Three review findings, all verified:
1. wry keys the WebKitGTK base-cache dir to the app DATA dir (same as
base-data), so on Linux the stale frontend cache also lives under
~/.local/share/ai.unsloth.studio. Clear the cache-typed subdirs there
(WebKitCache, CacheStorage, serviceworkers) while keeping localstorage,
indexeddb, and cookies. Tests extended to 23 assertions.
2. run_all.sh invoked the new test with sh, but the extracted setup.sh
function uses bash arrays; dash aborts with a syntax error before any
assertion. Invoke with bash.
3. The in-app desktop update runs start_backend_update before
downloadAndInstall/relaunch, so setup.ps1/setup.sh clear caches while
the live WebView still holds them and silently fail. Clear the caches
from the Rust side in main() before the Builder runs: the config window
(and the WebView lock) exists by the time setup hooks fire, so this is
the one point where the profile is guaranteed unlocked. Same cache-only
path lists per OS; cargo check passes.
The desktop app's WebView caches (keyed by the Tauri bundle id
ai.unsloth.studio) hold copies of the previous frontend and keep serving
them after an update, so old styles linger even though the code on disk
is new. Clear cache-only paths on every install/update via setup.sh and
setup.ps1 (both fresh installs and 'unsloth studio update' route through
them).
Cleared: the HTTP/network caches, CacheStorage, service workers, and GPU
caches for the bundle id. Kept: LocalStorage, IndexedDB, cookies,
settings, models, and the studio database.
macOS: ~/Library/Caches/<bid> and WebsiteData/{CacheStorage,
ServiceWorkers,DiskCache}. Linux: XDG cache dir. Windows:
EBWebView\Default\{Cache,Code Cache,GPUCache,Service Worker}.
Adds tests/sh/test_setup_webview_cache_clear.sh covering both OS
branches, XDG overrides, and that user-facing storage survives.
* unsloth start/run: tool-call flags, positional model, grouped help
Expose the existing tool-call controls as first-class CLI flags on both
unsloth run and unsloth start, add positional model detection with a GGUF
quant default, and group --help into rich panels.
Flags (unsloth run): --enable-tool-call-healing/--disable-tool-call-healing
(default on), --enable-tool-call-nudging/--disable-tool-call-nudging
(default on). Resolved before any re-exec and written to the existing env
controls (UNSLOTH_DISABLE_TOOL_CALL_HEALING, UNSLOTH_TOOL_CALL_NUDGE) so the
in-venv server reads them at import; an omitted flag respects a value the
parent already set.
Flags (unsloth start): --enable-tools/--disable-tools (default off, passthrough),
plus the same healing/nudging flags (default on). start conveys them to the
auto-started run via the child env and the tools flag, so it stays correct even
if run re-execs into an older Studio venv.
Positional model: a leading org/name(:variant) token routes to --model when
--model is absent, without stealing an option value or an agent passthrough arg.
A bare GGUF repo with no variant defaults to UD-Q4_K_XL for the unsloth namespace
and Q4_K_M elsewhere, applied only on the fresh auto-serve path so attaching to a
loaded model never reloads.
Help is grouped into rich panels (Model / Server / Session for start; Model /
Server and network / Tool calls / Advanced for run) so --help reads cleanly.
Adds unit coverage for the helpers, the start command-and-env forwarding, the
positional/quant defaulting, and the run env resolution.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Positional model: reuse _is_hub_model_id so local dirs and paths are not stolen
Route a bare org/name positional to --model only when it resolves as a hub id
(via the existing _is_hub_model_id, which rejects local paths and existing
dirs), so an OpenCode project dir like owner/repo is left for the agent. Apply
the same guard to the auto-serve GGUF quant default so a local -GGUF path is
not forced to a quant it may not contain.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* unsloth start: typer floor, drop redundant GGUF quant default, respect inherited tool-call env
- Require typer>=0.12.0. The rich_help_panel options added here crash at import
on typer<0.6, and the dependency was previously unbounded.
- Stop forcing a default GGUF quant for a bare org/name-GGUF on auto-serve. The
server's own quant preference already picks UD-Q4_K_XL for Unsloth uploads and
Q4_K_M otherwise, and falls back when that exact quant is missing, so forcing a
fixed variant broke external repos that only publish Q5_K_M/Q8_0.
- Make the healing/nudging start flags tri-state so an omitted flag keeps an
operator's inherited UNSLOTH_DISABLE_TOOL_CALL_HEALING / UNSLOTH_TOOL_CALL_NUDGE
instead of overwriting it with the start defaults.
* Fix start passthrough and inherited tool settings
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: oobabooga <112222186+oobabooga@users.noreply.github.com>
* Studio: add Voice settings tab (dictation, dictionary, read aloud)
New Voice tab in Settings, placed just before About:
- Dictation: microphone picker, browser STT engine, recognition language,
and an inline mic test with a live transcript
- Dictation dictionary: entries rewrite matching speech to their exact
spelling and casing, applied in both dictation paths
- Recent dictations: last 20 final transcripts with copy and clear, so
text can be recovered if it lands in the wrong place
- Read aloud: optional button on assistant responses with two engines,
curated system voices (novelty and legacy voices filtered, quality
ranked, capped at 20) or the TTS audio model loaded in Unsloth via
/audio/generate (e.g. Orpheus), plus speed, pitch, volume and preview
Settings persist in localStorage (unsloth_voice_settings) and are read
at call time so changes apply without reloading the runtime. Adds en
keys plus the tab label for ja, zh-CN and pt-BR.
* Studio: drop the single option STT engine select, rename TTS option
The STT engine dropdown only had one entry, so it added noise without
giving a real choice. The engine row can come back once local STT
models land. Also renames the TTS engine option Unsloth TTS model to
Load TTS model to make the action clearer.
* Studio: harden Voice settings against edge cases found in simulation
Simulated the feature across Chromium, Firefox and WebKit plus node
level unit runs and backend contract checks. Fixes from the findings:
- Dictionary rewrite used a replacement string, so entries containing
dollar patterns corrupted transcripts (A$$AP became A$AP, $& injected
the match). Switched to the callback form of String.replace
- Persisted voice settings now validate types on hydration: non string
micDeviceId, dictationLanguage and ttsVoiceURI, and non boolean
ttsEnabled fall back to defaults instead of flowing into the UI
- Dictionary entries are trimmed, capped at 120 chars and re-sanitized
on hydration
- The Test dictation panel now falls back to the default microphone
when the saved device is unplugged, matching the composer adapter
Test coverage: 46 unit assertions (dictionary regex edge cases across
unicode, word boundaries and injection, voice curation for simulated
macOS, Windows and Linux voice inventories, corrupt storage merge),
13 backend contract checks against /audio/generate on an isolated
instance, and 60 browser assertions across the three engines covering
rendering, degradation without SpeechRecognition, curation in a real
DOM, dictionary persistence with unicode and dollar entries, the
no-model preview error path and corrupt localStorage recovery.
* Studio: address Voice settings review feedback
Verified each review comment before acting. Confirmed and fixed:
- Editing a dictionary entry was broken in two ways: the store trimmed
on every keystroke so spaces could not be typed, and clearing the
field deleted the entry and unmounted the input mid edit. Updates now
keep the raw value and a blur commit trims or removes the entry
- The unplugged mic fallback checked instanceof DOMException, but a
cross browser probe showed Firefox and WebKit throw
OverconstrainedError objects that are not DOMExceptions, so the
fallback never fired there. Matching on the error name now
- When the browser ended a dictation test on its own (silence timeout),
the mic stream stayed open. All recognition end paths now stop the
tracks and save the transcript through a single finalize path
- The studio TTS audio element now releases its WAV data URL as soon as
playback ends, fails or is cancelled
- Allow microphone now reports insecure contexts (no mediaDevices)
accurately instead of claiming access was blocked
- Voice tab copy moved into i18n keys per src/i18n/AGENTS.md, so locale
overlays can translate it; en is the baseline and parity passes
- unsloth_voice_settings added to the Reset all local preferences key
list so voice preferences obey the reset
- Non default microphones note that the system default is used when the
browser speech engine cannot bind a specific device, since browsers
without the start(track) overload ignore the argument silently
Re-ran the full simulation set after the changes: 46 unit assertions,
13 backend contract checks and 60 browser assertions across Chromium,
Firefox and WebKit all pass, plus a dedicated browser probe for the
dictionary editing behavior.
* Studio: use the chat mic icon in Voice settings for consistency
The Voice tab and its buttons used the hugeicons Mic02 glyph while the
chat composer uses a custom filled mic. Extract that composer icon into
a shared lib/mic-icon component, drop the duplicate inline copies in
thread.tsx and shared-composer.tsx, and use it for the Voice tab icon
and the tab's mic buttons so the microphone looks the same everywhere.
* Studio: address second round of Voice settings review feedback
Verified each new comment against the current code first. One item was
already fixed in the previous round (recording transcripts when the
browser ends a dictation test on its own). Confirmed and fixed:
- The microphone row showed a picker with generic names when browsers
enumerate unlabeled devices before permission, leaving no way to
grant access from the row. It now branches on whether labels are
visible and shows Allow microphone otherwise
- Compare chat dictation ignored the selected microphone. It now opens
the chosen device with the same fallback rules as the main adapter,
passes the track to recognition where supported and releases the
stream when recognition ends
- Closing the Voice tab cancelled the shared speechSynthesis even when
read aloud was playing a chat message. Cleanup now only cancels when
the tab owns an active preview
- Double clicking Start test could race two recognizers and leak the
first stream. A starting flag set before the getUserMedia await makes
start reentrancy safe
- Turning off the read aloud setting mid playback removed the only stop
control. The stop button now renders whenever a message is speaking
- When an engine lacks the start(track) overload, both dictation paths
now release the selected device stream before retrying with the
default microphone instead of holding it open
- Read aloud support no longer requires Web Speech synthesis: the
Unsloth TTS engine only needs audio playback, so it stays available
in WebViews without speechSynthesis, with a clear error if the system
engine is chosen there
Not addressed here: cancelling in flight backend TTS generation on
stop. The route runs generation in a worker thread without a
cancellation path, which is shared pre existing behavior with audio
chat generation and belongs in a backend change.
All suites re-run green: 46 unit, 13 backend contract and 60 browser
matrix assertions across Chromium, Firefox and WebKit, plus probes for
the unlabeled device branch and the double click race.
* Studio: drop empty and duplicate voiceURIs so the Voice tab never renders a crashing Select item
* Studio: guard dictation mic lifecycle in Voice test and Compare composer
Release a microphone opened after the component unmounts, and stop Compare
dictation on a permission or security failure instead of silently recording
from the default device, matching the main chat adapter.
* Studio: fix dictation and read-aloud lifecycle edge cases in Voice settings
- Join final dictation chunks with a space so recorded transcripts do not merge words
- Ignore a stale recognizer onend so a quick stop then restart is not torn down
- Use previewingRef so a double click on TTS preview does not orphan the first request
- Keep the read-aloud stop control visible when a new run starts while a message is spoken
- Stop the dictionary remove button from deleting an adjacent entry on a blur then click race
* Studio: trim redundant Voice settings comments
* Studio: fix Voice preview and Compare dictation edge cases
- Only cancel the shared speechSynthesis for a system-voice preview, so stopping
a Studio preview no longer stops an unrelated chat read-aloud
- Release the Studio preview audio and its WAV data URL on normal completion
- Iterate every finalized result in Compare dictation so batched phrases are kept
- Cap persisted recent dictations to the last 20 on hydration
* Studio: use clipboard fallback for recents and release failed preview audio
- Copy recent dictations via the copyToClipboard helper so the execCommand
fallback works in Safari and insecure http LAN contexts
- Release the Studio preview audio when play() rejects, not just on ended/error
* Studio: add local speech-to-text dictation engine
Add an offline dictation engine that transcribes with a local faster-whisper
model, alongside the existing browser (Web Speech) engine. The browser engine
streams audio to Apple or Google speech services and needs internet; the new
engine runs on the server, works offline, and drives any chat model without
evicting it (it loads in the backend process, separate from the model
subprocess). It also gives Firefox dictation, which has no Web Speech support.
Backend: a lazily-loaded, kept-warm faster-whisper sidecar and three routes
under /api/inference/audio (stt/status, stt/load, transcribe). faster-whisper
is torch-free, so this does not disturb the existing model stack.
Frontend: a Dictation engine setting (browser or local model), a curated model
picker with sizes, and MediaRecorder capture posted to the transcribe route.
The model warms automatically when the engine is selected, with live status.
* Studio: stream local STT transcription as you speak
Local dictation showed nothing until you stopped, because the whole clip was
transcribed once on stop. Now the growing recording is re-transcribed on a
fast pass every second and emitted as live interim text, with an accurate
final pass on stop. Partial recordings decode fine, and the model refines
earlier words as more audio arrives.
Adds an interim flag to the transcribe route (beam 1, no VAD) for the fast
preview pass; the final stop uses the accurate path.
* Studio: make local dictation stop instant and reliable
Stopping local dictation waited for a final network transcription before the
session ended, so the stop button did not flip and a second click ended the
session early and dropped the text. Now stop commits the live transcript
immediately, releases the mic at once, and ignores a second stop while
finalizing. Previews run more often so the committed text is current.
* Studio: record local dictation in short clips for reliable streaming
Re-transcribing a growing buffer every second got slower as it grew, flooded
the backend, showed stale words, and could leave the stop button stuck waiting
on a backlog. Record short independent clips instead and transcribe each once,
appending the text as you speak. Work per clip is bounded, so stopping is
prompt (with a hard timeout as a safety net) and long dictations stay smooth.
* Studio: dictate then transcribe once on stop, ChatGPT style
Local STT dictation streamed by re-transcribing the growing clip, which
was quadratic and saturated the backend (multi-second lag), and stop only
halted the recorder without releasing the mic, so it kept recording. Record
the microphone continuously, release it the instant the user stops, and
transcribe the whole clip once. Stopping is immediate and the transcript
lands in about a second. Also add the tiny model for the fastest option.
* Studio: surface dictation and read-aloud failures instead of failing silently
- Compare dictation reports microphone and speech-recognition errors via toast,
reusing the main chat adapter's describeMediaError and describeSpeechError
- Read-aloud toasts genuine model or synthesis failures while ignoring cancellations
* Studio: ChatGPT-style recording bar for dictation
Clicking the mic now drops the composer into a dedicated recording bar
with a live waveform, a discard (X) and a confirm (tick), instead of a
plain stop button. The tick stops recording and transcribes the clip;
the X throws the recording away and keeps whatever text was already in
the composer. The model adapter taps the mic with an analyser to drive
the waveform, and the router tracks the live session so the X can cancel
it without transcribing.
* Studio: transcribe dictation while speaking, ChatGPT layout
Match ChatGPT's recording layout: the bar now renders in place of the
input with the left plus button kept, the waveform in the middle, and
the discard and confirm buttons together on the right.
Cut the post-confirm delay by transcribing in the background as the user
talks. The audio is split at natural pauses (voice-activity detection off
the same analyser that drives the waveform) and each clip is transcribed
as it is cut, so confirming only has to finish the short final tail. The
model is also warmed when recording starts so the first run never pays a
cold load.
* Studio: ChatGPT waveform, hide tools while dictating, faster STT
Make the recording UI read like ChatGPT: the waveform is now a dense row
of round dots that rise into thin centered bars, and while dictating only
the plus button shows, with the mode badge and tool toggles hidden so the
bar is just the waveform and controls.
Speed up transcription: decode greedily (beam_size=1), which is several
times faster on CPU with negligible accuracy loss on short dictation
clips, and cap background segments at 6s so the final tail after confirm
stays short.
* Studio: finish ChatGPT voice bar and low-latency STT
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: full-width waveform with a timer that freezes on stop
Use the full-width waveform for the recording bar: brighter, bigger bars
that advance on a fixed cadence (keeping peaks between advances) so they
glide instead of racing by, inset from the composer edges. Keep a visible
timer and the green confirm button, matching the ChatGPT reference, and
freeze the timer and waveform the moment the user confirms.
* Studio: fix multilingual local dictation
* Studio: speed up dictation and release local STT
* Studio: harden dictation finalization and STT decoding
* Studio: restore Firefox dictation fallback
* Studio: add dictation history manager
* Studio: manage speech model downloads
* Studio: remove em dash from voice model label
* Studio: move dictation history into Voice
* Studio: source local STT from Unsloth Whisper models
Point the dictation STT sidecar and its Model Hub download entries at
Unsloth's Hugging Face Whisper repos (small, large-v3-turbo, large-v3)
and run them through Transformers, so Studio only ever downloads
Unsloth-uploaded weights. Drop faster-whisper and the Systran/mobiuslabs
repos; keep the Model Hub as the only download path via local_files_only,
and keep PyAV for audio decoding.
Device selection uses float16 on CUDA and float32 on MPS and CPU, since
Whisper's decoder is unstable in float16 on MPS and repeats tokens.
Shorten the model picker labels to name plus download size and update the
STT tests for the new backend.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: smooth dictation waveform and keep pill height
* Studio: align STT model dropdown width and tidy voice copy
* Studio: guide to local engine when browser dictation is offline
* Studio: clarify voice section and STT model copy
* Studio: keep STT warm with training-aware eviction
* Harden STT lifecycle and browser compatibility
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix model discovery test lint
* Harden cross-browser microphone errors
* Harden cross-browser microphone errors
* Surface voice test recognition errors and fall back to Studio TTS
- Voice test now toasts non-abort speech-recognition failures instead of
ending silently, matching the main and Compare dictation paths.
- Read-aloud routes to the backend model when the runtime lacks Web Speech
synthesis (audio-only WebView), so it no longer errors immediately.
* Fix reviewed STT lifecycle races
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix read-aloud fallback controls
* Guard read-aloud stop when deleting a non-speaking message
aui.message().stopSpeaking() throws unless this message is the one being
read aloud, so calling it unconditionally rejected the delete handler before
the message was removed. Only stop speech when this message is speaking.
* Cap recent dictation transcript length before persisting
Recent dictations only limited entry count, so a long transcript stored the
full text in the persisted voice settings and a few could exceed the
localStorage quota, throwing synchronously from the uncaught dictation cleanup
path. Truncate each entry on save and on hydration, matching the dictionary cap.
* Studio: keep dictation mic clickable and guide to local model
Register the dictation adapter unconditionally so the mic stays enabled
for any engine and starts working right after switching to the local
model on an already-open thread.
When the browser engine cannot run (Firefox, Brave, non-secure origins),
clicking the mic shows a toast that points to the local speech-to-text
model instead of leaving a disabled button. The toast stacks its action
below the text with a fully rounded button.
* Studio: add bottom padding below the dictation guidance toast button
* Studio: increase bottom padding under the dictation toast button
* Studio: add bottom padding inside the dictation toast button
* Studio: add five Whisper defaults and custom model search
Add private UnslothAI Tiny and Base mirrors to the curated local STT choices while keeping Small as the default. Let users search or paste a Transformers-compatible Whisper repository and validate it end to end.
Keep short dictations in one clip to avoid repeated padded encoder work, then split longer recordings near Whisper's 30-second boundary.
Update hidden model filters and tests, including the CPU-only CI runtime stub for PyAV.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: use public Unsloth Whisper repositories
Point the Tiny and Base dictation defaults to the public unsloth repositories and remove the private mirror references from model filtering and tests.
* Studio: update Whisper download sizes
Reflect the cleaned public Tiny and Base repositories in the curated model labels.
* Studio: right-align STT model size, fix dropdown wheel scroll, refresh sizes
- Show the download size on the right of each model row so long names
like Whisper Large v3 Turbo no longer hide it
- Update curated Whisper sizes to the safetensors weights actually
downloaded: Tiny 151 MB, Base 290 MB, Small 967 MB
- Drive the model list scroll from a wheel handler so the mouse wheel
scrolls it inside the Settings dialog, not just the scrollbar
- Add a search icon and shorten the placeholder to Search model
* Studio: do not search when a dictation model is picked, shrink repo label
- Treat the filled-in model text as a selection, not a query, so choosing
a model no longer kicks off a Hugging Face search
- Make the repository line under each model name smaller
* Studio: tighten dictation model and local engine descriptions
* Studio: keep model display on pick instead of the query, shrink row text
- Guard the combobox input so selecting a model shows its name and does
not echo the typed query back or start a search
- Map the item label to the friendly display so picks fill the field
- Reduce the model name and size text in each row
* Studio: show only the model name in the dictation field, shrink size label
- Drop the download size from the search field; the name alone is shown
once a model is selected, with sizes kept in the dropdown list
- Reduce the size label text in each row
* Studio: clarify the dictation model description
* Studio: drop Hugging Face from the dictation model description
* Studio: move the dictation dictionary to its own Manage subpage
- Replace the inline entry list with a Manage row, matching Dictation
history, so a long dictionary no longer crowds Voice settings
- Add a DictationDictionaryView subpage that holds the entry editor
* Studio: match STT field font, use best voice for System default
- Bump the dictation model field text to text-sm so it matches the
engine dropdown next to it
- Resolve the System default read-aloud voice to the top curated voice
instead of the browser default, which is a robotic legacy voice on macOS
* Studio: rerank read-aloud voices and drop duplicate voice entries
- Rank by vendor quality, then the user's locale, then a preferred list of
natural voices, so the best voice leads instead of the first alphabetically
- Collapse voices that macOS reports twice under one name and language
* Studio: fold dictionary and recents into the dictation section
- Drop the separate Dictation dictionary and Recent dictations headings;
their Manage rows now sit under Dictation, split by the row divider
- Shorten the custom spellings description
* Studio: add search and sort to dictation history
- Filter saved dictations by text with a search field
- Sort by newest, oldest, or A to Z; show a no-matches message
- Keep Clear all available regardless of the current filter
* Studio: settle cancelled STT loads before training and fix dictation review items
Wait for a cancelled STT load to exit and release its memory before
reporting it freed for training, so the loader cannot still be inside
from_pretrained()/.to(device) holding VRAM when the training subprocess
starts. A load that finishes before observing the cancel now gets
unloaded so the memory is actually reclaimed.
Clear the accelerator cache before the CPU fallback in load() so a failed
CUDA/MPS load does not strand reserved VRAM once the sidecar is marked
CPU-resident.
Send the saved Hugging Face token when polling STT download progress so a
gated or private repo resolves and shows the correct Load/Downloaded
state instead of reporting missing.
Mark the composer Dictate button as type="button" so clicking it does not
also submit the draft when the composer already has text or attachments.
* Studio: pin dictation settings per session and close STT startup races
Capture the STT model and language when a dictation session starts and
pass them to every queued segment and the warm-up load, so changing the
model or language mid-recording no longer transcribes the same clip with
the wrong model or a model that is not downloaded.
Check the local runtime at the top of transcribe(), before the model
cache lookup and the bounded audio decode, so a server missing PyTorch or
Transformers returns 501 up front instead of decoding a long clip first.
Treat the training startup window as active for STT device selection.
start_training frees VRAM in before_spawn but only assigns _proc later, so
a concurrent STT load could take the GPU that was just cleared. A startup
flag now reports training active from the free until the process is live,
forcing those loads to CPU; a finally clears it on every exit.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: stub the STT runtime check in transcribe orchestration tests
transcribe() now verifies the local runtime up front, so the unit tests
that exercise transcription orchestration must treat the runtime as
present to keep passing where PyTorch, Transformers, and PyAV are not
installed. Stub ensure_stt_available in the shared fixture and restore
the real check in the availability and load-rejection tests.
* Harden custom Whisper dictation models
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add whisper.cpp dictation engine with per-engine downloads and history rework
Engines
- New GGML STT sidecar that runs a managed whisper-server subprocess with
idle unload, plus a pinned static build script (scripts/build_whisper_cpp.sh)
- Dictation engine picker now offers Browser, Local transcription
(whisper.cpp), and Local transcription (Transformers)
- Both local engines serve the same five curated Whisper models and download
them directly with byte-level progress reported by /audio/stt/status
- Models auto load on selection and when their download finishes
- Unload and training admission account for both engines
Benchmarks (Apple Silicon, greedy, warm, same checkpoints)
- whisper.cpp transcribes 2.4x to 5x faster than Transformers and loads in
about 0.45s vs 0.86s for Whisper Small
- whisper.cpp GGUF path is unchanged by the Transformers addition
(load 0.445s -> 0.444s, short clip 0.391s -> 0.347s, long 1.197s -> 1.129s)
Voice settings UI
- Plain curated model select replaces the searchable combobox
- Single download progress bar with transfer rate for both engines
- Dictation history now stores every dictation with Show more pagination,
a top Clear history action, and links back to the chat it was spoken into
- Archived chats dialog gets the same pagination
- Delete dialog offers deleting a dictation together with its chat
Tests: 88 backend STT tests pass, including new snapshot download coverage.
Frontend typecheck, lint, i18n parity, and production build pass.
* Merge local engines into one option and source GGML models from unslothai
Engine selection
- The dictation engine dropdown is back to two choices: Browser and Local
transcription. The selected model decides the backend: curated ids run
GGML checkpoints through whisper.cpp, searched Hugging Face repositories
run safetensors through Transformers
- Model picker lists the curated models and searches Hugging Face for other
Whisper repositories, validating them before selection. The trigger is a
plain button so the selection never renders inside a text input
- /audio/stt/status accepts a model query param so downloaded state works
for custom repositories; the engine param on load, transcribe, and
download routes is derived from the model everywhere
Model source
- Curated GGML checkpoints now download from the Unsloth-hosted
unslothai/whisper-*-GGUF repositories (one repo per model) instead of
ggerganov/whisper.cpp; cache lookups, progress totals, and in-flight blob
tracking are per-model
Fixes
- Voice settings and dictation history were not persisting: the quota-safe
localStorage wrapper was declared after the store that uses it, so the
persist storage factory failed silently. Every settings write also threw
mid-click, which kept the model picker popover from closing on selection
- is_model_downloaded now verifies config, preprocessor config, and real
weight files instead of trusting an offline snapshot lookup, so a partial
download left by an aborted fetch shows the Download button instead of
failing to load
- Removed whisper.cpp mentions from user-facing text: the ready status
shows Loaded instead of the runtime name, picker rows show the source
repository, and runtime error messages say local transcription runtime
Verified with automated browser sessions and live API checks: selection
closes the picker with no page errors, persisted settings hydrate on
reload, a stale partial snapshot triggers download then loads on MPS and
transcribes, and curated models download from the unslothai repos. 88
backend STT tests, typecheck, lint, i18n parity, and build pass.
