* add models for /update endpoint
* add logic for identifying out of date hf models
* add endpoint for updating hf models
* add relevant field to GgufVariantDetail
* make exception handling better
* add update_available flag for cached_models, and moved /update endpoint from inference -> models
* hook up /update endpoint on the frontend
* implement update scenarios for the model picker
* fix bug where downloaded flag for an older revision was being wrongly set to false
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix import and make hf calls async
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* remove has_vision from UpdateRequest
* fix ci
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* clear cancel event before updating gguf variant
* set _cancel_event back if it was set initially
* add hf_token to get_paths_info
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: harden model update endpoint and update checks
- update_hf_model: pass snapshot_download local_dir (local_path is not a
valid kwarg and 500s when updating bicodec audio models)
- get_gguf_variants: wrap the remote update check so a network, rate-limit,
gated, or offline failure degrades to "no update info" instead of failing
the whole variant listing, matching list_cached_models
- add regression tests for both paths
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: HF model update detection and Update action for cached models
Surface an "Update available" cue and a managed Update action for cached
on-device models. /api/hub/update-status compares each cached main GGUF
file's local blobs against the remote main revision using set membership
across all cached revisions, so a repo that was already updated (and still
holds the old snapshot alongside the new one) is not falsely flagged.
The Update action re-downloads through the download manager so it shows in
the Downloads panel with progress and cancel. The frontend wires the Update
button into the GGUF, on-device, and model-selector cards and keeps the
quant label fully visible when the action buttons crowd the row.
Adds regression tests for the multi-revision update check.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: accept force_download kwarg in hf_xet_fallback test double
The download seam now passes force_download to the attempt callable; the _FakeAttempt mock did not accept it, failing 6 tests with TypeError. Add the keyword (default False) so the scripted-results double matches the seam.
* Fix Studio model update regressions
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address Studio update review feedback
* Address Studio update edge cases
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Share GGUF update status helper
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix GGUF update detection and cache cleanup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix cached GGUF update badges
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: shimmyshimmer <107991372+shimmyshimmer@users.noreply.github.com>
Co-authored-by: Etherll <61019402+Etherll@users.noreply.github.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* Studio: clean up empty leftover quant folders so they can be deleted
An interrupted or cancelled split GGUF download leaves snapshots/<rev>/<quant>/
behind with no shards. Such a folder is neither a completed download nor a
tracked partial (no .incomplete blobs, no manifest), so it was invisible in the
variant list and a per-variant delete returned 404, leaving it on disk forever.
- list_empty_gguf_variant_dirs: detect quant folders that are empty in every
snapshot, excluding any quant that has shards in another snapshot.
- get_gguf_variants_response: surface those quants as partial (cleanable) so the
UI shows a delete affordance.
- _delete_gguf_variant_from_repos: remove the empty (or just-emptied) quant
subfolder and count it toward the result so the delete succeeds instead of 404.
Adds hub/tests/test_empty_variant_folder.py.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: simplify empty-dir check to any(iterdir())
* Studio: tighten comments on empty-quant-folder cleanup
* Studio: surface empty-folder removal failures and cleanables on local/offline paths
Address review feedback on the empty leftover quant folder cleanup:
- _remove_empty_variant_dirs now returns removal failures (read-only cache or a
locked dir), and the variant delete raises 409 instead of a misleading 404; a
concurrent download refilling the dir (ENOTEMPTY) is still treated as a skip.
- Empty leftover folders are surfaced as cleanable on every variant-listing path
(prefer_local_cache / offline / HF-fallback), not just a remote listing, via a
single post-process that flips a listed quant to partial or appends an
unlisted one.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: surface empty-folder cleanables even when metadata fetch fails
When the cache holds only an empty leftover snapshots/<rev>/<quant>/ folder
from an interrupted split download and the client is offline or the HF
metadata request fails, _compute() re-raised before cleanables were marked,
leaving the folder undeletable. Now fall back to marking cleanables against an
empty response and return them if any; otherwise re-raise the original error.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: add an Open button to reveal the models folder in the file manager
* Studio: report models folder creation failures
---------
Co-authored-by: Wasim Yousef Said <wasimysdev@gmail.com>
* Studio: free chat model VRAM at training start only when the GPU is tight
The training start route unconditionally tore down the transformers/MLX
inference subprocess before training, and never stopped the llama.cpp GGUF
server at all, so a loaded GGUF chat model kept holding VRAM for the whole
run. Conversely the HF model was always unloaded even when there was plenty
of room to keep it.
