@yzong-rh thanks, but I am not a coauthor ;) (no code seems to be directly taken from my abandoned PR + coauthorship potentially could complicate DCO)

Your PR looks good, two minor remarks:

• cognitively I preferred the explicit merging function; now it might be (slightly harder) to recognize that _construct_message_from_response_item() also does merging
• not sure about merging reasoning into a previous assistant message that also has reasoning, and merging content into a previous assistant message that also has content; both imo indicate that there likely is a problem, because (according to schema and how reasoning is handled in practice) chat completion models cannot generate an assistant chat completion message containing multiple reasoning or content fields. Usually, models are quite sensitive whether their own text generations and the rendered prompt is within their expectation/in distribution; ofc there could be benefits of your merging strategy, if you switched mid-session from a model like gpt-oss to a "native" chat completion model, but on the other hand, if a client supports such a model switch, it might handle that conversation/item merging internally (or ask the harmony model first for a concise summary and hand that over to the non-harmony model).

I am not a coauthor ;) (no code seems to be directly taken from my abandoned PR + coauthorship potentially could complicate DCO)

I pulled from you PR to work on top of it. Enough changes may have been made that not much is left of the original code. Happy to amend DCO and give you proper attribution

cognitively I preferred the explicit merging function; now it might be (slightly harder) to recognize that _construct_message_from_response_item() also does merging

I removed the explicit merge function to avoid code duplication in the if / else chain, although you are right that _construct_message_from_response_item() can now unexpectedly do merge. I've update the fn signature and comment to highligh this better.

not sure about merging reasoning into a previous assistant message that also has reasoning, and merging content into a previous assistant message that also has content; both imo indicate that there likely is a problem, because (according to schema and how reasoning is handled in practice) chat completion models cannot generate an assistant chat completion message containing multiple reasoning or content fields.

Agree with you that both would indicate a problem given the current models. Other than switching from a gpt-oss to a native model mid-session you mentioned, another case is that the user turn somehow got lost in the conversation, in which case having two consecutive assistant turns might be preferable over a single assistant turn with concatenated content and reasoning.

I originally aimed to replicate the llama.cpp PR but a less greedy approach might be less surprising here. Plus, the current content concatenation path isn't that robust, and the code will be much simpler. Updated the logic and BFCL as sanity check (no perf regression, as expected)