* Skip the duplicate source line for custom models in the STT picker
A custom repository's display name is its id, so search results and the
appended current selection rendered the same string twice. The source
line now only renders when it differs from the name; curated rows keep
their name, unslothai source repository, and download size.
* Verify every shard of a sharded checkpoint in the downloaded check
A snapshot holding one of N shards (or a corrupt shard index) passed the
downloaded check and then failed at load. When model.safetensors.index.json
exists, every shard in its weight map must now be present. Found by
simulation; covered by a regression test.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Rename stale _starting references in the pump resilience tests
The startup flag on TrainingBackend was renamed to _spawn_in_progress but
two tests added alongside it still asserted on the old name, failing the
Python 3.11 to 3.13 CI jobs.
* Make the selected model row clearly highlighted in the STT picker
The current selection was a faint background tint. It now uses the accent
background with a medium weight name. Two line rows use a small corner
radius; single line custom repo rows keep the pill shape.
* Address review feedback on STT snapshot checks, VRAM release, and dictation UX
Verify snapshot completeness in the load preflight so a partial download
fails before the audio is decoded, for curated and custom repos alike.
Drop the failed accelerator traceback before the CPU retry so the cache
clear can actually release that memory. Keep unloading the GGUF sidecar
after cancelling an in-flight Transformers load; both engines can hold
memory at once. Allow Auto language with English-only .en checkpoints,
matching the backend which sends no forced language. Keep the discard
button usable while a transcription is pending so a slow or hung request
cannot trap the composer in dictation mode. Stop linking Compare and
settings test dictations to the unrelated active single chat thread.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Move the CPU retry out of the exception handler
On Python 3.10 the interpreter exception state keeps its own reference
to the traceback, so dropping it from the caught exception was not
enough to release the failed accelerator load during the retry. Leaving
the handler before clearing the cache works on every supported version.
* Address review feedback on session handoff, chat pinning, and server lifetime
Starting a dictation from a second entry point now cancels the session
it replaces, so the old recording cannot keep the microphone open or
save a transcript with no discard button pointing at it. The linked
chat is pinned when recording starts, so switching threads while a
transcription finalizes cannot relink the transcript to the newly
opened chat. whisper-server is now bound to Studio's lifetime like the
other long-lived children: PDEATHSIG on Linux, the parent job object on
Windows, and pid adoption so the shutdown sweep reaps it; before this
it survived a Ctrl+C exit as an orphan still holding the model.
* Remove the dictation mic test from Voice settings
The composer dictate button covers the same check, so the test row, its
transcript panel, the unsupported fallback row, and their strings and
search entry are gone.
* Studio STT: gate GGUF whisper-server on training and fix dictation retry and dictionary edits
GGUF (whisper.cpp) sidecar:
- Launch whisper-server with --no-gpu while training is active, mirroring the Transformers sidecar's CPU device choice, so a mid-training dictation cannot reclaim the VRAM training just freed.
- Report is_loading() during whisper-server startup so training VRAM admission accounts for the accelerator memory it is about to bind.
- Require PyAV in is_available() so /audio/stt/status reports the engine unavailable when uploads cannot be decoded, instead of loading fine and then 501ing at transcription.
- Reject a missing model before decoding audio, matching the Transformers download preflight.
Voice settings:
- The download Retry button now restarts the download; the sidecar error is sticky until a new start(), so re-polling alone never cleared it.
Dictation dictionary:
- Tabbing from an emptied entry to its remove button no longer commit-splices the row first, which shifted indices and deleted the wrong entry.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio STT: fix curated GGUF whisper filenames to match hosted repos
The unslothai/whisper-*-GGUF repos host the checkpoint as whisper-<id>.bin,
not ggml-<id>.bin, so every curated dictation download and cached-path
lookup 404'd and the whisper.cpp engine could never load a model. Point
GGML_STT_MODELS at the real filenames and guard the naming with a test.
* Studio STT: validate a custom dictation repo before downloading it
The Transformers STT engine accepts an arbitrary owner/model repo, but the
download route handed it straight to snapshot_download, pulling a possibly large
non-Whisper repository into the shared HF cache. Confirm the repo is a Whisper
checkpoint first with the existing metadata-only validate_remote_model (no
weights); curated ids short-circuit and the GGUF engine (curated-only) is
unaffected. A non-Whisper repo now 422s before any download.
* Studio STT: preempt a still-loading GGUF server for training admission
A whisper-server still in its startup window binds accelerator memory but has no
loaded_model yet, so training admission could miss it and launch into an OOM.
Make the GGUF startup cancellable (cancel_pending_load signals an abort event and
terminates the starting process without the load lock; _wait_for_server observes
it and raises SttLoadCancelledError; wait_for_load_to_settle blocks on the lock
until the killed server is reaped), and always fold the GGUF sidecar into the
resident-STT summary so a resident Transformers model cannot mask a loading GGUF
server. free_stt_model_for_training now cancels an in-flight load and waits for it
to settle before training claims the memory.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio STT: fall back to Transformers when whisper-server is absent
A curated dictation model (including the default small) hard-pinned the GGUF
engine, but standard installs do not ship whisper-server, so every recording
501'd instead of using the Transformers engine that serves the same checkpoint
-- the GGUF sidecar's own documented contract. Add _resolve_serving_stt_engine:
a GGUF request for a curated id (the only ids GGUF accepts, all Transformers-
servable) downgrades to Transformers when whisper-server is unavailable, applied
consistently to download, load and transcribe (not unload, which targets a
specific engine). The Voice tab likewise falls back to the Transformers status so
the model is not shown unavailable and download is not blocked.
* Studio STT: hide custom Whisper caches from the legacy model pickers
The legacy /cached-models (and /cached-gguf) routes called is_hidden_model with
only the owner/model id, which cannot reach the config-based Whisper check, so a
downloaded custom (non-curated) Whisper checkpoint was still offered as a chat
model. Pass the cached snapshot path so _path_is_whisper_model inspects the repo
config and hides it, matching the discovery route.
* Studio STT: hide GGUF dictation repos, lock-free status, unload fallback, split training eviction
- Hide the curated GGUF dictation repos (unslothai/whisper-*-GGUF) from the chat
model inventory and pickers, backend and frontend. Only their Transformers
safetensors companions were hidden; the GGUF repos use a different org and a
-GGUF suffix and carry a raw .bin with no whisper config.json, so they leaked
into chat pickers.
- Make the GGUF sidecar loaded_model/device accessors lock-free, mirroring the
Transformers sidecar. transcribe() holds self._lock across the whole inference
call, so /audio/stt status polls and training admission previously blocked
behind an in-flight transcription.
- stt_unload resolves through the serving resolver: a "gguf" pick on a host
without whisper-server is served by the Transformers fallback, so unload must
target that engine or the resident model is never freed. Unload also attempts
every engine even if one raises, so a failure freeing one backend no longer
skips the other.
- free_stt_model_for_training frees the Transformers and GGUF sidecars under
independent exception boundaries so a failure unloading one no longer skips
the other before training claims the memory.
Adds tests/test_stt_review_fixes.py covering all four.
* Studio STT: resolve Auto dictation language for the model engine + snapshot process liveness
- The model dictation adapter sent the raw setting (the literal "auto") to the
backend, while the browser engine resolves Auto via resolveDictationLanguage.
A batch of non-English voice notes came back mostly English on Auto. Add
resolveModelDictationLanguage: only the literal "auto" is resolved to a
concrete locale, gated so it becomes a language the model AND Whisper can
honor (mirroring the backend's known-whisper-languages set); an explicit
language, or a locale Whisper cannot honor, stays unchanged/auto-detect. Wire
it into both adapter call sites.
- GgmlSttSidecar._process_alive() read self._process twice; a concurrent
unload() nulls it under the lock while loaded_model/device read lock-free, so
a null between the two reads called None.poll(). Snapshot once. Adds a
deterministic regression test.
* studio: tighten comments and docstrings in the dictation modules
* studio: harden dictation model downloads, GGML readiness, and recording paths
Address review findings on the STT dictation feature:
- build_whisper_cpp.sh refuses to delete a whisper.cpp tree under a custom
Studio home unless it carries the Studio ownership marker, matching the
setup.sh policy, and marks trees it creates
- _snapshot_is_complete validates every shard of a sharded PyTorch
(pytorch_model.bin.index.json) checkpoint like the safetensors path, and
requires tokenizer assets (tokenizer.json or vocab.json + merges.txt)
- custom-repo downloads pin the revision resolved at validation time and
restrict snapshot_download to the model/tokenizer/config/preprocessor file
classes Studio loads
- the GGML sidecar holds its port reservation until just before spawning
whisper-server and only accepts readiness from a responder that both looks
like whisper.cpp's server and belongs to the still-running managed child,
probing twice, so mic audio cannot be posted to a foreign local process
- the recording adapter transcribes every non-empty segment; the RMS meter
only shapes segment boundaries and can no longer discard quiet speech
- Compare-pane dictation can cancel a pending transcription on second click,
with the button relabeled while finalizing
- localStorage quota recovery halves the dictation history until the save
fits, so small histories shrink too
- the System default TTS voice resolves to the platform default voice
- new dictation UI imports go through the chat and hub feature barrels
Regression tests cover the build-script gate, sharded PyTorch and tokenizer
completeness, revision pinning and allow patterns, and the whisper-server
readiness probe.
* Fix STT download and voice picker follow-ups
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add dictation button regression coverage
* Studio: prebuilt whisper.cpp via the shared llama.cpp install core, slim bundles paired to the llama prebuilt (#7294)
* Studio STT: add prebuilt whisper.cpp (whisper-server) installer
New install_whisper_prebuilt.py downloads a per-platform whisper-server
bundle published by the unslothai/whisper.cpp prebuilt CI into the managed
whisper.cpp dir (build/bin/whisper-server) so local dictation needs no
compiler. Mirrors install_node_prebuilt.py / install_llama_prebuilt.py:
host + backend detection, sha256 pins (whisper_prebuilt_pins.json) as the
trust anchor, staging + install lock + atomic swap, traversal-safe extract,
co-located shared libs (RUNPATH=$ORIGIN), an UNSLOTH_WHISPER_PREBUILT_INFO.json
marker with idempotent "already matches", and exit codes 0/1/2/3. Not wired
into setup yet; the pins ship empty so every asset fails closed until the
first fork release is published and its digests are reviewed in.
* Studio STT: install prebuilt whisper.cpp during setup and update
Add a fail-open whisper.cpp block to setup.sh after the llama.cpp section so
`unsloth studio update` (and a fresh install) fetch the prebuilt whisper-server
into the managed whisper.cpp dir the sidecar discovers. It skips a user-set
WHISPER_SERVER_PATH/UNSLOTH_WHISPER_CPP_PATH, honors UNSLOTH_SKIP_WHISPER_INSTALL,
forwards the resolved ROCm gfx, and never aborts setup: a busy install keeps the
existing runtime, and an unavailable prebuilt stays quiet (source build is opt-in
via UNSLOTH_WHISPER_FORCE_COMPILE) since Transformers STT and browser dictation
remain. Register UNSLOTH_WHISPER_PREBUILT_INFO.json as Studio-owned evidence.
* Studio STT: harden whisper-server child env + WSL ROCm detection
- Sidecar spawns whisper-server with a scrubbed child env that prepends the
binary dir (co-located GPU libs) to the loader path, and on WSL2 ROCm loads
the system HIP first (HSA_ENABLE_DXG_DETECTION=1) so a bundle's bare-metal HIP
does not segfault on /dev/dxg. Secret-bearing vars are dropped from the child.
- find_whisper_server_binary now requires an executable, not just a file.
- Installer rocm probe passes HSA_ENABLE_DXG_DETECTION and falls back to
/opt/rocm/bin/rocminfo so a WSL ROCm host is not misdetected as CPU-only;
gfx parsing skips the gfx000 CPU agent and generic ISA lines.
- Tests for the child env (secret scrub, lib dir, WSL HIP precedence), the
executable check, and the WSL rocm detection.
* Studio STT: in-app whisper.cpp prebuilt update stack + ship pins in the wheel
Mirror the llama.cpp update stack for the whisper.cpp prebuilt so Studio can
detect and install a newer whisper-server release from inside the app:
- backend/utils/whisper_cpp_freshness.py: read UNSLOTH_WHISPER_PREBUILT_INFO.json
and compare the installed release against the newest unslothai/whisper.cpp
release. Whisper tags are v<upstream>-unsloth.<N>, so is_behind compares a
(major, minor, patch, serial) key with a strict downgrade guard; 24h cache;
fail-open.
- backend/utils/whisper_cpp_update.py: run install_whisper_prebuilt.py to fetch
and atomically swap the newest bundle, unloading the warm GGUF sidecar first.
- backend/routes/whisper.py mounted at /api/whisper (update-status + update).
- pyproject: add whisper_prebuilt_pins.json to studio package-data so the
installer's trust anchor ships in the wheel (it is a data file, not a .py
module, so package discovery alone does not include it; node_prebuilt_pins.json
is listed for the same reason). Without this a pip-installed wheel had no pins
and the prebuilt install aborted to Transformers STT.
Adds test_whisper_cpp_freshness.py (version parser, is_behind matrix + downgrade
guard, marker layouts, stale decision, fail-open).
* Studio STT: verify whisper prebuilts via the release checksum index, like llama.cpp
Re-align the whisper.cpp prebuilt installer to install_llama_prebuilt.py's trust
model: instead of a committed whisper_prebuilt_pins.json, verify every download
against the release's own whisper-prebuilt-sha256.json checksum index, fetched
from the same GitHub release.
- parse_release_checksums / fetch_release_checksums / expected_sha256_for replace
the pins layer. The index is validated for schema/component and that its
release_tag matches the resolved release; an asset absent from it, a release
that does not publish it, or a manifest sha256 that disagrees with it all fail
closed to a source build.
- resolve_release_tag now resolves the newest published release at runtime (or an
explicit --published-release-tag), matching llama and the freshness check;
removed the pinned-default and the UNSLOTH_WHISPER_ALLOW_UNVERIFIED opt-in.
- Delete studio/whisper_prebuilt_pins.json and drop its pyproject package-data
entry (nothing to ship now, same as llama which has no committed pins).
- Adds test_install_whisper_prebuilt_checksums.py (index parser, fail-closed on
uncovered asset, tampered-manifest guard, newest-release resolution).
This is a same-origin checksum (integrity, not authenticity), identical to the
llama.cpp installer; pair releases with GitHub artifact attestations for provenance.
* Resolve whisper prebuilt release via the download host (no GitHub API)
Mirror install_llama_prebuilt.py's fast path: resolve the release tag from
the releases/latest redirect and fetch the manifest + checksum index from
constructed releases/download URLs, so the common install path makes zero
api.github.com calls (unauthenticated api.github.com is capped at 60 req/hour
per IP; the download host is not). Fall back to the GitHub API only on a 404,
malformed asset, or tag mismatch.
* Studio STT: coverage-aware whisper prebuilt selection via a shared core
whisper's select_artifact returned the first os/arch/backend manifest match and
ignored the SM-coverage fields the release manifest already carries, so a
Blackwell B200 (sm_100) was served cuda12-legacy (sms 50-61) -- runnable only via
forward PTX JIT. install_llama_prebuilt.py on the same host correctly picks
cuda13-newer.
Extract the coverage-aware selection into a shared, component-agnostic core under
studio/backend/utils/prebuilt/ (selection + GPU host-capability detection), lifted
from llama's linux_cuda_choice_from_release / _artifact_covers_sms / _sm_range and
generalised over a normalised artifact. whisper's HostInfo now records the GPU
compute caps + driver CUDA version (honoring CUDA_VISIBLE_DEVICES), and
select_artifact routes CUDA/ROCm through the shared selector: every visible SM
must be covered, the tightest-covering profile wins (Blackwell-aware runtime-line
ordering), ROCm matches the gfx target exactly, and an uncovered GPU falls back to
the CPU bundle. CPU/Metal/Vulkan keep first-match. The resolver JSON, exit codes,
and "already matches" contract are unchanged.
On the B200 the installer now resolves cuda13-newer, matching llama.
* Studio STT: gate whisper CUDA selection on the on-disk runtime, like llama
The prebuilt CUDA bundles are dynamically linked and intentionally do NOT ship
libcudart/libcublas -- they load the same runtime the host already has. So the
driver's advertised CUDA version is only an upper bound: a cuda13 bundle still
needs cuda13 runtime libraries present on disk. Port llama's on-disk runtime
scan (detected_linux_runtime_lines / detected_windows_runtime_lines) into the
shared core and intersect it with the driver-compatible lines in
select_cuda_attempts. A host with a cuda13 driver but only cuda12 runtime (e.g.
torch-cuda12) now correctly gets a cuda12 bundle instead of an unloadable cuda13
one; a host with no CUDA runtime at all falls back to CPU.
Fixes a glob bug in the port (any(Path(d).glob(p) for d in dirs) tests generator
truthiness, not a match) that made every major report present; add a real
filesystem test that exercises the scan.
* studio: harden shared prebuilt core to full llama parity
Apply the review findings on the shared coverage-aware prebuilt-consumer
core so whisper.cpp selection is exactly equivalent to the llama.cpp path.
hosts.py: port llama's CUDA_VISIBLE_DEVICES handling. A GPU hidden by an
index/UUID selector now reports has_usable_nvidia False instead of staying
usable, via supports_explicit_visible_device_matching plus the physical /
explicit-match branches, and _select_visible_rows now matches rows the way
llama does (index or UUID, gpu- prefix optional) and skips unmatched tokens
rather than keeping all rows. Adds the Linux /proc/driver/nvidia/gpus
fallback and has_physical_nvidia. Adds parse_macos_version.
runtime_libs.py: the Linux on-disk scan now requires the exact libcudart /
libcublas SONAME (libcudart.so.13), not a libcudart.so.13* glob, so a bare
versioned file without the SONAME symlink no longer counts as loadable.
Hardens the ldconfig parse against an empty left-hand side.
selection.py: fix the Blackwell/torch reordering so it keys on the covering
runtime lines (falls through to the torch preference when the covering lines
were filtered out), matching linux_cuda_choice_from_release. Corrects the
compatible_runtime_lines_for_driver docstring: the bundles do not ship the
CUDA runtime, so the driver version is only an upper bound and the caller
must intersect with the on-disk scan.
install_whisper_prebuilt.py: enforce a macOS artifact's min_os (new
HostInfo.macos_version) so a bundle that cannot load on the host OS version
is dropped. Keep resolver stdout to only the JSON line by leaving logs on
stderr in --resolve-prebuilt mode, and map an unexpected probe failure to
prebuilt_available False instead of a traceback.
Tests: new host-probe suite for the visible-device logic, exact-SONAME
runtime-scan cases, macOS min_os filtering, resolver stdout-only-JSON,
exit-code mapping, and the repo key.
* studio: fix whisper prebuilt selection + launch parity gaps from review
A parallel review surfaced integration defects where the whisper path could
select or launch a bundle that cannot run on a concrete host. Each is fixed to
match install_llama_prebuilt.py.
macOS min_os: the manifest labels macOS requirements as macos-<version>
(e.g. macos-14.0), which the version parser could not read, so the guard was a
no-op and a macOS-13 host would install the macos-14 Metal bundle. Strip the
platform prefix before parsing.
ROCm gfx detection: _detect_rocm_gfx returned the first gfx token and ignored
HIP_VISIBLE_DEVICES / ROCR_VISIBLE_DEVICES / CUDA_VISIBLE_DEVICES. Since exact
ROCm matching treats that token as the active GPU, a mixed APU + dGPU host
(gfx1151 + gfx1100) with HIP_VISIBLE_DEVICES=1 installed the wrong archive. Route
through a shared pick_rocm_gfx_target (lifted from llama) that parses per-GPU
sections and honors the visibility vars (empty / -1 -> no AMD GPU).
--rocm-gfx override: recording the arch without setting has_rocm left the host on
its CUDA/CPU path so the ROCm bundle was never picked. --rocm-gfx now implies
has_rocm and clears NVIDIA state, like llama's _apply_host_overrides.
CUDA launch env: a CUDA bundle ships the ggml CUDA backend but not
libcudart/libcublas, and the sidecar launch env exposed only the bundle dir, so
on a host whose CUDA runtime lives only in the PyTorch wheels the selection would
gate cuda usable but the server could not load it. Add the CUDA-from-PyTorch
runtime dirs to the child loader path for CUDA bundles (bundle dir still first),
mirroring binary_env.
Also normalize a manifest artifact's supported_sms defensively (parity with
llama's parser) and document that blackwell_min_toolkit_for_caps is retained for
the Phase B llama Windows path.
Not changed (verified parity, not defects): Linux/Windows min_os is enforced
nowhere in llama (macOS only); the resolver is optimistic about the checksum
index and the install path verifies.
* studio: tighten prebuilt-core code comments
* studio: lift shared prebuilt installer core out of the whisper installer
* studio: reuse the llama.cpp prebuilt installer machinery for whisper
* studio: unify llama and whisper prebuilt installers on a shared descriptor core
* studio: consolidate prebuilt installer tests into the shared core suite
Grow tests/studio/install/test_prebuilt_core.py from 62 to 164 tests so every
component-agnostic behavior runs against both descriptors: the full seven
profile CUDA release matrix (multi-GPU, on-disk runtime gating, shuffle
stability, missing SM metadata, dotted SM normalization, no-driver fallback
policy), the ROCm gfx family matrix, macOS min_os gating and its helper,
backend resolution incl. cpu-fallback precedence and Intel-mac auto detect,
checksum-index non-object and plain-lookup cases, the tar symlink/hardlink
extraction guards moved from the llama suite, and the compute-cap, visible
device, runtime-line and Blackwell helper value tables moved verbatim from
the llama characterization suites.
Delete only tests whose exact behavior the master now asserts for the same
component: 40 pure-alias helper cases in test_selection_logic.py (replaced by
value-identical master tables plus an alias-identity pin), 6 extraction moves
and the master-absorbed zip-symlink case in the llama logic suite, 3 routing
twins in test_rocm_support.py already pinned byte-for-byte in
test_selection_logic.py, the 2 Blackwell helper tables in the backend resolve
suite, 28 whisper logic tests and 10 whisper checksum tests re-asserted by
the master whisper parameterization. Wrapper wiring pins, the llama release
plan dialect, fingerprints and every llama-only behavior stay untouched.
* studio: dedupe sidecar and update helpers into the backend prebuilt package
* studio: chain whisper.cpp prebuilt updates onto the llama.cpp update flow
* studio: consume paired slim whisper prebuilts via the llama ggml runtime
* studio: serve every whisper backend from slim prebuilts
* studio: drop the whisper fat per-accelerator selection chain
unslothai/whisper.cpp releases are slim-only from v1.9.1-unsloth.2: one
ggml-less bundle per os/arch, paired to the llama.cpp prebuilt that provides
every ggml backend. Delete the whisper-side fat CUDA/ROCm/metal/vulkan
selection glue; keep slim selection + pairing, link_ggml_runtime, and one
legacy shape, the published fat CPU bundle of an explicitly pinned pre-slim
release. Exit 2 now reads as prebuilt unavailable (whisper never source
builds); setup already treats it that way.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Wire libomp runtime DLL alongside ggml in slim whisper installs
llama's clang-built windows-arm64 ggml-base.dll imports
libomp140.aarch64.dll, shipped in the llama bundle but not a system DLL.
Without it next to whisper-server.exe the loader fails with
STATUS_DLL_NOT_FOUND before main. MSVC x64 links vcomp140.dll from
System32 and Linux ggml uses system libgomp.so.1, so only windows-arm64
was affected. The empty-runtime guard still requires a real ggml
library; libomp alone is not a pairing.
* studio: drop whisper-side fat-selection support structure
Slim whisper bundles are selected per os/arch only; all accelerator
capability comes from the installed llama.cpp prebuilt, whose installer
already did the coverage-aware selection. Remove the machinery that only
existed to pick among fat per-accelerator whisper bundles:
- prebuilt_core: delete the generic CUDA/ROCm coverage selection
(select_cuda_artifact, select_rocm_artifact, ArtifactView adapters,
detected_cuda_runtime_lines, the exact-SONAME linux probe) that no
shipped component routes through; llama keeps its own selection chain
and whisper shadows select_artifact with the slim-only version.
select_artifact is now a plain os/arch/backend first-match.
- install_whisper_prebuilt: drop the HostInfo CUDA fields
(compute_caps, driver_cuda_version, torch_runtime_line) and the torch
runtime probe that populated them; nothing reachable reads them, and
the resolver payload sources runtime_line from the artifact.
- whisper_cpp_update: delete the standalone start_update job worker;
whisper applies only run as the chained phase of the combined
llama+whisper update. The status payload keeps its job field (idle).
- routes/whisper: drop the progress logger that could never fire.
- tests: remove tests of the deleted paths and tests duplicating the
descriptor-parameterized core suite or the llama freshness suite.
Contracts unchanged: resolver JSON keys, exit codes, marker fields,
pairing logs, and the pinned pre-slim fat CPU escape hatch.
