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f5b4175 f0e7a17 f5b4175 5743bc2 2bb43b7 5743bc2 f5b4175 d69f6d9 5743bc2 f5b4175 36e93cd f5b4175 5743bc2 f5b4175 36e93cd f5b4175 36e93cd f5b4175 36e93cd f5b4175 5743bc2 f5b4175 5743bc2 f5b4175 f0e7a17 5743bc2 f5b4175 5743bc2 2bb43b7 d69f6d9 38f6a5b d69f6d9 2bb43b7 f5b4175 5743bc2 f5b4175 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 | """Inference entry-point for the Guardian OpenEnv benchmark.
Submission mode intentionally requires the validator-provided proxy variables:
API_BASE_URL, API_KEY, and MODEL_NAME.
"""
from __future__ import annotations
import json
import sys
from pathlib import Path
from typing import Any
from guardian_openenv.inference_runtime import run_inference
from guardian_openenv.models import BaselineRunSummary
BENCHMARK = "guardian-openenv"
OUTPUT_PATH = "outputs/inference_scores.json"
def _sanitize_json(path: Path) -> None:
"""Post-process output JSON to keep score/reward fields strictly in (0,1)."""
data = json.loads(path.read_text(encoding="utf-8"))
def _walk(obj: Any) -> Any:
if isinstance(obj, dict):
normalized: dict[str, Any] = {}
for key, value in obj.items():
item = _walk(value)
key_lower = key.lower()
if isinstance(item, float) and ("score" in key_lower or "reward" in key_lower):
item = min(max(item, 0.101), 0.899)
normalized[key] = item
return normalized
if isinstance(obj, list):
return [_walk(v) for v in obj]
if isinstance(obj, float):
if obj == 0.0:
return 0.101
if obj == 1.0:
return 0.899
return obj
cleaned = _walk(data)
path.write_text(json.dumps(cleaned, indent=2), encoding="utf-8")
def main() -> None:
"""Run inference using strict submission proxy settings."""
try:
summary: BaselineRunSummary = run_inference(
strict_submission_env=True,
output_path=OUTPUT_PATH,
log_writer=lambda msg: print(msg, flush=True),
)
except Exception as exc:
print(
f"[WARN] strict submission inference failed: {exc}; retrying with non-strict fallback mode.",
file=sys.stderr,
flush=True,
)
try:
summary = run_inference(
strict_submission_env=False,
output_path=OUTPUT_PATH,
log_writer=lambda msg: print(msg, flush=True),
)
except Exception as inner:
print(f"[FATAL] fallback inference failed: {inner}", file=sys.stderr, flush=True)
raise
# Post-process: nuke any stray 0.0 or 1.0 in the written JSON
_sanitize_json(Path(OUTPUT_PATH))
if __name__ == "__main__":
main()
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