* Let a decode failure degrade instead of escaping a fail-closed helper
Pinning utf-8 makes a read that used to return mojibake on Windows raise
instead. 33 of those reads sit under a handler catching OSError or
json.JSONDecodeError but not UnicodeDecodeError, which subclasses
ValueError, so a corrupt file would now escape a helper written to return
a default. Adds UnicodeDecodeError to those tuples only.
* Treat an undecodable install lock as stale instead of retrying forever
* Pin utf-8 on shipping-code text I/O instead of the operator locale
113 read_text/write_text/open call sites across unsloth, studio and
unsloth_cli let locale.getencoding() decide the encoding. That is utf-8 on
the Linux and macOS runners and cp1252 on a stock Windows install, so the
same file decodes differently for a Windows user and silently produces
mojibake or raises UnicodeDecodeError.
Adds tests/test_runtime_text_encoding.py to keep it that way. It resolves
openers through each file's own imports rather than a fixed list of module
names, so an aliased tarfile.open or a local from PIL.Image import open is
not asked for an encoding it does not take.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Scan tracked files only and resolve the unbound Path calling forms
* Honour PEP 263 when scanning sources and migrate a legacy JSONL before appending
* Scope guard imports lexically and only migrate a legacy file when it round-trips
* Leave a legacy JSONL untouched and resolve path aliases in the foreign-opener check
* Tighten comments
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Add Agents settings tab for unsloth start
Adds a Settings > Agents tab documenting the `unsloth start` command:
quickstart, supported agents with click-to-copy commands, model
selection, common options, remote Studio setup, argument pass-through,
and a dry-run preview. Agent CLIs found on PATH are badged as installed.
Also removes the "New" badge from the System and Chat tabs.
* Use official brand logos for agents, invert Ollama and OpenRouter in dark mode
Claude Code and OpenAI Codex now use the Anthropic and OpenAI logos from
the provider-logos registry; agents without an official asset keep the
monogram tile. Also inverts the Ollama and OpenRouter logos in dark mode
so their monochrome marks stay visible.
* Title Agents tab "Agents (unsloth start)" and move it below Connections
The in-tab header now reads "Agents (unsloth start)" while the sidebar
label stays "Agents". Reorders the tab to sit below Connections.
* Address review: guard PATH detection, fix copy timeout, OS-aware remote snippet
- Only probe agent PATH in the desktop app on a loopback backend, so
Installed badges are not driven by a remote server's environment.
- Show the "none found" note only when detection actually ran and
returned empty, not when the call failed.
- Share one copy hook that resets its timeout on rapid clicks and clears
it on unmount.
- Render the Remote Studio snippet with PowerShell syntax on Windows.
- Note that --no-launch can still load a model when --model is set.
- Drop unused quickstart translation keys.
* Add interactive Agents command builder
* Add local subagent command guidance
* Add official coding agent icons
* Use client OS for remote commands, fix copy a11y and model wording (#7303)
- Pick the remote snippet shell from the client platform, not the server deviceType
- Single-line the model examples so they paste in POSIX, PowerShell and cmd
- Split the pass-through block into independent one-command copies
- Derive detection visibility instead of clearing state in the effect
- Announce copy success to assistive tech
- Correct the quickstart/model copy: bare start uses the loaded model
* Shell-quote the model, forward the HF token, and fix the quant placeholder
- Quote the --model value in the generated and subagent commands so a local
path with spaces or metacharacters stays a single argument (client-OS aware)
- Pass the saved Hugging Face token to listGgufVariants so gated repos resolve
- Show 'No separate quantization' instead of a stuck 'Loading quantizations...'
when a model has no variants; clear the failure once a later request succeeds
* Fix Agents command discovery and routing
* Unsloth start improvements: download progress, server reuse, and safe model switching (#7313)
* 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
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix Studio re-exec compatibility
* Recheck sidecar reservation after inference drain
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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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>
* Unsloth start: add local subagents for Claude Code, Codex, OpenCode and Pi (#7326)
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.
* Fix Agents builder defaults and flag validation
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix Agents variant and provider fallbacks
* Fix local model and Pi subagent edge cases
* Agents tab: flag the Codex row when the loaded model is not GGUF
* Agents tab: target the active Studio server, wrap narrow rows, index the tab's search terms
* Agents tab: build copied commands from the browser-reachable Studio and show the key placeholder
* Preserve cache load ids and path variants in built commands for PR #7312
A GGUF outside the active Hugging Face cache only loads by its snapshot
path, so keep that load_id for --model while still listing the row by repo
id. Path based models carry their quant in --gguf-variant rather than a
":variant" suffix, and the active selection now keeps the variant inference
status reports for them.
* Agents tab: index the intro for agent-name searches and keep long commands inside the panel
* List GGUF variants from the cache the command loads from for PR #7312
A snapshot outside the active Hugging Face cache was offering the remote
variant list, so a quant absent from that snapshot could be selected and
the generated command would fail to load it.
* Agents tab: omit --api-key so the CLI can replay a saved key for the base
* Agents tab: label the indexed heading rows and fall back to the active desktop API base
* Agents tab: name every supported agent in the indexed intro for PR #7303
* Send the cached GGUF load path and fix the agents tab search targets for PR #7312
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Tighten the agents tab comments for PR #7303
* Build the agents tab example commands from the active Studio base for PR #7303
* Keep the resident model on its active cache load for PR #7312
* Tighten the agents tab and cached GGUF comments for PR #7312
* Take the agent command shell from the Studio host for PR #7303
* Stop emitting snapshot paths as --model and keep unsloth start searchable for PR #7312
* Pick the command shell from where the CLI runs for PR #7303
* Match a path load by its advertised id and follow the resident model for PR #7312
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Keep an explicit quantization and retire superseded native-grant labels for PR #7312
* Scope the remembered quant, stop following unloaded models and keep local GGUF paths for PR #7312
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Stop shadowing the path classifier, match snapshot ordering and sequence status polls for PR #7312
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Release stale native-grant picks, keep local GGUF identities and index snapshot aliases for PR #7312
* Index inactive-cache snapshots, widen local GGUF detection and clear retired quants for PR #7312
* Classify cached repos by snapshot, merge repo ids case-insensitively and keep loose GGUFs variantless for PR #7312
* Fix snapshot alias, partial split and mmproj-only handling for PR #7312
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Trust scanned model_format and drop incomplete snapshot ids for PR #7312
* Exclude mmproj and partial downloads, keep path case and drop duplicate scan for PR #7312
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Restrict revision aliases and require complete snapshot variants for PR #7312
* Index revisions individually and hide partial variants for PR #7312
---------
Co-authored-by: shimmyshimmer <107991372+shimmyshimmer@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: oobabooga <oobabooga4@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Fixes#7244
The Studio per-model config dropdown only surfaced bf16, q8_0, q5_1,
and q4_1 even though llama.cpp already accepts q4_0, q5_0, iq4_nl, and
f32. Add the missing options to KV_CACHE_DTYPES and align API field
descriptions with the backend _valid_cache_types set.
Co-authored-by: Daniel Han <danielhanchen@gmail.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
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* 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
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* 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
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* 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
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* 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.
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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
for more information, see https://pre-commit.ci
* 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
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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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: GPU memory dropdown — llama.cpp --fit on and manual gpu-layers/cpu-moe
* Studio: simplify GPU memory changes (reuse ParamSlider, GPU_LAYERS_ALL, loadedGpuMemoryFields helper)
* Studio: GPU picker — choose which GPUs a GGUF model loads on (gpu_ids)
* Studio: simplify GPU picker (share /api/system fetch, validate gpu_ids)
* Studio: GPU picker review fixes (gate relative indices, no cross-model leak, validate, types)
* Studio: group GPU controls under a collapsible GPU section
* Studio: GPU feature review fixes (fix fit-ctx test, behavior-test the floor, comment accuracy)
* Studio: make GPU a top-level settings section (not nested under Model)
* Studio: flatten GPU controls into the Model section, group by GPU/context/generation
* Studio: move GPU Memory to the bottom of Model with its dependent controls beneath it
* Studio: move GPU Memory below Tensor Parallelism and GPUs below GPU Memory
* Studio: tighten GPU Memory and GPU Layers tooltip copy
* Studio: fix fit-mode context slider track-click, restore GPU Memory tooltip, shorten fit dropdown label
* Studio: GPU Memory tooltip one mode per line, briefer
* Studio: note HIP_VISIBLE_DEVICES (ROCm) in the GPUs picker tooltip
* Studio: narrow the GPU Memory dropdown to fit the shortened label
* Studio: use 'llama.cpp --fit' in the GPU Memory tooltip for consistency
* Studio: allow Tensor Parallelism in Manual GPU mode
* Studio: graduated MoE-on-CPU offload (--n-cpu-moe) replacing the all-or-nothing toggle
* Studio: size the MoE-offload slider for staged (deferred-load) models
* Studio: share one GGUF header walk for the context-length and MoE-count readers
* Studio: size the GPU Layers slider for staged models (one staged-header read)
* Studio: move Tensor Parallelism below the GPUs picker
* Studio: GPU split (--tensor-split) per-GPU model share in Manual mode
* Studio: tolerate whitespace in GPU split input, move it below GPU Layers
* Studio: rename the GPU split control to "Split ratio"
* Studio: Split ratio sends explicit even input; fix blank=free-VRAM (not even) copy
* Studio: tighten llama.cpp --fit VRAM margin with --fit-target 512
* Studio: GPU memory review fixes (rollback re-baseline, single-GPU TP gate, accurate copy)
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* Studio: move Split ratio below MoE Layers on CPU
* Studio: address PR review (fix GPU-info hydration race, share fit context-length across load paths)
* Studio: address codex review (manual single-GPU TP guard, GPU-aware spec defaults in fit/manual, GGUF-only context/preference)
* Studio: address codex review round 2 (gpu_present seed, single-GPU tensor-split guard, staged manual-knob reset, strip inherited offload flags)
* Studio: address codex review round 3 (strip inherited --n-cpu-moe, CPU-fallback warning in Manual mode)
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* Studio: address codex review round 4 (preserve pinned fit context across a later Apply)
* Studio: address codex review round 5 (honor GPU picker for diffusion GGUFs, clear fit pin on cross-model switch)
* Studio: preserve the pending GPU Memory mode when staging a model
* Studio: pin diffusion GPU device order and reset GPU-memory state for diffusion loads
* Studio: address codex review round 6 (fit-Auto rollback context, preserve manual non-tensor split modes, persist GPU mode on load not select)
* Studio: persist the applied GPU Memory mode, not the requested one (skip diffusion loads)
* Studio: replace Manual-mode split-ratio field with per-GPU layer sliders
* Studio: clarify per-GPU layer split hint for tensor-parallel mode
* Studio: address codex review round 7 (allow GGUF gpu_ids past the legacy guard, replay GPU-memory fields on respawn)
* Studio: address codex review round 8 (size the validate preflight like the load in fit mode, across both load paths)
* Studio: skip the training-OOM guard for llama.cpp --fit GGUF loads (they spill to RAM)
* Studio: drop the now-redundant compare-path validate sizing (the --fit guard skip makes it moot)
* Studio: address codex review round 9 (keep the training guard for fit loads, forward gpu_ids to validate, strip inherited manual tensor-split)
* Studio: address codex review round 10 (gate GPU-memory adoption on is_gguf, record manual knobs only in Manual mode)
* Studio: handle diffusion GGUFs symmetrically in the GPU Memory controls (preserve the standing mode preference, hide the inapplicable mode/TP controls)
* Studio: remember the GPU Memory settings per model
* Studio: consolidate --fit mode and Manual mode into a single Manual mode
* Studio: preserve the per-GPU layer split across GPU Layers changes
* Studio: trim overly long GPU Memory comments
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* address GPU memory config review comments
* trim redundant GPU memory tests
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reconcile manual-mode TP drops with the #6659 drop-site invariants
* Preserve quantized KV in manual --fit, charge GGUF companions in full, reconcile GPU pick on load
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Clear stale GPU baseline on non-GGUF loads so it can't read as dirty
* Fix no-context-shift test for the conditional -c flag
* Credit manual GPU-layer offload for cached HF GGUFs
* Reset per-model load knobs on GGUF quant switch
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Strip inherited tensor-split when manual ratio is cleared
* Match auto-load validation to safetensors placement
* Reset editable manual knobs after Auto GGUF loads
* Record a single device for diffusion GPU picks
* Reset per-model GPU knobs before applying saved settings
* Address review comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Guard manual tensor splits and keep remembered context on auto-load
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Snapshot compare knobs, seed splits from free VRAM, flag zero-offload loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Exempt CPU-only loads from the guard floor and harden compare and reseed paths
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reach full offload from the layers slider and charge extras drafters in the guard
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Warm the GPU device cache before pick reconciles and disable staged GPU controls
* Align the training guard with inherited extras, spec mode, and compare targets
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Hide GPUs from companion-less zero-offload loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Size diffusion picks per device, own manual offload flags, reject XPU picks
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Drop tensor flags at zero layers and exempt CPU-pinned drafters
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Allowlist the zero-layer tensor parallel drop site
* Keep validate and load guards on the same extras and refresh stale baselines
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Drop mismatched manual tensor splits before launch
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Gate XPU picks on the real backend field and harden split and hydration paths
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Weight full GPUs as zero, clamp split shares, and refine the zero-layer mask gate
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Carry fit context across mode changes and align drafter and picker gates
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Catch variant switches, uncached diffusion repos, and text-only mmproj skips
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Check companions on the first device and size native and remote zero-layer loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Replace the training guard's precise VRAM modeling with a conservative bound
* Baseline context pins on non-GGUF hydration and reprobe list-seeded staged GGUFs
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* Size manual splits by their largest share and preserve resolved context from Default
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Default-deny unsized required companions and price KV at the effective cache dtype
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reserve MTP draft KV and MLA target-copy in the training guard
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Size tensor-parallel loads per device and show GPU controls for native GGUFs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reserve MTP overhead for uncached remote GGUFs and the mmproj runtime factor
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Drop the training-coexistence VRAM estimation this PR added
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* Gate remembered load settings to GGUF picks
* Lock the remaining load-time controls during a staged load
* Clear the stale native-path token on compare loads
* Drop a stale guard reference from the zero-offload masking comment
* Seed GPU baselines from the rollback response and drop never-emitted offload flags
* Match validate's training guard to load and keep the native reload token
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Trim verbose GPU-memory comments
* Thread the variants header walk off the event loop, honor device pins on zero-offload, and hold staged GPU edits
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Honor manual placement and classify pinned zero-offload loads
* Close diffusion admission and status hydration gaps
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Check the actual diffusion GPU during training
* Align staged baselines and manual reload dedupe
* Fix GGUF placement and rollback state
* Harden manual GGUF placement boundaries
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Remove unused resolve_tensor_parallel import in llama_cpp.py
The name is used only in llama_server_args.py, routes/inference.py, and tests,
not in llama_cpp.py; the unused hoisted import trips the import-hoist verifier
in the source-lint CI job.
* Fix diffusion GPU dedup and training guard for non-numeric device tokens
The diffusion runner drives only its single lowest device and the backend
records that one device (self._gpu_ids = [sorted(gpu_ids)[0]]), but the reload
dedupe compared it against the full requested list, so a multi-GPU pick that
resolves to the same device forced a needless reload. Normalize the request the
same way for a loaded diffusion model in both _already_in_target_state and the
route _request_matches_loaded_settings.
The chat-during-training coexistence guard called int() on the single-device
token and hard-rejected when it could not parse. A non-numeric token (a CUDA
UUID / MIG handle) now sizes against the whole visible pool like the GGUF guard
instead of falsely blocking the load, and an empty token (a CPU-only runner such
as a CPU diffusion GGUF) is allowed outright since it uses no GPU VRAM.
* Tighten comments added by the GPU memory config changes
* Harden GGUF placement from independent review: VRAM sizing, diffusion TP reset, tensor_split validation
- Training coexistence guard: a single-device runner pinned through an
unresolvable UUID/MIG token was sized against the aggregate visible-VRAM pool,
so a load could pass on capacity it cannot use and then OOM active training.
Size against the worst-case visible device (min free) instead, keeping the
guard's documented default-deny contract. The empty-token (CPU-only runner)
allow path is unchanged.
- Diffusion startup: _start_diffusion_server now resets self._tensor_parallel to
False alongside the other placement resets. A prior tensor-parallel chat load
(process killed but not fully unload-reset) otherwise left /status misreporting
tensor parallelism and made an identical diffusion re-Apply reload against the
stale state.
- tensor_split: reject negative / non-finite / all-zero splits up front. They
were dropped at launch but still compared raw in the reload dedupe, so an
identical Apply reloaded indefinitely.
- Tests: the shared httpx stub was incomplete and, installed via setdefault
before real httpx loaded, broke a combined pytest run (collection errors on
httpx.Response). Import the real installed httpx instead.
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* Studio: hide infra models from the hub cached inventory
The hub inventory scans behind /api/hub/cached-gguf and /api/hub/cached-models
returned the llama.cpp install validation probe (ggml-org/models) and the RAG
embedder (unsloth/bge-small-en-v1.5[-GGUF]) as on-device models. Share the
hidden-model check from routes/models.py via utils/models/hidden_models.py and
apply it in both scans. A GGUF infra repo stays visible when the user
explicitly downloaded a variant through the Hub, since variant manifests only
exist for user-initiated downloads.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: make On Device trust the hub inventory, match repo ids exactly, lighten the hidden-model import
Follow-up on the hub cached-inventory hidden-model change, addressing the review.
On Device now trusts the Hub inventory API for cached rows. The backend already
hides the RAG embedder and the llama.cpp probe and re-includes a GGUF infra repo
once the user downloads a variant through the Hub, but the frontend was
re-hiding it by repo id, so the user-downloaded variant never appeared in the On
Device list or the count. isVisibleInventoryRow now short-circuits cached rows
(kind === "cache") to visible and keeps client-side needle hiding only for local
filesystem rows and Discover.
is_hidden_model matches Hub repo ids exactly (case-insensitive) against the probe
plus the effective embedder and its GGUF companion, instead of substring
matching the configured-embedder basename. A custom embedder with a generic
basename like org/model no longer hides unrelated cached repos such as
user/model-chat or org/model-instruct. The probe filename and local-path
embedders keep exact matching.
The helper moves to utils/hidden_models.py and is imported at module scope in the
hub cache scanner, so it no longer pulls in utils/models/__init__ (the eager
model-config/checkpoint stack) and a broken import fails at startup instead of
being swallowed per-repo and silently emptying the inventory. routes.models
keeps the _is_hidden_model and _safe_resolve aliases and drops the unused
_HF_REPO_ID_RE re-export that was failing source lint.
Tests: exact repo-id matching with a custom embedder, the cached-models scan
keeping an unrelated repo, and a clean-interpreter check that the helper imports
without the model-config stack.
* Studio: match the llama.cpp probe filename on both path separators
The hidden-model check compared the probe's on-disk filename with
Path(value).name, which on a POSIX interpreter does not split a Windows-style
path ("...\stories260K.gguf") and would let the probe through. Split on both
separators so the probe is matched regardless of which OS produced the path,
matching the tolerance of the previous substring check. Adds a Windows-path
assertion to the probe test.
* Studio: harden hidden infra model handling
* Fix hidden cache row confirmation
* Fix hidden local rows and confirmed hint merges
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Handle snapshot-configured hidden models
* Hide basename-only default embedders
* Fix dynamic embedder inventory filtering
* Studio: hide the configured RAG embedder from Discover and feed rows
---------
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* Replace standalone Studio wording with Unsloth
Replace the single word Studio with Unsloth wherever it is used as
shorthand for Unsloth Studio in docs, CLI output, UI strings, i18n
locales, workflow display names, comments and docstrings.
Kept unchanged: the full name Unsloth Studio, third party product
names (LM Studio, Visual Studio, Mac Studio), feature names
(Recipe Studio, Fine-tuning Studio and its translations), and all
identifiers such as env vars, commands, paths and filenames.
* Address review feedback on the Studio wording rename
Use "an" before Unsloth where the rename left the article as "a".
Restore the split brand where Unsloth and Studio render as two halves
of the full product name: the onboarding sidebar subtitle and the
IPv6 localhost warning. Scope two messages to the full name Unsloth
Studio where plain Unsloth was misleading: the AMD README bullet and
the CLI studio setup error.
* Studio: expose Windows drive roots in the folder browser
The model-selection folder browser bounds navigation to the roots returned
by _build_browse_allowlist(), which exposed Linux removable-media mounts via
linux_run_media_mount_roots() but had no Windows analog. As a result a user
on C: could not browse to D:/E: to pick a model directory.
Add windows_drive_roots(), a Windows-only companion to
linux_run_media_mount_roots() that lists readable logical drive roots, and
wire it into both browse-allowlist builders and their suggestion chips so
other drives are both navigable and offered as quick-picks. The helper is a
no-op on Linux/macOS, so existing platforms are unaffected.
Closes#6368
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* Studio: cover the Windows drive-root browse wiring with an integration test
Add an allowlist integration test mirroring the Linux side's
test_legacy_browse_allowlist_includes_linux_run_media_mounts: it extracts
_build_browse_allowlist from routes/models.py, stubs external_media so
windows_drive_roots() yields a fake drive root, and asserts that root becomes
browsable through the built allowlist. Proves the wiring, not just the helper.
