* fix: allow absolute save_directory in export paths to prevent cross-drive copy failures
The GGUF export pipeline (and all other export flows) forced every
save_directory through resolve_export_dir(), which always resolved
the path under exports_root() — typically ~/.unsloth/studio/exports/
on the system drive (C: on Windows).
When a user selected an output directory on a different drive (E:):
1. The absolute path was rejected at the Pydantic validator level.
2. Even if it got through, resolve_export_dir would re-resolve it
under C:\Users\.unsloth\studio\exports\.
3. After GGUF conversion completed on E:, the relocation step would
try to move/copy the finished files to C:, causing:
- WinError 17 (cross-drive move failure when shutil.move falls
through to a cross-filesystem copy)
- WinError 112 (disk full on C:)
Fix both layers:
- _validate_save_directory: accept absolute paths (they represent an
explicit user choice of output location).
- resolve_export_dir, resolve_output_dir, resolve_tensorboard_dir:
return absolute paths as-is instead of forcing them under the
default root. Keep the existing safety checks (null bytes, '..'
segments) and fall through to resolve_under_root for relative paths.
Fixes: https://github.com/unslothai/unsloth/issues/6082
* refactor: centralize user path validation into _resolve_user_path helper
Addresses code review feedback: the null-byte, '..', and absolute-path
checks were duplicated across resolve_output_dir, resolve_export_dir,
and resolve_tensorboard_dir. Extract a single _resolve_user_path helper
that all three delegate to.
No behavioral change — pure consolidation.
* fix: address code review — contain destructive cleanup and scope absolute paths
Address all review feedback from gemini-code-assist:
1. P1: destructive subdirectory cleanup (export_gguf)
The flattening loop in export_gguf previously rmtree'd every
subdirectory under abs_save_dir. When targeting an existing user
directory on a different drive (#6082), this could nuke unrelated
subdirectories. Now snapshot existing subdirectories before the
export and only clean up dirs created during this run.
2. P2: keep scan/read endpoints contained
Only resolve_export_dir accepts absolute paths (export is a write
path where user picks location). Reverted resolve_output_dir and
resolve_tensorboard_dir to use resolve_under_root directly — these
are used by scan/read/training endpoints that must stay contained
under their respective roots.
3. Centralization feedback
Removed the _resolve_user_path helper since it's no longer needed
with the narrowed scope. resolve_export_dir has the absolute path
logic inline with a clear docstring.
* fix: skip pre-existing subdirs in GGUF flatten loop and clean stale export intermediates
Two issues caught in code review (chatgpt-codex-connector):
1. The flattening loop moved ALL .gguf files from ALL subdirectories
into abs_save_dir, including pre-existing unrelated user subdirs.
Now skip pre-existing subdirs entirely unless they are known
export-owned intermediates (model/, model_gguf/).
2. After a failed export, known export-owned subdirectories (model/,
model_gguf/) were snapshotted as pre-existing on retry and never
cleaned up. These are now always cleaned up regardless, since they
are known intermediates created by the export pipeline.
* fix: separate write vs read export paths, guard same-dir rmtree
Three issues caught in code review (chatgpt-codex-connector):
1. P1: scan endpoint containment
resolve_export_dir was changed to accept absolute paths, but it's
also used by scan/read endpoints (routes/models.py) that must stay
contained under exports_root(). Split into:
- resolve_export_dir: contained, used by scans
- resolve_export_write_dir: accepts absolute paths, used by export
backend only
2. P1: same-directory rmtree
When a non-PEFT checkpoint's gguf_dir resolves to the same path as
abs_save_dir (user selected the checkpoint's gguf output as their
export directory), shutil.rmtree(gguf_dir) would delete the user's
chosen output directory. Now skip relocation when both paths resolve
to the same location.
3. P1: pre-existing subdir flatten loop
Reverted _EXPORT_OWNED_SUBDIRS logic — 'model/' and 'model_gguf/'
are common directory names in shared model folders and don't prove
export ownership. Now only clean up subdirs that didn't exist before
the export started.
* fix: remove dead _EXPORT_OWNED_SUBDIRS and fix _export_details for absolute paths
Two fixes from review comments:
1. Remove unused _EXPORT_OWNED_SUBDIRS declaration (leftover from
previous iteration that was intentionally removed).
2. _export_details now returns the full absolute path when the export
target is outside exports_root(), instead of truncating to basename.
Users who export to E:\ can now see the full destination path in
the success dialog.
* fix: use unique tmp dir for GGUF intermediates to avoid overwriting user dirs
When exporting to an absolute destination that already contains a
model/ subdirectory (e.g. a shared models folder), the hard-coded
model_save_path would overwrite files in that unrelated directory.
Use _tmp_model_<uuid> as the intermediate path instead, so user
directories are never touched. The tmp dir is created as a new subdir
of abs_save_dir and cleaned up by the flatten loop after GGUF files
are relocated.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix GGUF local export paths for PR #6088
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address GGUF export follow-ups for PR #6088
* Clean GGUF temp dirs on export failure for PR #6088
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix/adjust export path tests for PR #6088
* Fix/adjust export path review findings for PR #6088
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix/adjust home export path handling for PR #6088
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
* chore(studio/frontend): normalize line endings to LF
45 source files under studio/frontend/ were committed with CRLF or mixed
line endings while the rest of the repo and the JS/TS tooling assume LF.
Add a scoped `studio/frontend/** text=auto eol=lf` rule to .gitattributes
and run `git add --renormalize studio/frontend` so these files are stored
with LF in the index. The rule is scoped to the frontend tree (not a
repo-wide *.ts/*.tsx/... policy) so it cannot force LF on files elsewhere;
text=auto leaves binary assets (logos, fonts) untouched.
This commit is whitespace-only (CRLF -> LF) — no source content changed
(verified with `git diff --ignore-cr-at-eol`). It is intentionally
isolated so it can be listed in .git-blame-ignore-revs and skipped by
reviewers and `git blame`.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* chore: ignore the frontend LF-normalization commit in git blame
Add .git-blame-ignore-revs listing the whitespace-only line-ending
normalization commit so it doesn't pollute `git blame` output. GitHub
applies this file automatically; locally run
`git config blame.ignoreRevsFile .git-blame-ignore-revs`.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
* Studio: use rounded rectangles for menu item hover states instead of pills
Dropdown, select, and model picker items previously used fully rounded
pill highlights. Switch them to an 11px rounded rectangle so hover and
selected states match across the plus menu, profile menu, run settings,
selects, and the model picker. Also add a small side gutter to the plus
menu so item highlights sit slightly inset from the menu edge.
* Studio: concentric menu corners, wider gutters, single-item pill menus
Container radius now equals the item hover radius plus the side gutter
(12px + 10px = 22px) so the curves run parallel. Menus with a single
item render as fully rounded pills. The profile menu gets the same
gutter and hover radius. Model picker rows go back to their original
fully rounded hover.
The --local / GGUF-only install resolves its Python deps from
no-torch-runtime.txt, installed with --no-deps. That file was missing the
RAG group that studio.txt declares (sqlite-vec, pymupdf, python-docx), so a
fresh `unsloth studio` came up with RAG disabled: rag_db.py cannot import
sqlite_vec and logs "RAG unavailable: sqlite-vec extension could not be
loaded", and the knowledge-base routes return 503. python-docx was also
absent, so DOCX ingestion failed.
Add the three RAG store and document-parsing deps with the same pins as
studio.txt so knowledge bases work out of the box on the no-torch path.
sentence-transformers (dense embeddings) was already present.
