Files
deer-flow/backend/tests/conftest.py
T
Xinmin Zeng df95154282 fix(tracing): propagate session_id and user_id into Langfuse traces (#2944)
* fix(tracing): propagate session_id and user_id into Langfuse traces

Adds Langfuse v4 reserved trace attributes (langfuse_session_id,
langfuse_user_id, langfuse_trace_name, langfuse_tags) to
RunnableConfig.metadata inside the run worker, so the langchain
CallbackHandler can lift them onto the root trace.

- New deerflow.tracing.metadata.build_langfuse_trace_metadata() returns
  the reserved keys when Langfuse is in the enabled providers, else {}.
- worker.run_agent merges them with setdefault so caller-supplied keys
  win, allowing per-request overrides from upstream metadata.
- session_id mirrors the LangGraph thread_id; user_id reads
  get_effective_user_id() (falls back to "default" in no-auth mode).
- trace_name defaults to "lead-agent"; tags carry env and model name
  when DEER_FLOW_ENV (or ENVIRONMENT) and a model name are present.

Closes #2930

* fix(tracing): attach Langfuse callback at graph root so metadata propagates

The first commit injected ``langfuse_session_id`` / ``langfuse_user_id`` /
``langfuse_trace_name`` / ``langfuse_tags`` into ``RunnableConfig.metadata``,
but on ``main`` the Langfuse callback is attached at *model* level
(``models/factory.py``). LangChain still threads ``parent_run_id`` through
the contextvar, so the handler sees the model as a nested observation and
``__on_llm_action`` strips the ``langfuse_*`` keys
(``keep_langfuse_trace_attributes=False``). The trace's top-level
``sessionId`` / ``userId`` therefore stayed empty in deer-flow's LangGraph
runtime — confirmed live against a real Langfuse instance.

This commit moves the callback to the **graph invocation root** so the
handler fires ``on_chain_start(parent_run_id=None)`` and runs the
``propagate_attributes`` path that actually lifts ``session_id`` /
``user_id`` onto the trace:

- ``models/factory.py``: add ``attach_tracing`` keyword (default ``True``)
  so standalone callers (``MemoryUpdater``, etc.) keep their direct
  model-level tracing.
- ``agents/lead_agent/agent.py``: call ``build_tracing_callbacks()`` once
  inside ``_make_lead_agent`` and append the result to
  ``config["callbacks"]``; the four in-graph ``create_chat_model`` sites
  (bootstrap, default agent, sync + async summarization) pass
  ``attach_tracing=False`` to avoid duplicate spans.
- ``agents/middlewares/title_middleware.py``: same ``attach_tracing=False``
  for the title-generation model, since it inherits the graph's
  RunnableConfig via ``_get_runnable_config``.

Test updates:

- ``tests/test_lead_agent_model_resolution.py`` and
  ``tests/test_title_middleware_core_logic.py``: extend the fake
  ``create_chat_model`` signatures / mock assertions to accept the new
  ``attach_tracing`` kwarg.
- ``tests/test_worker_langfuse_metadata.py``: switch the no-user fallback
  test from direct ContextVar mutation to ``monkeypatch.setattr`` on
  ``get_effective_user_id`` to avoid pollution across the langfuse OTel
  global tracer provider.
- ``tests/conftest.py``: add an autouse fixture that resets
  ``deerflow.config.title_config._title_config`` to its pristine default
  after every test. Any test that loads the real ``config.yaml`` (via
  ``get_app_config()``) calls ``load_title_config_from_dict`` and mutates
  the module-level singleton, which previously poisoned the
  title-middleware suite when run after, e.g., the new
  ``test_worker_langfuse_metadata.py`` cases. The fixture is independent
  of this PR's main change but unblocks the cross-file test run.

Live verification (same Langfuse instance as before):

- Drove ``worker.run_agent`` against the real ``make_lead_agent`` +
  ``gpt-4o-mini`` for three distinct ``user_context`` identities
  (``fancy-engineer``, ``alice-pm``, ``bob-designer``).
- Each run produced one ``lead-agent`` trace whose top-level
  ``sessionId`` / ``userId`` / ``tags`` carry the expected values, e.g.
  ``session=e2e-2930-8f347c-alice-pm user=alice-pm name='lead-agent'
  tags=['model:gpt-4o-mini']``.

