v0.4.0
invoke-ai/InvokeAIv0.4.0Oct 10, 2026by github-actions[bot]
Upgrading?
AI Summary
Selectively ports upstream Laya v0.4.1 runtime features to native MLX inference, introducing new routing behaviors, tournament prediction capabilities, and parallel layout support.
Key Highlights
- `Router()` now sends language-undecided inputs to the multilingual checkpoint by default
- Added `predict_tournament` to narrow large choice sets without an embedding model
- Added `min_confidence` gates to Agent and Router for filtering results
- Support for `option_layout='parallel'` throughout MLX inference, compilation, and caching
- Fixed FP32 intermediate computation to prevent native FP16 kernel crashes on macOS 26
Breaking Changes
- `Router()` default behavior changed: language-undecided inputs now go to the multilingual checkpoint (use `Router(default='english')` to retain previous fallback behavior)
New Features
- `predict_tournament` method for narrowing choice sets
- `min_confidence` gates (scalar and per-option-count)
- Support for `option_layout='parallel'` checkpoints
- Custom checkpoint registration and unregistration APIs
Full Release Notes
Laya-MLX v0.4.0 selectively ports upstream Laya v0.4.1 runtime features to native MLX inference. ## Behavior change `Router()` now sends language-undecided inputs to the multilingual checkpoint. Identified English still uses the English checkpoint. Set `Router(default="english")` to retain the previous fallback behavior. ## Changes - Keep resident-model requests and status reads available during cold checkpoint construction. Deduplicate builds and synchronize targeted unloads per checkpoint. - Register custom checkpoints with `register`, `unregister`, `registered`, or `models=`. Source replacement and unregistration cannot resurrect an outdated in-flight model. - Add `predict_tournament` to narrow large choice sets without an embedding model. Its probabilities and usage describe the final pass; metadata records finalists and elimination rounds. - Add scalar and per-option-count `min_confidence` gates to Agent and Router. Gate results are reported without replacing the original answer or automatically invoking a fallback. - Use FP32 intermediate computation for CPU parallel-option attention to avoid native FP16 kernel crashes on hosted macOS 26; GPU precision and parameter storage precision are unchanged. - Support checkpoints trained with `option_layout="parallel"` throughout MLX inference, compilation, prefix caching, and conversion. Existing checkpoints remain sequential; do not enable parallel layout by editing an old checkpoint's configuration. - Fix language detection for capitalized acronyms, address fragments, emphasis capitals, and mixed scripts; fix French device-footer removal. - Release MLX free-buffer caches on unload and eviction while preserving caller-owned and in-flight model references. - Update English/Chinese documentation, attribution, and CI with separate pinned sequential and parallel-layout upstream references. ## Validation - 231 tests passed on CPU and 231 on GPU before release. - Three published checkpoints in FP32 and FP16: 378/378 argmax agreements with the pinned sequential upstream reference. - 100 deterministic finite calls per configuration, 600 total, with zero measured active-memory growth. - Parallel-layout tests cover all 24 permutations of four options in FP32/FP16, numerical comparison with upstream v0.4.1, compilation, caching, and export/reload. - Ruff, wheel/sdist strict metadata checks, and installed-wheel smoke tests passed. [Raw checkpoint validation](https://github.com/mizorewww/laya-mlx/blob/v0.4.0/benchmarks/results/upstream-v041-validation.json) ยท [API and migration details](https://github.com/mizorewww/laya-mlx/blob/v0.4.0/README.md#upstream-v041-runtime-port) Install or upgrade: ```bash python -m pip install --upgrade laya-mlx==0.4.0 ```
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