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End-to-end variant interpretation platform for rare genetic disease research: SvelteKit UI, FastAPI + PostgreSQL API, Nextflow/Ensembl VEP pipeline, LightGBM pathogenicity scoring with MLflow, K8s/ArgoCD/GCP infrastructure. Public test data only; no clinical claims.
16 lines
588 B
Python
16 lines
588 B
Python
from pydantic_settings import BaseSettings, SettingsConfigDict
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class Settings(BaseSettings):
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model_config = SettingsConfigDict(env_file=".env", extra="ignore")
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database_url: str = "postgresql+asyncpg://rarelens:rarelens@localhost:5432/rarelens"
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mlflow_tracking_uri: str = "http://localhost:5000"
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model_name: str = "rarelens-pathogenicity"
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model_stage: str = "Production"
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gcs_bucket: str | None = None # set in GCP; local uses ./data
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pubsub_topic: str | None = None # "vcf-uploaded" in GCP; local runs pipeline inline
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settings = Settings()
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