The MINIMUM_CONTEXT_LENGTH floor in _compute_threshold_tokens only
degraded to the 85% trigger when it met or exceeded the effective
window exactly (#14690). Near-minimum windows slipped through: at
context_length=65536 the threshold passed through at 64,000 — 97.7%
of the window, ~1.5K tokens of output room — so pre-API compaction
effectively could not fire.
Providers that silently truncate over-window prompts instead of
rejecting them (e.g. ollama's OpenAI-compatible /v1 endpoint) never
deliver the reactive context-overflow backstop either. Observed live
on a 65,536-token local model: the session rode into the window
ceiling and each length-continuation retry re-sent a window-filling
prompt (65,120 -> 65,273 prompt tokens, 263 output tokens of room)
until the turn died with "Response remained truncated after 4
continuation attempts" — every retry paying a full multi-minute
prefill.
Cap the floored threshold at _MIN_CTX_TRIGGER_RATIO (85%) of the
effective input budget whenever the floor is the binding term. An
explicit threshold_percent above 85% is user intent and stays
uncapped; windows where the floor lands at/below the cap are
unchanged.
4252aecc2e