Release 1.4.0 (06-sep-2026)

[1.4.0] — 2026-09-06

Public release of nano-vllm-java 1.4.0 (Maven coordinates com.igormaznitsa:nano-vllm-java:1.4.0).
Meta fastText text classification, optional TornadoVM GEMV acceleration, and typed generate results
(LlmModality.resultType / cast — no caller cast).

Added

• Meta fastText supervised text classification (*.bin / *.ftz), including the official
  language-identification models
  (lid.176.bin preferred / lid.176.ftz, 176 languages). Load a file or folder with
  LlmModelFactory.make, then LLM.generate(LlmInText, LABELS) → ranked LlmOutLabels
  (__label__xx codes with probabilities). Pure Java (no JNI); hierarchical softmax,
  softmax, and one-vs-all. Download: models/download-fasttext-lid-176.sh (or .ps1 / .cmd)
  fetches the denser lid.176.bin (~126 MB). Sample: LanguageIdHelloWorld.
• Optional TornadoVM acceleration compiled into the main library (tornado-api /
  tornado-runtime optional Maven deps at 6.0.0-jdk22plus, not transitive). When TornadoVM is
  on the module path and reports at least one device, -Dnanollvm.kernels=auto (default) prefers
  TornadoVM for large dense GEMV; elementwise kernels stay on the Vector/scalar CPU backend.
  Explicit modes: tornado / gpu, vector / simd, scalar / plain. Tornado GEMV prefers
  the Kernel API (KernelContext + WorkerGrid1D, one thread per output row) per TornadoVM’s
  SGEMV guidance, with Loop Parallel (@Parallel over 0..outCount)
  as fallback; reuses compiled plans (LRU), keeps weights on-device for matching buffers/shape,
  and runs as one full-range launch (no CPU tile sharding against the device execute lock).
  Hybrid cuBLAS needs a CUDA Tornado SDK (not the OpenCL-only path). Samples: Maven profile
  -Ptornado launches via the tornado CLI with -Dnanollvm.kernels=tornado.

Changed

• LlmModality carries the concrete generate result class (TEXT→LlmOutText,
  AUDIO→LlmOutSoundData, EMBEDDING→LlmOutEmbedding, LABELS→LlmOutLabels).
  LLM.generate / LlmModel.generate return that type via LlmModality.cast, so callers no
  longer need an explicit cast.