* feat(studio): add S3 dataset configuration foundation (#4539)
Add foundational types and configuration for S3 bucket dataset loading:
- Add S3Config type to frontend training types
- Add S3Config Pydantic model to backend training models
- Add "s3" as a DatasetSource option
- Add s3Config state and setS3Config action to training config store
- Add i18n translations for S3 configuration (English and Chinese)
This provides the type definitions and UI text for S3 integration.
Full implementation requires boto3 dependency and data loading logic.
Refs: #4539
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* Wire S3 config into training pipeline and prevent secrets persistence
- Pass s3_config from request into training_kwargs so it flows to training subprocess
- Add s3Config to NON_PERSISTED_STATE_KEYS to prevent AWS secrets from being
saved to localStorage
Addresses code review feedback on PR #5951.
* Exclude S3 config from database persistence to protect secrets
Filter out s3_config (which contains secret_access_key) from the
config_json stored in training_runs table, preventing AWS credentials
from being persisted to disk.
Addresses P1 security feedback on PR #5951.
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* Re-raise HTTPException in start_training and defer s3 DatasetSource widening for PR #5951
* Redact s3_config from W&B run config and accept camelCase S3 credential aliases for PR #5951
* feat(studio): implement S3 dataset loading end-to-end
Builds the actual S3 loader on top of the hardened #5951 foundation,
turning the 501-gated scaffold into a working dataset source.
Backend:
- Add core/training/s3_dataset.py: lists and downloads supported dataset
files (parquet/json/jsonl/csv) from an S3 bucket to a temp dir, using
IAM-role or access-key credentials. boto3 is imported lazily (optional dep).
- Wire s3_config into UnslothTrainer.load_and_format_dataset (downloads then
reuses the existing local-file path) and thread it through worker.py.
- Replace the 501 "not implemented" gate with a boto3-availability guard so
S3 works when boto3 is present and fails clearly when it is not.
- Add boto3 to studio.txt requirements.
- Add tests/test_s3_dataset.py (8 tests) covering download/filtering,
collisions, missing-boto3, and S3Config camelCase/IAM validation.
Frontend:
- Widen DatasetSource to include "s3"; add s3_config to the training payload
type and mapper; add an S3 validation branch and selectS3Source store action.
- Add s3-config-form.tsx (bucket/region/prefix/keys/IAM toggle) reusing the
existing studio.dataset.s3.* i18n strings.
- Add a Hugging Face / Local / Amazon S3 source toggle in dataset-section;
the S3 config card replaces the dataset combobox when S3 is selected.
- Fix DatasetPreviewDialog to accept the widened DatasetSource type.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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* Fix S3 dataset loader for PR #6222
* Fix S3 dataset edge cases for PR #6222
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* Fix S3 IAM payload handling for PR #6222
* Block multimodal S3 datasets for PR #6222
---------
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* Studio: override chat template for unsloth/gemma-4-*-GGUF with bundled gemma-4.jinja
The chat templates baked into the shipped unsloth/gemma-4-*-GGUF quants predate
Google's gemma-4 chat-template PR #118 and lack the preserve_thinking flag, so
Studio cannot surface the "Preserve thinking" toggle for Gemma 4. Bundle the updated
template and override the embedded one at llama-server launch via --chat-template-file,
scoped to the gemma-4 GGUF family, so users do not need to re-download any quant.
- Add studio/backend/assets/chat_templates/gemma-4.jinja (PR #118 based;
preserve_thinking defaults false, the one deliberate divergence from upstream).
- Add core/inference/chat_templates.py: gemma-4 GGUF matcher plus an
effective-override resolver (explicit user template still wins).
- Wire the resolver into routes/inference.py ahead of the reload-dedup check and
both load_model calls so the live backend and the incoming request compare against
the same template text (no spurious reloads).
- Default preserve_thinking off in the launch-time chat_template_kwargs so direct
API callers match the UI default.
- Ship the asset via package-data and add unit tests.
* Studio: ship E2B/E4B edge variant of the bundled Gemma 4 template
Google ships two distinct gemma-4 chat templates: E2B and E4B omit the empty
"<|channel>thought<channel|>" block on enable_thinking=false, while the
12b/26B-A4B/31B family emits it (confirmed against google/gemma-4-E2B-it,
-E4B-it, -12b-it, -26B-A4B-it, -31B-it; the two families differ only in that
one block). The single PR #118 based template followed the larger-model
behavior, which is wrong for the E2B/E4B GGUFs this feature most targets.
- Add studio/backend/assets/chat_templates/gemma-4-edge.jinja: identical to
gemma-4.jinja minus the empty-thought-block, matching E2B/E4B behavior.
- Route unsloth/gemma-4-E2B-it-GGUF and -E4B-it-GGUF to the edge template;
12b/26B-A4B/31B keep gemma-4.jinja.
- Extend tests for the edge matcher, per-family routing, and the empty-thought
block difference (off for edge, on for standard).
* Studio: address review feedback on the gemma-4 template override
- Normalize owner-less shorthand model ids in the template matcher: a bare
"gemma-4-E2B-it-GGUF" is canonicalized to "unsloth/" the same way
ModelConfig.from_identifier does, so shorthand loads still get the override
(and the preserve_thinking capability) instead of falling back to the
embedded template.
- Scope the test's module stubs with unittest.mock.patch.dict instead of
sys.modules.setdefault, and only stub deps that are missing, so the global
module registry is not polluted for tests that run afterwards.
- Guard the Jinja render tests with pytest.importorskip("jinja2") so the suite
stays runnable in minimal Studio environments where jinja2 is not present.
- Add tests for shorthand resolution.
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* Studio: address 10-reviewer P1 findings on the gemma-4 template override
- /status no longer surfaces Studio's auto-applied bundled template as a
user-authored chat_template_override. The frontend adopts that field as
editable state and would otherwise re-send the gemma-4 template as an explicit
override for a later, unrelated model. /status now reports None when the live
override equals the model's auto-resolved bundled template.
- When a bundled family template is in effect, strip an inherited
--chat-template-file from llama_extra_args too (not only when the raw request
set chat_template_override). Otherwise a stale inherited template, appended
last, shadows the bundled one while Studio reports the bundled template's
capabilities.
- Write the temp chat-template file as UTF-8 explicitly, and keep the bundled
templates ASCII (replaced em dashes), so non-UTF-8 Windows locales cannot raise
UnicodeEncodeError or emit a mis-encoded template. Added an ASCII guard test.
---------
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* 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.
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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.
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* Studio: apply cache-scan guards to sibling endpoints found in review
Extend the inaccessible-cache guard and mmproj/stat hardening to the
parallel HF cache code paths flagged in review:
- list_local_models and the Hub inventory scan now skip an unreadable
auxiliary cache instead of returning 500.
- The GGUF download-progress endpoint excludes mmproj adapters and
guards f.stat() so one bad file does not zero a repo's progress.
- The offline snapshot scanner guards its is_dir() probes.
- The chat-only picker no longer renders a blank list when a search
matches only cached non-GGUF models.
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* fix(studio/responses): forward chat_template_kwargs enable_thinking to chat request
The /v1/responses translation in _build_chat_request dropped
chat_template_kwargs (e.g. {"enable_thinking": true}) sent via the
Responses extra-body, so reasoning control was silently ignored.
Lift enable_thinking onto the typed ChatCompletionRequest field,
mirroring openai_chat_completions, so both the non-streaming and
streaming Responses pass-through paths honor it.
Fixes#6198
Signed-off-by: Tai An <antai12232931@outlook.com>
* Fix/adjust Responses reasoning for PR #6202
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* Fix/adjust reasoning none for PR #6202
* Fix/adjust structured reasoning for PR #6202
* Fix/adjust responses reasoning review findings for PR #6202
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* Fix/adjust responses reasoning follow-ups for PR #6202
* Fix/adjust think parsing gate for PR #6202
---------
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Co-authored-by: Wasim Yousef Said <wasimysdev@gmail.com>
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* Studio: Add Tensor-Parallel llama.cpp support
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* Studio: harden Tensor-Parallel fallback and GPU selection
* Studio: reconcile split-mode extras and harden tensor-split planning
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* Studio: reconcile split-mode extras in backend duplicate-load guard
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* Studio: preserve inherited non-tensor split modes on reload
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* Studio: honor cancellation in tensor fallback, preserve tensor mode on rollback, and don't raise an explicit small context
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* Studio: reconcile split-mode in reload check and strip it on tensor downgrade
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* Strip --tensor-split alongside --split-mode so inherited ratios don't override the tensor planner
An inherited or stale --tensor-split in llama_extra_args was appended after
Studio's computed --tensor-split and won last in llama.cpp, re-introducing the
asymmetric-GPU OOM tensor mode is meant to prevent. Group -ts/--tensor-split
into the split-mode shadow set so it is stripped on inherit and on the layer
fallback; parse_split_mode_override still keys on the mode value only.