Make the unload VRAM aware and cover every inference backend:
- Add routes/training_vram.py with summarize_resident_chat(),
can_keep_chat_during_training() and free_chat_models_for_training(). The
keep/unload decision reuses the same estimator and live per device free
VRAM reader the training GPU selection already uses (auto_select_gpu_ids,
estimate_required_model_memory_gb, get_visible_gpu_utilization), so the
probe agrees with the placement computed later in start_training.
- When a chat model is resident and training fits alongside it with a
conservative margin (required_gb * 1.15 + 4 GB), keep it loaded so the
user can train and chat at the same time; on a multi GPU box training
lands on a different GPU and both coexist. Otherwise unload the HF/MLX
orchestrator and the llama.cpp GGUF server before training starts.
- The export subprocess shutdown stays unconditional and now runs first so
its freed VRAM is reflected in the decision.
Default deny: non CUDA backends, unestimable models, or any probe error
fall back to the previous always unload behavior.
Adds tests/test_training_vram_coexistence.py and updates two existing route
tests in test_gpu_selection.py.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: per-GPU floor for explicit GPU lists + don't unload chat on invalid gpu_ids
Address review feedback on the chat coexistence probe:
- Explicit gpu_ids mode now enforces a per-GPU floor in addition to the
aggregate free-VRAM check, mirroring auto_select_gpu_ids' min_per_gpu_N.
Without it, an uneven split such as free [45, 10] for a 40 GB job passed
the aggregate threshold and kept chat loaded even though the 10 GB GPU
could not hold its training shard, risking an OOM.
- Invalid explicit gpu_ids (ids outside the visible set, or a UUID/MIG
mask) make resolve_requested_gpu_ids raise. That request is rejected with
a 400 before training starts, so leave the resident chat model untouched
instead of unloading it.
- Tighten the target_modules / gpu_ids type hints to List[str] / List[int].
Adds tests for the per-GPU floor (uneven split unloads, even split keeps)
and for invalid gpu_ids keeping the chat model loaded.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: only free chat VRAM once training will start; handle in-flight and CPU-only chat
Address the second review pass on the chat-coexistence path:
- Run the chat/export VRAM teardown as a before_spawn hook inside
TrainingBackend.start_training, fired only after the start guards pass.
Previously the route freed chat VRAM before calling start_training, so a
refused start (e.g. a lingering pump thread) would tear down the resident
chat model even though no training job began.
- Treat an in-flight HF chat load (loading_models set, no active model yet)
as not safely sizeable: free it rather than risk both OOMing as the load
keeps allocating after training starts.
- Do not count or tear down a GGUF llama-server confirmed to run entirely on
CPU (_gpu_offload_active is False): it holds no VRAM, so killing it cannot
help training fit.
Adds tests for the before_spawn hook (runs on start, skipped when a
subprocess is alive or a pump thread will not die, survives a hook error),
the in-flight load flag, and the CPU-only GGUF exclusion in both the resident
summary and the unload path.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: treat any in-flight chat load (HF swap / mid-start GGUF) as unsafe to keep
Tighten the in-flight detection in summarize_resident_chat so the keep check
never sizes a load that is still allocating:
- Flag loading on ANY non-empty loading_models, not only when active_model_name
is empty. load_model adds the new model to loading_models before clearing the
old active_model_name, so a replacement load during a swap was previously
sized as a normal resident and could OOM as the new model finishes loading.
- Flag a GGUF server that is active but not yet healthy (is_loaded False) as
in-flight: it is still mmaping/offloading layers, so its final VRAM footprint
is unknown.
