chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,241 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import asyncio
|
||||
import sys
|
||||
from pathlib import Path
|
||||
from typing import Any, Literal, cast
|
||||
|
||||
from openai.types.responses import ResponseTextDeltaEvent
|
||||
|
||||
from agents import ModelSettings, Runner
|
||||
from agents.run import RunConfig
|
||||
from agents.sandbox import Manifest, SandboxAgent, SandboxRunConfig
|
||||
from agents.sandbox.config import DEFAULT_PYTHON_SANDBOX_IMAGE
|
||||
from agents.sandbox.entries import File
|
||||
|
||||
if __package__ is None or __package__ == "":
|
||||
sys.path.insert(0, str(Path(__file__).resolve().parents[2]))
|
||||
|
||||
from examples.sandbox.misc.workspace_shell import WorkspaceShellCapability
|
||||
|
||||
Backend = Literal["docker", "modal"]
|
||||
WorkspacePersistenceMode = Literal["tar", "snapshot_filesystem", "snapshot_directory"]
|
||||
|
||||
DEFAULT_QUESTION = "Summarize this sandbox project in 2 sentences."
|
||||
DEFAULT_BACKEND: Backend = "docker"
|
||||
DEFAULT_MODAL_APP_NAME = "openai-agents-python-sandbox-example"
|
||||
DEFAULT_MODAL_WORKSPACE_PERSISTENCE: WorkspacePersistenceMode = "tar"
|
||||
|
||||
|
||||
def _stream_event_banner(event_name: str) -> str | None:
|
||||
if event_name == "tool_called":
|
||||
return "[tool call] shell"
|
||||
if event_name == "tool_output":
|
||||
return "[tool output] shell"
|
||||
return None
|
||||
|
||||
|
||||
def _build_manifest(backend: Backend) -> Manifest:
|
||||
backend_label = "Docker" if backend == "docker" else "Modal"
|
||||
return Manifest(
|
||||
entries={
|
||||
"README.md": File(
|
||||
content=(
|
||||
b"# Demo Project\n\n"
|
||||
+ (
|
||||
f"This sandbox contains a tiny demo project for the {backend_label} "
|
||||
"sandbox runner.\n"
|
||||
).encode()
|
||||
+ b"The goal is to show how Runner can prepare a sandbox workspace.\n"
|
||||
)
|
||||
),
|
||||
"src/app.py": File(
|
||||
content=b'def greet(name: str) -> str:\n return f"Hello, {name}!"\n'
|
||||
),
|
||||
"docs/notes.md": File(
|
||||
content=(
|
||||
b"# Notes\n\n"
|
||||
b"- The example is intentionally minimal.\n"
|
||||
b"- The model should inspect files through the shell tool.\n"
|
||||
)
|
||||
),
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
def _build_agent(*, model: str, manifest: Manifest, backend: Backend) -> SandboxAgent:
|
||||
backend_label = "Docker" if backend == "docker" else "Modal"
|
||||
return SandboxAgent(
|
||||
name=f"{backend_label} Sandbox Assistant",
|
||||
model=model,
|
||||
instructions=(
|
||||
"Answer questions about the sandbox workspace. Inspect the project before answering, "
|
||||
"and keep the response concise. "
|
||||
"Do not guess file names like package.json or pyproject.toml. "
|
||||
"This demo intentionally contains a tiny workspace."