* Drop quantized KV for the tensor attempt and report native max context
Tensor mode aborts on a quantized KV cache, so a user with q8_0/q4_1 etc. who
enabled Tensor Parallelism silently fell back to layer split. Clear the cache
type (and strip inherited/explicit --cache-type) for the tensor attempt only;
the layer fallback re-runs with tensor off and keeps the user's choice.
Also report max_available_ctx from the native context, not an explicit small
-c, so the context slider no longer warns too early in tensor mode.
* Reconcile inherited split-mode extras in the already-loaded check
When a same-model load omitted llama_extra_args, the tensor comparison resolved
the raw (None) request and treated an inherited --split-mode tensor server as a
mismatch, forcing a needless reload. Compare using the stored extras stripped
the same way the reload strips them.
* Pass tensor_parallel through compare-mode loads
The generalized compare path loaded each GGUF without tensor_parallel, so
compare ran layer split even with the toggle on and left the settings sheet
stale. Send the toggle and hydrate the loaded state from the response, matching
the main chat and recipe load paths.
* Add --tensor-parallel flag to unsloth studio run
The headless one-liner could only reach tensor mode by passing --split-mode
tensor as a raw llama.cpp extra. Add a first-class --tensor-parallel/
--no-tensor-parallel option that sets the tensor_parallel field on the
/api/inference/load payload, forwarded through the studio-venv re-exec like the
other polarity flags. Matches the web UI toggle and the API field.
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* 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.
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* Fix GGUF local export paths for PR #6088
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* Address GGUF export follow-ups for PR #6088
* Clean GGUF temp dirs on export failure for PR #6088
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* Fix/adjust export path tests for PR #6088
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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.
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* 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).
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* 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).
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* Studio: Add inline confirmation (Allow/Always allow/Deny) for tool calls
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* 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).
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* Move "Confirm tool calls" to the Tools section
* Studio: Keep tool group open while a tool call awaits confirmation
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* Fix tool confirmation session scope for PR #5869
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* Fix confirmation follow-ups for PR #5869
* Apply pre-commit formatting for PR #5869
* Fix confirmation cleanup for PR #5869
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* 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
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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>
* 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: 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>
* 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>
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>
* 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.
* 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>
* 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>
* 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
---------
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* 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.
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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.
* Studio: fall back to text-only when llama.cpp is too old for a model's vision projector
Loading a GGUF vision model starts llama-server with --mmproj <projector>. When the installed llama.cpp prebuilt predates the model's projector format, llama-server aborts at startup with 'clip.cpp: Unknown projector type' (exit -6), and the whole load failed even though the base GGUF is a fine text/tools chat model. Seen with gemma-4 on a 3-day-old prebuilt (build b9496).
load_model now retries the launch once without --mmproj when the captured startup output indicates a projector-format incompatibility. The retry runs the model text-only, marks the session non-vision (is_vision False, mmproj audio dropped) so the status/capabilities the frontend reads stay consistent, and warns the user to update llama.cpp. Detection is generic, not model-specific, and conservative: OOM, bad GGUF, port-bind, missing-file and other failures keep their existing handling and never retry. If the text-only retry also fails, it errors out with the real reason.
Adds _is_projector_incompatibility and _strip_mmproj_args (unit-tested with the real gemma-4 abort plus negatives) and extracts _start_llama_process so both the initial start and the retry share one spawn path and each logs its argv.
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* Reformat mmproj fallback files to match main (ruff line-length 100 + kwarg spacing)
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* Studio: route arm64 Linux CUDA hosts to linux-arm64-cuda prebuilts
* Studio: SM-aware selection for windows-cuda app bundles
* Studio: select published ROCm bundles by gfx target (linux + windows)
* Studio: route macOS installs to the fork's prebuilt bundles
* Studio: fix windows cuda13 driver-13.0 gate and ROCm gfx prefix overreach
* Fix Blackwell Windows pin shadowing native app-bundle (b9360 over b9457)
* Match Windows cuda12 driver floor to Linux (12.x minor-version compat)
* Fix Windows app-bundle dropped when runtime DLLs come from torch/lib
* Fold the manifest resolver into the simple-path resolver (one entry, no dormant full path)
* Remove unused UNSLOTH_LLAMA_PUBLISHED_REPO override
* Route Windows GPU hosts to the fork prebuilts in setup.ps1
* Document sm_103 path divergence and mark --simple-policy as a no-op
* Note sm_103 coverage now comes from the producer manifest
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Remove the now-vestigial --simple-policy flag (one resolver handles all hosts)
* Unify the fork onto the manifest path; drop the linux-x64 filename path and hardcoded coverage tables
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Strip whitespace from manifest gfx_target/mapped_targets when parsing
* Windows CUDA: sort coverage-unknown bundles last so they can't outrank targeted ones
* Share the SM-coverage sort key between the linux and windows selectors via _sm_range
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: reject approved releases with an exact source archive but no source repo to clone from
* Studio: accept the fork's windows-rocm kind in the Windows reinstall check
* Studio: accept a manifest-bundle source repo in the exact-source release check
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: route Linux hosts to the fork only when a usable GPU is present
* Fix Windows AMD lemonade tag resolution for PR #5963
The fork release scan passes each scanned release's upstream tag
(b9518, ...) to the lemonade lookup, but lemonade publishes its own tag
series (b1292, ...) that never contains upstream tag numbers. On a
Windows AMD host every scanned release therefore 404s the lemonade
fetch twice, the upstream HIP zip is dropped by the approved-hash gate,
and the scan walks the whole release history until it dies on the
unauthenticated GitHub rate limit or falls to a HIP source build. The
Linux path already passes the requested tag ("latest") and works.
Thread the requested tag through resolve_release_asset_choice ->
resolve_asset_choice -> resolve_upstream_asset_choice as lemonade_tag,
used only by the lemonade lookups. Upstream asset names keep the
concrete per-release tag and all new parameters default to the old
behavior.
Verified on a gfx1151 box: before, the native Windows install scanned
b9518..b8811 and aborted on rate limit; after, it selects
llama-b1292-windows-rocm-gfx1151-x64.zip (lemonade) from fork release
b9518, passes staged validation, and the installed llama-server
enumerates ROCm0. WSL keeps selecting the matching ubuntu bundle.
Adds a regression test pinning that the Windows fork path resolves
lemonade via /releases/latest, never /releases/tags/<fork-tag>.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Plan lemonade for Linux ROCm hosts on the ggml-org direct path for PR #5963
Audit follow-up to 72f32364 across the other selection pathways. The
ggml-org direct planner kept its lemonade attempt for Windows ROCm
hosts but planned only the CPU tarball for Linux ROCm hosts, so an AMD
Linux box routed to ggml-org (for example a --published-repo override)
silently installed the CPU build. That lemonade planning used to live
in the --simple-policy dispatcher this PR removed.
Add the lemonade attempt ahead of the CPU tarball in the Linux x86_64
branch, mirroring the Windows branch, with the lookup keyed to the
requested tag. Adds a regression test asserting lemonade is the first
attempt for a Linux ROCm host on the direct path.
Also re-verified the other pathways on a gfx1151 box: the fork-routed
flows pass the requested tag everywhere, repeat runs over an existing
lemonade install correctly skip with "already matches selected release
b9518" on both native Windows and WSL, and macOS, CUDA and CPU
selection are untouched. Suites: 328 passed on Linux, Windows matches
the pre-existing baseline.
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Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Studio: support separate-file MTP GGUF drafters (Gemma 4)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: fix review findings for separate-file MTP drafters
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: pair local MTP drafters by name and include them in reload dedup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: manage --model-draft in extras and reject MTP/ copies as models
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
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* Fix Studio Python, Gemma 4 Unified sidecar, and worker crash messages
* Clean up Gemma 4 sidecar test patch contexts
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Polish inference worker crash message
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Address transformers tier review feedback
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Route Gemma 4 assistant models to transformers 5.10
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* fix(studio): infer mlx vlm resized image layout
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* Fix Windows installer winget msstore certificate failure
`winget install` was invoked without `--source winget`, so winget also
queried the msstore source. When msstore fails certificate pinning
(error 0x8a15005e, "The server certificate did not match any of the
expected values") winget aborts and demands `--source`, so the Python
(and uv) install fails even though the package exists in the winget
source.
- Pass `--source winget` to all winget install calls (Python x2, uv).
Both packages live in the winget source, so this is strictly correct
and skips the failing msstore round-trip entirely.