* Address review feedback on the whisper prebuilt update and install paths
- Pin the chained whisper phase to the release the freshness check
offered, so the download-host latest pointer cannot reinstall an
older build in a loop
- Wire the whisper prebuilt install into setup.ps1 (Windows setup
previously skipped it entirely)
- Treat a non-executable server or missing wired ggml libraries as a
broken install instead of reporting already matches
- Keep whisper sidecar reloads out of the job-level reload flag and
resync chat state after a partial chained update that unloaded llama
- Repoint home and profile vars for the whisper-server subprocess at a
managed scratch dir and drop credential-store pointers
- Clear the prebuilt marker before the opt-in source build overwrite
- Write the prebuilt marker with explicit utf-8 encoding
* Tighten comments in the whisper prebuilt consumer
* Harden the Windows whisper setup phase and the chained update edges
- setup.ps1: honor WHISPER_SERVER_PATH / UNSLOTH_WHISPER_CPP_PATH /
UNSLOTH_SKIP_WHISPER_INSTALL, run the custom-home ownership guard
before the atomic install, and forward the release-tag pin and ROCm
hints like setup.sh
- sidecar: a cpu-selected install launches whisper-server with --no-gpu
(slim wiring links every llama backend, so the flag is what keeps a
deliberate CPU choice off the GPU)
- chained update: leave whisper unpinned on macOS (the llama phase can
walk back there, and a newest-tag pin could be an impossible pairing
on every retry) and treat installer exit 2 as kept-existing-runtime
instead of failing the combined job
- job.to_tag now comes only from the llama phase, so a whisper-only
round cannot report a llama update that never ran
* Fix slim whisper runtime follow-ups
* Address remaining whisper update reviews
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address remaining prebuilt update reviews
* Fix remaining chained update reviews
* Fix remaining whisper runtime review edges
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: danielhanchen <unslothai@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: oobabooga <112222186+oobabooga@users.noreply.github.com>
---------
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Unsloth <michaelhan@Michaels-MacBook-Pro.local>
Co-authored-by: oobabooga <112222186+oobabooga@users.noreply.github.com>
Adds a configurable Hugging Face model download cache location to Unsloth Studio, selectable from Settings, with per-cache download manifests, scoped deletion, and read-only inventory of previously selected caches.
* Studio: drive UI font size through a typography scale, not the root font size
Follow up to #7355. The preference now writes --ui-font-scale
(selected / 16) and a data-ui-font-size attribute on the root instead
of mutating the root font size, and the applier clears any stale inline
root font-size left by older builds. Because the rem base never moves,
every layout-only rem-to-px conversion from #7355 is reverted to its
original form: the spacing, radius and container tokens, sidebar and
thread widths, grid tracks, calc margins and hub.css dimensions match
pre-#7355 main again, which also restores rem-based accessibility
scaling for users with a larger browser default font size.
Typography scales through tokens in index.css, all exact at 16px:
- The named Tailwind sizes (--text-xs through --text-4xl) multiply
their defaults by the scale, so standard utilities scale
- One token per design px size (--text-ui-8 ... --text-ui-34) replaces
every arbitrary text-[Npx] class; leading-ui-* mirrors the exact
line heights and the numeric --leading-3..10 scale as well
- CSS font-size and line-height declarations multiply by the scale
- Chart labels scale through a .recharts-text rule; streamdown and
react-flow px text is re-based via scaled overrides; KaTeX's 1px
layout trick stays fixed by design
- The logo lockups keep their half-rate behavior via the scale var
- The explicit Code font size remains unmultiplied
Keeps the #7355 behavior fixes: color chip min width, voice select
min/max widths, and the select and dropdown menus scrolling an inner
viewport so their corners stay rounded. The whitespace-password and
IME rename guards that merged alongside are preserved.
* Studio: contract and Playwright coverage for the UI font size scale
test_ui_font_scale_contract.py pins the mechanism (scale var written,
root font size never mutated, tokens scaled, code font size not
multiplied, the Radix select viewport owning scroll state) and guards
against new raw pixel typography, with a documented allowlist for the
recharts fontSize props covered by the stylesheet override and the
offscreen clipboard textarea.
playwright_ui_font_scale.py drives the real appearance controls: root
font size fixed at 12/16/20, text and line height scale by size/16,
sidebar width invariant, explicit code font size stays fixed, an
overflowing dictation select scrolls its Radix viewport by keyboard
and wheel, and the default restores exactly. Wired into the UI smoke
workflow against the second studio boot.
The thinking-compact and descender contracts move back to the rem and
token forms now that layout values no longer need px pinning.
The API key and Connections form reused grid tracks that only collapse at the
viewport width, so inside the narrower settings pane the provider selector and
API key input were clipped. Switch the form to container queries so it responds
to the pane width and stacks to a single column when narrow. Other settings
tabs are unaffected.
* fix(dataprep): don't emit a degenerate chunk for empty text
smart_chunk_text feeds empty / whitespace-only text (which tokenizes to
zero tokens) into the single-chunk branch, which unconditionally returns
one chunk. That yields a lone-EOS "document" (input_ids=[eos]) or, when
the tokenizer has no eos_token_id, a zero-length input_ids=[] — an
invalid sample that breaks a downstream collator/trainer.
load_from_file already guards against this with a ValueError, but
chunk_text, smart_chunk_text and load_from_files do not, so batch-loading
a directory that contains an empty file silently injects garbage rows.
Return no chunks when the tokenized text is empty, so empty inputs
contribute nothing instead of a degenerate sample. load_from_file keeps
its explicit ValueError (its guard runs first).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Guard empty/whitespace text before tokenizing in raw_text
Real BPE/SentencePiece tokenizers emit tokens for spaces and newlines, so the len(tokens)==0 check let whitespace-only documents through as a degenerate lone-EOS sample. Guard on text.strip() before tokenizing (mirroring load_from_file), and raise in load_from_files when every file is empty so return_tokenized mode never falls back to a text-column dataset. Test now uses a whitespace-preserving tokenizer and covers both return_tokenized modes.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
The rename input only ignored the composition-confirming Enter, so on WebKit an
Escape that cancels an IME candidate also cancelled the rename. Move the
composition guard ahead of the key branch so both Enter and Escape are ignored
while a CJK candidate is being composed.
* Studio: make UI font size scale all text without moving layout
The UI font size setting changes the root rem base, so only rem sized
text reacted. Hundreds of px text classes, px font sizes in CSS, and
chart labels stayed fixed, while rem based padding, widths and radii
wrongly grew.
Convert all text sizes to rem so every font follows the setting, and
pin spacing, radius, container widths, sidebar and thread widths to px
so layout no longer follows the rem base. Library styles (streamdown,
react-flow) are re-based via overrides. All conversions are exact at
the default 16px root, so the default rendering is unchanged.
* Studio: keep logo at fixed size and fit tight controls at large UI fonts
The logo lockups (sidebar wordmark with beta badge, onboarding wizard)
are branding and now keep px sizes at any UI font size.
Two controls clipped their text at the largest setting: the appearance
color chips (fixed w-24) and the voice tab selects (fixed w-56). Both
use min widths now, so they keep the default look at 16px and only
grow when the text needs the room.
* Studio: keep dropdown corners rounded when the menu scrolls
A scrolling dropdown lost its rounded corners on the scrollbar side:
WebKit paints the surface square when the rounded element itself hosts
the scrollbar, which shows up in the desktop app whenever a menu
overflows, for example at larger UI font sizes.
Dropdown menu and select content now clip with overflow hidden and
scroll an inner viewport instead. The surface padding insets the
scrollbar clear of the curve, so corners stay rounded in every engine.
Submenus are unaffected since sub content is portaled.
* Studio: scale the logo lockups at half the UI font size rate
Rather than pinning the logo, the sidebar lockup (sticker, wordmark,
beta badge) and the onboarding lockup now follow the UI font size at
half the rate of the change: size = base + (root - 16px) / 2, written
as calc((base - 8)px + 0.5rem). A 4px font size change moves the logo
by 2px, and the default 16px root renders the exact base sizes.
* Studio: address review feedback on leading, grid tracks and select scrolling
Numeric leading utilities (leading-3 through leading-10) derive from
--spacing, so pinning spacing to px also froze their line-heights while
the paired text sizes now scale. Define them as rem theme tokens so
line-height follows the UI font size again; values are identical at the
16px default.
Convert the grid tracks the rem-to-px codemod missed (rem followed by
an underscore escaped the word boundary): the response details label
column and the on-device folder rows.
Make the Radix select viewport the bounded scroller instead of a
wrapper div, so Radix's scroll handling and the browser scroll the same
element. Restore the app's thin scrollbar with an inline style, which
beats the scrollbar hiding stylesheet Radix injects at runtime.
* Studio: cap voice select widths and update CI contracts
* Studio: reject whitespace-only passwords
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: reject any whitespace in passwords
* Studio: surface whitespace error in setup form, isolate auth test import
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* installer: fix Linux AMD GPU detection + actionable ROCm-less warning
The rocminfo/amd-smi-less fallback in _has_amd_rocm_gpu keyed on a
/gpu_id/ line inside each KFD node's properties file, but gpu_id is a
separate sibling sysfs file and never appears in properties. The guard
never matched, so the fallback missed every AMD host without ROCm
tooling (e.g. a fresh CachyOS/Arch box) and reported 'no GPU detected'
despite vendor_id 4098 being present in the KFD topology.
Detect via vendor_id == 4098 directly: the KFD CPU node reports
vendor_id 0, so any 4098 node is an AMD GPU, while NVIDIA's KFD nodes
report 4318 and stay excluded.
Also rework the 'ROCm version could not be determined' warning into an
actionable message (install the ROCm/HIP SDK; Arch/CachyOS:
rocm-hip-sdk) so ROCm-less users know the concrete next step instead of
silently landing on CPU-only PyTorch.
* tests: replace the FNR==1 KFD invariant with the per-line vendor_id check
The FNR==1 reset guarded the old paired gpu_id+vendor_id awk against
cross-node state leakage. The new detection is a single atomic
vendor_id==4098 line condition, so there is no per-node state to reset;
assert the new invariant instead (single-line vendor match, and no
/gpu_id/ pattern, which never matched inside properties).
tests/studio/install/test_rocm_support.py: 344 passed, 2 skipped.
* installer: mirror the KFD vendor_id fix in setup.sh + honest CPU-fallback summary
Codex P2 follow-ups:
- studio/setup.sh carried the same dead gpu_id-inside-properties awk, so a
host install.sh now routes to ROCm still failed setup's independent AMD
re-probe and got a CPU llama.cpp. Use the same per-line vendor_id 4098
check.
- When the AMD GPU is detected but the torch index stays CPU, the summary
printed the old false diagnosis (gpu none / "No GPU detected"). Gate both
on _has_amd_rocm_gpu and say what actually happened: AMD GPU present, no
usable ROCm, CPU fallback.
- Structure test asserting setup.sh's KFD awk stays in sync with install.sh.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Keep KFD-only AMD hosts on the CPU fallback (Codex P2s)
The KFD-topology fix makes _has_amd_rocm_gpu / _setup_amd_detected true on hosts that expose an AMD GPU to the kernel but ship no rocminfo/amd-smi. Detection alone does not mean ROCm is usable or that the gfx arch is known, and two downstream paths wrongly assumed it did:
- studio/setup.sh forwarded --has-rocm with no gfx, so install_llama_prebuilt found no per-gfx bundle and dropped to a HIP source build (slow, or a hard failure without build deps) instead of the CPU prebuilt these hosts used to get. Now --has-rocm is forwarded for a gfx-unknown host only when hipcc is present; otherwise it keeps the CPU prebuilt.
- install.sh get_torch_index_url selected a generic rocmX.Y index whenever the ROCm version was readable, but the Strix reroute only learns gfx from rocminfo/amd-smi, so a Strix KFD-only host landed on the broken _grouped_mm wheels. Now, when neither rocminfo nor amd-smi is present (gfx unknowable), it stays on CPU with a hint to install them.
Detection and the improved diagnostics are unchanged; only the routing for gfx-unknown KFD-only hosts is made safe. Adds tests for both gates.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Harden KFD-only fallback: probe gfx, accept versioned hipcc (Codex P2s)
Follow-up to the previous commit's two guards:
- install.sh: the KFD-only torch guard tested only 'command -v rocminfo/amd-smi', so a host where those binaries exist but do not enumerate the GPU (gfx unreadable) slipped through and, with hipconfig/rocm-core present, still got a generic rocm index -- breaking Strix. Now it actually reads the gfx (rocminfo, then amd-smi list / static --asic, the same probe the reroute uses) and falls back to CPU whenever the arch is unreadable, not just when the binaries are absent.
- studio/setup.sh: the hipcc gate missed a HIP toolchain installed only under a versioned prefix (/opt/rocm-*/bin/hipcc), which the source build at setup.sh:1663 does support, so such hosts were dropped to the CPU prebuilt unnecessarily. The gate now also accepts /opt/rocm-*/bin/hipcc.
Tests updated to assert the gfx-read (not binary-presence) gate and the versioned hipcc path; full test_rocm_support.py green (347 passed). Verified the gfx probe by execution: rocminfo-with-no-gfx now routes to CPU, amd-smi fallback still resolves gfx.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Honor UNSLOTH_ROCM_GFX_ARCH before the CPU fallback for PR #7314
Seed both the gfx-unknown guard in get_torch_index_url and the Strix reroute
from UNSLOTH_ROCM_GFX_ARCH before probing rocminfo/amd-smi, so a host that
names its arch reaches the correct rocm index instead of being forced to CPU
(or to the generic wheels) when the runtime probes can't enumerate the GPU.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Probe gfx with visibility masks cleared for PR #7314 (Codex P2)
rocminfo/amd-smi honor ROCR/HIP_VISIBLE_DEVICES, so a container that masks the
GPU (e.g. ROCR_VISIBLE_DEVICES=-1) would make the gfx probe read nothing and
force CPU torch, even though the KFD-based AMD detection is env-independent and
hipconfig can still supply the ROCm version. Clear the visibility masks for the
rocminfo/amd-smi arch probe only (the Strix reroute keeps them for per-GPU index
selection), so a masked/container host keeps its ROCm route.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Re-probe gfx unmasked in the Strix reroute when a mask hides all agents for PR #7314 (Codex P2)
* Remove leftover conflict marker from the test merge
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Report an explicit CPU pin instead of a ROCm misdiagnosis for PR #7314 (Codex P3)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Trigger the reroute re-probe on a set-but-empty visibility mask for PR #7314 (subagent review)
* Guard the ROCm version chain against set -e when no source exists for PR #7314 (simulation find)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Preserve the inferred-gfx reroute for KFD-only hosts (Codex P2)
The gfx-unknown CPU guard in get_torch_index_url fired before the
runtime-less reroute could run: with the KFD topology fix,
_has_amd_rocm_gpu is true on KFD-only hosts, so the reroute's
'! _has_amd_rocm_gpu' gate never let _infer_linux_amd_gfx_arch route
them to AMD per-arch wheels, regressing inferable boxes (PCI/cpuinfo/
lspci) from arch-specific PyTorch to CPU-only.
- Factor the override->rocminfo->amd-smi gfx probe (masks cleared)
into _probe_amd_gfx_arch, shared by the guard and the reroute gate
so the two can't disagree on what 'readable' means.
- Reroute gate now also fires when the GPU is detected but the probe
is empty (KFD-only). Deliberate CPU fallbacks (old/unreadable ROCm
version) all had a readable gfx and stay excluded.
- The guard defers to the reroute (no false 'installing CPU-only
PyTorch' promise) only when inference yields a supported family;
otherwise the actionable CPU warning is unchanged.
Executed tests: KFD-only host reroutes to repo.amd.com per-arch wheels
and exports UNSLOTH_ROCM_GFX_ARCH for setup.sh; readable-gfx CPU
fallback stays un-rerouted; undetected-GPU reroute unchanged; the
guard's three inference outcomes covered. Suite: 375 passed, bash -n
clean on both scripts.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix two false diagnostics on the KFD-only paths (Codex P3s)
1. get_torch_index_url: with UNSLOTH_ROCM_GFX_ARCH set on a KFD-only
host that has no ROCm version sources, the no-version endpoint
printed 'falling back to CPU-only PyTorch' even though the reroute
(gated on the override) then installs the per-arch wheels. When the
override maps to a wheel family, defer with an accurate message;
an unmappable override keeps the CPU warning since the reroute
can't route it either.
2. Runtime-less reroute: the KFD-only branch reached the warning
'ROCm runtime not visible (/dev/kfd, rocminfo, amd-smi)' although
/dev/kfd is exactly what detected the GPU. The diagnostic now
distinguishes KFD-visible/tooling-blind hosts from truly
runtime-invisible ones.
Executed tests: supported override defers without the false CPU
warning, unsupported override and readable-gfx no-version hosts keep
it; KFD-only reroute emits the KFD wording, undetected-GPU reroute
keeps the original. Version sources are shimmed so the tests hold on
dev boxes with a real hipconfig. Suite: 376 passed, bash -n clean.
* [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>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Studio: clear composer draft on send
* Studio: verify the Cloudflare link is reachable before printing it
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: wait for tunnel DNS propagation before verifying the public URL
* Studio: bound tunnel DNS wait and health probe by one deadline
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: keep composer draft when overlay send validation fails
* Studio: retry transient DoH failures while waiting for tunnel DNS
* [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>
* fix(install): infer Strix gfx when ROCm runtime is absent
When /dev/kfd and rocminfo are missing on Linux (e.g. Arch/CachyOS Strix
Halo), route to AMD per-arch wheels via cpuinfo/lspci inference instead
of CPU-only PyTorch. Mirrors install.ps1 Windows behavior and fixes
studio update via install_python_stack.py (unslothai#7301).
* Map Radeon 8065S to gfx1151 in the Linux gfx inference (Codex P2)
install.sh _infer_amd_gfx_arch_from_gpu_name missed 8065S, so a Strix Halo host that only exposes 'AMD Radeon 8065S' via lspci (no Ryzen AI Max branding in /proc/cpuinfo) was left on CPU torch. setup.sh and setup.ps1 already list 8065S -> gfx1151. Added it, and widened the cpuinfo regexes (install.sh and install_python_stack.py) from Radeon 80[0-9]0S to 80[0-9][05]S to match the 80X5S naming, consistent with the display-side check already in install.sh. Tests cover the 8065S name and the cpuinfo-only case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Gate the Linux gfx inference out of WSL without the ROCDXG runtime for PR #7305
On WSL /proc/cpuinfo and lspci still see the host APU, so a standalone
'unsloth studio update' could infer gfx1151 and install per-arch ROCm wheels
into a WSL env whose ROCDXG bridge (librocdxg) was never bootstrapped, i.e. one
that cannot expose the GPU. Skip the cpuinfo/lspci inference on WSL unless
librocdxg is present; an explicit UNSLOTH_ROCM_GFX_ARCH override still wins.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address Codex review on PR #7305 (WSL runtime gate, Linux mirror, arch guard)
- install.sh _infer_linux_amd_gfx_arch: skip the cpuinfo/lspci inference on WSL
unless librocdxg is present (the ROCDXG bridge), mirroring the Python fix, so a
WSL box whose ROCm bootstrap was skipped keeps the CPU fallback instead of
installing AMD wheels that cannot reach the GPU. The explicit UNSLOTH_ROCM_GFX_ARCH
override still returns first, so it stays authoritative.
- install.sh: guard the inferred-gfx reroute on x86_64|amd64. ROCm torch wheels are
not published for arm64, so an inferred/overridden gfx no longer pushes an arm64
host to the AMD arch index (get_torch_index_url returns CPU there).
- install_python_stack.py _amd_arch_index_url: honour UNSLOTH_AMD_ROCM_MIRROR on
Linux (the same var install.sh uses) instead of the Windows mirror var, so a
mirrored/air-gapped Linux 'unsloth studio update' reaches the index install.sh
chose. Windows still delegates unchanged; both default to repo.amd.com.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Scan all AMD display controllers in the lspci fallback for PR #7305 (Codex P2)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix(studio): keep inferred AMD wheels from being overwritten
After a successful inferred-gfx install, skip the generic pytorch.org
ROCm reinstall so readable ROCm userland without /dev/kfd cannot undo
the per-arch repair (Codex P1 on #7305). Also merge latest main.
* Only take the inferred-gfx install when the runtime sees no GPU for PR #7305 (Codex P1)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Isolate three updater tests from the host cpuinfo for PR #7305 (Strix dev box leak)
* Gate the reroute on invisible ROCm and forward the inferred gfx to setup.sh for PR #7305 (Codex P2s)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Require AMD PCI display evidence for cpuinfo inference; honor gfx override with visible ROCm for PR #7305 (Codex P2s)
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: LeoBorcherding <borchborchmail@gmail.com>
* Studio: mask AMD GPU pins via ROCR so an unsupported iGPU can't crash llama-server
On a mixed AMD host (e.g. a discrete gfx1102 GPU next to a gfx1103 iGPU)
the bundled rocm-gfx110X llama.cpp build segfaults during HSA device
enumeration on the unsupported iGPU -- before llama-server prints a line,
so every model load fails with a bare signal and empty logs.
The GPU-subset pin masked visibility with HIP_VISIBLE_DEVICES, but HIP
filtering runs only after the HSA runtime has already enumerated (and
crashed on) every agent. Mask the subset via ROCR_VISIBLE_DEVICES (the
ROCr/HSA layer) instead, so a deselected/unsupported GPU is never
enumerated. Exactly one layer is masked (HIP cleared) to avoid the
double-mask reindex that would otherwise drop the child to CPU. The
whole-set tensor-split path and the CPU-only sentinel keep their existing
HIP behavior.
Also stop misreporting the resulting startup segfault as a vision
projector incompatibility: when the text-only mmproj retry also hard-
crashes with a signal, surface a GPU/driver init crash (with the ROCR
hint) instead of blaming the projector.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Tighten _emit_child_gpu_visibility comments for #7272
Comment and docstring only: condense the ROCR-vs-HIP masking rationale from ~22 to ~14 lines and the call-site note from 5 to 3, keeping every technical point (HSA enumeration segfault, physical ids, the -1 sentinel). Logic is unchanged, verified by an AST compare with docstrings stripped and by exercising _emit_child_gpu_visibility against a torch/HIP stub.
* Detect AMD SDK ROCm wheels (hip=None) in _emit_child_gpu_visibility (Codex P2)
The ROCm branch gated only on torch.version.hip, but AMD SDK wheels leave that unset while encoding 'rocm' in __version__ (detect_hardware handles this the same way). On such a wheel the masking was skipped entirely, leaving only CUDA_VISIBLE_DEVICES, so on a mixed AMD box the unsupported deselected iGPU still enumerated and could crash llama-server. Now the branch also treats 'rocm' in torch.__version__ as ROCm, mirroring detect_hardware. Adds tests for the hip=None SDK wheel (ROCR + default paths) and a CUDA guard so the version-string check can't false-positive.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Remap CUDA_VISIBLE_DEVICES to post-ROCR ordinals on prefer_rocr for PR #7272 (Codex P1)
On the prefer_rocr path _emit_child_gpu_visibility set ROCR_VISIBLE_DEVICES to the
physical id and cleared HIP_VISIBLE_DEVICES, but left CUDA_VISIBLE_DEVICES at the
physical id. ROCR re-indexes the visible agents from 0 and, with HIP cleared, HIP
honours CUDA_VISIBLE_DEVICES -- so a non-zero pick (e.g. GPU 1) pointed out of
range, HIP saw 0 devices, and the child fell back to CPU, defeating GPU-picker
selections other than physical GPU 0. Remap CUDA to the post-ROCR ordinals
(0..N-1); GPU 0 is unchanged, the default (HIP) path and the CPU sentinel are
untouched, and non-AMD wheels never enter this branch.
* Detect AMD SDK wheels in _resolve_visible_physical_ids for PR #7272 (Codex P2)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Keep the HIP mask on Windows ROCm in prefer_rocr for PR #7272 (Codex P2)
* Ignore ROCR_VISIBLE_DEVICES in _resolve_visible_physical_ids on Windows for PR #7272 (Codex P2)
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* Preserve inherited ROCR masks in the tensor-split pin for PR #7272 (Codex P2)
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Leo Borcherding <borchborchmail@gmail.com>
* Studio: put Hub above Projects in the sidebar
Swap the two nav rows so Hub sits directly under New Chat, ahead of
Projects. Order only, no behavior change.
* Studio: rename Hub to Models, lowercase New chat
Rename the Hub nav row and its page heading to Models (localized in all
locales). Use sentence case 'New chat' in the English label.
* Studio: fix dataset title and stale Hub tab hints after rename
Show 'Datasets' as the catalog heading in dataset mode, not 'Models'.
Update the download-conflict toasts to point at the Models tab.
* Studio: lighten chat text weight on Linux to match macOS rendering
* Exclude custom interface fonts from the Linux chat weight compensation
* Simplify Linux chat font weight override
* Faster safetensors weight loading on unified-memory (integrated) GPUs
On unified-memory GPUs (AMD APUs / "Strix Halo", NVIDIA GB10 "Spark", Intel
iGPUs) the GPU shares the system memory pool. PyTorch's fast pinned-DMA
host->device path does not recognize the Rust-allocated, mmap-backed buffers
that safetensors hands back, so a direct safetensors GPU load
(`safe_open(..., device=<cuda>)`) drops onto a slow per-tensor copy that, on
unified memory, additionally triggers page-attribute changes and page faults.
Wrap `transformers.modeling_utils.safe_open` so that, when transformers asks it
to load a shard directly onto a CUDA/HIP device, the shard is opened on CPU and
each tensor is `.clone()`-d into a normal torch allocation before `.to(device)`.
This restores the fast DMA path. Data, dtype and final device are unchanged, so
outputs are bit-identical -- only *how* the bytes reach the GPU changes.
Strictly gated to integrated/unified-memory GPUs via the standard `is_integrated`
device property (every visible device must be integrated): a hard no-op on
discrete NVIDIA/AMD GPUs, CPU, XPU and MLX, where the pinned-DMA path already
works. Only intercepts `framework="pt"` CUDA-device targets; CPU / disk-offload
loads are left untouched. Accuracy-neutral, idempotent, opt out with
UNSLOTH_DISABLE_UMA_CLONE_LOAD=1 (force the gate for tests with
UNSLOTH_FORCE_UMA=1/0).
This is the AMD/universal-UMA counterpart to the NVIDIA DGX Spark work in #5945
(which deliberately left the H2D clone-then-move out): gating on `is_integrated`
covers AMD Strix Halo, Intel iGPUs and Spark-class parts alike.
