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https://github.com/NousResearch/hermes-agent.git
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Adding endless terminal environment after rebase:
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Sam Herring
parent
d0f82e6dcc
commit
9139eeaa60
4 changed files with 329 additions and 0 deletions
257
environments/endless_terminals/endless_terminals_env.py
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257
environments/endless_terminals/endless_terminals_env.py
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"""
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Endless Terminals Environment for Hermes-Agent + Atropos RL.
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Loads pre-generated terminal tasks from HuggingFace dataset and scores
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agent performance using test execution in Apptainer containers.
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Dataset: https://huggingface.co/datasets/obiwan96/endless-terminals-train
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Run:
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python environments/endless_terminals/endless_terminals_env.py process \
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--config environments/endless_terminals/default.yaml
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"""
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import asyncio
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import os
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import random
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import subprocess
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import sys
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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from pydantic import Field
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# Ensure hermes-agent root is on path
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_repo_root = Path(__file__).resolve().parent.parent.parent
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if str(_repo_root) not in sys.path:
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sys.path.insert(0, str(_repo_root))
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from atroposlib.envs.base import ScoredDataItem
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from atroposlib.type_definitions import Item
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from environments.hermes_base_env import HermesAgentBaseEnv, HermesAgentEnvConfig
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from environments.agent_loop import AgentResult
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from environments.tool_context import ToolContext
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# Add endless-terminals to path for imports
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ENDLESS_TERMINALS_PATH = os.getenv(
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"ENDLESS_TERMINALS_PATH",
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str(Path.home() / "Desktop" / "Projects" / "endless-terminals")
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)
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sys.path.insert(0, ENDLESS_TERMINALS_PATH)
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class EndlessTerminalsEnvConfig(HermesAgentEnvConfig):
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"""Configuration for Endless Terminals environment."""
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# Dataset settings
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use_dataset: bool = Field(
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default=True,
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description="Load tasks from HuggingFace dataset (recommended). If False, generate procedurally."
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)
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dataset_name: str = Field(
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default="obiwan96/endless-terminals-train",
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description="HuggingFace dataset name"
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)
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dataset_split: str = Field(
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default="train",
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description="Dataset split to use"
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)
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dataset_cache_dir: str = Field(
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default="~/.cache/huggingface/datasets",
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description="HuggingFace datasets cache directory"
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)
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tasks_base_dir: str = Field(
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default="",
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description="Base directory containing task_* folders. If empty, uses paths from dataset."
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)
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# Test execution
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test_timeout_s: int = Field(default=60, description="Test execution timeout (seconds)")
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# Agent defaults
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max_agent_turns: int = Field(default=32, description="Max turns for agent (increased for long traces)")
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class EndlessTerminalsEnv(HermesAgentBaseEnv[EndlessTerminalsEnvConfig]):
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"""
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Endless Terminals environment using pre-generated HuggingFace dataset.
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Loads terminal tasks from dataset, runs agent with terminal tools,
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and scores by executing tests in Apptainer containers.
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"""
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name = "endless_terminals_env"
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env_config_cls = EndlessTerminalsEnvConfig
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs)
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self._dataset = None
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self._dataset_indices = []
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self._current_index = 0
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async def setup(self):
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"""Load HuggingFace dataset."""
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if not self.config.use_dataset:
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print("[EndlessTerminalsEnv] Using procedural task generation (not implemented yet)", flush=True)
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return
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print(f"[EndlessTerminalsEnv] Loading dataset: {self.config.dataset_name}", flush=True)
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try:
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from datasets import load_dataset
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self._dataset = await asyncio.get_event_loop().run_in_executor(
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None,
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lambda: load_dataset(
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self.config.dataset_name,
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split=self.config.dataset_split,
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cache_dir=os.path.expanduser(self.config.dataset_cache_dir)
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)
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)
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# Create shuffled indices
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self._dataset_indices = list(range(len(self._dataset)))
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random.shuffle(self._dataset_indices)
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self._current_index = 0
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print(f"[EndlessTerminalsEnv] Loaded {len(self._dataset)} tasks from dataset", flush=True)
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except Exception as e:
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print(f"[EndlessTerminalsEnv] ERROR loading dataset: {e}", flush=True)
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raise
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async def get_next_item(self) -> Item:
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"""Sample next task from dataset."""
