* 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* add logic for identifying out of date hf models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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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
for more information, see https://pre-commit.ci
* 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
for more information, see https://pre-commit.ci
* 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
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* 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
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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
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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
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
* fix _scan_ollama_dir to handle ollama cloud models correctly
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---------
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>
* 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
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* 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
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* 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
for more information, see https://pre-commit.ci
* 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
for more information, see https://pre-commit.ci
* 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
Three fixes on top of the download progress feature:
1. Backend: Replace broken "no .incomplete = done" completion check
with a 95% byte threshold. HF downloads files sequentially, so
between files there are briefly no .incomplete files even though
the download is far from done (e.g. Kimi-K2.5 reported "done"
after downloading 22KB of config files out of 595GB).
2. Frontend: Track hasShownProgress flag. Only show "Download
complete. Loading into memory..." if we actually displayed
download progress before. For already-cached models where the
first poll returns progress=1.0, this avoids the misleading
"Download complete" message.
3. Frontend: Deduplicate recommended vs downloaded -- filter out
models already in the "Downloaded" section. Cache the fetched
lists at module level so re-mounting the popover does not flash
an empty "Downloaded" section.
Previously only GGUF models showed download progress in Chat. Non-GGUF
models (safetensors, bnb quantized, etc.) showed a static message with
no progress indication. This adds progress tracking for all model types
and fixes several related issues.
Backend:
- Add /api/models/download-progress endpoint that checks the HF cache
blobs directory for completed and .incomplete files. Uses model_info()
(cached per repo) to determine expected total size for percentage.
- Add /api/models/cached-models endpoint that lists non-GGUF model repos
from the HF cache via scan_cache_dir().
- Fix progress stuck at 0.99: when no .incomplete files remain, report
1.0 immediately (blob deduplication can make byte totals mismatch).
Frontend:
- Remove the ggufVariant gate so download progress polling works for all
non-cached models, not just GGUFs.
- Use GGUF-specific endpoint when variant + expectedBytes available,
otherwise use the general download-progress endpoint.
- Fix toast stuck after load: check loadingModelRef.current before and
after the async poll to prevent overwriting the success toast.
- First poll at 500ms instead of waiting for the 2s interval.
- Show downloaded non-GGUF models in the Hub model picker "Downloaded"
section alongside GGUFs.
* chat only with gguf for mac devices
* resolving gpt comments
* add change-password for chat only
* hide lora adaptors dropdown
* solving gpt comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* addressing the comment
* fixing auth flow
---------
Co-authored-by: Datta Nimmaturi <venkatadattasainimmaturi@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Daniel Han