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3 commits

Author SHA1 Message Date
Vadym Samoilenko
ce1d10d9b2 Fix matplotlib.colormaps import in processing service
colormaps is a module attribute, not a submodule — remove the explicit import.
Also relax matplotlib pin back to >=3.5 (minimum for colormaps attribute).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-11 13:34:00 +00:00
Vadym Samoilenko
8eac800442 Pin matplotlib==3.9.4 in processing Cloud Run service
matplotlib.colormaps requires >=3.5; pinning avoids stale cache resolving an older version.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-11 13:30:55 +00:00
Vadym Samoilenko
2c5e17c7c4 Add Google Cloud Run offloading for ML inference and image processing
- Create cloud_run/saliency: FastAPI service running DeepGaze I/IIE/III
  on Cloud Run (4 vCPU, 16GB RAM); pre-downloads model weights in Docker
  build to eliminate cold-start delays; returns saliency map + gaze
  sequence + hotspots + design scores
- Create cloud_run/processing: lightweight FastAPI service for heatmap
  generation and gaze sequence visualization (2 vCPU, 4GB RAM)
- Add cloud_run/deploy.sh for gcloud deployment to project optical-414516
  in region europe-west2
- Refactor analysis pipeline to route via Cloud Run when
  CLOUD_RUN_SALIENCY_URL is set, with local fallback for dev mode
- Add cloud_run_client.py with sync httpx wrappers for background tasks
- Split pyproject.toml: base = API-only deps, [ml] = torch/deepgaze for
  local dev; production Dockerfile is now lightweight (~no PyTorch)
- Preserve Dockerfile.full + docker-compose.dev.yml for local ML dev
- Auth via X-Internal-Secret header (CLOUD_RUN_SECRET env var)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-04 19:39:52 +00:00