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2026-07-13 11:59:58 +08:00

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Python

"""Regression anchor: UploadsMiddleware must not block the event loop.
``before_agent`` scans the thread uploads directory (``exists`` / ``iterdir`` /
``stat`` plus reading sibling ``.md`` outlines). LangChain wires a sync-only
``before_agent`` as ``RunnableCallable(before_agent, None)``; langgraph's
``ainvoke`` runs it directly on the event loop when ``afunc is None``. So the
filesystem scan must be offloaded (the middleware provides ``abefore_agent``).
This anchor drives the real ``create_agent`` graph via ``ainvoke`` under the
strict Blockbuster gate. If the scan regresses back onto the event loop,
Blockbuster raises ``BlockingError`` and this test fails.
The graph/middleware construction is offloaded with ``asyncio.to_thread`` only
because ``Paths.__init__`` resolves paths synchronously; the surface under test
(``before_agent``'s directory scan) is exercised on the event loop, not
bypassed.
"""
from __future__ import annotations
import asyncio
from pathlib import Path
import pytest
from langchain_core.language_models.fake_chat_models import FakeMessagesListChatModel
from langchain_core.messages import AIMessage, HumanMessage
pytestmark = pytest.mark.asyncio
class _FakeModel(FakeMessagesListChatModel):
"""FakeMessagesListChatModel with a no-op ``bind_tools`` for create_agent."""
def bind_tools(self, tools, **kwargs): # type: ignore[override]
return self
async def test_before_agent_uploads_scan_does_not_block_event_loop(tmp_path: Path) -> None:
from langchain.agents import create_agent
from deerflow.agents.middlewares.uploads_middleware import UploadsMiddleware
from deerflow.runtime.user_context import get_effective_user_id
mw = await asyncio.to_thread(UploadsMiddleware, str(tmp_path))
uploads_dir = await asyncio.to_thread(mw._paths.sandbox_uploads_dir, "t1", user_id=get_effective_user_id())
uploads_dir.mkdir(parents=True, exist_ok=True) # test-side seeding (not in scanned_modules)
(uploads_dir / "existing.txt").write_text("hello", encoding="utf-8")
agent = await asyncio.to_thread(lambda: create_agent(model=_FakeModel(responses=[AIMessage(content="ok")]), tools=[], middleware=[mw]))
result = await agent.ainvoke(
{"messages": [HumanMessage(content="hi")]},
{"configurable": {"thread_id": "t1"}},
)
assert result["messages"]