LM Studio was ejected, so serving is ours now: tools/serve_local.py serves base+LoRA via
Unsloth (.venv-train cu128) as an OpenAI endpoint — no llama.cpp build (this CPU has no
AVX-512, which SIGILLs the prebuilt llama-cpp-python CUDA wheels). api_draft/lora_grind hit
it unchanged.
PROMPT FIX (api_draft.LEAN_SYS + format_finetune.SYS, kept in sync): 'translate EVERY
instruction, never an empty body' — a prompt test took the small-leaf band 0/3 -> 2/3 MATCH
(the v2 corpus overfit an empty void f(void){} leaf pattern). Validated end-to-end: a fresh
ov_SC01_001 batch banked 3 via the local server + better prompt.
CORPUS-V3 (export_pairs + format_finetune):
- export_pairs now ALSO mines the 1623 DEFINE_func macro bodies in engine_core.h (the shared
setters/return-const/dispatchers extract_defs never saw -> 96.6% of v2 was overlay-unique,
the root of the empty-leaf overfit). Corpus 1312 inline -> 2891 (1312 inline + 1579 macros).
- format_finetune inlines engine_types.h structs in the compile-filter so struct-using bodies
are KEPT not dropped: train 2534/2591 (97.8%) compile standalone (v2 was 1111 total).
Found 50% of bare-def corpus completions fail standalone compile (undeclared globals/structs — externs
lived in TU headers). Filtering to compile-verified pairs so the pilot LoRA learns to emit COMPILABLE
matching C, not uncompilable bodies. (Drops harder struct/global fns; corpus v2 = add externs to recover.)
Drew T