This repository contains the initial scaffold for LifeAI, an offline-first Progressive Web Application built with Next.js 14 and shadcn/ui. The goal is to deliver an AI-powered life management experience that captures multi-format notes, synchronises with Google services, and provides insights across eight pillars of human well-being.
- Next.js App Router + TypeScript foundation ready for incremental feature development.
- Tailwind CSS design system with shadcn/ui-compatible tokens and helper utilities.
- Dashboard scaffolding for notes, calendar, tasks, AI assistant, and pillar analytics.
- Firebase & Google integrations stubbed for future authentication, storage, and AI workflows.
- PWA essentials including manifest, service worker registration, and offline Dexie database layer.
The project dependencies reference private registries that may not be available in this offline environment. Run the following commands locally after cloning:
npm install
npm run devThe development server defaults to http://localhost:3000.
src/
app/
(auth)/ # Login and signup routes
(dashboard)/ # Protected dashboard sections
api/ # Future route handlers for AI, Google, and sync operations
components/
ai/ # AI assistant previews
calendar/ # Calendar timeline previews
layout/ # Shared layout components
notes/ # Note capture previews
pillars/ # 8-pillar insights
search/ # Search filters and hero
tasks/ # Task insights and kanban board
lib/
ai/ # Gemini helper (mock)
db/ # Offline Dexie helpers
firebase/ # Firebase client initialization
google-apis/ # Google API helpers
sync/ # Service worker utilities
utils/ # Shared utilities
styles/ # Tailwind configuration and CSS tokens
public/
manifest.json # PWA manifest
sw.js # Placeholder service worker
- Integrate Firebase Auth and Firestore using the stubs in
src/lib/firebase. - Replace mock UI data with live data sources and state management (e.g. Zustand).
- Connect Gemini and Google APIs for conversational AI, scheduling, and search.
- Implement offline-first note capture and background sync workflows.
- Add automated tests, accessibility refinements, and deployment scripts.
This project is released under the MIT license. Feel free to adapt and extend it for your own AI productivity experiences.