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v3.19.0 Feature

This release adds 2 notable features for engineering teams evaluating rollout.

✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

agentic-ai agentic-framework agentic-workflow agents ai-agents ai-assistant
+14 more
ai-coding ai-skills autonomous-agents claude-code codex harness mcp-server multi-agent multi-agent-systems npm skills swarm swarm-intelligence typescript

Summary

AI summary

Updates The complete #2549 arc, New, and default across a mixed release.

Full changelog

The final piece of the #2549 saga (reported by @pacphi): neural train now trains through @ruvector/ruvllm's native TrainingPipeline, not only the WASM path.

New

  • neural train --backend auto|native|wasmauto (default) routes the LoRA training leg through the native pipeline when @ruvector/ruvllm resolves: real epochs, loss history, early stopping, EWC registration
  • Checkpoints carry trained weights — the previous best-effort block saved a freshly-constructed adapter's untrained weights; the native path checkpoints the pipeline that actually trained (ruvllm-checkpoint v1 envelope on disk)
  • --backend native fails loudly when the pipeline can't run; --backend wasm preserves prior behavior exactly; SONA/ReasoningBank persistence unchanged in all modes; graceful WASM fallback when the module is absent

The complete #2549 arc

  1. 3.18.1neural status no longer misreports the native path (dead variable + cross-process global)
  2. @ruvector/ruvllm 2.5.7saveCheckpoint(path) actually persists (upstream, RuVector#637)
  3. 3.18.2 — version floors + mkdir fix + version-gated capability reporting
  4. 3.19.0 — training itself routes through the native pipeline (this release)

E2E: auto → native backend, finalLoss 4.25e-3, trained checkpoint on disk. Tests 6/6.

PR: #2556

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Beta — feedback welcome: [email protected]