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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]