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cd601a6 ec8b2ca cd601a6 ec8b2ca cd601a6 ec8b2ca cd601a6 ec8b2ca cd601a6 ec8b2ca cd601a6 ec8b2ca cd601a6 ec8b2ca cd601a6 ec8b2ca cd601a6 ec8b2ca | 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 | # 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.
"""
Data models for the Self-Healing DevOps Sandbox Environment.
Defines the Action and Observation types used by the RL agent to interact
with a broken Node.js backend. The agent acts as a DevOps engineer, diagnosing
and fixing production-like bugs using bash commands.
"""
from typing import Any, Dict, List, Optional
from pydantic import Field
from openenv.core.env_server.types import Action, Observation
class BashAction(Action):
"""Action: a bash command to execute inside the sandbox.
The agent sends shell commands (ls, cat, sed, grep, node, npm, etc.)
to diagnose and repair the broken Node.js application.
"""
command: str = Field(
...,
description=(
"The bash command to execute in the sandbox terminal "
"(e.g., 'ls -la', 'cat server.js', "
"'sed -i s/old/new/ file.js')."
),
)
class TerminalObservation(Observation):
"""Observation returned after executing a bash command.
Includes stdout/stderr from the command, working directory context,
the current task identifier, grader's partial score, and episode metadata.
"""
stdout: str = Field(
default="",
description="Standard output from the executed command.",
)
stderr: str = Field(
default="",
description="Standard error from the executed command, if any.",
)
current_dir: str = Field(
default="/app",
description="The current working directory inside the container.",
)
task_id: str = Field(
default="devops_sandbox",
description="Identifier for the current task scenario (easy/medium/hard).",
)
grader_score: float = Field(
default=0.01,
ge=0.0,
le=1.0,
description="The grader's partial reward strictly within (0, 1).",
)
grader_feedback: str = Field(
default="",
description="Human-readable feedback from the grader.",
)
done: bool = Field(
default=False,
description="Whether the episode is complete (all bugs fixed or max steps reached).",
)
reward: Optional[float] = Field(
default=None,
description="Incremental reward for this step (score delta).",
)
metadata: Dict[str, Any] = Field(
default_factory=dict,
description="Additional metadata: files_modified, commands_count, bugs_found, etc.",
)
__all__ = ["BashAction", "TerminalObservation"] |