Remove the retired applications, asset-specific libraries and DJ pack tool
from Makepad, together with their workspace and launcher entries. All 981
removed source paths are accounted for in the private Stage repository.
Keep public AI chat generation through the AI Hub's generic job runner.
Extract shared SHA-256 and UDP binding into core_util so the public hub and
model crates no longer depend on the relocated asset libraries. Preserve
the retained public coverage in the split wasm validation script.
Validation on the exact cleanup tree in an isolated checkout:
- Release checks: core_util, model, aichat, WM and Builder.
- Release builds: aichat, WM and Builder.
- Existing tests: core_util 5, model 30, aichat 7, Builder 2 passed.
- Core/model checks: wasm32, Linux and Windows passed.
- No warnings in the successful checks, builds or tests.
Known baseline: WM library tests do not compile because the unchanged
style-transition assertion compares seven expected weights with eight.
The unrelated working-tree correction is intentionally outside this commit.
A test is a ci.splash beside what it tests; the script decides every input and the model only ever judges one picture against one acceptance text. mod.ci: launch (hidden, --remote, user_seq preserved), key, type_text, click, get, snap, wait_log (a * is a gap inside one line), no_errors, grab, quit; step, sleep, check, run; cargo, check_targets (the cargo makepad check matrix, check only for platforms we are not on, a test fails if the two tables drift), test, build, machine (another box over the makepad tunnel), exclusive; judge, accept, ask. The watcher polls git ls-remote once a minute for work and any extra branches, syncs a checkout the CI owns, runs the root script first and alone, then the rest up to a parallel limit behind one shared model judge. The window is a wall of squares, one per script: green passed, orange warnings, red failures, with a detail panel for the selected one.
Scripts: the root ci.splash (workspace check with core warnings denied, the tests), apps/wm (desktop up, switch to macOS by Cmd+Space / type / Return, launch the terminal and the browser, each waited for by the WM's own first-frame line), and one per main app in the default shape. Proven here: apps/wm/ci.splash green in 280 s, fifteen target checks and seven vision verdicts.
Models come from Hugging Face through the hub: registry entries qwen3.5-4b-vision and qwen3.5-9b-vision with exact revisions, sizes and digests, and hub-install, a command line over LocalModels::start_install. vlm-probe reads PNG.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
libs/sqlite_query reads WITHOUT ROWID tables through the index cursor,
refuses to write them, and the pager releases its process write slot on
drop. libs/tar is an in-repo tar reader with gzip through fast_inflate.
libs/git imports packed objects with bounded checkout writers and its
HTTP file responses carry a trailer. libs/code_language gains a Haskell lexer with literate (Bird) dialect
detection. libs/loader_bundle and libs/search are new;
libs/app_module carries the super-app module surface; libs/workspace
adds Settings.infinite_zoom and RendererChoice::gpu_env_value; libs/ai
builds without warnings across the hub, llm, metal and model crates;
windows-rs job object handles are c_void.