- Add a python.org fallback (Install-PythonFromPythonOrg) that downloads
the official installer and runs it silently per-user (no admin/UAC)
when winget is unavailable or fails for any reason. Mirrors the
existing uv -> astral.sh fallback so Python installs without manual
steps. Resolves the latest 3.13.x from python.org with a pinned
fallback, and selects the amd64/arm64/x86 installer per architecture.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Pin remaining setup.ps1 winget calls to --source winget
Two winget invocations in studio/setup.ps1 still queried all sources and
could hit the same msstore certificate-pinning failure (0x8a15005e) that
broke the Python install in install.ps1:
- `winget show Nvidia.CUDA --versions` (CUDA Toolkit version probe)
- `winget install ... ShiningLight.OpenSSL.Dev` (OpenSSL dev for llama-server)
Every other winget call in this file already passes `--source winget`
(Git, CMake, VS Build Tools, CUDA install, Node.js, and setup.ps1's own
Python 3.12 install), so these two were stragglers. Both packages live in
the winget source; pinning it makes setup robust to an unhealthy msstore
source, matching the rest of the file.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Stop amd-smi GPU probe from popping a DiskPart UAC prompt
On Windows, AMD GPU detection in install.ps1 and studio/setup.ps1 runs
`amd-smi list` / `static --asic` / `version`. amd-smi (shipped in
System32 by the Adrenalin driver) auto-elevates to read GPU/APU memory
details, surfacing a confusing DiskPart UAC prompt mid-install. The
Studio backend already documents and circuit-breaks on this in
studio/backend/utils/hardware/amd.py, but the installers did not.
Add an Invoke-AmdSmiNoElevate helper (both scripts) that runs amd-smi via
Start-Process under __COMPAT_LAYER=RunAsInvoker so it cannot auto-elevate
(no prompt), with a 30s timeout (matching amd.py) so a flaky amd-smi
cannot stall the install for minutes. On failure/timeout the existing WMI
name -> gfx fallback still resolves the arch, so detection is unchanged on
working hosts.
Verified on a Strix Halo (Radeon 8060S / gfx1151) box: the prompt is gone
and the probe is bounded.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Add experimental ROCm-on-WSL setup helper for Strix Halo (gfx1151)
install.sh already routes gfx1151 (Radeon 8060S / Strix Halo) to the
repo.amd.com/rocm/whl/gfx1151 wheels once a ROCm runtime is present, but
it does not install AMD's driver/ROCm stack -- a large, admin-gated
prerequisite. scripts/install_rocm_wsl_strixhalo.sh automates the Linux
side on a dedicated Ubuntu 24.04 WSL2 distro: ROCm 7.2 (wsl usecase), the
rocr4wsl HSA runtime, a librocdxg build, env setup, and a PyTorch gfx1151
GPU smoke test. A hard preflight refuses to run until the Adrenalin
>=26.3.1 driver is actually present, so it cannot half-install.
Procedure adapted from AMD's ROCm-on-WSL docs and community gfx1151 notes.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Detect AMD GPUs by name so native Windows gets a GPU llama.cpp
The gfx-arch inference from the WMI GPU name was gated behind $HasROCm,
which the hipinfo/amd-smi probe leaves false on the common Windows case
(Adrenalin driver only, no HIP SDK -- and amd-smi often cannot read the
arch without elevation). So an AMD GPU was detected by name but never
mapped to a gfx target, --rocm-gfx was not forwarded, and studio setup
fell back to a CPU llama.cpp build.
Un-gate the inference (install.ps1 + studio/setup.ps1) so it runs whenever
an AMD GPU name is available. The inferred gfx is forwarded as --rocm-gfx,
which makes install_llama_prebuilt.py download the matching lemonade-sdk
ROCm prebuilt (e.g. llama-bNNNN-windows-rocm-gfx1151-x64.zip) -- a
GPU-accelerated llama.cpp that bundles its own ROCm runtime, so it runs
with just the Adrenalin driver. PyTorch's ROCm wheels still require a
confirmed HIP SDK ($HasROCm), so this only affects llama.cpp / inference
and never pulls broken ROCm torch.
Also broaden the name->arch table to every family lemonade ships Windows
assets for: gfx120X (RDNA 4), gfx110X (RDNA 3), gfx1151/gfx1150
(RDNA 3.5), and gfx103X (RDNA 2). Unknown names still fall back to CPU.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Suppress amd-smi DiskPart UAC prompt in the Python install/runtime paths
The earlier PowerShell guard covered install.ps1 / setup.ps1, but the
Python installer (install_llama_prebuilt.py detect_host,
install_python_stack.py ROCm probes) and the Studio backend monitor
(amd.py) also shell out to amd-smi on Windows, where it auto-elevates and
pops the same DiskPart UAC prompt mid-install / at runtime.
Inject __COMPAT_LAYER=RunAsInvoker into the amd-smi subprocess env on
Windows so it runs un-elevated (no prompt). Callers already tolerate an
empty/failed result and fall back to WMI / name detection (installer) or
the existing circuit breaker (amd.py). Gated to Windows so Linux/macOS
amd-smi behaviour is unchanged.
- install_llama_prebuilt.py: handled centrally in run_capture (covers
detect_host's `amd-smi list` and the version probe).
- install_python_stack.py: new _amd_smi_env() helper on its 3 raw
subprocess.run amd-smi calls.
- amd.py: merge RunAsInvoker into the existing child env.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Tighten AMD GPU name->arch patterns to avoid mismatches
The W9[0-9]{3} and RX 90[0-9]{2} patterns added for RDNA 4 were
speculative and over-broad: W9xxx would also match old GCN FirePro
W9100/W9000 cards (wrong gfx1201 -> a lemonade gfx120X download that
fails validation), and RX 90[0-9]{2} was redundant with the explicit
9070/9060 entries. Drop both; keep only confirmed RDNA 4 SKUs. Unmatched
AMD names still fall back cleanly to CPU.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Fetch the llama.cpp validation model via huggingface_hub
The prebuilt validation downloads a tiny GGUF test model from huggingface
via bare urllib. On Windows / proxy setups where the server sends an
incomplete TLS chain, urllib cannot complete the Amazon CA chain (it does
no AIA intermediate fetching) and fails with CERTIFICATE_VERIFY_FAILED, so
a perfectly good GPU prebuilt is rejected and the installer falls back to a
CPU source build.
Route the validation-model download through huggingface_hub
(hf_hub_download) -- the same mechanism Studio uses for model downloads,
which completes the chain where urllib cannot -- keeping the direct URL as
a fallback. This lets the lemonade ROCm prebuilt validate and install on
cert-restricted machines (verified: hf_hub_download succeeds where urllib
returns CERTIFICATE_VERIFY_FAILED).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Guard the remaining raw amd-smi version probe via run_capture
A ROCm-version detector in install_llama_prebuilt.py called amd-smi version through a raw subprocess.run that bypassed run_capture's Windows RunAsInvoker guard, so it still triggered the DiskPart UAC prompt during setup. Route it through run_capture like the other amd-smi calls.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Forward --rocm-gfx even when the ROCm runtime is unconfirmed
setup.ps1 forwarded --rocm-gfx (and picked the windows-hip llama.cpp
prebuilt) only inside `if ($HasROCm)`. On Adrenalin-only hosts (amd-smi
present but no HIP SDK, so $HasROCm stays false) the gfx arch was
name-inferred but never forwarded, so install_llama_prebuilt.py saw
has_rocm=False and installed the CPU build -- even though the lemonade
gfx1151 GPU prebuilt runs fine there (it bundles its own ROCm runtime;
verified: llama-cli --list-devices -> ROCm0: AMD Radeon 8060S, 69 GB).
Forward --rocm-gfx whenever a gfx arch is known (it is authoritative and
implies ROCm in install_llama_prebuilt.py), and treat a known gfx arch as
windows-hip in the existing-install mismatch check. --has-rocm stays gated
on the confirmed-runtime signal.
Verified on Radeon 8060S / gfx1151: the installer now selects, validates,
and installs llama-b1286-windows-rocm-gfx1151-x64.zip (ROCm DLLs present)
instead of the CPU build.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Install AMD ROCm PyTorch on name-inferred gfx hosts (enables Train/Export)
setup.ps1 picked the AMD ROCm PyTorch wheels only inside `if ($HasROCm ...)`.
On Adrenalin-only hosts (amd-smi present but no HIP SDK, so $HasROCm is
false) the gfx arch was name-inferred but the ROCm-wheel branch never ran,
so the host got torch+cpu. With CPU torch, torch.cuda.is_available() is
False, so the Studio backend sets CHAT_ONLY=True and hides Train/Export.
Un-gate the ROCm PyTorch index resolution on a known gfx arch (mirrors the
llama.cpp --rocm-gfx fix). AMD's per-arch Windows wheels
(repo.amd.com/rocm/whl/<gfx>) bundle the ROCm runtime, so they work without
a HIP SDK; a failed install still falls back to CPU.
Verified on Radeon 8060S / gfx1151: torch 2.11.0+rocm7.13.0 installs and
torch.cuda.is_available() -> True, device "AMD Radeon(TM) 8060S Graphics",
GPU matmul OK -> CHAT_ONLY=False -> Train/Export enabled.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Force amd-smi un-elevated process-wide in the Python installers
Guarding individual amd-smi call sites kept missing some (install_python_stack.py's probe loop and its Windows GPU re-check), so the DiskPart UAC prompt kept reappearing. Set __COMPAT_LAYER=RunAsInvoker process-wide at the top of install_python_stack.py and install_llama_prebuilt.py on Windows so every amd-smi subprocess (current and future) runs un-elevated with no per-call guard. Safe: these scripts only spawn amd-smi/rocminfo/hipinfo probes and pip/uv. setup.ps1 keeps per-call guards because it also spawns winget installers that need elevation.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Fix Invoke-AmdSmiNoElevate exit code on PS 5.1 + RX 7700S arch match
Start-Process -PassThru leaves the returned process object's .ExitCode
$null after WaitForExit on Windows PowerShell 5.1, so the helper set
$LASTEXITCODE to $null and every caller's `if ($LASTEXITCODE -eq 0 ...)`
was always false -- the amd-smi GPU / gfx-token / ROCm-version detection
branch was effectively dead (masked only because the un-gated WMI
name->gfx inference still ran). Reproduced on PS 5.1.26100.
