chore: import upstream snapshot with attribution
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wehub-resource-sync
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"""Runnable sandbox coding example used by docs/sandbox_agents.md.
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This example gives the model a tiny repo plus one lazy-loaded skill, then
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verifies that the agent edited the repo and ran the targeted test command.
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"""
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from __future__ import annotations
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import argparse
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import asyncio
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import json
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import sys
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from collections.abc import Sequence
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from pathlib import Path
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from agents import ModelSettings, Runner
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from agents.items import ToolCallItem, ToolCallOutputItem
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from agents.run import RunConfig
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from agents.sandbox import Manifest, SandboxAgent, SandboxRunConfig
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from agents.sandbox.capabilities import LocalDirLazySkillSource, Skills
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from agents.sandbox.capabilities.capabilities import Capabilities
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from agents.sandbox.entries import LocalDir
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from agents.sandbox.sandboxes.unix_local import UnixLocalSandboxClient
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DEFAULT_MODEL = "gpt-5.6-sol"
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TARGET_TEST_CMD = "sh tests/test_credit_note.sh"
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DEFAULT_PROMPT = (
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"Open `repo/task.md`, use the `$credit-note-fixer` skill, fix the bug, run "
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f"`{TARGET_TEST_CMD}`, and summarize the change."
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)
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EXAMPLE_DIR = Path(__file__).resolve().parent
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if __package__ is None or __package__ == "":
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sys.path.insert(0, str(Path(__file__).resolve().parents[3]))
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def build_agent(model: str) -> SandboxAgent[None]:
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return SandboxAgent(
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name="Sandbox engineer",
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model=model,
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instructions=(
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"Inspect the repo, make the smallest correct change, run the most relevant checks, "
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"and summarize the file changes and risks. "
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"Read `repo/task.md` before editing files. Stay grounded in the repository, preserve "
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"existing behavior, and use the `$credit-note-fixer` skill before editing files. "
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"When using `apply_patch`, remember that paths are relative to the sandbox workspace "
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"root, not the shell working directory, so edit files as `repo/credit_note.sh` and "
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"`repo/tests/test_credit_note.sh`. "
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f"Run the exact verification command `{TARGET_TEST_CMD}` from `repo/`, then mention "
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"that command in the final answer."
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),
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default_manifest=Manifest(
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entries={
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"repo": LocalDir(src=EXAMPLE_DIR / "repo"),
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}
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),
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capabilities=Capabilities.default()
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+ [
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Skills(
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lazy_from=LocalDirLazySkillSource(
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# This is a host path read by the SDK process.
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# Requested skills are copied into `skills_path` in the sandbox.
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source=LocalDir(src=EXAMPLE_DIR / "skills"),
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)
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),
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],
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model_settings=ModelSettings(tool_choice="required"),
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)
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async def _read_workspace_text(session, path: Path) -> str:
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handle = await session.read(path)
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try:
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payload = handle.read()
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finally:
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handle.close()
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if isinstance(payload, str):
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return payload
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return bytes(payload).decode("utf-8", errors="replace")
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def _tool_call_name(item: ToolCallItem) -> str:
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raw_item = item.raw_item
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if isinstance(raw_item, dict):
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raw_type = raw_item.get("type")
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name = raw_item.get("name")
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else:
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raw_type = getattr(raw_item, "type", None)
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name = getattr(raw_item, "name", None)
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if raw_type == "apply_patch_call":
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return "apply_patch"
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if isinstance(name, str) and name:
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return name
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if isinstance(raw_type, str) and raw_type:
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return raw_type
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return ""
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def _tool_call_arguments(item: ToolCallItem) -> dict[str, object]:
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raw_item = item.raw_item
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if isinstance(raw_item, dict):
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arguments = raw_item.get("arguments")
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else:
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arguments = getattr(raw_item, "arguments", None)
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if not isinstance(arguments, str) or arguments == "":
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return {}
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try:
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parsed = json.loads(arguments)
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except json.JSONDecodeError:
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return {"_raw": arguments}
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if isinstance(parsed, dict):
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return parsed
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return {"_value": parsed}
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def _saw_target_test_command(tool_calls: list[ToolCallItem]) -> bool:
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for item in tool_calls:
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if _tool_call_name(item) != "exec_command":
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continue
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arguments = _tool_call_arguments(item)
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cmd = arguments.get("cmd")
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workdir = arguments.get("workdir")