The post-install path cleared only the in-memory freshness caches and then
re-primed the 24h disk cache with a forced GitHub refresh. When that refresh
cannot reach GitHub, latest_published_release falls back to the last-good disk
value, so a still-fresh same-base mix tag cached before the swap (b9596-mix-aaa
vs the just-installed b9596-mix-bbb) is replayed and the prebuilt reads as
behind, surfacing a false update banner that points back at the build that was
just replaced.
Give reset_caches a drop_disk option and use it on the update path: with the
disk cache gone, an offline post-install refresh leaves latest as None and the
banner fails open (off) instead of lingering on the stale same-base value. The
no-arg form stays in-memory only. Adds regression coverage for the drop, the
default no-op, and the fail-open vs stale-replay contrast.
* Studio: tune llama.cpp env for data-center GPUs
Detect datacenter/professional NVIDIA GPUs at llama-server launch and set
the llama.cpp env flags that help them, gated so consumer GeForce, AMD/ROCm,
CPU and macOS are never touched.
- GGML_CUDA_FORCE_CUBLAS_COMPUTE_32F=1 for any DC GPU (FP32 cuBLAS
accumulation). On a B200 this is ~0% throughput cost with identical
perplexity (7.3230 wikitext-2-raw, baseline and on), where on GeForce the
same flag costs real throughput, hence the gate.
- GGML_CUDA_P2P=1 and CUDA_SCALE_LAUNCH_QUEUES=4x for multi-GPU DC boxes.
Benchmarked on 6x B200: +33-51% prompt processing on tensor (row) split and
+8-16% on the default pipeline (layer) split, with no regression on the
other split or on token generation.
Detection uses torch device names (A100/A30/H100/H200/H800/GH200/B200/GB200/
GB300/L40/L4/RTX PRO 6000/RTX 6000 Ada). A mixed box with one consumer GPU in
the selection is treated as non-DC. All writes are setdefault so a user value
always wins, and UNSLOTH_DISABLE_DC_TUNING=1 turns the whole thing off.
37 unit tests cover detection, multi-GPU gating, user-override precedence, the
disable flag and fail-open on error.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: fix data-center GPU detection false positives and physical-id mapping
Two issues in the data-center llama.cpp env tuning gate:
- _is_datacenter_gpu matched the marker allowlist as unbounded substrings, so
workstation/laptop parts "NVIDIA RTX A1000" and "NVIDIA RTX A3000" matched
"a100"/"a30" and were wrongly tuned as data-center GPUs (forcing FP32 cuBLAS
accumulation and the multi-GPU env, which carry a real cost on those cards).
Switch to a word-boundary regex.
- gpu_indices carries physical GPU ids (translated from torch ordinals by
_get_gpu_free_memory via CUDA_VISIBLE_DEVICES), but they were passed straight
into torch.cuda.get_device_properties, which expects mask-relative ordinals.
On a masked host (e.g. CUDA_VISIBLE_DEVICES=4,5,6,7) a selection like [4,5]
fell out of range and silently dropped the tuning, and on a mixed mask it could
probe the wrong GPU class. Build a physical-id to device-name map mirroring
_get_gpu_free_memory, then look up the selection by physical id.
Add regression tests for the A1000/A3000 false positives and for masked-host
physical-id selection (reordered and mixed-class masks included).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: tighten data-center GPU tuning comments
Comment-only pass over the DC tuning block and its tests: shorten verbose
docstrings/comments, drop ones that restate the code, collapse multi-line
blocks. Keep the load-bearing rationale (physical-id vs ordinal mapping, the
word-boundary reason, the B200 benchmark numbers). No code change: verified
with comment_tools.py check --strip-docstrings (code unchanged, comments only).
---------
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Fix step count mismatch when sequence packing is enabled
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Emit a single step-0 progress event and guard applyStatus totalSteps
Merge the two consecutive _update_progress calls before train() so the
step-0 gate in _on_progress fires once instead of twice, avoiding a
duplicate startup event and a null-metric step-0 row in training_metrics.
Apply the same positive-number guard to applyStatus that applyProgress
uses, so a stale or startup status poll can no longer overwrite the
packed step count with 0 or replace it with a stale total.
* Log debug message when train_dataset length is unavailable
The TypeError fallback for length-less datasets (e.g. streaming
IterableDataset) was silent, leaving no trace that the step estimate
came from the raw dataset rather than the packed one.
* [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: Etherll <61019402+Etherll@users.noreply.github.com>
IOReport energy counters can reset (sleep/wake, power gating), making a poll
delta negative. Return None for a negative total so the monitor shows -- for
that poll instead of a bogus negative wattage; it self-corrects next poll.
* Studio: Add inline confirmation (Allow/Always allow/Deny) for tool calls
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix race in tool-call confirmation gate
* Studio: gate built-in tool calls and harden the confirmation handshake
The Allow / Always allow / Deny controls only lived in the fallback tool
card, but the built-in tools (web search, python, terminal, code
execution, image generation) render with their own components and so
never showed the buttons. Those calls paused after tool_start with no way
to approve them, hanging until the 1 hour timeout. Only MCP tools, which
use the fallback renderer, actually worked.
Render the controls for every tool card by wrapping each registered tool
component (and the fallback) in thread.tsx with a shared
ToolConfirmationControls, so the gate applies uniformly.
Also make the handshake robust:
- The gate keys on a per-call approval_id minted by the backend and
echoed in tool_start, instead of session_id alone, so a stale or
concurrent confirmation can no longer resolve the wrong call.
- The approval slot is registered before tool_start is yielded, closing
the race where a fast click or an auto "Always allow" could reach the
backend before the waiter existed.
- The frontend resolves with the same session id the request was sent
with (plus the approval_id), fixing the new-thread mismatch where the
confirmation targeted a different session than the blocked stream.
- The confirm endpoint returns {resolved}; the UI keeps the buttons and
shows a retry hint until the backend confirms a match, instead of
hiding them on a failed or mistargeted post.
- The gate runs after the disabled-tool and duplicate-call checks, so a
call that will not execute is not put up for approval. A denied call is
still excluded from duplicate detection, so re-issuing and approving it
works.
- "Always allow" is scoped per session to match the backend gate.
Add backend tests for the approval registry, the SSE no-deadlock
handshake, and the loop integration (allow, deny, disabled, duplicate,
re-issue after deny).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Move "Confirm tool calls" to the Tools section
* Studio: Keep tool group open while a tool call awaits confirmation
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix tool confirmation session scope for PR #5869
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix confirmation follow-ups for PR #5869
* Apply pre-commit formatting for PR #5869
* Fix confirmation cleanup for PR #5869
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Harden confirmation lookups for PR #5869
* Studio: make the tool-call confirmation decision immutable
resolve_tool_decision accepted a second confirmation for the same approval_id
and overwrote slot["decision"] in the window before the waiter reads it and
pops the slot, so a duplicate or out-of-order POST could flip an Allow to Deny
(and returned a misleading resolved:true). Reject once the slot's event is
already set so the first decision wins. Adds a regression test.
* Fix/adjust tool confirmations for PR #5869
* [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>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
* Studio: show Apple GPU temperature and power in the GPU monitor (macOS)
The GPU monitor on Apple Silicon always showed -- for Temperature and
Power: the MLX branch of get_gpu_utilization() hardcoded None because
ioreg's AGXAccelerator PerformanceStatistics carries neither metric.