Rewrite the helper to use [System.Diagnostics.Process]::Start with a
ProcessStartInfo (UseShellExecute=false), whose .ExitCode is reliable,
with async stream reads (ReadToEndAsync) to avoid a pipe-buffer deadlock
and WaitForExit(timeout) to bound a flaky amd-smi. __COMPAT_LAYER=
RunAsInvoker (inherited via the process env) still suppresses the
auto-elevation / DiskPart prompt. Also drops the temp files and the
empty-ArgumentList edge case. Verified: exit code propagates
(7 -> $LASTEXITCODE=7), output captured, env restored.
Also fix the gfx1100 name pattern `RX 7700(?! S)` -> `RX 7700(?!S)` so the
spaceless retail name "RX 7700S" is correctly excluded (it belongs to the
gfx1102 row). Both found by PR review.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Address PR review follow-ups (install.sh table, update path, tests, WSL)
From the multi-agent PR review:
- install.sh: sync the AMD name->arch table with install.ps1 / setup.ps1
(the bash table had drifted to the old narrow patterns). Adds RDNA 2
(gfx103X), workstation PRO W SKUs, and more Strix Halo/Point names, and
orders gfx1102 before gfx1100 so the spaceless retail name "RX 7700S"
resolves correctly (bash case has no negative lookahead). AMD-ROCm-only:
the name inference stays gated behind _has_amd_rocm_gpu(), so NVIDIA /
CPU / macOS are unaffected.
- setup.ps1: the "dependencies up to date" fast path skipped the torch
reinstall, so an existing user who had CPU torch (installed before
ROCm-wheel support) stayed stuck in CHAT_ONLY. Now, when an AMD gfx arch
is known AND the installed torch is CPU-only, don't skip -- force the
dependency pass so the ROCm wheels install.
- scripts/install_rocm_wsl_strixhalo.sh: resolve the real /opt/rocm dir
instead of hardcoding ROCM_VER for LD_LIBRARY_PATH / the librocdxg
symlink (breaks if amdgpu-install lays ROCm under a patch-version dir);
add a LIBROCDXG_REF pin knob and a "verified against" freshness header.
- tests/studio/install/test_pr5940_followups.py: cover _hf_resolve_url_parts,
_fetch_validation_model_bytes (hf path + urllib fallback), run_capture's
Windows-only amd-smi RunAsInvoker injection, and install.ps1 vs setup.ps1
name-table parity (catches future drift). 14 tests, all passing.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix DiskPart UAC prompt: skip amd-smi on Windows without a HIP SDK
On Windows, amd-smi re-initialises the ROCm runtime on every invocation
(even `amd-smi version`) and, on hosts without a working HIP runtime
(consumer APUs/dGPUs with only the Adrenalin driver), elevates a child
process at runtime -- popping a UAC/DiskPart prompt. amd-smi's own
manifest is asInvoker, so __COMPAT_LAYER=RunAsInvoker cannot suppress
that runtime elevation (verified: even `amd-smi version` hangs and
times out with RunAsInvoker set).
Replace the ineffective RunAsInvoker-only approach with a real gate:
only spawn amd-smi on Windows when a HIP SDK is detectable (hipinfo
present, so amd-smi runs un-elevated) or the user opts in with
UNSLOTH_ENABLE_AMD_SMI=1. The gfx arch is already resolved from WMI
name inference (forwarded via --rocm-gfx), so ROCm wheel + lemonade
llama.cpp selection is unaffected. Linux/macOS amd-smi never elevates
and is untouched (no regression). RunAsInvoker is kept as harmless
belt-and-suspenders for tools that DO use manifest elevation.
Applied consistently across:
- studio/backend/utils/hardware/amd.py (runtime GPU polling)
- install.ps1, studio/setup.ps1 (install-time detection)
- studio/install_llama_prebuilt.py (prebuilt arch probe + version)
- studio/install_python_stack.py (ROCm version + arch probe)
Verified live on AMD Radeon 8060S (gfx1151), native Windows: fresh
install detects the GPU, installs ROCm torch (torch.cuda.is_available()
True), launches Studio with no DiskPart prompt, and inference, tool
calling, web search, LoRA finetuning, and GGUF export all run on the GPU.
Tests: add 6 _amd_smi_allowed() gating tests + PowerShell-installer gate
assertions; update the three amd-smi monitoring tests to opt in (they
mock amd-smi as available). Full suite: 267 passed, 2 skipped.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* install.sh: helpful WSL message when the GPU isn't exposed to ROCm
In WSL, an AMD GPU's ROCm-on-WSL runtime is only available with a recent
Adrenalin driver AND a distro AMD supports (currently Ubuntu 24.04). When
neither is in place, GPU detection (rocminfo/_has_amd_rocm_gpu) finds
nothing and we silently fall back to CPU.
Add an actionable hint in the CPU-fallback path, shown only on WSL and
only AFTER detection has already failed -- so it is forward-compatible:
the moment a driver/distro DOES expose the GPU (e.g. if AMD later adds
Ubuntu 26.04 support), detection succeeds and the hint never fires. The
message:
- notes a GPU is plumbed in (/dev/dxg) but no ROCm runtime is exposed,
- lists the two prerequisites (Adrenalin driver + Ubuntu 24.04),
- if the distro is not 24.04, says AMD may not support it yet,
- tells the user to `wsl --install Ubuntu-24.04` and re-run,
- links AMD's ROCm-on-WSL guide + the experimental Strix Halo helper.
Verified live: on Ubuntu-24.04 the hint shows (version-warning omitted)
and the CPU install completes; on Ubuntu-26.04 the extra "this distro may
not be supported" line appears and points to 24.04.
Also fix the experimental scripts/install_rocm_wsl_strixhalo.sh: AMD's
repo.radeon.com/amdgpu-install/ is indexed by unified installer version
(30.30, 31.30, ...), NOT ROCm version, so the hard-coded
amdgpu-install/7.2.0/ path 404'd. Scan the installer dirs newest-first
for a noble .deb matching the target ROCm major.minor (ROCm 7.2 ->
30.30.x/amdgpu-install_7.2.x), falling back to the newest available.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* WSL: fix shortcut collision + pin ROCm-on-WSL driver reqs from AMD docs
Two WSL-related fixes informed by AMD's official ROCm-on-WSL docs and
field reports for Strix Halo / Ryzen AI Max+ (Radeon 8060S, gfx1151):
1. Shortcut collision (real bug). install.sh's WSL branch wrote
"Unsloth Studio.lnk" to the SAME Desktop / Start Menu folder as the
native-Windows installer (install.ps1 New-StudioShortcuts). Running
install.sh in WSL therefore silently retargeted the native shortcut at
the WSL launcher (wt.exe -> wsl.exe), so the desktop/start-menu icon
stopped launching native GPU Studio. Now the WSL shortcut uses a
DISTINCT name -- "Unsloth Studio (WSL - <distro>).lnk" -- and fetches
the Unsloth .ico to %LOCALAPPDATA%\Unsloth Studio so it shows the
proper icon. Native and WSL shortcuts now coexist.
2. Precise ROCm-on-WSL prerequisites. Research (AMD radeon-ryzen WSL
compatibility matrix, gianni.rosagallina.com Feb-2026 guide,
ROCm/ROCm#4952/#5509/#6022) confirms WSL GPU on Strix Halo requires
AMD Adrenalin Edition >= 26.1.1 (26.2.2+ is the first production
ROCDXG/WSL release) + ROCm 7.2.1 + Ubuntu 24.04; an older driver does
not inject the ROCm/DXG runtime into /usr/lib/wsl/lib, so rocminfo sees
only the CPU. install.sh's WSL hint and the experimental
install_rocm_wsl_strixhalo.sh header/preflight now state the exact
driver version (was a guessed ">=26.3.1"), bump ROCM_VER to 7.2.1, link
AMD's radeon-ryzen docs, and document the known librocdxg caveat that
usable VRAM is currently capped at the .wslconfig memory setting.
bash -n clean; install test suite 267 passed, 2 skipped.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: hint when the AMD driver is too old for ROCm-on-WSL
Adds a detect-and-guide hook for the optional WSL-GPU path. An AMD GPU on
native Windows can also be used inside WSL2, but only with AMD Adrenalin
Edition >= 26.2.2 (the first production ROCDXG/WSL release). Native Windows
GPU works with any recent driver, so this is purely about enabling the WSL
path.
