Datasets:
File size: 3,241 Bytes
1836fe9 | 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 | # SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: LicenseRef-NVIDIA-OneWay-Noncommercial
"""Prompts, benchmark loading and result files shared by the three stages."""
from __future__ import annotations
import json
import os
import sys
PROMPTS_DIR = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "..", "prompts"
)
def load_prompt(name: str) -> str:
"""Read a prompt text file from the top-level ``prompts/`` directory."""
with open(os.path.join(PROMPTS_DIR, name), "r", encoding="utf-8") as f:
return f.read()
PRINCIPLES = load_prompt("eval_principles.txt")
DEFAULT_QUESTION = load_prompt("eval_question_default.txt")
JUDGE_SYSTEM_PROMPT = load_prompt("eval_judge_overall_system.txt")
JUDGE_USER_TEMPLATE = load_prompt("eval_judge_overall_user.txt")
# The four prompt conditions of the paper: a 2 x 2 of task instruction
# (absent / present) and safety principles (absent / present).
PROMPT_TYPE_NAMES = ("default", "task", "principles", "task_principles")
def build_question(prompt_type: str, task: str) -> str:
question = DEFAULT_QUESTION
if prompt_type == "default":
return question
if prompt_type == "task":
return f"You are instructed to {task}. \n" + question
if prompt_type == "principles":
return PRINCIPLES + "\n" + question
if prompt_type == "task_principles":
return (
PRINCIPLES + "\n"
f"You are instructed to {task}. \n" + question
)
raise ValueError(f"Unknown prompt type: {prompt_type}")
def load_eval_items(path: str) -> list[dict]:
"""One item per benchmark entry; ``scenario_index`` is the entry's position."""
with open(path, "r", encoding="utf-8") as f:
rows = json.load(f)
if not isinstance(rows, list):
print("Scenario JSON must be an array.", file=sys.stderr)
sys.exit(1)
items: list[dict] = []
for i, row in enumerate(rows):
if not isinstance(row, dict) or not row.get("video_path"):
continue
items.append({
"scenario_index": i,
"side": row.get("side", ""),
"video_path": row["video_path"],
"task": row.get("task", ""),
"robot": row.get("robot", ""),
})
return items
def model_slug(model: str) -> str:
return model.replace("/", "_").replace(" ", "_")
def result_path(output_dir: str, stage: str, model: str, prompt_type: str,
scenario_idx: int, side: str) -> str:
"""``<output_dir>/<stage>/<model_slug>/<prompt_type>/idx_NNNN_<side>.json``."""
d = os.path.join(output_dir, stage, model_slug(model), prompt_type)
return os.path.join(d, f"idx_{scenario_idx:04d}_{side}.json")
def save_result(path: str, data: dict) -> None:
os.makedirs(os.path.dirname(path), exist_ok=True)
tmp = path + ".tmp"
with open(tmp, "w", encoding="utf-8") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
f.write("\n")
os.replace(tmp, path)
def load_result(path: str) -> dict | None:
if not os.path.isfile(path):
return None
with open(path, "r", encoding="utf-8") as f:
return json.load(f)
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