start.sh

#!/usr/bin/env bash
# Launch the MuleGuard backend (FastAPI) + frontend (Streamlit) together.
set -e

# Pre-score the bundled sample so the alert queue is populated on first load,
# unless a pre-generated store already shipped with the image.
if [ ! -f src/simulator/alerts_store.jsonl ]; then
  python -m src.simulator.feed --once || true
fi

# Backend: FastAPI scoring API on :8000 (internal).
uvicorn src.api.main:app --host 0.0.0.0 --port 8000 --log-level warning &

# Frontend: Streamlit analyst console on :7860 (exposed by the Space).
exec streamlit run dashboard/app.py \
  --server.port "${PORT:-7860}" \
  --server.address 0.0.0.0 \
  --server.headless true \
  --browser.gatherUsageStats false