Add utils/hardware/apple.py, mirroring macmon's no-sudo approach:
- Temperature: average of the AppleSMC "Tg*" float keys via the
AppleSMCKeysEndpoint user client (ctypes/IOKit, macOS 14+).
- Power: IOReport "Energy Model" group, "GPU Energy" channels; each
poll diffs the energy counter against the previous poll's sample, so
the value is the average wattage over the polling window. The first
poll only sets the baseline and returns None.
Both readers latch to None on first failure and never raise, so
non-Mac platforms and locked-down hosts keep the previous behavior.
* Sample IOReport with the subscribed channels descriptor for PR #6187
IOReportCreateSubscription writes the channel descriptor that later samples
must use; sampling with the original requested group can return no Energy
Model entries on hosts that normalize the channel set, leaving power_draw_w
null after the baseline. Use the subscribed descriptor (matching macmon) and
fall back to the requested channels if the OS leaves it unset.
---------
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: danielhanchen <23090290+danielhanchen@users.noreply.github.com>
The post-download llama-quantize / llama-server smoke test JIT-compiles CUDA kernels on the first GPU forward pass and stalls every install and update by minutes on Blackwell (sm_100). Gate it behind _RUN_STAGED_PREBUILT_VALIDATION, disabled for now, keeping the smoke test and the source-build fallback it triggers fully intact so it can be restored by flipping the flag to True.
Hashless external prebuilts (e.g. lemonade) are not in the approved-sha256 manifest and rely on the functional smoke test as their only integrity gate, so they are always validated regardless of the flag; only approved bundles, already proven by the sha256 manifest, skip it.
The sha256 archive verification and the static Linux/macOS preflights are unchanged and still run for every install.
* fix(studio): adopt server-loaded model before chat auto-load
When the user starts Studio via `studio run -m`, the web UI could still
auto-load a different cached GGUF on the first message because the chat
checkpoint was empty. Sync from /api/inference/status before falling back
to autoLoadSmallestModel so CLI-loaded models are not replaced.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(studio): hydrate adopted CLI model and harden auto-load errors
Extract shared inference-status hydration for refresh() and CLI adopt
paths so the first chat turn gets reasoning/tools flags. Wrap auto-load
(including adopt) in try/catch for image-edit cleanup, and drop the
redundant adopt call in run().
Co-authored-by: Cursor <cursoragent@cursor.com>
* Guard model adoption against status failures and mid-flight selection for PR #5900
* ci: trigger pre-commit.ci after main merge
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* fix(studio): inherit llama_extra_args and honor --no-mmproj
Reloading the same GGUF from the UI without gguf_variant no longer drops
CLI pass-through args like --no-mmproj. Skip mmproj download and launch
when --no-mmproj is present in llama_extra_args.
Co-authored-by: Cursor <cursoragent@cursor.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix(studio): tighten GGUF llama_extra_args variant inheritance guard
Reject inherited CLI args when the request changes gguf_variant or when
omitted variant resolves differently from the stored extra_args source.
Co-authored-by: Cursor <cursoragent@cursor.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Treat --no-mmproj-auto and --mmproj-auto with last-wins parsing for PR #5902
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* fix: deduplicate lemonade ROCm prebuilt selection log
resolve_lemonade_rocm_choice() is called twice per install (direct
planner + resolve_upstream_asset_choice). The API fetch is already
memoised via _fetch_lemonade_release_cached but the selection log
lines were still emitted on both calls, printing the 'trying
lemonade-sdk ROCm prebuilt' banner and hash-manifest NOTE twice.
Add _lemonade_selection_logged set keyed on (gfx_target, asset_name)
and guard the two log() calls behind a membership check so they print
exactly once per process regardless of call count.
Also extend the _clear_lemonade_release_cache test fixture to clear
the new set between tests to prevent cross-test state bleed.
Fixes#6020
* fix: write log() output to stdout to avoid PowerShell NativeCommandError
On Windows, PowerShell treats any stderr output from a native process as
an error record and prefixes it with 'python.exe :' and sets the
ErrorId to NativeCommandError. Since log() wrote to sys.stderr, every
[llama-prebuilt] status line triggered this, making normal progress
output look like errors in the installer console.
Switch log() to sys.stdout. The download progress bar (DownloadProgress)
retains its stderr/tty logic unchanged -- that path is for interactive
terminal rendering, not status logging.
* fix: remove redundant 'or ""' in lemonade log_key
host.rocm_gfx_target is already guaranteed truthy by the early
return at the top of resolve_lemonade_rocm_choice. The fallback
was dead code.
* Keep resolver stdout machine-readable, route install logs to stdout
log() sending everything to stdout breaks the resolver modes: setup.sh
json.load()s the whole stdout, so one helper log line (network retry,
release-tag scan) corrupts the parse and silently drops back to building
"latest". Default log() to stderr and flip to stdout only on the install
path, where PowerShell otherwise renders stderr as NativeCommandError
noise. Also tighten the lemonade dedup comments.
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
On a 0.0.0.0 bind whose public ip:port is not reachable (cloud firewall),
the banner still printed "Secure link access via Cloudflare: <url>" right
after "is NOT reachable from the public internet", which reads as if the
tunnel might also be blocked. The Cloudflare quick-tunnel works regardless.
Thread the reachability probe result through a module-level _public_reachable
tri-state and, when the public probe definitively failed but the tunnel is
up, print "Also, the secure link access via Cloudflare works: <url>".
Reachable or undecided cases keep the existing wording.
* Studio: llama.cpp update banner redesign, About tab license info, inline system prompt editing, naming cleanup
- Redesign the llama.cpp update banner to match the chat composer surface
(borderless rounded card, composer shadow, Hellix Medium title), rename
actions to Update and add a 15 minute Remind me later snooze
- Keep the banner up until the user explicitly acts on it; drop the
outside click dismissal
- Add a Settings > General > Notifications toggle to disable the banner
for training-only setups (on by default)
- Rename the Help settings tab to About and add a License section
(Unsloth Studio AGPL-3.0, Unsloth Core Apache-2.0) linking to the
license files in this repo
- Make the run settings system prompt box an inline editable textarea;
the popup editor opens when the prompt overflows the box
- Pointer cursor on the preset dropdown chevron
- Dark mode toasts use the chat composer surface color
- Replace standalone Studio with Unsloth in user facing strings; keep
Unsloth Studio, LM Studio, Fine-tuning Studio, Recipe Studio and CLI
commands unchanged
* Studio: open the system prompt popup on box click, balance banner padding
- The system prompt box opens the Edit System Prompt dialog on click,
matching the pencil action
- Slightly more bottom padding on the llama.cpp update banner so the
spacing reads even next to the action pills
* Studio: replace unsloth studio update with the installer commands in update guidance
- The unsloth studio update command no longer works, so the About tab
update section now shows the one-line installer (curl or irm) for
PyPI and unknown installs, and git pull plus the local installer for
checkouts
- Add a short note that unsloth studio update is no longer supported
- Link the Installation, Updating and Windows install docs pages
- The package update banner now copies the platform installer command
instead of unsloth studio update
* Studio: rounder account menu, inline system prompt box with popup from the label
- Account menu corners go from 14px to 18px via a specific override,
since list menus pin border-radius globally
- llama.cpp banner bottom padding 22px
- System prompt is an inline editable textarea again; clicking the
System Prompt label opens the popup editor, and an overflowing
prompt opens it on box click
* Studio: show the standard install commands in the About update section
- Both one-line install commands (MacOS/Linux/WSL and Windows
PowerShell) are always shown, labeled like the docs, since running
them again updates an existing install
- Drop the unsloth studio update deprecation note
- Add the Mac install guide to the docs links
* Studio: clearer platform toggle and layout in the About update section
- Section heading is Update
- Platform picker is a pair of pill buttons, MacOS / Linux and Windows,
and only the selected platform's install command is shown
- Intro reads: To install or update Unsloth
- Local update heading separates checkout guidance from the standard
install command
* Studio: report GitHub branch instead of dev for source checkouts
A source checkout not on an exact release tag now shows
GitHub <branch> (e.g. GitHub main) as the Studio version in About.
