env.example

# ARIA Core — Environment Variables
# Copy to .env and customize for your deployment.

# Server
ARIA_HOST=0.0.0.0
ARIA_PORT=8090
ARIA_CORS_ORIGIN=*

# Buffer limits
ARIA_MAX_SNAPSHOTS=50000
ARIA_MAX_EVENTS=100000

# External tool paths (optional — auto-detected if installed in standard locations)
# ARIA_NASA42_MODEL_DIR=/path/to/nasa-42/Model

# LLM Cognitive Engine (optional — falls back to rule-based if not set)
# Set both vars to enable the primary cloud-LLM backend. The reference
# Python SDK is `anthropic` (see pyproject.toml); set ARIA_LLM_MODEL to
# whatever model id your SDK expects. Without the key, the engine uses
# the deterministic rule-based fallback.
# ANTHROPIC_API_KEY=
# ARIA_LLM_MODEL=

# Optional secondary advisor (google-genai SDK reads GEMINI_API_KEY).
# Provide a comma-separated rotation of model ids — lite tiers first.
# If unset, the secondary advisor is disabled.
# GEMINI_API_KEY=
# ARIA_GEMINI_MODELS=

# Logging
ARIA_LOG_LEVEL=INFO

# OpenTelemetry (optional)
# OTEL_EXPORTER_OTLP_ENDPOINT=http://tempo:4317