Squashed from work (the libs parts of each):
- Restore retained renderer support for Scope (libs/search)
- Share Builder target across Makepad app builds (libs/loader_bundle)
- Index local Apple Mail with Gmail labels, attachments and reimport (libs/sqlite_query)
- libs/ai: warning cleanup across the hub, llm, metal and model crates
- code_language: a Haskell lexer with literate (Bird) dialect detection
- git: packed imports and bounded checkout writers; HTTP file responses carry a trailer
- builder: dedicated-folder installer checks, catalog and runtime fixes; Windows job objects hold c_void handles (libs/windows)
- workspace: Settings.infinite_zoom, the experimental prepared map inside the glyph
- wm: the Android super-app hosts apps as on-demand dylibs (libs/app_module)
- libs/tar: an in-repo tar reader; the super-app unpacks its archives with it
- workspace: RendererChoice::gpu_env_value follows the platform's runtime GPU choice
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Squash of 54 work commits (Sep 1–12):
6251f7c ai-hub: body domain — live pose packets ride the realtime session
ea50c77 chat_ui: the feed's session gets its profile brief back
f51b5f3 ai-body: the crate for the native SAM 3D Body port, with its weights reader
8211ae6 ai-body: the MHR rig and the pose head's parameter decoding, oracle-exact
9e343a8 ai-body: the DINOv3 ViT-H+/16 backbone, crop and ray conditioning; Metal gains rope-half and affine layer norm
69d842c ai-body: the promptable pose decoder and its refinement loop, oracle-matched on Metal
66e5e2f ai-hub: SAM 3D Body runs natively — `sam3dbody` on the body domain, oracle-matched end to end
a634198 ai-hub: the body-native commit carried a peer's in-flight hub hunks; put them back where they were
9ff44e8 ai-hub: the body-native wiring, this time only the lane's hunks
6a1c16b ai-body: third-party notices — what the port is implemented after, and what it is not
d78411a ai-body: the per-step work moves to the GPU
b22259b ai-body: the context stays on the GPU; only the pose token leaves the loop
346f31f ai-body: flash attention for the head-dim-64 blocks
45b5b98 ai-body: the crop size is a runtime knob, and the loop reports where its time goes
4be6d19 ai-body: the test modules import the grid constants they still use
7598346 ai-body: tensor-core GEMMs for the backbone, and the rig's correctives only where they count
a9ce596 ai-body: the crop warp runs across cores
8964ba6 ai-body: an FP8 backbone mode, off by default, measured against the oracle
a2aaa8f ai-body: the FP8 bias rides a column-broadcast add on the device
d53c77d metal: a device-resident ViT stack, and the body backbone rides it
d006d0a metal: resident f32 linears keep their weight on the device
525ba1c metal: a device-resident two-way decoder layer, and the body decoder rides it
c9e6d88 ai-body: the hands pass — hand crops, the hand decoder, the hand-mode rig and the wrist fusion
62dff26 ai-body: the mask prompt — a person's segmentation mask conditions the body pass
a648cf8 ai-hub: body session options — hands, detect, persons=N
8c568df ai-hub: drop the SAM 3D Body reference worker backend
7ff875a ai-hub: keep a peer's in-flight beats/notes/local work out of the body commits
31e5faa ai-hub: local model runner, licence acknowledgements, a shared install panel; Beat This!, Basic Pitch and the Salamander drum-kit entries
b94bc58 ai-services: the wire, the app port and the panel state — one conversation, many apps
2acb798 ai-services: wire v2 — endpoints, receiver-side caps, result disposition
8ae0ffb ai-services: the engine core — registry, router and conversation, tested against a scripted model
2308736 ai-services: the real models behind the engine feature — local through the hub, Claude, and none
c3f631d livepipe: one reusable pipe from a camera to a fleet node and back
ff62db3 ai libs: the runtime env-var cleanup — precision is a per-caller policy, not an environment side channel
04a94ef realtime: one service-log line when a live session opens and one when it closes
0ecb81c ai models: the model-crates env-var cleanup — 172 research knobs gone, the unset default is the code
4ca36c1 ai hub + services: the assistant's model comes from wherever it is resident — the fleet chat box, with tools, then the local weights
432121e aichat engine + wm: launch, then use — the assistant continues in the same turn once the app it started is on the bus
7a5bf69 ai-hub registry: the Salamander drumkit samples come from the makepad.nl mirror — the GitHub repo only carries the .sfz files
102ffc5 ai-services: messages on the bus — a manifest declares topics, the engine subscribes on a tool's behalf or by ToolResult.subscribe, a service publishes Message frames, an idle conversation wakes on a message as an event turn under rate laws; the WM bus forwards the new frames; every app that matches the wire gets its arm
