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>
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>
One backend call per SAM-style decoder layer (PE norms, token
self-attention, token-to-image cross-attention, erf-GELU feed-forward,
final norm) inside one command buffer, with the layer's f32 weights cached
on the device under their content identity and pooled transients.
gpu_two_way_layer_resident in the common backend; CUDA declines and the
per-op path stays. Body decoder loop on the M3 Max: layers 100 -> 9 ms,
frame 405 -> 266 ms, oracle parity unchanged (kp3d 1.5 mm).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
gpu_linear_f32_resident promised a resident weight but the Metal tensor
backend re-uploaded it every call, which for the MHR rig's 664 MB pose
corrective matrix cost 50 ms a step. Metal tensors now carry a content
identity (fresh at creation and after every in-place write, so a cache
keyed by it can never serve a stale weight), and the resident linear caches
the device buffer under it. Body frame on the M3 Max: 705 -> 405 ms (rig
302 -> 20 ms, refine 41 -> 13 ms, heads 10 -> 6 ms).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
The Metal tensor backend is host-Vec based: every op copied its inputs up
and its result back, which put the DINOv3 backbone at 2.1 s a frame on an
M3 Max. try_vit_backbone_resident_f32 runs a whole pre-norm ViT stack
(LayerNorm, q/k/v, rotate-half rope from tables, flash attention, out,
LayerNorm, SwiGLU, down; residuals in place) inside one command buffer
against cached bf16 weights, with a new kernel_makepad_rope_half_tables_f32
kernel for the rope. The precompiled metallib now carries the bf16 GEMM
kernels the runtime source compile already enabled on bfloat devices.
The common backend exposes it as gpu_vit_backbone_resident (CUDA declines;
its per-op path is already resident) and the body backbone tries it first:
233 ms a frame on the M3 Max, same oracle parity (kp3d 1.5 mm).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
The FP8 backbone mode added each linear's bias by downloading, tiling and
re-uploading it per call, which cost more than the FP8 GEMM saved. A
gpu_add_cols_broadcast op (CUDA kernel; host loop on the Metal tensor
backend) adds a cols-wide bias to every row on the device, and each linear
keeps its bias resident after the first upload.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
dino.rs is the 32-block ViT-H+/16 on the gpu_* surface after the TRELLIS
conditioner: bf16-resident linears with f32 accumulation, layer scale
folded into the output projections, rotate-half rope, SwiGLU, the
model's own final norm. preprocess.rs is the crop (box -> 1.25 pad ->
3:4 -> square -> 512 bilinear warp, ImageNet normalisation), the CLIFF
condition vector and the patch rays; condition.rs is the dense
positional encoding and the ray-conditioned decoder context. Against the
reference oracle on Metal: backbone 1.1% mean relative (bf16 noise),
ray-conditioned context 8e-5, crop within one u8 rounding step, rays and
dense PE 1e-7. One reference detail the paper does not state: its shrink
of the ray field is an antialiased filter whose taps clip at the image
edge, so the two edge patches sample inside their block centre (9.03 and
501.97 rather than 7.5 and 503.5); block centres left 0.1 of error.
The Metal tensor backend was missing rope_half (it aliased the
interleaved layout) and layer_norm_mul_add; both now exist with the
CUDA contract, which is what lets this backbone run on Apple silicon.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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>
Squashed from work; the fine-grained history is under tag archive/work-2026-08-26:
- vj: the tweener learns — RIFE runs on the Mac and feeds the warp
- asset-ai: the chat tells the truth while it works
- llm: a cold turn on the solo slot takes the session-native speculative path — think-mode turns no longer re-ingest the whole conversation through the draft head (66 → 122 tok/s on the four-lane box)
- llm: the step cost model is chosen per device — the RTX PRO 6000's measured verify curve (13.7 + 3.17·B ms) beside the 5090's; the bench warms every tail shape and times two windows
- vj: local store, lyrics and model plumbing, and the frame-interpolator's device parity check
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.
Admin