Consolidates the signal into a single resident["loading"] flag; the route frees
the chat model whenever it is set. Adds tests for the replacement HF load and
the mid-start GGUF cases.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: tighten comments in chat/training VRAM coexistence (comments only)
* Studio: run before_spawn VRAM hook only after GPU-selection validation
Reviewers found the before_spawn hook fired before prepare_gpu_selection
validated gpu_ids (and before config build), so a refused start (invalid
gpu_ids -> 400, or a bad grad-clip value) could still tear down chat/export
VRAM. Move the hook to immediately before proc.start(), once all synchronous
validation and process construction have passed. This also fixes the route's
in-flight-chat loading branch, since that teardown runs inside the same hook.
Add test_hook_skipped_when_gpu_selection_rejects.
* Studio: recompute GPU auto-selection after the before_spawn VRAM hook
Codex P2: with before_spawn moved after prepare_gpu_selection, placement was
frozen against the pre-teardown VRAM state while the hook freed export/chat
afterward. Auto-selection could pin training onto a GPU the hook then cleared
(or onto a kept chat model). Split validation from placement: explicit gpu_ids
are still validated before the hook (raise -> 400, no teardown; explicit
placement is VRAM-independent), but VRAM-dependent auto-selection now runs
after the hook so it sees the freed memory.
Add test_auto_placement_runs_after_hook and test_explicit_placement_validated_before_hook.
* Studio: allow chatting during training (lift sidebar gate + VRAM-aware load guard) (#6335)
* Studio: allow chatting during training (lift sidebar gate + VRAM-aware load guard)
The sidebar disabled New Chat, project, and home navigation while a training
run was active, so users could not chat during training even though the backend
serves inference fine alongside a run. This removes that gate and adds a backend
guard so the one genuinely risky operation, loading a new local chat model
mid-training, is refused with a clear 409 when it would not fit beside the run.
Frontend (app-sidebar.tsx): drop the chatDisabled = isTrainingRunning gate and
its consumers. Navigation triggers no model load on its own, so chat stays
usable during training.
Backend (routes/training_vram.py, routes/inference.py): add
can_load_chat_during_training plus a load/validate guard that sizes the same
effective load the loader performs (LoRA 4-bit to 16-bit resolved first, HF auto
placement via auto_select_gpu_ids, explicit multi-GPU per-GPU floor, GGUF sized
from on-disk shards and companions or the selected remote variant). It is a
no-op when training is inactive, never blocks external providers or
already-resident models, and default-denies only on a CUDA sizing failure so a
load can never OOM the run. Validate refuses early with the real settings so the
frontend does not unload the resident chat model for a load that would be
rejected.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: address review feedback for chat-during-training load guard
- Run the load/validate VRAM guard via asyncio.to_thread so the sync
nvidia-smi + HF metadata work never blocks the event loop.
- Size the GGUF KV cache at the requested context (_estimate_gguf_kv_gb)
and add it to the local GGUF estimate so large-context picks are not
under-counted.
- Keep the requested quantization when adapter_config.json is malformed
(not a JSON object) instead of raising in _effective_load_in_4bit.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: size the training load guard at the launcher's effective GGUF context
The GGUF KV-cache estimate used max_seq_length only, but the llama.cpp
launcher honors a user --ctx-size/-c in llama_extra_args. A load such as
max_seq_length=4096 with --ctx-size 131072 was sized against a 4k cache
while the server allocates 131k, so the guard could approve a long-context
GGUF load that then OOMs training. Size the guard's KV at the larger of
max_seq_length and the parsed --ctx-size (reusing the launcher's own
parse_ctx_override), keeping the conservative f16 cache so the estimate is
never smaller than what the server allocates.