Refs #2930.

* fix(tracing): extend root-callback + metadata injection to the embedded client

Addresses Copilot review on PR #2944.

Commit 2 disabled model-level tracing for ``TitleMiddleware`` and
``_create_summarization_middleware`` because ``_make_lead_agent`` now
attaches the tracing callbacks at the graph invocation root. But the
embedded ``DeerFlowClient`` does not call ``_make_lead_agent`` — it
calls ``_build_middlewares`` directly and never appends the tracing
handlers to its ``RunnableConfig``. So under the embedded path,
title-generation and summarization LLM calls were left untraced —
a regression introduced by this PR.

This commit mirrors the gateway worker's injection in
``DeerFlowClient.stream``:

- Append ``build_tracing_callbacks()`` to ``config["callbacks"]`` so
  the Langfuse handler sees ``on_chain_start(parent_run_id=None)`` at
  the graph root and runs the ``propagate_attributes`` path.
- Merge ``build_langfuse_trace_metadata(...)`` into
  ``config["metadata"]`` with ``setdefault`` so caller-supplied keys
  still win.
- ``_ensure_agent`` now creates its main model with
  ``attach_tracing=False`` to avoid duplicate spans now that the
  callback lives at the graph root.

Docs:
- ``backend/CLAUDE.md`` Tracing section rewritten to describe the
  graph-root attachment model (replacing the inaccurate
  "at model-creation time" wording).
- ``README.md`` Langfuse section now lists both injection points
  (worker + client) instead of only the worker path.

Tests:
- ``tests/test_client_langfuse_metadata.py`` (new, 3 cases):
  callbacks + metadata are injected when Langfuse is enabled,
  caller-supplied metadata overrides win via ``setdefault``, and the
  injection is inert when Langfuse is disabled.

Live verification on the real Langfuse instance:

  === user=fancy-client ===
    id=cbd22847..  session=client-2930-6b9491-fancy-client  user=fancy-client  name='lead-agent'
  === user=alice-client ===
    id=b4f6f576..  session=client-2930-6b9491-alice-client  user=alice-client  name='lead-agent'

Refs #2930.

* refactor(tracing): address maintainer review on PR #2944

Addresses @WillemJiang's 5 comments.

1. Duplicated metadata-injection code between worker.py and client.py
   New ``deerflow.tracing.inject_langfuse_metadata(config, ...)`` helper
   takes the 10-line build + merge + setdefault logic that was duplicated
   in ``runtime/runs/worker.py`` and ``client.py``. Both callers now share
   a single source of truth, so the two paths cannot drift.

2. Direct private-attribute mutation in conftest.py and tests
   Added public ``reset_tracing_config()`` / ``reset_title_config()``
   functions. ``tests/conftest.py`` and every test that previously did
   ``tracing_module._tracing_config = None`` or
   ``title_module._title_config = TitleConfig()`` now goes through the
   public API. A future internal rename will surface as an ImportError
   instead of a silent no-op.

3. client.py reading os.environ directly
   ``DeerFlowClient.__init__`` grows an optional ``environment`` parameter
   so programmatic callers can pass the deployment label explicitly.
   ``stream()`` consults ``self._environment`` first and only falls back
   to ``DEER_FLOW_ENV`` / ``ENVIRONMENT`` env vars when nothing was
   passed in. Backwards compatible — env-var behaviour preserved for
   callers that opt to keep using it.

4. build_tracing_callbacks() cached on hot path
   Not implemented. Inspected the langfuse v4 ``langchain.CallbackHandler``
   constructor: it only resolves the module-level singleton client via
   ``get_client()`` and initialises a few dicts (no I/O, no env parsing
   at construction time). The build is essentially free. Caching would
   trade a non-measurable speedup for two real risks: handler instances
   carry per-run state internally (``_run_states``, ``_root_run_states``,
   ``last_trace_id``), and tracing config can be reloaded by env-var
   changes between runs. Will revisit if profiling ever shows it as
   a hot spot.

