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d2961aabae
* fix(uploads): keep malformed metadata from aborting chat turns * fix(uploads): log skipped probes and bound size labels --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
70 lines
2.9 KiB
Python
70 lines
2.9 KiB
Python
"""Regression anchor: UploadsMiddleware must not block the event loop.
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``before_agent`` scans the thread uploads directory (``exists`` / ``iterdir`` /
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``stat`` plus reading sibling ``.md`` outlines). LangChain wires a sync-only
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``before_agent`` as ``RunnableCallable(before_agent, None)``; langgraph's
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``ainvoke`` runs it directly on the event loop when ``afunc is None``. So the
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filesystem scan must be offloaded (the middleware provides ``abefore_agent``).
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This anchor drives the real ``create_agent`` graph via ``ainvoke`` under the
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strict Blockbuster gate. If the scan regresses back onto the event loop,
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Blockbuster raises ``BlockingError`` and this test fails.
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The graph/middleware construction is offloaded with ``asyncio.to_thread`` only
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because ``Paths.__init__`` resolves paths synchronously; the surface under test
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(``before_agent``'s directory scan) is exercised on the event loop, not
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bypassed.
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"""
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from __future__ import annotations
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import asyncio
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from pathlib import Path
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import pytest
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from langchain_core.language_models.fake_chat_models import FakeMessagesListChatModel
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from langchain_core.messages import AIMessage, HumanMessage
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pytestmark = pytest.mark.asyncio
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class _FakeModel(FakeMessagesListChatModel):
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"""FakeMessagesListChatModel with a no-op ``bind_tools`` for create_agent."""
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def bind_tools(self, tools, **kwargs): # type: ignore[override]
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return self
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@pytest.mark.parametrize(
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"files,size,size_label",
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[
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(None, None, None),
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([{"filename": 42}, {"filename": "existing.txt", "size": "1" + "0" * 400}], 0, "0.0 KB"),
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([{"filename": "existing.txt", "size": 10**308}], 10**308, ">= 1 TB"),
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],
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ids=["no-current-files", "malformed-with-valid-sibling", "huge-finite-size"],
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)
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async def test_before_agent_uploads_scan_does_not_block_event_loop(tmp_path: Path, files, size, size_label) -> None:
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from langchain.agents import create_agent
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from deerflow.agents.middlewares.uploads_middleware import UploadsMiddleware
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from deerflow.runtime.user_context import get_effective_user_id
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mw = await asyncio.to_thread(UploadsMiddleware, str(tmp_path))
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uploads_dir = await asyncio.to_thread(mw._paths.sandbox_uploads_dir, "t1", user_id=get_effective_user_id())
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uploads_dir.mkdir(parents=True, exist_ok=True) # test-side seeding (not in scanned_modules)
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(uploads_dir / "existing.txt").write_text("hello", encoding="utf-8")
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agent = await asyncio.to_thread(lambda: create_agent(model=_FakeModel(responses=[AIMessage(content="ok")]), tools=[], middleware=[mw]))
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result = await agent.ainvoke(
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{"messages": [HumanMessage(content="hi", additional_kwargs={"files": files})]},
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{"configurable": {"thread_id": "t1"}},
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)
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assert result["messages"]
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if files:
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assert [file["filename"] for file in result["uploaded_files"]] == ["existing.txt"]
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assert result["uploaded_files"][0]["size"] == size
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assert f"existing.txt ({size_label})" in result["messages"][0].content
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