# =============================================================================
# Mnemos — end-user configuration
# =============================================================================
#
# Copy this file to `.env` (next to docker-compose.yml) and edit the values.
# Docker compose automatically reads `.env` for variable interpolation.
#
# Anything left at its default is fine for a casual home setup. Change the
# secrets before exposing Mnemos to anything beyond localhost.
#
# ---- Secrets (change these!) ------------------------------------------------

# PostgreSQL password for the pgvector database. Used by both pgvector itself
# and the backend's MNEMOS_VECTOR_DSN. Pick something long and random.
MNEMOS_PG_PASSWORD=mnemos-pgvector-changeme

# Frontend session-cookie signing key. Must be at least 32 bytes of random
# data. Generate one with:  openssl rand -hex 32
MNEMOS_FE_SECRET=change-me-please-rotate-on-first-run-32bytes

# ---- Image selection --------------------------------------------------------

# Tag of the prebuilt images to pull from ghcr.io/vithurshanselvarajah.
# Pin to a specific release (e.g. 0.1.0) once you go to production, or leave
# as "latest" to track the bleeding edge.
MNEMOS_TAG=latest

# ---- Model selection --------------------------------------------------------

# Default face-recognition model. Options: buffalo_s (fast, ~300MB) or
# buffalo_l (slower, more accurate, ~1GB). Can also be changed at runtime
# from the UI's Model page.
MNEMOS_DEFAULT_MODEL=buffalo_s

# ---- Inference backend ------------------------------------------------------
# Selects the InsightFace inference provider baked into the backend image.
# Must match a tag suffix on ghcr.io/vithurshanselvarajah/mnemos-backend,
# e.g. -cpu, -nvidia, or -rockchip. Override at deploy time with
# `MNEMOS_PROVIDER=nvidia docker compose pull` (no rebuild needed when
# pulling prebuilt images).
MNEMOS_PROVIDER=cpu