5. attach_tracing=False easy to forget at new in-graph call sites
   - Module docstring at the top of ``lead_agent/agent.py`` documents
     the invariant ("every in-graph ``create_chat_model`` MUST pass
     ``attach_tracing=False``") and enumerates the current sites.
   - New regression test
     ``test_make_lead_agent_attaches_tracing_callbacks_at_graph_root`` in
     ``tests/test_lead_agent_model_resolution.py`` locks both halves of
     the invariant: ``config["callbacks"]`` carries the tracing handler
     after ``_make_lead_agent``, AND every ``create_chat_model`` call
     captured by the test passes ``attach_tracing=False``. A future
     in-graph site that forgets the flag will fail this test.

Lint clean. Full touched-suite bundle: 246 passed.

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2026-05-21 16:49:31 +08:00

231 lines
7.7 KiB
Python

"""Test configuration for the backend test suite.
Sets up sys.path and pre-mocks modules that would cause circular import
issues when unit-testing lightweight config/registry code in isolation.
"""
from __future__ import annotations
import importlib.util
import sys
from pathlib import Path
from types import SimpleNamespace
from unittest.mock import MagicMock
import pytest
from support.detectors.blocking_io import BlockingIOProbe, detect_blocking_io
# Make 'app' and 'deerflow' importable from any working directory
sys.path.insert(0, str(Path(__file__).parent.parent))
sys.path.insert(0, str(Path(__file__).resolve().parents[2] / "scripts"))
_BACKEND_ROOT = Path(__file__).resolve().parents[1]
_blocking_io_probe = BlockingIOProbe(_BACKEND_ROOT)
_BLOCKING_IO_DETECTOR_ATTR = "_blocking_io_detector"
# Break the circular import chain that exists in production code:
# deerflow.subagents.__init__
# -> .executor (SubagentExecutor, SubagentResult)
# -> deerflow.agents.thread_state
# -> deerflow.agents.__init__
# -> lead_agent.agent
# -> subagent_limit_middleware
# -> deerflow.subagents.executor <-- circular!
#
# By injecting a mock for deerflow.subagents.executor *before* any test module
# triggers the import, __init__.py's "from .executor import ..." succeeds
# immediately without running the real executor module.
_executor_mock = MagicMock()
_executor_mock.SubagentExecutor = MagicMock
_executor_mock.SubagentResult = MagicMock
_executor_mock.SubagentStatus = MagicMock
_executor_mock.MAX_CONCURRENT_SUBAGENTS = 3
_executor_mock.get_background_task_result = MagicMock()
sys.modules["deerflow.subagents.executor"] = _executor_mock
@pytest.fixture()
def provisioner_module():
"""Load docker/provisioner/app.py as an importable test module.
Shared by test_provisioner_kubeconfig and test_provisioner_pvc_volumes so
that any change to the provisioner entry-point path or module name only
needs to be updated in one place.
"""
repo_root = Path(__file__).resolve().parents[2]
module_path = repo_root / "docker" / "provisioner" / "app.py"
spec = importlib.util.spec_from_file_location("provisioner_app_test", module_path)
assert spec is not None
assert spec.loader is not None
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
@pytest.fixture()
def blocking_io_detector():
"""Fail a focused test if blocking calls run on the event loop thread."""
with detect_blocking_io(fail_on_exit=True) as detector:
yield detector
def pytest_addoption(parser: pytest.Parser) -> None:
group = parser.getgroup("blocking-io")
group.addoption(
"--detect-blocking-io",
action="store_true",
default=False,
help="Collect blocking calls made while an asyncio event loop is running and report a summary.",
)
group.addoption(
"--detect-blocking-io-fail",
action="store_true",
default=False,
help="Set a failing exit status when --detect-blocking-io records violations.",
)
def pytest_configure(config: pytest.Config) -> None:
config.addinivalue_line("markers", "no_blocking_io_probe: skip the optional blocking IO probe")
def pytest_sessionstart(session: pytest.Session) -> None:
if _blocking_io_probe_enabled(session.config):
_blocking_io_probe.clear()
