Sherpa

Sherpa is an AI-powered student career dashboard built for the Google AI Hackathon 2026. It helps students plan their next career move with a guided assistant, CV feedback, and internship application tracking in one place.

What Sherpa does

Sherpa brings together three key workflows:

• AI career guidance chat for personalized next steps
• CV and resume analysis with ATS-style scoring and actionable rewrite suggestions
• Internship and graduate scheme tracking across application stages

The app is designed for students who want practical support while applying for internships, graduate roles, and other early-career opportunities.

Core features

• Smart assistant chat powered by Gemini
• Personalized next-step recommendations based on profile and activity
• Resume/CV scoring with detailed feedback and rewritten bullet points
• CV generation from a LaTeX template for polished output
• Application tracking for Saved, Applied, Interview, and Offer stages
• Firebase-based authentication and profile storage

Tech stack

• Frontend: React, Vite, Tailwind CSS
• Backend: Express server with Gemini API integration
• Data: Firebase Auth + Firestore
• CV generation: LaTeX template rendering via a local LaTeX engine

Local development

Prerequisites

• Node.js
• A Gemini API key

Setup

1. Install dependencies:

   npm install

2. Create a local environment file with your Gemini key:

   echo "GEMINI_API_KEY=your_key_here" > .env.local

3. Start the app:

   npm run dev

The app runs locally at http://localhost:3000.

Useful commands

• npm run dev — start the full app (Express + Vite in middleware mode)
• npm run build — build the frontend and bundle the server
• npm start — run the production build
• npm run lint — run TypeScript type-checking

Project structure

• server.ts — Express server and Gemini API routes
• src/ — React frontend, components, and app state
• src/components/ — dashboard, CV tools, tracker, and auth UI
• templates/ — LaTeX resume template used for CV generation

Deployment notes

The CV generation endpoint depends on a LaTeX engine being available on the server path. Supported options include:

• pdflatex
• xelatex
• lualatex
• tectonic

If no LaTeX engine is installed, CV generation will return an error instead of crashing.

Notes

This project does not include a separate test suite. Type checking is available via npm run lint.