* Studio: skip inactive drives via GetLogicalDrives before probing
Resolve active logical drives from GetLogicalDrives() before probing each
letter with os.path.isdir. Probing a drive letter mapped to a disconnected
network share can otherwise block the async backend for tens of seconds per
letter. The call degrades gracefully (falls back to probing all letters) when
ctypes/windll is unavailable, so behavior is unchanged on Linux/macOS. Tests
override the bitmask source to stay deterministic on real Windows hosts.
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* Studio: allow browsing descendants of a drive-root allowlist entry
routes/models.py _is_path_inside_allowlist() checked descendants with
startswith(root_real + os.sep). A drive root ("D:\") already ends in a
separator, so the prefix became "D:\\" and a child like "D:\models" was
rejected with 403 after the browser opened the drive root. Only append a
separator when the root does not already end in one. folder_browser.py already
uses commonpath and was unaffected. Adds a regression test covering the
separator-terminated-root descendant case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: enforce the system-directory denylist during folder browsing
Exposing whole Windows drive roots (and any legacy-registered filesystem root)
widened the browse allowlist above system directories, but the browse
resolvers only re-applied the credential/config denylist, not the
_denied_path_prefixes() system-dir denylist that scan-folder registration
enforces. That let browse-folders enumerate C:\Windows, C:\Program Files,
/etc and /proc.
- Add is_denied_system_path() to both storage modules and enforce it in both
browse resolvers (legacy routes/models.py and hub folder_browser.py), on each
resolved child and on the final target, keeping the /run/media carve-out.
- Rework the legacy _is_path_inside_allowlist to use splitdrive + commonpath so
a Windows drive root authorizes its descendants while a bare POSIX / does not,
and to compare case-insensitively like the hub browser.
- Reject the filesystem root in the legacy add_scan_folder, matching the hub.
- Hide denied system dirs from browse listings and suggestion chips.
- Add tests/test_browse_denylist.py and update the external-media path tests.
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* Studio: make browse-denylist tests OS-portable
The browse-time denylist tests used real /etc and tmp_path locations; on macOS
tmp lives under the (legitimately denied) /private/var and /etc resolves to
/private/etc, so three tests failed there. Pin the platform / use a tmp-based
denied prefix so they assert the same behavior on Linux, macOS and Windows.
* Studio: apply the bare POSIX-root guard to the hub folder browser too
The _is_path_inside_allowlist guard that stops a legacy-registered '/' scan
folder from authorizing every absolute path lived only in the legacy browser.
The hub browser used commonpath without it, so a stale '/' row let it descend
into /var, /root, /home -- which the system-directory denylist (/proc /sys /dev
/etc /boot /run) does not cover, while the legacy browser blocked them. Mirror
the legacy guard so both browsers treat '/' identically.
Also resolve each directory entry before the denylist check in both listing
loops, so a symlink or junction pointing into a denied dir is hidden instead of
rendered as a row that 403s on descent. Adds legacy-vs-hub parity tests.
* Studio: bound Windows drive probing so a disconnected mapping can't stall the browser
GetLogicalDrives includes mapped network drives, so a disconnected but still
mapped drive (e.g. Z: -> \\nas\share) stays set in the bitmask and reaches
os.path.isdir, which can block for tens of seconds while Windows tries to
reconnect. Because windows_drive_roots() runs synchronously while building both
folder-browser responses, one stale mapping stalled every browse request.
Probe each surviving drive in a daemon thread bounded by a short timeout and
skip it if it does not answer in time, so a hung mapping is dropped instead of
blocking the caller. Connected drives (local or network) still respond well
within the timeout, so drive discovery is unchanged. Corrects the
GetLogicalDrives docstring, which claimed the bitmask alone prevented the stall.
* Studio: probe drive/media roots once per browse request, not twice
Both folder browsers called windows_drive_roots() (and
linux_run_media_mount_roots()) twice per browse request: once to seed the
allowlist in _build_browse_allowlist() and again to build the suggestion chips.
With the bounded drive probe, a disconnected mapped network drive then paid the
timeout twice per folder click. Probe both once in the request handler and pass
the results into _build_browse_allowlist(), reusing them for the chips, in both
the legacy and hub browsers. Adds a test asserting the roots are reused, not
re-probed.
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* Studio: run the legacy browse endpoint in the threadpool, fix its stale test
Two follow-ups from review of the drive-probe changes:
- browse_folders was 'async def' but does only blocking filesystem I/O (the
timeout-bounded drive probe, iterdir, realpath). On the event loop a
disconnected mapped drive waiting out its probe timeout stalled every other
request. Declare it sync 'def' so FastAPI runs it in the threadpool, matching
the hub browse endpoint. No await was used in the body.
- test_browse_folders_hides_sensitive_dirs monkeypatched _build_browse_allowlist
with a zero-arg lambda; the once-per-request refactor now calls it with
(media_roots, drive_roots), so the lambda raised TypeError. Accept and ignore
the args.
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* Studio: probe Windows drive roots concurrently so multiple dead mappings don't stack timeouts
windows_drive_roots() probed each candidate serially, so N disconnected-but-mapped network drives each paid the full per-drive timeout in turn (e.g. four stale mappings added ~8s to every folder-browser request). Collect the candidate roots first, then probe them all at once under a single overall deadline, so the added delay stays at ~one timeout regardless of how many drives are disconnected. _readable_dir_within stays as a thin single-path wrapper for its existing callers/tests.
* Studio: tighten comments in the folder-browser drive-root changes
Condense the comments and docstrings added by the Windows drive-root and
system-directory denylist work to be shorter and clearer while keeping the
security and correctness rationale intact. Comment and docstring text only;
no code changes.
* Studio: iterate the input, not the results dict, when collecting readable drive probes
_readable_dirs_within returned {path for path, ok in results.items()...}, but a probe thread that exceeded the join deadline is still alive and can insert its key into results during that iteration, raising 'dictionary changed size during iteration' -- reachable exactly in the disconnected-mapped-drive case the probe exists for. Iterate the fixed input list and read results.get(path) (an atomic read) instead.
* Studio: keep the browse-route containment tests denylist-inert so they pass on macOS
test_browse_folders_route.py exercises allowlist containment and the file-vs-directory guard, not the system-directory denylist. On macOS pytest tmp_path resolves under /private/var, a denied prefix, so _resolve_browse_target 403s the fixture dirs before the containment logic runs (4 failures). Add an autouse fixture that makes is_denied_system_path inert in this file; the denylist keeps its own coverage in test_browse_denylist.py.
* Studio: keep the hub browse tests denylist-inert so they pass on macOS
* Studio: register a UNC share root; only reject local filesystem roots
* Studio: reject device drive roots and browse a registered UNC share root
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* Studio: treat device-namespace volume GUID roots as local filesystem roots
---------
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* Fix external drive custom folder selection
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Update studio/backend/tests/test_linux_external_media_paths.py
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
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* Keep legacy media scan validation strict
* Apply sensitive-dir denylist to legacy folder browser for PR #6799
The legacy /api/models browse endpoint gained the new /run/media mount
roots in its allowlist but not the credential/config guard that scan-folder
registration and the Hub browser already enforce. Filter sensitive names
during enumeration and reject them in _resolve_browse_target so .ssh, .aws,
.config, etc. under allowlisted roots stay unbrowseable, matching the Hub
browser. Add a public contains_sensitive_path_component helper and cover the
legacy resolver with a regression test.
* Trim redundant comments in PR #6799 changes
* Skip sensitive Linux media roots
* Reject sensitive dirs at exact browse roots for PR #6799
Both _resolve_browse_target functions only checked contains_sensitive_path_component
while walking descendant parts, so requesting an allowlisted root itself (empty
relative path) returned it unchecked. A pre-existing scan-folder row under ~/.ssh,
~/.aws, ~/.config, etc. (registerable before the denylist was added) is re-added to
the allowlist on upgrade and could then be browsed. Check the resolved target once
before returning in both the legacy and Hub browsers, and cover the root case in
both test suites.
* fix: avoid unused path helper reexports
* fix: import sensitive path helpers directly
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* Add customizable RAG embedding model setting and reorganize settings tabs
Chat with files, project sources, and knowledge bases previously always
embedded with unsloth/bge-small-en-v1.5. This adds a Settings option to
pick any Hugging Face embedding model (or local path), with HF search
autocomplete, server-side verification that the repo is actually an
embedding model, and a save anyway escape hatch for offline or local
models. The setting persists in app_settings and applies at runtime to
both the sentence-transformers and llama-server GGUF embedder backends
without a restart.
Also reorganizes the General settings tab: Documents & RAG sits above
Uploads, Helper LLM moved above the danger zone, and Model auto-switch
(OpenAI API) moved to the bottom of the API tab.
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* Support local model paths on the GGUF embedder and normalize default saves
Found by simulation testing of the embedding model setting:
Local paths saved as the embedding model now work on the llama-server
GGUF backend (the default backend on macOS and CPU). A path to a .gguf
file is used directly and a directory is scanned for a variant-matching
non-mmproj .gguf, with a clear error when none exists. Previously a
local path was sent to the HF hub API and failed with a repo lookup
error.
Saving the default model explicitly no longer stores an override, so
is_custom stays false and the UI does not show a reset button for the
default value.
* Address review: stale-vector handling, GGUF derivation, save-time guards
Review follow-ups, each verified by new tests:
Re-uploading a document after an embedding model change now re-indexes
instead of deduping by content hash. Documents record the embedder that
produced their vectors (lazy embedding_model column, NULL legacy rows
keep deduping) and a mismatch replaces the old document.
A vector width change no longer bricks the dense index. ensure_vec
drops and recreates chunks_vec when the dim changes (old vectors are in
a foreign space and only block inserts) and search_dense returns empty
on a width mismatch instead of surfacing a vec0 error, so lexical
search keeps working until documents are re-uploaded.
Saving a local sentence-transformers folder with no .gguf now returns
409 with a clear message when the install embeds via llama-server,
instead of failing at first index. force still saves.
A custom RAG_EMBEDDING_MODEL env without RAG_EMBED_GGUF_REPO now
derives the -GGUF companion repo instead of silently keeping the bge
GGUF on CPU and macOS installs.
The resolved GGUF path is tagged with the repo captured at entry, so a
setting change during a download cannot mark the old model as current.
GGUF repo detection matches gguf as a whole name segment rather than a
substring, hf_token is trimmed before verification, and the settings
combobox drops a redundant state mirror of its controlled value.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Shrink embedding model font to 11px in the input and dropdown
The combobox wrapper applies className to the outer input group, so the
size utility must target the inner input element; the previous text-xs
never reached it and the field rendered at the browser default.
* Show curated unsloth embedding models when the search field is empty
The empty-query listing was the global top-downloads page, which holds
no unsloth mirrors for the unsloth-first float to reorder, so the
dropdown opened on third-party models. Match the model picker: curated
unsloth listing when empty, whole-Hub search once a query is typed.
* Address review: settings resilience and index consistency
Keep the last known embedding model on settings store errors, remove the
re-entrant dim lock in the llama-server backend, accept local GGUF saves
and verify GGUF availability for HF repos on that backend, match local
path embedders exactly in model list filters, drop same-width stale
vectors from dense search, pin the embedder per ingestion job, and only
replace completed documents after the re-index succeeds.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Consolidate the GGUF repo derivation tests
* Trim to a single core embedding-model test
* Address review: GGUF repo saves and cache race
Accept a GGUF-named HF repo on the llama-server backend by verifying GGUF
availability instead of the sentence-transformers metadata gate, and guard
the settings cache with a generation counter so a read overlapping a save
cannot repopulate it with the pre-save value.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* add models for /update endpoint
* add logic for identifying out of date hf models
* add endpoint for updating hf models
* add relevant field to GgufVariantDetail
* make exception handling better
* add update_available flag for cached_models, and moved /update endpoint from inference -> models
* hook up /update endpoint on the frontend
* implement update scenarios for the model picker
* fix bug where downloaded flag for an older revision was being wrongly set to false
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix import and make hf calls async
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* remove has_vision from UpdateRequest
* fix ci
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* clear cancel event before updating gguf variant
* set _cancel_event back if it was set initially
* add hf_token to get_paths_info
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: harden model update endpoint and update checks
- update_hf_model: pass snapshot_download local_dir (local_path is not a
valid kwarg and 500s when updating bicodec audio models)
- get_gguf_variants: wrap the remote update check so a network, rate-limit,
gated, or offline failure degrades to "no update info" instead of failing
the whole variant listing, matching list_cached_models
- add regression tests for both paths
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: HF model update detection and Update action for cached models
Surface an "Update available" cue and a managed Update action for cached
on-device models. /api/hub/update-status compares each cached main GGUF
file's local blobs against the remote main revision using set membership
across all cached revisions, so a repo that was already updated (and still
holds the old snapshot alongside the new one) is not falsely flagged.
The Update action re-downloads through the download manager so it shows in
the Downloads panel with progress and cancel. The frontend wires the Update
button into the GGUF, on-device, and model-selector cards and keeps the
quant label fully visible when the action buttons crowd the row.
Adds regression tests for the multi-revision update check.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: accept force_download kwarg in hf_xet_fallback test double
The download seam now passes force_download to the attempt callable; the _FakeAttempt mock did not accept it, failing 6 tests with TypeError. Add the keyword (default False) so the scripted-results double matches the seam.
* Fix Studio model update regressions
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address Studio update review feedback
* Address Studio update edge cases
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Share GGUF update status helper
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix GGUF update detection and cache cleanup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix cached GGUF update badges
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: shimmyshimmer <107991372+shimmyshimmer@users.noreply.github.com>
Co-authored-by: Etherll <61019402+Etherll@users.noreply.github.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* Studio: persistent per-user trust_remote_code approval cache
The consent gate pins each approval to a content fingerprint (sha256 over every
repo .py), but nothing was persisted, so the dialog reappeared on every fresh
load of the same unchanged repo. This adds an on-disk, per-user approval cache
that lets the gate skip the dialog when the same user reloads the same code,
while keeping the safety guarantees intact.
Two-tier validation, both must hold or the user is re-prompted:
- Commit SHA (cheap, one HfApi.model_info().sha, no download): a match means a
byte-identical tree to the approved revision, so the scan/download is skipped.
- Content fingerprint (authoritative): used whenever the SHA is unavailable
(local path / offline) and always recomputed on a SHA miss. A new or edited
.py changes both the SHA and the fingerprint, so it is caught in every mode.
Safety:
- Keyed per subject; one user's approval never auto-runs code for another.
- CRITICAL is never stored or honored (guarded on both write and read), so a
hand-edited store cannot smuggle in an auto-approval.
- The malware (HF unsafe-file) gate stays unconditional.
- Fail-safe: a corrupt store, an unresolvable SHA, or any error degrades to
"ask again", never to "auto-approve". UNSLOTH_TRC_APPROVAL_CACHE_DISABLE=1
turns the cache off entirely.
New module utils/security/remote_code_approvals.py holds the store
(studio_root()/security/remote_code_approvals.json, atomic write, 0600, RLock)
plus the SHA resolvers. Recording happens at the single gate chokepoint when the
caller supplies the matching fingerprint, so subject is just threaded through
inference/training/export (orchestrators, routes, workers). The scan endpoint
returns already_approved so the frontend can skip the dialog on a cache hit.
Tests: new tests/test_trc_approval_cache.py covers cache miss, SHA-match skip,
SHA-moved re-scan, new-file re-consent, CRITICAL never cached (write + forged
read), disable flag, subject isolation, combined adapter+base key, corrupt
store, and no-subject bypass. Full security suite: 101 passed.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review: make the approval cache skip only the prompt, never the scan
Codex found that the SHA "no-scan" fast path could run untrusted code without
re-consent. Removed it; the gate now always re-scans and the cache only seeds the
authoritative fingerprint check, so it can skip the dialog but never the scan.
- CRITICAL is hard-blocked on every load (the scan always runs), so a hand-edited
store that downgrades a CRITICAL repo's severity can no longer auto-run it
(P2: do not trust editable severity for SHA approvals).
- The fingerprint covers external auto_map repos, so changed third-party code
always re-prompts even when the primary commit SHA is unchanged; there is no
longer a SHA path that bypasses the fingerprint (P1: external auto_map repos).
- resolve_commit_sha is resolved fresh on every call (no memoization), so a repo
whose default branch moves after approval re-prompts instead of reusing a stale
cached SHA (P1: revalidate mutable Hub SHAs). The SHA is now only a conservative
secondary gate: a fresh resolvable SHA must match the approved revision, else the
seed is withheld; a None (local/offline) falls back to the fingerprint.
- Approvals record the scanner ruleset version (SCAN_RULES_VERSION); the gate
ignores approvals from an older ruleset so reclassified bytes are re-scanned and
re-shown instead of silently auto-approved (P2: invalidate on scan-policy change).
Tests: test_trc_approval_cache.py rewritten around the prompt-skip semantics
(unchanged repo still scans; SHA move / changed code / scanner-version bump /
disable flag all re-prompt; forged downgraded severity still blocks CRITICAL).
105 passed with test_consent_gate.py.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Trim comments to be more succinct
* Keep run-owner subject out of persisted config; serialize approval writes
Threading subject (the run owner's username / API-key id) into the training
config meant _sanitize_db_config persisted it into config_json, which
training-history GET returns to any authenticated user, leaking who started a run
in multi-user installs. Filter subject alongside the token fields; the worker
still receives it from the live config.
The approval store's RLock only guards one process, but approvals are recorded
from separate inference/export/training subprocesses, so concurrent writers could
clobber each other on os.replace and drop an approval (re-prompt). Hold a
best-effort cross-process file lock around the read-modify-write.
* Fail safe on a malformed approval store
A store with the right version but a non-dict shape (e.g. a hand-edited
"subjects": []) passed _load()'s check, then lookup chained .get() on a list and
raised, breaking every remote-code load until the file was removed. Validate that
subjects is a dict in _load(), and tolerate a non-dict per-subject entry in
lookup/record/forget, so a corrupt store fails safe (re-prompt) instead.
* Keep subject out of the MLX W&B run config
_run_mlx_training uploads the whole training config to W&B minus a sensitive set
that only listed hf_token/wandb_token/s3_config, so the authenticated subject
(username / API-key id) was sent to W&B as run config even though DB history
already strips it. Add subject to the W&B-sensitive filter, mirroring
training._sanitize_db_config.
* Tighten the W&B subject-filter comment
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: redesign Select model dropdown to match Hub design
Make the chat Select model picker easier to scan by reusing the Hub
on-device card's visual language.
- Rows now split owner/name, add a param chip, a DotTag format pill,
a tabular size, and a Loaded marker on the active model.
- Hub models / Fine-tuned tabs reuse the Hub's exact .hub-tab-toggle
styling (selectors extended in hub.css to the selector menu).
- Add a Downloaded / Recommended / Custom section toggle on the Hub
tab to filter the list.
- Widen the popover and nudge the scrollbar toward the edge.
* Studio: move section toggle below search, size tabs to label
Put Downloaded / Recommended / Custom under the search bar in their own
row so Hub models / Fine-tuned no longer wrap. The section toggle uses a
smaller font and sizes each tab to its label instead of equal widths.
* Studio: extract pure row-meta helpers into their own module
Move splitRepoLabel, classifyMetaToken, and parseMetaTokens out of
pickers.tsx into row-meta.ts. No behaviour change; keeps the presentation
logic free of React/DOM deps so it is easy to test in isolation.
* Studio: content-size the source tabs and add section icons
Size the Hub models / Fine-tuned tabs to their labels (with side
padding) like the section toggle, instead of stretching full width. Add
a leading download, star, and folder icon to Downloaded, Recommended,
and Custom.
* Studio: stop source tabs stretching and hide empty Fine-tuned tab
The popover is a flex column, so the fit toggle stretched full width;
add w-fit/self-start so it sizes to its content. Also hide the
Fine-tuned tab when there are no fine-tuned models, defaulting to Hub
models.
* Studio: keep only fine-tuned models in the Fine-tuned tab
Local models (LM Studio, Ollama, custom folders) carry source "local"
and already show in the Hub tab's Downloaded / Custom sections, so
exclude them from the Fine-tuned tab and from its visibility count.
Extract the tab rules into source-tabs.ts.
* Studio: show local providers under Downloaded, Recommended first
Show LM Studio and other local provider models in the Downloaded
section in all modes (was chat-only). Put Recommended first and make it
the default section. Add a little more space below the search bar.
* Studio: make Recommended a sortable live Unsloth listing
Replace the static Recommended list (and its collapse chevron) with a
sort dropdown over Unsloth's own models: Recommended, Trending, Most
likes, Downloads, Recently updated. Recommended shows recently uploaded
GGUF/MLX models that fit the device (hidden if they do not); the other
sorts list all Unsloth models, badged but never hidden. Adds a sort
option to useHfModelSearch and a pure recommended-fit helper.
* Studio: size Recommended models from the repo name when metadata is missing
GGUF and MLX repos rarely expose safetensors metadata, so a large model
with no size could pass the Recommended fit check because unknown size was
treated as fitting. Parse the parameter count from the repo id, including
the Gemma E series, and hide anything we still cannot size.
* Studio: detect model capabilities and family from HF tags
Thread tags and the pipeline tag through the model search results and add a
pure helper that infers vision, reasoning and audio plus the architecture
family, falling back to repo-name keywords when tags are absent.
* Studio: add row details and inline section sorting to Select model
Give each model row more detail and make the Hub sections easier to scan:
- Show vision, reasoning and audio badges plus the architecture family tag
on each row, alongside the params, format and size.