The chat model picker also validated with the raw max_seq_length while
/load sizes with resolveLoadMaxSeqLength, so validate could pass, unload
the current model, then have /load reject the native-context load. Validate
now uses the same effective context; the load path is unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: size the GGUF training guard at the server parallel-slot count
The KV-cache estimate assumed a single slot, but llama-server allocates the
cache across --parallel slots (app.state.llama_parallel_slots). On a Studio
launched with --parallel N>1 the guard under-sized the cache N-fold and could
approve a GGUF chat load that then OOMs training. Thread the same slot count
the loader uses into the guard's KV estimate; default 1 leaves single-slot
setups unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Trim comments for chat-during-training guard
* Studio: keep chat generation alive across navigation; Train spinner + Return to Chat
Hoist the base chat runtime above the routed outlet so navigating to Train (or any tab) no longer aborts an in-flight generation; only an explicit Stop cancels. Add a Train sidebar spinner and swap New Chat to Return to Chat while a run is active, with a lightweight completion watch so the spinner clears from any tab. Also respawn a chat llama-server killed mid-session and guard unreadable HF cache dirs that 500'd the hub model list.
* Studio: show Return to Chat on the Train tab whenever a chat is live
Previously the top sidebar item only swapped to Return to Chat while training was running; on the Train tab with an idle/just-finished run it stayed New Chat, which started a fresh thread and cancelled an in-flight generation. Show Return to Chat (and navigate back, preserving the run) whenever a generation is running or its thread is still active, or training is in progress.
* Studio: keep a running chat alive when starting a New Chat
Starting a New Chat (or switching threads) while a generation was in flight
remounted the single-chat runtime provider, which detached the in-flight run
and cut the previous chat off (it showed up frozen / empty when reopened).
Key the single-chat view by project instead of by thread or new-chat nonce so
the provider stays mounted and assistant-ui switches to a fresh thread in place.
The previous generation keeps streaming in the background and autosaves on
completion, and returning to that thread reattaches the live run instead of
reloading a half-saved one.
Also:
- "Return to Chat" now lands on the thread that is still generating rather than
the empty new chat that became active after New Chat.
- Skip the explicit /inference/cancel POST when an abort comes from a runtime
detach (navigation / background switch) rather than an explicit Stop, so a
backgrounded generation is never cancelled behind the scenes.
* Studio: make model export non-blocking and inline
The Export tab opened a full-screen modal that trapped focus, could not be
closed or cancelled while running, and showed no progress. It also stopped
training and unloaded the chat model before loading, so export could not run
alongside them.
Export now mirrors the training runtime pattern:
- Inline panel embedded where the Export Model button was, with no modal or
backdrop, so the rest of the UI stays usable during an export.
- Global export runtime store plus an app-root lifecycle hook, so a run keeps
going and streaming across navigation and is reflected on the Export nav item
from any tab.
- The worker log stream now stays connected across the load to export phase
boundary instead of stranding on "Waiting for worker output".
- Progress bar driven by phase and quant index (quant N of M for GGUF), with
elapsed time and a working Cancel.
- load-checkpoint no longer stops training or unloads inference; export loads in
its own subprocess in parallel and surfaces out-of-memory as a clear error.
- Add POST /api/export/cancel and is_export_active on /api/export/status.
* Studio: show Return to Chat on the Export tab too
Extend the New Chat to Return to Chat swap to the Export route so leaving a
running chat for Export offers a way back to the live generation, matching the
Train tab.
* Studio: smooth out Export animations and polish the panel
- Drop the height-based reveal animations (source switch, run panel, quant
picker, hub fields) that caused flashing and reflow; use instant swaps and
quick opacity fades instead.
- Method and quant cards now transition colors only, with no transition-all or
hover lift, so selecting a method or quant is crisp instead of jumpy.
- Auto-scroll the export panel into view when it opens and add a scroll-to-bottom
button when its output is below the fold, like Chat.
- Show Return to Chat on the Export tab while an export is running, matching how
training drives it on the Train tab.
- Surface the current phase or stage in the live output before the first worker
line arrives so the panel never looks stuck while progress is advancing.
* Studio: show Return to Chat on every non-chat tab
Generalize the Return to Chat swap from just Train/Export to any non-chat route
(Recipes, Projects, Hub, ...) so a running or active chat is always one click
away, instead of showing New Chat there.
* Studio: stream export logs over the Cloudflare tunnel; drop janky export animations
Exporting over a --secure Cloudflare quick tunnel showed "connecting..." with no
logs while the progress bar advanced. Cloudflare buffers text/event-stream and
only flushes when the stream closes, so the SSE log stream never reached the
browser during the run (direct localhost is unaffected, which is why this only
showed up over the tunnel).
