Golden Hours

Shikha Singh — Sun, 11 Oct 2026 06:20:32 +0000

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass

A team project by @shikha_singh_20 and @shreyash_magar.

What I Built

Golden Hour is a calm, mobile-first web app that nudges you to step outside around sunrise and sunset.

You pick sunrise, sunset or both, and how many minutes ahead you want a reminder. When it's time, your phone gets a notification such as "Golden hour in 20 minutes. Take your chai out to the terrace." You go to your balcony or terrace, take one photo of the sky, and enjoy a chai, coffee or snack. Then you tap Done. The check-in is recorded, your streak goes up, and you put the phone away.

It's for people who spend long hours on screens and for people in apartments, where "going outside" can simply mean going to the balcony. The screen is the shortest part of the experience: a short setup, and a tap on Done.

Code

[https://github.com/shikha-code404/golden-hour]

How I Built It

Open-source pieces

Gemma (open-weight), run locally through Ollama. We used it to write the reminder messages, treat suggestions and completion lines. We generate them with scripts/make_nudges.js, review them by hand, and save them to data/nudges.json. The server picks lines from that file, so the live app doesn't need a model running.
SunCalc calculates sunrise, sunset and golden hour offline from latitude, longitude and date.
Node.js and Express for the server, and Web Push with VAPID keys for notifications. The frontend is a plain-JavaScript PWA with a service worker.
MongoDB Atlas stores subscribers, reminders and check-ins.

How it works

You allow notifications and share your location. The app stores your timezone too.
A scheduler calls our /api/tick endpoint every minute with a secret header. The endpoint plans upcoming reminders from SunCalc and sends the ones that are due.
Tapping the notification opens an "outside" screen with the camera, a treat picker and a Done button.
Your photo is saved in your phone's IndexedDB and is never uploaded. The server only stores the check-in (date, kind and optional treat) to count your streak.

Data model: subscribers (push endpoint and keys, location, timezone, preferences, lead time), reminders (kind, event time, fire time, sent time) and checkins (kind, local date, optional treat).

Hosting: Render runs the web service, defined in a render.yaml Blueprint with a /health check and secrets entered in the dashboard. Render is only hosting. Any server with Node.js and MongoDB can run the app.

How we built it: We used Antigravity as a coding assistant and built the app in phases (database, sun-time module, API, frontend, messages, deployment), checking each step ourselves.

Why Does Open Innovation Matter?

We could read and curate every message. Because Gemma is open-weight and ran on our own machine, we generated the messages, deleted the odd ones, and shipped a fixed set. We aren't relying on a hosted model whose wording or terms could change.
No per-use AI cost. The model runs once, offline, on a laptop. There are no third-party AI API keys, so the AI part of the app costs nothing to run. (Web Push and MongoDB Atlas still need their normal service credentials.)
Privacy by design. Photos of someone's home never leave their phone, and sun times are calculated with an open library instead of sending the person's location to a sun-times API.
Swappable and extensible. When a better small model appears, we can regenerate the messages and compare. Anyone can fork the repo, edit data/nudges.json, and add their own language or tone.

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