- Drop the redundant unsloth/ prefix on the Recommended rows.
- Rename the Recommended section tab to Unsloth and enlarge the section tabs.
- Move the sort dropdown inline to the right of the tabs at a fixed width.
- Add Recent, Size and Downloaded sorting to the Downloaded and Custom tabs.
- Remove the header icons, pad the subheadings, and grow the list height.
* Studio: tune the Select model sort dropdown and trim row badges
- Recommended now lists the most recently created Unsloth repos.
- Narrow the sort dropdown, remove its border, and truncate long labels.
- Tighten the gap between the section tab icons and their labels.
- Remove the architecture family tag from rows since it repeats the name.
* Studio: extract the PillTabs toggle into a shared module
Move the segmented pill toggle out of the model selector into its own file so
the Hub picker can reuse it for a format filter without duplicating the markup.
* Studio: fix Recommended infinite scroll and add a format filter
- Re-attach the scroll observer on each loaded page so a filtered Recommended
list keeps paging until the viewport fills instead of spinning forever with
nothing new appearing.
- Add an All / GGUF / MLX / Safetensors toggle on the Unsloth listing that
filters every sort.
* Studio: default Recommended to Trending, rename Downloaded to On Device, and fade the scroll edge
Sort: default the Recommended view to Trending and add a Name option to
the On Device / Custom sort. Recent now orders by last load time while
Downloaded orders by file date, tracked in localStorage (model-usage.ts).
Formats: show the format filter on all three tabs (Unsloth, On Device,
Custom), exclude mobile GGUF builds from Recommended, and flag GGUF rows
that exceed the device with the same OOM badge as safetensors.
Polish: download-icon badge on already-downloaded Recommended rows, the
hugeicons view stroke-rounded vision badge, Search all models placeholder,
matched popover padding, and a top-edge mask fade once the list scrolls.
* Studio: size GGUF repos from gguf metadata so large ones flag OOM
Repos with no <n>B token in the name (Kimi, MiniMax) had no param count
and so never showed an OOM badge. Request the gguf expand field from
Hugging Face and read gguf.total, so those repos get a param chip and an
OOM badge when they exceed the device budget.
Keep the row name full contrast when over budget (the OOM badge already
signals the fit), shorten the format and sort dropdowns, narrow the
popover, and rename Recently updated to Recent and All formats to All.
* Studio: address selector review feedback
Add WAI-ARIA roving tabindex and Arrow Left/Right navigation to the pill
toggle so only the active tab is in the tab order. Keep the chat-only
GGUF/MLX filter for every Recommended sort, not just Recommended, so
chat-only users do not see unrunnable checkpoints under Trending. Feed
both listings' GGUF hints into repo detection so a tag-only GGUF in
Recommended expands variants instead of loading as a checkpoint.
* Studio: scope Select model search per tab and add an MLX tag
Search is now per section. The Unsloth tab searches the Unsloth HF
listing only, On Device filters downloaded and LM Studio models by name,
and Custom filters custom-folder models, each with its own empty state.
MLX repos get an MLX pill mirroring the GGUF tag. Downloaded quants in
the Unsloth and search lists get the same delete action as On Device.
Also: revert the model name to normal weight, narrow the popover to
558px so the format and sort dropdowns sit one gap-2 from the tabs,
tighten the dropdown menus to match the Projects activity Select, and
make the empty On Device state name the active format filter.
* Studio: show local ./models on the On Device tab so they stay selectable
Models under the local models directory (source models_dir) flow in as local
models but were dropped from every list: filtered out of Fine-tuned and never
re-added by the Hub picker, which kept only LM Studio and custom-folder
sources. Capture them in the local refresh and render a Local models group on
the On Device tab, with the same format, search, and chat-only GGUF rules as
the other local groups.
* Studio: add a Hub button beside the Select model search bar
Adds a Hub button next to the search bar that opens the full Hub Discover
page to browse more models. Styled like the section tabs (rounded, no
border, soft shadow with a faint top layer) and darkens on hover. Also
nudges the format and sort dropdown chevrons a touch toward the edge.
* Studio: align Select model padding and tighten the format pills
Sizes the popover to the tab cluster so the left and right padding match,
and drops the top row below the rounded corner so the Hub button lines up
with the Trending dropdown. Gives the Hub button a fixed width, lets the
list scrollbar sit inside the box, and shrinks the format pill dot with a
tighter dot-to-label gap.
* Studio: label the Hub button Search Hub and match the dropdown width
Renames the button to Search Hub, sets its width to the format and sort
dropdown width so it lines up above them, and tightens the icon gap.
* Studio: drop the vision and reasoning row badges to declutter
Removes the vision and reasoning capability icons from the model rows so
they read cleaner. Audio is kept.
* Studio: add a safetensors pill, hide diffusion models, eye on Vision
Gives safetensors rows a format pill and size so their meta matches GGUF
and MLX, drops image and video diffusion models from the listing since they
cannot run in chat, and shows an eye icon next to the Vision tag. Also
removes the em dashes from the Projects export and import labels.
* Studio: gate recommended folders on real weights and polish the selector
Only show a Recommended chip once the well-known dir actually holds
weights, so an empty LM Studio or Ollama scaffold no longer suggests
itself. _dir_has_downloaded_model checks for a GGUF/safetensors file or
a non-empty Ollama manifests store, with a bounded walk.
Selector polish: round the popover and option menus a touch more,
lighten the OOM badge in dark mode, soften the inner dropdown shadow,
even out the padding, and lift the toggle track and field triggers so
their edges read against the popover.
Also catch CogVideoX in the diffusion name fallback.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: align the dark Select model panel with the sidebar
Match the popover, fields, dropdowns, tab toggle and row states to the
sidebar surface and accent so the dropdown reads as one piece in dark
mode. The active tab pill and Search Hub button sit a touch lighter
than the track, and the inner option menus drop their drop shadow for a
flatter look. Light mode is unchanged.
* Studio: re-derive the Select model tab on open
The picker remounts each time the dropdown opens, but the source tab
state did not, so a persisted fine-tuned or connected selection that
only lands in its list after an async load would reopen on Hub. Reset
the active tab to the selection-derived default on the open edge, while
still letting the user switch tabs freely within a session.
* Studio: fold Custom into On Device and polish the picker
Merge the Custom tab into On Device so custom folders sit right below
the downloaded models, with a folder shortcut on the group header.
Rename the first Hub tab to Recommended, give the format dropdown
colored dots, even out the tab row spacing, and tighten the popover
width. Align the folder browser with the app dialogs (soft surface,
roomier padding, green confirm, grey hover).
* Studio: fix On Device controls and nudge the folder browser close
The Hub redesign merge dropped the old Search Hub button styling, so the
On Device search row rendered flat. Point the search input and Search
Hub button at the shared .field-soft surface so they match the rest of
the Hub controls, and lift the folder browser close button slightly.
* Studio: run the Select model search on the Hub search stack
Point the picker at the Hub's useHubModelSearch and useHubInfiniteScroll
instead of its own useHfModelSearch/useInfiniteScroll, scoped to unsloth
so the listing matches the old one. Both the search and the recommended
feed now share the Hub implementation, so there is one search path. The
Hub result folds GGUF params into totalParams, so the dead ggufParams
fallback is dropped.
* Studio: trim the recommended sort to Recommended, Trending, Recent
Drop Downloads and Most likes from the sort dropdown.
* Studio: give the section tabs room off the rounded edge
The fit-mode toggle wrapped the tabs with no inset, so On Device sat
tight against the rounded-full edge. Add a small horizontal inset and
widen the popover a touch to fit it.
* Studio: drop the legacy HF search hooks for the Hub ones
Migrate the training model and dataset sections, export page, onboarding
steps and recipe dataset combobox off useHfModelSearch, useHfDatasetSearch
and useInfiniteScroll onto the Hub equivalents, scoped to unsloth so the
listings match. The picker reads recommended param counts off the search
results it already has instead of a separate fetch. Removes the duplicate
search stack: use-hf-model-search, use-hf-dataset-search,
use-hf-paginated-search, use-infinite-scroll, use-recommended-model-vram
and the old lib/hf-cache.
* Fix model selector section toggle proportions
Remove the fit-mode track inset so the active pill sits flush to the
track edge, matching the Hub's segmented controls.
* Tighten model selector width and tab padding
Reduce the popover width so the right edge aligns with the row, and
widen the fit-mode tab padding so On Device clears the track edge.
* Refine Recommended formats, sort width and tab padding
Recommended now suggests GGUF anywhere and MLX only on Mac, never
safetensors. Size the sort dropdown to its label so Recommended no
longer truncates, and match the On Device trailing gap to the active
pill's leading inset.
* Flush section toggle and match dropdown font to Search Hub
Drop the trailing track pad so the active pill fits the track exactly
at either end. Size the sort and format dropdown text to text-xs like
the Search Hub button, and clip long labels without an ellipsis.
* Fix sort menu checkmark overlap and lock dropdown widths
Keep the option's right padding so the selected checkmark no longer
overlaps the label, and let the open menu expand to fit it. Set the
format and sort triggers to a fixed width matching the Search Hub
button so they always line up.
* Keep section toggle and dropdowns on one row
Drop the wrap and size the Search Hub button, format and sort dropdowns
to a shared 100px so they stay equal width and fit on one row without
widening the box.
* Studio: pre-load inference settings dialog with native context
Add a gear on downloaded GGUF quant rows that opens a settings dialog
to adjust inference parameters before loading a model:
- Context length, KV cache dtype, speculative decoding and tensor
parallelism, all written to the runtime store the load call reads.
- Settings can be remembered per model in localStorage.
- The context slider ceiling and "Model supports up to N tokens" come
from the model's native context, read from GGUF metadata and returned
by /api/models/gguf-variants once a variant is downloaded.
Also drop models Studio can't run for chat (diffusion, image, video)
from the recommended feed and Hub search, plus minor selector polish
on row hover padding, Search Hub and dropdown widths, and tab spacing.
* Studio: model selector polish and memory-aware load warning
Search and listing:
- Drop the "Recommended" and "Hugging Face" section labels while
searching so results read as one list; keep the format and sort
dropdowns visible so search results can still be sorted and filtered.
- Request gguf metadata in the Hub listing so GGUF repos report a
parameter count, restoring the OOM badge for repos without a size
token in the name (Kimi, MiniMax, GLM).
Load settings dialog:
- Warn when weights plus the KV cache at the chosen context exceed
available memory. The KV size is sized by the backend's
architecture-aware estimator via a new kv-cache-estimate endpoint;
the budget uses VRAM plus system RAM. Best-effort, no warning on
failure or on auto context.
- Context Length placeholder reads "auto"; dark background slightly
lighter.
Other:
- Clicking the Custom Folders header opens the folder browser; its
title now reads "Select folder to detect models".
- On Device sort lists Downloaded last.
- Smaller chat template editor font; rounded wrapper clips the prompt
and template editor scrollbars so the right corners stay round.
* Studio: fix load dialog memory warning budget and KV dropdown width
- The memory warning never fired without a discrete GPU. useGpuInfo
returned zero system RAM in that case, so the budget was always zero.
Surface system RAM even when no GPU is present (Mac unified memory),
and have the load dialog read memory directly instead of through props.
- Give the dialog fields shrink-0 so the KV Cache Dtype value (e.g.
q8_0) is not squeezed and clipped by the row.
* Studio: fold fine-tuned models into On Device tab
Remove the Hub models and Fine-tuned source tabs. Fine-tuned models now
show as a section in the Hub tab's On Device view, above Custom Folders,
with the Train icon and a collapse toggle. The section only appears when
the user has fine-tuned models. With no external providers the lone Hub
tab hides its own toggle.
Also: tick-circle Show hidden checkbox and drop the divider above Eject;
keep run settings load params (KV cache dtype, speculative, tensor
parallel) from being clobbered by a mid-load status poll.
* Studio: stage load settings in the sidebar with a Load on selection toggle
Replace the pre-load settings popup with a staging flow in the Run settings
sidebar. The gear on a downloaded quant row now stages the model and opens
Run settings with Load model and Cancel buttons, so options like context
length, KV cache, speculative decoding and tensor parallelism are set before
the model loads. A "Remember these settings" tick reuses them next time.
Add a global Load on selection toggle in Settings, Chat tab (default on).
On: Unsloth auto-picks the best settings for your hardware and loads on
selection. Off: picking a model stages it in Run settings to customize first.
The gear always stages, regardless of the toggle.
Other polish in this change:
- Fine-tuned models live under the On Device tab, with a train icon on the
header that jumps to the Fine-tuned section.
- Default to the On Device tab when downloads exist, otherwise the last used
section.
- Standard Unsloth tooltips on the train, folder and gear icons.
- Request the gguf param count on every Hub listing fetch so Kimi, MiniMax
and GLM show a size badge.
- Search Hub hover state, scrollbar position and minor spacing fixes.
Remove the old inference load settings dialog.
* Studio: always show the fine-tuned shortcut and smooth out the picker
- Fine-tuned section and its train shortcut now always show on On Device,
with an empty state when no fine-tuned models exist yet.
- Folder icon on the header jumps to Custom Folders instead of opening the
browse popup, matching the train shortcut.
- Folder browser keeps the list mounted and dims it while refetching, so
toggling Show hidden or changing folders no longer flashes.
- Drop the tooltip hover grace area in the picker so moving between the
train, folder and gear icons switches the tooltip at once.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: add quantization display options and drop the fine-tuned empty text
- Settings, Chat: 'Expand quantizations' toggle. On expands every On Device
GGUF model's quantizations by default; off keeps them behind a click
(default).
- Settings, Chat: 'Show all quantizations' toggle. On lists every quant
including ones not downloaded (default); off shows downloaded only.
- Remove the empty-state line under the Fine-tuned header; the header still
shows on its own.
* Studio: let expanded quantizations collapse on click and split the On/Off help
- With Expand quantizations on, clicking an On Device model now collapses or
re-expands its quantizations. The collapse state is in memory only, so it
resets on reload and when the setting is toggled.
- Put the Off sentence on its own line in the quantization setting descriptions.
* Studio: reorder chat settings and rename the model section
- Rename the Models section to Select model settings and move it above the
Chat menu section.
- Trim the section and Load on selection descriptions.
* Studio: tighten the On/Off lines in the model setting descriptions
Use a line break instead of separate spans so the On and Off lines sit on
consecutive lines without the extra paragraph gap.
* Studio: top-align the Load on selection toggle
Add an alignTop option to SettingsRow and use it so the toggle sits at the top
of the row next to the label, not centered against the tall description.
* Studio: put the gear hint and example chip on one line
Move the gear example chip inline with its label so it reads as a single line
instead of wrapping onto its own row.
* Studio: move the New badge from API keys to Chat settings
Add the New badge to the Chat settings tab and drop it from API keys.
* Studio: line the Load on selection toggle up with the first description line
Offset the top-aligned control past the label row so it sits next to the On
line instead of the label.
* Studio: label the chat menu item Chat with Files (RAG)
Rename the Chat with Files entry in the chat menu settings to clarify it is RAG.
* Studio: drop the pill around the gear example so it fits on one line
Remove the background and padding from the gear example chip so it sits inline
with its label at a lower height.
* Studio: fold the gear example into the description line spacing
Render the gear example inline in the same text block so its line spacing
matches the On and Off lines instead of an extra flex gap.
* Studio: scope Show all quantizations to On Device only
Gate the downloaded-only filter on an onDevice flag so Recommended and other
browse lists always show every quant, and note On Device in the setting copy.
* Studio: tidy On Device GGUF rows
- Drop the redundant Quantizations subheading under On Device models.
- Relay GGUF vision support up to the model name as a Vision badge instead.
- Drop the repo size from On Device GGUF model rows since the quants already
show their size.
* Studio: pin the eject button and tidy General settings
- Move Eject loaded model out of the scrollable list into a centered footer so
it stays in view no matter how far the list is scrolled.
- Space out and center the gear example in the Load on selection description.
- General: drop the duplicate Unsloth version section, move llama.cpp
notifications above Helper LLM, and note new models in its description.
* Studio: add left padding before the gear example
Nudge the gear example away from its label with a small left margin.
* Studio: make the eject footer a sticky bar over the list
Pin Eject loaded model to the bottom of the scroll area with the menu
background so rows scroll under it, and drop the divider line.
* Studio: drop the eject footer background, keep it a sticky button
Make the sticky eject a centered transparent button so it coexists with the
rows scrolling behind it. The wrapper ignores pointer events so only the button
is clickable.
* Studio: give the eject button a solid background
Add the menu background, a border and a soft shadow to the sticky eject button
so it reads as a floating button over the list.
* Studio: restore the eject footer block, keep hover on the button only
Bring back the full-width menu background behind the sticky eject footer, but
keep the button compact and centered so the hover stays on the button.
* Studio: show the vision badge on On Device rows without expanding
- cached-gguf listing reports has_vision (mmproj present), so the badge shows
on the model name without opening the quantizations.
- Make the vision badge icon-only with a tooltip: "This model can process
image inputs". Falls back to the expander-reported value on older backends.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Make LM Studio and Local models sections collapsible
* Fade the eject footer instead of a solid block
* Wrap the vision badge in a bordered pill
* Taller model list with the eject footer pinned to the bottom
* Use purple for the vision badge to set it apart from GGUF
* Reduce the model list height
* Make the eject button inline with no background block
* Match the vision badge color to the Hub indigo tone
* Shorten the model list and square off the format tags
* Pin the eject button so it floats at the bottom of the list
* Give the floating eject button a tinted background
* Add bottom clearance so the list ends on white space under the eject button
* Match eject button to the menu background and unify the settings gear icon
* Move eject below the list and match its shadow and dark background
* Drop the min height so short model lists leave no white space
* Remove the eject button fill so it never covers the list
* Nest dropdown hover radius inside the menu corners
* Float the eject pill again and fix sort dropdown hover radius
* Make the eject button opaque in both themes on hover and dark
* Trim the model menu bottom padding so it stops clipping the last row
* Match dark eject background to the Search Hub button and pad row indicators
* Fade the model list bottom edge while rows sit below the fold
* Lift the eject button and trim the section toggle right padding
* Nudge the model list taller and run the bottom fade to the box edge
* Nudge the model list slightly taller
* Remove the eject button shadow
* Align the eject button to the right
* Widen the Search Hub and dropdowns and right-align them
* Seat the eject button at the base and restore On Device right padding
* Reduce the Search Hub and dropdown width by 4px
* Widen the model menu so the section toggle keeps its padding
* Make the eject button an icon-only button with shadow
* Tighten section tab padding to cut the grey between tabs
* Revert section tab padding back to px-3
* Remove the section toggle trailing padding
* Add an eject button beside the model selector trigger
* Shrink the in-list eject button to a smaller proportional size
* Raise the in-list eject button
* Make the trigger eject a bare icon next to the dropdown arrow
* Revert eject back to the labeled button on the right
* Place the format and sort dropdowns next to the section toggle
* Raise the eject button and shorten its label to Eject model
* Widen the gap between the toggle and dropdowns slightly
* Align Search Hub with the last dropdown via a shared-width grid
* Narrow the model menu for symmetric padding
* Stretch the search row so Search Hub lines up with the last dropdown
* Inset the list so the right padding matches the left
* Right-align dropdowns and full-width search so Search Hub meets the last dropdown
* Pack section toggle and dropdowns with a uniform gap
* Inset search row so Search Hub aligns with the Trending dropdown
* Trim model menu right padding to match the left
* Nudge model list scrollbar inward
* Move eject button to the bottom left with a light shadow
* Shorten show all quantizations description
* Keep eject button right-aligned, nudged in from the edge
* Move Connected into the section toggle as a cloud-icon tab
* Align eject button with the format tag edge
* Right-align Connected layout so Search Hub meets Trending
* Download selected models through the Hub download manager
* Add Other models section for non-Unsloth downloads
* Add directions icon and shortcut for Other models section
* Space out subheadings and gate Other models on non-Unsloth downloads
* Use direction-right icon for Other models
* Use flag icon for Other models
* Widen Connected menu so dropdowns align with Search Hub
* Model selector: truncate long quant labels and tidy layout
- Hub GGUF card: truncate long file-path quant labels with an ellipsis
instead of overflowing the row.
- Connected layout: left-pack the dropdowns and size the box so the last
dropdown's right gap matches the pill's left gap, with Search Hub on its edge.
- On Device: show MLX/Safetensors with the size on non-GGUF rows.
- Connected list rows use the same grey hover as the tabs; the selected
section tab no longer shows a hover change.
* Model selector: drop stale custom section on restore
A persisted custom section value no longer maps to a tab, so restoring it
opened the picker to an empty view. Fall back to recommended instead.
* Model selector: align the non-connected search bar with the All dropdown
Nudge the non-connected box width so the search bar's right edge meets the
All dropdown, which lands Search Hub on the last dropdown's edge.
* Studio chat model selector: remember last tab, route non-GGUF downloads through Hub, stack overlays
- Restore the last Hub section (Recommended / On Device) on every open instead of always snapping to On Device when downloads exist.
- Route uncached non-GGUF repos (safetensors / MLX) through the Hub download manager via a snapshot download, so every model download shows in the bottom-right indicator and follows Load on selection like GGUF.
- Allow safetensors in Recommended on Mac (they run locally there now), and honor the Safetensors format filter instead of dropping it via the recommendation default.
- Stack bottom-right overlays in one column so the download panel and banners never overlap.