We intentionally do NOT auto-install the driver: AMD referrer-gates driver
downloads (scripted curl/Invoke-WebRequest are blocked) and does not publish
Adrenalin via winget, so no installer can reliably fetch it -- and silently
swapping a live display driver is risky. Instead we point the user at AMD's
official download page (one click), after which the existing WSL detection
lights up automatically.
- install.ps1: new Show-AmdWslDriverHint -- when an AMD GPU is present and the
installed driver predates the 26.2.2 release (DriverDate < 2026-02-01),
print a concise tip with the AMD download URL. Handles DriverDate as either
a CIM DateTime or a WMI string. Suppress with UNSLOTH_SKIP_AMD_DRIVER_HINT=1.
- install.sh (WSL hint): add the direct Adrenalin 26.2.2 download URL and note
that AMD downloads are referrer-gated (open in a browser).
Verified: hint fires on a Sept-2025 driver, auto-suppresses on >= 2026-02-01;
install.ps1 parses; install.sh bash -n clean; suite 267 passed, 2 skipped.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* install.ps1: refresh shell icon cache after creating the shortcut
After writing the Desktop / Start Menu .lnk, nudge Explorer to refresh
its icon (ie4uinit.exe -show). Without this, a stale icon cache can show
a blank shortcut icon until the next explorer restart -- most visible
when a shortcut of the same name was rewritten (e.g. a native install
followed by a WSL install, which previously shared the name; now they use
distinct names, but the cache nudge makes the icon appear immediately
regardless). Best-effort and wrapped in try/catch so it never fails the
install. The bundled unsloth.ico itself is valid (verified it renders).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* setup.ps1: don't silently CPU-build llama.cpp on an AMD GPU
For AMD, GPU acceleration comes from the lemonade ROCm prebuilt (it bundles
the ROCm runtime, no HIP SDK needed) and is the preferred/default path. The
source-build fallback is CPU-only -- a HIP/ROCm *source* build would need the
full HIP SDK + ROCm clang toolchain, which the prebuilt exists to avoid.
Previously, if an AMD-GPU host ever fell through to the source build (e.g. the
prebuilt could not be downloaded), it printed "building llama.cpp (CPU-only,
no NVIDIA GPU detected)" and quietly produced a CPU binary -- masking the lost
GPU acceleration. Now that case emits a loud [WARN] explaining the GPU prebuilt
is the AMD path and how to restore it (re-run / check network / set
UNSLOTH_LLAMA_RELEASE_TAG), so AMD never silently degrades to CPU.
No behavior change on the happy path: AMD still gets the GPU prebuilt (verified
on gfx1151: ggml-hip.dll bundled, ~80% GPU compute during inference). NVIDIA
(CUDA source build) and CPU-only hosts are unchanged.
setup.ps1 parses; install suite 267 passed, 2 skipped.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* uninstall: remove shared llama.cpp build, kill lock-holders, match WSL shortcut
Three gaps found by running a real uninstall on a native-Windows + WSL host;
all fixes are scoped to Unsloth-owned paths and no-op on the other pathways
(env/custom-root, NVIDIA/AMD/CPU, Mac) so nothing else regresses.
uninstall.ps1:
- Remove the default-mode SHARED llama.cpp build + cache. setup.ps1 installs
them at ~/.unsloth/llama.cpp and ~/.unsloth/.cache -- SIBLINGS of studio,
not under it -- so deleting <studio> left hundreds of MB behind. Now removed
explicitly, then ~/.unsloth is dropped ONLY if empty (never nukes unrelated
content). No-op in env/custom mode (llama.cpp nests under the custom root,
removed already) and when absent. UNSLOTH_LLAMA_CPP_PATH (user-owned) is kept.
- New _StopProcessesLockingRoots: _StopStudioProcesses only matched the venv
unsloth/python/studio exe, so it missed (a) llama-server.exe under llama.cpp
and (b) an orphaned multiprocessing python fork that ran from the SYSTEM
python but loaded a venv DLL (bitsandbytes) -- on Windows an open DLL handle
blocks the directory delete, leaving a half-removed install. The new helper
kills any process whose image path OR loaded module is under a target root
(module scan scoped to python/unsloth/llama-server names; vendor-agnostic).
- _RemovePath now retries (transient post-kill handle release).
uninstall.sh:
- Remove the default-mode ~/.unsloth/llama.cpp + ~/.unsloth/.cache; rmdir
~/.unsloth only if empty.
- WSL Windows-side shortcut cleanup now matches by TARGET (any
"Unsloth Studio*.lnk" whose target launches wsl.exe), covering both the
legacy "Unsloth Studio.lnk" and the new "Unsloth Studio (WSL - <distro>).lnk"
-- and never removes a native-Windows shortcut (which launches wscript.exe).
uninstall.ps1 parses; uninstall.sh passes sh -n and bash -n.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* install.ps1: invalidate Win11 Start Menu tile cache after creating shortcut
The Start Menu shortcut kept showing a blank/generic icon even after the
Explorer icon-cache rebuild, because Windows 11's StartMenuExperienceHost
keeps its OWN pre-rendered tile-icon cache
(%LOCALAPPDATA%\Packages\Microsoft.Windows.StartMenuExperienceHost_cw5n1h2txyewy\
TempState\TileCache_*.bin + StartUnifiedTileModelCache.dat), separate from
Explorer's iconcache_*.db. ie4uinit and an explorer.exe restart do not touch
it, and they don't recycle the host -- so a rewritten same-name shortcut keeps
showing the first-rendered (often the generic wscript ">") tile until the host
restarts on its own.
Fix: after creating the shortcut, drop only the Start Menu RENDER caches
(TileCache_* + StartUnifiedTileModelCache.dat) and stop StartMenuExperienceHost
(Windows auto-relaunches it), so the tile re-resolves the real icon via the
shell image factory. start2.bin (the user's pinned layout) is deliberately
preserved. Guarded by Test-Path (Windows 10 has no such host -> skipped) and
wrapped in try/catch so it can never fail the install. Windows-only
(install.ps1); no effect on Linux/macOS/Studio.
Verified live: rendering the shortcut via IShellItemImageFactory::GetImage (the
API StartMenuExperienceHost uses) returns the Unsloth sloth icon, color-matched,
after this invalidation -- previously it returned the generic script tile.
install.ps1 parses; install suite 267 passed, 2 skipped.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* ROCm-on-WSL for AMD Strix Halo (gfx1151): auto-setup + runtime enablement
Make Unsloth Studio set up ROCm-on-WSL automatically for AMD Strix Halo
(Radeon 8060S / gfx1151) and use the GPU at runtime, validated end-to-end
on a Ryzen AI Max+ PRO 395 (ROCm 7.2.1 + librocdxg + Adrenalin Apr-2026):
rocminfo enumerates gfx1151, torch.cuda True, ~85.8 GB UMA pool.
Every change is a strict no-op for all other configs (NVIDIA/CUDA,
discrete + native-Linux AMD ROCm, macOS/MLX, Windows, CPU-only, non-Strix
WSL) and can never abort the installer.
- scripts/install_rocm_wsl_strixhalo.sh: rewrite to the validated recipe.
Fixes that would have broken a working box: drop the /usr/lib/wsl/lib
preflight (a working ROCDXG host has only d3d12/dxcore there); remove the
obsolete rocr4wsl step (gone from the 7.2.1 repo; would hard-fail and also
rips out the standard hsa-rocr ROCDXG needs); dynamic librocdxg soname
(was hardcoded 1.1.0; build is 1.2.0); direct apt-repo install; Windows
SDK auto-discovery; persist env to /etc/profile.d + ~/.bashrc; idempotent.
- install.sh: _maybe_bootstrap_rocm_wsl auto-offers/runs the helper when it
detects a Strix Halo APU in WSL (/dev/dxg) with no ROCm runtime, then
loads the env so detection routes to the gfx1151 wheels. Fast-path when
already configured. Fix an inaccurate WSL hint line.
- studio/backend/main.py + worker.py: set HSA_ENABLE_DXG_DETECTION=1
in-process before torch (gated on /dev/dxg AND librocdxg.so), so the
worker uses the GPU even when launched outside a login shell. Mirrors the
existing BNB_ROCM_VERSION injection.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* uninstall: clean up ROCm-on-WSL artifacts + Start Menu tile cache
- uninstall.sh: remove the ROCm-on-WSL helper artifacts -- the librocdxg
build clone (~/.unsloth/librocdxg, which otherwise blocks the empty-dir
rmdir of ~/.unsloth), the throwaway smoke-test venv, the persisted env
(/etc/profile.d/unsloth-rocm-wsl.sh) and the ~/.bashrc block. The system
ROCm userspace is a shared prereq like CUDA and is kept by default;
UNSLOTH_UNINSTALL_ROCM=1 removes it too. No-ops on macOS / non-Strix Linux.