Verified on an AMD Radeon 8060S (gfx1151, Strix Halo) Windows ROCm box with
in-process, ordering-cancelled A/B benchmarks:
- H2D mechanism (safe_open device=0 vs cpu->clone->.to(0)): 2.08x faster
(1.076s -> 0.518s for a 988MB bf16 shard)
- full `from_pretrained`: 1.56x faster (1.552s -> 0.996s), saving 0.555s --
matching the H2D delta exactly
- max|logit diff| stock vs patched == 0.0 (bit-identical), generate + a LoRA
train step both verified
The absolute/relative win grows with bf16/fp16 weight volume (the same trick is
reported as ~2.3-2.75x on NVIDIA GB10 Spark for larger models).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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* fix: evaluate the integrated-GPU gate lazily, not at import (Gemini review)
patch_unified_memory_safetensors_load() called
is_integrated_unified_memory_gpu() at install time, and the gate queries
torch.cuda.get_device_properties() for every visible device -- initializing
the CUDA context during `import unsloth` on every CUDA machine (discrete
included). That (a) breaks fork-based multiprocessing, (b) runs BEFORE
patch_dgx_spark_memory_config can set PYTORCH_CUDA_ALLOC_CONF on Spark,
defeating that patch's expandable_segments config in the very environment
this PR targets, and (c) charges a CUDA context to CPU-only imports.
The gate now runs lazily inside the wrapper, ordered AFTER the
framework/device check so non-CUDA loads never trigger the property query;
a CUDA-target safe_open means the caller is initializing CUDA anyway, and
the gate is lru-cached so it is evaluated once. The wrapper installs
unconditionally (opt-out and idempotency unchanged) and passes through when
the gate is off.
Tests: install-time no-eval guarantee (gate raises if called during
install), wrapper passthrough with the gate off, all previous gating /
passthrough / CUDA correctness tests kept -- 16/16 pass. Verified on the
N1X (WSL2): module exec + patch install leave torch.cuda.is_initialized()
unchanged; CPU loads pass through; forced CUDA-target loads intercept and
land bit-identical on the GPU.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Compress PR comments to essentials (comment-only; AST-verified)
Docstrings and the _utils hook comment trimmed to their load-bearing
content (lazy-gate rationale, gating scope, opt-out env). AST dumps
with normalized docstrings are identical before/after for all three
files; the module's 16 unit tests pass unchanged.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* docs: tighten the UMA-load import comment (no code change)
* Tighten and trim code comments
* Drop unused is_integrated_unified_memory_gpu import from _utils.py
The UMA hook only needs patch_unified_memory_safetensors_load(); the
gate symbol is imported and used from ._uma_safetensors directly, so the
hoisted alias here was dead and tripped the import-hoist safety-net lint.
* Scope the UMA loader docstring to CUDA/HIP direct-device loads
The module text claimed Intel iGPU coverage, but the gate and device check
are CUDA/HIP only, and the clone path only wraps safe_open calls that carry
a CUDA device. State the actual scope and name the deliberate exclusions
(Intel XPU, CPU-open + .to() flows like bnb/HQQ) until they can be validated
on real hardware. Comment-only change.
* Tighten UMA safetensors loader comments
Trim the inline comments in the UMA clone-then-move path and the
_utils.py install site to be shorter and clearer. No code changes.
* uma: fall back to the direct move when the clone cannot allocate
The clone-and-move fast path transiently doubles one tensor's CPU
footprint while the mmap source and the CUDA destination are live. On a
UMA box with little free shared memory a large tensor could OOM where
the stock direct safe_open path would have loaded it. Both move sites
now go through a helper that catches the allocation failure and falls
back to the direct (slow but allocation-free) move, so the load always
succeeds; a genuine non-memory error re-raises identically from the
fallback.
Added a test that forces the clone to fail and verifies the wrapper
still lands tensors on the device with intact values (17 tests pass on
a real GPU).
* tests: track the moved pass-through inheritance in the gguf order check
Main moved the llama_extra_args pass-through inheritance out of the
GGUF branch into _resolve_inherited_extra_args, which runs before it,
so the source-order assertion's "if request.llama_extra_args is None"
anchor no longer exists inside the branch and the check failed after
the main merge. The test now asserts the same property in the current
shape: inheritance before the GGUF branch (a carried --no-mmproj still
shapes the hub guard's companion requirement), and marker, hub guard,
unload in order within the branch. Full file passes (32 tests).
* tests: anchor the inheritance order check on the call, not the definition
source.index("_resolve_inherited_extra_args(") matched the function
definition, which always precedes the endpoint, so the ordering
assertion was vacuously true. Anchoring on "= _resolve_inherited_
extra_args(" pins the first call site inside the load endpoint (line
4505), which is the statement whose position relative to the GGUF
branch the test is meant to guard. 32 tests pass.
* tests: align the gguf order test with main
Main fixed the stale ordering assertion in PR 7252; adopting its
version verbatim removes this file from the branch diff entirely and
avoids a conflict on the next main merge. 32 tests pass.
* uma: tighten comments
* Relicense UMA safetensors module and test under AGPL-3.0
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* fix(install): route Strix to AMD gfx index on ROCm 7.14
When ROCm 7.3+ caps to the generic pytorch.org rocm7.2 index (or the
Radeon repo is unavailable), gfx1150/gfx1151 hosts were left on
torch 2.11+rocm7.2 instead of AMD's arch-specific wheels. Broaden the
Strix reroute in install.sh and studio/install_python_stack.py so
`studio update` repairs the same path as fresh installs (unslothai#7280).
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Bring the local-subagent support onto main. The original change (#7316) merged
into the stacked pr/daniel-unsloth-start-audit branch rather than main, and #7313
reached main via squash, so these files never landed on main.
Adds --as-subagent for claude, codex, opencode and pi: the parent agent keeps its
own cloud model while a locally served GGUF is registered as a delegated subagent,
using ephemeral per-session config that never touches the user's real agent config.
* studio: classify embedding models from the HF cache and honor offline mode
is_embedding_model() went straight to huggingface_hub.model_info() for any repo
id, so in offline mode (no DNS, or HF_HUB_OFFLINE set) selecting an
already-downloaded model hung on network retries that could never succeed and
training/export never started (#6817).
Check the local HF cache first: a sentence-transformers repo carries
modules.json in its snapshot (the same marker used for local paths), so a cached
model is classified with no network call. When HF_HUB_OFFLINE / TRANSFORMERS_OFFLINE
is set, anything not positively an embedding model returns False without a
network call instead of retrying a doomed request. Online, uncached lookups still
fall through to model_info(), so tag-only embedding models (feature-extraction)
are unaffected.
Adds _embedding_marker_in_hf_cache() over the existing _iter_hf_cache_snapshots.
* studio: judge the active cached revision, harden the cache probe, stop stub leaks
Three review fixes on the cache-first embedding detection:
1. Prefer the revision refs/main resolves to. The HF cache keeps snapshots of
older revisions, so an any-snapshot scan could classify a repo by a stale
revision -- e.g. a repo that used to be a sentence-transformers model would
short-circuit even the online lookup. When refs/main is recorded, only its
snapshot is consulted; the newest-first scan remains the fallback for caches
with no ref.
2. Keep the cache probe inside the detection error boundary. The snapshot
iterator stat()s entries and could raise if a cached model is deleted
concurrently, propagating a 500 out of the config/check-embedding routes.
_embedding_marker_in_hf_cache now catches everything and reads as
not-cached, so callers keep their normal Hub/offline fallback.
3. Stub loggers/structlog in the test only when the real modules are absent
(try-import, mirroring test_windows_gpu_detection_mock), so collecting this
file first can no longer shadow the real packages for later tests in the
same pytest process.
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* studio: treat a missing active-ref snapshot as a cache miss, don't cache offline misses
Two review fixes on the cache-first embedding detection:
1. When refs/main is recorded but points at a commit whose snapshot dir is
absent (partial download / cache pruning), the recorded ref is still
authoritative: return None (cache miss) instead of falling through to scan
older snapshots, which could report a stale historical revision's
modules.json as the active one -- the same stale-cache class this helper
avoids.
2. Do not cache the offline negative. When HF_HUB_OFFLINE/TRANSFORMERS_OFFLINE
is set and the repo is not positively an ST model from modules.json,
is_embedding_model stored False under the (model_name, hf_token) key shared
with online lookups; after the env var cleared in the same process, a
tag-only (feature-extraction) embedder returned the cached False and never
reached model_info(). The offline negative is now returned without caching.
* studio: defer online embedding detection to the Hub, re-probe offline
The local modules.json marker short-circuited is_embedding_model() even
online, so a repo that dropped (or added) the marker since it was cached
was judged by its stale local revision instead of the current remote one.
Online now treats model_info() as authoritative and uses the cache marker
only as an uncached fallback when the Hub is unreachable, so a transient
failure never poisons the memo. Offline re-probes the marker on every call
without consulting or populating the memo, so a model downloaded later in
the session (or a cached online negative that predates the download) is
detected. _embedding_marker_in_hf_cache() now treats an unreadable refs/main
(a non-FileNotFoundError OSError) as a cache miss rather than scanning stale
history -- only a genuinely missing ref enables the fallback scan.
* studio: harden offline embedding detection against empty refs, offline flips, and cache casing
- _embedding_marker_in_hf_cache: an existing-but-empty/whitespace refs/main
(a partial write or in-progress truncate-and-rewrite) now reads as a cache
miss (None) instead of falling through to scan stale snapshots; only a
genuinely missing ref enables the historical scan.
- is_embedding_model: while offline, retain a positive already confirmed online
this session (model_info only ever memoizes Hub-derived results), so
_hf_offline_if_dns_dead() flipping the process to offline mid-load can't
downgrade a verified tag-only embedder to False. Cached negatives are still
bypassed and re-probed.
- resolve_cached_repo_casing + settings route: persist the embedding model in
the casing its local HF cache dir uses. Validation accepts a case-insensitive
cache hit, but an offline SentenceTransformer load resolves the cache by exact
case, so storing the requested spelling (baai/bge-m3 vs models--BAAI--bge-m3)
made the model fail to load on a case-sensitive filesystem.
* studio: reuse the exact-match-first case resolver and preserve the default
Replace the ad-hoc resolve_cached_repo_casing with the existing
resolve_cached_repo_id_case, which already prefers the exact-case cache dir
before any case variant and tie-breaks variants deterministically -- so an
exact requested id is never rewritten to a differently cased directory just
because iterdir() happened to yield it first.
Skip the normalization entirely when the submitted model equals the default:
rewriting its casing would make set_rag_embedding_model()'s exact-string
default comparison treat it as a custom override, pinning it so later changes
to the configured default stop taking effect.
* studio: don't let a stale cache marker mask a permanent Hub error
is_embedding_model's Hub-failure fallback consulted the local modules.json
marker for ANY model_info() exception, so a permanent error -- a deleted repo,
a gated repo without credentials, or a typo that matches stale cache casing --
could pass online validation on a stale marker instead of returning the
documented 409, and the persisted model could then fail when the loader
refreshes from the Hub. Classify permanent Hub errors (RepositoryNotFound,
GatedRepo, RevisionNotFound, EntryNotFound) as False, matching the nearby
GGUF/vision detectors, and reserve the cache fallback for transient/5xx failures.
* studio: honor TRANSFORMERS_OFFLINE in the embedding preflight, skip casing for local paths
- The embedding-model save reached the offline-aware is_embedding_model() only
after two preflight helpers made direct huggingface_hub calls that honor just
HF_HUB_OFFLINE: _st_module_subdirs() downloads modules.json and the security
scan fetches Hub metadata twice. In a TRANSFORMERS_OFFLINE-only session those
blocked on network timeouts before the offline return, so saving an already
cached model stalled. Both now consult a canonical hf_env_offline() helper --
the download passes local_files_only, and the metadata-only security scan
short-circuits to its documented fail-open instead of burning both timeouts.
- Skip cache-casing normalization for local paths: a relative directory such as
"org/model" is loaded from disk, so rewriting it to a case-insensitive HF
cache collision ("Org/model") would stop resolving to that directory and be
read as a Hub repo id instead.
* studio: never skip the security scan on TRANSFORMERS_OFFLINE alone
The previous commit skipped the Hub security scan whenever either offline flag
was set, but huggingface_hub honors only HF_HUB_OFFLINE: under a
TRANSFORMERS_OFFLINE-only session the later SentenceTransformer load still
reaches the network, so the scan was being skipped while the repo's pickle could
still be downloaded and deserialized -- waving through exactly what
_guard_model_security exists to block.
Split the flags: hf_hub_offline() (HF_HUB_OFFLINE, the only one that actually
prevents a fetch) gates the security short-circuit, while hf_env_offline()
(either flag, the user's intent) is used only where local-only behavior is
forced explicitly. The SentenceTransformer load now passes local_files_only from
that intent, so TRANSFORMERS_OFFLINE genuinely stops the loader fetching instead
of merely being assumed to.
* studio: short-circuit the security preflight under either offline flag
With the loader now pinned to the local cache by local_files_only =
hf_env_offline(), a TRANSFORMERS_OFFLINE-only session can no longer fetch
anything -- yet the preflight still fell through to two model_info() attempts on
10s and 20s timeouts, stalling every save and load of an already-cached embedder
for half a minute before failing open anyway.
Skip the metadata-only scan whenever either flag is set. The scan's job is to
stop a poisoned pickle being downloaded and deserialized, and nothing can be
downloaded under that predicate; the residual case -- a model cached BEFORE it
was flagged -- is the same fail-open this function has always documented for an
unavailable scan, and is exactly what HF_HUB_OFFLINE already did.
That safety argument depends on every loader behind the gate honoring the same
predicate, so it is pinned as a test invariant instead of a comment: removing
local_files_only from the SentenceTransformer construction now fails the suite.
Drops the short-lived hf_hub_offline() helper, which no longer has a caller.
* studio: scope the offline scan bypass to callers that load local-only
The previous commit put the offline short-circuit inside _fetch_security_status,
which is the malware gate shared by every loader -- so TRANSFORMERS_OFFLINE=1
disabled it for all of them, while only the RAG embedder had been changed to
pass local_files_only. MLX inference (core/inference/worker.py -> FastMLXModel
.from_pretrained), training and export call from_pretrained with no local-only
argument, and huggingface_hub ignores that flag, so those paths could still
fetch and deserialize an unscanned model with the gate switched off.
The bypass is now an explicit local_only_load argument, defaulting to False, and
only the two RAG embedding callers -- whose loader is pinned to the local cache
by the same predicate -- opt in. Tests pin both halves: the shared gate must
still scan under either offline flag by default, and no other caller may pass
local_only_load without constraining its loader.
* studio: capture offline state once, and probe the ST cache root
Two holes in the offline embedding path:
- _get() read hf_env_offline() twice: once inside _guard_model_security and
again for local_files_only. _hf_offline_if_dns_dead() mutates the process-wide
offline vars and restores them on exit, so a concurrent load could see True in
the guard -- skipping the Hub malware scan -- and False by the time the
constructor ran, fetching and deserializing the unscanned repo and breaking
the very invariant that licenses the bypass. The value is now read once in
_get() and passed to both; _guard_model_security takes it as an argument
instead of re-deriving it.
- The cache probe searched only HF_HUB_CACHE. SentenceTransformer downloads into
SENTENCE_TRANSFORMERS_HOME when that is set, using the same
models--org--name/snapshots layout under a different root, so a model fully
present there looked uncached and was rejected with a 409 offline even though
the local-only loader could load it. Snapshot lookup now covers both roots.
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* studio: probe the cache the ST loader actually uses, and require it be loadable
Adding SENTENCE_TRANSFORMERS_HOME to the shared snapshot iterator was too broad
in one direction and too narrow in another:
- _get() builds SentenceTransformer with no cache_folder, so with ST_HOME set it
searches THAT root only, never the Hub cache. Probing the union let offline
validation pass on a repo cached only in the Hub cache, after which the loader
looked in ST_HOME and failed. The Sentence-Transformers probe now resolves to
exactly one root: ST_HOME when set, the Hub cache otherwise.
- The shared iterator is also used by the GGUF detectors, whose downloads go
through hf_hub_download with no cache_dir and therefore really do use the Hub
cache. It is back to Hub-cache-only so detection cannot pick a snapshot the
GGUF load will not find.
- Casing normalization ran through resolve_cached_repo_id_case, which scans the
Hub cache, so with ST_HOME set the requested spelling was persisted unchanged
and the exact-case offline load missed the differently cased directory that
detection had just accepted. It now resolves against the same roots detection
uses, exact match first.
- A snapshot carrying only modules.json no longer counts as cached: the online
security preflight downloads that single file itself, and a partial download
leaves it behind, so validation passed for a snapshot with no weights and the
first RAG load then failed. A hit now requires the marker plus a config and at
least one weight file.
* studio: thread the captured offline state into the module probe, fix the gate shard
- _st_module_subdirs() re-read the process env for its local_files_only. With
_hf_offline_if_dns_dead() flipping those vars from another thread, a load that
captured local_only=False could still force this probe local-only, get () back
because modules.json is not cached, and leave the scan with NO module load
roots -- a Hub-flagged pickle under 0_Transformer/ would then pass as an
unreferenced nested artifact while the loader fetched and deserialized it. It
now takes the captured predicate as an argument, and the settings route reads
the state once and uses that single value for both the probe and the scan.
- Skip ST-cache casing on the llama-server backend. Nothing there loads through
SentenceTransformer: the embedder derives a GGUF companion from the saved
spelling and fetches it from the HUB cache, so normalizing to an ST_HOME
spelling would point it at a repo _hf_gguf_backend_error() never validated
(BAAI/bge-m3-GGUF instead of the checked baai/bge-m3-GGUF).
- Fix the security-gate shard, which the signature change had broken: the direct
_guard_model_security / _st_module_subdirs callers now pass the new argument
(they were raising TypeError before reaching any assertion), and the casing
tests patch utils.models.resolve_st_cached_repo_id_case, which the route
actually calls, instead of the Hub-only resolver it no longer uses -- those
patches were being silently ignored.
* studio: accept only torch-loadable weights in the offline ST probe; fix re-export lint
_snapshot_is_loadable_st_model accepted a cached snapshot whose only weights
were .onnx (or .pt), but the RAG loader builds SentenceTransformer with the
default torch backend, so such a snapshot passed offline validation and then
failed on the first load, the exact validate-then-fail this helper exists to
prevent. Restrict _ST_WEIGHT_SUFFIXES to .safetensors and .bin and add a
regression test for an ONNX-only snapshot.
Also teach scripts/verify_import_hoist.py that names listed in a module-level
__all__ are uses, so the legitimately added resolve_st_cached_repo_id_case
re-export in utils/models/__init__.py no longer trips HOISTED-IMPORT-UNUSED.
Covered by two new self-test cases.
* studio: probe the exact repo dir and revision an offline load resolves
The cache probe modelled the cache loosely rather than modelling what
SentenceTransformer actually does with local_files_only=True:
- It merged snapshots across every case-variant repo dir and then read refs/main
from whichever held the newest one. With both models--baai--bge-m3 and
models--BAAI--bge-m3 present, a complete embedding snapshot in the directory
the loader opens could be judged by a newer partial snapshot in the other,
failing validation for a usable model. It now selects the ONE directory the
loader opens, by the same exact-case-first rule resolve_st_cached_repo_id_case
uses to choose the spelling that gets persisted.
- It fell back to scanning historical snapshots when refs/main was absent. With
local_files_only the default revision is resolved THROUGH that ref, so a
snapshot directory alone is not discoverable: the settings request succeeded
and the loader then failed at first indexing. A missing, empty or unreadable
ref is now a cache miss, and the historical scan is gone.
The tests exercise the real lookup against a built cache tree instead of
patching the snapshot iterator, so they now cover the directory selection and
ref resolution the loader depends on.
* studio: record refs/main in the ONNX-only probe test
The ONNX-only regression test predates the refs/main requirement, so after that
change it returned None (a cache miss for want of a ref) before ever reaching
the weight-format check it exists to make. Recording the ref restores its
intent: the snapshot resolves, and the answer is False because an ONNX export is
not loadable by the RAG loader's default Torch backend.
* studio: recognize base-model weight files and gate the offline positive on a materialized snapshot
_snapshot_is_loadable_st_model matched any .safetensors/.bin by suffix, so a
partial cache carrying only a commonly published non-weight bin such as
training_args.bin (or an adapter-only artifact) passed offline validation and
then failed the local_files_only load at first indexing. Match recognized Torch
base-model weight filenames (model / pytorch_model, including sharded) by name.
is_embedding_model retained an online-confirmed positive offline even when no
files were cached, so a metadata-only /check-embedding result let an uncached
repo be saved and then fail at first indexing. Retain the positive only when the
active revision is materialized locally, which still covers a downloaded tag-only
embedder whose snapshot carries no modules.json.
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* studio: require a complete weight set offline and persist embedder verdicts across restarts
Two follow-ups to the offline embedding-model classifier:
- _snapshot_is_loadable_st_model now requires a COMPLETE Torch base-model
weight set in one snapshot directory, not just any single recognized weight
file. A partially downloaded sharded model (model-00001-of-00002 without its
sibling) no longer passes offline validation and then fails at first indexing
under local_files_only. Weight files are grouped by directory and a directory
counts only when it holds a single model.safetensors / pytorch_model.bin or a
full shard set whose indices cover 1..total.
- Online-confirmed embedder verdicts are now recorded under the resolved Studio
home (embedding_verdicts.json). The session memo is lost on exit, so a
downloaded tag-only feature-extraction embedder (snapshot present but no
modules.json) was misclassified as non-embedding the first offline call after
a restart. The offline branch consults this durable allowlist in addition to
the memo, still gated on the active revision being materialized on disk, so an
uncached repo is never trusted. Writes are best-effort and only positive
verdicts are stored.
* studio: require complete weights (with shard index) and resolve default casing offline
Follow-ups to the offline embedding-model classifier from the latest review:
- Trust a recorded embedder verdict (session memo or persisted allowlist) offline
only when the active snapshot carries a COMPLETE, loadable weight set, not merely
that it is materialized. A partial download (config present, weights missing or an
incomplete shard set) makes _embedding_marker_in_hf_cache read False rather than
None, so the previous marker-is-not-None gate wrongly returned True and the
local_files_only load then failed. Split out _snapshot_has_complete_weights (config
plus complete weights, modules.json aside) and _active_snapshot_dir, and gate the
known-embedder positive on the weight set.
- Require a sharded checkpoint's index map (model.safetensors.index.json /
pytorch_model.bin.index.json) in addition to every shard before accepting it:
transformers discovers and wires shards through that index, so a complete shard set
without it fails the local-only load.
- Resolve the embedding model name to its exact cache casing in the RAG loader before
constructing SentenceTransformer. The settings route persists that spelling for a
custom override but deliberately leaves the configured default verbatim, so a
default whose casing differs from the cache dir would miss it and fail offline.
Resolving at load time covers the default too; a no-op for a local path or when
nothing case-matching is cached, and idempotent for an already-normalized override.
Adds regression tests for the partial-snapshot verdict, the missing shard index, and
the loader casing resolution; updates the offline-invariant source assertion to the
resolved-name variable.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: require a tokenizer, case-fold verdict ids, and serialize verdict writes
Three follow-ups to the offline embedding-model classifier from the latest review:
- _snapshot_has_complete_weights now also requires a tokenizer asset. A
SentenceTransformer Transformer module builds an AutoTokenizer, so a snapshot with
a complete weight set but no tokenizer.json / tokenizer_config.json / vocab still
fails the local_files_only load. The check is a permissive union over the common
fast-tokenizer, config, and WordPiece/BPE/SentencePiece assets, so an unusual but
valid layout is not rejected -- only a genuinely tokenizer-less partial download.
- The persisted embedder allowlist is now keyed case-insensitively. model_info() is
queried under the requested casing while the settings route saves the cache-resolved
casing, so an exact-string lookup missed the persisted positive after a restart
(baai/model recorded, BAAI/model looked up) and a loadable tag-only embedder was
rejected. Both persist and lookup case-fold the id.
- _persist_embedder serializes its read-modify-write under a lock and writes through a
per-thread temp file, so concurrent confirmations of different embedders no longer
drop each other's entry or collide on the temp path. Cross-process writers stay
best-effort (os.replace is atomic; a dropped verdict is only an optimization miss a
later online re-confirmation heals).
Adds regression tests for the missing-tokenizer reject, alternate tokenizer assets,
cross-casing verdict match, and concurrent verdict writes; updates the snapshot test
helpers to materialize a tokenizer alongside config and weights.
* studio: tighten comments in the offline embedding-model classifier
Comment-only pass over the PR's changed files. Collapse the long block
comments and docstrings around is_embedding_model, the cache-snapshot and
weight-completeness helpers, the embedder-verdict persistence, the offline
security gate, and the offline/casing tests to short one- or two-line forms.
Preserve the rationale (issue #6817, the local_files_only invariant, the
casing and weight-gate reasons) in far fewer words. No code changes.
* studio: drop redundant comments in the offline embedding-model classifier
Second comment-reduction pass over the offline embedding-model cache work:
delete comments and trailing notes that restate the adjacent code or an
assertion, and trim the remaining docstrings and rationale comments to their
load-bearing invariants. Comments and docstrings only; no code changes.
* studio: pin embedder verdicts to a revision, canonicalize default aliases
- A persisted verdict recorded that the Hub tagged ONE revision an embedder, but
was stored per repo. Once refs/main advanced to a complete but non-embedding
Transformer snapshot, the offline path still returned True: the settings route
accepted the updated model without force and RAG could silently load it as an
embedder. Verdicts now carry the commit they were confirmed at and are trusted
only while the active revision matches. One confirmed before the repo was
cached has no revision to compare, so the first revision observed afterwards is
pinned then -- which is what lets a later advance be caught. The persisted file
gains a {id: commit} form and still reads the previous list format.
- tokenizer_config.json no longer counts as a tokenizer asset. It only DESCRIBES
a tokenizer, so a snapshot with config, weights and just that file passed
validation and then failed AutoTokenizer.from_pretrained(local_files_only=True)
at first indexing for common BERT/GPT-style models.