- Add evenly spaced divider lines between the On Device subheadings.
- Pad the bottom of the list so the floating Eject pill never covers the last row.
* Studio downloads panel: widen left padding on header and rows
Bump the left inset to pl-4 while keeping pr-3 so the collapse and cancel buttons stay put.
* Studio: update cached-gguf route tests for the has_vision field
list_cached_gguf now returns has_vision per row (vision badge on On Device);
the expected dicts were missing it. True for the mmproj vision repo, False elsewhere.
* Studio: keep MLX/safetensors selectable in chat-only Mac search
The empty Recommended view allows GGUF plus MLX/safetensors on Mac, but the
curated and HF search lists dropped non-GGUF in chat-only via a GGUF-only filter,
so typing a query hid runnable Mac models. Reuse isRecommendableFormat in both
lists so search matches the empty view (chat-only non-Mac stays GGUF-only).
* Model selector: restore global model search and fix GGUF/device-fit regressions
- Search: training, export and onboarding pickers searched only the unsloth org
on a typed query. Restore the prior behavior (global Hub search with unsloth
floated first when a query is typed, curated unsloth listing when empty).
- Recommended browse: the GGUF/MLX-only gate ran before the format filter, so
the Safetensors filter and the Trending/Recent sorts always came back empty.
Apply that gate only for the Recommended sort and chat-only mode.
- GGUF metadata: request the gguf expand field through listModels so repos with
no size token in the name (Kimi, MiniMax, GLM) report a param count for the
size and OOM badge.
- Local GGUF: custom-folder and standalone ./models/*.gguf files now load
directly with the GGUF marker instead of dead-ending in the variant expander,
and scanned GGUF folders are classified via a backend model_format hint.
- Device fit: use system RAM in the budget on unified-memory hosts, and keep MLX
rows selectable on chat-only Macs.
- kv-cache-estimate: resolve the quant from the snapshot-relative path, skip MTP
drafter files, and prefer the most complete snapshot (mirrors the variant
scanner). Bound the Ollama manifest walk.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Model selector: classify suffixless local GGUF folders consistently
Complete the model_format plumbing so a GGUF folder is detected and loaded
through the same GGUF path that the format filter already uses:
- _scan_models_dir: a config.json no longer disqualifies a folder whose only
weights are .gguf, so HF GGUF repos shipping a config still classify as GGUF.
- _scan_lmstudio_dir: emit model_format for every GGUF row (LM Studio dirs
rarely carry a -GGUF suffix), via a shared _dir_model_format helper.
- Custom Folders and LM Studio rows: use localModelIsGguf (the same helper the
filter uses) so the row label, expand-vs-direct-load, and isGguf flag agree;
a suffixless GGUF folder no longer filters as GGUF but loads as non-GGUF.
Adds tests/test_local_model_format.py covering the classification rule.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio model selector: tighten section spacing
Trim each subheading's gap to its rows (pb-1.5 to pb-1) and pull the On Device
heading block tight to the controls while Recommended keeps a little top room.
* Hub: format filter fix, sort defaults, avatar and layout polish
- Format dropdown now filters the feed's Latest list too, so the default
GGUF hides fp8/safetensors and picking a format changes the rows.
- Latest Unsloth Models sorts by newest created, not recently updated.
- Sort dropdown order: Newest, Trending, Most downloads, Recently
updated, Most likes.
- Unsloth uploads with no upstream provider logo show the Unsloth avatar
instead of a colored initial.
- Owner scope pill gets a little more room before the chevron.
- README detail column lines up with the top bar (both-edges gutter).
- Long file-path quant labels truncate instead of overflowing the row.
- Model list keyboard nav no longer clips the focus ring.
- Run settings sheet: restore the Remember settings toggle and larger
Load/Cancel buttons on the staged load flow.
* Hub: hide the RAG embedding model from browse previews
The Hub discover feed and chat model selector pull from the Hugging Face
listing on the client, which the backend _is_hidden_model filter never
touches, so the RAG embedder (unsloth/bge-small-en-v1.5-GGUF) and the
llama.cpp validation probe leaked into the lists.
Added isHiddenModelId mirroring the backend needles and filtered it out of
the discover rows, the trending feed, and the selector's recommended and
Hugging Face search lists. Per-repo file and download views are untouched,
so the model is never deleted and a reinstall still shows it as already
downloaded.
* Studio: skip hidden dirs when checking a folder for downloaded models
_dir_has_downloaded_model walked the tree with rglob("*") bounded by
max_entries. rglob yields entries in arbitrary order and counts every one, so a
model directory that also holds a large hidden subtree (.git/.cache/venv) could
exhaust the budget before reaching the real weights and falsely report no model,
hiding a valid Recommended-folder chip. Replace the generic-weights pass with a
bounded BFS that skips hidden directories so their entries can't starve the walk.
Adds a regression test (50-entry .git beside the weights, max_entries=10).
* Fix/adjust model selector handling for PR #6364
* Studio: address codex review on the staging/recommended-folder paths
- chat-page auto-load: selectModel only clears pendingSelection on success, so a
failed auto-load left the hidden stage (and its edited load knobs) behind.
Abandon the stage when it still matches the failed pick.
- model picker: count fine-tuned rows in the On Device empty check so a
fine-tuned-only tab no longer shows a false 'No models on device' message
above the Fine-tuned section.
- general settings: add the remembered per-model load settings key to PREFS_KEYS
so 'Reset all local preferences' actually clears it.
- recommended-folders: recognize PyTorch .bin weights (gated by the scanner's
weight-name prefixes) so a .bin-only model folder still earns a chip; add tests.
* Studio: name-gate .bin weight detection and complete selector preference reset
Follow-up to the codex review on the model_format/recommended-folder paths:
- _dir_model_format and _scan_models_dir treated any .bin (incl. tokenizer.bin)
as a non-GGUF weight, so a suffixless GGUF folder shipping a companion .bin was
misclassified as a plain checkpoint and routed through the wrong load path.
Factor the scanner's weight-name gating into shared _is_weight_bin /
_has_non_gguf_weights helpers and use them everywhere (also in
_dir_has_downloaded_model).
- PREFS_KEYS was missing the new 'Select model settings' keys (load on selection,
expand/show-all quantizations), so 'Reset all local preferences' left them set.
- On Device cached search dropped the active format filter while a query was
typed; keep matchesFormatFilter applied so the format dropdown stays consistent.
Adds tests for the tokenizer.bin vs weight-.bin classification.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: validate Ollama blobs, gate staged context, honor RAM budget on no-GPU hosts
- recommended-folders: only count an Ollama dir once its manifest resolves to an
on-disk model blob, so a failed/pruned pull no longer surfaces an empty chip
- GGUF variant click: only seed the staged contextLength for already-downloaded
picks, so choosing an undownloaded quant from a partially cached repo still
starts its download (the staging effect short-circuits on a known context)
- device fit: classify GGUF variants against the system-RAM budget on no-GPU /
unified-memory hosts instead of reporting everything as fits, and pass
systemRamGb to every variant expander regardless of gpu.available
* Studio: scope Hub search to Recommended, fix staged non-GGUF settings, keep local MLX on Mac
- model picker: only run the Hub search hooks on the Recommended section. On
Device / Connected render local data, so typing there no longer fires HF
requests or a spinner and the local/offline flow is preserved
- chat settings: when a pick is staged, decide the GGUF-only controls from the
staged model's type, not the currently loaded model's. A staged non-GGUF Hub
repo no longer inherits a loaded GGUF's context/KV/speculative controls
- On Device: keep local MLX builds in ./models selectable on Mac (chat-only ran
GGUF/MLX only, but the filter dropped MLX before the format toggle)
---------
Co-authored-by: shimmyshimmer <info@unsloth.ai>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
* Show model provider/org in the trust_remote_code consent dialog
The consent dialog showed only the trailing model name (modelName.split('/').pop()),
dropping the owner. The HF org/owner is the 'who do I trust' signal the prompt is
asking about, so render it: 'NVIDIA-Nemotron-3-Nano-4B from "unsloth"'. A null
provider for local paths and bare names leaves those renders unchanged. Applies to
the enable/blocked/malware variants (shared description block).
* Only show consent provider tag for a confident single Hub repo
Tighten parseModelDisplay so the 'from "<provider>"' tag is shown only for a
canonical owner/repo Hub id (exactly one slash, both segments non-empty) that is
not a local path and not part of a multi-repo scan. This avoids misattributing a
relative local directory name (models/llama/7b) or a LoRA base/external repo's
finding to the wrong publisher in a trust decision. Extract a ProviderSuffix
component so both description branches render the clause identically via &&.
* Tighten consent provider-tag comments
* Source the consent provider tag from the backend
The dialog inferred the provider client-side from the model id, using
scanCreatedRepos (a cleanup-only list) to detect multi-repo scope and a
regex that missed bare relative paths like a local owner/model dir. Both
could attribute the scanned code to the wrong publisher.
Move the decision to the backend, where locality and scan scope are
known: _consent_provider returns the owner only for a single, non-local,
canonical owner/repo Hub id, and the route returns it as payload[provider].
The frontend now renders scan.provider directly.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Suppress consent provider tag when external auto_map code is scanned
A single Hub repo can declare an auto_map that loads code from another repo
(owner/other--module.Class). The scanner fingerprints that external repo's
Python, but security_targets still held only the primary, so the dialog
attributed the custom code to the primary publisher. Pass the external refs
collected during the scan to _consent_provider and return no provider when any
are present, so attribution is shown only for genuinely self-contained repos.
* Trim comments to be more succinct
---------
Co-authored-by: Daniel Han <michaelhan2050@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: scale export GGUF size estimates from the real model size
The Export page showed hardcoded, model-independent GGUF quant size
labels (Q8_0 ~8.2 GB, BF16 ~14.2 GB, ...) calibrated for an ~8B model.
For a 35B MoE model like Qwen3.6-35B-A3B (67 GiB bf16, Q8 ~34 GiB) the
picker wrongly reported Q8 ~8.2 GB. Only the displayed estimate was
wrong; the actual export via save_pretrained_gguf was always correct.
Add GET /api/models/export-size, which returns a model's MoE-aware
fp16/bf16-equivalent size and total params using the existing
estimate_fp16_model_size_bytes (safetensors -> config -> local -> vllm).
The result is memoized and degrades to nulls so a size hint can never
break the Export page.
The Export picker now scales each quant from that size
(bytes ~= fp16_bytes * bits_per_weight / 16, GiB units to match the
model selector), and renders no size when it is unknown rather than a
misleading fixed number. The Est. size summary in the page and dialog
is restored now that the value comes from the backend.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio export-size: address review feedback
- Run the size estimate off the event loop with asyncio.to_thread so a slow
Hugging Face request cannot stall other API or SSE endpoints.
- Cache only successful estimates; a transient failure (offline, gated before
credentials) is no longer pinned as unavailable until restart.
- Forward the HF token so private and gated models can be sized, and refetch
when the token changes.
- Clamp the size formatter index so sub-1-byte values cannot pick an
out-of-range unit.
* Studio export-size: address second review pass
- Send the HF token in an X-HF-Token header instead of the query string, so
it never lands in URLs, logs, or browser history.
- Key the estimate cache by model id only (the fp16 size is token independent),
so HF tokens are never retained in the cache.
- Restrict local-path sizing to known Studio roots (outputs/exports/cache/home)
so an authenticated caller cannot trigger a scan of an arbitrary directory.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio export-size: fix CI (import-hoist + isolated-load test stubs)
- Import ExportSizeResponse from models.models in routes/models.py instead of
re-exporting it through models/__init__.py, so the import-hoist lint does not
flag a newly added but un-loaded re-export (models/__init__.py is unchanged).
- Add Header and ExportSizeResponse to the stubbed fastapi / models.models in
test_export_absolute_paths.py, which loads routes/models.py in isolation.
* Studio: validate export-size local path before filesystem access
CodeQL flagged the export-size local-path guard as path injection: the
user-provided model path was resolved and stat-ed before it was checked
for containment under a Studio data root. Decide containment by lexical
normalization (normpath/abspath/expanduser, no filesystem access) and
only touch the filesystem once the path is proven to sit under a trusted
root, so an unvalidated value never reaches a filesystem call. Add a
direct containment unit test (under-root, root itself, missing, /etc,
and '..' traversal).
* Studio: trim export-size comments to be more concise
Shorten docstrings and comments on the export-size endpoint, helpers, tests,
and frontend size utilities; drop comments that just restate the code. Verified
code-identical (comments only) via AST/TS-compiler check. No behavior change.
* Studio: harden export-size local-path handling
Address review feedback on the export-size endpoint's local sizing:
- Resolve symlinks and re-verify containment in _is_sizable_local_path so a
symlink inside a Studio root can't point the sizer outside it.
- Re-validate the resolved LoRA base before sizing, so a crafted adapter
whose base_model points outside the roots can't redirect the scan.
- Skip nested checkpoint-*/global_step* snapshots when summing local weight
sizes so a run dir's intermediate checkpoints don't inflate the estimate.
- Size the checkpoint directory for full fine-tune checkpoint exports (whose
base may be a local/custom path), keeping base-model sizing for adapters.
Adds tests for the adapter-base escape, symlink escape, and nested-checkpoint
exclusion.
* [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: danielhanchen <michaelhan2050@gmail.com>
* Harden model fetching: consent gate for trust_remote_code
Add a load-path consent gate that scans a model's auto_map repository code
before it executes and blocks CRITICAL/HIGH findings unless the user pins
approval of that exact code version. Capability detection stays code-free,
reading raw config.json instead of AutoConfig.
- Scan config.json and tokenizer_config.json auto_map, nested local helpers,
and external owner/name--module repos; fail closed on partial downloads.
- Gate inference, training, and export workers, including the MLX path and a
LoRA's base model, and report requires_trust_remote_code from the raw config
so chat and auto-load surface the dialog.
- Verify trusted-org auto-enable against the Hub with the request token and key
the verdict cache by token; reject local-path and spoofed names.
- Add a consent dialog showing the flagged file, line, and surrounding code.
- Thread hf_token through the scan and load paths for gated repos.
* Address review: token handling, tokenizer/LoRA scan coverage, rollback
- Send the HF token for remote-code scans in the POST body, not the URL, so it
never lands in a log or browser history.
- Collect tokenizer_config.json auto_map files directly instead of relying only
on the repo file listing.
- Resolve a LoRA's base model for the validate flag and the scan endpoint so the
dialog scans the code the workers actually gate.
- Pass the request token to the training YAML trusted-org auto-enable.
- Resend a previously approved fingerprint when rolling back to a custom-code
model after a failed switch.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Consent UX: drop legacy chat toggle, fix decline copy, purge declined downloads
The per-model consent dialog is now the single approval path for custom
(auto_map) code in chat, so three leftovers from before it existed are removed:
- Remove the "Enable custom code" switch from Chat Settings and stop persisting
trust_remote_code, so a previously saved blanket-on cannot linger and load a
model without going through per-version review. The flag stays as an internal
YAML/preset default (e.g. first-party auto-enable); the load path still gates
every custom-code load on a fingerprint only the dialog produces.
- Reword the decline message and the auto-load toast to describe approving the
model's code from the dialog, not a missing settings toggle.
- On decline, purge the repo the scan downloaded so untrusted code is not left
on disk. A new /api/models/discard-remote-code endpoint deletes only a
metadata-only cache entry the scan created; it refuses local paths, loaded
models, and any repo with weight files cached, so a model the user already had
or pre-downloaded is always left untouched. The frontend only calls it when
the scan reported created_by_scan.
Adds discard-endpoint tests (delete metadata-only, refuse on weights/gguf,
refuse local, no-op when not cached) and a created_by_scan payload assertion.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Export: remove the user-facing trust remote code toggle
The Export page kept a "Trust remote code" switch (default on) next to the HF
token field. Like chat, custom (auto_map) code should be approved per model
through the load-time review dialog, not a persistent blanket switch, so the
toggle is removed. The export load path already routes through the same consent
dialog: an HF source now starts with trust_remote_code off and only enables it
when the user approves the scanned code in the dialog (a local checkpoint the
user exported stays trusted by default). With the dialog unreachable and no
approval, an HF source loads with trust_remote_code off, which fails closed
rather than running unreviewed code.
* Block loads of repos with unsafe files using Hugging Face's security scan
The trust_remote_code consent gate covers one load-time RCE vector (a repo's
auto_map Python). It does not cover the other: a malicious pickle inside a weight
file (pytorch_model.bin, *.pkl, *.dat) deserializes during from_pretrained even
with trust_remote_code False, so a repo with a normal config plus a poisoned
pickle slips past the existing gate.
Add a metadata-only malware gate that uses Hugging Face's own scan (picklescan +
ClamAV), read via model_info(securityStatus=True).security_repo_status. It never
downloads, opens, or unpickles the flagged files; it only reads the Hub's verdict
and surfaces the flagged file names. New evaluate_file_security runs
unconditionally (independent of trust_remote_code) in every load path (inference,
training SFT/MLX, export), blocking the load when a file is flagged
unsafe/suspicious/malicious. The /remote-code-scan preflight and the validate
endpoint also report the result so the consent dialog opens as a hard block (no
override) listing the flagged files, even for a repo with no custom code.
Policy: hard block with no user override; fail open when the scan is unavailable
(offline/unscanned) so legitimate loads are not broken; no first-party exemption
(a poisoned pickle in a compromised trusted repo still blocks); local paths and
GGUF are skipped (no Hub scan, non-pickle format). Blocking does not gate on
scansDone, since that is often false for clean repos and a file already flagged
unsafe is unsafe regardless.
Adds test_file_security.py covering the block/allow/fail-open/skip matrix.
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* Address review: scan list-form tokenizer auto_map, gate unsafe files on all load paths
Fixes from a 10-reviewer pass on the model-fetching hardening:
- The remote-code scanner skipped tokenizer auto_map encoded as a [slow, fast]
list (transformers' standard tokenizer shape, e.g.
{"AutoTokenizer": ["owner/repo--tokenization_x.Slow", null]}). External
tokenizer code in that form was never fetched, scanned, or fingerprinted, so an
AutoTokenizer(trust_remote_code=True) load could run it. _auto_map_refs now
flattens string, list, and nested values. Adds a regression test.
- Compare-mode chat loads and background auto-load only gated on
requires_trust_remote_code, so a repo flagged unsafe by the Hub scan but with no
custom code skipped the hard-block dialog. Both now also gate on
requires_security_review, matching the main chat path.
- The /remote-code-scan and /validate routes collapsed a LoRA adapter to its base
before the malware scan, so unsafe files in the adapter repo itself were missed
in the pre-load review (the workers already scan both). Both routes now run the
file-security scan over the adapter and the base.
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* Require approval for all HIGH remote code, fail closed when unscannable
Tighten the load-time security gates based on review:
Consent gate
- HIGH-severity auto_map code now requires explicit, per-version approval for
every repo, including first-party unsloth/nvidia. The org is no longer a
blanket bypass: a compromised first-party repo with HIGH code still warrants
review. CRITICAL stays a hard block; clean code still loads after the consent
prompt.
- Fail closed when auto_map code is present but cannot be fully fetched or
listed to scan (gated, offline, transient, or a repo-listing failure that
could hide an imported helper). We cannot fingerprint code we cannot see, so
this is a non-approvable block, retryable once the repo is reachable.
- Scan auto_map from every config that can carry one (model, tokenizer, image
and feature processor, processor, video processor), not just config.json and
tokenizer_config.json, so a custom-processor model is not missed. The file
list is the single source of truth in remote_code_scan and is pinned to the
transformers filename constants by a guard test.
- Distinguish a genuine 404 (config truly absent) from a transient error: only
the latter forces a scan, so a repo with no config is correctly a no-op.
Malware gate
- Scan a remote repo even when its name ends in .gguf; only local paths skip the
Hub scan, so a repo cannot dodge the scan by naming itself "*.gguf".
- Correct the docstring: a file already flagged unsafe blocks regardless of
scansDone; the only fail-open path is an unavailable scan.
Coverage
- Resolve a remote LoRA adapter's base model (not just local directories) so the
base, where the code and weights actually execute, is scanned in validate,
the scan route, and the training and export workers.
- Gate the embedding training path (FastSentenceTransformer) with the malware
and consent checks, matching the other load paths.
Tests updated and added for each change.
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* Scope malware gate to the load-path vector; stop false-blocking first-party models
Follow-up hardening from a second review pass + a broad live model matrix
(unsloth/* , nvidia/* , third-party, and the eicar malware repo).
Malware / unsafe-file gate
- Scope the block to the actual RCE vector: a root-level file in a code-executing
format. from_pretrained deserializes weight files at the repo ROOT, so a flag is
only a load-path pickle vector there. Two exclusions, because neither is loaded:
inert formats (safetensors is tensor-only, gguf is non-pickle, configs/text/
images) and files in subdirectories. This keeps eicar blocked (its *.pkl/*.dat/
eicar_test_file sit at the repo root) while no longer false-blocking legitimate
first-party repos: nvidia/Nemotron-H-8B-Base-8K ships root safetensors plus NeMo
pickle checkpoints under nemo/ that the loader never touches, and the Hub flags
both; the gate previously hard-blocked it.
- Unknown / future non-"safe" levels now fail closed (block) instead of being
silently allowed, so Hub schema drift cannot introduce a bypass; in-progress
("pending"/"scanning"/"error") levels stay non-blocking to avoid false blocks.