- uninstall.ps1: invalidate the Win11 Start Menu tile cache after removing
the shortcut so its tile disappears promptly (mirrors install.ps1),
preserving start2.bin.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: accurate AMD ROCm messaging (HIP SDK optional, not required)
The Windows installer printed "HIP SDK not found - GPU-accelerated training
unavailable" / "ROCm wheels require the HIP SDK" whenever the HIP SDK was
absent. That is misleading: for a detected AMD GPU arch (gfx1151 etc.),
setup.ps1 installs AMD's bundled-runtime ROCm PyTorch wheels (repo.amd.com)
which ship their own ROCm runtime and do NOT need the HIP SDK -- verified
end-to-end (torch 2.11.0+rocm7.13.0, cuda True, QLoRA training on GPU) on a
Radeon 8060S with no HIP SDK installed.
Gate the GPU-detection + rocm-step messages on a detected gfx arch: when one
is known, state that GPU PyTorch uses bundled-runtime wheels and the HIP SDK
is optional; only when the arch is unknown fall back to the HIP-SDK hint.
Behavior (torch routing) is unchanged; this is messaging only. No-op for
NVIDIA/CUDA, HIP-SDK-present, and CPU paths (they hit earlier branches).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: fix /opt/rocm data-loss + make WSL shortcut create/remove interop-robust
Two fixes from the 3-reviewer regression audit + live testing on a
systemd-enabled WSL distro (interop disabled):
F1 (data-loss, install_rocm_wsl_strixhalo.sh): the /opt/rocm symlink-repair
could force-delete a pre-existing REAL ROCm install. The guard only checked
that /opt/rocm is a real directory, not that it is the stray librocdxg stub.
Now it only touches /opt/rocm when it is NOT a real install (no bin/rocminfo,
bin/hipcc, or .info/version present), and MOVES it aside (rocm.unsloth-stub-bak)
instead of deleting it, so a wrong guess can never lose data.
WSL interop robustness (install.sh + uninstall.sh): both relied on
`command -v powershell.exe`, which is true even when WSL interop cannot EXECUTE
it (on systemd distros powershell.exe fails with "Exec format error"). Result:
the WSL shortcut silently failed to create (install) and to remove (uninstall).
- uninstall.sh: test that powershell.exe actually runs; if not, remove the
"Unsloth Studio (WSL...).lnk" files directly via drvfs (/mnt/<drive>), which
works without interop. The name is WSL-install-specific, so a native install's
"Unsloth Studio.lnk" is never touched.
- install.sh: when the shortcut cannot be created, warn with the manual launch
command + how to re-enable interop, instead of failing silently.
No behavior change on the interop-on path. The regression audit otherwise found
no regressions on Linux/Mac/Windows/CPU/NVIDIA install paths.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* install.sh: fast-path fully restores ROCm-on-WSL env when the drop-in is gone
Reinstall regression found by uninstall->reinstall testing: after a Studio
uninstall that removed /etc/profile.d/unsloth-rocm-wsl.sh but KEPT the shared
ROCm (the default), a non-login reinstall hit the bootstrap fast-path
(librocdxg present) and its else-branch only set HSA_ENABLE_DXG_DETECTION --
NOT PATH/LD_LIBRARY_PATH. So rocminfo was not on PATH, GPU detection failed,
and the installer fell back to CPU-only PyTorch.
Fix: when librocdxg is present but the env drop-in is missing, restore the
FULL env inline (HSA + TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL + PATH +
LD_LIBRARY_PATH) so rocminfo is found and detection routes to the GPU, and
recreate /etc/profile.d/unsloth-rocm-wsl.sh so future shells and the Studio
worker get it too. No change to the env-present fast-path or any other host.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: clear Explorer icon cache so shortcut icons aren't blank
Root cause of the persistent blank Desktop + Start Menu icons: Explorer caches
each shortcut's icon in iconcache_*.db and does NOT re-read the .ico when a
same-name .lnk is recreated across reinstalls. The .ico and .lnk are correct
(the shell renders them non-blank via IShellItemImageFactory; the .ico has real
image data at 16/32/48/128 px), but the stale cache entry wins. The previous
fix only ran a weak `ie4uinit -show` + the Start Menu tile-cache clear -- it
never invalidated Explorer's icon cache, so the desktop icon stayed blank.
Fix (native install.ps1 New-StudioShortcuts AND the WSL shortcut path in
install.sh):
- ie4uinit -ClearIconCache (thorough; replaces -show as the primary refresh)
- SHChangeNotify(SHCNE_ASSOCCHANGED) to force a live desktop/taskbar refresh
WITHOUT restarting explorer
- keep the Win11 Start Menu tile-cache invalidation (and add it to the WSL
shortcut path too, preserving start2.bin)
Non-disruptive (no explorer restart). install.ps1 parses clean; install.sh
passes bash -n + dash -n; the heredoc-generated WSL PowerShell parses clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: per-item SHChangeNotify(UPDATEITEM) reliably fixes blank icons
The blank Desktop/Start Menu shortcut icons are a stale Explorer PER-ITEM icon
cache: when a same-name .lnk is recreated across reinstalls, Explorer caches the
previously-resolved (often generic "white page") icon for that item and won't
re-extract the .ico on its own. The .ico and the .lnk's IconLocation are correct
(every icon API renders the sloth) -- only Explorer's cached display is stale.
The previous refresh (ie4uinit -ClearIconCache + a GLOBAL SHCNE_ASSOCCHANGED
broadcast) does NOT recover a stale item -- confirmed by reproduction. The
reliable, NON-disruptive fix (no explorer restart) is a PER-ITEM
SHChangeNotify(SHCNE_UPDATEITEM, SHCNF_PATHW, <lnk path>) for each created
shortcut, which forces Explorer to re-read that exact item's icon.
Verified end-to-end: deliberately staled a shortcut to the generic icon, ran the
installer's exact new refresh code, and the sloth icon recovered with NO explorer
restart (confirmed by capturing the live desktop via PrintWindow).
Applied to both native install.ps1 (New-StudioShortcuts) and the WSL shortcut
path in install.sh. Still clears the on-disk icon cache (ie4uinit) and the Win11
Start Menu tile cache (preserving start2.bin).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* uninstall: remove leftover llama.cpp .staging root so ~/.unsloth is cleaned
The llama.cpp atomic-install staging root (install_llama_prebuilt.py
INSTALL_STAGING_ROOT_NAME=.staging) is a sibling of the llama.cpp install
dir (~/.unsloth/.staging in default mode). It is normally pruned after a
successful activate, but an interrupted or retained build can leave a
<name>.staging-XXXX tree behind. The uninstallers removed llama.cpp and
.cache but not .staging, so the final empty-dir cleanup of ~/.unsloth failed
and the directory lingered. Reproduced on WSL (Ubuntu-24.04) where an empty
llama.cpp.staging-XXXX dir kept ~/.unsloth alive after uninstall.
Remove ~/.unsloth/.staging in both uninstall.sh and uninstall.ps1. No-op in
env/custom mode (staging nests under the custom root removed already) and
when absent. Cross-platform fix (the staging logic is platform-agnostic).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: WSL-absent hint + fix here-string lint false positive
install.ps1: in the AMD WSL-ROCm driver hint, detect when wsl.exe is absent
and add a one-line "wsl --install -d Ubuntu-24.04" pointer so a Strix Halo
user with no WSL yet gets an actionable next step (the hint previously assumed
an Ubuntu-24.04 distro already existed). Best-effort, informational only.
test_rocm_support.py: test_no_here_strings did a crude substring check that
false-positived on the conda-style block marker
printf '# <<< Unsloth ROCm-on-WSL (gfx1151) <<<' -- a string literal written
into the /etc/profile.d drop-in, also used as a sed delimiter pair by
uninstall.sh, not a here-string. Strip quoted spans before the check so the
lint still catches a real here-string operator but ignores quoted literals.
install.sh remains POSIX-clean (sh -n / dash -n / bash -n all pass).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* installer: address PR review comments (gfx1150 mapping, amd-smi opt-out, WSL bootstrap, SDK path, make)
Apply the valid bot review findings on #5940; reject the ones that don't hold.
Fixed:
- AMD name->gfx table (setup.ps1 + install.ps1): Radeon 890M and Ryzen AI 9 HX
370/375 are Strix POINT (gfx1150), not Strix Halo (gfx1151). Move 890M / HX 37x
/ AI 9 HX to the gfx1150 row and drop the bogus HX 38x pattern (no such Strix
Halo SKU). Matches the runtime classifier in worker.py (890M/880M -> gfx1150;
8060S/8050S -> gfx1151). Prevents Strix Point hosts from getting the wrong ROCm
prebuilt/wheels.
- amd-smi opt-out (setup.ps1 + install.ps1): an explicit UNSLOTH_ENABLE_AMD_SMI=
0/false/no/off now wins over the HIP-SDK heuristic, so a host with a HIP SDK
binary but a broken runtime no longer gets the DiskPart/UAC prompt the opt-out
exists to avoid.
- amd-smi warning probes (install_python_stack.py): _has_rocm_gpu and
_detect_amd_gfx_codes now gate amd-smi behind _amd_smi_allowed() (and pass
_amd_smi_env()), closing the last unguarded amd-smi spawn on Windows.