- A casing-only alias of the default is canonicalized to the default up front.
Repo ids are case-insensitive but every gate here compares exact strings, so
saving "Unsloth/bge-m3" against a default of "unsloth/bge-m3" ran the
verification and scan for a custom model and then persisted an override --
after which later changes to the configured default stopped applying.
- verify_import_hoist.py replays __all__ assignments in order instead of unioning
them. Only the final value exports anything, so a later plain "=" that drops a
name must leave its import counted as unused; "+=" still extends, and an
unreadable rebind keeps the earlier names rather than flagging real re-exports.
* studio: validate the real ST load root, and pin verdicts to the Hub revision
Four ways the offline probe still disagreed with what the loader does:
- Verdicts were pinned to the LOCAL refs/main, but model_info() describes the
current HUB revision. With a stale cache the two differ, so an older snapshot
nobody verified was allowlisted. The pin is now info.sha, taken from the
ModelInfo that produced the positive. A verdict carrying no revision (a legacy
entry) is no longer trusted at all -- trusting it meant pinning whatever
happened to be cached, which is the same bug; the next online check re-records
it properly.
- config, tokenizer and weights had to exist somewhere in the snapshot, not
together. modules.json can send SentenceTransformer at 0_Transformer/, which is
loaded FROM that directory, so a cache with the config at the root and only
0_Transformer/model.safetensors passed and then failed the local-only load.
Each directory is now checked as a complete load root, which covers both the
plain HF layout and the ST module layout.
- vocab.json and merges.txt counted independently, but BPE needs the pair unless
a serialized tokenizer.json is present, so half a pair validated and then
failed AutoTokenizer.from_pretrained(local_files_only=True).
- A slashless short name like all-MiniLM-L6-v2 is a supported ST alias that the
loader resolves through the sentence-transformers/ organization, so its
snapshot is cached under that full id. Probing only the bare name reported a
miss and 409'd a model that was cached and loadable; the bare id is still tried
first, matching the loader's own order.
* studio: fail closed for an offline security scan instead of failing open
A local_only (offline) load cannot fetch Hugging Face's malware scan, and the previous
behaviour skipped the scan and failed OPEN, so a cached repo with a poisoned pickle weight
could deserialize under SentenceTransformer(local_files_only=True). Evaluate it fail-CLOSED
against the cached files instead: block a base-model pickle weight the load would deserialize
(pytorch_model.bin and its shards, in a directory with no safetensors alternative) and allow a
pickle-free (safetensors / gguf are inert) cache. A cached pickle model must be reloaded online
once to be scanned, or shipped as safetensors. Nothing cached is not a security event.
_fetch_security_status no longer needs the local_only_load skip (the offline branch is handled
in evaluate_file_security). Adds a regression test covering the safetensors-allow and
pickle-block paths with no Hub call.
* studio: only suppress an offline pickle when a loadable safetensors weight exists
The offline security gate treated any .safetensors in a directory as covering a
pickle weight, so a cache with pytorch_model.bin beside a bare adapter_model.safetensors
(or an orphan shard with no index) passed the fail-closed check even though
from_pretrained still selects and deserializes the pickle. Require a genuinely loadable
safetensors weight -- an unsharded base file or a complete indexed shard set -- before
treating the pickle as covered.
Also make the import-hoist analyzer preserve uncertainty when __all__ is extended by a
value it cannot read statically (__all__ += dynamic()), matching how it already handles
an unreadable rebind, so a dynamically-supplied re-export is not flagged HOISTED-IMPORT-UNUSED.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: scope the offline pickle scan to load paths; reset __all__ opacity on rebind
Address three review follow-ups on the offline security gate and the import-hoist analyzer:
- The offline pickle scan walked the whole snapshot, so a stray pickle in a non-load
subdirectory (archive/, nemo/) that SentenceTransformer never deserializes was blocked.
Scope it to real from_pretrained load roots -- the snapshot root, or a subdir that holds
its own config.json -- matching the online scan's load-path scoping.
- _collect_dunder_all kept a sticky opaque flag: a readable replacing assignment after an
unreadable extend (__all__ += dynamic(); __all__ = []) still credited every import, so a
genuinely unused hoist went unreported. A replacing assignment now resets opacity.
- A bare __all__: list[str] annotation has no runtime value; it was treated as an unreadable
assignment and marked the export set opaque. Skip annotation-only declarations.
* studio: recase slashless ST aliases and accept a pinned embedder after a transient failure
Two offline-detection gaps on well-formed input:
- resolve_st_cached_repo_id_case bailed on every slashless name, so a differently-cased
short alias (all-minilm-l6-v2) validated case-insensitively but was loaded verbatim; the
SentenceTransformer loader rewrites it to sentence-transformers/all-minilm-l6-v2 and looks
it up case-sensitively, missing the canonical sentence-transformers/all-MiniLM-L6-v2 cache
dir. Resolve through _st_cache_repo_dir, which follows the same org alias, and hand back the
on-disk casing.
- On a transient (non-permanent) Hub failure, is_embedding_model only accepted a cached
modules.json marker, so a downloaded tag-only embedder (no modules.json) with a verdict
pinned to the active revision was rejected even though the offline branch accepts the
identical cache. Mirror the offline branch's pinned-verdict acceptance.
* studio: scan modules.json-declared module roots in the offline pickle gate
The offline pickle scan treated only the snapshot root and config.json-bearing subdirs as
load roots, so a pickle in a non-Transformer SentenceTransformer module directory that has no
config.json (e.g. a 0_WordEmbeddings/ module: wordembedding_config.json + pytorch_model.bin)
was skipped even though the loader deserializes it. Parse modules.json (and thread through
load_subdirs) to treat every declared module directory as a load root, so such a pickle is
scanned and fail-closed offline.
* studio: classify cached non-Transformer SentenceTransformer models offline
_snapshot_has_complete_weights recognized only a Transformer-shaped load root (config +
tokenizer + weights co-located), so a fully-cached model built from a non-Transformer module
(0_WordEmbeddings uses wordembedding_config.json + embedding weights and its own tokenizer, no
HF config.json; BoW keeps its vocab in config.json) was classified non-embedding offline and
the settings endpoint returned 409.
Add _snapshot_modules_all_loadable, which parses modules.json and accepts a snapshot when every
declared module's path directory carries the files that module class's own load() reads (a
Transformer/root module still needs the full HF load root; a WordEmbeddings module needs its
config plus a complete weight set; other modules need their *_config.json), and at least one
embedding-producing module is present. It is OR-ed after the Transformer check, so it only ever
accepts more and cannot regress the existing path or reject a pruned cache.
* studio: scan PEFT adapter pickle weights in the offline security gate
from_pretrained auto-detects an adapter_config.json in the load root and deserializes the
adapter weights on top of the base model, so adapter_model.bin is a separate pickle RCE vector
that a safetensors base weight does not cover. The offline scan matched only base-model pickle
names, so an offline local-only load with safetensors base weights plus a cached
adapter_model.bin was allowed despite the live adapter pickle. Scan adapter pickles too, scoped
to a load root where adapter_config.json is present and no adapter_model.safetensors exists.
* studio: require weights for Dense/CNN/LSTM SentenceTransformer modules offline
_module_dir_is_loadable accepted a Dense, CNN, or LSTM module dir with only its config, but
those modules' load() hard-load model.safetensors else pytorch_model.bin (verified against
sentence-transformers source: no fallback, raises if neither exists) -- exactly like
WordEmbeddings. A cache with such a module's config but no weights would validate and then
fail the local_files_only load. Require a complete weight set for every weighted module, not
just WordEmbeddings.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: scan root-index subdir pickle shards offline; handle __all__.append/.extend
- The offline pickle scan followed only load-root directories, so a shard mapped by a root
pytorch_model.bin.index.json into a non-root subdirectory was skipped even though
from_pretrained follows the index weight_map and deserializes it (a layout an attacker can
craft to evade the scanner). Read the local index and scan its referenced pickle shards,
covered by a loadable base safetensors at the index root -- mirroring the online scan.
- The import-hoist analyzer ignored __all__.append("X") / __all__.extend([...]) runtime
re-export mutators, so an import added solely for one tripped HOISTED-IMPORT-UNUSED. Read
their string args like +=, and treat any other __all__ method call as opaque.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: classify StaticEmbedding offline, require WordEmbeddings tokenizer, bound model_info
- A StaticEmbedding module (e.g. sentence-transformers/static-retrieval-mrl-en-v1's
0_StaticEmbedding/) holds tokenizer.json + weights and NO config, so the config-gated
non-Transformer path 409'd it offline. Recognize it by what StaticEmbedding.load() reads: a
tokenizer.json plus a complete Torch weight set.
- WordEmbeddings.load() rebuilds its tokenizer via the configured tokenizer_class.load() from the
module dir, so a WordEmbeddings module now also requires a tokenizer artifact
(whitespacetokenizer_config.json / phrasetokenizer_config.json, or a shared HF tokenizer asset),
not just its config + weights.
- With neither offline env var set, an unbounded model_info() could hang on connect/DNS retries
for networkless users (the #6817 symptom). Bound it with a 15s timeout so a dead network fails
fast and the existing transient-failure cache fallback resolves a cached model, while a
reachable Hub still wins. (Documented caveat: a stalled DNS getaddrinfo may exceed this.)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Resolve indexed safetensors shards relative to their index
_safetensors_index_complete compared shard basenames against the flat
set of files in the index directory, so an index whose weight_map names
shards in a subdirectory was treated as incomplete whenever a legacy
pytorch_model.bin sat beside it. That falsely blocked a snapshot whose
pickle weights are fully covered by a complete, loadable safetensors
shard set. Resolve each shard path relative to the index directory
instead, and add a regression test for the subdir-mapped shard case.
* Restrict offline weight-completeness check to declared load roots
_snapshot_has_complete_weights scanned every directory in a snapshot and
accepted it when ANY directory was a complete Transformer load root. When
modules.json is present a SentenceTransformer load only opens the declared
module paths, so a snapshot whose declared modules are incomplete but which
happens to contain an unrelated complete directory was accepted offline and
then failed at the first local_files_only load. Restrict the candidate
directories to the roots a load actually opens: the snapshot root plus each
modules.json module path. For a well-formed snapshot the verdict is
unchanged; only a complete directory at an undeclared path no longer vouches
for an otherwise-incomplete snapshot.
* Scan SentenceTransformer Router child module weights offline
A Router (legacy Asym) snapshot declares its child sub-modules only in
router_config.json, not the top-level modules.json, and Router.load()
deserializes each child's weights from its own subdir. A config.json-less
child such as query_0_WordEmbeddings (wordembedding_config.json plus a
pickle pytorch_model.bin loaded via torch.load) was therefore neither a
modules.json-declared load root nor a config.json-bearing dir, so the
offline gate skipped its pickle even though the loader deserializes it.
Parse router_config.json at each load root and treat every declared child
subdir as a load root (bounded BFS, so nested routers are covered), so
those child pickles are scanned. Add Router regression tests: a pickle
child blocks, a safetensors child is allowed, and a Router in a declared
subfolder is followed.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Do not treat an unreferenced config subdir as an offline load root
The offline pickle gate skipped a directory only when it was neither a
declared load root nor held a config.json. Because _st_load_roots already
resolves every real load root (snapshot root, modules.json / load_subdirs
dirs, Router children), the config.json fallback only ever promoted an
UNREFERENCED subdir -- a nested checkpoint-500/ or archive/ that ships its
own config.json + pytorch_model.bin -- to a load root. from_pretrained
never descends into such a subdir and the online scan ignores the same
unindexed pickle, so offline mode wrongly blocked a model the loader reads
from a clean safetensors root. Scope the pickle to directory in roots
only, and add a regression test (a stray checkpoint-500/ no longer blocks;
a modules.json-declared module dir still does).
* Classify a root Router (Asym) model as loadable offline
_module_dir_is_loadable applied Transformer root requirements (config +
tokenizer + weights) to every root module, so a Router saved at the
snapshot root -- which carries only modules.json + router_config.json and
loads its weights from child subdirs -- was classified not loadable
offline, and is_embedding_model missed a cached Router embedder. Dispatch
on the module class before the root Transformer fallback: a Router/Asym
dir is loadable when router_config.json parses and every declared child
subdir is loadable (validated recursively through _module_dir_is_loadable,
so nested routers and every child type are covered) with at least one
embedding-producing child. This also tightens a non-root Router, which
previously validated on the mere presence of router_config.json without
checking its children. Add Router regression tests (root and declared
subfolder, complete and incomplete-child).
* Require every declared module before accepting an offline cache
_snapshot_is_loadable_st_model returned has_complete_weights OR
modules_all_loadable, so a complete 0_Transformer short-circuited the or
and vouched for the whole snapshot even when a declared sibling module was
missing its serialized weights; SentenceTransformer builds every module in
modules.json, so that snapshot passed offline validation and then failed
the local-only load. When modules.json declares a non-empty list it is now
authoritative (modules_all_loadable validates every declared module);
has_complete_weights stays the fallback only for an empty/non-list
modules.json (the plain from_pretrained root). Also add the weight-bearing
modules whose load() hard-loads via load_torch_weights and previously fell
to the config-only path -- LayerNorm, WeightedLayerPooling, SparseAutoEncoder
-- to _ST_WEIGHTED_MODULE_NAMES, with source citations and the deliberate
exclusions (Pooling/Normalize/BoW/WordWeights read no weights on load).
Add parametrized regression tests over LayerNorm/WeightedLayerPooling/Dense
(a weightless sibling rejects, a complete sibling accepts).
* Reject self-referential Router children instead of recursing forever
_router_dir_is_loadable validates each router_config.json child through
_module_dir_is_loadable, which re-enters _router_dir_is_loadable for a
Router child. A malformed types entry naming the router's own directory
(a key of ".", which normalizes to the same dir) made that recursion
never descend, so it looped until RecursionError -- breaking the
documented never-raises contract and turning a crafted/corrupted cached
model into a 500 from is_embedding_model instead of a graceful
unverifiable result. A real child reference is a subdir and always
resolves deeper, so reject any child whose resolved path is the router
dir itself. Add a regression test (a router_config naming "." as a
Router child returns False without raising).
* Treat a destructuring __all__ assignment as opaque
_collect_dunder_all detected __all__ only as a direct ast.Name assignment
target, so a binding through a destructuring target (__all__, meta = [...],
v -> an ast.Tuple) was skipped entirely, leaving an empty, non-opaque
export set. A newly hoisted import re-exported only through that assignment
was then falsely flagged HOISTED-IMPORT-UNUSED. Its value cannot be mapped
statically, so mark the export set opaque when __all__ is reached only
through a destructuring / item / attr target, matching how the collector
already handles other unreadable __all__ forms. Add a self-test case.
* Canonicalize declared module paths before scoping the offline pickle gate
A repo could declare a traversing module path such as 0/../evil in
modules.json (or a router_config child), which SentenceTransformer resolves
to evil/ and deserializes evil/pytorch_model.bin. _st_load_roots recorded
the raw snap/"0/../evil", which never equals the snap/evil that rglob
yields, so the offline pickle gate skipped that directory and a malicious
repo slipped a pickle past the newly added gate. Add _canonical_load_dir
to collapse ./ and ../ components lexically and reject an upward escape,
and route the modules.json paths, load_subdirs and router children through
it so the gate scopes the same normalized directory the loader opens. Add
regression tests for a traversing modules.json path and router child.
* Close offline embedding-classification completeness gaps
Five real offline misclassifications, each a false negative (the #6817 hang
recurs) or false positive (accepted then 409s at the local_files_only load).
Dispatch _module_dir_is_loadable on the module class before the root
Transformer fallback. A module with save_in_root=True (every InputModule:
WordEmbeddings, StaticEmbedding, SparseStaticEmbedding, Transformer, Router)
is saved at the snapshot root, so a root WordEmbeddings was wrongly held to
Transformer requirements (an HF tokenizer it never writes) and classified not
loadable.
CLIPModel is Transformer-shaped: CLIPModel.load() reads AutoModel weights plus
AutoProcessor, so a config-only CLIP dir must not validate.
SparseStaticEmbedding needs a tokenizer plus either idf.json or a complete
torch weight set (conditionally weight-bearing); a config alone is not enough.
A present but empty or malformed modules.json is not loadable and does not fall
back to a root Transformer: with modules.json present the loader never takes
the plain-Transformer path (base/model.py _load_config_modules). The tag-only
no-modules.json embedder is classified separately via
_snapshot_has_complete_weights.
Validate a sharded weight index against its weight_map (every mapped shard
present, resolved relative to the index dir) instead of trusting the index
file's mere existence, mirroring the security-side check.
Add regression tests for all five.
* Close case-folding and online-traversal holes in the offline pickle gate
Two gate bypasses where the security scan credited or scoped a path
differently from what the loader actually resolves:
The safetensors credit was case-folded. _cached_pickle_weight_files lowercases
every filename, and the loadable-safetensors and adapter checks tested those
folded keys against the exact-lowercase names. On a case-sensitive filesystem
(Linux, the Studio default) a crafted repo shipping Model.SafeTensors plus a
malicious pytorch_model.bin makes transformers and sentence-transformers miss
the exact-name model.safetensors and deserialize the pickle, while the gate
credited an inert safetensors and did not block. Credit safetensors
case-sensitively against real filenames, and drop pytorch_model.safetensors
from the credit set (transformers loads only model.safetensors, never that
name). Pickle matching stays case-insensitive (over-blocking a mis-cased
pickle the loader would not load is the safe direction).
The online scan did not canonicalize traversing paths while the offline gate
did. A repo-controlled modules.json path (threaded into the online scan via
the RAG guard) or a weight_map shard entry like 0/../evil / ../evil was
compared verbatim, so a flagged evil/pytorch_model.bin never matched and
evaded the online scan though the loader resolves and deserializes it.
Canonicalize the repo-controlled load-subdir prefixes and weight_map shards
the same way the offline gate does, so offline and online agree.
Add regression tests for both bypasses.
* Treat a conditional __all__ mutation as opaque in the import-hoist linter
_collect_dunder_all replayed only top-level module statements, so an __all__
assignment or mutation inside a module-level if / try / for / while / with /
match (or a deeper scope) was ignored, leaving the export set understated. A
newly hoisted import re-exported only through such a conditional __all__ was
then falsely flagged HOISTED-IMPORT-UNUSED, blocking a valid change. A
conditional value cannot be replayed statically, so mark the export set opaque
when __all__ is bound or mutated anywhere other than a top-level statement.
Add a self-test case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Scope Router child sub-modules as load roots in the online embedding scan
The RAG embedding security guard unions the SentenceTransformer module dirs
from modules.json into the load roots it scopes for the Hub scan, so a flagged
pickle directly under a Transformer module blocks. A Router (legacy Asym)
module declares its child sub-modules only in router_config.json, not in
modules.json, and Router.load() deserializes each child from its own subdir.
The online scan therefore dropped a flagged child pickle (for example
query_0_WordEmbeddings/pytorch_model.bin) as an unreferenced nested shard while
the loader still deserialized it, the counterpart to the offline gate which
already expands router children via _router_child_dirs.
_st_module_subdirs now reads router_config.json for any Router-typed module and
adds each declared child (joined onto the module path, canonicalized so a
traversing entry is dropped) to the load roots. The config is read only for a
Router-typed module, so a plain embedder pays no extra fetch, and every failure
path still returns () so the guard never bricks the embedder.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Allow a recorded-clean pickle embedder to load offline
The offline embedding security gate is fail-closed: with no network to reach
Hugging Face's scan, a cached pickle weight cannot be verified, so it is blocked
and a model the user already downloaded and used online will not load offline.
This adds a persistent cache of clean Hub verdicts so that exact content can load
offline, without weakening the gate for an unknown or never-scanned pickle.
When an embedding repo is loaded online and HF's scan returns a completed clean
verdict, the load roots are hashed and recorded under the scanned commit as an
exact map of snapshot-relative pickle name to sha256, in a per-user JSON store at
studio_root()/security/embedding_scan_verdicts.json (atomic write, 0600, thread
and cross-process locked, 30-day TTL). Offline, a cached pickle model loads only
when the active cached commit and every load-root pickle's sha256 match the
recorded verdict; a missing record, moved commit, changed or added pickle,
expired record, or any error keeps blocking. Online loads always re-query the
Hub and an authoritative unsafe verdict deletes any stale record, so a
now-flagged commit cannot keep loading on an old clean record.
The store binds repo id, full commit, and a per-file sha256 map so a locally
swapped pickle at the same commit, a branch advance, or an added load-relevant
pickle is detected. A same-user attacker who can rewrite the model cache or the
store is outside the enforceable boundary and this is documented; the sha256 is
computed just before load, so a narrow verify-to-load window remains, and a Hub
scanner false negative is recorded faithfully (safetensors stays the stronger
defense).
Recording is triggered post-load in the RAG embedder because the settings route
only validates and the pre-load guard runs before the constructor downloads;
recording is skipped when the loaded commit differs from the scanned commit. The
blocked-pickle enumerator now returns snapshot-relative Paths so two module dirs
that ship the same pickle basename are hashed and reported distinctly.
* Harden the embedding verdict cache against review findings
Tighten the offline verdict cache and its enumeration so every uncertain or
malformed input fails closed and the recorded hashes always match the files the
loader reads:
- Hash every case-colliding pickle in a load root, not one representative. On a
case-sensitive filesystem pytorch_model.bin and PYTORCH_MODEL.BIN are distinct
files; keying by lowered name dropped one and could hash a decoy instead of the
loader's target. The enumerator now returns every variant Path.
- Only persist a clean verdict for a COMPLETED, entirely-benign scan. Require
scansDone to be the boolean True (not a truthy string), filesWithIssues to be a
well-formed list, and every flagged file to be a definitively-safe level; a
pending, error, unknown, or malformed entry no longer records as clean. The
online block decision is unchanged.
- Fail closed when the offline cache cannot be inspected: an rglob error now
propagates and blocks instead of reading as pickle-free, and a snapshot that
errors on resolution (vs a clean not-cached) blocks. The offline guard also
raises instead of returning when its own inspection throws, so the constructor
never deserializes an unverified cached pickle.
- Expand online Router children recursively (bounded BFS with a seen set),
mirroring the offline load-root expansion, so a flagged grandchild pickle is
scoped online and cannot be recorded clean.
- Reject absolute and drive/UNC declared paths in the load-root canonicalizers;
the loader would resolve them outside the snapshot, so collapsing them to an
in-snapshot relative dir scoped the wrong place.
- Pin verdict recording to the scanned commit's snapshot and take the offline
verify commit from the snapshot directory name, removing a second refs/main read
and the skew it allowed.
- Drop the now-unused pickle-name wrapper.
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* Tighten offline embedding classification and the pickle gate
Close a set of offline edge cases where validation accepted a cache the
local_files_only load then rejects, and one gate bypass:
- Credit a sharded model.safetensors.index.json for a pickle sibling only at a
from_pretrained root. A non-Transformer SentenceTransformer module (Dense,
WordEmbeddings, StaticEmbedding) loads via Module.load_torch_weights, which
reads model.safetensors then pytorch_model.bin and never the index, so a sharded
safetensors index in such a module dir must not vouch for its pytorch_model.bin.
- Stop counting pytorch_model.safetensors as loadable in the offline classifier:
the loader probes model.safetensors (then its index) or pytorch_model.bin, never
pytorch_model.safetensors, matching the gate that already treats it as a decoy.
- Treat a present but unreadable weight index as incomplete: transformers opens
and parses any present index, so a malformed one or one without a weight_map
fails the load rather than falling back to filename-numbered shards.
- Require the CLIP image-processor config (preprocessor_config.json) for a CLIP
module: CLIPModel.load builds a CLIPProcessor that needs it, so a tokenizer
alone is not enough.
- Require a SparseStaticEmbedding config to actually select idf.json (a path
ending .json) or ship loadable weights; a bare idf.json the config does not name
falls through to load_torch_weights and raises.
- Do not use the tag-only recorded-verdict fallback when modules.json is present:
with the file present the loader takes the modules.json path, so a present but
empty or malformed manifest must not be validated as a plain root Transformer.
- Import-hoist linter: only a module-level conditional mutation or a function that
declares global __all__ makes the export set opaque; a __all__ bound as a local
in a nested function or class no longer masks a genuinely unused hoisted import.
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* Scope Router-child pickles to their deepest load root and gate the ST offline kwarg
The online scan stripped the first matching load-subdir prefix from a flagged file, so a
nested Router child pickle (0_Router/query_0_WordEmbeddings/pytorch_model.bin) matched the
parent 0_Router root, looked like an unreferenced nested shard, and slipped the gate even
though Router.load() deserializes that child directly. Match the deepest (longest) load
subdir instead, so the child becomes root-level under its own load root and blocks.
pyproject sets no lower bound on sentence-transformers and the local_files_only constructor
arg is absent on older releases, so always forwarding it broke every embedder warm on those
installs. Pass it only for an offline load; an online warm never forwards it and works as
before, while the offline capability still requires a version that supports it.
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* Reject snapshot-escaping shard paths and credit Transformer submodule safetensors
The offline pickle enumerator joined a weight-index weight_map value straight to the load
root and followed it, so a repo-controlled index mapping "../.." into a sibling snapshot
made an offline from_pretrained deserialize an out-of-snapshot pickle, and an online load
would then hash and record that external file as the scanned commit's clean content. Reject
any shard path that escapes the snapshot root and fail closed, mirroring the canonical-root
check the online shard scan already applies.
A complete model.safetensors.index.json was credited over a sibling pickle only at the
snapshot root, but a Transformer module subdirectory (0_Transformer/) is loaded via
AutoModel.from_pretrained, which honors that shard set and never reads the pickle. Credit the
sharded index for Transformer-typed modules declared in modules.json so a cached model that
ships both a sharded safetensors checkpoint and an unused PyTorch checkpoint is no longer
falsely blocked offline. Non-Transformer modules (Dense, WordEmbeddings, StaticEmbedding) read
a flat weight with no index and keep their pickle blocked.