@pytest.hookimpl(hookwrapper=True)
def pytest_runtest_call(item: pytest.Item):
if not _blocking_io_probe_enabled(item.config) or _blocking_io_probe_skipped(item):
yield
return
detector = detect_blocking_io(fail_on_exit=False, stack_limit=18)
detector.__enter__()
setattr(item, _BLOCKING_IO_DETECTOR_ATTR, detector)
yield
@pytest.hookimpl(hookwrapper=True)
def pytest_runtest_teardown(item: pytest.Item):
yield
detector = getattr(item, _BLOCKING_IO_DETECTOR_ATTR, None)
if detector is None:
return
try:
detector.__exit__(None, None, None)
_blocking_io_probe.record(item.nodeid, detector.violations)
finally:
delattr(item, _BLOCKING_IO_DETECTOR_ATTR)
def pytest_sessionfinish(session: pytest.Session) -> None:
if _blocking_io_fail_enabled(session.config) and _blocking_io_probe.violation_count and session.exitstatus == pytest.ExitCode.OK:
session.exitstatus = pytest.ExitCode.TESTS_FAILED
def pytest_terminal_summary(terminalreporter: pytest.TerminalReporter) -> None:
if not _blocking_io_probe_enabled(terminalreporter.config):
return
header, *details = _blocking_io_probe.format_summary().splitlines()
terminalreporter.write_sep("=", header)
for line in details:
terminalreporter.write_line(line)
def _blocking_io_probe_enabled(config: pytest.Config) -> bool:
return bool(config.getoption("--detect-blocking-io") or config.getoption("--detect-blocking-io-fail"))
def _blocking_io_fail_enabled(config: pytest.Config) -> bool:
return bool(config.getoption("--detect-blocking-io-fail"))
def _blocking_io_probe_skipped(item: pytest.Item) -> bool:
return item.path.name == "test_blocking_io_detector.py" or item.get_closest_marker("no_blocking_io_probe") is not None
# ---------------------------------------------------------------------------
# Auto-set user context for every test unless marked no_auto_user
# ---------------------------------------------------------------------------
#
# Repository methods read ``user_id`` from a contextvar by default
# (see ``deerflow.runtime.user_context``). Without this fixture, every
# pre-existing persistence test would raise RuntimeError because the
# contextvar is unset. The fixture sets a default test user on every
# test; tests that explicitly want to verify behaviour *without* a user
# context should mark themselves ``@pytest.mark.no_auto_user``.
@pytest.fixture(autouse=True)
def _reset_skill_storage_singleton():
"""Reset the SkillStorage singleton between tests to prevent cross-test contamination."""
try:
from deerflow.skills.storage import reset_skill_storage
except ImportError:
yield
return
reset_skill_storage()
try:
yield
finally:
reset_skill_storage()
@pytest.fixture(autouse=True)
def _restore_title_config_singleton():
"""Reset ``_title_config`` to its pristine default after every test.
``AppConfig.from_file()`` writes the on-disk ``title`` block into the
module-level singleton (``config/app_config.py`` calls
``load_title_config_from_dict``). Any test that loads the real
``config.yaml`` therefore leaves the singleton in a state that
``test_title_middleware_core_logic.py`` does not expect; that suite
relies on the pristine ``TitleConfig()`` default (``enabled=True``).
We restore the default after every test so test files stay
independent regardless of order.
"""
try:
from deerflow.config.title_config import reset_title_config
except ImportError:
yield
return
try:
yield
finally:
reset_title_config()
@pytest.fixture(autouse=True)
def _auto_user_context(request):
"""Inject a default ``test-user-autouse`` into the contextvar.
Opt-out via ``@pytest.mark.no_auto_user``. Uses lazy import so that
tests which don't touch the persistence layer never pay the cost
of importing runtime.user_context.
"""
if request.node.get_closest_marker("no_auto_user"):
yield
return
try:
from deerflow.runtime.user_context import (
reset_current_user,
set_current_user,
)
except ImportError:
yield
return
user = SimpleNamespace(id="test-user-autouse", email="test@local")
token = set_current_user(user)
try:
yield
finally:
reset_current_user(token)