a837792 hub + flow: a whitespace-only chat completion is retried once and then fails instead of passing as an answer; a flow's model is a fleet model id unless it names a weight file on disk; chat models show under the text domain in /v1/models
bc6c620 hub + flow: what the chat review found — the in-process route retries an empty completion too, a node says whether its prefill opened thinking so a brief-mode answer is never discarded, a preferred model falls back to normal election when no node has it, discovery keeps looking for the preferred model until patience runs out
75c3441 hub: the PRO 6000 serves image as well as chat and text
ad5e98b hub registry: flux2-dev's VRAM estimate is its measured peak, 30 GB
c7241e0 hub: a node that evicted every resident releases its cached allocator pool before refusing a load or publishing usable VRAM
30575f0 flow: route generation by request workload
1be1e21 ai-hub: gate downloads by disk capacity and recover fleet admission
df6b394 filesystem_watcher, bounded_http, ai services: live and tool prerequisites
79ebdb9 ai-hub: add a native Pixal3D image-to-3D backend
0ba0d74 ai-hub: propagate typed refusals under reject queue policy
cc6c872 Speed up H3 conditioning and video decoding
e512059 Fix Qwen vision residency and generated material colors
2864f68 ai-hub http client: bound every plain TCP connect to 3 s per address
3d93229 ai: CUDA is a Linux/Windows-only dependency; the hub library defaults to llm + stt
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Account for missing and partial model files per volume, reserve headroom, and reject disk-constrained workers before accepting a job. Preserve typed admission failures so callers can choose another peer, and make activity gating and cancellation recover cleanly.
Validation: 592 release hub tests passed, one ignored; required-CUDA builds deployed to six idle Windows workers.
Clocked piano/ironfish/drum rack, program-bus mix, splat/mixer/music
updates. Silence the unused warnings that show up in `cargo check -p
makepad-vj --release`.
The 5090 kept about 1.5 GB of CUDA allocator pool after evicting every
model, so a card that fits flux2-dev refused it (30510 MB free reported,
32090 MB in a fresh process). Admission now trims the pool when the last
resident is gone and re-measures before refusing; usable VRAM is measured
after the same trim; the refusal names the pool it released.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Measured on the RTX 5090 (2026-09-04, 1024x1024, 8 steps, nvidia-smi 250 ms
samples): 30.5 GB used at peak, the run completed in 52 s. The old 29 GB
was a pre-measurement guess that under-reported the model by 1.5 GB.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
flux2-dev cannot fit on the 5090 at the default reserve, and the role
table barred the only card that can hold it. The user opened image on
10.0.0.165 ("let the rtx serve images too"); the role test and the
flow's role-aware listing test follow.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
The 5090 listed flux2-dev ready (total VRAM passed the gate) then refused
every job (29696 + 2048 reserve > ~30510 usable); the flow picked it by
domain ETA and never retried. Nodes now publish vram_usable_mb and mark
un-admittable models too_small; the fleet gate uses usable VRAM; the
flow's gen executor picks admitted nodes for the requested model (ready
first), retries up to three nodes after an admission refusal, and when no
node can take the model its error says why per node (role, too small with
the numbers, waiting for VRAM). The flow's model listing drops (model,
node) pairs the node's fleet role bars, so the picker no longer counts the
chat-only PRO 6000 as ready for image; its label reads ready/absent/too
small with the GPUs named.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
The hub chat session's election no longer stops at this machine: a
co-located serving holder first, then a fleet chat node heard by
discovery and role-allowed for chat (a short patience for beacons),
then the weights on this machine — and an honest answer naming both
misses and where weights may be put when none of those exists. Tool
packs ride every route: the system text carries the tool table as the
node's chat_system, one splitter strips thinking and collects
<tool_call> bodies across deltas, the in-process worker's parser is the
one parser, and tool results go back as tool turns. A node that fails
mid-turn ends that turn with the node named; the person's next line
re-elects, served first on the new route. The tools-only guard on the
proxy is gone. The session exposes its route, and the panel's chip
shows it.
