LM Studio / llama.cpp-style servers report the context window in tokens
but the prompt size in characters, e.g. "maximum context length is 65536
tokens. However, you requested 65536 output tokens and your prompt
contains 77409 characters". When a provider profile's default_max_tokens
equals the model's context window, the very first request asks for the
whole window as output and the server returns a hard HTTP 400 — even on a
trivial "hi".
parse_available_output_tokens_from_error did not recognise this phrasing,
so the overflow was misrouted to the prompt-too-long/compression path
(which can't help when the input already fits) instead of the output-cap
reduction + retry path. Detect the "requested N output tokens" form,
estimate the input from the character count (~3 chars/token, conservative
so the retried cap stays inside the window), and return the available
output budget so the existing retry logic shrinks max_tokens and succeeds.
xxxigm
3a74b75217