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Manthan Ankolekar
Manthan Ankolekar

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🚀 Building an AI-Powered Resume Optimizer with Angular, Node.js & Gemini

#webdev #programming #beginners #angular

Struggling to tailor your resume for specific job postings? I built an AI-powered Resume Optimizer that helps you analyze your resume against any job description using Google Gemini. Here's how I built it using the MEAN stack (MongoDB-free) with Angular standalone components, Tailwind CSS, and Google’s Generative AI API.

💡 Why I Built This

Every job role has unique expectations, but most resumes stay generic. I wanted to automate the process of matching resumes with job descriptions, highlighting what's missing, and suggesting improvements—all with the power of AI.

🛠 Tech Stack

Layer Stack
Frontend Angular 20, Standalone Components, Tailwind CSS, Signals, Reactive Forms
Backend Node.js, Express, Multer
AI Engine Google Gemini via @google/genai
Parsing pdf-parse and mammoth for file extraction

🧠 Features

  • ✅ Upload Resume (PDF or DOCX)
  • ✅ Upload or Paste Job Description

  • ✅ Get AI analysis:

    • Match Score
    • Missing Keywords
    • Tailored Suggestions

  • 🌗 Dark Mode Support

  • 📱 Fully Responsive UI

🧩 System Architecture 

[Angular UI] --> [Express API] --> [Gemini API]
                    |
             [PDF/DOCX Parser]
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🖥️ Frontend Highlights

  • Standalone Angular Components
  • Signals for local state (resumeFile, jdFile, etc.)
  • Native control flow (@if, @else) over structural directives
  • Reactive Forms for input validation
  • Markdown rendering using ngx-markdown for AI response formatting 
const form = fb.nonNullable.group({ jdText: '' });
const resumeFile = signal<File | null>(null);
const result = signal<string | null>(null);
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🔧 Backend Highlights

  • File parsing using pdf-parse (PDF) and mammoth (DOCX)
  • Gemini prompt format: 
Compare the following resume and job description. Provide:
- Match score (0-100)
- Missing keywords
- Suggested improvements
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  • AI integration via @google/genai: 
const ai = new GoogleGenAI({ apiKey: process.env.GEMINI_API_KEY });
const response = await ai.models.generateContent({ model: 'gemini-2.5-flash', contents: prompt });
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🚀 How to Run It Locally

🔗 Clone the Project 

git clone https://github.com/manthanank/resume-optimizer.git
cd resume-optimizer
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⚙️ Backend Setup 

cd backend
npm install
cp .env.example .env
# Add your GEMINI_API_KEY
npm run dev
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🌐 Frontend Setup 

cd frontend
npm install
ng serve
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🌐 Hosted Live (Demo)

📦 Future Improvements

  • 🔐 Auth for saving resume history
  • 📝 Editable resume templates
  • 📄 PDF download of feedback
  • 🌍 Multi-language support

📃 License

MIT — Free to use and modify. Contributions welcome!

✨ Final Thoughts

This project taught me how to combine real-time file processing with AI content generation in a full-stack TypeScript environment. Whether you're building something for HR, job seekers, or just love AI—this app is a perfect side project to learn from.

👉 Want to try it?
🔗 GitHub Repo
🚀 Live Demo

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