Limit the import-hoist verifier's global __all__ scan to the declaring function's own scope so
a nested inner-scope local __all__ no longer marks the module export set opaque and mask an
unused hoisted import.
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* Scope Router children against the snapshot and mirror the ST alias rewrite
Router.load resolves each child at Path(subfolder, model_id) relative to the Router dir, so a
nested 1_Router with a "../evil" child points at evil/ inside the snapshot and the loader
deserializes evil/pytorch_model.bin. The offline enumerator canonicalized the child against
the Router dir alone and dropped anything with "..", so that pickle was never scanned and the
gate reported the cache pickle-free. Canonicalize router children against the snapshot,
retaining in-snapshot siblings as load roots and failing closed on a child that escapes the
snapshot itself, matching the online scan which already joins the prefix before normalizing.
The security gate resolved a slashless model id by probing the bare cache dir first, but the
SentenceTransformer constructor rewrites a non-basic slashless name to sentence-transformers/
<name> and loads THAT snapshot (only the basic ORIGINAL_TRANSFORMER_MODELS load bare). With
both models--<name> and models--sentence-transformers--<name> cached, the gate inspected the
bare dir while the loader read the namespaced one, so a pickle there bypassed the local-only
gate. Mirror the constructor: try the namespaced candidate first for non-basic slashless names.
Add the same not (snapshot / modules.json).is_file() guard to the transient-Hub-failure
tag-only fallback that the offline branch already carries, so a cache whose present manifest is
empty or malformed is no longer reported as a loadable embedder.
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* Tighten root shard credit, module-path escapes, and weight-set probe order
Credit the sharded safetensors index at the snapshot ROOT only when the root is actually loaded
through an AutoModel/from_pretrained path. A modules.json root module of a non-Transformer type
(StaticEmbedding / WordEmbeddings / Dense) loads via load_torch_weights, which reads
pytorch_model.bin and ignores the index, so crediting a root shard index there suppressed a live
root pickle and let the offline gate report the cache pickle-free.
Recognize the Transformer subclasses CLIPModel and MLMTransformer as index-honoring load roots
(they load via from_pretrained), so a sharded-safetensors CLIP/MLM submodule with a legacy
pytorch_model.bin sibling is no longer falsely blocked offline. Mirrors the classifier dispatch.
Fail closed on an absolute or snapshot-escaping modules.json module path (or load_subdirs entry)
instead of silently dropping it: SentenceTransformer resolves such a path outside the snapshot and
would deserialize an external pytorch_model.bin the gate cannot scan.
On the classifier side, walk the weight set in the exact from_pretrained probe order
(model.safetensors, its index, pytorch_model.bin, its index) so a pickle behind a malformed
safetensors index is no longer accepted as complete, and restrict shard names to the loader-probed
stem/ext pairs so a decoy model-*.bin / pytorch_model-*.safetensors set is not treated as loadable.
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* Restore scripts/verify_import_hoist.py to main
The offline embedding cache fix does not depend on the __all__ scope
handling that had accumulated in this linter, so revert the file to its
main version and keep the PR focused on the feature. The feature modules
still pass the existing import hoist check unchanged.
* Reuse a shared HF cache skeleton in the offline classification tests
Extract _mk_repo and _activate helpers for the repeated snapshot cache
setup that every per-type builder duplicated, and fold the two
StaticEmbedding missing-asset cases into one parametrized test. Same 125
collected items, all still passing.
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* Reclassify embedding models from the cache on every offline call
is_embedding_model consulted its process memo before the offline branch, so an
online lookup that memoized True from tags (without caching any weights) was returned
unchanged once the session went offline -- the studio flips HF_HUB_OFFLINE in-process
on a dead DNS, and the ungated check-embedding route can populate the memo. Settings
would then accept a repo the offline loader cannot open. Run the offline
cache-marker reclassification ahead of the memo and never record it, so an offline
verdict always reflects the local cache and a later cache materialization is not
masked by a stale negative. Add regression tests.
* Tighten comments on the offline embedding path
Condense the offline-embedding helper docstrings and inline comments added in
this PR to fewer, clearer lines, keeping the non-obvious security and offline
rationale. Comments and docstrings only; no code change.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothai@gmail.com>
* studio: show system-wide VRAM in the multi-GPU System tab view on ROCm
The System tab's per-GPU list comes from get_visible_gpu_utilization. When
amd-smi is unavailable (always on Windows, minimal Linux installs) it fell back
to torch, whose readings are process-local: on Windows WDDM hands each process
its own budget, so a model held by the separate llama-server process read as
~0 VRAM used even with the GPU full (#7072). The primary-GPU endpoint already
compensates with system-wide sources -- Windows Performance Counters (Task
Manager's source) and Linux DRM sysfs -- but the multi-device endpoint never
got those fallbacks.
Add per-GPU variants of both sources and overlay them onto the torch fallback:
_rocm_windows_perf_counter_vram_per_adapter_gb() attributes Dedicated Usage per
physical adapter (phys_<N> in the counter instance name), and
_rocm_linux_sysfs_vram_per_card_gb() reads mem_info_vram_{used,total} per DRM
card. _overlay_system_wide_vram() applies them to the device list, ROCm-only,
best-effort: unmatched adapters and ambiguous card counts keep the torch
figures, and NVIDIA paths are untouched.
Fixes#7072
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* studio: match VRAM overlay sources by device, honor unified memory, unblock the loop
Five review fixes on the multi-GPU system-wide VRAM overlay:
1. Linux: match DRM cards to devices by PHYSICAL index instead of a positional
zip, so a reordering visibility mask (HIP_VISIBLE_DEVICES=1,0) no longer
swaps each card's figures onto the other GPU (which would mislead
auto_select_gpu_ids and the coexistence checks). An index with no matching
card keeps its torch figures.
2. Linux: skip the overlay for a device whose sysfs total is below torch's --
on unified-memory APUs (Strix Halo) mem_info_vram_total is only the small
dedicated slice while torch sees the GTT-backed pool, and
_apply_unified_memory_correction already defines larger-total-wins.
3. Windows: group counter instances by adapter LUID, not the phys_<N> suffix --
separate adapters each read phys_0, which collapsed every GPU into key 0.
LUIDs are mapped to 0-based positions by ascending value as the closest
stand-in for device order.
4. Windows: pair the system-wide usage with the physical capacity from
get_device_properties (as the primary-GPU fallback does) -- under WDDM
mem_get_info's "total" is the process budget, which misreported capacity
and pushed utilization to 100%.
5. Run get_visible_gpu_utilization off the event loop in the /hardware/visible
route (asyncio.to_thread, the repo's convention): the ROCm fallbacks can
shell out to PowerShell with a 5s timeout, which would stall every other
request while the System view polls.
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* studio: skip the system-wide VRAM overlay for relative GPU indices
The overlay matches its per-GPU sources (Windows perf counters, Linux sysfs) by
physical device index, but under a UUID/MIG visibility mask the torch fallback
enumerates ordinals and reports index_kind == "relative", where `index` is a
visible ordinal, not a physical id. Applying the overlay there let card/adapter
0's system-wide VRAM overwrite the torch reading of a process that actually
exposes physical GPU 1, misleading auto_select_gpu_ids and the coexistence
checks. Gate the overlay on index_kind == "physical"; relative-index paths keep
the torch fallback.
* studio: drop the unreliable Windows VRAM overlay, keep the Linux one
The multi-GPU system-wide VRAM overlay is now Linux-only. The Windows
per-adapter Performance Counter path could not be made correct: the wildcard
Get-Counter query also returns non-ROCm/iGPU adapters and LUID order is not the
ROCm device order, so an adapter's usage could be overlaid onto the wrong GPU;
and it read only Dedicated Usage, missing WDDM shared memory on unified-memory
GPUs (Strix Halo), overstating free VRAM. Rather than misattribute VRAM and
skew placement decisions, Windows keeps the process-local torch fallback (no
regression vs before this PR); Linux DRM sysfs -- matched by physical index --
still fixes#7072 for the reporter's native-Linux ROCm case.
Removes _rocm_windows_perf_counter_vram_per_adapter_gb and _torch_props_total_gb.
* studio: key sysfs VRAM by DRM card number so filtering can't renumber cards
_rocm_linux_sysfs_vram_per_card_gb dropped cards with a zero total or unreadable
files and then the overlay enumerated the compacted list, so if card0 was
dropped, card1's usage was assigned to physical GPU index 0 (equal-capacity GPUs
slip past the unified-memory total guard). Return {card_number: (used, total)}
and match a device to its card number directly: a hole stays a hole -- device 0
keeps its torch figures when card0 is absent, and card1 maps to device 1.
* studio: key system-wide VRAM by ROCm ordinal, not raw DRM card number
When a non-amdgpu adapter (Intel iGPU, a display-only card) owns an earlier
DRM slot, DRM card numbers stop equalling ROCm device ordinals -- Intel card0
plus AMD card1/card2 gives ROCm devices 0/1, so keying the sysfs overlay by
card number handed ROCm device 1 card1's data (AMD device 0) and left device 0
on stale torch figures, corrupting free-VRAM placement on equal-capacity GPUs.
Only amdgpu cards expose mem_info_vram_*, so the glob already excludes foreign
adapters; order the surviving cards by their PCI address (ROCm/HIP's default
device order, read from each card's device symlink) and key by that position --
the ROCm physical ordinal, which is what the overlay matches against dev index.
An unreadable / zero-total amdgpu card still consumes its ordinal so a later
card is never renumbered onto its slot.
* studio: skip the VRAM overlay under layered HIP-over-ROCR masks
ROCR_VISIBLE_DEVICES filters physical GPUs at the HSA/ROCr layer, and a
HIP_VISIBLE_DEVICES set on top selects WITHIN that already-filtered set
(apply_gpu_ids sets HIP while leaving an inherited ROCR mask in place). When
both are active _get_parent_visible_gpu_spec() prefers the HIP value, so the
reported device index is a ROCR-relative ordinal, not a physical GPU id --
overlaying DRM-sysfs figures by that index would pull another GPU's usage
(e.g. ROCR=2,3 + HIP=1 is physical GPU 3, but the overlay would read card 1),
and equal-capacity cards bypass the total-size safeguard. Detect layered masks
and keep torch's process-local figures there rather than risk misattribution;
a single mask still leaves the index physical and is overlaid as before.
* studio: only overlay whole-card VRAM onto 1:1 ROCm devices
The overlay guard only skipped the case where sysfs total < torch total
(unified-memory APUs), so a partitioned ROCm device (MI300 in CPX mode) --
where HIP exposes several logical devices per physical card but sysfs reports
the whole card's aggregate -- passed the guard: the card total exceeds a
partition's torch total, and the overlay overwrote the partition with
whole-card usage and capacity, letting downstream selection think a partition
had the entire card free. Require the sysfs card total to match the torch
device total (within ~10%) so a mismatch in either direction -- unified memory
(sysfs smaller) or partitioning (sysfs larger) -- keeps torch's figures.
* studio: treat CUDA-over-ROCR as layered, enumerate AMD cards by driver
Two remaining mismatches between the reported device index and the DRM card the
overlay reads:
- On ROCm the HIP layer honors CUDA_VISIBLE_DEVICES as well as
HIP_VISIBLE_DEVICES, so a CUDA mask composed over ROCR layers identically:
ROCR=2,3 with CUDA=1 is physical GPU 3, yet the spec reports the ROCR value
[2,3] and the device was labeled index 2, overlaying card 2's usage onto GPU 3.
The layered check now treats ROCR combined with either HIP or CUDA as layered.
- The ROCm device set is now enumerated by bound driver (device/driver resolves
to amdgpu) instead of by the presence of mem_info_vram_*. An AMD device with
incomplete sysfs support (some APUs expose no VRAM files at all) was omitted
by the glob entirely and shifted every later card down one ordinal, letting a
similar-capacity GPU pass the total guard with another device's usage. Such a
card now consumes its ordinal and simply yields no entry.
* studio: honor GPU_DEVICE_ORDINAL and require an unambiguous card mapping
Two remaining ways the reported device index could be matched to the wrong DRM
card:
- GPU_DEVICE_ORDINAL is a supported ROCm visibility variable that
_get_parent_visible_gpu_spec() never consults, so GPU_DEVICE_ORDINAL=1
surfaces physical GPU 1 as torch ordinal 0 and it was mislabeled index 0,
overlaying card 0's usage onto GPU 1. The mask check now covers it, and is
renamed _rocm_device_index_unreliable() to say what it actually decides.
- driver == amdgpu is only a SUPERSET of the ROCm-visible set: an amdgpu-bound
adapter HIP cannot enumerate (an unsupported older AMD GPU beside a supported
one) still took an ordinal and shifted every real compute device. There is no
torch-side PCI identity to match against, so the overlay now requires the
amdgpu card count to equal the device count -- exactly the condition under
which position-in-PCI-order is a sound 1:1 mapping. Any disagreement keeps
torch's process-local figures: less informative, never misattributed.
* studio: keep the VRAM overlay working for masked GPU subsets
The card-count guard compared the amdgpu card list against the VISIBLE device
list, so any visibility mask disabled the overlay outright: HIP_VISIBLE_DEVICES=1,3
on a four-GPU host gives two devices against four cards. Those masked GPUs then
kept reporting process-local torch usage, hiding VRAM held by llama-server and
letting the training/chat placement checks overestimate free memory -- the exact
problem the overlay exists to fix.
The count check now applies only when no visibility mask is active, which is the
case where the reported devices really are the whole host and a mismatch means an
amdgpu adapter ROCm cannot enumerate is shifting the ordinals. Under a mask the
subset is expected, so each device's physical index is validated individually
instead: the per-card lookup bounds-checks it and the total-size guard rejects a
card whose capacity does not match the device's.
* studio: match GPUs to DRM cards by PCI identity, not by position
Every mapping bug on this PR came from the same root cause: there was no
authoritative link between a reported device index and a DRM card, so the
overlay kept inferring one positionally and each heuristic broke on a new host
shape -- foreign adapters on earlier DRM slots, cards with no VRAM sysfs, and
most recently amdgpu-bound adapters HIP cannot enumerate, which the count guard
could only catch on an unmasked host and therefore missed under any mask.
Use the link ROCm itself enumerates from. KFD topology
(/sys/class/kfd/kfd/topology/nodes/<N>/properties) lists exactly the GPUs HIP
exposes -- GPU nodes in node-id order are HIP's device order -- and each carries
its PCI location, so index N there IS physical device N with a stable identity.
DRM sysfs now supplies system-wide VRAM keyed by that same PCI address, and the
overlay is a join on it.
Every previous skew becomes a failed join rather than a misattribution: an
unenumerable adapter has no KFD node so it never takes an ordinal, a foreign
adapter contributes no entry, and a masked subset resolves each physical index
directly. That removes the count heuristic and its mask exception entirely. With
no KFD topology there is no identity to join on, so the overlay is skipped rather
than guessing positionally.
* studio: require verified host visibility and AMD-only KFD nodes
Three ways the identity map could still be built on a false premise:
- The NVIDIA open kernel module registers KFD topology nodes with a positive
SIMD count, so an earlier NVIDIA node shifted every AMD ordinal and ROCm
device 1 resolved to AMD GPU 0. GPU nodes now require vendor_id 4098 (0x1002),
the same filter install.sh already applies for this exact reason.
- A GPU node with an unreadable properties file or no location_id was skipped,
which silently shifted every later ordinal. Both now fail the whole map
closed, so the overlay is disabled rather than misattributing.
- A container exposing only some render devices through device cgroups sets no
visibility variable, yet torch compacts what it can see to ordinals from zero
while the host-mounted KFD and DRM trees still list every GPU. Nothing in the
reported payload distinguishes that from a full host, and torch exposes no PCI
id to check against, so the overlay now runs only when host visibility is
positively verified: no visibility mask AND device count equal to the host GPU
count. That also subsumes the previous layered-mask and GPU_DEVICE_ORDINAL
checks, so _rocm_device_index_unreliable() is gone.
This trades coverage for correctness: masked subsets and filtered containers now
keep torch's process-local figures instead of a mapping that cannot be verified.
* Fix the multi-GPU VRAM overlay docstring for PR #7216
The docstring claimed a reordering mask keeps each card on the right GPU,
but the overlay skips any active visibility mask and keeps torch's figures.
State the actual gating instead.
* Tighten comments in the multi-GPU VRAM overlay and its tests
Collapse the verbose docstrings and inline explanations added for the Linux
ROCm system-wide VRAM overlay to succinct one-liners, keeping the non-obvious
rationale (fail-closed KFD mapping, PCI-identity join, mask gating, the 10%
whole-card guard). Comments only, no behavior change.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
The enforcing pip scan-packages hf-stack shard fails on two CRITICAL
staged-dropper findings in unsloth-zoo test files:
tests/test_mlx_save_export_regressions.py and
tests/test_vision_collator_audio.py. Both are false positives: the
combination heuristic matches a /tmp path literal alongside unrelated
subprocess/import references in the same file, but those are mocked test
fixtures (monkeypatch.setattr on subprocess, asserted /tmp path strings),
not droppers. Add both to the reviewed allowlist so the gate stops
red-failing on legitimate test code. The scan then exits 0 on both the
hf-stack shard and a direct unsloth-zoo scan.
* Improve unsloth start runtime lifecycle
* Remove speculative Gemma prompt override
* Polish model download progress output
* Refine unsloth start status output
* Clarify unsloth readiness banner
* Clarify model reuse and switching output
* Queue model switches behind active inference
* Tighten unsloth start model switching
* Reduce model switch bookkeeping
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* Fix Studio re-exec compatibility
* Recheck sidecar reservation after inference drain
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* Pass start marker through child environment
* Fix key redaction, switch-waiter ordering, and stop/messaging gaps for PR #7313
- Redact minted sk-unsloth keys from the startup-failure log tail: the early
key marker lands in the server log before the model load finishes, so a
load-phase crash printed a live key to the terminal
- Deregister a finished switch waiter before releasing the swap gate so a
swap on another event loop cannot count it as still queued and unload the
model the finished request is about to generate against
- Warn on same-repo quant switches: an explicit variant replaces the resident
weights for every attached session, but the repo ids match so no switch
warning was printed
- Note the agent exit code when it is nonzero so the server keep-alive
message does not read as a successful session
- Use taskkill /T in unsloth studio stop so llama-server children stop too
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* Tighten comments in start, studio, and inference changes
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Studio: reuse MLX prompt cache across turns instead of re-prefilling
* clean up
* key prompt cache on what the KV covers
* skip windowed KV caches past their window
* verify prefix coverage before caching KV
* Studio: move sidebar search into the header
Put the search action as an icon button next to the sidebar toggle in
the header instead of a full-width nav row, so New Chat is the only
fixed row above the scrolling list. The search row is kept for the
collapsed icon rail only. Also add a small bottom gap under New Chat
when it is pinned during scroll.
* Studio: keep search row on custom-titlebar platforms
The header search button only renders on mac/web where the brand row
shows. On win/linux custom titlebars there's no header button, so keep
the full-width search row visible instead of hiding it.
* Studio: address review on sidebar search tooltip
- Hide the search tooltip on mobile (hidden={isMobile}), matching the
SidebarMenuButton tooltip convention.
- Show Cmd K on Mac and Ctrl K elsewhere instead of a hardcoded glyph;
the search dialog binds both meta and ctrl. Uses getClientPlatform so
it is correct on web too, not just Tauri.
* install.sh: route Strix (gfx1151/gfx1150) to the AMD arch index on rocm7.2, add PCI hint
Two Linux install fixes for AMD Strix Halo / Strix Point:
1. #7264: Strix reverts to rocm7.2. Modern ROCm (7.3+) caps to the generic
rocm7.2 index and the Radeon repo can be unavailable, so gfx1151/gfx1150
landed on a non-arch-specific build (torch 2.11+rocm7.2) instead of
repo.amd.com/rocm/whl/gfx<arch> (torch 2.11+rocm7.13, AMD's real Strix
fixes). The reroute to that arch index only fired on rocm7.1; broaden it to
rocm7.2 too. Only acts when a gfx1151/gfx1150 is actually detected, so other
arches on rocm7.2 pass through unchanged.
2. Rows about Strix not detected -> CPU-only: when no GPU is detected but an AMD
display GPU is on the PCI bus, print a targeted hint (ROCm kernel stack /
/dev/kfd missing) instead of only the generic docs pointer. Purely
additive diagnostic; does not change the torch index decision.
* Address review on PR #7293: gate PCI hint on ROCm-detection failure, fix test marker, use read builtin
- Only show the 'ROCm cannot see the GPU' hint when _has_amd_rocm_gpu fails;
a detected-but-too-old ROCm (rocminfo works, wheels need 6.0+) has its own path.
- Update test_previous_torch_pin.sh to the stable 'Strix Halo / Strix Point:'
marker after the heading reworded (the old grep broke the ordering assert).
- _amd_gpu_present_via_pci: read builtin instead of spawning cat twice per
device, and guard /sys/bus/pci/devices existence.
* install.sh: reroute Strix on any generic index older than the arch build
Generalize the Strix reroute from the hardcoded rocm7.1/rocm7.2 match to a
version compare against the arch index's own build (rocm7.13):
- backwards: rocm6.0-6.4 and rocm7.0 now reroute (were silently missed)
- forwards: any future intermediate rocm7.x below 7.13 reroutes; rocm7.13+
is left alone so a generic index that already carries the fix is not
downgraded to the arch build
_rocm_index_below does an integer major.minor compare (so rocm7.2 < rocm7.13);
non-rocm, arch (gfx), and unparseable URLs return false, so NVIDIA/CPU and the
arch index itself are untouched. Reroute still fires only for gfx1150/gfx1151.
* install.sh: tighten _amd_gpu_present_via_pci comment (no code change)
* install.sh: match the index leaf in the Strix version reroute (#7293 review)
Address two review points on the rocm-version reroute:
- Parse the final path segment (_torch_index_leaf) instead of grepping the whole
URL. A custom mirror whose base path holds its own rocm token (e.g.
.../rocm7.13/cache/rocm7.2) previously matched the base and skipped the reroute;
now it compares the leaf (rocm7.2) like the nearby index-family logic. Renamed
the helper to _rocm_leaf_below and switched the case selector to $_torch_index_leaf.
- Replace the stale test_strix_override_only_fires_on_rocm71 (which passed by
matching the new rocm7.13 comment) with an executed test that runs _rocm_leaf_below
and asserts rocm6.0-7.12 reroute while rocm7.13+/gfx/cu leaves do not.
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* install.sh: keep gfx probes non-fatal under set -e (#7293 review)
The Strix reroute now matches every rocm* index, not just rocm7.1, so its gfx
detection runs on all AMD installs. Each `_gfx_all=$(rocminfo|amd-smi | grep -oE
gfx...)` returns 1 when grep finds no match, which under set -euo pipefail aborts
the installer before the next fallback runs (e.g. rocminfo present but emitting no
gfx token). Append `|| true` to the three probes, matching the display block that
already guards this. Add an executed regression test (shimmed rocminfo/amd-smi)
that fails if any probe becomes fatal again.
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---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* fix(install.ps1): use ordinal IndexOf when stripping index URL credentials
On non-English Windows locales, culture-aware String.IndexOf can
mis-locate punctuation-only markers like ://, which corrupts scheme and
authority parsing and crashes Remove-IndexUrlCredentials with a Substring
ArgumentOutOfRangeException (issue 7279).
Force Ordinal comparison for URL scheme/host parsing.
Fixes#7279
* Condense the ordinal parsing comment in Remove-IndexUrlCredentials
---------
Co-authored-by: Daniel Han <michaelhan2050@gmail.com>
* Recognize Radeon 8065S (Gorgon Halo / Ryzen AI Max 400) as gfx1151
* Classify Radeon 8065S (Gorgon Halo) as unified memory in ROCm OOM guard
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* studio: extend the _grouped_mm null-kernel guard to Linux ROCm RDNA4
torch._grouped_mm has a null HIP kernel on RDNA4 (gfx1200/gfx1201) at
ROCm <= 7.12 (fixed in 7.13; ROCm/TheRock #5284). The existing guard that
registers a Python mm/bmm fallback was win32-only, so Linux gfx1201 (e.g.
R9700 Pro on Ubuntu) hits the null kernel -> illegal instruction during
training.
Extract the fallback registration into a module-level helper
(_install_grouped_mm_cpu_fallback) and add a Linux branch that installs it,
gated on gfx1200/gfx1201 AND HIP < 7.13 so NVIDIA/CUDA and every non-RDNA4
AMD arch are untouched, and it is a no-op on fixed runtimes. The Windows
path now calls the same helper with identical behavior.
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* Resolve HIP version from torch.__version__ when version.hip is unset for PR #7292
AMD SDK / Radeon ROCm wheels leave torch.version.hip empty and encode the
version only in torch.__version__ (e.g. +rocm7.12). The Linux gfx120X guard
parsed version.hip only, so those affected installs skipped the fallback and
still hit the null _grouped_mm kernel. Mirror the Windows parse: version.hip,
then the embedded rocmX.Y, then assume affected unless a post-fix rocmsdk wheel.
* Scan all GPUs and add RDNA4 name fallback for _grouped_mm guard in PR #7292
* worker.py: tighten gfx120X Linux guard comments (no code change)
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* fix(rocm): prepend system ROCm libs on native Linux to avoid bundled HIP crash
Prebuilt llama.cpp bundles ship their own ROCR/HIP runtime which can be
incompatible with the host's amdkfd kernel driver, causing hsa_init()
to crash or report zero devices. The llama-server then silently falls
back to CPU while the UI reports GPU.
The existing workaround (_wsl_system_rocm_lib_dirs) that prepends
/opt/rocm/lib to LD_LIBRARY_PATH was gated on WSL (/dev/dxg) only,
leaving native Linux AMD hosts unprotected.
This commit adds _native_linux_system_rocm_lib_dirs(), a parallel
helper gated on:
- Linux platform (not WSL)
- /dev/kfd present (bare-metal AMD compute)
- Bundle contains bundled HIP libs (libggml-hip.so)
- System has libhsa-runtime64.so(.1)
It is called from both _llama_server_env_for_binary (serve-time)
and binary_env (install-time validation), directly after the WSL
block in both paths.
