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https://github.com/headroomlabs-ai/headroom.git
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82 lines
2.7 KiB
Python
82 lines
2.7 KiB
Python
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"""tiktoken vocab loading must be bounded (GH #956).
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tiktoken downloads its BPE vocab via ``requests.get`` with no timeout, so a
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stalled/firewalled connection blocks indefinitely. The proxy calls this lazily
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inside a request worker, so the only bound was the 30s compression timeout —
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yielding "every request times out, 0 compression". The bounded loader caps the
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wait and falls back to estimation instead.
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"""
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from __future__ import annotations
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import time
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import pytest
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from headroom.tokenizers import tiktoken_counter as tc
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from headroom.tokenizers.estimator import EstimatingTokenCounter
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from headroom.tokenizers.registry import TokenizerRegistry
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@pytest.fixture(autouse=True)
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def _reset_encoding_state():
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tc._get_encoding.cache_clear()
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tc._load_failed.clear()
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yield
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tc._get_encoding.cache_clear()
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tc._load_failed.clear()
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def _stalled_get_encoding(_name: str):
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# Simulates tiktoken's unbounded network download stalling.
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time.sleep(2.0)
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return object()
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def test_load_encoding_is_bounded_on_stall(monkeypatch: pytest.MonkeyPatch) -> None:
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import tiktoken
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monkeypatch.setattr(tiktoken, "get_encoding", _stalled_get_encoding)
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monkeypatch.setenv("HEADROOM_TIKTOKEN_LOAD_TIMEOUT_SECONDS", "0.2")
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start = time.perf_counter()
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with pytest.raises(tc.TiktokenLoadError):
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tc.load_encoding("stall-enc")
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elapsed = time.perf_counter() - start
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assert elapsed < 1.5, f"load was not bounded (took {elapsed:.2f}s vs the 2s stall)"
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def test_failed_encoding_short_circuits(monkeypatch: pytest.MonkeyPatch) -> None:
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import tiktoken
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monkeypatch.setattr(tiktoken, "get_encoding", _stalled_get_encoding)
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monkeypatch.setenv("HEADROOM_TIKTOKEN_LOAD_TIMEOUT_SECONDS", "0.2")
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with pytest.raises(tc.TiktokenLoadError):
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tc.load_encoding("stall-enc-2")
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# A second request must fail instantly via the _load_failed short-circuit,
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# not wait out the timeout again (this is what makes it not "every request").
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start = time.perf_counter()
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with pytest.raises(tc.TiktokenLoadError):
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tc.load_encoding("stall-enc-2")
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assert time.perf_counter() - start < 0.1
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def test_fast_load_returns_encoding(monkeypatch: pytest.MonkeyPatch) -> None:
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import tiktoken
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sentinel = object()
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monkeypatch.setattr(tiktoken, "get_encoding", lambda _name: sentinel)
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assert tc.load_encoding("fast-enc") is sentinel
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def test_registry_falls_back_to_estimator_on_stall(monkeypatch: pytest.MonkeyPatch) -> None:
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import tiktoken
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monkeypatch.setattr(tiktoken, "get_encoding", _stalled_get_encoding)
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monkeypatch.setenv("HEADROOM_TIKTOKEN_LOAD_TIMEOUT_SECONDS", "0.2")
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counter = TokenizerRegistry()._create_tiktoken("gpt-4")
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assert isinstance(counter, EstimatingTokenCounter)
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