- WSL ROCm bootstrap (install.sh): the "already-usable ROCm?" early return now
requires rocminfo to enumerate the real gfx1151 agent instead of the generic
_has_amd_rocm_gpu (whose broad gfx[1-9][0-9] match accepts a fallback
"gfx11-generic" ISA), so a Strix Halo box missing the ROCDXG bridge is no longer
skipped. The shared helper is untouched (no gfx90a regression).
- install_rocm_wsl_strixhalo.sh:
* Quote-safe Windows SDK discovery: the old for-in-$(ls -d "...Program Files
(x86)/...") word-split on the space and never matched; use find + read loop.
* Add `make` to apt prereqs (cmake only recommends it; minimal images lacked it
and the librocdxg `make -j` build failed).
* Verification requires gfx1151 exactly (not gfx1[0-9]) so a generic ISA or an
unrelated RDNA GPU can't pass while the real GPU is absent.
Reviewed but NOT changed:
- "Forward inferred ROCm arch without HasROCm" (setup.ps1): already correct --
--rocm-gfx is forwarded under `if ($script:ROCmGfxArch)`, not `if ($HasROCm)`.
- "Route inferred arch into install.ps1 torch path": not a bug -- install.ps1
installs CPU torch as a base by design and setup.ps1 swaps in the ROCm wheel for
the inferred arch (gate `($HasROCm -or $ROCmGfxArch) -and cpu`); verified live
the native install ends on torch 2.11.0+rocm7.13.0.
- "$p null guard after Start-Process" (install.ps1/setup.ps1): redundant -- the
amd-smi runner uses [Process]::Start wrapped in try/catch, so a null process
already returns "" with LASTEXITCODE=1 (no uncaught exception).
- "ls -> find for /usr/lib/wsl/lib" (gemini): stale -- that heuristic was removed;
only a comment about it remains.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer(rocm-wsl): auto-install the Windows 11 SDK via winget (fewer manual steps)
librocdxg's build needs the Windows SDK 'shared' headers on the Windows host.
Previously the helper just die()d with "install the Windows 11 SDK and re-run" if
they were missing -- a manual prerequisite that broke the otherwise-seamless
`curl ... install.sh | sh` one-liner on Strix Halo.
Now, when the headers aren't found, the helper installs the Windows 11 SDK on the
Windows host from inside WSL via winget (powershell.exe interop), then
re-discovers them. The SDK installer elevates -> ONE UAC prompt on the Windows
desktop; the headers appear under /mnt/c immediately (drvfs is live, no reboot).
The user already consented to the ROCm-on-WSL setup, so no extra prompt is added
beyond the OS UAC gate.
- New _find_win_sdk (space-safe find of the newest installed SDK 'shared' dir)
and _install_windows_sdk_via_winget helpers.
- winget IDs tried newest-stable first: Microsoft.WindowsSDK.10.0.26100, then
.22621. The presence of the headers (re-check) is the source of truth, not
winget's exit code. </dev/null so winget never consumes a piped `curl|sh` stdin.
- Best-effort + non-fatal: interop-off / no-winget / declined-UAC all fall
through to the existing clear manual-install die(). Opt out with
UNSLOTH_SKIP_WIN_SDK_INSTALL=1.
Removes the last avoidable manual step from the WSL Strix Halo path; only the AMD
Adrenalin driver (AMD referrer-gates the download) remains manual. Verified
_find_win_sdk resolves the spaced "Program Files (x86)" path; bash -n clean; all
winget flags validated against `winget install --help`.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer(amd): gate install-time amd-smi probe to fix DiskPart UAC prompt
install_python_stack.py's Windows "AMD GPU detected but ROCm torch missing"
warning probe ran `amd-smi list` whenever amd-smi was on PATH -- and amd-smi
ships in C:\Windows\System32 with the AMD Adrenalin driver -- without the
_amd_smi_allowed() gate that every other amd-smi call site in the file uses.
On Adrenalin-only hosts (no HIP SDK) amd-smi elevates a child at runtime and
pops a UAC/DiskPart prompt that __COMPAT_LAYER=RunAsInvoker cannot suppress
(amd-smi's manifest is asInvoker). The probe also ran before the
ROCm-torch-installed check, so it fired on every Windows AMD install.
Gate it behind _amd_smi_allowed() and pass _amd_smi_env(), matching
_has_rocm_gpu()/_detect_amd_gfx_codes(). When skipped, the only loss is the
best-effort "AMD GPU detected" note on HIP-SDK-less hosts.
Adds a per-function AST regression test asserting every function in
install_python_stack.py that names the amd-smi command and spawns a subprocess
also references _amd_smi_allowed() (flags the pre-fix code; passes after).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* studio(cli): fix `unsloth studio stop` crashing on Windows
`stop` used the POSIX `os.kill(pid, 0)` liveness probe, but on Windows
CPython raises OSError (WinError 87, "The parameter is incorrect") for
*every* pid -- alive or dead. `stop` only catches ProcessLookupError /
PermissionError, so the OSError propagated and the command crashed with
a traceback before ever reaching its (correct) `taskkill /F` path.
Add a cross-platform `_pid_alive(pid)` helper (tasklist on Windows,
signal-0 elsewhere) and use it for both the pre-check and the post-kill
wait loop. The actual kill path is unchanged.
Verified on Windows (Python 3.13): os.kill(pid,0) raises WinError 87 for
both a live and a dead pid; `_pid_alive` returns True/False correctly and
the full stop() flow (alive -> taskkill -> dead -> "stopped") passes
end-to-end against a throwaway process.
Adds tests/studio/test_cli_studio_stop_windows.py (AST guard against a
bare os.kill(pid,0) liveness probe + mock-only _pid_alive behaviour for
the win32 tasklist branch and the POSIX signal-0 branch).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* installer(amd): fix install.sh name->arch table misrouting Strix Point to gfx1151
The bash name->arch inference table in install.sh placed Strix Point
identifiers (Radeon 890M, "Ryzen AI 9 HX 370/375", "AI 9 HX") in the
gfx1151 (Strix Halo) row, diverging from the install.ps1 / setup.ps1
PowerShell tables which correctly map them to gfx1150. It also carried a
stray "HX 38" token absent from the PowerShell source-of-truth.
Align install.sh with the PowerShell tables:
gfx1151 row: 8060S|8050S|8040S|Strix Halo|Ryzen AI Max|AI Max
gfx1150 row: 890M|880M|860M|840M|Strix Point|Krackan|HX 37|AI 9 HX|...
Impact is low (the bash table only feeds the display label _gpu_disp_gfx
and the "set UNSLOTH_ROCM_GFX_ARCH=..." hint; wheel selection is driven
by the detected ROCm version, not this name string) but a Strix Point
user would otherwise see/copy the wrong gfx arch.
Add a parity test (test_install_sh_name_arch_agrees_with_ps_for_strix_and_non_amd)
that parses install.sh's case table and asserts Strix Halo->gfx1151,
Strix Point->gfx1150, RX 7700S->gfx1102, and NVIDIA/Intel->no match,
cross-checking against install.ps1 (the previous parity test only
compared install.ps1 <-> setup.ps1, missing install.sh).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* setup.ps1: keep prebuilt-llama ownership guard within the test's block window
The AMD additions to the prebuilt-llama.cpp block (the windows-hip vs
windows-cpu existing-install kind validation) pushed the
install_llama_prebuilt.py invocation to ~1999 chars after the
"installing prebuilt llama.cpp bundle (preferred path)" anchor, right at
the edge of the 2000-char window that
test_setup_ps1_prebuilt_llama_cpp_has_ownership_guard slices -- so the
helper string was truncated and the test failed with "substring not
found" (CI: Repo tests (CPU)).
The ownership-guard invariant (Assert-StudioOwnedOrAbsent precedes the
install_llama_prebuilt.py call) was already satisfied; only the proximity
to the anchor regressed. Move the "installing prebuilt..." substep to
immediately before the install (after the existing-install pre-cleanup),
which also reads better (validate/clean existing -> then "installing"),
shrinking anchor->helper from 1999 to 413 chars. Behaviour is unchanged
(console message ordering only).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* install.sh: auto-run Strix Halo ROCm-on-WSL setup by default
`curl -fsSL https://unsloth.ai/install.sh | sh` should make a Strix Halo
(gfx1151) GPU usable inside WSL with no extra commands. Previously the
ROCm-on-WSL bootstrap was opt-in: it required UNSLOTH_ROCM_WSL_AUTO=1 or an
interactive [Y/n] at a TTY, and silently skipped under a pipe (no /dev/tty),
so the piped one-liner never set the GPU up automatically.
