Add POST /v1/systemone, /v1/systemone/permute, and
/v1/systemone/separate to LocalAI, mirroring the kev project's
structured-extraction API. Each endpoint runs zero-shot NER over the
rendered state text and builds kev-compatible answers for three question
types: noul (binary entity presence), choice (pick one option), and
score (pick one level).
The TokenClassifyRequest proto gains a `repeated string labels` field so
each question can supply its own labels at inference time, and
TokenClassifier gains TokenClassifyWithLabels for per-call label
selection. The vllm-cpp backend uses request labels when non-empty,
falling back to configured ner_labels then the built-in defaults.
Helpers (renderState, softmax, choiceConfidence, scoreConfidence, r2)
are ported from kev/api.py and mirrored in vllm.cpp's api_server.cpp so
both servers produce the same answer shape.
Following-Agents-Protocol: true
AI-Assisted: true
Assisted-by: AGENT:regolo/glm5.2 [maki]