2c5e17c7c4
- 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>
48 lines
1.2 KiB
YAML
48 lines
1.2 KiB
YAML
services:
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postgres:
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image: postgres:16-alpine
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ports:
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- "5453:5432"
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environment:
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POSTGRES_USER: olivas
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POSTGRES_PASSWORD: olivas
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POSTGRES_DB: olivas
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volumes:
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- pgdata:/var/lib/postgresql/data
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healthcheck:
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test: ["CMD-SHELL", "pg_isready -U olivas"]
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interval: 5s
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timeout: 5s
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retries: 5
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backend:
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build: ./backend
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ports:
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- "8000:8000"
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environment:
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DATABASE_URL: postgresql+asyncpg://olivas:olivas@postgres:5432/olivas
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UPLOAD_DIR: /app/data/uploads
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DEVICE: auto
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CORS_ORIGINS: http://localhost:1577
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ANTHROPIC_API_KEY: ${ANTHROPIC_API_KEY:-}
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# Google Cloud Run — set these to enable Cloud Run offloading
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CLOUD_RUN_SALIENCY_URL: ${CLOUD_RUN_SALIENCY_URL:-}
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CLOUD_RUN_PROCESSING_URL: ${CLOUD_RUN_PROCESSING_URL:-}
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CLOUD_RUN_SECRET: ${CLOUD_RUN_SECRET:-}
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GOOGLE_CLOUD_PROJECT: ${GOOGLE_CLOUD_PROJECT:-optical-414516}
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volumes:
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- uploads:/app/data/uploads
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depends_on:
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postgres:
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condition: service_healthy
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frontend:
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build: ./frontend
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ports:
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- "1577:1577"
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depends_on:
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- backend
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volumes:
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pgdata:
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uploads:
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