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Changelog

All notable changes to SKaiNET-transformers are documented here. The version line is kept in lock-step with the underlying SKaiNET engine (sk.ainet.core:*) — a transformers X.Y.Z ships against engine X.Y.Z.

The format roughly follows Keep a Changelog, and this project adheres to Semantic Versioning.

[0.23.4] — 2026-05-08

Transformers-only release; no SKaiNET engine bump in this version. The focus is the BOM and the consumer-facing docs.

Fixed

  • BOM coverage gap. :llm-inference:apertus and :llm-inference:voxtral ship to Maven Central but were missing from skainet-transformers-bom's constraints. Consumers who imported the BOM and pulled either of these artifacts got no version alignment for them.
  • Wrong artifact IDs in the README and tutorials. The "Current release" snippet in README.md and the two tutorial pages (getting-started-java.adoc, llama3-tool-calling.adoc) showed sk.ainet.transformers:llm-core / llm-runtime-kllama / llm-agent — those are project paths, not published artifact IDs. The real coordinates are skainet-transformers-core, skainet-transformers-runtime-kllama, skainet-transformers-agent; anyone copy-pasting hit a "module not found" error. Fixed and switched the snippets to the BOM pattern so future version bumps only need to touch one line.

Changed

  • BOM internals: auto-discovery. The constraint list in llm-bom/build.gradle.kts is no longer hand-maintained. A new convention plugin in buildSrc/ (sk.ainet.transformers.bom-coverage) auto-discovers every sibling subproject that applies com.vanniktech.maven.publish and adds it as an api constraint on the BOM. The only manual input left is the exclusion list (currently just :llm-performance); the BOM is coherent by construction — missing or drifting modules can no longer happen.
  • llm-test-java consumes SKaiNET through the BOM so the BOM is exercised during the build itself; a regression in BOM constraints fails locally instead of leaking into a published artifact.
  • Removed dead group = "sk.ainet.llm" override from the root build. The published group has always been sk.ainet.transformers (sourced from gradle.properties); the override was being overridden in turn by vanniktech at publish time. The in-memory project group now matches the published group, which removes a footgun for anyone trying to resolve internal modules by GAV.

[0.23.3] — 2026-05-06

Version-aligned with SKaiNET 0.23.3.

Added

  • Prefill progress callback. generateUntilStop gains an optional onPrefill: ((Int, Int) -> Unit)? parameter that fires once per prompt token during the autoregressive prefill loop, with (done, total) — done is 1-based, total is prompt.size. Plumbed through both AgentLoop.run and AgentLoop.runWithEncoder as a new default-no-op AgentListener.onPrefillProgress(done, total) method.

    Why this matters: prefill is autoregressive in 0.23.x (the comment on generateUntilStop documents the forwardBatched correctness regression we reverted), so on a CPU-only runtime with a 300-token prompt the first onToken lands tens of seconds to minutes after the agent loop starts — UIs previously had no way to show the loop was alive. The new callback closes that gap (e.g. prefill: 32/282 (11%)).

    Backwards compatible — the new parameter and interface method default to null/no-op, so existing AgentListener implementations and callers compile and behave unchanged.

Tests

  • New tests for the prefill callback in GenerateExtensionsTest:
    • generateUntilStopReportsPrefillProgressForEachPromptToken — one (done, total) pair per prompt token, in order, with done 1-based and total = prompt.size.
    • generateUntilStopWithEmptyPromptDoesNotInvokePrefillCallback — callback never fires for an empty prompt.

[0.23.2] — 2026-05-05

Version-aligned with SKaiNET 0.23.2.

Added

  • Llama 3 tool-calling walkthrough — end-to-end docs for app integrators, covering chat template, JSON tool-call format, and JavaAgentLoop wiring.
  • Llama-3.2-1B-Instruct smoke test with a tool-calling assertion.
  • MongoDB / mdbr-leaf-ir embedding entry in the smoke runner catalogue.
  • kllama-cli: prompts, raw responses, and tools list now logged by ToolCallingDemo.

Changed

  • kllama-cli, kllama-native, and kllama-wasm swapped to the DSL path (OptimizedLLMRuntime + llamaNetwork()); placeholder GPU attention/tensor stubs deleted; native benchmark scenario renamed to native-cpu-throughput.
  • KLlamaJava facade swapped to the DSL path.
  • llm-core: SentencePiece decorator + GGUF tokenizer now route through upstream sk.ainet.io.tokenizer instead of a local fork; fixes Qwen / GPT-2 BPE GGUF tokenization.

Fixed

  • fix(tool-calling): tolerate markdown code fences around Llama 3 JSON tool calls — the parser previously skipped fenced JSON, causing the agent loop to keep generating until maxTokensPerRound instead of executing the call.
  • fix(qwen): NEOX (SPLIT_HALF) RoPE pairing for Qwen3 GGUFs.
  • fix(transformer): thread metadata RMSNorm eps through QK-norm.
  • fix(llama): inject logical 2D shape and dequant token_embd in DSL converter.
  • fix(kllama-cli): route Llama GGUF/SafeTensors back to eager LlamaRuntime`` — the DSL Q4/Q8 path is functionally correct but needs first-class Q4/Q8 DTypes to match the SIMD perf of the legacy path. Tracked as a followup.
  • fix(kllama-cli): apply application plugin so :run task is wired.
  • fix(smoke): tolerate runners that don't emit tok/s (embedding models).