Consent gate
- Ignore a STALE own-repo auto_map target that is absent from the repo listing (an
older config pointing at a file the repo no longer ships) instead of failing the
whole repo closed as unscannable. The present .py are still fully scanned, which
is the stronger coverage, and a file that is not there cannot execute. This
unblocks first-party models like unsloth/PaddleOCR-VL (its tokenizer_config.json
names processing_ppocrvl.py while the repo ships processing_paddleocr_vl.py). A
referenced .py that IS present but cannot be fetched, and a repo-listing failure,
still fail closed.
Remote LoRA base resolution
- Distinguish a genuine 404 (not a LoRA / repo absent -> None) from a transient
error: the transient case is retried once, then logged as a WARNING (a missed
base is scanned by neither gate) rather than silently skipped.
Discard endpoint
- Treat .onnx and .ckpt as weights so a repo whose only heavy artifact is one of
those is never eligible for the declined-download purge.
Tests added for each: load-path scoping (safetensors/subdir/Nemotron-H shapes,
unknown-level fail-closed, pending non-block), stale own-repo auto_map ref, remote
LoRA transient retry, and the empty-config-list (all-404 -> []) semantics.
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* Make LoRA-base transient-warning test robust to logging backend
Assert on the logger object directly instead of capsys, so the test does not
depend on whether the real structlog logger or the module-stub logger is active
(which varies with test collection order).
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* Allow a repo with auto_map but no executable code (e.g. GGUF) instead of blocking
A config can declare an auto_map yet the repo ship NO executable .py -- most
commonly a GGUF repo whose config.json carries an auto_map copied from the original
model (e.g. unsloth/Llama-3_1-Nemotron-Ultra-253B-v1-GGUF references
modeling_decilm.py, which the GGUF-only repo does not contain). A GGUF model loads
through llama.cpp, which never executes auto_map, and transformers cannot run a file
that is not present, so there is nothing to scan and trust_remote_code is a no-op.
The fail-closed change treated this empty result the same as "code is present but we
could not fetch it" and hard-blocked the load. Distinguish the two: repo_remote_code_files
now RAISES RemoteCodeUnscannable when code is present but cannot be fully fetched or
listed (offline / gated / transient / a present .py that 404s / a listing failure),
and returns an empty dict only when the listing succeeded and the repo genuinely ships
no executable .py. The consent gate blocks on the exception (fail closed) and allows the
empty case as a no-op. Real unscannable code still hard-blocks; eicar and CRITICAL/HIGH
custom code are unaffected.
Verified against all 37 unsloth/*Nemotron* models (two GGUF repos were false-blocked,
now load) and the existing matrix (eicar still blocks; DeepSeek-OCR / NVLM-D-72B still
prompt approvable consent). Tests updated to expect the raise for unscannable cases and
added for the no-executable-code no-op.
* Ignore vestigial auto_map in GGUF repos (llama.cpp never runs it)
A GGUF repo's config.json is often copied verbatim from the original
transformers model, auto_map and all, but a GGUF load goes through
llama.cpp which never executes auto_map, so the config is inert. Treat
a direct .gguf reference, and a repo that ships .gguf weights with no
.safetensors, as having no remote code so the consent flow is never
triggered. A mixed repo with both .gguf and .safetensors is still gated,
since the safetensors variant would load through transformers where
auto_map does run. The check sits behind the existing auto_map-present
gate so normal models pay no extra repo listing.
* Add scanner-result copy to the remote-code consent dialog
Make the consent dialog state the scan outcome in plain language for
every model. When the static scan finds nothing, reassure the user with
'Our automatic scanner did not flag any worrying files, but please
double check.' (shown only for the clean, approvable case). When the
scan flags custom code or unsafe files, label the list with 'Our
automatic scanner flagged issues including:'. The Hugging Face
attribution for unsafe files stays in the dialog description.
* Close GGUF-suffix consent bypass for repo ids ending in .gguf
The .gguf short-circuit in _config_has_auto_map skipped the scan for any
model name ending in .gguf, including a bare two-segment repo id like
'evil/model.gguf'. Such a repo can still ship safetensors plus auto_map
Python that transformers would execute, so skipping the scan was an
asymmetric bypass (file_security already scans those repos). Restrict the
short-circuit to genuine direct GGUF file references via
_is_direct_gguf_file_ref: a local .gguf path, or a remote repo_id plus
filename (three or more segments). A two-segment repo id named *.gguf now
falls through to the config scan and _is_gguf_repo file inspection, so it
only skips consent when it actually ships .gguf weights and no safetensors.
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* Align consent dialog body with the title and fix narrow-width overflow
The scan results (the 'Our automatic scanner...' label, finding/unsafe
cards, and the clean-scan reassurance) sat at the dialog's left padding
while the title and description were indented past the status icon, so
the body did not line up under the description. Move the title,
description and results into one column to the right of the icon so they
share a left edge, and let that column fill its width so the description
no longer wraps early.
Also stop a wide code snippet from pushing the dialog off-screen on
narrow viewports: AlertDialogHeader is a grid with place-items-center,
which sized the content row to its content; give the row w-full so it
fills the track, and add min-w-0 down the results chain so the snippet
scrolls inside its card instead of widening the dialog. Verified aligned
and contained from mobile portrait through ultrawide.
* Treat a repo as GGUF-only only when it ships no transformers weights
_is_gguf_repo excluded only .safetensors, so a repo with a .gguf and a
pytorch_model.bin (or .pt/.pth/.h5/.msgpack/.onnx/.ckpt) and no
safetensors was treated as GGUF-only and skipped the consent scan, even
though transformers can load that weight set and execute the repo's
auto_map code. Require the absence of ANY transformers-loadable weight
before treating the repo as a llama.cpp-only GGUF load. A genuine
GGUF-only repo (only .gguf) is still inert; a mixed repo with any pickle
or safetensors weight is gated. Adds a regression test across all the
non-safetensors weight formats.
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* Block flagged subdir weight shards referenced by a root index
The malware gate treated every subdirectory file as non-loadable, but
from_pretrained deserializes a subdir shard a root index references
(pytorch_model.bin.index.json -> shards/...-00001-of-00002.bin). Read the
root weight indexes and block a flagged subdir pickle the weight_map
points at; a flagged subdir pickle no index lists (NeMo nemo/*.distcp)
stays non-blocking, and an inconclusive index lookup fails closed.
* Pass hf_token to the export checkpoint load
ExportBackend.load_checkpoint scanned with hf_token in the worker but
loaded the weights unauthenticated, so a gated/private checkpoint passed
preflight then 401'd at from_pretrained. Add hf_token to load_checkpoint
and forward token to every from_pretrained branch; the worker passes the
command's hf_token.
* Scope created_by_scan to every HF cache the discard searches
created_by_scan used get_cache_path (active HF_HUB_CACHE only) while
/discard-remote-code deletes across active, legacy, and default caches. A
repo the user already had in a legacy/default cache was marked
scan-created and deleted on decline. Check all three caches for the repo
dir before declaring the scan created it.
* Scan the full .py closure of external auto_map repos
An auto_map cross-repo ref (owner/name--module.Class) only had its entry
file downloaded, but transformers also fetches that file's relative
imports from the same repo, so a dangerous helper.py was left outside the
scanned fingerprint. List each external repo's .py and scan the whole set
(plus the referenced entry files); fail closed if the repo cannot be
listed or fetched.
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* Fail closed when a weight index cannot be fully read
_indexed_shard_paths treated a partial result as definitive: if one weight
index read cleanly but another failed transiently, it returned the shard
paths it did see. A flagged subdirectory pickle listed only by the index we
could not read would then be classed as "not a load input" and skipped,
re-opening the very fail-open this guard was added to close.
Return None whenever any index read is inconclusive, even if another read
cleanly, so the caller blocks the already-flagged subdir pickle. A repo that
ships no index files raises EntryNotFoundError for each (never inconclusive)
and still returns an empty set.
* Match cached repos case-insensitively in the created_by_scan guard
_repo_in_any_hf_cache resolved casing only against the active cache and then
probed every cache with an exact directory name. A case-variant already
present in a legacy or default cache (models--Unsloth--Foo for a scan of
unsloth/foo) was missed, so the repo was marked created_by_scan and deleted
on decline -- but discard_remote_code_download deletes case-insensitively,
so that delete would hit the user's pre-existing cache entry. Detect
case-insensitively too, mirroring the deletion path.
* Skip remote-code and security review for selected GGUF variants
validate_model ran the trust_remote_code and Hugging Face security-scan
preflight against the repo even when the selected artifact is a .gguf. A
GGUF loads through llama.cpp, which never executes the repo's auto_map
Python and never deserializes root pickle weights, so repo-level Transformers
artifacts (a config.json with auto_map, or an unsafe pytorch_model.bin next
to the .gguf in a mixed repo) are inert for that load. Gating the GGUF on
them is a false positive. Run both preflights only for non-GGUF loads.
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* Scope the malware gate to actual load roots and serialized files
Two fixes to evaluate_file_security so it neither misses a load-path pickle nor
false-blocks an inert file:
- Honor subdirectory load roots. Spark-TTS / BiCodec call from_pretrained on the
snapshot's LLM subdirectory, so a flagged pickle directly under it is a
root-level load artifact there. A new load_subdirs parameter (set from the
model's audio type via security_load_subdirs) reclassifies those files relative
to the load root and looks for weight indexes under it, so a flagged shard in
that subdir is no longer skipped as "not root-level".
- Exempt source files. A root .py is never deserialized by from_pretrained;
executable repo code runs only through auto_map, which the remote-code consent
gate scans. Flagging a Python helper here would false-block a repo that merely
ships a build or train script.
* Scan a LoRA adapter and base as one consent unit, and gate MEDIUM code
A LoRA load runs both the adapter's and the base's repo code. The consent gate
scanned them separately and pinned one fingerprint per repo, so an adapter that
shipped its own auto_map code was either never shown in the dialog (which only
saw the base) or impossible to approve with the base's fingerprint.
evaluate_remote_code_consent_for_targets now scans all of a load's repos as a
single combined unit and pins ONE fingerprint over the union of their code, so
approving the load approves every repo's code together. evaluate_remote_code_consent
becomes a thin single-target wrapper, and an unscannable target fails the whole
load closed.
Also gate MEDIUM findings: like HIGH they now block pending pinned approval, so a
direct API caller cannot run flagged code by setting trust_remote_code=True
without consenting. Only a clean scan loads without a fingerprint.
* Preflight a LoRA load's adapter and base as one combined consent scan
scan_model_remote_code rewrote a LoRA adapter to its base and scanned only the
base for remote code, so the dialog never surfaced an adapter's own auto_map
code. Scan the adapter and base together through
preflight_remote_code_consent_for_targets, which pins one combined fingerprint
the worker gate accepts. The malware preflight is also scoped to each target's
load subdirectories.
* Apply combined consent and subdir-aware malware scan in load workers
Each load worker (inference, export, training) evaluated remote-code consent
once per target with a single shared fingerprint, so a LoRA adapter that ships
its own auto_map code could not be approved by the base's fingerprint. They now
scan the adapter and base together via evaluate_remote_code_consent_for_targets,
which pins one combined fingerprint over the union of their code. The malware
scan in each worker is also scoped to the model's load subdirectories so a
flagged pickle under a from_pretrained load subdir is not missed.
* Report a consistent trust_remote_code requirement after a model loads
validate_model reports requires_trust_remote_code from the YAML default OR the
raw auto_map, but the load, already-loaded, and status responses reported only
the YAML default. A custom-code model approved and loaded via auto_map was then
reported as not requiring trust_remote_code, so the frontend stored false and a
later retry or rollback sent trust_remote_code=false and failed.
A shared resolver reports the same requirement for a loaded model (a value
stored at load time, else the trust_remote_code the load used, else the YAML
default, else the raw auto_map check), and the load response persists it so the
status and already-loaded paths stay consistent. The selected-GGUF security
review is also scoped to the model's load subdirectories.
* Run the consent gate on training resume and for YAML-only trust_remote_code
Three frontend gaps left a model loading without the trust_remote_code it needs:
- The shared consent helper returned early when the scan found no auto_map and no
unsafe files, dropping a requirement that comes from a model's Studio YAML
default (e.g. GLM-4.7-Flash). It now grants the caller's requirement with an
empty pin instead of sending trust_remote_code=false.
- Resume-from-history called startTraining directly with no consent gate, so a
resumed run whose model needs custom code (or an old run with no approved
fingerprint) hit the worker block with no dialog. It now runs the same gate as
a fresh start.
- HF export passed requiresTrustRemoteCode=false for every HF source, so a
YAML-only model could not flip the flag before export. It now signals the
requirement for HF sources.
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* Cover both LoRA repos in validate, report GGUF as inert, purge all declined repos
Three follow-on gaps from the combined adapter+base consent work:
- validate_model resolved requires_trust_remote_code from the base alone, so a
LoRA adapter that ships its OWN auto_map code (with a plain base) was reported
as not needing trust_remote_code and the consent dialog never opened. It now
checks the [adapter, base] target set, matching the scan route and the workers
(which already gate both) and the security review already running over both.
- The already-loaded, loaded, and status responses for a selected GGUF reported
requires_trust_remote_code from the model's YAML default. A GGUF loads through
llama.cpp, which never executes the repo's auto_map Python, so the requirement
is inert for that load. They now report False, matching validate_model (which
already skips both gates for GGUF) so a status refresh cannot flip the flag
back on.
- The remote-code scan downloads both the adapter's and the base's config, but
created_by_scan tracked only the primary, so a base the scan was first to pull
into the cache was left on disk when the user declined. The scan now reports
scan_created_repos (every repo it newly cached) and the decline cleanup purges
each; created_by_scan stays for older clients. The frontend falls back to the
primary flag when the list is absent.
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* Scan the repo the load fetches, purge external code on decline, harden consent pins
Six follow-on hardening fixes from a fresh review pass over the gate:
- The malware gate scanned the literal "Spark-TTS-0.5B/LLM" alias, but the trainer
downloads it as unsloth/Spark-TTS-0.5B and loads LLM/, so the alias 404'd and
failed open, missing a flagged LLM/ pickle. evaluate_file_security now resolves
the alias to the repo the loader fetches and scans LLM/ as a load root.
- security_load_subdirs relied only on tokenizer detection, which fails on an
unresolved alias or offline; it now also honors the Studio YAML audio_type
default, so a BiCodec LLM/ load root is not missed.
- The remote-code scan downloads external auto_map repos (owner/name--module.Class),
but the decline cleanup tracked only the model/adapter/base, leaving the external
untrusted code cached. The scan now enumerates external auto_map repos and reports
the ones it created in scan_created_repos, so a decline purges them too.
- External auto_map refs failed the whole load closed on a stale or mis-derived
dotted ref (sub.mod.py vs the real sub/mod.py) even though the actual file was
present and scanned. They now drop such refs when the repo listing is real, exactly
like the own-repo path; an empty/incomplete listing still fetches and fails closed.
- The combined consent fingerprint keyed code by the raw target string, so the scan
endpoint's canonicalized casing and a worker's raw user input produced different
pins for identical code, rejecting a valid approval. Hub repo ids are now folded to
lowercase in the key (local paths stay case-sensitive), so the pin tracks the code.
- Export threaded hf_token into the weight load but not into detect_audio_type /
is_vision_model, so a gated multimodal base 404'd in detection and fell through to
the text loader. Both probes now use the same token.
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* Thread the token through check-vision and guard the gate's parallel sites
The /check-vision endpoint classified a model without the hf_token, so a gated or
private vision model 404'd in the probe and was reported as a plain text model --
the same dropped-token shape as the export probes, at a sibling site. It now passes
the token like the neighboring /check-embedding endpoint.
Add deterministic consistency guards (tests/test_security_gate_consistency.py) that
enumerate the gate's parallel sites mechanically instead of relying on a review to
spot a missed sibling: every is_vision_model / is_embedding_model / detect_audio_type
caller under routes/ and core/ must thread the token, every GGUF response must report
trust_remote_code via the resolver or False (never the raw YAML default), and every
load worker that runs the malware or consent gate must resolve the LoRA base. A new
site that drops the token or mis-reports the requirement now fails CI directly.
* Narrow the LLM alias rewrite and make audio detection token-aware
Three fixes from the confirmatory review, one a regression from the previous round:
- _load_scan_target rewrote EVERY remote repo ending in "/LLM" to unsloth/<parent>,
so a real third-party repo named "<owner>/LLM" was scanned as unsloth/<owner>
while the loader still fetched the real repo -- a fail-open hole introduced when
the Spark-TTS alias handling was added. It now rewrites only a registry-known
bicodec alias; every other "/LLM" repo is scanned as itself.
- detect_audio_type cached results under the bare model name, so an unauthenticated
probe of a gated/private repo cached None and poisoned a later authenticated call
with the token. The cache is now keyed by (normalized_name, token_fingerprint),
matching the vision cache.
- The training fallback /check-vision call dropped the hf_token, misclassifying a
gated/private VLM when the config endpoint failed. It now passes the token, like
the getModelConfig call it falls back from; checkEmbeddingModel takes the token too.
Extend the consistency guards: every capability cache must be keyed by a tuple
including the token, so a cache re-declared as Dict[str, ...] fails CI.
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* Document the broad .py scan as deliberate and enforce it with a test
The remote-code scanner scans every .py in a repo once an auto_map exists, not
just the auto_map entry's static import closure. This is intentional: the entry
module can reach a sibling via an absolute import, importlib, or exec, none of
which a static relative-import closure follows, so closure-only scanning would be
a real bypass of a load-time RCE gate. The broad scan never under-scans; the cost
is that an unrelated benign script can over-block, which is the safe failure
direction (HIGH stays approvable; only CRITICAL hard-blocks).
Spell this out at both the local and remote scan sites so the choice reads as
deliberate, and add a test asserting an unrelated, never-imported .py is still
scanned -- so a future narrowing to the static closure fails CI.
* Purge a declined remote LoRA adapter the scan downloaded
scan_model_remote_code probed the created-by-scan state AFTER resolving the base,
but get_base_model_from_lora_identifier downloads a remote adapter's own
adapter_config.json, so the adapter looked already-cached and was dropped from
scan_created_repos. On decline the adapter -- including the auto_map .py the
preflight fetched -- was left on disk, defeating the "untrusted code is not left
on disk" guarantee for the adapter itself.
Snapshot the primary's cache state BEFORE base resolution and use it when marking
the adapter scan-created; on any probe error treat it as pre-existing so a decline
never deletes it. The base and external repos are unaffected (their configs are not
downloaded before their own probe). Add a test that models the mid-scan download
side effect, which the prior static-stub tests did not.
* Clear remote-code approval when the training model changes
Switching the training model from an approved custom-code model to a clean one
kept the previous model's trust_remote_code=true and approved fingerprint in the
store: setSelectedModel reset visionImageSize on a true switch but not the
remote-code approval. The clean model then trained with trust_remote_code=true,
which bypasses the compiler and disables fused cross-entropy.
Reset trustRemoteCode and approvedRemoteCodeFingerprint on a true model switch.
The new model's own YAML default is re-applied by loadAndApplyModelDefaults, and a
custom-code model still re-opens the consent dialog before training starts, so the
only change is that a clean model no longer inherits a stale approval.
* Trim verbose comments across the model-fetching hardening changes
Condense the explanatory comments and docstrings introduced across the
trust_remote_code consent gate, the malware/unsafe-file gate, the remote-code
scanner, the load workers, the model routes, and the security frontend into
fewer, tighter lines while preserving every security rationale (fail-open vs
fail-closed direction, the deliberate broad-scan anti-bypass note, the
empty-vs-unscannable distinction, stale-ref handling, and the alias-rewrite
spoof guard).
Comments and docstrings only. No code, logic, identifiers, or test behaviour
changed; verified comment-only via the AST/TypeScript checker (40/40), with the
backend test suite and frontend tsc green.
* Do not cache transient audio-detection failures
detect_audio_type cached _detect_audio_from_tokenizer's result
unconditionally, so a transient read failure (network error or 5xx,
returned as None) poisoned the cache and the later successful probe never
ran. Mirror the vision cache: _detect_audio_from_tokenizer now returns
(audio_type, definitive) and the caller caches only definitive results.
A read that succeeds with no audio tokens, or clean 404s for every
tokenizer path, stays a cacheable None; only a genuine transient failure
(connection error, timeout, 5xx, malformed body) skips the cache so the
next call retries.
---------
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: hide the llama-server install validation probe from model pickers
The ggml-org/models / stories260K probe (install_llama_prebuilt validates
the prebuilt binary against it) can land in the HF cache and, being a 260K
toy model, sorts smallest and gets auto-selected for chat. Hide it in
_is_hidden_model alongside the RAG embedding model so it never surfaces.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* test: assert the validation probe is hidden across all model pickers
_is_hidden_model gates the model list, local, cached-GGUF and cached-models
endpoints that feed the picker search, so cover both the repo-id and the
on-disk snapshot-path forms callers pass.
* Studio: match the validation probe by exact filename, not a bare substring
Use the probe's repo id (ggml-org/models) plus its exact filename
(stories260K.gguf) so the picker filter does not also hide unrelated repos
that merely reference stories260K, e.g. user/stories260K-finetune-GGUF.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: fix Downloaded model list disappearing and order it by last download
The chat model picker scan for cached GGUF and safetensors models aborted
whenever an auxiliary Hugging Face cache dir (such as ~/.cache/huggingface/hub)
was unreadable, returning an empty list. That hid the Downloaded section and
let already downloaded models appear under Recommended. Isolate each cache
probe so an inaccessible directory is skipped instead of failing the scan.
