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https://github.com/usestrix/strix.git
synced 2026-08-21 10:48:59 +02:00
Ahmed Allam
4eedfc64b4
- Clamp the summary request's max_tokens to the model's output limit so a large STRIX_CONTEXT_SUMMARY_TOKENS can't get the request rejected (which left the overflowing session uncompacted). Applied consistently to the input-budget reservation and the request itself. - Replace the tokenizer-unavailable fallback with the UTF-8 byte length, a guaranteed upper bound on tokens for byte-level BPE, so budget checks can never under-count dense history.
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
"""Tests for model-aware token budgets."""
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from __future__ import annotations
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from typing import TYPE_CHECKING
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from strix.config import load_settings
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from strix.llm import context_budget
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if TYPE_CHECKING:
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import pytest
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def test_context_window_known_model() -> None:
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# gpt-4o is mapped by LiteLLM at 128k input tokens.
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assert context_budget.context_window("gpt-4o") == 128_000
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def test_context_window_strips_provider_prefix() -> None:
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assert context_budget.context_window("openai/gpt-4o") == 128_000
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def test_context_window_unmapped_uses_fallback(monkeypatch: pytest.MonkeyPatch) -> None:
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context_budget._model_info.cache_clear()
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def _raise(_model: str) -> dict[str, int]:
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raise ValueError("This model isn't mapped yet.")
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monkeypatch.setattr("strix.llm.context_budget.litellm.get_model_info", _raise)
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expected = load_settings().context.fallback_context_tokens
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assert context_budget.context_window("totally-made-up-model") == expected
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context_budget._model_info.cache_clear()
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def test_count_tokens_fallback_on_error(monkeypatch: pytest.MonkeyPatch) -> None:
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def _raise(**_kwargs: object) -> int:
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raise RuntimeError("no tokenizer")
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monkeypatch.setattr("strix.llm.context_budget.litellm.token_counter", _raise)
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# UTF-8 byte length is a guaranteed upper bound on tokens, so budgets never
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# under-count when no tokenizer is available.
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assert context_budget.count_tokens("weird-model", "x" * 400) == 400
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# Multibyte text: bytes (not chars) bound the token count.
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assert context_budget.count_tokens("weird-model", "😀" * 10) == 40
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def test_count_tokens_empty_is_zero() -> None:
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assert context_budget.count_tokens("gpt-4o", "") == 0
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