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>
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>
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>
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>
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
Squashed from work:
- asset-ai: FastH3 4-step fast video backend; clip keyframes on the wire
- asset-ui: loop video chains — text→image→video that ends where it began
- h3: safetensors -> pruned-Q4_K GGUF quantizer for the 24GB DiT tiers
- h3_quant_gguf verify: row-error gates calibrated to the measured Q4_K floor
- asset-ai realtime: the feedback loop — the source anchors, the drifted frame inits
- asset-ai realtime: a feedback loop survives a resize and travels by default
- asset-ai realtime: the feedback loop frees itself from the feed handshake and pauses for its listener
- asset-ai realtime: the outbound encode leaves the loop's critical path
- asset-ai ocr: the ocr domain — Chandra 2 at page resolution, and the tower goes planner-owned
- llm slots: a lane can hold an image span — embedding prefill and a rope cursor of its own
- vision tower on CUDA: the encode leg gets its two missing kernels
- llm/ocr: one M-RoPE grid encoder for both image paths, and a livelock made an error
- vision tower on CUDA: the f16 GEMM keeps the precision it was throwing away
- live: a feed that moves box takes its trip with it — one seed image
- vision tower on CUDA: the tiled attention becomes bit-exact, and tensor cores go
- llm prefill on CUDA: the MMA attention kernel gets the tile a 4-to-1 model needs
- asset-ai ocr: the CUDA encode lane joins the integration — vision-parity sits beside run's three arms, and the kernels
- Merge branch 'ocr-perf-integration' into work
- asset-ai: the live anchor can follow the trip, and text leaves the 5090
- asset-ai: the camera moves the world, and the world starts still
- asset-import: the EA strategy classics, in the one 2D contract
- rtsmap: one seeded generator for tiled strategy maps
- asset-ui: one card for the strategy classics, with a pack dropdown
- asset-ai: music3 reference-audio path, ocr/h3 backends, registry
- asset: mp4 sample index for range-streaming, chat tools, import profiles
- cnc: tiberium is twelve growth frames, not twelve empty variants
- platform: native file and save dialogs, in-house on all three desktops
- chat: the scan holds out for a lane home
- chat: a full home queues you — take the free lane
- chat: the preload has a percentage, and the boundless cap stops showing
- llm cuda: the 32x2 attention tile — even GQA ratios stay on MMA
- sa3 gets a bake path: the sfx model's tables precomputed by a diffusion-side bin
- sqlite_query: anti-join regression test
- td import: HARV's second frame block is its harvesting cycle, not a turret
- asset-ui: sprite enhancement runs on the 32B dev DiT — distillation, not the prompt, was the ceiling
- ai-hub: makepad-asset-ai becomes makepad-ai-hub at libs/ai/hub, the chat pane becomes makepad-chat-ui, the service bin
- asset-ui: test health fixtures grow the realtime field they were born without
- ai-hub: one home at ~/.makepad — weights/ run/ cache/ logs/, the service cache migrates from ai_content by a single re
- ai-hub: subprocess workers die with the node — process groups everywhere, PDEATHSIG on linux, one KILL_ON_JOB_CLOSE Jo
- ai-hub: the hub object — AiHub::in_process, pipes vocabulary, and the local LLM engine generalized out of mpfiles (aic
- strict-json: the dependency-free JSON module gets its own crate; asset-client re-exports it so nothing downstream move
- ai-hub: the machine layer — node entries, the 0600 machine token, and the residency election that IS the lock (aicore
- ai-hub: MPHUB1 — the fabric beacon only dedicated nodes can send (aicore §4)
- ai-hub: job leases — work lives only while it is renewed (aicore §8)
- asset-creator: the pipeline library is born — specs, the deps gate, and the derived-state law (aicore §9)
- ai-hub: RAM residency facts — the CPU-side twin of residency.rs (aicore §3)
- ai-hub: ETA placement primitives — relative GPU throughput, the four-term estimate, and an observable breakdown (aicor
- ai-hub: leases go live on the wire — origin fields on submit, /job/<id>/keepalive, /bye, and the reaper that cancels w
- ai-hub: the chat providers move in — fleet qwen, openai, grok, claude/codex/grok CLIs, the responses driver, and the w
- asset-creator: the engine — one pipeline run against the hub, deps-gated, spliced, cancellable, resumable-by-construct
- ai-hub: the machine node mode — --machine binds loopback, registers in ~/.makepad/run, and exits on its own once idle
- asset-creator: makepad-creator-run — the detached client for runs that must outlive a window (aicore §9)
- ai-hub: a native Claude Messages-API provider — API-key or Claude Code OAuth, bounded SSE streaming, injected tools (a
- route + converse: off makepad_ai — the Agent seam moves to converse, route's cloud dispatcher rides the hub's Claude p
- asset-creator: the preset tables move in — fifteen chain-policy constants shared by every creator app (aicore §9 / P6)
- makepad_ai is deleted — every backend is a hub pipe, the agent seam lives with its consumers (aicore §14, decided 2026
- ai-hub: loads hold the machine residency election — set_model_state claims on Loaded and publishes the service port (a
- ai-hub: chats run the machine election — route to a serving holder, wait on a loading one, claim and publish when open
- ai-hub: pick_for_domain_eta — ETA-ranked placement over the shared hard-filter core (aicore §6 / P4)
- asset-creator: the engine picks a provider per stage at dispatch time — a chain's later stages see fresh fleet state (
- ai-hub: the fabric secret gates the service HTTP surface — bearer on everything but /health and the ticketed peer path
- vj: DREAM runs execute in the app — pipelines.rs becomes the run it used to watch (aicore §9 / F1)
- asset-creator: the runner — generate one thing and put it in the catalog, one implementation for every surface (aicore
- chat-ui: the session runs in the app — no broker anywhere on the chat path (aicore P8 / F5)
- asset-store: assets.query is a first-class query endpoint — the bounded SQL surface outlives the broker (aicore P8 / F
- asset-creator: CreatorTools — the chat tool pack for a store that only stores (aicore §9 / P8)
- asset-store: the shrink — the store stores (aicore P7)
- importer + asset-server host: the coordination era ends (aicore P7)
- store config purge + asset-ui goes fleet-direct; the derive protocol gets its route proof (aicore P7)
- client + chat dispatcher: the dead wire comes out (aicore P7/P8)
- ai-hub: 0.3.0 — the health version says which era a node runs
- ai-hub: the default fleet is 'gen' — apps hear the LAN without env plumbing
- ai-hub: the preload note percents the prefill, not the job bar
- ai-hub: conversations keep their KV — the wire mirror, the lane identity, the in-turn dynamic context (aicore §7)
- ai-hub: an open-think model is thinking from its first token
- libs: the zero-warning sweep — stitch casts say what they mean, xatlas keeps upstream's surface quietly
- zero-warning sweep, round two — the first full-workspace pass
- zero-warning sweep, round three — the model lanes and the deep examples
- zero-warning sweep, round four — the last stragglers
- zero-warning sweep, round five — vj and chat-ui
- zero-warning sweep, round six — three cascades
Co-authored-by: Claude <info@makepad.nl>
2026-09-01 16:46:31 +02:00
Renamed from libs/asset/ai/registry.json (Browse further)