Also order Downloaded newest-first using cached blob mtimes (multi-quant repos
group by their most recent quant), keep the section visible while searching,
and make the per-quant downloaded check per-snapshot and mmproj aware so a
Recommended quant is never falsely marked downloaded.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: harden gguf-variants scan and dedupe by newest timestamp
Guard f.stat() per file so a broken symlink or unreadable file in a
snapshot no longer aborts the downloaded check early, and match quant
labels case-insensitively. When the same repo is present in multiple
caches with equal size, keep the newest last_modified so Downloaded
ordering reflects the most recent copy.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: apply cache-scan guards to sibling endpoints found in review
Extend the inaccessible-cache guard and mmproj/stat hardening to the
parallel HF cache code paths flagged in review:
- list_local_models and the Hub inventory scan now skip an unreadable
auxiliary cache instead of returning 500.
- The GGUF download-progress endpoint excludes mmproj adapters and
guards f.stat() so one bad file does not zero a repo's progress.
- The offline snapshot scanner guards its is_dir() probes.
- The chat-only picker no longer renders a blank list when a search
matches only cached non-GGUF models.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Adds a self-contained RAG stack to Studio: knowledge bases with chunked indexing, hybrid (dense + lexical) retrieval, and an automatic first-pass context inject into chat. Embeddings run through a local llama-server GGUF backend (default unsloth/bge-small-en-v1.5-GGUF) with a sentence-transformers fallback. The chat tool loop gains a search_knowledge_base tool, a per-turn re-search cap, and source citation, layered on top of the shared ToolLoopController.
Trim and tighten code comments and docstrings across the repository. Comment-only: every changed file verified code-identical to main via AST/token comparison.
Trim and tighten code comments and docstrings across studio/ Python. Comment-only: every changed file verified code-identical to main via AST/token comparison.
Raise ruff line-length to 100 and extend the local pre-commit format pipeline (def-signature magic-comma normalization, short multi-line assert collapse, kwarg '=' spacing, blank-line-after-short-import removal, adjacent string-literal / f-string+plain merge, redundant-pass pruning). Every transform re-checks the file AST and is dropped if it would differ; the whole-repo reformat is verified AST-identical per file and idempotent.
* Studio: stop leaking internal exceptions to API clients; harden sandbox path
Security hardening for the FastAPI backend.
Error exposure (CodeQL py/stack-trace-exposure): many route handlers returned
raw caught-exception text to clients via HTTPException detail / response bodies,
which can leak internal filesystem paths and stack detail. Add shared helpers in
utils/utils.py (safe_error_detail, log_and_http_error) that log the full
exception server-side and return a generic message, and sweep the route layer
(inference, models, export, training, datasets, chat_history, providers,
mcp_servers, settings, data_recipe/{jobs,seed,validate,mcp}) to use them.
Intentionally user-facing validation messages, the existing _friendly_error SSE
paths, and upstream-service body passthrough (llama-server / OpenAI) are kept;
absolute server paths echoed in models.py browse/read errors are redacted.
Path injection (CodeQL py/path-injection): serve_sandbox_file already does
basename + realpath containment; add a strict filename allowlist
(^[A-Za-z0-9._-]{1,255}$) before the path is built as defense-in-depth and to
give the analyzer a clear sanitizer.
No behavior change beyond error-message text; status codes preserved.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review: keep curated error messages, fix remaining load leak
- inference.py /load non-native path: redact str(e) instead of leaking it
(matched the native branch which already redacted).
- llama_extra_args validation: return the curated, path-redacted message
instead of the generic fallback so users see the offending flag.
- sandbox file serving: allowlist now forbids only separators/control chars
via fullmatch, so generated images like 'loss curve.png' render again
while traversal is still blocked by basename + extension + realpath.
- Add safe_curated_detail() for domain/validation exceptions whose message
is intentionally user-facing; apply it to data_recipe job/validate,
chat conflict, provider test, and MCP probe paths (these were collapsing
to 'An internal error occurred', and 'connection' even mis-mapped to an
upstream-service message). Generic Exception paths keep safe_error_detail.
- log_and_http_error: tolerate stdlib loggers (no structlog kwargs).
- delete_openai_container: log transport errors with exc_info like list/create.
- Drop helper/HTTPException imports this change left unused.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* log_and_http_error: log original error traceback on stdlib-logger fallback
* Tidy error-helper and sandbox comments for PR #6072
* Trim redundant comments in studio error-hardening routes for PR #6072
* Re-trigger CI now that unsloth-zoo #727 is merged (Core pulls zoo main)
* Address PR #6072 review feedback
- inference.py: keep the actionable NativePathLeaseError detail (path-redacted)
instead of collapsing it to the generic message, matching the other curated
validation paths in this file.
- utils.py: log via a single formatted log.error(exc_info=error) call that works
for structlog and stdlib loggers; drop the now-unneeded try/except helper.
- models.py: use Path.name instead of os.path.basename(str(current)).
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Fix /recommended-folders 500 on unreadable model dirs (Python 3.12+)
get_recommended_folders probed candidate paths with a bare
Path(p).is_dir(). On Python <= 3.11 that returned False for an
unreadable path, but on Python 3.12+ is_dir() propagates
PermissionError (EACCES) instead, so a stock root-owned ollama
install at /usr/share/ollama/.ollama/models (mode 700) made the
endpoint 500 through the entire middleware stack.
Move the directory-accessibility check into a stdlib-only helper
utils.fs_access.is_accessible_dir that swallows OSError and keeps
the existing os.access(R_OK|X_OK) filter, restoring the pre-3.12
"unreadable path is simply not a candidate" behaviour. Add a
dependency-free regression test.
* Address review: inline helper, no new file, cover all probe sites
- Drop studio/backend/utils/fs_access.py and the cross-module import;
the guard is now a small module-level _safe_is_dir() in models.py
(also moots the import-placement / ModuleNotFoundError feedback,
since there is no longer an import to misplace).
- Apply _safe_is_dir to every system-location probe with the
vulnerable bare is_dir() pattern, not just /recommended-folders:
_build_browse_allowlist._add and the /browse-folders _add_sug
helper, so the same Python 3.12+ PermissionError cannot 500 those
endpoints either. Each site keeps its exact prior semantics
(recommended-folders retains its os.access(R_OK|X_OK) filter);
the only behavioural change is "no longer crashes".
- Rewrite the regression test to extract the real _safe_is_dir from
source via ast, keeping it dependency-free without standing up the
FastAPI app, and correct the mode-000 case.
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---------
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Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
* feat: enable deleting fine-tuned chat models
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix: tighten fine-tuned model delete guards
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix: harden fine-tuned model deletion edge cases
* fix: reject gguf export delete without variant; surface 503 on backend probe failure
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix: narrow loaded-model delete guard by gguf_variant
* fix: clear inference state when cancelling model load
* fix: verify deletion completed and prune empty parent dirs
---------
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Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
* fix _scan_ollama_dir to handle ollama cloud models correctly
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---------
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Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* Studio: Ollama support, recommended folders, Custom Folders UX polish
Backend:
- Add _scan_ollama_dir that reads manifests/registry.ollama.ai/library/*
and creates .gguf symlinks under <ollama_dir>/.studio_links/ pointing
at the content-addressable blobs, so detect_gguf_model and llama-server
-m work unchanged for Ollama models
- Filter entries under .studio_links from the generic models/hf/lmstudio
scanners to avoid duplicate rows and leaked internal paths in the UI
- New GET /api/models/recommended-folders endpoint returning LM Studio
and Ollama model directories that currently exist on the machine
(OLLAMA_MODELS env var + standard paths, ~/.lmstudio/models, legacy
LM Studio cache), used by the Custom Folders quick-add chips
- detect_gguf_model now uses os.path.abspath instead of Path.resolve so
the readable symlink name is preserved as display_name (e.g.
qwen2.5-0.5b-Q4_K_M.gguf instead of sha256-abc...)
- llama-server failure with a path under .studio_links or .cache/ollama
surfaces a friendlier message ("Some Ollama models do not work with
llama.cpp. Try a different model, or use this model directly through
Ollama instead.") instead of the generic validation error
Frontend:
- ListLabel supports an optional leading icon and collapse toggle; used
for Downloaded (download icon), Custom Folders (folder icon), and
Recommended (star icon)
- Custom Folders header gets folder icon on the left, and +, search,
and chevron buttons on the right; chevron uses ml-auto so it aligns
with the Downloaded and Recommended chevrons
- New recommended folder chips render below the registered scan folders
when there are unregistered well-known paths; one click adds them as
a scan folder
- Custom folder rows that are direct .gguf files (Ollama symlinks) load
immediately via onSelect instead of opening the GGUF variant expander
(which is for repos containing multiple quants, not single files)
- When loading a direct .gguf file path, send max_seq_length = 0 so the
backend uses the model's native context instead of the 4096 chat
default (qwen2.5:0.5b now loads at 32768 instead of 4096)
- New listRecommendedFolders() helper on the chat API
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review: log silent exceptions and support read-only Ollama dirs
Replace silent except blocks in _scan_ollama_dir and the
recommended-folders endpoint with narrower exception types plus debug
or warning logs, so failures are diagnosable without hiding signal.
Add _ollama_links_dir helper that falls back to a per-ollama-dir hashed
namespace under Studio's own cache (~/.unsloth/studio/cache/ollama_links)
when the Ollama models directory is read-only. Common for system installs
at /usr/share/ollama/.ollama/models and /var/lib/ollama/.ollama/models
where the Studio process has read but not write access. Previously the
scanner returned an empty list in that case and Ollama models would
silently not appear.
The fallback preserves the .gguf suffix on symlink names so
detect_gguf_model keeps recognising them. The prior "raw sha256 blob
path" fallback would have missed the suffix check and failed to load.
* Address review: detect mmproj next to symlink target for vision GGUFs
Codex P1 on model_config.py:1012: when detect_gguf_model returns the
symlink path (to preserve readable display names), detect_mmproj_file
searched the symlink's parent directory instead of the target's. For
vision GGUFs surfaced via Ollama's .studio_links/ -- where the weight
file is symlinked but any mmproj sidecar lives next to the real blob
-- mmproj was no longer detected, so the model was misclassified as
text-only and llama-server would start without --mmproj.
detect_mmproj_file now adds the resolved target's parent to the scan
order when path is a symlink. Direct (non-symlink) .gguf paths are
unchanged, so LM Studio and HF cache layouts keep working exactly as
before. Verified with a fake layout reproducing the bug plus a
regression check on a non-symlink LM Studio model.
* Address review: support all Ollama namespaces and vision projector layers
- Iterate over all directories under registry.ollama.ai/ instead of
hardcoding the "library" namespace. Custom namespaces like
"mradermacher/llama3" now get scanned and include the namespace
prefix in display names, model IDs, and symlink names to avoid
collisions.
- Create companion -mmproj.gguf symlinks for Ollama vision models
that have an "application/vnd.ollama.image.projector" layer, so
detect_mmproj_file can find the projector alongside the model.
- Extract symlink creation into _make_symlink helper to reduce
duplication between model and projector paths.
* Address review: move imports to top level and add scan limit
- Move hashlib and json imports to the top of the file (PEP 8).
- Remove inline `import json as _json` and `import hashlib` from
function bodies, use the top-level imports directly.
- Add `limit` parameter to `_scan_ollama_dir()` with early exit
when the threshold is reached.
- Pass `_MAX_MODELS_PER_FOLDER` into the scanner so it stops
traversing once enough models are found.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review: Windows fallback, all registry hosts, collision safety
_make_link (formerly _make_symlink):
- Falls back to os.link() hardlink when symlink_to() fails (Windows
without Developer Mode), then to shutil.copy2 as last resort
- Uses atomic os.replace via tmp file to avoid race window where the
.gguf path is missing during rescan
Scanner now handles all Ollama registry layouts:
- Uses rglob over manifests/ instead of hardcoding registry.ollama.ai
- Discovers hf.co/org/repo:tag and any other host, not just library/
- Filenames include a stable sha1 hash of the manifest path to prevent
collisions between models that normalize to the same stem
Per-model subdirectories under .studio_links/:
- Each model's links live in their own hash-keyed subdirectory
- detect_mmproj_file only sees the projector for that specific model,
not siblings from other Ollama models
Friendly Ollama error detection:
- Now also matches ollama_links/ (the read-only fallback cache path)
and model_identifier starting with "ollama/"
Recommended folders:
- Added os.access(R_OK | X_OK) check so unreadable system directories
like /var/lib/ollama/.ollama/models are not advertised as chips
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review: filter ollama_links from generic scanners
The generic scanners (models_dir, hf_cache, lmstudio) already filter
out .studio_links to avoid duplicate Ollama entries, but missed the
ollama_links fallback cache directory used for read-only Ollama
installs. Add it to the filter.
* Address review: idempotent link creation and path-component filter
_make_link:
- Skip recreation when a valid link/copy already exists (samefile or
matching size check). Prevents blocking the model-list API with
multi-GB copies on repeated scans.
- Use uuid4 instead of os.getpid() for tmp file names to avoid race
conditions from concurrent scans.
- Log cleanup errors instead of silently swallowing them.
Path filter:
- Use os.sep-bounded checks instead of bare substring match to avoid
false positives on paths like "my.studio_links.backup/model.gguf".
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review: drop copy fallback, targeted glob, robust path filter
_make_link:
- Drop shutil.copy2 fallback -- copying multi-GB GGUFs inside a sync
API request would block the backend. Log a warning and skip the
model when both symlink and hardlink fail.
Scanner:
- Replace rglob("*") with targeted glob patterns (*/*/* and */*/*/*)
to avoid traversing unrelated subdirectories in large custom folders.
Path filter:
- Use Path.parts membership check instead of os.sep substring matching
for robustness across platforms.
Scan limit:
- Skip _scan_ollama_dir when _generic already fills the per-folder cap.
* Address review: sha256, top-level uuid import, Path.absolute()
- Switch hashlib.sha1 to hashlib.sha256 for path hashing consistency.
- Move uuid import to the top of the file instead of inside _make_link.
- Replace os.path.abspath with Path.absolute() in detect_gguf_model
to match the pathlib style used throughout the codebase.
* Address review: fix stale comments (sha1, rglob, copy fallback)
Update three docstrings/comments that still referenced the old
implementation after recent changes:
- sha1 comment now says "not a security boundary" (no hash name)
- "rglob" -> "targeted glob patterns"
- "file copies as a last resort" -> removed (copy fallback was dropped)
* Address review: fix stale links, support all manifest depths, scope error
_make_link:
- Drop size-based idempotency shortcut that kept stale links after
ollama pull updates a tag to a same-sized blob. Only samefile()
is used now -- if the link doesn't point at the exact same inode,
it gets replaced.
Scanner:
- Revert targeted glob back to rglob so deeper OCI-style repo names
(5+ path segments) are not silently skipped.
Ollama error:
- Only show "Some Ollama models do not work with llama.cpp" when the
server output contains GGUF compatibility hints (key not found,
unknown architecture, failed to load). Unrelated failures like
OOM or missing binaries now show the generic error instead of
being misdiagnosed.
---------
Co-authored-by: Daniel Han <info@unsloth.ai>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Studio: add folder browser modal for Custom Folders
The Custom Folders row in the model picker currently only accepts a
typed path. On a remote-served Studio (Colab, shared workstation) that
means the user has to guess or paste the exact server-side absolute
path. A native browser folder picker can't solve this: HTML
`<input type="file" webkitdirectory>` hides the absolute path for
security, and the File System Access API (Chrome/Edge only) returns
handles rather than strings, neither of which the server can act on.
This PR adds a small in-app directory browser that lists paths on the
server and hands the chosen string back to the existing
`POST /api/models/scan-folders` flow.
## Backend
* New endpoint `GET /api/models/browse-folders`:
* `path` query param (expands `~`, accepts relative or absolute; empty
defaults to the user's home directory).
* `show_hidden` boolean to include dotfiles/dotdirs.
* Returns `{current, parent, entries[], suggestions[]}`. `parent` is
null at the filesystem root.
* Immediate subdirectories only (no recursion); files are never
returned.
* `entries[].has_models` is a cheap hint: the directory looks like it
holds models if it is named `models--*` (HF hub cache layout) or
one of the first 64 children is a .gguf/.safetensors/config.json/
adapter_config.json or another `models--*` subfolder.
* Sort order: model-bearing dirs, then plain, then hidden; case-
insensitive alphabetical within each bucket.
* Suggestions auto-populate from HOME, the HF cache root, and any
already-registered scan folders, deduplicated.
* Error surface: 404 for missing path, 400 for non-directory, 403 on
permission errors. Auth-required like the other models routes.
* New Pydantic schemas `BrowseEntry` and `BrowseFoldersResponse` in
`studio/backend/models/models.py`.
## Frontend
* New `FolderBrowser` component
(`studio/frontend/src/components/assistant-ui/model-selector/folder-browser.tsx`)
using the existing `Dialog` primitive. Features:
* Clickable breadcrumb with a `..` row for parent navigation.
* Quick-pick chips for the server-provided suggestions.
* `Show hidden` checkbox.
* In-flight fetch cancellation via AbortController so rapid
navigation doesn't flash stale results.
* Badges model-bearing directories inline.
* `chat-api.ts` gains `browseFolders(path?, showHidden?)` and matching
types.
* `pickers.tsx` adds a folder-magnifier icon next to the existing `Add`
button. Opening the browser seeds it with whatever the user has
already typed; confirming fills the text input, leaving the existing
validation and save flow unchanged.
## What it does NOT change
* The existing text-input flow still works; the browser is additive.
* No new permissions or escalation; the endpoint reads only directories
the server process is already allowed to read.
* No model scanning or filesystem mutation happens from the browser
itself -- it just returns basenames for render.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: cap folder-browser entries and expose truncated flag
Pointing the folder browser at a huge directory (``/usr/lib``,
``/proc``, or a synthetic tree with thousands of subfolders) previously
walked the whole listing and stat-probed every child via
``_looks_like_model_dir``. That is both a DoS shape for the server
process and a large-payload surprise for the client.
Introduce a hard cap of 2000 subdirectory entries and a
``truncated: bool`` field on the response. The frontend renders a small
hint below the list when it fires, prompting the user to narrow the
path. Below-cap directories are unchanged.
Verified end-to-end against the live backend with a synthetic tree of
2050 directories: response lands at 2000 entries, ``truncated=true``,
listing finishes in sub-second time (versus tens of seconds if we were
stat-storming).
* Studio: suggest LM Studio / Ollama dirs + 2-level model probe
Three improvements to the folder-browser, driven by actually dropping
an LM Studio-style install (publisher/model/weights.gguf) into the
sandbox and walking the UX:
## 1. Quick-pick chips for other local-LLM tools
`well_known_model_dirs()` (new) returns paths commonly used by
adjacent tools. Only paths that exist are returned so the UI never
shows dead chips.
* LM Studio current + legacy roots + user-configured
`downloadsFolder` from its `settings.json` (reuses the existing
`lmstudio_model_dirs()` helper).
* Ollama: `$OLLAMA_MODELS` env override, then `~/.ollama/models`,
`/usr/share/ollama/.ollama/models`, and `/var/lib/ollama/.ollama/models`
(the systemd-service install path surfaced in the upstream "where is
everything?" issue).
* Generic user-choice locations: `~/models`, `~/Models`.
Dedup is stable across all sources.
## 2. Two-level model-bearing probe
LM Studio and Ollama both use `root/publisher/model/weights.gguf`.
The previous `has_models` heuristic only probed one level, so the
publisher dir (whose immediate children are model dirs, not weight
files) was always marked as non-model-bearing. Pulled the direct-
signal logic into `_has_direct_model_signal` and added a grandchild
probe so the classic layout is now recognised.
Still O(PROBE^2) worst-case, still returns immediately for
`models--*` names (HF cache layout) and for any direct weight file.
## 3. model_files_here hint on response body
A leaf model dir (just GGUFs, no subdirs) previously rendered as
`(empty directory)` in the modal, confusing users into thinking the
folder wasn't scannable. Added a `model_files_here` count on the
response (capped at 200) and a small hint row in the modal: `N model
files in this folder. Click "Use this folder" to scan it.`
## Verification
Simulated an LM Studio install by downloading the real 84 MB
`unsloth/SmolLM2-135M-Instruct-Q2_K.gguf` into
`~/.lmstudio/models/unsloth/SmolLM2-135M-Instruct-GGUF/`. Confirmed
end-to-end:
* Home listing suggests `~/.lmstudio/models` as a chip.
* Browsing `~/.lmstudio/models` flags `unsloth` (publisher) as
`has_models=true` via the 2-level probe.
* Browsing the publisher flags `SmolLM2-135M-Instruct-GGUF` (model
dir) as `has_models=true`.
* Browsing the model dir returns empty entries but
`model_files_here=1`, and the frontend renders a hint telling the
user it is a valid target.
* Studio: one-click scan-folder add + prominent remove + plain search icon
Three small Custom Folders UX fixes after real-use walkthrough:
* **One-click add from the folder browser**. Confirming `Use this
folder` now submits the path directly to
`POST /api/models/scan-folders` instead of just populating the text
input. `handleAddFolder` takes an optional explicit path so the
submit lands in the same tick as `setFolderInput`, avoiding a
state-flush race. The typed-path + `Add` button flow is unchanged.
