.env.example

# PostgreSQL
DATABASE_URL=postgresql+asyncpg://dalston:password@localhost:5432/dalston
POSTGRES_PASSWORD=password

# Redis
REDIS_URL=redis://localhost:6379
# DALSTON_EVENTS_MAX_DELIVERIES=5
# DALSTON_EVENTS_DLQ_STREAM=dalston:events:dlq
# DALSTON_EVENTS_DLQ_MAXLEN=10000

# S3 Storage
DALSTON_S3_BUCKET=dalston-artifacts
DALSTON_S3_REGION=eu-west-2
DALSTON_S3_ENDPOINT_URL=http://localhost:9000  # For MinIO local dev
DALSTON_S3_PUBLIC_ENDPOINT_URL=http://localhost:9000  # Browser-reachable endpoint for presigned URLs
# WARNING: dummy MinIO creds. Do NOT `source .env` in a shell that also runs
# `infra/scripts/dalston-aws` — boto3 will pick up `minioadmin` as your real
# AWS access key. Export only what you need (e.g. `export HF_TOKEN=...`).
AWS_ACCESS_KEY_ID=minioadmin
AWS_SECRET_ACCESS_KEY=minioadmin

# Optional: HuggingFace (for pyannote in later milestones)
# HF_TOKEN=hf_xxxxxxxxxxxxxxxxxxxxx
# Required for pyannote models - get token from https://huggingface.co/settings/tokens
# You must also accept the model license at https://huggingface.co/pyannote/speaker-diarization

# Optional: LLM APIs (for llm-cleanup in later milestones)
# ANTHROPIC_API_KEY=sk-ant-xxxxxxxxxxxxxxxxxxxxx
# OPENAI_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxx

# Engine device selection (cuda or cpu)
# Defaults to cuda if available, falls back to cpu
# Set to cpu for local development without GPU
# DALSTON_DEVICE=cpu

# Rate Limiting (optional, these are defaults)
# DALSTON_RATE_LIMIT_REQUESTS_PER_MINUTE=600
# DALSTON_RATE_LIMIT_CONCURRENT_JOBS=10
# DALSTON_RATE_LIMIT_CONCURRENT_SESSIONS=5

# Logging (optional)
# DALSTON_LOG_LEVEL=INFO       # DEBUG, INFO, WARNING, ERROR, CRITICAL
# DALSTON_LOG_FORMAT=json      # json (production) or console (development)

# Engine availability behavior (optional)
# DALSTON_ENGINE_UNAVAILABLE_BEHAVIOR=wait        # wait or fail_fast
# DALSTON_ENGINE_WAIT_TIMEOUT_SECONDS=300         # only used when behavior=wait