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>
41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
from pydantic_settings import BaseSettings
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class Settings(BaseSettings):
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DATABASE_URL: str = "postgresql+asyncpg://olivas:olivas@localhost:5453/olivas"
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UPLOAD_DIR: str = "./data/uploads"
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DEVICE: str = "auto" # auto | cpu | cuda
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ANTHROPIC_API_KEY: str = ""
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CORS_ORIGINS: str = "http://localhost:1577"
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BACKEND_HOST: str = "0.0.0.0"
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BACKEND_PORT: int = 8000
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# Google Cloud Run service URLs (empty = use local processing)
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CLOUD_RUN_SALIENCY_URL: str = "" # e.g. https://olivas-saliency-xxx-ew.a.run.app
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CLOUD_RUN_PROCESSING_URL: str = "" # e.g. https://olivas-processing-xxx-ew.a.run.app
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CLOUD_RUN_SECRET: str = "" # Shared secret for X-Internal-Secret header
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GOOGLE_CLOUD_PROJECT: str = "optical-414516"
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@property
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def use_cloud_run(self) -> bool:
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return bool(self.CLOUD_RUN_SALIENCY_URL)
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@property
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def device(self) -> str:
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if self.DEVICE == "auto":
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try:
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import torch
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return "cuda" if torch.cuda.is_available() else "cpu"
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except ImportError:
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return "cpu"
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return self.DEVICE
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@property
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def cors_origins_list(self) -> list[str]:
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return [o.strip() for o in self.CORS_ORIGINS.split(",")]
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model_config = {"env_file": ".env", "env_file_encoding": "utf-8"}
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settings = Settings()
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