Resume Analyzer App

A shared folder with AI prompts and code snippets

From workspace: Replit

Team: AI Prompts

Total snippets: 10

Replit

Resume Analyzer App

10 snippets

10. Deploy Resume Analyzer to Replit

Package and deploy full-stack app on Replit with environment variables.

Guide for deploying the Resume Analyzer on Replit: – Use Replit's Node + Python template – Move frontend into `/frontend` and backend in `/backend` – Add `.env` with OpenAI key – Use `flask run` + React dev server with proxy or manual fetch to...

9. Polish with Dark Mode & Branding

Add basic branding and light/dark mode toggle to the app.

Improve visual style of the Resume Analyzer app. – Add a logo – Add dark/light mode toggle – Use system preference by default – Apply consistent typography + spacing

8. Add Resume History & Local Storage

Store past resume feedback in local storage for quick access.

After each analysis, save the resume file name + feedback to localStorage. Display: – Recent resumes analyzed – Click to view past AI feedback without uploading again

7. Display AI Feedback in React

Render structured resume feedback in the frontend.

Add a feedback view in React that shows: – Strengths (bullet list) – Weaknesses (bullet list) – Suggested job roles Style the layout simply and show loading while waiting for AI response.

6. Send Resume Text to AI for Feedback

Send extracted resume text to OpenAI API and return summary.

Add AI analysis logic to Flask: – Use OpenAI's Chat API – Prompt: "Analyze this resume and give strengths, weaknesses, and job fit" – Use extracted text as input – Return feedback to frontend Keep API key secure in .env.

5. Add Resume Text Extraction in Flask

Extract text from uploaded .pdf or .txt file in Flask.

Extend the `/upload` Flask endpoint to: – If file is .txt → read with open() – If file is .pdf → extract text using `PyMuPDF` or `pdfminer.six` – Return extracted text in JSON: `{ text: "..." }`

4. Send Resume from React to Flask

Connect the React frontend to Flask backend for file uploads.

Using Axios or Fetch, send the uploaded file from React to Flask `/upload`. Requirements: – Use FormData – Show success or error message on response – Display loading state during upload

3. Create Flask API Endpoint for Resume Upload

Build a Flask endpoint to receive uploaded resume files.

Create a Flask endpoint `/upload` that: – Accepts POST requests – Accepts file via `request.files['resume']` – Saves file temporarily to disk – Returns success response with file name Enable CORS for localhost:3000 (React client).

2. Build Resume Upload Component (React)

Create a file input component in React for PDF or TXT resumes.

Build a React component for uploading a resume file. Requirements: – Accept only .pdf or .txt – Allow drag-and-drop and click-to-upload – Show filename preview once selected Do not yet send the file — just capture it.

1. Setup Resume Analyzer Project Structure

Create frontend and backend folders for a resume review app.

Create a new project directory with this structure: /resume-analyzer /frontend – React app /backend – Flask API Add a README.md with the project goal: "Analyze uploaded resumes using an AI backend and return job-fit suggestions."

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