Add a tunnel-safe JSON poll fallback (GET /api/export/logs?since=) that the
runtime lifecycle hook polls while a run is active. Short JSON responses are not
buffered by the proxy, so logs show up in near real time over the tunnel. It
shares the orchestrator's monotonic seq cursor with the SSE stream and the store
de-dupes by seq, so the two transports run together (SSE on localhost, poll over
the tunnel) without double-printing. A successful poll marks the panel
"streaming" instead of leaving it stuck on "connecting...".
Also remove the framer-motion AnimatePresence reveals from the export config and
run panel (quant picker, hub fields, the inline run panel, and the live log
section). The expand/slide animations flashed and felt clunky; the sections now
render in place.
* Studio: recover export over the Cloudflare tunnel when the blocking POST times out (524)
A model export over a --secure Cloudflare quick tunnel showed "Request failed
(524)" even though the export succeeded on the backend (the GGUF was written).
Cloudflare returns 524 when a single request takes longer than ~100s to respond,
and a GGUF conversion routinely runs for minutes, so the blocking per-method
export POST is cut off while the backend keeps going.
Confirm completion via short status polls instead of relying on the long POST
response (the same approach that fixed log streaming):
- The orchestrator records each finished op's outcome (status / output_path /
error) with a monotonic seq, exposed on GET /api/export/status.
- parseJson now preserves the HTTP status; a 524/520/522/523/502/503 or a
status-less network drop is classified as a recoverable transport error.
- runExport wraps each phase (load, every export method, each GGUF quant): on a
recoverable failure it keeps the run alive (logs keep streaming, the panel
shows "reconnecting...") and polls status until the still-running op finishes,
then settles from the recorded result, recovering the output path for the
success banner. A real 4xx still fails immediately; localhost still uses the
fast POST response. applyBackendStatus also settles a reloaded run from the
last-op record.
Verified over the tunnel: a 3m14s gemma-4-E4B-it GGUF export now ends on the
success banner with the output path instead of 524.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: keep the export method + logs visible after navigating away mid-export
While an export was running, navigating to another tab and back to Export
remounted the page and reset the local form state (exportMethod, quant levels),
so the method card showed unselected and the run panel's log area was hidden
until the card was re-clicked. The run itself lives in the global store and was
unaffected.
Seed exportMethod / quantLevels from the active run's summary via lazy useState
initializers on (re)mount, and gate the panel's log area on the live run
(isExporting / logLines / the run's method) rather than only the local form
selection. The card stays selected and the logs/progress stay visible across
navigation; nothing changes when no run is active.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: address export/training review findings
- Export: guard Start against an empty GGUF quant selection so an inline-panel
run with no quant can't settle as success with no file produced.
- Export: thread the source HF token into the background load so gated/private
HF source exports (and gated bases) authenticate, matching the consent path.
- Export: only settle a recovered (non-owned) run as a finished export when the
last backend op was an export, not a standalone load_checkpoint.
- Training: free the export subprocess whenever an export is active, not only
once a checkpoint is loaded, so an in-flight export load can't race training
for VRAM (current_checkpoint is unset during the load phase).
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio Hub: default downloads to Xet transport
Model and dataset downloads defaulted to HTTP; flip the default to Xet for faster parallel chunked transfers.
- Frontend: DEFAULT_TRANSPORT_MODE is now Xet, so a user with no saved preference starts on Xet. effectiveTransportMode() already downgrades to HTTP and warns when hf_xet is unavailable, so this degrades gracefully.
- Backend: DownloadModelRequest.use_xet and DownloadDatasetRequest.use_xet default to True, keeping the API in step with the UI. Set use_xet=False for sequential HTTP Range-resume.
- Align the internal _spawn_download_worker default so no caller silently falls back to HTTP.
Inference and training model loads were already Xet-first with an HTTP stall fallback, so this brings explicit downloads in line with the rest of Studio.
