AI Resume Analyzer & Search

A full-stack application built with React, Express, Firebase, and Endee Vector Database.

Features

• PDF/TXT Parsing: Extract text from resumes.
• AI Analysis: Get key skills, strengths, and improvements using Gemini.
• Semantic Search: Fast vector search using Endee (with Firestore fallback).
• Secure Auth: Google Login via Firebase.

Setup

1. Prerequisites

• Node.js 18+
• Firebase Project
• Google Gemini API Key
• (Optional) Endee Vector Database running locally or in a container.

2. Environment Variables

Create a .env file in the root:

GEMINI_API_KEY=your_gemini_api_key
# Optional:
ENDEE_URL=http://localhost:8080/api/v1
ENDEE_AUTH_TOKEN=your_token

3. Firebase Configuration

Ensure firebase-applet-config.json is present in the root with your Firebase credentials:

{
  "apiKey": "...",
  "authDomain": "...",
  "projectId": "...",
  "appId": "...",
  "firestoreDatabaseId": "(default)"
}

4. Installation

npm install

5. Development

npm run dev

6. Production Deployment

1. Build the frontend:

   npm run build

2. Start the server:

   npm start

Deployment to GitHub

1. Create a new repository on GitHub.
2. Push your code:

   git init
   git add .
   git commit -m "Initial commit"
   git remote add origin <your-repo-url>
   git push -u origin main

3. Note: This is a full-stack app. GitHub Pages only supports static sites. To deploy the full app, use platforms like Cloud Run, Render, Railway, or Heroku.

Vector Database (Endee)

This app uses Endee for high-performance vector search. If Endee is not running, the app will automatically fall back to Firestore-based semantic search, so it will still work!