* fix(coding-agent): resume after context-limited length stops
Treat length stops as context overflow when prompt usage is within 1% of
Pi's configured context window. Include cache-write tokens in that usage
and allow non-zero output because OpenAI may emit reasoning tokens before
returning an incomplete response.
After compaction, remove any retryable error or truncated-length assistant
message restored from persisted session history so the interrupted agent
turn can continue.
This is specifically for handling this case for openai models:
https://developers.openai.com/api/docs/guides/reasoning
> If the generated tokens reach the context window limit or the max_output_tokens value you’ve set, you’ll receive a response with a status of incomplete and incomplete_details with reason set to max_output_tokens. This might occur before any visible output tokens are produced, meaning you could incur costs for input and reasoning tokens without receiving a visible response.
This detection currently assumes the reported prompt usage is within 1% of
the context window configured in Pi. Its reliability therefore depends on
Pi's model contextWindow metadata matching the provider's effective limit.
Maybe we should consider treating OpenAI incomplete responses as requiring compaction
regardless of the local context-window estimate?
fixes#7020
* fix(coding-agent): recover truncated responses after compaction
Classify length stops by comparing provider-reported output usage with the model's intended output limit. Compact and retry once when generation ends below that limit, avoiding unreliable context-window estimates while preserving genuine max-output stops.
Normalize OpenAI Responses incomplete reasons so only max_output_tokens is treated as a length stop. Preserve qualified provider reasons for diagnostics, surface other reasons as errors, and use neutral truncation wording in the TUI.