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if self._dataset is None:
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raise RuntimeError("Dataset not loaded. Call setup() first.")
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# Get next task (with wraparound)
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idx = self._dataset_indices[self._current_index]
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task = self._dataset[idx]
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# Advance to next task
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self._current_index += 1
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if self._current_index >= len(self._dataset_indices):
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# Reshuffle for next epoch
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random.shuffle(self._dataset_indices)
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self._current_index = 0
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print("[EndlessTerminalsEnv] Reshuffled dataset (completed one epoch)", flush=True)
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# Extract task directory path
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task_dir = task.get("extra_info", {}).get("task_dir")
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if not task_dir:
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task_dir = task.get("reward_spec", {}).get("ground_truth")
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# If tasks_base_dir is configured, reconstruct path
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if self.config.tasks_base_dir:
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original_path = Path(task_dir)
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task_name = original_path.name
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task_dir_path = Path(self.config.tasks_base_dir) / task_name
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else:
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task_dir_path = Path(task_dir)
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# Verify directory exists
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if not task_dir_path.exists():
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print(f"[EndlessTerminalsEnv] WARNING: Task dir not found: {task_dir_path}", flush=True)
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print(f"[EndlessTerminalsEnv] Hint: Set tasks_base_dir to directory containing task_* folders", flush=True)
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return await self.get_next_item() # Try next task
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container_sif = task_dir_path / "container.sif"
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final_test = task_dir_path / "test_final_state.py"
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# Verify files exist
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if not container_sif.exists() or not final_test.exists():
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print(f"[EndlessTerminalsEnv] WARNING: Missing files in {task_dir_path}", flush=True)
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return await self.get_next_item()
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return {
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"task_id": f"{task_dir_path.name}",
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"description": task.get("description", ""),
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"task_dir": str(task_dir_path),
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"container_sif": str(container_sif),
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"final_test": str(final_test),
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"dataset_index": idx,
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}
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def format_prompt(self, item: Item) -> str:
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"""Return the task description for the agent."""
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return str(item.get("description", ""))
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async def compute_reward(
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self,
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item: Item,
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result: AgentResult,
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ctx: ToolContext
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) -> float:
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"""
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Run final tests in container and return binary reward.
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Returns 1.0 if tests pass, 0.0 otherwise.
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"""
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task_id = item.get("task_id", "unknown")
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container_sif = Path(item.get("container_sif", ""))
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final_test = Path(item.get("final_test", ""))
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if not container_sif.exists() or not final_test.exists():
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print(f"[EndlessTerminalsEnv] ERROR: Missing test files for {task_id}", flush=True)
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return 0.0
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print(f"[EndlessTerminalsEnv] Running tests for {task_id}...", flush=True)
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try:
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# Run final tests in container
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success = await self._run_tests_in_container(container_sif, final_test)
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score = 1.0 if success else 0.0
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print(f"[EndlessTerminalsEnv] Task {task_id} score: {score}", flush=True)
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return score
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except Exception as e:
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print(f"[EndlessTerminalsEnv] ERROR scoring {task_id}: {e}", flush=True)
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return 0.0
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async def _run_tests_in_container(
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self,
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container_sif: Path,
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final_test_path: Path
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) -> bool:
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"""Run pytest in Apptainer container."""
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loop = asyncio.get_event_loop()
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try:
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result = await loop.run_in_executor(
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None,
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lambda: subprocess.run(
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[
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"apptainer", "exec",
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"--fakeroot",
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"--userns",
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"--writable-tmpfs",
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"--cleanenv",
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str(container_sif),
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"pytest", "-q",
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str(final_test_path.name),
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],
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capture_output=True,
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text=True,
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timeout=self.config.test_timeout_s,
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cwd=str(final_test_path.parent),
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)
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)
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return result.returncode == 0
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except subprocess.TimeoutExpired:
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print(f"[EndlessTerminalsEnv] Test timeout for {final_test_path}", flush=True)
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return False
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except Exception as e:
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print(f"[EndlessTerminalsEnv] Test execution error: {e}", flush=True)
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return False
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async def evaluate(self):
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"""Periodic evaluation (optional)."""
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return {}
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if __name__ == "__main__":
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EndlessTerminalsEnv.cli()
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