Fixes#7208Fixes#7208
* Add UNSLOTH_LLAMA_NO_SYSTEM_ROCM opt-out to native-Linux system ROCm preference for PR #7233
Lets a host where the bundled runtime works but system ROCm is mismatched keep
the bundle. Mirrored in llama_cpp.py and install_llama_prebuilt.py.
* Prefer env-configured ROCm root over /opt/rocm fallback for PR #7233
Put HIP_PATH/HIP_PATH_57/ROCM_PATH-derived roots before /opt/rocm so a stale
/opt/rocm can't shadow the driver-matching install the env vars point at.
Mirrored in llama_cpp.py and install_llama_prebuilt.py.
* Match versioned libggml-hip.so via glob so the native-Linux ROCm fix fires for PR #7233
* Clarify native-Linux ROCm prepend uses the consistent system stack for PR #7233
* llama_cpp: tighten native-Linux ROCm prepend comments (no code change)
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Add project pinning with sidebar chats, full project chat menu, and new-chat fixes
* Fold pinned projects into the Pinned section with chat icons and lighter show-more
* Address review: queue guard, HTTP-safe nonce, projects show-more, dialog state resets
- Project new-chat composer now shows Stop instead of Queue while running, and the queue click is guarded so a disabled queue cannot enqueue.
- Replace crypto.randomUUID with a helper that falls back on non-secure (HTTP LAN) contexts where it is undefined.
- Projects page keeps all projects reachable: the grid caps at four with a Show more/Show less toggle instead of hiding the rest.
- Reset the rename draft and the delete-files checkbox so a project dialog never opens with stale state.
* Address review: dedupe pinned chats, close drawer on nested nav, gate saved-prompt queue, reset delete toggle
- Pinned chats that live inside a pinned project now render only nested under the project, not a second time in the flat pinned list.
- Opening a chat nested under a pinned project closes the mobile drawer, matching the other sidebar nav handlers.
- The saved-prompt Run-list path now honours disableQueue, so running a prompt list from the project new-chat composer cannot queue against an unbound thread.
- Reset the delete-files toggle when opening a project delete, since the Cancel button closes the dialog programmatically and skips the onOpenChange reset.
* Sidebar: give nested project chats the full options menu and a pin quick-action
- Chats nested under a pinned project now render through the shared chat row, so they get the same hover kebab (Rename, Pin, Move, Export, Archive, Delete) plus a pin/unpin quick-action, matching top-level chats.
- Show more/less now uses the muted nav token with an override, since the sidebar-nav-btn color rule otherwise won so the label matched the chat rows; it now reads clearly dimmer in both light and dark mode.
* Projects list view, pinned-chat promotion, and sidebar polish
- Pinning a chat inside a project now promotes it into the pinned chats list and removes it from the project's nested list, so it shows once in the Pinned section.
- Sidebar highlights only the open chat, not its parent project folder, while a chat inside the project is active.
- Rename project uses the edit icon instead of the compose icon so it no longer matches New chat.
- Projects page is now a list: Name and Modified columns, a pin indicator on pinned rows, and the row options menu on hover, replacing the card grid.
* Redirect after deleting a project viewed via a thread-only URL
commitDelete only redirected when the ?project= param matched the deleted
project. On a thread-only URL the project is resolved from the thread into the
runtime store, so also compare that resolved id, otherwise the user is left on
a deleted thread.
* Restore the unpin quick-action on pinned chats
Pinned rows in Recents already reserved room for it, but only the kebab
rendered. Show the unpin button on hover, left of the options button.
* Projects list: alignment, spacing, no icon overlap, fit-to-height paging
- Add side padding to the list and more room after the folder icon.
- Column header now shares the row layout so Name and Modified line up with the values.
- Pin indicator and options button swap by display so they no longer overlap.
- Show more only appears once projects exceed the page height and reveals five more per click.
* Projects list: align Name to the folder icon and narrow the table
- Drop the header leading spacer so Name starts at the folder icon edge; the
right-anchored columns keep Modified aligned.
- Narrow the page to max-w-4xl so the table is less wide.
* Projects list: widen slightly and add top spacing
Bump the page to max-w-5xl and increase the top padding so the header sits
a little lower.
* Projects list: infinite scroll instead of Show more
- First page fills the viewport, then a sentinel loads another batch as it
scrolls into view, re-observing after each load so it keeps filling.
- Search still filters the full project set and shows every match uncapped.
* Projects list: drop dividers for a rounded-row hover style
Remove the row and header borders and give each row a rounded hover fill so
the list reads cleaner, closer to a modern file list.
* Projects list: more row spacing and a tighter hover radius
Increase row padding so projects sit further apart, and drop the hover
corner radius so it reads as a rounded rectangle rather than a pill.
* Projects list: more space below the title
Increase the list top margin so the header sits further from the rows.
* Project landing: narrow slightly and drop the Sources New badge
Reduce the landing column to 44rem and remove the New badge from the Sources
tab.
* Project switcher: rounded-rectangle rows instead of pill
The switcher rows are short, so the shared 12px item radius reads as a pill.
Scope a smaller radius to this menu so the highlight is a rounded rectangle.
* Project landing: add a header options menu
Add a kebab menu next to the project title with Rename project, Pin or Unpin
project, Export, and Delete project, reusing the existing project actions.
* Project switcher: round the scrollbar-side corners
Revert the earlier item-radius tweak. The container corners were squared on
the scrollbar side because the container itself scrolled; move the scroll to an
inner wrapper so the rounded container never scrolls.
* Projects: keep row kebab focusable, gate off-route dialogs, refresh history on delete
* Projects: fix delete copy, refresh history on landing delete, gate chat-delete dialog off-route
---------
Co-authored-by: shimmyshimmer <info@unsloth.ai>
* Studio: show the mobile sidebar trigger above the chat header
* fix
* correct z-index
---------
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* Installer: enable ROCm torch on RDNA2 (gfx1030-1036) on Windows
repo.amd.com publishes a gfx103X-all wheel family with win_amd64 torch
2.9.1/2.10.0/2.11.0+rocm7.13.0 (cp310-313), but both Windows allowlists
omitted RDNA2, so RX 6000 cards (gfx1030/1032, etc.) fell back to CPU-only
torch. Map gfx1030-1036 to gfx103X-all in install.ps1 ($archFamilyMap) and
install_python_stack.py (_GFX_TO_AMD_INDEX_ARCH). No torch floor (mirrors
gfx110X-all: newest wheel, no _grouped_mm bug on RDNA2). NVIDIA/Mac/CPU and
Linux paths untouched; gfx906 stays CPU (no wheels published).
* Sync studio/setup.ps1 RDNA2 (gfx1030-1036) allowlists for PR #7277
* Studio: show HF token tick only after validation
* Studio: prevent stale HF token validation state
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---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Installer: report the installed Unsloth version
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Fix resume training crash recovery and MLX checkpoints
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Address review: preserve interrupted stop-and-save output_dir, verify MLX checkpoint
- finish_run: add clear_output_dir flag; preserve output_dir for stopped/error
unless cancel explicitly clears it (fixes pump finalization wiping persisted path).
- training pump: pass interrupted stop-and-save context into finalize_run_in_db.
- MLX stop-and-save: verify resumable checkpoint exists before sending complete;
return bool from _write_mlx_stop_checkpoint and add regression tests.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Address Codex review: MLX current-step checkpoint and cancel error finalize
- Only skip MLX stop checkpoint write when checkpoint-{current_step} exists;
stale periodic checkpoints no longer mask missing stop saves.
- Pass clear_output_dir through error-event finalization so Stop-without-save
cannot leave a persisted output_dir that still offers Resume.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Address review
* Address more reviews
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* more reviews
* clear in-memory output_dir on interrupted cancel
* allow resuming errored runs at the final step
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Clear persisted output_dir in cancel watchdog path
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Write MLX stop checkpoint in stop path, keep output_dir on crash finalize
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix(studio): harden resumable run finalization
* fix(studio): defer safetensors checkpoint import
* fix(studio): reject stale training cancellation
* fix(studio): replay null resume targets
* fix(studio): serialize terminal cancellation
* Harden resume checkpoint validation and fix stop-save cleanup
- Reject unrecognized shard formats and keep indexed shard paths inside the checkpoint dir
- Require a non-empty tensor record when validating .pt/.bin optimizer and model state
- Always finalize TensorBoard and W&B on stop-save-failure exits
- Refuse writing an MLX stop checkpoint through a symlinked directory
- Clarify the resume rejection message to cover errored runs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Tighten resume/checkpoint comments
* Recover resumability when a valid stop checkpoint landed
- Re-validate the current-step checkpoint in the dead-worker and error finalization paths so a stop-and-save that actually wrote a valid checkpoint is not wrongly marked error/resume_blocked
- Accept a valid tensor-free optimizer state (e.g. SGD without momentum); the model-state check still requires real tensors
- Include errored runs in the frontend resume rejection message
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Lyxot <longyixing331@gmail.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
* Fix Studio desktop reliability
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix desktop export completion and layout migration
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix maximized setup layout migration
* Adapt desktop exports to data settings
* fix(studio): harden desktop reliability edge cases
* fix(studio): preserve rounded combobox focus fill
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* refactor(studio): move chat model picker into features/model-picker
Relocate model-selector + its support files from components/assistant-ui
into a self-contained features/model-picker feature (own barrel), mirroring
the modular Hub layout. Pure move + import repoint; no behaviour change.
* feat(model-picker): add per-model config persistence layer
Superset PerModelConfig (customContextLength, kvCacheDtype, speculativeType,
specDraftNMax, tensorParallel, chatTemplateOverride, trustRemoteCode) persisted
to localStorage (unsloth_model_configs) with schema versioning + LRU budget.
KV-dtype and speculative value sets match main's sidebar (no q4_0/ngram-simple).
Reuses features/hub/lib/model-identity for normalization; adds storage-key layer
and applyPerModelConfigToRuntime (sets tensorParallel, which the old PR omitted).
* feat(picker): modular backend for chat-template validate + default fetch
New studio/backend/picker package (schemas/service/routes) mounted at /api/picker:
- POST /api/picker/validate-chat-template (Jinja syntax validation, no false positives)
- GET /api/picker/chat-template/{model_name} (default template from tokenizer_config.json,
reusing get_cache_path/resolve_cached_repo_id_case; graceful null, no model-code exec)
Frontend api/templates.ts client + hooks/use-model-defaults lazy cache. No backend
changes to the existing inference load route (per-model load fields already supported).
* feat(model-picker): bind picker on-device list to shared hub inventory
Picker now sources cached + local models from useHubInventory (the Hub's shared
store) via a thin adapter, replacing its own /api/models/* fetchers + module
caches. Hub, download manager, and picker now share one source of truth, so
completed downloads reflect in the picker automatically. Partial/live-download
rows are filtered from the cached lists (unchanged rendering). Local naming/search
preserved via additive LocalInventoryRow modelId/displayName. Variant expander,
scan-folder management, recommended-fit, search, external providers untouched.
Known minor: cached 'Downloaded date' sort tiebreak degrades to alphabetical
(hub cached rows carry no mtime); default 'recent' (load-time) sort preserved.
* feat(model-picker): per-model config step inside the picker
Picking a (non-external) model now opens an in-picker config view built from
main's current load controls (context length, KV cache dtype, speculative
decoding, draft tokens, tensor parallel) plus a chat-template editor backed by
the picker validate/default endpoints. 'Remember for this model' persists the
config per model+variant; Run forwards the config to the existing load flow via
meta.config. External models bypass the step. Two-view orchestration lives in
model-selector (single interception point); pickers.tsx call sites untouched.
trustRemoteCode dropped from PerModelConfig to preserve main's per-load consent.
* feat(chat): apply/persist per-model config through the load flow
handleCheckpointChange threads meta.config into the selection; stageOrLoad and
the autoload/Hub-run paths now apply the picker config (explicit pick or saved
remembered config) via applyPerModelConfigToRuntime before staging/loading, with
keepSpeculative set so a remembered speculative mode survives the model switch.
Replaces the old remembered-load-settings seeding (resolveInitialConfig now the
single source). SelectedModelInput carries config.
* refactor(chat): remove per-model load config from the right sidebar
The load knobs (context, KV cache, speculative, draft tokens, tensor parallel)
and the chat-template editor now live only in the picker config step. The sheet's
Model section keeps the staged Load/Cancel flow (config is applied at pick time);
sampling params, system prompt, and RAG are unchanged. Deletes the superseded
remembered-load-settings module + the store's applyRememberedLoadSettings action,
removes the now-dead sheet state/imports, and points the settings reset at
unsloth_model_configs. Delete-cleanup deferred (stale config is LRU-capped).
* fix(model-picker): remove leftover sidebar-staging cogwheel + empty Model section
The downloaded-variant gear (ModelLoadSettingsAction) staged a model straight
into the right-sidebar Run-settings flow -- the old 'configure before load' path
now fully replaced by the in-picker config step. Removed the gear + its component.
Also gate the sheet's 'Model' section to staged picks only (pendingSelection):
after the load-knob strip its content is staged-only, so it was rendering an
empty section header whenever a model was merely loaded.
* chore(chat): remove dead per-model-config setters + modelControlsDisabled
After the load-config UI moved into the picker, the store's per-model setters
(setKvCacheDtype/setSpeculativeType/setSpecDraftNMax/setTensorParallel/
setCustomContextLength/setChatTemplateOverride) had zero callers
(applyPerModelConfigToRuntime writes via setState), and the sheet's
modelControlsDisabled was unreferenced. Verified dead across the whole tree.
* fix(chat): config-step Load actually loads (ignore Load-on-selection)
Root cause: with Settings > Chat > 'Load on selection' turned OFF, the config
step's load went down the deferred-staging path -- opening the right sidebar with
'<model> is staged, not loaded yet / Choose Load model'. The in-picker config step
IS the deliberate load action, so its Load now loads immediately (or downloads +
auto-loads when not cached) regardless of the toggle. Renamed the button
'Run model' -> 'Load model' to match. Native/dropped picks still honor the toggle.
* refactor(chat,hub): retire 'Load on selection' — config step is the only load flow
The in-picker config step (and the Hub Run button) now fully supersede the old
stage-to-sidebar flow, so the Load-on-selection toggle is removed everywhere:
- chat stageOrLoad: every pick loads immediately, or downloads + auto-loads when
not cached (the previous default behaviour, now universal).
- hub Run: drops the stage branch; downloaded GGUFs load directly with their saved
per-model config (no collision with the chat config step — both end at selectModel).
- store: removed loadOnSelection field/setter/key/default; Settings>Chat toggle and
its settings-reset entry removed.
- staged sidebar section is now a download-progress view (auto-loads on completion).
No manual staging remains; stageModel is used only for background auto-load downloads.
* feat(model-picker): default chat template from GGUF + thread variant through config flow
Read the embedded tokenizer.chat_template from GGUF files (read_gguf_chat_template
in gguf_metadata) and use it as the per-model default. Plumb gguf_variant through
the picker service, /api/picker/chat-template route, frontend templates API, and
use-model-defaults so the right variant's template is fetched.
Also refine the picker config-page/model-selector wiring, drop the dead
ggufNativeContextLength runtime path, and add the per-model-config storage keys to
the settings prefs export.
* feat(model-picker): read safetensors chat template + hide editor where it has no effect
Resolve the default chat template for safetensors models: prefer the modern
chat_template.jinja, fall back to the tokenizer_config.json chat_template field,
then chat_template.json (multimodal processor), then the GGUF embedded template.
Applied to local dirs, the HF cache snapshot scan, and the HF remote fetch.
Hide the chat-template editor in the picker for safetensors models — the override
is only applied at load by the GGUF/llama.cpp backend, so editing it on safetensors
currently has no effect. GGUF keeps the editor. Nothing removed; the dialog stays
for when the safetensors apply path is wired up in a later branch.
* fix(model-picker): set legacy-migration flag only after the write succeeds
Set unsloth_model_configs_migrated only once writeMap confirms the migrated
map persisted, so a quota/storage failure no longer marks migration done and
silently drops the user's pre-existing remembered settings — the next load retries.
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* MVP model picker fixes
* MVP picker config fix
* MVP safetensors config
* MVP max seq config
* MVP max seq fix
* Fix static max tokens cap ignoring model context
* Fix picker GGUF scan parity
* fix(studio): harden model picker config loading
Apply remembered per-model configs consistently from picker and Hub loads, keep default configs from overriding standing speculative settings, add config access for direct local GGUF files, and support saving or forgetting active model settings without a reload.
* Fix model picker config flow
* Fix model picker config loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Avoid recursive per-model config migration reads
* Apply the displayed context length when loading a GGUF
* Fix template validation, cached template lookup, and failed load rollback
- Validate chat templates with the loopcontrols extension so templates
that use break or continue tags pass the picker validator, matching the
inference renderer that already accepts them.
- Read the default chat template from the newest cache snapshot rather than
an arbitrary iterdir order, so an older cached revision no longer prefills
a stale template.
- Capture the runtime per-model config before a load and reapply it when the
load fails, so a failed switch leaves the active model context, KV cache,
template, and speculative settings as they were.
* Make chat template view only for safetensors models
Custom chat template overrides are applied at inference only for GGUF
models, which pass the template to llama-server. The safetensors backend
renders with the model built-in template and ignores the override, so
editing it would save a value that never loads. For safetensors the
config page now opens the template as a read-only preview with a note
that editing is not available yet. This can become editable once
inference support for custom safetensors templates lands in main.
* Fix model picker config edge cases
- Restore prior runtime config when a load no-ops for the active model
- Cap the picker validator request body via the protected prefixes
- Keep the GGUF context slider max above the loaded context
- Fetch subfolder chat templates for uncached Hub repos
- Show the compare side config when reopening the picker
* Keep saved GGUF context above the fallback ceiling
* Show the model config in the run settings sidebar
* Fix model config sidebar reset and context slider
- Stack the remember toggle and action buttons in the sidebar
- Reset the config to defaults instead of the loaded values
- Fetch the native context so the slider max is not the loaded value
* Fix model picker config and download regressions
- Run picker chat template routes off the event loop
- Depth and root guard local template directory scans
- Restore download manager flow for uncached hub picks
- Apply per model context length on reload
- Import model picker symbols from the feature barrel
* Fix model picker config and cached download sorting
- Restore load settings when a Hub run is rejected mid load
- Reuse one NumericValueInput instead of a duplicate copy
- Fix double decode of the model name in the template route
- Remove the unused reset-to-loaded settings action
- Fix cached model download sorting
* Fix model picker per-model config edge cases
Honor a saved or typed max seq length above the model's native context so
RoPE extended values are no longer clamped and silently overwritten. Allow
typing past native while the slider keeps native as a soft ceiling.
Guard the fetch success paths in use-model-defaults against an aborted
signal, and refetch when the HF token changes.
Hash the chat template content in the sidebar remount key instead of its
length. Enable reset for a GGUF whose native context is unknown, and floor
the context slider max so it can never fall below the min.
* Fix GGUF context auto-fit and gated model config token
Stop forcing a 32768 context when a GGUF native context is unknown so the backend auto-fits to VRAM again, while still honoring an explicit context edit.
Send the HF token as a query param so gated safetensors models resolve their max position embeddings.
Derive model default state during render to drop the set-state-in-effect calls.
* Fix native GGUF context ceiling and guard picker template reads
Restore the native context store field so the sidebar slider keeps the
full ceiling for drag and drop GGUFs. Limit local chat template reads to
the browse allowlist, skip malformed repo ids, and drop unused model
picker exports.
* Fix model picker lint boundaries
* Fix model picker review findings
Chat template editor never seeded its draft. Radix only calls onOpenChange
from internal events, so the seed in the nextOpen branch was dead and a model
with a saved override opened empty. Saving then cleared the override. Drop the
dead branch, treat draft as an untouched sentinel, and reset it on every close.
Uncached Hub picks could auto load a model after the user left the chat. Main
detached the staged pick on route exit and on chat context change. Carry the
context key on the pending pick and skip the load when it no longer matches.
Also clear configTarget when the picker closes, restore the onUpdated ref so
variant rows stop resubscribing on every parent render, skip the LRU write when
the entry is already most recent, import NumericValueInput relatively, and drop
the unused ModelUpdateAction barrel export.
* Preserve GGUF context on active reload
* Fix model picker per-model config regressions
- Stop reloading the already loaded model on re-pick
- Hide infra models from the chat picker
- Detect vision support on cached GGUF repos
- Honor saved maxSeqLength on auto load
- Restore default chat template for local GGUFs
- Warn on save failure and revert config on cancel
- Refetch picker inventory on open
- Persist read only per model config safely
* Fix stale model auto load
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* Fix model picker numeric input sizing and constraints
Size value inputs to their content so long context lengths are not clipped,
restrict them to numeric characters, and stop the speculative decoding label
from truncating in the sidebar.
* Fix picker CI tests and harden chat template resolution for PR #6647
- tests: point the descender guard at the moved model-selector.tsx path
- tests: exclude the disabled Reload model button from the regenerate locator so .first targets the real Regenerate
- picker/service.py: reject symlinked template/gguf leaves that resolve outside the browse allowlist (HF cache reads unchanged)
- compare mode: resolve each pane's own remembered chat template instead of inheriting the other pane's from the store
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* Protect future-schema per-model configs from deletion for PR #6647
savePerModelConfig already refuses to overwrite a stored config whose schema version is newer than this client understands, but deletePerModelConfig did not. Unchecking Remember on an older client therefore silently destroyed a newer client's saved config. Apply the same guard on delete and surface the blocked case through the existing saveFailed toast.
* Protect future-schema per-model configs from quota eviction for PR #6647
The save and delete guards already refuse to touch a stored config whose schema version is newer than this client understands, but the quota-eviction path did not, so a full store on an older client could still evict a newer client's config. Skip future-schema entries when evicting and fail the save if the budget cannot be met without them.
* Fix GGUF context persistence, compare context, and rollback settings for PR #6647
Persist a GGUF context override from the user's intent instead of collapsing it against the loaded context, which reintroduced the context-reset (f4838782cb reverted the native-baseline fix). model-config-page now collapses the saved value against native, and use-chat-model-runtime and chat-adapter retain the requested context on load so re-saving another setting keeps the override; a null request stays null so a VRAM auto-fit never becomes a stored override.
shared-composer: a compare pane with no explicit GGUF context now loads at native (0) like single-view, not the session maxSeqLength that silently shrank the shown context.
use-chat-model-runtime: restore the previous model's KV cache dtype and chat template on a failed-load rollback so it runs as it was, not with backend defaults.
* Preserve native path token when reloading the active model for PR #6647
handleReloadActiveModel rebuilt the selection without the store's activeNativePathToken, so reloading a file-picked GGUF after a settings change validated the display label as a repo/path and failed. Thread the active native token through the reload selection so native-loaded models reopen correctly.
* Make picker template validation resilient and accept HF generation tags for PR #6647
Import Jinja lazily inside validate_chat_template so a backend without the optional jinja2 package (GGUF-only installs) still starts instead of raising ModuleNotFoundError at import time. Register a no-op extension for the Transformers {% generation %} assistant-mask tag so pasting a valid HF chat template validates, matching the renderer, rather than being rejected as an unknown tag.
* Honor remembered compare config and parse processor chat_template.json for PR #6647
* Fix failed-load rollback context and processor template map fallback for PR #6647
* Restore speculative decoding config on failed-switch rollback
When a model switch fails after the previous model was unloaded, the
rollback reload restored tensor_parallel, KV cache dtype and the chat
template override, but omitted speculative_type and spec_draft_n_max and
cleared their loaded shadows to null. The previous model therefore came
back running at backend defaults (speculation off) while the UI still
showed it enabled, and the status resync confirmed the off state. Resend
the previous model's speculative settings in the rollback load and keep
the store's active and loaded speculative fields in sync with them.
* Reset max sequence length when a model has no saved config
applyPerModelConfigToRuntime reset every per-model field except
maxSeqLength, which it only wrote when the incoming config had one.
maxSeqLength is the sole field carried on store.params, so selecting a
model with no remembered config left the previous model's value in place
and later loaded the new model at that leaked length. Fall back to the
standing default so an unremembered model loads at its own default.
* Surface a message when a variant update cannot start
startManagedUpdate handled the conflict and error start outcomes but let
busy fall through as if the update began, so the confirm dialog closed
with no job created and the cached variant stayed stale. Show an info
message when the repo is busy with a sibling transfer so the click is
not silently dropped.
* Keep per-model speculative choices out of the global default
A staged load with a per-model or one-off config sets keepSpeculative,
which already skips reading the global speculative preference. The
matching save still ran unconditionally, so the model-specific choice was
written to the global unsloth_chat_speculative_type and a later model with
no saved config started from it instead of Auto. Skip saveSpeculativeType
when keepSpeculative so the per-model choice stays isolated.
* Seed non-active model settings from the app default max length
The Run settings page captured initialMaxSeqLength from the loaded
model's runtime params and fell back to it for a model with no saved
config. Opening settings for a different, unloaded model and clicking
Load then sent the active model's context (for example 64k) instead of
the 4096 default, risking validation failures or OOMs. Seed the default
for non-active models and keep the runtime value only for the active one.
* Prefer sidecar tokenizer chat template over the GGUF copy for variants
_chat_template_from_dir returned the embedded GGUF template first when a
variant was selected, reversing the tokenizer-first precedence of the
no-variant path. A model whose chat_template.jinja or tokenizer_config.json
supersedes a stale embedded template then got the wrong template on
variant selection. Keep tokenizer files first regardless of variant; the
variant only picks which GGUF is the fallback. Adds regression tests for
both the tokenizer-wins and gguf-fallback cases.
* Keep per-model speculative choices load-local in autoload and compare
The interactive load path treats a per-model speculative choice as
load-local and skips writing it to the global default. Autoload and
generalized compare still called saveSpeculativeType unconditionally, so a
remembered off or ngram setting leaked into unsloth_chat_speculative_type
and later models with no saved config inherited it. Persist the global
preference only when the value came from the global settings.