* Studio Hub: gracefully fall back to HTTP when Xet is unavailable
With Xet now the default, an omitted or explicit use_xet=True from a non-UI API caller would 400 on installs without hf_xet, since resolve_transport raises when the transport is unavailable.
Add resolve_effective_use_xet(), which downgrades a Xet request to HTTP (with a warning) when hf_xet is missing, mirroring the frontend's own downgrade. Both the model and dataset flows now derive a single effective use_xet and feed it to resolve_transport and spawn_worker, so the recorded transport and the worker env can never disagree. The UI is unaffected: it already resolves availability and passes use_xet explicitly.
* Add tests for resolve_effective_use_xet Xet to HTTP fallback
* Trim comments for PR #6433
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* fix(hub): stop demoting cached gguf variants on mmproj or filename mismatch
- bug: a quant with its bytes on disk was marked not fully downloaded when the API-preferred main filenames did not match or the mmproj adapter was absent
- fix: fall back to the on-disk quant byte signal, the same one inventory uses for on-device, so a present quant is no longer demoted
- broaden mmproj detection to accept any mmproj-looking cached file, not only the API-preferred name
* feat(hub): full-page redesign with trending feed, search, and persisted state
- convert the hub to a full-page view with a new layout, model cards, and a sortable models table
- add a trending/latest/finetune feed with model and section deep-link params validated on the hub route
- add recent searches and rework model and dataset search with pagination and infinite scroll
- persist feed and token state through a dedicated store and persist-storage layer
* fix(hub): browse sorting, deep-link presets, dataset URLs, and persistence
- sort dropdown: drive HF-wide browse across all repos by the chosen sort, respecting format and capability filters
- section deep-link: apply the section preset (format and sort) on refresh and deep-link, not only on click
- dataset detail URL: persist the resource kind so refresh and share resolve datasets correctly
- gguf card: show a Loading state for hub-cache dir-path repos via repo-id match
- active-model CTA: New Chat now actually opens a fresh chat
- persist-storage: fix throttle keying with a Map and dedupe a duplicated util
- transport-toggle: drop redundant controlled-tooltip state
* Studio: polish hub redesign UI and unify segmented tabs
Refinements on top of the hub full-page redesign:
- Unify every segmented control (Discover/On Device, models/datasets,
Unsloth/All, recent/name/size, settings tabs, train dataset source,
profile shape, theme, OS toggle) on one filled-pill design.
- Hub list now loads in larger batches with a shorter fetch interval so
results fill in fast instead of dripping one row at a time.
- Disable remote avatar fetches in list rows and brighten the colored
initial fallbacks so they read clearly without network calls.
- Add a split master-detail view for model lists and make it the default.
- Left-align the split "Showing GGUF models" header with the rows below.
- Round the "Load more" footer box and tidy On Device stats layout.
- Show recent trainings on Recipes and Export, falling back to recent
chats when there is no training history.
* Studio: address hub review comments (filter warning + scrollMargin)
- DiscoverFetchMoreFooter only shows the "results may be hidden by your
filters" note when a filter is actually active, instead of always.
- Use the destructured scrollMargin prop directly in the row transform
rather than reaching into virtualizer.options.scrollMargin.
* Fix/adjust Hub metadata and deep links for PR #6349
* Studio: drop avatar ring in hub split view
The split master-pane rows (discover + on device) added a ring-1 around
the owner avatar that read as a shadow. Remove it so split-view avatars
match the flat avatars elsewhere; grid cards and the full list keep theirs.
* Studio: hub sort + scope as dropdown pills beside view tabs
Recent/Name/Size and Unsloth/All were segmented controls that dropped to
their own row in the narrow split pane. Make each a compact dropdown pill
(HubOptionMenu) that sits in the header actions slot next to the view-mode
tabs in every layout, so split view no longer needs a separate row.
* Studio: align hub list header with the view tabs and rows
- Vertically center the "On device" / "Showing GGUF models" title with the
dropdown pill and view-mode tabs (items-center instead of items-end), so a
short title no longer sits low against the taller tab row.
- Nudge the back chevron 2px further left (-ml-2) so its glyph edge lines up
with the start of the row hover below it.