Detached or unusual HEADs still fall back to dev.
* Studio: tighten the About update section copy and toggle styling
- Platform toggle buttons are borderless pills
- Shorter local update wording and restart note
- Docs links read Mac and Windows
* Studio: tighten line spacing in the sidebar account button
* Studio: fix vanishing compact MCP icon on hover, single line pill tooltips
- Compact caret pills (MCP, RAG) keep their icon on hover for inactive
pills too; the off switch hover rules hid the icon while compact mode
hid the X, leaving an empty slot
- Compact icon tooltips and single line compact tooltips render as full
pills; wrapped tooltips keep the 9px corners. TooltipContent measures
line count in a ref callback since Radix mounts portal content
without re-rendering the wrapper
- 1px gap between the name and Unsloth lines in the sidebar account
button
* Studio: Projects hover plus button, align recents with the label
- Hovering the Projects nav item reveals a plus button that opens the
New project dialog, with the same circular hover treatment as the
chat row actions
- Recent chat titles start at the same x as the Recents label
- The system prompt overflow lock only engages for a non-empty prompt
with a laid-out box, so a mis-measure cannot turn clicks into the
popup
* Clip system prompt overflow inside the rounded box
Wrap the inline system prompt textarea in a rounded overflow-hidden
surface so scrolled text and the scrollbar stay inside the box. The
focus ring moves to the wrapper via focus-within.
* Add updating progress bar to llama banner and shorten settings copy
While an update is applying, the banner action row becomes an
indeterminate progress bar that keeps animating under reduced motion,
matching the other loading indicators. Settings descriptions across
General, Profile, Appearance, Chat, Connections, API, and About are
trimmed without losing meaning.
* Address review: desktop update note, server platform detection, zh-CN keys
The About tab no longer shows terminal install commands in the desktop
app, where the bundled backend updates through the built-in updater;
it shows a short note and the docs links instead.
fetchDeviceType now sends the auth token to /api/health, which only
reports the server platform to authed callers, and caches only a
server-reported value. Copied install commands then match the host
platform rather than the browser when they differ (WSL, SSH).
zh-CN gains translations for the new notification and license keys,
the renamed About tab title, and the desktop update note.
* Real download progress for llama.cpp updates, prompt and sidebar polish
The update worker now streams the installer output and parses its
download percent lines into job progress, exposed via the update-status
API. The installer emits finer non-tty milestones when
UNSLOTH_PROGRESS_PERCENT_STEP is set; the worker requests 5 percent
steps. The banner renders a determinate bar from the reported fraction
and falls back to the sweep until the first percent arrives.
Also removes the focus ring on the inline system prompt box and
slightly shrinks the Projects hover plus icon.
* fix(rocm): stop overwriting ROCR_VISIBLE_DEVICES in apply_gpu_ids
ROCR_VISIBLE_DEVICES uses HSA agent-level indexing, not physical GPU
indices. Setting it to a bare integer breaks multi-GPU ROCm systems
where the parent already set ROCR_VISIBLE_DEVICES=0,1: narrowing to
1 causes torch.cuda.is_available() to return False in the training
worker, producing a misleading 'no HIP accelerator' error even on a
correctly configured ROCm host.
HIP_VISIBLE_DEVICES is sufficient for GPU selection on ROCm.
Leave ROCR_VISIBLE_DEVICES inherited from the parent environment.
* test(rocm): update apply_gpu_ids test to assert ROCR_VISIBLE_DEVICES is not overwritten
• fix: handle empty responses tool output
Normalize empty Responses `function_call_output.output` values before converting them into Chat Completions `role="tool"` messages. Empty strings, whitespace-only strings, and empty arrays now use the existing no-output sentinel, while non-empty text and content arrays are preserved.
Add regression coverage for empty tool outputs, image payloads outside `output`, content-array serialization, validator round trips, and preserving non-empty text.
---------
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
Co-authored-by: Tai An <antai12232931@outlook.com>
Co-authored-by: Datta Nimmaturi <venkatadattasainimmaturi@gmail.com>
When pinning GPUs for the llama-server child, the ROCm path set both
HIP_VISIBLE_DEVICES and ROCR_VISIBLE_DEVICES to the same physical
indices. These masks filter at different layers and stack:
ROCR_VISIBLE_DEVICES reduces the visible set at the HSA/ROCr layer and
re-indexes from 0, then HIP_VISIBLE_DEVICES indexes into that reduced
set. _select_gpus ranks by free VRAM and picks the most-free card, so a
single non-zero pin (e.g. "1") becomes out of range at the HIP layer,
HIP enumerates 0 devices, and the model silently runs on CPU
("ggml_cuda_init: failed to initialize ROCm: no ROCm-capable device is
detected").
Set only HIP_VISIBLE_DEVICES (which narrows correctly on its own) and
clear any inherited ROCR mask so it can't double up.
Verified on a 2x Radeon AI PRO R9700 (gfx1201) host, ROCm 7.1.1: the
same selected=[1] load that fell back to CPU (~7.7 tok/s) now runs on
the GPU (~78 tok/s).
Fixes#6175
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* studio: import MCP servers from a config file
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* import config' on the add-server form
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: defensively handle MCP config imports
* fix: address MCP import review follow-ups
* fix: preserve apostrophes in Windows MCP commands
* fix: preserve apostrophe-wrapped Windows MCP args
* fix: align Windows MCP parsing with list2cmdline
* fix: preserve explicit MCP remote transport intent
* fix: trim MCP remote URLs before transport checks
---------
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: imagineer99 <samleejackson0@gmail.com>
* fix(studio): surface live step with null loss through the SSE progress stream
The metric histories skip non-finite steps, so during a NaN stretch the
SSE live loop and final complete event replayed the last finite
step/loss pair. Follow the live progress step when it is ahead of the
history tail and report its loss honestly (null until recovery).
Completes the NaN honesty fix for the SSE consumer flagged in review.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Apply live-step handling to inactive streams and clear the UI loss on null for PR #6206
Fresh /progress connections after a finished run took the inactive branch
which still replayed the last finite step and loss pair; apply the same
live-step correction there. On the frontend, applyProgress kept the stale
currentLoss when a payload advanced the step with a null loss; clear it so
the display shows -- until the loss recovers. Widen the runtime state type
to number | null, which the view layer already handles.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: report the real llama-server context window and add an opt-in overflow policy for OpenAI-compatible serving
A community report showed OpenCode failing tool calls every few minutes
against Studio's OpenAI-compatible API while the same GGUF was stable on
LM Studio. Root cause: Studio advertises the requested context length, but
llama-server can allocate less (memory-fit step on small GPUs, --parallel
slot split), so clients budget against a window that does not exist. Their
generations truncate mid tool call at the real wall (finish_reason=length
with cut JSON arguments) and eventually the prompt itself exceeds the real
window, returning a 400 that agentic clients treat as non-retryable.