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* Studio: record the compare pane's loaded context in runtime state so the active model's settings and any reload or save use it, not the previous context
* Studio: notify the user when a Hub autoload can't start because another download for the model is already running, instead of silently dropping it
* Studio: drop the merge's orphaned staged-model store helpers and unused alert imports
The main merge left isPendingGguf and pendingSelectionMatches referencing the
removed PendingModelSelection type, and the alert-dialog/alert imports unused
after the permission-mode dropdown replaced the bypass dialog, so tsc -b failed.
* Studio: cache a null default chat template so the viewer stops re-fetching it
A model with no sidecar or embedded template resolves to a terminal null, but
that result was never cached, so reopening the template viewer re-ran the
backend and Hugging Face lookup every time.
* Studio: detect direct-file GGUFs in run settings so Max Tokens uses their context
A GGUF loaded from a local file or custom folder has no variant label, so the
run-settings panel treated it as non-GGUF and clamped Max Tokens to the session
max_seq_length instead of the loaded GGUF context. Detect it via the reported
GGUF context and the .gguf checkpoint suffix, matching the chat page.
* Studio: prompt to re-select a local model file when its lease expired before reload
A file-picked GGUF is reachable only through a native path token that the
desktop host prunes after a TTL. Reloading reused that token blindly, so a
reload long after the initial load failed with an opaque error. Track the
token's expiry and, when it has passed, ask the user to re-select the file
instead of attempting a doomed reload.
* Fix descender-clipping test to tolerate sidebar layout utilities
The sidebar account-block div carries layout utilities (min-w-0, flex-1)
between 'flex' and 'flex-col', so the descender-clipping guard's regex,
which required 'flex' immediately followed by 'flex-col', no longer matched
and the test failed to locate the account-block div. Generalize the prefix
to allow intervening flex utilities while still capturing the leading-*
class before the collapsible visibility utility and asserting leading-tight,
so the guard against clipped glyph descenders is fully preserved.
* Harden picker chat-template resolution
Enforce the 64 KiB chat-template contract at the validate endpoint's request
model so a direct caller cannot submit a template far larger than the frontend
allows (MaxBodyMiddleware only bounds the whole request body, not this field);
oversized templates now return a clean 422.
Apply sidecar-over-GGUF template precedence globally across cached snapshots
instead of per snapshot. A repo with multiple cached revisions previously
returned the first snapshot's template, so a newer GGUF-only revision could
win over an older revision's maintained chat_template.jinja sidecar, which
contradicted the documented intent that sidecars supersede the embedded copy.
* Guard per-model config against future-schema and lossy migration
Two forward-compatibility gaps in the versioned per-model config store:
- The load/apply path returned and normalized a stored record without checking
its schema version, so a record written by a newer client was reinterpreted
under the current schema and applied to a live model load, even though save,
delete and eviction all refuse to touch future-schema records. Reject
future-schema records on load too.
- The one-time legacy migration enforced the storage budget without protecting
the entries it had just migrated and set the completion flag unconditionally.
When storage was already full of future-schema records (which are unevictable
by an older client), the migrated entries were the only evictable ones and
could be dropped while migration was still marked complete. Protect the
migrated keys during eviction and only mark migration complete when they
survive, so it retries once space frees up.
* Discard chat-template validation results after the dialog closes
Server-side template validation is async, but closing or cancelling the editor
did not abort it, so a late-arriving valid response still called onSave and
applied a template the user had already dismissed. Track a validation token
that is bumped on close and ignore any validation result whose token is stale.
* Record native lease expiry when loading a picked GGUF from the chip
The pending-native-model chip loaded via stageOrLoad directly, bypassing
loadNativeModelIntent, so activeNativePathExpiresAtMs was never recorded for a
chip-loaded file. A later reload then either skipped the lease-expiry guard
entirely (expiry left null) or compared against a previously loaded file's
stale expiry, so reload could reuse an already-pruned token or wrongly block a
still-valid one. Route the chip through loadNativeModelIntent, which builds the
same selection and records the expiry.
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* Prefer sidecar template for a directly selected local GGUF file
A direct .gguf file path read its embedded chat template without checking the
parent directory for a maintained sidecar (chat_template.jinja /
tokenizer_config.json), while directory and variant selections already prefer
the sidecar. That let the config editor preview or save a stale embedded
template for the same model depending on how it was selected. Check the parent
directory sidecars first, then fall back to the embedded copy, and cover both
paths with tests.
* Resolve cached chat template per revision, newest first
The earlier change searched every cached snapshot for a sidecar before
considering any snapshot's embedded GGUF template, which let an obsolete sidecar
from an older revision override the newest revision's template. Restore
per-snapshot resolution (newest first): a revision's sidecar still supersedes
its own embedded GGUF copy, but a newer revision is no longer overridden by an
older revision's sidecar.
* Preserve autoload transport conflicts and surface background busy downloads
- When a Hub autoload hits a transport conflict, keep pendingHubAutoLoad bound
instead of clearing it. Clearing it re-keyed the download surface and its
cleanup cancelled the conflict the toast tells the user to resolve, so the
Hub resume affordance was gone the moment it appeared. Return early on
conflict, mirroring the started branch, so resolving it from the Hub still
auto-loads on completion.
- The background-download branch handled started and conflict but silently
dropped a busy outcome, leaving the user with no feedback when a peer variant
of the same repo was already downloading. Surface the same busy toast the
autoload path uses.
* Fix context length, GGUF template, fetch state and lease expiry bugs
Keep explicit context length values instead of collapsing to null at
native. The collapse made the slider jump back at the native maximum
and made Reload load the previous context instead of the chosen one.
Prefer the first split when resolving a GGUF without a variant. Later
splits carry no chat template metadata, so picking the largest file
could return no template for a sharded model.
Clear stale fetch state when template and metadata lookups retry, so
a previous terminal error is not shown while a new fetch is running.
Record native path lease expiry together with the token when a load
commits. The expiry was written by only one load path and even when
the load did not start, so a reload could be blocked with an expired
file message for a still valid token.
* fix(model-picker): resolve review findings across config, inventory, and templates
- Apply remembered per-model config in the training-compare chat handoff so a
prior model's customContextLength no longer leaks into the next load
- Match GGUF variant labels with the inventory extractor too, so cached
no-quant-token files resolve their default chat template
- Show "Auto" instead of a fabricated 32768 when native context is unknown
- Reuse the identical staged auto-load object on same-pick so a re-pick during
download pre-flight no longer disarms auto-load via "busy"
- Union supports_vision when deduping cross-cache inventory rows
- Serve hidden-model needles from a new GET /api/hub/hidden-models endpoint and
merge them client-side, covering runtime-configured RAG embedders
- Clamp GET chat templates to MAX_CHAT_TEMPLATE_BYTES (route + jinja sidecar),
matching the validate endpoint's contract
- Lower-clamp stored customContextLength to shared CONTEXT_LENGTH_MIN
- Wipe unsloth_chat_load_on_selection in Settings "Reset all"
- Drop stale pendingHasContext comment describing deleted staging machinery
* Fix stale defaults cache, token in query string and rounded up context ceiling
Refresh cached chat template and max position data when a model update
completes. Send the HF token for model config requests in the dedicated
header instead of the URL. Snap the native sequence length ceiling down
to the nearest step so the slider cannot exceed the declared maximum.
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* Fix compare pane reverting active checkpoint on non-GGUF load
Re-read runtime params after setCheckpoint so the fresh checkpoint is
kept instead of being overwritten by the pre-setCheckpoint snapshot.
* Send the HF token via header for the vision and embedding checks
checkVisionModel and checkEmbeddingModel still passed the HuggingFace
token as a ?hf_token= query parameter, so it landed in server access
logs, proxy logs, and browser history. Move them to the
X-Unsloth-HF-Token header like getModelConfig already does, and accept
the header on the check-vision and check-embedding routes with the
existing query parameter kept as a fallback for older clients.
* Cap the chat template on the model load path
The load endpoint accepted an unbounded chat_template_override, so a
direct caller could hand llama.cpp an arbitrarily large Jinja template
even though the frontend, the validate endpoint, and the read paths all
enforce the 64 KiB limit. Reuse MAX_CHAT_TEMPLATE_BYTES in the
LoadRequest validator, rejecting oversized templates with a fast
character-count check before the exact UTF-8 byte check.
* Protect existing per-model configs during legacy migration
When the one-time legacy import pushes the store over budget, eviction
now protects the entries the user already has and drops only the
just-migrated legacy entries, so importing old load settings can never
discard a newer per-model config.
* Reset clears the context override instead of pinning the native value
Reset wrote the discovered native context into customContextLength for
GGUF models, but isDefaultConfig treats any non-null customContextLength
as an explicit pin, so Reset with Remember enabled persisted a fixed
context and future loads stopped using the native auto context. Reset
now restores the full default (customContextLength null); the native
value is still shown through the existing display fallback.
* Bound chat-template sidecar reads to a size limit
The chat_template.json, tokenizer_config.json, and Hub-downloaded sidecar
readers decoded and json-parsed the whole file before the extracted
template hit the 64 KiB response cap, so an oversized metadata file could
exhaust memory. Read them through a bounded reader (4 MiB envelope) that
returns None when the file is larger, matching the existing chat_template.jinja
size guard. Adds tests for oversized tokenizer_config.json and chat_template.json.
* Keep the native-path token and lease expiry in sync
Rollback after a failed reload restored the previous token but left the
failed load's expiry in the store, so a later reload could be falsely
blocked as expired (token A paired with load B's lease). Restore the
previous lease alongside the token, and clear the expiry wherever the
token is cleared on a non-GGUF transition, so the two never diverge.
* Clear the native file lease on compare-pane loads
* Studio: add regression tests for the model-picker per-model-config
Guard the specific regressions that reverted the predecessor change:
- backend pytest (studio/backend/tests/test_model_picker_regression.py):
infra-model hiding, HF token via header with query fallback, and the
chat-template byte caps.
- source contracts (tests/studio/test_model_picker_contracts.py): the token
stays out of the URL, the context ceiling is floored, the native lease is
cleared on compare-load and restored on rollback, the default caches key on
the inventory version, and the hidden needles stay present.
- Playwright E2E (tests/studio/playwright_model_config.py) wired into
studio-ui-smoke.yml on port 18898: Context Length persists across a reload,
Reset clears the stored override, and infra models are absent from the picker.
- optional GPU-gated inference smoke (tests/studio/test_gpu_inference_smoke.py)
that auto-skips on GPU-less CI and stays short on a GPU.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: model pinning, row menus, hub inference settings, and inventory filters
Pinning
- Add a pinned models store (localStorage) with repo and per-quant pins
- Pinned section in the model selector's On Device list and the hub inventory,
with newest pins first so Pin to top lands on top
- Deleting a repo drops its pins
Row menus
- Replace loose row icons with a shared 3-dots menu (pin, reveal in file
manager, copy identifier, copy path, delete) on picker rows, hub quant rows,
the hub run bar, and on-device inventory rows
- Menus only render for models actually on disk; platform-aware reveal labels
- Backend: cached-model-path and reveal-cached-model endpoints resolving
managed HF-cache repos only
Hub inference settings
- Gear in the GGUF run bar opens an Inference settings dialog reusing the chat
page's controls: model config (context length, KV cache, speculative
decoding, chat template), system prompt, reasoning, sampling, tools and
retrieval
Inventory
- Model-type filter (text, vision, embedding, STT, TTS, diffusion) beside the
sort pill, both with a sort icon, capped widths and truncation so the
On device heading never wraps
- Unsloth-owned repos without an upstream provider logo fall back to the
Unsloth mascot avatar
- Discover / On Device tabs widened; hub search bar narrowed to match
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: revert the Unsloth mascot avatar fallback
Unsloth-owned repos without an upstream provider match go back to the
colored-initial tile, and unslothai is no longer a relabeled owner.
* Studio: run-bar options on single models, and aligned type/capability filters
- Give single-model (non-GGUF) run bars the same 3-dots options menu and
settings gear as GGUF, at repo level
- Drop Pin to top from the run-bar menus; pinning stays in the On Device list
- Add an Image to text (diffusion) capability with detection, and surface it
in both the hub Discover capability filter and the On Device type filter
- Align the On Device type filter with the Discover capability options and
share the same detection so both dropdowns match
* Studio: apply hub inference config on reload, eject action, and run-bar polish
- Fix inference settings not applying: the hub dialog now writes the config to
the runtime before reload, matching the chat page (selectModel reads runtime
state, not the selection)
- Order the settings gear before the 3-dots menu in the run bars
- Replace the loaded-model run-bar action (New Chat) with Eject, wired through
the inspector to the hub's ejectModel
- Truncate the results heading so a long search query clips instead of
overlapping the header pills in split view
- Use a plain magnifying-glass icon for the no-results empty state
* Studio: fix GPU settings loss, load guards, pins, filters, and cached paths
Reloading a model from the chat sidebar or the hub gear dialog rebuilt the
per-model config without the GPU memory fields, so manual GPU layers, MoE
placement, and the GPU pick were reset on every reload and could be saved
over a remembered config. The active config now comes from a shared
useActiveModelConfig hook that carries the GPU fields for GGUF models, and
the sidebar remount signature tracks them through a shared gpuFieldsSignature
helper.
The in-flight load guard lived in a ref inside each useChatModelRuntime
instance, so the chat page, hub page, and gear dialog could not see each
other's loads. A load started from the gear dialog left the hub page free to
eject the model mid-reload or start a second concurrent load. The runtime
store now records the loading pick, selectModel checks it across instances,
and ejectModel refuses with a toast while any load is in flight.
The cached-model-path endpoint matched GGUF files by basename and excluded
only mmproj, so Copy path and Reveal could return an MTP drafter for a quant
and returned 404 for directory layouts like BF16/model-00001.gguf. Variant
files are now resolved from snapshot-relative paths with the same drafter,
mmproj, and big-endian exclusions as the load path, shared through a new
_main_variant_gguf_label helper.
Hub and picker fixes:
- rename the diffusion capability label from "Image to text" to
"Image generation", since it detects image generators
- validate pinned quants through the cached variant listing, keep the last
verified set while revalidating, and drop deleted quants immediately
- pass a measured scroll margin to the on-device virtual list so rows past
the overscan stay visible below the pinned block
- keep the delete menu for stopped partial safetensors downloads
- give the inventory type filter a reset in Clear filters, a truthful empty
state with a Show all types action, and hide it on the datasets view
- order picker pinned rows by pin recency, include pinned matches in the
empty-state check, and sync pins across browser tabs
- count only the visible rows in the On device list header
Tests: contract checks for each fix in test_model_picker_contracts.py and a
backend test for the variant label selection.
* Studio: reveal cached models in Windows Explorer under WSL
The reveal endpoint only branched on macOS, Windows, and generic Linux.
Under WSL the Linux branch spawned xdg-open, which is missing on a stock
distro without a Linux desktop, so the request failed with a 500 and the
UI showed a failed to open file manager error.
WSL is now detected with the existing helper and the path is converted
with wslpath before opening explorer.exe, selecting the file the same
way native Windows does. Directories open directly. When interop is
unavailable the old xdg-open fallback still runs. The macOS, native
Windows, and native Linux branches are unchanged, and the Tauri app is
covered since its hub reveal calls this same local endpoint.
Tests: platform guards for the WSL reveal, the interop fallback, and
the unchanged native Linux behavior in tests/studio/test_reveal_file_manager.py.
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* Adjust model picker row spacing and cogwheel hover consistency
* Studio: exact hidden model ids and newest revision cached paths
A custom RAG embedder repo was published to the frontend as a basename
substring needle, so a generic name like org/model could hide unrelated
models in the pickers. The hidden-models endpoint now sends full repo ids
that are matched exactly.
Copy path and Reveal picked a GGUF variant from an arbitrary cache
revision when the same file existed in more than one. The newest revision
now wins, matching the whole repo lookup.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix model picker GPU config, metadata, and cache selection
Load each compare model with its saved GPU memory mode, GPU layers, CPU MoE layers, and selected GPU IDs. Reconcile saved GPU IDs with the current hardware. Include the active native GGUF path token in metadata checks. Search all Hugging Face cache roots when resolving cached models and select the largest visible cache entry. Remove obsolete barrel exports and the staging-only GPU memory helper.
* Studio: hide hub inference settings gear for now
The cogwheel in the hub download cards is out of scope for this PR. The
dialog component stays in place and a TODO marks where the button
returns in a future PR.
* Refresh hidden model matchers
* Fix GGUF detection, compare context pin, and picker delete staleness
Treat any pick with a GGUF variant as GGUF in selectModel so the first
load after downloading an uncached quant validates and sizes with the
right GPU settings instead of unloading the current model on a wrong
preflight. Variant picks now also set isGguf on their selection meta.
Stop compare panes from inheriting the active model's context pin when
their own saved config says Auto. Null context in a remembered config
now means no pin, matching how the pane settings are shown.
Route picker deletes through the hub inventory client, which
invalidates the HF cache scan and the variants cache. The legacy
delete route left the scan cache warm, so deleted models reappeared
in the picker until the TTL expired. Removed the now unused legacy
delete client and updated the contract test to match.
* Studio: fix stale GGUF load-marker ordering test
The load-in-flight marker still precedes the hub-download guard and the
unload, but the llama_extra_args inheritance that used to sit between the
marker and the guard now runs ahead of the GGUF branch, so it is no
longer a landmark inside the sliced source. Drop it from the ordering
assertion and keep the marker -> guard -> unload invariant.
* Studio: fix per-model config edge cases in compare loads and saved defaults
- chat-settings-sheet: gate the MTP fallback note and context/VRAM warning on
the broader isGguf (variant, loaded gguf context, or .gguf suffix) instead of
isLoadedGguf, so direct-file and custom-folder GGUF loads still surface
those diagnostics.
- shared-composer: a compare pane's context now comes from its own config only
(a saved pin, else null for Auto/native). It no longer inherits the active
model's shared snapshot, which resolveFitMaxSeqLength treated as an explicit
pin and could load a pane at another model's context (VRAM/OOM), matching the
single-model load path.
- model-config-page: when an auto-fit GGUF is saved with fixed GPU layers
(Manual) and Remember, pin the displayed fitted context so a later fresh load
keeps the placement instead of sending native/0 and recreating the OOM.
- per-model-config: treat Auto GPU memory mode and Auto/default speculative type
as follow-global defaults; do not persist them as per-model overrides so later
global preference changes keep applying.
* Studio: gate vision capability on GGUF projectors and bound remote template downloads
- cache_inventory: only mark a cached repo vision-capable when it holds an actual
GGUF mmproj projector, not any file whose name merely contains "mmproj" (e.g.
mmproj_config.json), matching the runtime's GGUF-only projector detection.
- picker/service: pre-check the remote file size before downloading an uncached
repo's chat template / tokenizer config, so a maliciously large sidecar is
skipped instead of fetched and retained in full, mirroring the size gate the
local-file path already applies.
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* Studio: add source-contract guards for the per-model-config edge-case fixes
Guard the four per-model-config fixes against silent regression in CI:
- local GGUF diagnostics gate on the broad isGguf, not the variant-only isLoadedGguf
- fixed-layer GGUF saves pin the displayed context
- Auto GPU mode and Auto/default speculative are not persisted as per-model overrides
- a compare pane's context comes from its own config, not the active model's snapshot
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* Studio: clear manual GPU knobs on Default and resolve local embedders before repo-id
- model-config-page: switching GPU Memory back to Default now clears the Manual-only
knobs (gpuLayers/nCpuMoe/selectedGpuIds); otherwise a remembered config kept stale
pins that a later load re-applied when the global GPU preference was Manual, despite
the page showing Default.
- routes/models hidden_model_matchers: resolve an existing local path before the repo-id
regex, mirroring is_hidden_model, so a local embedder shaped like "models/embedder" is
hidden by exact path instead of leaking as a chat model.
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* Studio: add _is_mtp_drafter to the model_config stub in the export-paths test
routes/models.py imports _is_mtp_drafter from utils.models.model_config at module
load, but the lightweight stub in test_export_absolute_paths.py did not provide it,
so loading the module under the stub raised ImportError on Backend CI. Add the stub.
* Studio: read a picked GGUF's chat template through the native path lease
The picker chat-template GET has no native-path-lease plumbing, so a
desktop-picked (drag-drop) GGUF could not show its default chat template
in Run Settings until the model was loaded: the endpoint only receives
the display label, not the leased file path.
Read the embedded template through the existing lease-aware
/api/inference/validate probe instead. A new include_chat_template flag
resolves the granted canonical path and returns the GGUF's own embedded
template, never a sibling sidecar (the grant authorizes just that one
file); it skips the training guard like include_context_length and is
bounded by MAX_CHAT_TEMPLATE_BYTES. The frontend fetch mints a one-shot
validate-model lease when a native token is present and keeps the plain
GET path for HF and allowlisted local models.
Adds backend and source-contract regression tests.
* Studio: call worker.direct_wheel_url in the ROCm wheel-url test
The ROCm Mamba/SSM test referenced worker.py's private _direct_wheel_url,
but the worker imports the wheel helper under its public name
direct_wheel_url (utils.wheel_utils). When the worker module loads (its
imports resolve in CI), worker_mod._direct_wheel_url raised AttributeError;
the test only masked it by skipping when the worker could not be imported.
Call the name that actually exists so the assertion runs; it still returns
None for an empty cuda_major (ROCm).
* Studio: reset max sequence length to the app default, not the loaded value
For a non-GGUF active model, the per-model config seeds maxSeqLength from
the loaded runtime value so the panel opens showing the running context.
Reset set config.maxSeqLength to null, but the null fallback resolved back
to that captured runtime value, so the field kept showing the old custom
length and the config saved/reloaded it again. A remembered or active
max-length override therefore could not be cleared from Run settings.
Fall the null/default case back to the app default (clamped to the model's
native ceiling) instead of the active runtime snapshot, so Reset actually
clears the override. The initial view is unaffected: an active model's
config.maxSeqLength is already non-null, so it still shows the loaded value.
Adds a source-contract regression guard.
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* Studio: persist default max length, refresh deleted quants, hide non-chat locals
Three follow-up fixes from review of the per-model-config picker:
- Max sequence length: the persisted per-model record now keeps config's
maxSeqLength (null after Reset) so isDefaultConfig can clear a remembered
override; the resolved app-default is substituted only into the load
request, never the saved record. Previously Reset saved the concrete
default and left the model pinned/remembered.
- GGUF variant expander: deleting a downloaded quant from a repo that still
has other cached quants now bumps the expander refresh key, so the removed
quant stops showing as downloaded and clickable (which would try to reload
the deleted file) until the repo is collapsed and reopened.
- Local picker rows: require capabilities.canChat before listing a local
models-folder / LM Studio row. A weightless folder (only config.json) is
classified non-chat, and toLocalModelInfo drops capabilities, so selecting
such a row would try to load a path the inventory already marked non-chat.
Adds source-contract regression guards for all three.
* Fix compare-pane and Reset context defaults in model picker
Two related per-model-config default regressions:
- A non-GGUF compare pane with no saved maxSeqLength fell back to the
active model's shared runtime snapshot, so comparing a saved 128K model
against an unconfigured pane loaded the latter at 128K and could OOM. It
now falls back to the shared app default (DEFAULT_MAX_SEQ_LENGTH), the
same fallback the single-model config path uses.
- contextAtDefault treated an explicit customContextLength equal to the
native ceiling as a default, which wedged the Reset button disabled for
a deliberate pin-to-native. It now counts as default only when there is
no override at all.
DEFAULT_MAX_SEQ_LENGTH becomes a single exported constant in
per-model-config.ts so the single-model config and the compare path share
one source of truth. Adds source-contract guards for both fixes.
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* Skip over-cap remote Jinja templates so the tokenizer template wins
The remote chat-template resolver bounded raw chat_template.jinja downloads
only by MAX_TEMPLATE_METADATA_BYTES (4 MiB), then returned the first
non-empty Jinja unconditionally. The picker route drops any template larger
than MAX_CHAT_TEMPLATE_BYTES (64 KiB), so an uncached repo whose
chat_template.jinja sits between 64 KiB and 4 MiB returned no template at
all, even when a valid smaller tokenizer_config.json template existed. The
local path already skips oversized .jinja files and falls through.
Gate the extracted Jinja on MAX_CHAT_TEMPLATE_BYTES and continue searching
when it exceeds the cap, matching _chat_template_from_jinja_file. The 4 MiB
download bound stays for JSON files that merely embed a small template. Adds
a regression test that a big Jinja plus a valid tokenizer config resolves to
the tokenizer template.
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* Guard legacy per-model-config migration idempotency
The v1->v2 localStorage migration (unsloth_load_settings ->
unsloth_model_configs) runs on every store read, so it must migrate exactly
once and never re-run, duplicate, or clobber a newer per-model config on a
reload or restart. That was covered only by a manual proof, so add durable
guards:
- Source-contract test pinning the three idempotency layers (the in-memory
legacyMigrationChecked guard, the persistent unsloth_model_configs_migrated
flag set in every terminal branch, and the non-overwriting Object.hasOwn
merge-skip) plus the readMap invocation. Reddens if any layer is dropped.
- Playwright model-config E2E: promote the legacy-migration step to a gating
check (soft_fail, which gates under the CI STUDIO_UI_STRICT=1) that the
migrated value is preserved and the flag is set, then reload again with a
fresh legacy seed present and assert the stored key set is unchanged, so a
second reload cannot re-migrate, duplicate, or clobber.
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* Note the migration E2E now gates idempotency under STUDIO_UI_STRICT
* Tighten model-picker per-model-config code comments
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: shimmyshimmer <shimmyshimmer@users.noreply.github.com>
Co-authored-by: Unsloth <michaelhan@Michaels-MacBook-Pro.local>
Co-authored-by: oobabooga <112222186+oobabooga@users.noreply.github.com>
* Studio: make repeated tab switches feel immediate
* Keep cached Studio navigation data fresh
* Make first Studio tab visits responsive
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Serve range requests uncompressed for immutable assets (PR #7271)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
Co-authored-by: test <test@test.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
shimmyshimmer