File size: 3,195 Bytes
e918a5c | 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 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
"""Agent-safe evaluation protocol helpers for pathway_analysis_env."""
from __future__ import annotations
from copy import deepcopy
from typing import Any, Dict, List, Optional
from ..models import PathwayObservation
# Keys never sent to agents when eval_mode is on.
_AGENT_METADATA_BLOCKLIST = frozenset(
{
"correct",
"static_top_genes",
"static_top_pathways",
"true_pathway",
"ground_truth",
"episode_score",
}
)
def default_max_steps(case: Dict[str, Any]) -> int:
return max(5, int(case.get("max_steps", 30)))
def resolve_eval_mode(case: Dict[str, Any], reset_kwargs: Dict[str, Any]) -> bool:
"""Eval mode is on unless reset(eval_mode=False) or case sets eval_mode: false."""
if "eval_mode" in reset_kwargs:
return bool(reset_kwargs["eval_mode"])
return bool(case.get("eval_mode", True))
def resolve_orchestrator_mode(case: Dict[str, Any], reset_kwargs: Dict[str, Any]) -> bool:
"""Expose scoring details in metadata (for in-repo harnesses only)."""
if "orchestrator_mode" in reset_kwargs:
return bool(reset_kwargs["orchestrator_mode"])
return bool(case.get("orchestrator_mode", False))
def shaping_reward(eval_mode: bool, nominal: float) -> float:
"""Zero intermediate shaping in eval mode; terminal scoring is separate."""
if eval_mode:
return 0.0
return nominal
def sanitize_metadata_for_agent(
metadata: Optional[Dict[str, Any]], *, eval_mode: bool
) -> Dict[str, Any]:
if not metadata:
return {}
if not eval_mode:
return dict(metadata)
out = {k: v for k, v in metadata.items() if k not in _AGENT_METADATA_BLOCKLIST}
return out
def sanitize_observation_for_agent(
obs: PathwayObservation,
*,
eval_mode: bool,
orchestrator_mode: bool,
reward_override: Optional[float] = None,
) -> PathwayObservation:
if not eval_mode:
return obs
meta = sanitize_metadata_for_agent(obs.metadata, eval_mode=True)
if orchestrator_mode and obs.metadata and "correct" in obs.metadata:
meta["correct"] = obs.metadata["correct"]
if orchestrator_mode and obs.metadata and "episode_score" in obs.metadata:
meta["episode_score"] = obs.metadata["episode_score"]
reward = obs.reward if reward_override is None else reward_override
if eval_mode and not orchestrator_mode:
# Hide reward signal except strict terminal failures (negative).
if obs.done and reward and reward > 0:
reward = 0.0
elif not obs.done:
reward = 0.0
return obs.model_copy(
update={
"metadata": meta,
"reward": reward,
}
)
def strip_legacy_answer_leaks(
inspect_meta: Dict[str, Any], *, eval_mode: bool
) -> Dict[str, Any]:
if not eval_mode:
return inspect_meta
out = dict(inspect_meta)
out.pop("static_top_genes", None)
out.pop("static_top_pathways", None)
return out
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