# Ilera — Field Triage Assistant
**Multimodal, multilingual, agentic triage support for community health workers — built on Gemma 4.**
> Built for the *Build with Gemma: AI for Africa* Hackathon (Minna, 2026)
🔗 **Live demo:
ilera-mc67.onrender.com
A health worker describes symptoms (and optionally attaches a photo).
Gemma returns a structured triage assessment — severity, likely conditions,
red flags, recommended action — which can be output in English, Hausa, or
Yoruba. The system then autonomously drafts a referral note and schedules
a follow-up based on urgency
## Why this isn't "just a chat prompt"
- **Multimodal reasoning, not captioning.** Gemma 4 reasons jointly over a
photo and free-text notes to produce a differential and flag risks a
non-specialist might miss (e.g. the elevated danger of facial infections
spreading via the "danger triangle").
- **Structured output that drives real logic.** Gemma's response is forced
into a strict JSON schema via the API's `responseSchema` feature. That
object — not free text — is what the referral and follow-up scheduling
logic actually runs on.
- **Local language, done carefully.** Clinical reasoning stays in English
internally (more reliable to validate). Only the final output is
translated, and it's back-translated and confidence-checked before being
shown — Gemma auditing Gemma's own translation. See `translate.py`.
- **Agentic follow-through.** The triage result triggers real downstream
action: a referral note is drafted and a follow-up is scheduled
automatically based on urgency. See `agent.py`.
## Setup
To run it locally:
```bash
cd ilera
python3 -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
# edit .env and paste in your ownGemma API key (from Google AI Studio)
```
### Find your exact model name first — don't guess it
Gemma 4 uses capability-tier naming (e.g. `gemma-4-31b-it`,
`gemma-4-26b-a4b-it`), not the p …