plugin.toml

# LFM2.5-Audio (MLX backend) shipped as Python source — Apple Silicon only.
#
# Sibling of `examples/lfm2-audio-python-source-plugin/` (torch+CUDA path).
# Same source-load distribution mechanism; different model backend.
#
# This plugin requires Apple's `mlx-audio` package, which only builds on
# `darwin` + arm64. On Linux / x86_64 / Windows hosts uv will fail to
# resolve `mlx-audio` and this plugin won't load. Use the torch sibling
# instead on those platforms.
#
# Resolver dispatch (same as the torch sibling):
#
#   1. Parse this plugin.toml.
#   2. See `language = "python"`.
#   3. Provision a uv-managed venv from [python].requires.
#      (~2 GB on first run: mlx-audio + transitive deps. Much lighter
#       than the torch path — no CUDA wheels.)
#   4. Spawn `python -m remotemedia.core.multiprocessing.runner`
#      with --module-root <this dir> --register-module lfm2_audio_mlx_source.
#   5. Register LFM2AudioMlxNode into the executor's registry.
#
# Model weights download lazily on first turn (~1.95 GB for the 4-bit
# quantisation at `mlx-community/LFM2.5-Audio-1.5B-4bit`).

[plugin]
name        = "lfm2-audio-mlx-python-source"
version     = "0.1.1"
language    = "python"
description = "LFM2.5-Audio MLX backend for Apple Silicon, distributed as Python source. Drop-in equivalent to the in-tree `LFM2AudioMlxNode`."
license     = "RemoteMedia-Community-License-1.0"

[python]
entry_module = "lfm2_audio_mlx_source"
node_types   = ["LFM2AudioMlxNode"]
module_root  = "."

# MLX-only deps — much lighter than the torch sibling. No CUDA, no
# liquid-audio, no transformers. The mlx-audio package itself drags in
# mlx, mlx-lm, and the mimi/detokenizer assets via its own dep graph.
#
# `mlx-audio` only publishes wheels for darwin-arm64 (M-series Macs).
# On any other platform uv will fail to resolve this requirement and
# the plugin won't load. Consumers on non-Apple-Silicon should use
# `examples/lfm2-audio-python-source-plugin/` instead.
requires = [
    "mlx-audio>=0.1",
    "numpy>=1.24",
]