I built a free weather app that talks: how the AI morning briefing works

Description and use

An Android weather app offers a spoken AI briefing, using a server‑side model and a fallback template when the AI is unavailable.

Most weather apps provide raw data without interpretation, leaving users to interpret themselves.

The app delivers a friendly spoken briefing, reduces server load via caching, and degrades gracefully when AI is unavailable.

Fetch weather, air quality, and UV data for the user’s location.
Build a small JSON payload from the data; raw API responses are never sent elsewhere.
Send the payload to a server‑side endpoint that calls a language model and returns briefing text.
Speak the returned text using text‑to‑speech.
If the AI request fails, fall back to a templated sentence built from the same data.
Cache briefing text per weather payload to avoid redundant AI calls.

The app fetches weather, air quality and UV data for your location.

It builds a small, compact JSON payload from that data. Raw upstream API responses are never sent anywhere.

The payload is sent to a server‑side endpoint that calls the language model and returns the briefing text.

If the AI request fails, the app falls back to a templated sentence built from the same data.