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if cmd == TARGET_TEST_CMD and workdir == "repo":
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return True
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if isinstance(cmd, str) and TARGET_TEST_CMD in cmd:
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return True
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if isinstance(cmd, str) and workdir == "repo" and TARGET_TEST_CMD in cmd:
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return True
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return False
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def _tool_call_debug_lines(tool_calls: list[ToolCallItem]) -> list[str]:
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lines: list[str] = []
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for item in tool_calls:
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lines.append(
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f"{_tool_call_name(item)}: {json.dumps(_tool_call_arguments(item), sort_keys=True)}"
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)
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return lines
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def _tool_output_debug_lines(new_items: Sequence[object]) -> list[str]:
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lines: list[str] = []
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for item in new_items:
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if not isinstance(item, ToolCallOutputItem):
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continue
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output = item.output
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if isinstance(output, str):
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rendered = output
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else:
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rendered = str(output)
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lines.append(rendered[:400] if len(rendered) > 400 else rendered)
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return lines
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def _saw_target_test_success(new_items: Sequence[object]) -> bool:
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awaiting_target_output = False
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for item in new_items:
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if isinstance(item, ToolCallItem):
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if _tool_call_name(item) != "exec_command":
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awaiting_target_output = False
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continue
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arguments = _tool_call_arguments(item)
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cmd = arguments.get("cmd")
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if isinstance(cmd, str) and TARGET_TEST_CMD in cmd:
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awaiting_target_output = True
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continue
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awaiting_target_output = False
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continue
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if awaiting_target_output and isinstance(item, ToolCallOutputItem):
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output = item.output
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if isinstance(output, str) and "2 passed" in output:
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return True
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awaiting_target_output = False
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return False
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async def main(model: str, prompt: str) -> None:
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agent = build_agent(model)
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client = UnixLocalSandboxClient()
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sandbox = await client.create(manifest=agent.default_manifest)
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try:
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async with sandbox:
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result = await Runner.run(
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agent,
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prompt,
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max_turns=12,
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run_config=RunConfig(
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sandbox=SandboxRunConfig(session=sandbox),
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tracing_disabled=True,
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workflow_name="Sandbox docs coding example",
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),
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)
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tool_calls = [item for item in result.new_items if isinstance(item, ToolCallItem)]
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tool_names = [_tool_call_name(item) for item in tool_calls]
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if "load_skill" not in tool_names:
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raise RuntimeError(f"Expected load_skill call, saw: {tool_names}")
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if "apply_patch" not in tool_names:
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raise RuntimeError(f"Expected apply_patch call, saw: {tool_names}")
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if not _saw_target_test_command(tool_calls):
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raise RuntimeError(
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"Expected the agent to run the targeted test command.\n"
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+ "\n".join(_tool_call_debug_lines(tool_calls))
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)
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if not _saw_target_test_success(result.new_items):
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raise RuntimeError(
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"Expected the targeted test command to report `2 passed`.\n"
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"Tool calls:\n"
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+ "\n".join(_tool_call_debug_lines(tool_calls))
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+ "\nTool outputs:\n"
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+ "\n".join(_tool_output_debug_lines(result.new_items))
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)
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verification = await sandbox.exec(
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f"cd repo && {TARGET_TEST_CMD}",
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shell=True,
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)
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verification_text = verification.stdout.decode(
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"utf-8", errors="replace"
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) + verification.stderr.decode("utf-8", errors="replace")
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if verification.exit_code != 0 or "2 passed" not in verification_text:
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raise RuntimeError(f"Post-run verification failed:\n{verification_text}")
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updated_module = await _read_workspace_text(sandbox, Path("repo/credit_note.sh"))
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print("=== Final summary ===")
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print("final_output:", result.final_output)
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print("tool_calls:", ", ".join(tool_names))
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print("verification_command:", TARGET_TEST_CMD)
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print("verification_result: observed target test output with `2 passed`")
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print("updated_credit_note.sh:")
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print(updated_module, end="" if updated_module.endswith("\n") else "\n")
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finally:
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await client.delete(sandbox)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Run a self-validating sandbox coding example used by the docs."
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)
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parser.add_argument("--model", default=DEFAULT_MODEL, help="Model name to use.")
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parser.add_argument("--prompt", default=DEFAULT_PROMPT, help="Prompt to send to the agent.")
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args = parser.parse_args()
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asyncio.run(main(args.model, args.prompt))
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