The local lookup is independent of the working directory: the env
override, then the makepad home's weights (Qwen preferred, largest),
then the checkout the binary came from, then the cwd — so an assistant
launched from a binary copy finds the same weights as one run from the
checkout, and the Local provider always builds even with none.
Proven live with no local weights: from the sheets overlay a plain
line reached the fleet's 27B (the node with the model resident won the
pick), the model called sheets.summary and answered in 12 s; the app
stayed at 254 MB. hub_chat + local_llm 11, services 34.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
A headless box's service log showed only the startup banner for a whole
session; now it records the model and wire encodings on open, and on close the
elapsed time, frames in/out, fps, and the dropped/undecodable/unencoded counts.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
The AI runtime crates read their precision, activation and kernel
choices from environment variables; the code path taken with none set
is the one that ships, so every knob that selected it is now an explicit
argument and every losing path is gone. GemmPrecision { f16_accumulate,
f16_activations } is passed by each caller: the default {true, true} is
the old unset Flux route; H3's DiT and text encoder pass {false, false}
(H3's >1e4 activations saturate f16 — the policy H3 used to set through
FLUX_GEMM_F16ACC=0 on itself), its VAE {true, false}; DA3's StrictF32
selects f32 packed attention in code; Hy-Motion carries an explicit
f16_attention_operands flag through its text refiner, its double and
single blocks and the CUDA backend (true in production, false only in
its full validator). The libs/diffusion bins — a separate workspace —
are migrated to the same shapes.
Benches and validators no longer set variables on themselves: llama's
skip-logits is a session option (the CUDA bench turns it on), OCR takes
explicit use_f16_gemm and tiled_roformer options, the lane speculative
probe reads its CLI. The live gates the first cut had deleted are back
as explicit-config tests: MMQ M=129, the strided-f32 MMV path, the
RMS+MUL CPU oracle. The loader's THREADS and CHUNK_MB stay real settings.
The Metal quantized-matmul experiment (metal_qmm and its vendored MLX
kernels) was reachable only through a knob and goes with it.
Reviewed in three rounds by the delegate reviewer (the last round
accepted everything but one Hy-Motion call site, fixed in round four
and reviewed here), and gated on the Windows CUDA box: lib checks of
common/paint/loader/cuda/llm/motion/vision, motion 24 and vision 23
tests, the hub check, the diffusion bins, llm 253 passed / 1 ignored.
On this Mac: the same checks plus the motion and vision tests.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
The live decoder never produced a frame on the body node: MF_E_TRANSFORM_STREAM_CHANGE
was hand-derived as 0xC00D6D60, which is MF_E_TRANSFORM_TYPE_NOT_SET; the real stream
change (0xC00D6D61) was treated as a hard error, the output type was only negotiated
lazily, and without MF_LOW_LATENCY the decoder holds a reorder window a 2-3 frame live
pipeline never fills. Set MF_LOW_LATENCY on the transform, commit NV12 before the first
ProcessOutput, re-negotiate on TYPE_NOT_SET/STREAM_CHANGE/BUFFERTOOSMALL, drain on
NOTACCEPTING, and stamp packets with monotonic 100 ns timestamps. MAKEPAD_H264_DEBUG=<file>
traces packets, HRESULTs, negotiations and frames for headless services.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Packages are makepad-<name> with the short name as the binary. Env vars
follow (MAKEPAD_WM_*, MAKEPAD_FILES_*, MAKEPAD_TERMINAL_*), config moves
under ~/.makepad/<app>/, the theme namespaces are mod.wm_theme and
mod.browser_theme, the hosted AI envelope key is wm_ai. platform/video
becomes makepad-platform-video so the video app can be makepad-video.
