.env.example

# NGINX Basic Auth — single source of truth (never commit real .env)
# Generate htpasswd files: make gateway-auth
# Admin ≠ public user (usernames and passwords must both differ).
GATEWAY_ADMIN_USER=admin
GATEWAY_ADMIN_PASSWORD=change-me-gateway-admin
GATEWAY_USER=user
GATEWAY_USER_PASSWORD=change-me-gateway-user

# Inference device: auto (default in base compose). CI overlay sets CAFA_DEVICE=cpu
# via docker-compose.ci.yml; use docker-compose.gpu.yml + NVIDIA for GPU access.

# Model registry
REGISTERED_MODEL_NAME=proseqgo-model
PROMOTION_THRESHOLD=0.28

# Postgres (MLflow backend store)
POSTGRES_USER=mlflow
POSTGRES_PASSWORD=change-me-postgres
POSTGRES_DB=mlflow

# Durable job history DB (embedding + training APIs). Same Postgres instance, separate database.
JOBS_DATABASE_URL=postgresql://mlflow:change-me-postgres@postgres:5432/proseqgo_jobs

# Redis / RQ (transient job dispatch)
REDIS_URL=redis://redis:6379/0

# RQ job timeouts (seconds)
EMBEDDING_JOB_TIMEOUT_SEC=3600
TRAINING_JOB_TIMEOUT_SEC=86400

# Request envelope (MVP production limits)
MAX_SEQUENCES_PER_REQUEST=20 # 20 sequences per request
MAX_SEQUENCE_LENGTH_AA=1000 # 1000 amino acids per sequence
MAX_FASTA_UPLOAD_MB=2 # 2MB
SYNC_PREDICT_TIMEOUT_SEC=600 # 10 minutes
SYNC_PREDICT_POLL_INTERVAL_SEC=1.0 # 1 second

# MinIO (S3-compatible artifact store)
MINIO_ROOT_USER=mlflow-minio
MINIO_ROOT_PASSWORD=change-me-minio
AWS_ACCESS_KEY_ID=mlflow-minio
AWS_SECRET_ACCESS_KEY=change-me-minio

# MLflow S3
MLFLOW_S3_ENDPOINT_URL=http://minio:9000
MLFLOW_ARTIFACT_ROOT=s3://mlflow-artifacts/

# Backup sidecar
BACKUP_RETENTION_DAYS=7
BACKUP_RETENTION_WEEKS=4
BACKUP_OFFLOAD_TARGET=s3://mlflow-db-backups/