Changes:
- After llama-server health, read default_generation_settings.n_ctx from
/props and adopt it whenever it is below Studio's computed context, with
a warning. The load response, status route, UI value, and the passthrough
max_tokens ceiling all become honest automatically.
- Expose context_length and max_context_length on /v1/models so clients can
budget against the enforced window.
- Accept empty role=tool content (commands with no output are routine in
agentic loops; OpenAI and llama-server both accept it) instead of a 400.
- Add context_overflow=truncate_middle (per request, or server-wide via
UNSLOTH_CONTEXT_OVERFLOW=truncate_middle): on exceed_context_size_error
the passthrough drops whole middle turn-groups (system prompt, first turn,
and recent turns kept; tool calls stay paired with their results), clips
oversized contents middle-out when group-dropping is not enough, clamps
max_tokens to the generation headroom, and retries. Default stays 'error'
with code=context_length_exceeded so clients running their own compaction
keep full control.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: allocate the requested context for real (kv-unified, fit-ctx floor)
Two launch-flag gaps caused the advertised vs allocated divergence at the
source:
- llama-server enables --kv-unified only when the slot count is auto; Studio
always passes --parallel N, which silently splits -c into per-slot windows
of -c/N. Pass --kv-unified when N > 1 so a single request can use the full
advertised window (same total KV memory, shared pool).
- with --fit on the fit step may set ctx as low as 4096; pass
--fit-ctx <requested> for explicit requests so fit offloads or fails into
the existing --fit off retry instead of silently shrinking the window.
Both flags are gated on --help capability probing so older builds keep the
current behavior, where the /props readback remains the backstop. Verified
live: -c 98304 --parallel 4 now serves per-slot n_ctx 98304 (was 24576),
48k-token requests pass through the passthrough, and the readback warning no
longer fires.
* [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>
Studio's frontend exposes a Resume action and submits requests with
resume_from_checkpoint set to a previous run's output_dir. The CUDA
training paths in worker.py read this field from config and pass it to
trainer.train() (see lines 2729-2787 and 3108-3229). The MLX path
_run_mlx_training did neither: it never read config['resume_from_checkpoint']
and called trainer.train() with no args. The MLX trainer also did not
accept the kwarg, so even threading it through would have been a no-op.
With this PR + the unsloth-zoo companion PR adding the trainer-side
support (saves optimizer_state + trainer_state, accepts and applies
resume_from_checkpoint in MLXTrainer.train()), MLX Resume now works
end-to-end. Verified on M2 16GB with Qwen3-0.6B + unsloth/LaTeX_OCR:
loss at every post-resume step matches a fresh run bit for bit
(2.168627977371216 == 2.168627977371216 at step 6, etc).
Two lines: read the field near the other config.get() extractions in
_run_mlx_training, pass it as a kwarg at the trainer.train() call site.
Companion PR: unslothai/unsloth-zoo#751
When training produced a NaN or Inf loss event, the handler filtered the
value to None but never updated progress.loss — clients kept seeing the
last finite value as if everything were fine.
Now: on non-finite loss, clear progress.loss to None and log a one-shot
warning. Training continues (no phase=error, no _should_stop), matching
the expected behavior for a non-fatal numerical event.
Test: tests/test_training_nan_loss_handling.py with 6 cases covering
finite, NaN, +/-Inf, idempotency of the one-shot warning, and recovery
when a finite step follows a non-finite one.
* Studio: auto Cloudflare tunnel for 0.0.0.0 launches
Binding Studio to 0.0.0.0 for remote access often leaves the raw
http://<ip>:<port> URL unreachable (https-vs-http, blocked high ports,
closed cloud security groups). On a wildcard bind, auto-start a free
cloudflared quick tunnel and show its https://*.trycloudflare.com URL in
the startup banner:
Secure link access via Cloudflare: https://<random>.trycloudflare.com
- new studio/backend/cloudflare_tunnel.py: find or download+cache the
cloudflared binary (per-OS/arch GitHub release, safe .tgz extract),
start the tunnel, parse the URL, tear it down. Stdlib only; best-effort
and non-fatal throughout (a missing binary or offline box never blocks
or slows startup).
- run_server starts the tunnel for 0.0.0.0 only (skips loopback, api-only
and Colab), prints the line in the banner, and _graceful_shutdown stops
the child so it never orphans.
- --cloudflare/--no-cloudflare flag (default on) on `unsloth studio` and
`unsloth studio run`, forwarded through the re-exec into run_server.
- tests for the helper, the CLI flag forwarding, and the run.py defaults.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio cloudflare: send a User-Agent on the cloudflared download
GitHub's CDN can 403 the default Python-urllib User-Agent on release asset
downloads. Set an explicit UA and pin it with a test.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio cloudflare: address review (opt-out for subcommands, tunnel teardown)
- reject --no-cloudflare placed before a subcommand (it would not reach the
subcommand), mirroring the --parallel guard
- register the tunnel before waiting for its URL so a shutdown during the wait
stops cloudflared instead of orphaning it
- tear the server + children down if `unsloth studio run` startup aborts
(health timeout, model-load error, Ctrl+C) before the wait loop
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* fix(studio): reuse venv Python in setup instead of re-probing system
* Reuse venv Python for studio setup
Pass the venv interpreter from install.ps1 to studio/setup.ps1 via UNSLOTH_SETUP_PYTHON and prefer it over probing the system. Added Resolve-ReusedSetupPython to accept the handed-off path (or derive the venv python when setup runs standalone), validate it (Python 3.11–3.13 and non-conda), and inject its Scripts dir onto PATH. When a reused interpreter is accepted, py.exe enumeration and further system probing are skipped. install.ps1 also sets the env var before running setup and removes it on cleanup to avoid leaving state behind. This prevents setup from being tripped by unsupported Python 3.14 or Windows Store stubs on PATH.
* Harden setup Python detection for PR #6033: py -All, shared conda check, bare ~ guard
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* center the search dialog and change the wrong borders
* fix the mistake of 1 to l
* Fix/adjust search dialog radius for PR #6184
---------
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
* Stop HF 429 rate limits from sinking the llama.cpp prebuilt path in Studio CI
The Windows Studio API smoke job failed when anonymous huggingface.co
fetches of the tiny GGUF validation model (stories260K.gguf) hit HTTP 429
on the shared runner IP. The installer correctly refused the unvalidated
prebuilt and fell back to a source build, which the prebuilt assert then
flags. Three layers fix this:
1. Installer: auth_headers sends HF_TOKEN (or HUGGING_FACE_HUB_TOKEN) to
huggingface.co hosts, mirroring the existing GH_TOKEN handling for the
GitHub API rate limit. A redirect handler strips Authorization when a
download is redirected off-host (CDN signed URLs reject foreign auth;
urllib forwards headers on redirect, unlike requests/huggingface_hub).
2. Workflows: the HF_HOME prime steps also prefetch the validation model
so the install's hf_hub_download resolves from the local cache even
when the Hub is rate limiting; cache keys bumped v1 to v2 to repopulate.
This also covers fork PRs, which cannot see secrets.
3. Workflows: every Install Studio / update step that already passes
GH_TOKEN now also passes HF_TOKEN, so both the huggingface_hub path and
the direct URL fallback are authenticated.
Tests: tests/studio/install/test_hf_auth.py covers token-to-host routing,
the cross-host redirect strip, and the download_bytes wiring (offline).
Verified live: authenticated download of the validation model through the
new opener (CDN redirect exercised, pinned sha matches) and an offline
hf_hub_download cache hit against an HF_HOME primed by the new step.
