• Email: meetvora877@gmail.com