Carries the Score entries that were pending in the WM's curated table.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
LocalModels runs registry models in-process (install state, resumable downloads, recorded licence acknowledgements at $MAKEPAD_HOME/license_acks.json, weight paths by file role) and libs/ai/hub_ui is the install panel + licence modal every app can embed. New native ports: Beat This! (beats + downbeats) and Basic Pitch (note transcription) with their registry entries; the Salamander Drumkit samples (CC BY-SA 3.0, 37 files pinned by size and sha256) as a sample bank the downloader fetches like a model.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
The last two hub commits staged whole files and carried uncommitted hunks
of another lane (beats-native, notes-native, the local runner, new
domains and license keys) that reference files not yet in the tree. This
restores those files to the body changes only; the other lane's edits
stay in its working tree.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
The native port covers everything the Python reference worker did (body,
hands, mask prompt, multi-person), so the subprocess backend, its fake
worker harness, the sam3dbody-ref registry entry and the
MAKEPAD_SAM3DBODY_* environment go. The packet validator moves to the
native backend.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
The sam3dbody backend reads its options from the request's prompt string
(`hands`, `detect`, `persons=N`): `hands` runs the full mode and the
packet carries which hands were fused and their boxes; `detect` finds up
to N persons with SAM 3.1 (an optional native-segment role on the body
entry, the same artifact the segment entry pins) and runs one body pass
per person with its box and mask, so the packet's people array grows.
The body crate shares one body pass between the packet, mask and hands
entry points, and infer_full takes the mask prompt too.
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 recut in a6341981d applied its patch against the wrong directory
and restored the six shared files to the previous tree without the
body-native hunks. This commit adds exactly those: the `body-native`
feature and optional dependency, the pinned `sam3dbody` registry entry
and its test, the backend arms and the module declaration. Working
tree untouched.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
66e5e2f11 committed the working tree of the shared hub files and with it
another lane's uncommitted edits (a new domain, request fields, a
backend arm, manifest lines). This commit restores those files to the
previous tree plus only the body-native hunks. The working tree is
untouched: the peer's edits stay on disk as their uncommitted work,
exactly as before.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
model.rs closes the loop: crop -> backbone -> ray-conditioned context ->
six decoder steps, each through the pose head, the rig, the camera and
the projection, then the packet the sandbox already reads (kp3d/kp2d in
camera axes, the 204 rig parameters, global rotation, camera translation,
joint positions). Against the reference on the oracle image, on Metal:
3D keypoints within 1.7 mm, 2D within 0.4 px, rig parameters, camera
and rotation within 2e-3. packet.rs writes the JSON by hand with the
reference worker's rounding and field order.
The hub gains the `body-native` feature (default on): registry entry
`sam3dbody` pinned to the Comfy-Org repack by revision, size and sha,
body_native_backend.rs beside the subprocess reference backend with the
same live_step contract, the `body` capability advertised when the
feature is compiled, and a stubbed test double for the CPU-only tests.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
A realtime feed session parked in its wait-for-a-frame loop forever when
the client died without sending stop (a sandbox quit left job-2 live on
.123 for five minutes holding the GPU slot). The wait loop now returns
to the top of the session loop once no socket is left, where the idle
timeout counts a socketless session down. Test covers it.
SkinnedModel gains node_parent/node_count, joint_skinned_centroid (the
direction a leaf limb actually runs, from the flesh it skins) and
from_nodes (a mesh-less rig for hierarchy-maths tests) — what the
sandbox's webcam mocap retarget needs.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01B626urtY1Xo4hQdLzvSK6F
New `body` backend (sam3dbody-ref): a persistent length-prefixed-PNG /
JSON-lines worker subprocess seam with ready handshake, per-frame timeout,
bounded restarts. LiveFrameOut grows aux_json — structured per-frame JSON
sent to the client before the frame — and output_encoding "none" makes a
session pose-only (refused with loop_mode feedback, also on control flips,
which upgraded apply_control to Result). Worker code+model stay
box-provisioned via MAKEPAD_SAM3DBODY_WORKER; the repo carries only the
MIT seam. Codex lane + Fable review (ready handshake, spawn timeout).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0165w1ZL1f1TruX5u2qC7mSX