|
||||
),
|
||||
# `default_manifest` tells the sandbox agent which workspace it should expect.
|
||||
default_manifest=manifest,
|
||||
# `WorkspaceShellCapability()` exposes one shell tool so the model can inspect files.
|
||||
capabilities=[WorkspaceShellCapability()],
|
||||
# `tool_choice="required"` makes the demo more deterministic by forcing the model
|
||||
# to look at the workspace instead of answering from prior assumptions.
|
||||
model_settings=ModelSettings(tool_choice="required"),
|
||||
)
|
||||
|
||||
|
||||
def _require_modal_dependency() -> tuple[Any, Any]:
|
||||
try:
|
||||
from agents.extensions.sandbox import ModalSandboxClient, ModalSandboxClientOptions
|
||||
except Exception as exc: # pragma: no cover - import path depends on optional extras
|
||||
raise SystemExit(
|
||||
"Modal-backed runs require the optional repo extra.\n"
|
||||
"Install it with: uv sync --extra modal"
|
||||
) from exc
|
||||
|
||||
return ModalSandboxClient, ModalSandboxClientOptions
|
||||
|
||||
|
||||
def _path_resolves_to(path: str, target: Path) -> bool:
|
||||
try:
|
||||
return Path(path or ".").resolve() == target
|
||||
except OSError:
|
||||
return False
|
||||
|
||||
|
||||
def _import_docker_from_env() -> Any:
|
||||
script_dir = Path(__file__).resolve().parent
|
||||
original_sys_path = sys.path[:]
|
||||
try:
|
||||
sys.path = [entry for entry in sys.path if not _path_resolves_to(entry, script_dir)]
|
||||
from docker import from_env as docker_from_env # type: ignore[import-untyped]
|
||||
except Exception as exc: # pragma: no cover - import path depends on local Docker setup
|
||||
raise SystemExit(
|
||||
f"Docker-backed runs failed to import the Docker SDK: {exc}\n"
|
||||
"Install the repo dependencies with: make sync\n"
|
||||
"If you are running this file directly, try:\n"
|
||||
"uv run python -m examples.sandbox.basic --backend docker"
|
||||
) from exc
|
||||
finally:
|
||||
sys.path = original_sys_path
|
||||
|
||||
return docker_from_env
|
||||
|
||||
|
||||
def _require_docker_dependency() -> tuple[Any, Any, Any]:
|
||||
docker_from_env = _import_docker_from_env()
|
||||
from agents.sandbox.sandboxes.docker import DockerSandboxClient, DockerSandboxClientOptions
|
||||
|
||||
return docker_from_env, DockerSandboxClient, DockerSandboxClientOptions
|
||||
|
||||
|
||||
async def _create_session(
|
||||
*,
|
||||
backend: Backend,
|
||||
manifest: Manifest,
|
||||
agent: SandboxAgent,
|
||||
):
|
||||
if backend == "docker":
|
||||
docker_from_env, DockerSandboxClient, DockerSandboxClientOptions = (
|
||||
_require_docker_dependency()
|
||||
)
|
||||
client = DockerSandboxClient(docker_from_env())
|
||||
sandbox = await client.create(
|
||||
manifest=manifest,
|
||||
options=DockerSandboxClientOptions(image=DEFAULT_PYTHON_SANDBOX_IMAGE),
|
||||
)
|
||||
return client, sandbox
|
||||
|
||||
ModalSandboxClient, ModalSandboxClientOptions = _require_modal_dependency()
|
||||
client = ModalSandboxClient()
|
||||
sandbox = await client.create(
|
||||
manifest=manifest,
|
||||
options=ModalSandboxClientOptions(
|
||||
app_name=DEFAULT_MODAL_APP_NAME,
|
||||
workspace_persistence=DEFAULT_MODAL_WORKSPACE_PERSISTENCE,
|
||||
),
|
||||
)
|
||||
return client, sandbox
|
||||
|
||||
|
||||
async def main(
|
||||
model: str,
|
||||
question: str,
|
||||
backend: Backend,
|
||||
) -> None:
|
||||
manifest = _build_manifest(backend)
|
||||
agent = _build_agent(model=model, manifest=manifest, backend=backend)
|
||||
client, sandbox = await _create_session(
|
||||
backend=backend,
|
||||
manifest=manifest,
|
||||
agent=agent,
|
||||
)
|
||||
|
||||
await sandbox.start()
|
||||
print(await sandbox.ls("."))
|
||||
|
||||
try:
|
||||
# `async with sandbox` keeps the example on the public session lifecycle API.
|
||||
# `Runner` reuses the already-running session without starting it a second time.
|
||||
async with sandbox:
|
||||
# `Runner.run_streamed()` drives the model and yields text and tool events in real time.
|
||||
result = Runner.run_streamed(
|
||||
agent,
|
||||
question,
|
||||
run_config=RunConfig(
|
||||
sandbox=SandboxRunConfig(session=sandbox),
|
||||
workflow_name=f"{backend.title()} sandbox example",
|
||||
),
|
||||
)
|
||||
saw_text_delta = False
|
||||
saw_any_text = False
|
||||
|
||||
# The stream contains raw text deltas from the assistant plus structured tool events.
|
||||
async for event in result.stream_events():
|
||||
if event.type == "raw_response_event" and isinstance(
|
||||
event.data, ResponseTextDeltaEvent
|
||||
):
|
||||
if not saw_text_delta:
|
||||
print("assistant> ", end="", flush=True)
|
||||
saw_text_delta = True
|
||||
print(event.data.delta, end="", flush=True)
|
||||
saw_any_text = True
|
||||
continue
|
||||
|
||||
if event.type != "run_item_stream_event":
|
||||
continue
|
||||
|
||||
banner = _stream_event_banner(event.name)
|
||||
if banner is not None:
|
||||
if saw_text_delta:
|
||||
print()
|
||||
saw_text_delta = False
|
||||
print(banner)
|
||||
|
||||
if saw_text_delta:
|
||||
print()
|
||||
if not saw_any_text:
|
||||
print(result.final_output)
|
||||
finally:
|
||||
await client.delete(sandbox)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--model", default="gpt-5.6-sol", help="Model name to use.")
|
||||
parser.add_argument("--question", default=DEFAULT_QUESTION, help="Prompt to send to the agent.")
|
||||
parser.add_argument(
|
||||
"--backend",
|
||||
default=DEFAULT_BACKEND,
|
||||
choices=["docker", "modal"],
|
||||
help="Sandbox backend to use for this example.",
|
||||
)
|
||||
args = parser.parse_args()
|
||||
asyncio.run(
|
||||
main(
|
||||
args.model,
|
||||
args.question,
|
||||
cast(Backend, args.backend),
|
||||
)
|
||||
)
|
||||
Reference in New Issue
Block a user