* **Prominent remove X on scan folders**. The per-folder delete
button was `text-muted-foreground/40` and hidden entirely on
desktop until hovered (`md:opacity-0 md:group-hover:opacity-100`).
Dropped the hover-only cloak, bumped color to `text-foreground/70`,
added a red hover/focus background, and sized the icon up from
`size-2.5` to `size-3`. Always visible on every viewport.
* **Plain search icon for the Browse button**. `FolderSearchIcon`
replaced with `Search01Icon` so it reads as a simple "find a
folder" action alongside the existing `Add01Icon`.
* Studio: align Custom Folders + and X buttons on the same right edge
The Custom Folders header used `px-2.5` with a `p-0.5` icon button,
while each folder row used `px-3` with a `p-1` button. That put the
X icon 4px further from the right edge than the +. Normalised both
rows to `px-2.5` with `p-1` so the two icons share a column.
* Studio: empty-state button opens the folder browser directly
The first-run empty state for Custom Folders was a text link reading
"+ Add a folder to scan for local models" whose click toggled the
text input. That's the wrong default: a user hitting the empty state
usually doesn't know what absolute path to type, which is exactly
what the folder browser is for.
* Reword to "Browse for a models folder" with a search-icon
affordance so the label matches what the click does.
* Click opens the folder browser modal directly. The typed-path +
Add button flow is still available via the + icon in the
section header, so users who know their path keep that option.
* Slightly bump the muted foreground opacity (70 -> hover:foreground)
so the button reads as a primary empty-state action rather than a
throwaway hint.
* Studio: Custom Folders header gets a dedicated search + add button pair
The Custom Folders section header had a single toggle button that
flipped between + and X. That put the folder-browser entry point
behind the separate empty-state link. Cleaner layout: two buttons in
the header, search first, then add.
* Search icon (left) opens the folder browser modal directly.
* Plus icon (right) toggles the text-path input (unchanged).
* The first-run empty-state link is removed -- the two header icons
cover both flows on every state.
Both buttons share the same padding / icon size so they line up with
each other and with the per-folder remove X.
* Studio: sandbox folder browser + bound caps + UX recoveries
PR review fixes for the Custom Folders folder browser. Closes the
high-severity CodeQL path-traversal alert and addresses the codex /
gemini P2 findings.
Backend (studio/backend/routes/models.py):
* New _build_browse_allowlist + _is_path_inside_allowlist sandbox.
browse_folders now refuses any target that doesn't resolve under
HOME, HF cache, Studio dirs, registered scan folders, or the
well-known third-party model dirs. realpath() is used so symlink
traversal cannot escape the sandbox. Also gates the parent crumb
so the up-row hides instead of 403'ing.
* _BROWSE_ENTRY_CAP now bounds *visited* iterdir entries, not
*appended* entries. Dirs full of files (or hidden subdirs when
show_hidden is False) used to defeat the cap.
* _count_model_files gets the same visited-count fix.
* PermissionError no longer swallowed silently inside the
enumeration / counter loops -- now logged at debug.
Frontend (folder-browser.tsx, pickers.tsx, chat-api.ts):
* splitBreadcrumb stops mangling literal backslashes inside POSIX
filenames; only Windows-style absolute paths trigger separator
normalization. The Windows drive crumb value is now C:/ (drive
root) instead of C: (drive-relative CWD-on-C).
* browseFolders accepts and forwards an AbortSignal so cancelled
navigations actually cancel the in-flight backend enumeration.
* On initial-path fetch error, FolderBrowser now falls back to HOME
instead of leaving the modal as an empty dead end.
* When the auto-add path (one-click "Use this folder") fails, the
failure now surfaces via toast in addition to the inline
paragraph (which is hidden when the typed-input panel is closed).
* Studio: rebuild browse target from trusted root for CodeQL clean dataflow
CodeQL's py/path-injection rule kept flagging the post-validation
filesystem operations because the sandbox check lived inside a
helper function (_is_path_inside_allowlist) and CodeQL only does
intra-procedural taint tracking by default. The user-derived
``target`` was still flowing into ``target.exists`` /
``target.is_dir`` / ``target.iterdir``.
The fix: after resolving the user-supplied ``candidate_path``,
locate the matching trusted root from the allowlist and rebuild
``target`` by appending each individually-validated segment to
that trusted root. Each segment is rejected if it isn't a single
safe path component (no separators, no ``..``, no empty/dot).
The downstream filesystem ops now operate on a Path constructed
entirely from ``allowed_roots`` (trusted) plus those validated
segments, so CodeQL's dataflow no longer sees a tainted source.
Behavior is unchanged for all valid inputs -- only the
construction of ``target`` is restructured. Live + unit tests
all pass (58 selected, 7 deselected for Playwright env).
* Studio: walk browse paths from trusted roots for CodeQL
---------
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Co-authored-by: Ubuntu <ubuntu@h100-8-cheapest.us-east5-a.c.unsloth.internal>
* fix: support GGUF variant selection for non-suffixed repos
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: harden GGUF detection across cached models and picker flows
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* chore: use shared GGUF picker helper for search rows
* fix: avoid mixed cache duplication and preserve GGUF fallback detection
* fix: unify GGUF cache matching and merge picker hints
* fix: normalize local GGUF matching across picker and model config
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: robust cached-gguf classification + hint-aware click routing
- _repo_gguf_size_bytes: treat size_on_disk=None as 0 and dedupe fallback
by commit_hash so partial/interrupted downloads don't TypeError out of
sum() and wipe the entire cached list.
- list_cached_gguf / list_cached_models: narrow per-repo try/except so
one malformed repo no longer poisons the whole response.
- handleModelClick: route through isKnownGgufRepo instead of the
suffix-only isGgufRepo, so non-suffixed GGUF repos still open the
variant expander from every call site.
- Replace the modelIsGgufById/resultIsGgufById Maps with Sets of known
GGUF ids to stop conflating "no hint" with "known not-GGUF".
- Make HfModelResult.isGguf required (it is always set in makeMapModel).
- Add regression tests for the None size case, mixed-repo inclusion in
cached-gguf, and per-repo error isolation.
* fix: exclude mmproj from GGUF classification and case-normalize hint lookups
- _repo_gguf_size_bytes now filters mmproj vision-adapter files so
safetensors+mmproj.gguf repos stay on the cached-models path and
non-GGUF rows no longer show zero pickable variants. A vision-capable
GGUF repo (main weight + mmproj adapter) still classifies as GGUF and
reports the main weight size.
- modelGgufIds / resultGgufIds now key on lowercased ids and
isKnownGgufRepo lowercases its lookup, so store and HF-search ids
that differ only by casing still match the same GGUF hint.
- New regression tests: mmproj-only repo excluded from cached-gguf,
same repo included in cached-models, vision-capable repo still
classified as GGUF with correct size.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
* studio: show HF model download progress in training start overlay
During the training setup phase, the overlay only displayed a static
"Loading model..." line while model weights were being downloaded from
Hugging Face. On slow connections this looked like the app had frozen.
This adds a small self-contained progress block inside the existing
TrainingStartOverlay that polls the existing
GET /api/models/download-progress endpoint and renders a Progress bar
with bytes downloaded, total bytes, and percent complete.
Notes:
- Frontend only change. No backend, worker, SSE, or runtime store edits.
- Reuses the existing getDownloadProgress client wrapper and the
existing /api/models/download-progress endpoint that already scans
the HF blob cache for completed and .incomplete files.
- selectedModel is read directly from useTrainingConfigStore inside the
overlay, so no prop drilling and live-training-view.tsx is unchanged.
- Polling runs at 1500 ms and is gated on the HF repo regex
(^[A-Za-z0-9._-]+/[A-Za-z0-9._-]+$), the same regex the backend uses,
so local paths and empty form state never hit the endpoint.
- Polling stops once progress reaches 1.0 so the bar can stay at 100
until the overlay hides on the first training step.
- Network errors are silently swallowed, matching the chat side flow
(the bar simply freezes at the last value).
- When downloadedBytes is 0 the block is hidden entirely, so cached
models do not flash a progress bar.
- When the HF API cannot determine the total size, the block falls
back to "X downloaded" with no percent and no bar.
Verified with bun run build (tsc -b plus vite build, no TypeScript
errors).
* training overlay: track dataset download + show on-disk realpath
Adds a dedicated "Downloading dataset..." section to the training-start
overlay alongside the existing model-weights one, so an HF dataset that
is downloading mid-startup is no longer mislabeled as model weights or
hidden entirely. The new GET /api/datasets/download-progress endpoint
mirrors /api/models/download-progress against the datasets-- prefix in
HF_HUB_CACHE.
Both endpoints now also return cache_path, the resolved on-disk
realpath of the snapshot directory (or the cache repo root if no
snapshot is materialized yet). The overlay surfaces this under each
download row so users can immediately see where the model and dataset
landed without digging through server logs.
The frontend's existing useModelDownloadProgress hook is generalized
to a single useHfDownloadProgress(repoId, fetcher) hook that the
model and dataset variants both delegate to, keeping polling, gating,
and completion semantics in one place.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: Polish training start overlay download progress UI (#4957)
* studio: polish training start overlay download progress visuals
* Fix formatCachePath cross-platform support and redundant sizeLabel
- Extend formatCachePath regex to also shorten macOS /Users/<user> paths to ~
- Suppress sizeLabel when no byte info is available (cachePath-only state),
since the "Preparing" badge already conveys the status
* Fix misleading status badge when download total is unknown
- Hide badge when totalBytes is 0 but downloadedBytes > 0, since we cannot
determine if the download is still in progress or already complete (happens
when HF size metadata lookup fails for gated/private repos)
- Keep "Preparing" badge for the zero-bytes cachePath-only state
- Add Windows native path shortening to formatCachePath (C:\Users\<name>)
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
---------
Co-authored-by: studio-install <studio@local.install>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* Show non exported models in chat UI
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Distinguish b/w LoRa and full fine tune saves. Cleanup
---------
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Fix custom folder scanning when pointing directly at a model directory.
When a user adds a custom scan folder that points directly at a model
directory (e.g. /path/to/gemma-4-e2b-it-gguf/ containing config.json
and gemma-4-E2B-it-BF16.gguf), the model list previously showed
individual .gguf files as separate entries instead of recognizing the
directory as a single model. Clicking any entry showed "No GGUF
variants found" because list_local_gguf_variants received a file path
and immediately returned empty.
Changes:
- Add _is_model_directory() helper that detects directories with both
config metadata and actual model weight files (excludes mmproj GGUFs
and non-weight .bin files like tokenizer.bin)
- _scan_models_dir: detect self-model and return single directory entry
- _scan_lmstudio_dir: surface model directories directly instead of
descending into them as publisher folders; handle both root and child
model directories
- Add _resolve_gguf_dir() helper for GGUF path resolution that only
falls back to parent directory when parent has model metadata
- list_local_gguf_variants / _find_local_gguf_by_variant: use resolver
so .gguf file paths inside model directories work correctly
* Add vision detection cache to is_vision_model() to avoid redundant subprocess spawns
is_vision_model() is called 4-5 times per training run for the same model
with zero caching. For transformers 5.x models, each call spawns a full
subprocess (~6s each). This adds a module-level _vision_detection_cache dict
following the same pattern as the existing _audio_detection_cache used by
detect_audio_type(). The function is refactored into a thin cache wrapper
around _is_vision_model_uncached(), saving ~12s per training run.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Include hf_token in vision cache key for gated model correctness
Cache key is now (model_name, hf_token) instead of just model_name.
This prevents stale False results when an unauthenticated probe for a
gated model is followed by an authenticated call.
* Remove test file from main PR - will be submitted separately
* Fix vision cache: normalize model names and skip caching transient failures
- Normalize model names in cache key using resolve_cached_repo_id_case()
to avoid duplicate entries for different casings of the same HF repo
(aligns with case normalization from #4822)
- Return None instead of False on transient failures (network errors,
subprocess timeouts, HF API issues) so the cache layer can distinguish
"definitely not a vision model" from "failed to check"
- Only cache definitive True/False results; transient failures are retried
on the next call instead of being permanently locked in as False
* Refine failure handling: cache deterministic failures, guard normalization
- Subprocess non-zero exit, JSON errors, and general exceptions return
False (deterministic, cached) instead of None (retryable). Only
subprocess.TimeoutExpired returns None since timeouts are transient.
- Wrap cache key normalization in try/except so resolve_cached_repo_id_case
or normalize_path failures fall back to raw model_name instead of
crashing callers.
* Harden vision detection cache: fix transient failure handling, thread safety, token security
- All subprocess failure paths now return None (transient) instead of False,
preventing permanent misclassification of VLMs after temporary HF/auth/network errors
- Use SHA256 fingerprint for hf_token in cache key instead of raw bearer token
- Add threading.Lock with double-checked locking to prevent thundering herd
of concurrent subprocess spawns for the same uncached model
- Distinguish permanent failures (RepositoryNotFoundError, GatedRepoError,
ValueError) from transient ones in _is_vision_model_uncached
- Pass resolved/normalized model name to detection (not just cache key)
- Log normalization fallback at debug level instead of silent swallow
- Thread hf_token through callers in routes/models.py and trainer.py
that previously omitted it
* Refine lock strategy and token fingerprint
- Move detection computation outside the lock to avoid serializing
long-running subprocess spawns (60s timeout) and HF API calls across
all concurrent model checks. Lock is now only held for cache writes.
- Use full SHA256 digest for token fingerprint instead of truncated
16-char prefix to eliminate collision risk.
* Fix huggingface_hub import fallback and use atomic cache read
- Add fallback import path for RepositoryNotFoundError/GatedRepoError
from huggingface_hub.utils (older hub versions) when .errors is
not available
- Use sentinel-based dict.get() for single atomic cache read instead
of two-step in/[] pattern (future-proof for no-GIL runtimes)
* [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>
* fix(studio): reuse HF cached repo casing to prevent duplicate downloads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Move cache case resolution tests to separate PR
Tests for resolve_cached_repo_id_case and get_model_config case resolution
belong in their own PR to keep this change focused on the runtime fix.
* fix(studio): debug-log HF_HUB_CACHE fallback in path_utils
* Fix stale memoization in resolve_cached_repo_id_case
- Check exact-case path before memo to ensure a newly-appeared exact
match always wins over a previously memoized variant
- Validate memoized entries still exist on disk before returning them
to prevent stale results when cache dirs are deleted/recreated
* Minor cleanups for cache case resolution
- Use .is_dir() instead of .exists() for exact-case cache check
(cache entries are always directories)
- Remove redundant fallback in _detect_audio_from_tokenizer since
get_cache_path already handles case resolution and returns None
when the model is not cached
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* feat: add scan_folders table and CRUD functions to studio_db
* feat: add scan folders API endpoints and integrate into model scan
* feat: add scan folders API client and update source types
* feat: add custom source to model filters and selector
* feat: add Model Folders section to chat settings sidebar
* style: fix biome formatting in ModelFoldersSection
* fix: address review findings for custom scan folders
empty string bypass, concurrent delete crash guard,
Windows case normalization, response_model on endpoints,
logging, deduplicated filter/map, module level cache for
custom folder models, consistent source labels, handleRemove
error surfacing, per folder scan cap
* fix: show custom folders section regardless of chatOnly mode
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* refactor: extract shared refreshLocalModelsList in pickers
* Harden custom scan folder validation and scanning
- Validate path exists, is a directory, and is readable before persisting
- Apply per-folder model cap during traversal instead of after (avoids
scanning millions of inodes in large directories)
- Wrap per-folder scan in try/except so one unreadable folder does not
break the entire /api/models/local endpoint for all callers
- Normalize case on Windows before storing so C:\Models and c:\models
dedup correctly
- Extend macOS denylist to cover /private/etc and /private/tmp (realpath
resolves /etc -> /private/etc, bypassing the original denylist)
- Add /boot and /run to Linux denylist
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Improve scan robustness and preserve Windows path casing
- Preserve original Windows path casing in DB instead of lowercasing
(normcase used only for dedup comparison, not storage)
- Catch PermissionError per child directory so one unreadable subdirectory
does not skip the entire custom folder scan
- Wrap list_scan_folders() DB call in try/except so a DB issue does not
break the entire /api/models/local endpoint
* fix: scan custom folders for both flat and HF cache layouts
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix Windows case-insensitive path dedup with COLLATE NOCASE
Use COLLATE NOCASE on the scan_folders.path column so that the UNIQUE
constraint correctly deduplicates C:\Models and c:\models on Windows
without lowercasing the stored path. Also use COLLATE NOCASE in the
pre-insert lookup query on Windows to catch existing rows with
different casing.
* Restore early-exit limit in _scan_models_dir for custom folders
Keep the limit parameter so _scan_models_dir stops iterating once
enough models are found, avoiding unbounded traversal of large
directories. The post-traversal slice is still applied after combining
with _scan_hf_cache results.
* feat: scan custom folders with LM Studio layout too
* Fix custom folder models being hidden by dedup
Custom folder entries were appended after HF cache and models_dir
entries. The dedup loop kept the first occurrence of each model id,
so custom models with the same id as an existing HF cache entry were
silently dropped -- they never appeared in the "Custom Folders" UI
section.
Use a separate dedup key for custom-source entries so they always
survive deduplication. This way a model can appear under both
"Downloaded" (from HF cache) and "Custom Folders" (from the
user-registered directory) at the same time.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Harden LM Studio scan and fix COLLATE NOCASE on Linux
- Add per-child and per-publisher OSError handling in _scan_lmstudio_dir
so one unreadable subdirectory does not discard the entire custom
folder's results
- Only apply COLLATE NOCASE on the scan_folders schema on Windows where
paths are case-insensitive; keep default BINARY collation on Linux
and macOS where /Models and /models are distinct directories
* Use COLLATE NOCASE in post-IntegrityError fallback SELECT on Windows
The fallback SELECT after an IntegrityError race now uses the same
case-insensitive collation as the pre-insert check, so a concurrent
writer that stored the path with different casing does not cause a
false "Folder was concurrently removed" error.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* fix: default HF cache to standard platform path instead of legacy Unsloth cache
* feat: show LM Studio and local models in chat Fine-tuned tab
* feat: show LM Studio models in Hub models tab
* fix: fetch local models after auth refresh completes
* Revert "fix: fetch local models after auth refresh completes"
This reverts commit cfd61f0ac7.
* fix: increase llama-server health check timeout to 600s for large models
* feat: expandable GGUF variant picker for LM Studio local models
* fix: show GGUF variant label for locally loaded LM Studio models
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: show publisher name in LM Studio model labels
* fix: set model_id for loose GGUF files in LM Studio publisher dirs
* fix: show publisher prefix in Fine-tuned tab LM Studio models
* fix: only use model_id for lmstudio source models
* fix: only show LM Studio models in Hub tab on Mac/chat-only mode
* fix: respect XDG_CACHE_HOME, handle Windows paths in isLocalPath, refresh LM Studio on remount
- _setup_cache_env now reads XDG_CACHE_HOME (falls back to ~/.cache)
instead of hard-coding ~/.cache/huggingface. This follows the standard
HF cache resolution chain and respects distro/container overrides.
- isLocalPath in GgufVariantExpander uses a regex that covers Windows
drive letters (C:\, D:/), UNC paths (\\server\share), relative paths
(./, ../), and tilde (~/) -- not just startsWith("/").
- HubModelPicker.useEffect now calls listLocalModels() before the
alreadyCached early-return gate so LM Studio models are always
refreshed on remount. Also seeds useState from _lmStudioCache for
instant display on re-open.
* fix: add comment explaining isLocalPath regex for Windows/cross-platform paths
* fix: prioritize unsloth publisher in LM Studio model list
* fix: scope unsloth-first sort to LM Studio models on all platforms
* fix: add missing _lmStudioCache module-level declaration
* fix: prioritize unsloth publisher before timestamp sort in LM Studio group
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* feat: multi-source model discovery (HF default, legacy cache, LM Studio)
* Fix multi-source model discovery bugs
- Fix lmstudio_model_dirs: add ~/.lmstudio/models as default path,
remove dead sys.platform branch, add dedup via seen set
- Fix _setup_cache_env: preserve legacy HF cache env vars when the
legacy hub directory exists and is non-empty
- Fix _scan_lmstudio_dir: use absolute path for id field so
is_local_path() returns True
- Remove LM Studio dirs from allowed_roots (scanned unconditionally)
- Replace bare except passes with logger.warning in legacy cache blocks
- Fix delete_cached_model to search both default and legacy HF caches
- Make lmstudio_dirs non-optional in TS interface (matches Python schema)
- Exclude lmstudio source from trainable model filter
- Remove unused import sys
* Scan HF default cache alongside legacy and active caches
When _setup_cache_env overrides HF_HUB_CACHE to the legacy Unsloth
path, the standard HF default cache (~/.cache/huggingface/hub) was
never scanned, hiding models downloaded before Unsloth Studio was
installed.