* [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>
* Require a found ROCm DLL before forcing BNB_ROCM_VERSION in Studio paths
main.py previously set BNB_ROCM_VERSION=72 whenever HIP_PATH or ROCM_PATH
was set, and the training worker fell back to a blind 72 when DLL
detection found nothing. On a Windows machine with the AMD HIP SDK
installed but CUDA or CPU torch, that forces a ROCm backend onto a
non-ROCm bitsandbytes wheel, which raises at import. Both paths now only
write the override when a libbitsandbytes_rocm DLL actually exists (or a
seeded value is already present), matching the strict gates in
unsloth/import_fixes.py.
Also removes four redundant local import shutil statements in
unsloth/save.py that shadow the module-level import, the same pattern
that caused the UnboundLocalError fixed in #6149.
* Worker: gate the BNB override on a found ROCm DLL, preserving seeded marker
Review follow-ups: track _found_rocm_bnb in the worker like main.py so a
ROCm DLL with an unparsable name still gets the seeded or 72 fallback,
and skip the env write entirely when no DLL exists so a seeded value
keeps its sitecustomize marker and stays redetectable by later import
fixes.
* Studio: surface the llama.cpp update affordance when MTP is disabled
When a model asks for MTP (auto on an MTP model, or forced mtp / mtp+ngram)
but it gets disabled, the load already degrades gracefully and serves without
speculative decoding. Until now the UI gave no hint why, or that an update
would fix it.
Record why MTP was dropped on the backend (spec_fallback_reason): the probe
found no mtp token (binary_no_mtp), the spawn aborted with an outdated-arch /
context-build error such as a prebuilt that predates the Gemma drafter
(binary_outdated), or the current build could not run it, e.g. a CUDA kernel
limit (runtime_error). Expose it in the inference status. In the chat
Speculative Decoding section, show a short note and, for the two update-fixable
reasons, an inline Update llama.cpp button that reuses the existing update flow.
A runtime_error gets the note without an update push, since a newer build may
not fix it.
Backend tests cover the reason being set / cleared. Frontend typechecks.
* Address review: tighten the update hint to genuinely outdated binaries
Reserve binary_outdated (which surfaces the Update llama.cpp affordance) for an
unknown-architecture abort, which proves the prebuilt predates the model;
classify the generic memory/context build failures as runtime_error, where an
update may not help. Frontend: only append the "Update llama.cpp to enable it"
sentence when an update is actually available, so the text never points at an
action the UI is not offering.
* fix(studio): prevent UI freeze when switching tabs from heavy pages
Change AnimatePresence mode from "wait" to "popLayout" to fix issue
where switching tabs from Export (or other heavy pages) would cause
the URL to update but the UI to freeze.
With mode="wait", the exit animation must complete before the new
component mounts. If the exiting page has expensive computations,
this blocks the UI. mode="popLayout" allows the new route to mount
immediately while the old one animates out.
Fixes#5850
* fix: add relative positioning for popLayout mode
AnimatePresence mode='popLayout' applies position: absolute to the
exiting element, so the parent container needs position: relative
to prevent layout jumps during transitions.
---------
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
The export route's load_checkpoint waits for the training subprocess to
exit by calling time.sleep(0.5) in a loop (up to 30s) inside an async
function. time.sleep blocks the whole event loop, so every other request
to the server stalls for that duration. Use await asyncio.sleep(0.5),
matching the async pattern already used elsewhere in this file
(asyncio.to_thread, await asyncio.sleep).
Co-authored-by: Wasim Yousef Said <wasimysdev@gmail.com>
* fix(studio): fall back to copy when os.replace is blocked during install activation
On Windows ARM64 the antivirus scanner can transiently hold a freshly
extracted DLL open while MoveFileEx runs, so activating the staged
llama.cpp prebuilt fails with [WinError 5] Access is denied. Attempt
os.replace first, then fall back to a file-by-file copytree which
bypasses the rename.
* address review: keep os.replace for rollback, scope copy-fallback to staging
The copy + rmtree fallback could silently corrupt a live install if the
existing directory is busy. Restrict it to freshly extracted staging
trees (renamed activate_staged_dir) and keep strict os.replace for the
rollback move so a busy active install raises immediately.
* fix(studio): scope copy-fallback to busy-lock errors, log it, and add tests
---------
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: Etherll <61019402+Etherll@users.noreply.github.com>
* Studio: enable MTP for sub-3B Gemma separate-drafter GGUFs
The sub-3B auto-drop to ngram-mod was tuned for an embedded draft head
(Qwen), whose per-token cost regresses below 3B. Gemma ships the head as a
separate root mtp-*.gguf drafter, a tiny standalone model that is cheap
enough to win below 3B: B200 Q4_K_XL bench, draft-mtp n=2 vs spec-off,
gemma-4-E2B (2B) = 1.21x (accept ~0.65) while ngram-mod is 1.00x.
Exempt a separate drafter from the sub-3B gate everywhere the threshold is
applied: the resolver (_mtp_too_small), the auto-fit VRAM reserve, the
drafter auto-download decision, and the reload-skip mirror via a
has_separate_drafter flag on _auto_mode_drops_mtp. Embedded sub-3B heads
(Qwen) still drop to ngram-mod. A drafter the binary cannot build (older
prebuilt, or a CUDA kernel limit) still aborts the spawn and the load
retries once without speculative decoding.
Adds the full Qwen3.5 + Gemma-4 (regular and QAT) auto/off/forced resolver
matrix, plus explicit sub-3B exemption tests.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Always compare the separate drafter in the reload-skip mirror
The sub-3B wrapper around the drafter compare could skip it when the drafter
was deleted out from under a running sub-3B server (detected None, stored set),
leaving a stale launch. The resolved-path compare is cheap and already handles
every case, so drop the _auto_mode_drops_mtp guard (and its now-unused imports)
and always compare when the mode can use a drafter and the user does not own
--spec-type. Addresses review feedback on #6191.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: fetch the release source asset for exact (mix) source builds
The source-build fallback rebuilt the codeload/archive URL from the
source repo and commit. A mix build's merged tree is never pushed to any
repo (it ships only as the release's llama.cpp-source-commit-<sha>.tar.gz
asset), so codeload 404s on the merge commit and an uncovered host could
not build from source. When an exact-source asset exists, fetch it
directly from the release and keep codeload as the fallback for vanilla
builds whose commit is real.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* fix: ignore unsupported env proxy during Studio startup
* fix: handle missing socksio env proxy at startup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Match printf logging style and inline the proxy predicate for PR #6102
* [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>
* Installer: harden GPU detection follow-ups after #6174
Ports the NVIDIA-priority and /proc/driver/nvidia/gpus hardening from #6174
to the remaining pathways and adds recovery for already-poisoned venvs:
- install_python_stack.py: add _ensure_cuda_torch so 'unsloth studio update'
force-reinstalls CUDA torch when the venv carries a ROCm build on an NVIDIA
Linux host (the pre-#6174 poisoning signature). Honors UNSLOTH_TORCH_BACKEND,
UNSLOTH_ROCM_TORCH_INSTALLED, and CUDA_VISIBLE_DEVICES=-1/'' opt-outs; never
touches healthy CUDA, deliberate CPU wheels, macOS, or Windows.
- install_llama_prebuilt.py: detect_host gains the /proc NVIDIA fallback and
skips ROCm probes when NVIDIA is usable; forwarded --rocm-gfx/--has-rocm
overrides still win.
