"""Harness B: route a scene's on-disk explicit spatial code -- as TEXT,
no video frames -- to all three models, for every VSI-Bench question.

Reuses harness.A's model registry/adapters and fixed generation protocol exactly; only
what is fed to the model differs (spatial-code text instead of frame images). Results
are written in the identical per-question JSON shape harness.A uses, so B's records are
directly comparable to A's -- the frame-provenance fields are simply replaced with
spatial-code provenance fields (see harness.B.run._build_record).
"""

from __future__ import annotations

import os
from pathlib import Path

from encoder.config import DEPTH_VARIANTS, TRACKING_MODES

from harness.A import (
    DO_SAMPLE,
    JSONL,
    MAX_NEW_TOKENS,
    MODEL_PATHS,
    TEMPERATURE,
    WORKSPACE_ROOT,
)

# The harness consumes the encoder's fixed explicit spatial-code output.
SPATIAL_CODE_FORMATS = ("explicit",)
DEFAULT_SPATIAL_CODE_FORMAT = "explicit"

# Same vocabulary as inference.SAM3_FRAME_SELECTIONS / harness.A.FRAME_SELECTIONS --
# which raw video sampling the on-disk spatial code was itself built from.
INPUT_SELECTIONS = ("uniform", "selective")
DEFAULT_INPUT_SELECTION = "uniform"

# Same depth/tracking vocabulary encoder.config uses to lay out spatial codes on disk --
# real sweepable axes here too (see sweep.py's --depths/--trackings), not fixed
# constants; DEFAULT_DEPTH/DEFAULT_TRACKING are just the single-value default when a
# caller doesn't ask to sweep them, matching this workspace's shipped production config.
DEFAULT_DEPTH = "metric"
DEFAULT_TRACKING = "tracking"

FRAMES_PER_VIDEO = int(os.environ.get("VSI_HARNESS_B_FRAMES_PER_VIDEO", "32"))

# One JSON per question, matching harness.A's layout:
# results/B/<model>/<spatial_code_format>/<depth>/<tracking>/<input_selection>/<frame_count>/<scene>/<question_id>.json
RESULTS_DIR = Path(os.environ.get("VSI_HARNESS_B_RESULTS_DIR", "/root/results/B"))