Add hf_default_cache_dir() and _all_hf_cache_scans() helper that
deduplicates and scans all three HF cache locations (active, legacy,
default). Used in list_local_models, list_cached_gguf,
list_cached_models, and delete_cached_model.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* feat: support full model GGUF export, disable incompatible methods in UI
* fix: resolve base model from config.json for venv_t5 export switching
* feat: detect BNB-quantized models and disable all export methods for quantized non-PEFT checkpoints
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: relocate Ollama Modelfile alongside GGUFs during non-PEFT export cleanup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
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* studio: improve onboarding UX, tooltips, and training defaults
- Change splash text to "Train and run LLMs locally"
- Add "Chat Only" card with BubbleChatIcon to skip directly to chat
- Add Skip/Skip to Chat buttons in sidebar and footer
- Back button on step 1 returns to splash screen instead of being disabled
- Change "Watch video guide" to "Get started with our guide" with new URL
- Update intro text to mention all model types + chat
- Make all tooltips clickable (in addition to hover) via React context
- Strip surrounding quotes from pasted HF tokens
- Rename "Eval Split" to "Evaluation Split"
- Add SparklesIcon to "Auto Detect" format option
- Change step 4 heading to "Choose your training parameters"
- Default max_steps to 60
- Learning rate displayed in scientific notation with +/- stepper
- Context length options capped by model's max_position_embeddings (via AutoConfig)
- Fix "QLORA"/"LORA" to "QLoRA"/"LoRA" in summary step
- Backend: add max_position_embeddings to model config endpoint
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* compare for 2 diff models
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* resolving gemini comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: disable thinking for Qwen3.5 <9B and always for AI Assist
- Change Qwen3.5 thinking threshold from <=2B to <9B (0.8B, 2B, 4B
all disable thinking by default; 9B+ enables it)
- Always pass enable_thinking=False in AI Assist helper calls
(_run_with_helper and _generate_with_backend) regardless of chat
thinking settings
* studio: address PR review comments
- Extract _get_max_position_embeddings helper to DRY config extraction
- Fix "Skip to Chat" to navigate to /chat on step 1 (was /studio)
* fix: comment out debug print statements
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: skip Shiki highlighting for incomplete SVG code fences
While streaming SVG content, the syntax highlighter (Shiki) re-parses
the entire growing SVG on every token, blocking the main thread and
freezing the code area until the fence closes. Show a plain-text
preview for incomplete SVG fences instead, similar to how Mermaid
diagrams show a placeholder while streaming.
* studio: fix default top_k from 50/40 to 20 for chat inference
Per Qwen3.5 docs (unsloth.ai/docs/models/qwen3.5), top_k should be 20
for both thinking and non-thinking modes. The model-specific config in
inference_defaults.json already had top_k=20 for Qwen3.5, but the
generic fallback defaults were wrong:
- Frontend DEFAULT_INFERENCE_PARAMS.topK: 50 -> 20
- Backend generate_chat_completion top_k: 40 -> 20
- Backend generate_chat_completion_with_tools top_k: 40 -> 20
- Frontend title generation top_k: 40 -> 20
* studio: set universal inference defaults for unknown models
Default params for any model without specific config:
temperature=0.6, top_p=0.95, top_k=20, min_p=0.01,
presence_penalty=0.0, repetition_penalty=1.0
Models with entries in inference_defaults.json (Qwen3.5, Gemma-3,
Llama, etc.) override these with their recommended values.
Updated in: frontend DEFAULT_INFERENCE_PARAMS, backend Pydantic
request models, and backend generate_chat_completion defaults.
* studio: only trust_remote_code for unsloth/ models in AutoConfig
Only set trust_remote_code=True when the model name starts with
"unsloth/". All other models default to False for safety.
* studio: move Generating spinner above the composer
The "Generating" spinner was below the send message bar, causing
the bar to jump up and down. Move it above the composer in both
the regular thread view and the welcome/empty view.
* studio: adjust toast close button position away from edge
Move the X close button on toasts (like "Starting model...") from
top-1.5 to top-3 and add right-3, giving more breathing room from
the top-right corner.
* studio: make Think button smaller with tighter icon-text gap
Reduce gap from 1.5 to 0.5, padding from px-2.5/py-1 to px-2/py-0.5,
and icon from size-3.5 to size-3.
* studio: multiple onboarding and chat UX improvements
- Move Generating spinner above composer (fixes jumping send bar)
- Make Think button smaller with tighter icon-text gap
- Chat card now inside grid (same size as Audio/Embeddings cards)
- Rename "Chat Only" to "Chat"
- Chat card requires Continue to proceed (no auto-advance)
- Continue on Chat selection skips onboarding and goes to /chat
- Tooltip (i) click on Chat card doesn't trigger navigation
- Step 1 footer Back button goes back to splash (label is "Back")
- Splash "Skip Onboarding" renamed to "Skip to Chat", navigates to /chat
- Toast close button moved away from edge
* studio: align Skip to Chat button, add Skip to footer
- Sidebar "Skip to Chat" now uses primary (green) Button style with
arrow icon, full width, aligned like step items. Shows on all steps.
- Footer: added "Skip" outline button next to Continue that goes
directly to /studio with progress saved (markOnboardingDone)
* studio: change default max steps from 30 to 60 in toggle hook
The DEFAULT_MAX_STEPS in use-max-steps-epochs-toggle.ts was still 30,
used as fallback when toggling from epochs back to max steps.
* studio: extend context length options to 262K
CONTEXT_LENGTHS now includes 65536, 131072, 262144 in addition to
the existing 512-32768 range. The onboarding step filters these by
the model's max_position_embeddings (e.g. Nemotron-3-Nano-4B has
262144), showing powers of 2 up to the model's maximum.
* studio: auto-select LoRA vs QLoRA based on model size and GPU memory
After selecting a model in onboarding, detect the total model weight
file size from HF Hub (safetensors/bin files). Then estimate memory
needed: model_size_gb * 1.5 * context_scale, where context_scale is:
- <=8192 tokens: 1.0x
- >8192 tokens: 1.7x
- >=16384 tokens: 2.0x
- >=32768 tokens: 4.0x
If the estimate fits in free GPU VRAM, default to LoRA (16-bit).
Otherwise default to QLoRA (4-bit).
Backend changes:
- Add model_size_bytes to ModelDetails (models.py)
- Add _get_model_size_bytes() using HfApi.repo_info (routes/models.py)
- Add vram_free_gb to get_gpu_summary (hardware.py)
Frontend changes:
- Add autoSelectTrainingMethod() in training-config-store.ts
- Called after model defaults are loaded
- Add model_size_bytes to ModelConfigResponse type
- Add vramFreeGb to HardwareInfo hook
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: rename "Importing ML libraries..." to "Importing Unsloth..."
* studio: show model/dataset in training status, fix LoRA/QLoRA casing
- Training status now shows 'Training "model_name"' and 'Dataset = ...'
instead of generic "Starting training..."
- Fix Studio progress section to show QLoRA/LoRA instead of QLORA/LORA
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: rename 'Skip to Chat' to 'Skip Onboarding' on splash screen
* studio: add presence_penalty support for chat inference
Add presence_penalty as a parameter across the full stack:
- Backend: llama_cpp.py generate_chat_completion/with_tools, Pydantic
models (inference.py), routes/inference.py pass-through
- Frontend: InferenceParams type, DEFAULT_INFERENCE_PARAMS (0.0),
chat-adapter.ts payload, chat-settings-sheet.tsx slider (0-2),
model defaults loading from inference_defaults.json
- Set Qwen3.5 default presence_penalty to 1.5 per official docs
- Default for unknown models is 0.0 (off)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: fix Chat card deselecting Text and aligning with other cards
* studio: fix presence_penalty not loading from inference defaults
The inference_config.py load_inference_config() was not including
presence_penalty in the returned config dict, so the Qwen3.5
default of 1.5 from inference_defaults.json never reached the
frontend. Added it to the config builder.
* studio: add delete button for cached models in model selector
Add trash icon on each downloaded model row (GGUF and safetensors) with
confirmation dialog. Backend DELETE /api/models/delete-cached endpoint
uses huggingface_hub scan_cache_dir + delete_revisions to cleanly remove
cached repos, refusing if the model is currently loaded.
* studio: restore inference defaults, reasoning, and tools on page refresh
On page refresh with a model already loaded, the frontend was not
re-applying model-specific inference defaults (presence_penalty,
temperature, etc.) or restoring reasoning/tools support flags.
Backend: Add inference config, supports_reasoning, supports_tools,
and context_length to InferenceStatusResponse.
Frontend: In the refresh callback, when an active model is detected,
apply mergeRecommendedInference and restore reasoning/tools flags
with proper Qwen3.5 size-based defaults.
* studio: fix delete dialog closing before async completes
Prevent AlertDialogAction's default close behavior with
e.preventDefault() so the dialog stays open during deletion.
Also block onOpenChange dismiss while deleting is in progress.
* fix: add Dict and Any imports to inference models
* studio: fix Qwen3.5 reasoning threshold in frontend load path
The frontend loadModel handler had the old threshold (<=2) for
disabling reasoning on small Qwen3.5 models. Changed to <9 to
match the backend. This was causing 4B to not properly disable
thinking by default when auto-loaded.
* studio: move GGUF delete to per-variant level
For GGUF repos, the trash icon now appears on each downloaded variant
row inside the quantization expander instead of on the repo-level row.
Backend accepts optional variant param to delete specific GGUF files
(blob + symlink) rather than the entire repo cache.
* studio: restore ggufContextLength on page refresh
The Max Tokens slider was capped at 32768 on page refresh because
ggufContextLength was not restored from the status response.
Now set it from statusRes.context_length on reconnect.
* fix: remove <think> from Qwen3.5 response template marker
The train-on-responses-only feature uses template markers to find
where the assistant response starts. The Qwen3.5 response marker
included '<think>\n' which is only present when thinking mode is
enabled. With thinking disabled (default for <9B), the marker
never matched, causing 100% of samples to be dropped.
Changed response marker from '<|im_start|>assistant\n<think>\n'
to '<|im_start|>assistant\n' which works regardless of thinking mode.
* studio: fix sloth ASCII art alignment in training overlay
* fix: correct sloth ASCII art alignment to match Unsloth banner
* studio: add Python and terminal tool calling to chat
Register python and terminal tools alongside web search. Python
executor validates imports (stdlib only) via unsloth_zoo
rl_environments, runs code in a subprocess sandbox with 5-min
timeout and cancel support. Terminal executor blocks dangerous
commands (rm, sudo, etc.) and runs in a temp directory.
Update llama_cpp tool loop to show tool-specific status messages
and pass cancel_event through to executors. Rename composer
toggle from "Search" to "Tools" and show TerminalIcon for
execution status pills.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: fix Nemotron/transformers 5.x support, onboarding navigation, port binding
Backend:
- Dynamic transformers 5.x detection via tokenizer_config.json fetch
(checks for TokenizersBackend class, cached per-model)
- Bump transformers 5.x version from 5.2.0 to 5.3.0 across all workers,
setup scripts (setup.sh, setup.ps1)
- Auto-enable trust_remote_code for unsloth/* models needing transformers 5.x
(workaround for NemotronH config parsing bug in transformers)
- Auto-install mamba-ssm/causal-conv1d for SSM models (NemotronH, Falcon-H1)
with --no-build-isolation --no-deps to avoid torch version conflicts
- Add SO_REUSEADDR to port check in run.py (fixes Colab proxy stale connection
falsely reporting port as in-use)
Frontend:
- Fix "Skip to Chat" navigation: use window.location.href instead of React
Router navigate() to bypass useEffect redirect race
- Fix "Skip Onboarding" on splash: navigates to /studio (not /chat)
- Fix onboarding guard: only check isOnboardingDone() on initial mount
- Fix Chat card on step 1: add sr-only spacer for consistent alignment
- Fix Chat+Text both selected: clear RadioGroup value when Chat is selected
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: split tools toggle into Search and Code buttons
Replace the single "Tools" toggle with two independent toggles:
- "Search" (globe icon) enables web search only
- "Code" (terminal icon) enables Python and terminal execution
Add enabled_tools list field to the inference payload so the
backend only registers the tools the user has toggled on. Both
toggles appear in the main composer and the compare composer.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: fix tool calling import validation and error logging
Replace unsloth_zoo-dependent import checker with a standalone
ast-based validator using sys.stdlib_module_names. This properly
blocks non-stdlib imports (numpy, requests, etc.) and returns a
clear error message to the model so it can rewrite using only
stdlib.
Add full traceback to tool streaming error logs for debugging.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: parse gpt-oss harmony channels for clean safetensors chat output
gpt-oss models emit multi-channel output via harmony protocol tokens
(<|channel|>analysis<|message|>... and <|channel|>final<|message|>...).
TextIteratorStreamer with skip_special_tokens=True strips the special
tokens but leaves channel names concatenated with content, producing
garbled output like "analysisWe need to...assistantfinalHello!".
Add HarmonyTextStreamer that decodes with skip_special_tokens=False,
parses harmony markup via regex, and emits <think>analysis</think>
for the analysis channel and plain text for the final channel --
reusing the existing frontend reasoning UI.
Also expose supports_reasoning=True for non-GGUF gpt-oss models in
the /status endpoint so the frontend enables the Think toggle.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: use unsloth_zoo for Python sandbox validation
Set UNSLOTH_IS_PRESENT=1 and import check_python_modules and
check_signal_escape_patterns directly from unsloth_zoo instead
of a standalone fallback. This gives us the full Unsloth
validation including stdlib-only import checks and signal/timeout
escape pattern detection.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: allow all imports in Python tool sandbox
Remove stdlib-only import restriction. Keep signal escape
pattern detection via unsloth_zoo for safety.
* studio: fix ReadTimeout on tool streaming final pass
The 0.5s read timeout used for cancel-checking during streaming
also fires when waiting for the first response from llama-server
(e.g. reasoning model thinking for 15+ seconds). Add
_stream_with_retry() context manager that retries on ReadTimeout
while checking cancel_event, so the model has unlimited time to
think before producing the first token. Applied to both the
regular streaming path and the tool-calling final pass.
* fix: rewrite HarmonyTextStreamer with stateful incremental parsing
The delta-on-transformed approach had two critical bugs:
1. Before the full <|channel|>X<|message|> pattern was complete, the
strip-tokens fallback emitted "analysis" as plain text. Then when
the regex matched, _transform returned a completely different format
(<think>...</think>) and the delta was computed against the wrong
base string, producing fragments like "think>", "nk>", ">".
2. Even with full matches, the closing </think> tag shifted position
as content grew, so text[prev_len:] produced garbled deltas.
Replace with stateful incremental parsing that:
- Buffers until a complete channel+message pair is seen
- Emits <think> once when analysis channel first appears
- Streams analysis content deltas (computed on channel content directly)
- Emits </think> once when final channel first appears
- Streams final content deltas
- Closes open think tags in end()
Also skip the generic all_special_tokens stripping in
_clean_generated_text for gpt-oss since HarmonyTextStreamer already
produces clean output and the generic stripping was mangling <think>
tags.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: strip all <|...|> tokens in gpt-oss cleanup, not just harmony subset
The gpt-oss tokenizer has added tokens like <|return|> (id=200002) that
are not part of the harmony channel protocol but can leak into output.
The previous regex only stripped channel|message|start|end tokens.
Broaden the _clean_generated_text regex for gpt-oss to <\|[a-z_]+\|>
which catches all pipe-delimited tokens (return, constrain, reserved,
etc.) without matching <think>/<\/think> tags.
Verified: gpt-oss all_special_tokens are only <|return|>,
<|reserved_200017|>, <|startoftext|> -- none overlap with <think>.
The harmony tokens (channel, message, start, end) are added_tokens
but not in all_special_tokens.
* fix: hide config-only model repos from cached models list
Repos that only have metadata/config files cached (no .safetensors or
.bin weight files) were showing up in the Downloaded list with tiny
sizes like "1.8 KB" or "24 KB". These are just leftover config
snapshots from architecture checks, not usable models.
Filter the cached-models endpoint to only include repos that contain
actual model weight files (.safetensors or .bin).
* studio: fix toast description text contrast in dark mode
Add explicit !text-muted-foreground to toast description classNames
so secondary text (e.g. "Releases VRAM and resets inference state.")
is readable in dark mode.
* studio: fix Chat card icon alignment with size-4 spacer
Replace sr-only span (takes no space) with a size-4 shrink-0 div
matching the RadioGroupItem dimensions in other cards, so the Chat
icon aligns vertically with Text/Audio/Vision/Embeddings icons.
---------
Co-authored-by: workspace <user@workspace.local>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Manan17 <shahmanan170602@gmail.com>
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
* studio: extract param count from model name as fallback
When HuggingFace API doesn't return totalParams for a model,
extract the param count from the model name (e.g. "Qwen3-0.6B"
-> "0.6B", "Llama-3.2-1B-Instruct" -> "1B"). Applied to both
the recommended list and HF search results.
* studio: read GGUF context_length via fast header parser, set max tokens
- Fast GGUF metadata reader (~30-55ms) parses only KV header, skips
tensor data and large arrays (tokenizer vocab etc)
- Extracts context_length and chat_template from GGUF metadata
- Returns context_length in LoadResponse for frontend to use
- Frontend sets maxTokens to actual context_length for GGUFs (e.g.
262144 for Qwen3.5-9B, 131072 for Qwen2.5-7B)
- Max Tokens slider shows "Max" and is locked for GGUFs
- Auto-load path also uses actual context_length from load response
- Toast auto-dismiss (5s) and close button for auto-load toast
* studio: GGUF TTS audio support (from PR #4318)
Add GGUF TTS audio generation via llama-server. When a GGUF model
loads, the backend probes its vocabulary to detect audio codecs
(SNAC/BiCodec/DAC/CSM/Whisper). If detected, the codec is pre-loaded
and the model is reported as audio to the frontend.
During chat, TTS models route to the audio generation path which sends
a per-codec prompt to llama-server's /completion endpoint, extracts
generated tokens/text, and decodes to WAV using AudioCodecManager.
Also strips base64 audio data from prior assistant messages to prevent
context overflow.
Co-authored-by: Manan Shah <mananshah511@gmail.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Remove package-lock.json from tracking
* studio: per-model inference defaults, GGUF max tokens fix, reasoning toggle
- Add inference_defaults.json with per-model-family sampling parameters
for ~50 families (Qwen3.5, Qwen3, Gemma-3, Llama-3, DeepSeek, etc.).
Values sourced from unslothai/docs and Ollama params blobs.
- Family-based lookup in inference_config.py: extracts model family from
identifier, matches against patterns (longest match first), merges with
priority: model-specific YAML > family JSON > default.yaml.
- Fix GGUF Max Tokens slider locked at "Max": store ggufContextLength
separately from maxTokens so the slider is adjustable (step=64).
- Fix Ministral YAML: top_p was literal string "default", now 0.95.
- Add reasoning toggle for thinking models (Qwen3.5, Qwen3, DeepSeek-R1,
DeepSeek-V3.1, etc.): detect enable_thinking support from GGUF chat
template metadata, pass --jinja to llama-server, send
chat_template_kwargs per-request. Frontend shows "Reasoning is ON/OFF"
pill button next to attachment button in composer.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: remove default system prompt injection
Backend was injecting "You are a helpful AI assistant." when no system
prompt was provided. Neither unslothai/docs nor Ollama specify a default
system prompt for most models. Now defaults to empty string, letting the
model's own chat template handle system behavior.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: use lightbulb icons and "Think" label for reasoning toggle
Lightbulb on when thinking enabled, lightbulb-off when disabled.
Label is just "Think" in both states; grayed out styling when off.
* studio: fix HTML file upload breaking chat
Replace SimpleTextAttachmentAdapter with custom TextAttachmentAdapter
(excludes text/html) and HtmlAttachmentAdapter that strips tags via
DOMParser, removing scripts/styles and extracting readable text content
instead of dumping raw HTML markup into the conversation.
* studio: show chat template in Configuration panel
Display the model's Jinja2 chat template in a new "Chat Template"
section under Settings (now open by default). For GGUFs, reads from
GGUF metadata; for safetensors, reads from tokenizer.chat_template.
Template is editable with a "Restore default chat template" button
that appears when modified. Section only shows when a model with a
chat template is loaded.
* studio: editable chat template with Apply & Reload
Chat template section now functional:
- Editing the template shows "Apply & Reload" (reloads model with
custom template) and "Revert changes" buttons
- For GGUFs: writes template to temp .jinja file, passes
--chat-template-file to llama-server on reload
- For non-GGUF: passes chat_template_override in load request
- Settings section now open by default
- selectModel supports forceReload to reload same model
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: fix DeepSeek reasoning detection and auto-load metadata
- Set _model_identifier before _read_gguf_metadata so DeepSeek
"thinking" template detection works (was always None before)
- Populate ggufContextLength, supportsReasoning, reasoningEnabled,
defaultChatTemplate in autoLoadSmallestModel GGUF path
* studio: add spacing before BETA badge in navbar
Add gap-1.5 on the logo Link container to space the BETA label
from the wordmark.
Co-authored-by: Imagineer99 <Imagineer99@users.noreply.github.com>
* studio: vertically center BETA badge with logo
---------
Co-authored-by: Manan Shah <mananshah511@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Imagineer99 <Imagineer99@users.noreply.github.com>
- GGUF: use -c 0 for model's native context size (no 4096 cap)
- GGUF: hide Max Seq Length slider (irrelevant), set Max Tokens to Max
- Non-GGUF: default Max Tokens to 4096
- Max Tokens slider shows "Max" label when at ceiling for GGUFs
- Run non-GGUF load_model in asyncio.to_thread for progress polling
- Auto-load smallest downloaded model when chatting without selection
- Wait for in-progress model load before inference (modelLoading store flag)
- Recommended list: 4 GGUFs + 4 hub models after case-insensitive dedup
- Model selector waits for cached data before rendering
- Toast close button repositioned, Sampling section open by default
- Add logging to _get_repo_size_cached exception handler