feat(serve): support ignore_eos on Chat Completions - #197
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ninfer-serve accepts the ignore_eos field and ignores it, so a request generates the checkpoint's own number of tokens rather than max_tokens. With max_tokens 512 and ignore_eos true, a chat completion that stops naturally after 267 tokens should run to 512, which is what SGLang returns for the same request; ninfer returned 267 with finish_reason "stop". Any cross-engine throughput comparison then measures decode rates over windows of different lengths. StopPolicy already carries include_model_defaults (include/ninfer/types.h:234), and merge_stop_policy (src/targets/qwen3_6/impl/frontend/frontend.cpp:389) appends the tokenizer's default stop tokens only when it is set. The serve layer had no way to clear it. Add a bool ignore_eos to GenerationRequest, parse it with the existing get_bool helper in parse_stop, and map it in to_request_options as options.stop.include_model_defaults = !request.ignore_eos. Caller-supplied stop strings and stop token ids are unaffected: only the checkpoint's own defaults are suppressed, which is the documented meaning of the field in vLLM, SGLang and llama.cpp. The default is false, so a request that does not send the field behaves exactly as before, and only the OpenAI Chat Completions path is touched (/v1/messages and /v1/responses are not). Verified against the same server and prompt: ignore_eos=true gives completion_tokens=512 and finish_reason length; ignore_eos=false gives 267 and stop, unchanged.
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ninfer-serve accepts the ignore_eos field and ignores it, so a request generates the checkpoint's own number of tokens rather than max_tokens. With max_tokens 512 and ignore_eos true, a chat completion that stops naturally after 267 tokens should run to 512, which is what SGLang returns for the same request; ninfer returned 267 with finish_reason "stop". Any cross-engine throughput comparison then measures decode rates over windows of different lengths.
StopPolicy already carries include_model_defaults (include/ninfer/types.h:234), and merge_stop_policy (src/targets/qwen3_6/impl/frontend/frontend.cpp:389) appends the tokenizer's default stop tokens only when it is set. The serve layer had no way to clear it.
Add a bool ignore_eos to GenerationRequest, parse it with the existing get_bool helper in parse_stop, and map it in to_request_options as options.stop.include_model_defaults = !request.ignore_eos. Caller-supplied stop strings and stop token ids are unaffected: only the checkpoint's own defaults are suppressed, which is the documented meaning of the field in vLLM, SGLang and llama.cpp.
The default is false, so a request that does not send the field behaves exactly as before, and only the OpenAI Chat Completions path is touched (/v1/messages and /v1/responses are not).
Verified on the box against the same server and prompt: ignore_eos=true gives completion_tokens=512 and finish_reason length; ignore_eos=false gives 267 and stop, unchanged.