* Studio: align back chevron tip with the row hover edge
The arrow glyph is inset ~6px inside its centered icon box, so an
edge-aligned button left the visible chevron sitting in from the column.
Pull the button out (-ml-3.5) so the chevron tip lands on the row hover's
left edge instead of floating to its right.
* Studio: unify every bare tick on the shared check mark
Point all plain checkmarks at the canonical @/lib/tick-icon tick (the one
already used in the chat composer and menus), so there is a single tick
across the app:
- Hub: model-inspector, hub-option-menu, path-info-button were importing
the stock hugeicons Tick02Icon; switch them to the shared icon.
- Chat / assistant-ui: artifact-surface, prompt-storage-dialog, reasoning,
tool-ui-python, tool-ui-terminal, tool-ui-code-execution, and the
tool-fallback status map used lucide CheckIcon; render the shared tick
via HugeiconsIcon instead (tool-fallback wraps it to fit its icon map).
The circular CheckmarkCircle success badges are intentionally left as-is.
No bare CheckIcon/stock Tick02Icon references remain; verified the tick
renders in every converted spot via typecheck + build.
* Studio: nudge back chevron 2px right
-ml-3.5 pushed the chevron a touch too far left; -ml-3 sits it just
inside the row hover edge, aligned with the avatars below.
* Studio: search base-model chips across all publishers
Clicking a Base model chip searches the Hub for the upstream repo, which
lives under another publisher (google, meta, etc.). It left ownerScope at
the default "unsloth", so the search hard-restricted to the Unsloth org and
could never surface the base model. Switch the scope to "all" for this action.
* Studio: label the safetensors list header "Safetensors"
The focused list heading showed "Showing Checkpoint ... models" while the
format dropdown labels the same checkpoint filter value "Safetensors". Match
the dropdown so the header reads "Showing Safetensors ... models".
* Studio: simplify the focused list heading to "Models"
Drop the format/capability composition (e.g. "Showing Safetensors Reasoning
models") so the focused list heading just reads "Models" (or "Datasets").
Search keeps its "Results for ..." label.
* Studio: drop the header refresh button to the text baseline
The refresh button sat at the heading's vertical centre. Nudge it down so
it lines up with the bottom of the title text instead.
* Studio: hide redundant "Back to Hub" in the split detail pane
In split view on large screens the master list sits beside the detail, so
the back button is redundant. Hide it there (lg) and reclaim the top space.
It stays on the small-screen overlay and the full-page detail, where the
list is hidden and back is the only way out.
* Studio: match the readme scroll fade to the left column
The detail pane relied on the sticky back-bar's fade, which is now hidden in
split view. Add the same hub-scroll-fade overlay the master list uses so the
readme fades consistently at the top when scrolled. The back-bar, when shown,
sits above and covers it.
* Studio: align Hub refresh button to the heading text bottom
* Studio: nudge Hub refresh button up to the heading text
* Studio: optically centre the HF token shield in its circle
* Studio: preview the first visible on-device row in split view
* Studio: calm the on-device row colour and fix size tooltip contrast
* Studio: fix Hub reset tab and clear search when opening a section
* Studio: fix Hub feed defaults, filter sync, and GGUF vision download state
* Studio: condense Hub redesign code comments
---------
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: shimmyshimmer <info@unsloth.ai>
Co-authored-by: Michael Han <107991372+shimmyshimmer@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Studio: support separate-file MTP GGUF drafters (Gemma 4)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: fix review findings for separate-file MTP drafters
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: pair local MTP drafters by name and include them in reload dedup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: manage --model-draft in extras and reject MTP/ copies as models
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Adds the Studio Hub and download manager: browse Hugging Face models and datasets, download GGUF and safetensors with live progress and cancellation, and manage on-device inventory. The Hub does not require a GPU, so it is available on chat-only hosts.
CI: all substantive checks pass, including the three Core jobs after unsloth-zoo#736. The two red checks are non-code flakes, a transient npm-registry DNS resolution failure in the package scan and one quantized vision-model output assertion whose sibling shards passed.