deer-flow/backend/tests/test_tiktoken_cache_and_count_tokens.py
Willem Jiang 519200728a
fix(middleware): offload memory injection off event loop to prevent tiktoken blocking (#3402) (#3411)
* fix(middleware): offload memory injection off event loop to prevent tiktoken blocking (#3402)

  DynamicContextMiddleware.abefore_agent() called _inject() synchronously
  on the asyncio event loop.  The first time memory is injected (second
  request), _inject() → format_memory_for_injection() → _count_tokens()
  → tiktoken.get_encoding("cl100k_base") needs to download the BPE data
  from openaipublic.blob.core.windows.net.  In network-restricted
  environments this download blocks until the OS TCP timeout (~26 min),
  starving ALL concurrent handlers including /api/v1/auth/me.

  Fix:
  - abefore_agent now uses asyncio.to_thread(self._inject, state) so
    file I/O and tiktoken never block the event loop.
  - Extract _get_tiktoken_encoding() with a module-level cache so
    tiktoken.get_encoding() is called at most once per encoding name.
  - Add warm_tiktoken_cache() startup helper; gateway lifespan pre-warms
    the cache via asyncio.to_thread so the first request never triggers a
    cold download.
  - _count_tokens falls back to len(text) // 4 on any encoding failure.

  Tests:
  - tests/test_tiktoken_cache_and_count_tokens.py (12 tests): cache
    hit/miss, fallback paths, warm-up helper.
  - tests/blocking_io/test_dynamic_context_middleware.py (2 tests):
    Blockbuster gate verifies abefore_agent does not block the event
    loop; async/sync parity check.

  Fixes #3402

* Apply suggestions from code review

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

* fix the lint error

* fix(memory): use future annotations to avoid NameError when tiktoken is absent

Add `from __future__ import annotations` to prompt.py so that
tiktoken.Encoding type hints are never evaluated at runtime.  Without
this, environments where tiktoken is not installed could raise NameError
on the module-level cache and function return annotations.

Addresses Copilot review comment on PR #3411.

* fix(middleware): bound abefore_agent injection with timeout to prevent hung requests

Wrap the asyncio.to_thread(self._inject) offload in asyncio.wait_for()
with a 5-second cap.  If the startup warm-up failed silently (e.g.
network blip during deploy), a cold tiktoken BPE download on the first
request can block until the OS TCP timeout (~26 min).  The bounded
timeout ensures the request degrades gracefully (no memory/date context
for that turn) rather than hanging.

Adds test_abefore_agent_returns_none_on_timeout to the blocking-IO
regression anchors.

Addresses review feedback from xg-gh-25 on PR #3411.