Removed

  • :llm-runtime:kqwen module and LlamaIngestionBlocking.kt deleted.

Docs

  • API dumps refreshed for 0.23.2 (api/ directory).

0.23.1 — 2026-05-04

Version-aligned with SKaiNET 0.23.1.

Added

  • Apertus end-to-end. Real-GGUF loading now works on top of skainet 0.23.x's block-major Q4_K TensorData wiring. Routing fix to go through OptimizedLLMRuntime + apertusNetwork(), plus chat template, tool calling, and integration tests against Apertus-8B-Q4_K_S. See APERTUS_ROLLOUT.md.
  • Gemma 4 chat-model JVM facade (Gemma4ChatModel) for embedded text-only deployments. close() now propagates to the mmap arena. The PLE mmap path consumes upstream loadTensorStorageMapped rather than maintaining a fork.
  • Multi-id EOS / stop-token support in the chat layer — needed for templates that emit several end-of-sequence markers (e.g. ChatML / Apertus).
  • End-to-end smoke test in llm-test/llm-test-java (Llama3LeafSmokeTest) that wires LEAF (mdbr-leaf-mt, via KBertJava) and Llama 3.2-1B (KLlamaJava) in one JVM, gated on env vars / cache fallbacks so CI without the checkpoints cleanly skips.
  • Apertus tool calling as a first-class family alongside Llama 3, Gemma 4, Qwen, and ChatML/Hermes.

Changed

  • gradle/libs.versions.toml skainet pin: 0.22.1 → 0.23.1.
  • VERSION_NAME: 0.21.1 → 0.23.1 (no 0.22.x transformers release was tagged; the version line jumps to keep the engine and consumer artifacts in sync).
  • kllama-cli and skainet-cli shadow-jar builds now apply the ServiceLoader META-INF/services merge fix-up so the priority-100 skainet-backend-native-cpu provider is picked up at runtime.
  • llm-test/llm-test-java maxHeapSize 8g → 16g — the previous cap OOM'd while loading both Llama 3.2-1B + LEAF in a single JVM.

Fixed

  • fix(apertus): force-dequant token_embd under NATIVE_OPTIMIZED — Apertus was producing garbage on quantized embeddings; we now dequant the token embedding tensor regardless of policy, matching upstream behaviour.
  • fix(tokenizer): auto-detect SentencePiece marker in fromTokenizerJson — models that ship a tokenizer.json without the explicit pre_tokenizer.type = SentencePiece marker now decode correctly.
  • fix(gemma4): produce coherent text on real SafeTensors checkpoint — the loader path for full HF-format Gemma 4 checkpoints (not just the GGUF variant) now produces coherent generations end-to-end.
  • fix(apertus): route through OptimizedLLMRuntime + apertusNetwork() — the legacy direct-runtime path was bypassed; Apertus now flows through the optimized DAG runtime like every other family.

Tests / CI

  • test(apertus): real-GGUF loader integration test against Apertus-8B-Q4_K_S.
  • test(apertus): pin weight-loader fixes with regression tests.
  • test(kgemma): fast tokenizer parity guard against HF reference.
  • test(kgemma): tighten tool-call probe budget + add env override.
  • Native-cpu provider now wired into the qwen and llama JVM test runs so the priority-100 FFM kernels are exercised during CI.

Docs

  • docs(apertus): document chat-template format plus the staged-rollout plan at the repo root (APERTUS_ROLLOUT.md).
  • README refreshed: lead with native FFM CPU performance numbers, current release coordinates at 0.23.1, "What's new" section in place of the previous "In develop, not in X yet" callout.

Removed

  • chore(apertus): close out rollout — remove deprecated runtimes. The pre-rollout direct-runtime entry points for Apertus are gone.

0.21.1 — 2026-04-30

Hotfix release: add missing POM_NAME for the apertus, voxtral, and llm-performance modules so Maven Central publishing succeeds.

0.21.0 — 2026-04-29

Version-aligned with SKaiNET 0.21.0.

  • chore(release): bump SKaiNET to 0.21.0, prepare transformers 0.21.0 — mirror the engine version in the transformers line so the coupling is explicit for Maven Central consumers. Engine highlights (delivered via the bump): Panama Vector FP32 matmul kernel auto-discovered via ServiceLoader, ScratchPool SPI, Q4_K SIMD-fused matmul kernel, Q6_K dequant via ByteVector ql + qh extraction, canonical ggml layout for Q4_K + Q5_K, FP32 MemSeg arena leak fix.
  • VERSION_NAME jumps 0.18.0 → 0.21.0 to align tags with the engine; no 0.17.0 / 0.19.x / 0.20.0 transformers releases were ever tagged.

0.18.0 — earlier

Last published transformers release before the engine-aligned version line. See git log v0.16.0..0.18.0 for details.