The per-family model crates (flux, h3, paint, music, speech, stems,
vision, sfx, rife, trellis, beats, common) and the libs/diffusion
research binaries read some 190 environment variables that were
research knobs: tensor dumps, per-stage timing, oracle-parity and
fixture rigs, experiment toggles. The path taken with none of them set
is the one that ships; every such knob is deleted with the code it
gated, and every losing branch of an experiment toggle goes with its
toggle — dead kernels, fields and functions included. What remains are
the real configuration variables (the FLUX_*_MODE family, FLUX_GRAPH,
the VAE pool cap, the FLUX2 text-encoder residency, H3_VAE_BATCH, the
music3 caches and official modes, the stems/beats f16 switches, the
weight and data roots) and the build-script variables.
Rebased on the runtime cleanup: precision stays explicit everywhere
(GemmPrecision, f16_attention_operands, the H3 text precision, DA3's
StrictF32 in code); no act16, no H3_ACT_F16, no FLUX_ATTN_F16 or
FLUX_VAE_CONV_GEMM reads survive.
Reviewed by the delegate reviewer (APPLY, no findings) and gated on the
Windows CUDA box: all seventeen model crates check, motion and vision
tests, the hub and the diffusion bins — the gate caught one CUDA-only
tap marker the Mac never compiles, removed here. On this Mac: the same
checks plus motion 24, paint 158 and vision 23 tests.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Apps ask the hub for a recognizer or a voice and get one; where it runs is
the hub's decision. AiHub::start_stt / start_tts return poll-driven
sessions shaped like the chat session. The Auto ladder is Whisper/Kokoro in
this process (weights present, machine election), on the machine node over
loopback, on a LAN node, else the OS engine; SpeechReach::Local is the
"don't reach out" knob. Audio always comes back as PCM: the app owns the
device.
Three layers:
- makepad-ai-speech is the whole speech model family, engines only.
libs/voice (Whisper + Silero VAD) folds in as the `whisper` and `vad`
modules next to kokoro and indextts, each a cargo feature; the Apple
bridges and the Speaker/VoiceTranscriber selection leave it.
- makepad-system-speech (new) is the OS speech services as blocking fns:
Apple SpeechAnalyzer/AVSpeechSynthesizer via Swift, Windows.Media.Speech*
on the vendored bindings, Android SpeechRecognizer/TextToSpeech through
MakepadSpeech.java (API 26 floor), espeak-ng on Linux. It models the two
STT shapes honestly: PCM in (Whisper, Apple) versus an engine that owns
the microphone (Android, Windows), with capabilities the caller reads.
- the hub grows speech sessions, in-process Whisper/Kokoro workers with the
residency election, a `whisper` wire backend (stt domain, registry entry
pinned to ggerganov/whisper.cpp) so a Mac can serve a Quest, and a
`language` field on the generate request.
Consumers: the Window voice input runs on an STT session and switches to
engine-mic mode when the recognizer owns the microphone; converse's
SpeechOutput is a lazily started TTS session plus a pump thread; route
drops its private speech copy for converse; vj's lyrics fallback and the
alignment bakes call the engines directly.
Verified here: speech-roundtrip through the real sessions (Apple voice in,
in-process Whisper on Metal out, 4.3% WER); system-speech-test TTS->STT
verbatim; hub/converse/system-speech unit tests; msvc, aarch64-android and
linux-gnu cross-checks; Java against android-34. Windows, Android and Linux
bridges are compile-checked only.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
The model code was spread across eight crates that had grown into each other:
ggml and cuda and mlx each owned part of a tensor runtime, llama and tts and
voice2 each owned part of a model, and libs/diffusion owned everything else.
They are now one tree with an explicit shape:
libs/ai/cuda — kernels and launch surface
libs/ai/metal — Metal shaders and the shim
libs/ai/llm — the language-model runtime (sessions, lanes, contexts,
the CUDA and Metal executors, the compiled Metal path)
libs/ai/models/ — common, flux, h3, music, paint, speech, stems, vision
libs/diffusion is not deleted but demoted: what remains is the VALIDATOR
crate — several dozen `*_validate.rs` oracles that check a native
implementation against a reference, which is where they belong now that the
implementations live next door.
The functional work inside the move is mostly in the LLM runtime: N lanes that
draft while one verify batch serves all of them, per-slot prefill over a shared
folded attention arena, speculation that survives batching, and a scheduler
that reports rather than publishes. And in the CUDA build: a machine without
usable CUDA must still LINK (and say so), the default kernel arch is the
building machine's GPU, `NO_CUDA` forces the stub even where the toolkit
exists, and kernels compile in parallel with progress.
libs/video_flow is new here: classical optical flow estimation and the `mkfl`
motion-field payload — a flow field measured from a clip without a model,
which is what drives free-rate bounce-looping playback and the uprez/tween
enhance pipe.