---------

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
2026-06-08 12:21:55 +08:00

149 lines
5.7 KiB
Python

"""Tests for tiktoken encoding cache and _count_tokens fallback.
Verifies:
- Module-level cache avoids repeated ``get_encoding`` calls.
- ``_count_tokens`` falls back to character estimation when tiktoken is
unavailable or the encoding fails to load.
- ``warm_tiktoken_cache`` populates the cache on success.
"""
from __future__ import annotations
from unittest import mock
from deerflow.agents.memory.prompt import (
_count_tokens,
_get_tiktoken_encoding,
_tiktoken_encoding_cache,
warm_tiktoken_cache,
)
# ---------------------------------------------------------------------------
# _get_tiktoken_encoding
# ---------------------------------------------------------------------------
class TestGetTiktokenEncoding:
"""Tests for _get_tiktoken_encoding caching and fallback."""
def test_returns_none_when_tiktoken_unavailable(self, monkeypatch):
monkeypatch.setattr("deerflow.agents.memory.prompt.TIKTOKEN_AVAILABLE", False)
assert _get_tiktoken_encoding("cl100k_base") is None
def test_returns_encoding_on_success(self, monkeypatch):
# Clear cache to ensure a fresh call
_tiktoken_encoding_cache.pop("cl100k_base", None)
fake_enc = mock.Mock()
monkeypatch.setattr("deerflow.agents.memory.prompt.tiktoken.get_encoding", mock.Mock(return_value=fake_enc))
enc = _get_tiktoken_encoding("cl100k_base")
assert enc is fake_enc
def test_populates_cache_on_success(self, monkeypatch):
_tiktoken_encoding_cache.pop("cl100k_base", None)
fake_enc = mock.Mock()
monkeypatch.setattr("deerflow.agents.memory.prompt.tiktoken.get_encoding", mock.Mock(return_value=fake_enc))
_get_tiktoken_encoding("cl100k_base")
assert _tiktoken_encoding_cache["cl100k_base"] is fake_enc
def test_returns_cached_encoding_without_calling_get_encoding(self, monkeypatch):
fake_enc = mock.Mock()
monkeypatch.setitem(_tiktoken_encoding_cache, "cl100k_base", fake_enc)
# Now patch tiktoken.get_encoding to raise if called
import tiktoken
monkeypatch.setattr(tiktoken, "get_encoding", mock.Mock(side_effect=RuntimeError("should not be called")))
# Cached path — should NOT call get_encoding
enc = _get_tiktoken_encoding("cl100k_base")
assert enc is fake_enc
tiktoken.get_encoding.assert_not_called()
def test_returns_none_and_warns_on_get_encoding_failure(self, monkeypatch):
_tiktoken_encoding_cache.pop("bogus_encoding", None)
import tiktoken
monkeypatch.setattr(tiktoken, "get_encoding", mock.Mock(side_effect=OSError("download failed")))
result = _get_tiktoken_encoding("bogus_encoding")
assert result is None
assert "bogus_encoding" not in _tiktoken_encoding_cache
# ---------------------------------------------------------------------------
# _count_tokens
# ---------------------------------------------------------------------------
class TestCountTokens:
"""Tests for _count_tokens fallback behaviour."""
def test_returns_character_estimate_when_tiktoken_unavailable(self, monkeypatch):
monkeypatch.setattr("deerflow.agents.memory.prompt.TIKTOKEN_AVAILABLE", False)
text = "Hello, world! This is a test."
result = _count_tokens(text)
assert result == len(text) // 4
def test_returns_character_estimate_when_encoding_fails(self, monkeypatch):
monkeypatch.setattr(
"deerflow.agents.memory.prompt._get_tiktoken_encoding",
lambda _name=None: None,
)
text = "Some text to count"
result = _count_tokens(text)
assert result == len(text) // 4
def test_returns_token_count_on_success(self, monkeypatch):
fake_enc = mock.Mock()
fake_enc.encode.return_value = [0, 1, 2, 3]
monkeypatch.setattr("deerflow.agents.memory.prompt._get_tiktoken_encoding", mock.Mock(return_value=fake_enc))
text = "Hello, world!"
result = _count_tokens(text)
assert result == 4
assert result <= len(text)
def test_falls_back_on_encode_exception(self, monkeypatch):
# Cache an encoding whose .encode raises
fake_enc = mock.Mock()
fake_enc.encode.side_effect = RuntimeError("encode failed")
monkeypatch.setitem(_tiktoken_encoding_cache, "test_enc", fake_enc)
text = "Fallback test"
result = _count_tokens(text, encoding_name="test_enc")
assert result == len(text) // 4
# ---------------------------------------------------------------------------
# warm_tiktoken_cache
# ---------------------------------------------------------------------------
class TestWarmTiktokenCache:
"""Tests for warm_tiktoken_cache startup helper."""
def test_returns_true_on_success(self, monkeypatch):
_tiktoken_encoding_cache.pop("cl100k_base", None)
fake_enc = mock.Mock()
monkeypatch.setattr("deerflow.agents.memory.prompt.tiktoken.get_encoding", mock.Mock(return_value=fake_enc))
assert warm_tiktoken_cache() is True
assert _tiktoken_encoding_cache["cl100k_base"] is fake_enc
def test_returns_true_if_already_cached(self, monkeypatch):
fake_enc = mock.Mock()
monkeypatch.setitem(_tiktoken_encoding_cache, "cl100k_base", fake_enc)
import tiktoken
monkeypatch.setattr(tiktoken, "get_encoding", mock.Mock(side_effect=RuntimeError("should not be called")))
assert warm_tiktoken_cache() is True
tiktoken.get_encoding.assert_not_called()
def test_returns_false_when_tiktoken_unavailable(self, monkeypatch):
monkeypatch.setattr("deerflow.agents.memory.prompt.TIKTOKEN_AVAILABLE", False)
assert warm_tiktoken_cache() is False