Fix live demo: self-healing model fetch + slimmer image#66
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- views/api.py: download the released M-4s model into the artifacts dir on first use if missing, so the deployed app works even when the image didn't bake it in (was returning model_unavailable on Render); broaden the failure path to degrade gracefully - Dockerfile: chown /app to appuser so the runtime model fetch can write - setup.py: drop unused torch/torchvision (large, never imported) to slim the build
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- views/api.py: download the released M-4s model into the artifacts dir on first use if missing, so the deployed app works even when the image didn't bake it in (was returning model_unavailable on Render); broaden the failure path to degrade gracefully - Dockerfile: chown /app to appuser so the runtime model fetch can write - setup.py: drop unused torch/torchvision (large, never imported) to slim the build
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The Render live demo returned
model_unavailablebecause the deployed container didn't have the M-4s model atmodels/triage/(it was running the new triage code on the old image/Dockerfile).views/api.pynow downloads the released M-4s model + artifact bundle into the artifacts dir on first prediction if it's missing — so the demo works regardless of how the image was built. Failures degrade gracefully.chown/app to the runtime user so that fetch can write.torch/torchvision(never imported) — large dependencies that bloated the Render build.