APP_ENV=development
LOG_LEVEL=INFO
MODEL_VERSION=v3.0.0

REDIS_URL=redis://localhost:6379/0

HF_TOKEN=
# ABMIL: either local path OR Hub (Hub wins when ABMIL_HF_REPO_ID is set)
# NOTE: this code targets the scale-aware hybrid-LSE ABMIL. Point ABMIL_HF_FILENAME/REVISION
# at the RETRAINED checkpoint (the old plain-attention _v2 file will NOT load under strict=True).
MODEL_CHECKPOINT_PATH=/absolute/path/to/production_model.pt
ABMIL_HF_REPO_ID=
ABMIL_HF_FILENAME=production_model_s16plus_v3.pt
ABMIL_HF_REVISION=
ABMIL_HF_SUBFOLDER=
ABMIL_HF_LOCAL_FILES_ONLY=false

# Production backbone is ViT-S/16+ (384-dim) — must match the retrained checkpoint's input_dim.
DINOV3_MODEL_ID=facebook/dinov3-vits16plus-pretrain-lvd1689m
EMBEDDING_BATCH_SIZE=16
EMBEDDING_DEVICE=
EMBEDDING_DTYPE=
DINOV3_LOCAL_FILES_ONLY=false

REPLAY_ATTACK_TTL_S=60
PREDICTION_CACHE_TTL_S=300
MAX_IMAGE_SIZE_MB=16

# Multi-scale tiling (must match the training extraction config used to build the checkpoint's bags).
TILE_SIZES=128,64
TILE_OVERLAP_RATIO=0.25
TILE_SHRINK_FACTOR=0.92
TILE_MIN_MASK_COVERAGE=0.8

# Optional tile-quality gates — DISABLED by default to match current training extraction.
TILE_VARIANCE_GATE_ENABLED=false
TILE_MIN_VARIANCE=50.0
TILE_HIGHLIGHT_GATE_ENABLED=false
TILE_HIGHLIGHT_THRESH=235
TILE_MAX_HIGHLIGHT_FRAC=0.40

# Scale-aware hybrid-LSE ABMIL params (scale_embed_dim / num_scales are inferred from the
# checkpoint; ABMIL_LSE_R is NOT stored in the checkpoint and must match the training default).
ABMIL_SCALE_EMBED_DIM=16
ABMIL_NUM_SCALES=3
ABMIL_LSE_R=5.0