- setup.sh: GPU summary classifies NVIDIA first through a timeout-bounded
probe with the /proc fallback; AMD probes are bounded and gain a KFD
vendor_id 4098 fallback; the llama.cpp source build only selects
GGML_CUDA/GGML_HIP when the matching GPU is actually detected.
- install.sh: bound both nvidia-smi calls with a 10s timeout (no behavior
change when healthy or when the timeout binary is absent); classify the
exported UNSLOTH_TORCH_BACKEND on the final index path segment so custom
mirrors containing 'rocm'/'gfx' in their base path are not mislabeled.
- install.ps1 + setup.ps1: NVIDIA probes now require a real 'GPU N:' row from
nvidia-smi -L under a 10s bound instead of bare exit code 0; later CUDA
version and compute_cap queries are bounded too.
Tests: 3 new test files (50+ tests), suite at 788 passed.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix Resolve-CudaToolkit driver probe for extracted-function unit test
tests/studio/test_resolve_cuda_toolkit.ps1 extracts Resolve-CudaToolkit alone
into a child pwsh and stubs nvidia-smi with a .ps1 script. The bounded runner
is not in scope there (and ProcessStartInfo cannot dispatch .ps1 stubs), so
the DriverMaxCuda parse silently returned nothing and the major-mismatch
scenarios failed. Fall back to direct invocation when Invoke-NvidiaSmiBounded
is unavailable; production setup.ps1 always has it defined and keeps the
10s bound.
* Treat CUDA_VISIBLE_DEVICES empty or -1 as hidden in NVIDIA-first guards
The NVIDIA-first guards added in this branch only special-cased
CUDA_VISIBLE_DEVICES=-1 at two setup.sh gates and ignored the empty-string
form entirely, while the Python detector (install_llama_prebuilt.py)
already treats both as hidden. On a mixed AMD+NVIDIA host steered to the
AMD card via CUDA_VISIBLE_DEVICES, the guards suppressed the AMD probes,
so setup.sh fell to a CPU llama.cpp build and install.sh picked CUDA
wheels instead of ROCm.
Move the policy into the helpers so every consumer agrees:
- install.sh: new _cvd_hides_nvidia checked first in _has_usable_nvidia_gpu
- studio/setup.sh: same via _setup_cvd_hides_nvidia; the two ad-hoc
CUDA_VISIBLE_DEVICES=-1 gate conditions are now redundant and removed
- studio/install_python_stack.py: _has_usable_nvidia_gpu returns False
when CUDA_VISIBLE_DEVICES is set to or -1 (whitespace tolerated)
Tests: 5 new sh scenarios (hidden via , -1, padded -1, visible device,
and mixed host with hidden NVIDIA restoring the ROCm route) plus a pytest
class covering all three implementations behaviourally.
Addresses the review comment on the NVIDIA-first setup.sh block.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Retrigger CI after PyPI 503 outage during the previous run
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: offer the in-app llama.cpp update for source-build (markerless) installs
Source-build installs have no UNSLOTH_PREBUILT_INFO.json marker, so freshness
reported supported=False and the Update button never showed (notably on macOS,
where the fork shipped no prebuilt before b9585 and setup fell back to a source
build). When an install has no marker but an official prebuilt now exists for
the host, surface the update and let one click swap it in place.
- install_llama_prebuilt.py: published_repo_for_host() (the setup.sh host->repo
rule in Python) and a --resolve-prebuilt mode that reports whether a prebuilt
exists for this host without downloading.
- llama_cpp_update.py: markerless branch in get_update_status/start_update,
version-suppressed so source builds already newer than latest are not nagged;
fail-open throughout.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: run llama update detection off the event loop, expose source_build
The markerless source-build check probes the host and reads GitHub, so run
get_update_status and start_update in a worker thread to keep the API
responsive. Expose source_build in the status response so the banner can label
the source-build switch.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Keep the llama-route auth stub out of sys.modules for the rest of the suite
test_llama_route.py replaced sys.modules['auth.authentication'] with a
bare stub at collection time and never restored it, so every later test
importing create_access_token got the stub: 17 failures across
test_desktop_auth, test_middleware, test_openai_tool_passthrough and
test_rag_preview on all four Backend CI Python versions. Import the
real module when its deps are available and only stub in minimal envs,
popping the stubs after the standalone route load either way.
* Studio: address review on the source-build update path
- published_repo_for_host: route CPU-only Windows to ggml-org too (mirrors
setup.ps1; the fork ships no win-cpu bundle), macOS always the fork.
- markerless detection compares/display the upstream llama_tag, not a possible
fork wrapper release_tag, so a source build is not wrongly judged newer.
- do not offer when there is no resolvable install root (a pinned
LLAMA_SERVER_PATH outside a managed dir): an apply would not take effect.
* Ignore version probes in the update tests' subprocess capture
The status polls in these tests trigger the new source-build detection,
which shells out to llama-server --version through the same patched
subprocess.run. On slow runners that probe lands after the installer
call and clobbers the single captured argv, failing the flag
assertions (seen on the 3.10/3.11 Backend CI jobs). Skip probe calls
in all three fakes so only the installer invocation is captured.
* Skip markerless re-detection while the update job is swapping the tree
On a source-build install the frontend polls update-status every 3s
during an apply, and each poll ran _source_build_status, which execs
the very llama-server binary the job is concurrently replacing. On
Windows that exec can hold the exe long enough to fail the installer's
os.replace; everywhere it is a per-poll subprocess spawn for a status
the poller does not read (it only consumes job progress). Gate the
markerless branch on the job not running; the marked path is probe-free
and still returns the live job state.
* Studio: tighten source-build update root, repo routing, and downgrade guard
Only manage a markerless install when the active binary lives under a
resolvable llama.cpp root (marker dir, UNSLOTH_LLAMA_CPP_PATH it sits in,
or a llama.cpp ancestor); a pinned LLAMA_SERVER_PATH or a PATH/system
binary is left alone so an apply cannot install where it would not take
effect. Gate start_update on the same suppression as detection so a
direct POST cannot downgrade a source build newer than the latest
prebuilt. Route Linux hosts with AMD tooling (rocminfo/amd-smi/hipconfig/
hipinfo) to the fork in --resolve-prebuilt, matching setup.sh, so a HIP
source build is not offered an upstream CPU prebuilt.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: cover inactive env root and pinned llama.cpp checkout in update root tests
---------
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: forward preserve_thinking + reasoning_effort on the OpenAI passthrough
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Provide _request_reasoning_kwargs on the responses passthrough test backend mock
The OpenAI passthrough body builder now asks the active backend for
capability-gated reasoning kwargs. The responses stream adapter test fakes
the backend with a bare SimpleNamespace, so give it the same method a
non-reasoning template would expose (returns None, keeping
chat_template_kwargs out of the captured body).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Shorten the backend mock comment
---------
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: prevent ROCm torch from installing on NVIDIA Linux hosts
NVIDIA's open kernel module (driver 560+) registers GPU topology nodes in
the KFD sysfs hierarchy with non-zero gpu_id values. The _has_amd_rocm_gpu
(install.sh) and _has_rocm_gpu (install_python_stack.py) sysfs fallbacks
previously treated any non-zero gpu_id as proof of an AMD GPU, so an
NVIDIA-only host with the open kernel driver was misrouted to the ROCm
install path, replacing the correctly-installed CUDA torch with ROCm wheels.
Fixes:
1. install.sh _has_amd_rocm_gpu sysfs fallback: require vendor_id 4098
(AMD 0x1002) in the KFD node properties file before declaring an AMD
GPU present. NVIDIA KFD nodes carry vendor_id 4318 (0x10DE) and are
now skipped.
2. install_python_stack.py _has_rocm_gpu sysfs fallback: same vendor_id
guard. Also preserves the existing fallback for older kernels that
don't ship a properties file (trusts gpu_id alone there).
3. install.sh now exports UNSLOTH_TORCH_BACKEND ("cuda"/"rocm"/"cpu")
immediately after get_torch_index_url() resolves the wheel family.
install_python_stack.py reads this as _TORCH_BACKEND and short-circuits
_ensure_rocm_torch() entirely on cuda/cpu hosts, providing a second
layer of defense that is independent of subprocess GPU detection.
Tests: 9 new cases in TestHasRocmGpuKfdVendorGuard,
TestEnsureRocmTorch, and TestInstallShStructure cover all three changes.
Full test_rocm_support.py suite: 289 passed, 2 skipped, 0 failed.
Closes#6172
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: show actual torch backend in progress step labels
The 'ROCm torch check' and 'ROCm torch (final)' step labels were
hardcoded regardless of whether the installer was targeting CUDA, ROCm,
or CPU. On NVIDIA hosts they showed 'ROCm' even though no ROCm wheels
were being installed, which was misleading.
Add _torch_step_label(suffix) which reads UNSLOTH_TORCH_BACKEND (set by
install.sh) and formats the label as e.g. 'torch check (cuda)' or
'torch final (rocm)'. Falls back to live GPU detection for standalone
studio update runs that bypass install.sh.
* fix: make KFD sysfs vendor check conservative -- skip if no properties file
The previous implementation fell through to `return True` when the KFD
node's properties file was missing (OSError), intending to support older
kernels. But NVIDIA open driver KFD nodes can also lack a properties file
on some kernel versions, so the fallback still produced a false positive.
Change the `except OSError: pass` to `continue` so any node without a
readable properties file is skipped rather than trusted. KFD properties
files exist on every kernel version that actually exposes /sys/class/kfd,
so this does not regress real AMD GPU detection -- if the directory exists
at all, properties files will be present for genuine GPU nodes.
* fix: bulletproof NVIDIA vs AMD GPU detection
Four changes that together ensure ROCm torch can never be installed on an
NVIDIA host regardless of which detection path fires:
1. _has_rocm_gpu() (Python): NVIDIA guard at the top -- returns False
immediately when _has_usable_nvidia_gpu() is True, blocking rocminfo,
amd-smi, and KFD sysfs from producing a false positive even when ROCm
tools are co-installed alongside the NVIDIA driver.
2. _has_amd_rocm_gpu() (install.sh): same NVIDIA guard -- calls
_has_usable_nvidia_gpu first and returns 1 if it succeeds.
3. _has_usable_nvidia_gpu() (Python): adds /proc/driver/nvidia/gpus/
sysfs fallback. The NVIDIA driver populates this directory on Linux
regardless of nvidia-smi state, so a subprocess PATH gap, timeout, or
driver initialisation race can no longer silence NVIDIA detection.
4. _has_usable_nvidia_gpu() (install.sh): same /proc/driver/nvidia/gpus
fallback, tried after nvidia-smi -L rather than instead of it.
Together: NVIDIA wins at every decision point. If nvidia-smi works, it
confirms NVIDIA. If it fails, /proc/driver/nvidia confirms NVIDIA. If
somehow both fail, _has_rocm_gpu still checks NVIDIA first before any AMD
path runs.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: two KFD/proc-only corner cases from Codex review
1. KFD awk state not reset per node file (Ryzen+NVIDIA false positive):
The awk glob processes all topology node properties files in one pass.
Without FNR==1 reset, a Ryzen+NVIDIA host where an AMD CPU-agent node
sets amd=1 (vendor_id 4098, gpu_id 0) can combine with a later NVIDIA
node setting gpu=1 (gpu_id > 0), triggering found=1 before vendor_id
4318 is seen. Added FNR==1{ gpu=0; amd=0 } to reset per file.
2. proc-only NVIDIA not reaching CUDA wheel selection:
_has_usable_nvidia_gpu returning true via /proc/driver/nvidia fallback
left _smi empty, so get_torch_index_url entered the AMD/CPU branch and
selected CPU wheels despite NVIDIA being confirmed. Introduced
_nvidia_detected flag (separate from _smi) so the AMD branch is skipped
whenever NVIDIA is confirmed by any path, while _cuda_ver reads from
_smi when available (with the existing cu126 fallback when _smi is absent).
* [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>
Follow-up to #6097. The update banner appeared 8s after load and auto-hid after
about 10s. Show it about 1s after a newer prebuilt is detected and keep it up
until the user dismisses it (click outside or the X) or runs the update; it
stays during an in-progress update so the progress is visible.
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Studio: gracefully disable MTP when the model has no head or drafter
Selecting MTP or MTP+Ngram in Speculative Decoding on a GGUF with no nextn
head and no separate drafter aborted the whole load. llama-server does not
no-op an empty draft-mtp request: it exits with 'failed to measure MTP
context memory: failed to create llama_context', surfaced to the user as a
generic 'llama-server failed to start. Check that the GGUF file is valid
and you have enough memory.'
Build-time fix in _build_speculative_flags: when a forced mtp / mtp+ngram
mode targets a model with no MTP head and no drafter (is_mtp_model is
False), default back instead of emitting draft-mtp. mtp falls back to
--spec-default; mtp+ngram keeps the ngram-mod half, which needs no head.
Real MTP models (embedded head or separate drafter), sub-3B MTP overrides,
and the auto path are unchanged.
Runtime hardening: the existing post-launch MTP retry only fired for
separate-file drafters (--model-draft in spec_flags), so an embedded-head
model that the binary cannot build still hard-failed. Gate the retry on the
spec block requesting MTP, recognise the embedded-head abort strings
('failed to measure MTP context memory', 'failed to create llama_context'),
and make the drafter name None-safe in the warning.
Tests: extend the resolver matrix (forced mtp / mtp+ngram on a non-MTP
model) and add two cases asserting the default-back emission.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Adds an in-app "Update llama.cpp" banner and button to Unsloth Studio. When the installed prebuilt is behind the latest published release, a non-invasive banner appears; clicking Update downloads the latest prebuilt for this host and swaps it in place in the background, with no restart.
Detection reuses the freshness check from #5529. The update re-runs install_llama_prebuilt.py the same way setup.sh and setup.ps1 do after #5963: it forwards the published repo and the AMD gfx target derived from the install marker, and does not pass the removed --simple-policy or the arm64-only --cpu-fallback.
While the installer swaps binaries the backend enters a maintenance state (flag set under the serial load lock, active server unloaded) so a concurrent load cannot start a server from a half-swapped binary; the next load uses the new build. The banner also handles refused responses and jobs started in another tab so it never sticks on "Updating...".
Verified end to end on an NVIDIA B200: installed b9493, detected the update, applied it, and confirmed the binary at the same path advanced to b9585 in the same process. Hermetic backend tests and the frontend type-check pass.
* feat(hub): enable Run/New Chat for downloaded GGUF models, fix README bottom spacing
- enable the Run / New Chat action for GGUF models that are already downloaded, across the download card, on-device card, and hub page
- remove the extra bottom spacing under the model inspector README
* fix(hub): sync active GGUF variant on mount
* feat(hub): open a new chat immediately when Run is clicked
---------
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