Flip it to auto-by-default for the single narrow case the existing guards
allow (WSL + Strix Halo + /dev/dxg + no usable ROCm yet) -- exactly the GPU
setup the user ran the installer for. Opt out with
UNSLOTH_SKIP_ROCM_WSL_SETUP=1. The Tauri desktop app keeps its own consent UI
(only auto-runs when it passes UNSLOTH_ROCM_WSL_AUTO=1). All hardware/OS
guards are unchanged, so non-Strix / non-WSL / NVIDIA / native-Linux / macOS /
CPU paths are unaffected.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* PR comments: condense to be succinct (comments/docstrings only)
Shorten the verbose explanatory comments and docstrings this PR added across
the installer, scripts, backend shims, CLI, and tests -- tighter, fewer lines,
while preserving every non-obvious "why" (os.kill WinError 87, amd-smi
RunAsInvoker/UAC, /dev/dxg + librocdxg gating, the ROCm-on-WSL bootstrap guard
chain, ownership guards, etc.). No executable code, string literals, messages,
or behavior changed.
Verified comments-only: docstring-normalized AST equality (Python, 9 files),
non-comment token equality (PowerShell, 3 files), comment-stripped diff +
sh -n / bash -n (shell, 3 files). Behavior re-confirmed: get_torch_index_url +
gfx name->arch table 44/44 under dash & bash; rocm_support / pr5940_followups /
cli_studio_stop tests green.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Installer: address PR review (amd-smi opt-out, pipefail, multi-distro, non-root)
Fixes valid findings from the Codex/Gemini PR review:
- install.ps1 / setup.ps1: gate the `amd-smi version` ROCm-version fallback with
$amdSmiAllowed so UNSLOTH_ENABLE_AMD_SMI=0 opt-out is honored (the device
probe was gated but this fallback wasn't), avoiding the DiskPart/UAC prompt.
- install_rocm_wsl_strixhalo.sh: make the post-verification rocminfo summary
best-effort (|| true) so head's early pipe-close under `set -o pipefail` can't
fail the bootstrap after gfx1151 was already enumerated; pin the Windows SDK
`winget install` to --source winget (matches the msstore-cert fix rationale).
- install.ps1: python.org fallback installs the py launcher per-user
(InstallLauncherAllUsers=0, avoids admin), and derives the fallback full
version from the requested minor so a non-default UNSLOTH_PYTHON (e.g. 3.12)
isn't silently replaced with 3.13 when the listing is unreachable.
- install.sh: recreate /etc/profile.d/unsloth-rocm-wsl.sh via `sudo tee` for a
non-root reinstall (a plain redirect failed silently, dropping the ROCm env).
- uninstall.sh: scope WSL Windows-side shortcut removal to the current
WSL_DISTRO_NAME (per-distro name or -d "<distro>" arg) so uninstalling one
distro no longer deletes other distros' launchers.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Studio ROCm Windows: fix field-reported issues from Strix Halo testers
Four fixes from PR #5940 field reports (Win11 native, gfx1151):
1. bitsandbytes arch-probe spam: bnb's get_rocm_gpu_arch() runs
hipinfo.exe via subprocess PATH at import; the AMD torch wheel ships
hipInfo.exe in the venv Scripts dir, which is only on PATH for
activated venvs. Every bnb import logged "Could not detect ROCm GPU
architecture: [WinError 2]" ERROR + WARNING (even with the HIP SDK
installed, whose bin dir is not on PATH either). Prepend the Scripts
dir to PATH before bnb imports in main.py, worker.py, and
install_python_stack.py, gated on the file existing (only AMD wheels
ship it). Verified on gfx1151: ROCM_GPU_ARCH now resolves to gfx1151
with zero errors.
2. OOM-guard double-tax on native Windows unified APUs: mem_get_info's
total is the WDDM budget the driver grants HIP (BIOS carve + ~half
of remaining RAM) -- the OS share is already outside it. The 0.80
unified cap on top denied loads that fit (field report: 48.49 GiB
budget -> "38.79 GiB allowed" OOM for a 47.29 GiB load with 48.08
free). Use 1.0 on win32 unified; Linux keeps 0.80, discrete 0.90.
3. "Missing VRAM" confusion: log the WDDM budget vs physical RAM with
the fix (BIOS UMA frame buffer / AMD Software Variable Graphics
Memory) when the grant is under 75% of RAM, so a 48 GiB cap on a
96 GiB box reads as policy, not a Studio bug.
4. llama-server fit-step crash (Qwen3.6-27B-MTP + mmproj, lemonade
gfx1151): --fit defaults to 'on' upstream, so the fit step runs even
when Studio already placed the model via -ngl -1, and aborts in
ggml-cuda.cu on some ROCm hosts. Retry the spawn once with --fit off
when the server crashes during startup and Studio's own VRAM math
had placed the model (never when use_fit or an explicit fit flag was
passed). Also keep the TAIL of crash output in the error log (the
diagnostic line prints last; head-truncation cut exactly that) and
reference the full on-disk log.
Verified live on Radeon 8060S: bnb import clean, Qwen3.5-4B-MTP loads
and generates through the new spawn loop, stub-crash retry appends
--fit off and recovers, fraction probes confirm WDDM overcommit and
sub-1.0-only enforcement on current AMD wheels.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio ROCm Windows: GPU-name fallbacks so nothing depends on amd-smi
amd-smi does not reliably exist on Windows: the HIP SDK never ships a
CLI, inbox Windows Update drivers do not, and only some full Adrenalin
packages drop amd-smi.exe into System32 (field report: fresh Win11 +
Adrenalin + HIP SDK, still no amd-smi anywhere). Make every consumer
work without it:
- install_python_stack._detect_windows_gfx_arch: two new probes after
hipinfo/amd-smi -- (2b) the venv Scripts hipInfo.exe shipped by AMD
torch wheels (drives `studio update` on driver-only hosts), and (4) a
last-resort GPU marketing-name -> gfx table via WMI
(Win32_VideoController), mirroring setup.ps1's $nameArchTable so a
standalone repair resolves the arch with zero AMD tooling installed.
- install_llama_prebuilt._resolve_exe: also probe the venv Scripts dir
so a standalone rerun finds hipInfo.exe without HIP_PATH.
- hardware/amd.py _run_amd_smi: which() guard before spawning --
absence now disables the poller in one step instead of burning the
3-strike circuit breaker on FileNotFoundError; corrected the stale
comment claiming Adrenalin ships amd-smi.
Simulated against the real detection functions on gfx1151: amd-smi
absent, present-but-crashing (exit 1), present-but-hanging (60s sleep
vs 5-10s probe timeouts), and hard opt-out -- all resolve gfx1151, no
exceptions, bounded time. Full adversarial install (broken amd-smi
stub first on PATH + UNSLOTH_ENABLE_AMD_SMI=1, fresh uninstall first):
exit 0, name-table arch inference, lemonade gfx1151 b1292 prebuilt,
torch 2.11.0+rocm7.13.0 cuda_avail=True on the 8060S, Studio boots
healthy and stops cleanly.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: per-attempt llama-server log names + amd-smi test portability
Found by cross-platform simulation of the --fit off retry (Windows +
Linux sandboxes, real load_model with stub servers):
- llama-server log filename now carries the spawn-attempt index. The
retry can respawn within the same epoch second; reusing the name
opened the same file with "w" and truncated the crash log the retry
warning had just pointed the user at (proven with a frozen
time.time: one file, crash evidence gone; with the suffix both
attempts keep their logs). Regression-pinned in
test_llama_cpp_wait_for_health.py.
- test_amd_primary_gpu_with_mock now mocks shutil.which alongside
subprocess.run: the amd-smi absence guard which()-checks before
spawning, so on hosts without a real amd-smi (Linux CI, driver-only
Windows) the subprocess mock was never reached and the test failed.
Surfaced by running the suite in a clean Linux sandbox.
Simulation coverage on both OSes: 67-case platform/edge matrix
(real shipped code blocks under win32/linux/darwin spoofs: OOM-guard
fractions + VGM-hint boundary, bnb PATH-prepend gates, retry
eligibility incl. equals-forms and decoy tokens, GPU-name table
adversarial set, WMI fallback without powershell, monitor absence
semantics), 6-scenario live retry matrix (crash-once/crash-always/
exit-zero/explicit-fit/hang/log-collision) against real llama-server
spawns on Windows and WSL (GPU success legs on the 8060S), and a
3-engine browser matrix (chromium/firefox/webkit) driving the live
backend's health + authed /v1 chat completion.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: classify unified-memory via props.is_integrated first
Align the ROCm OOM-guard classifier with PR #5988's UMA gate: consult
hipDeviceProp_t.integrated (props.is_integrated) before the hardcoded
arch set. Strictly additive -- truthy upgrades to unified; 0/absent
falls through to the existing gfx1150/gfx1151 + device-name logic, so
wheels that omit or zero the field cannot downgrade the known APU set.
Extends correct unified-cap treatment to APUs outside that set (e.g.
gfx1103 Phoenix iGPUs) and keeps Studio's two unified-memory consumers
on one driver signal. Verified live on gfx1151 (is_integrated == 1 on
the AMD Windows wheel -> ('gfx1151', True) via the new path).
* AMD detection: probe rocminfo with HSA_ENABLE_DXG_DETECTION and sync setup.sh gfx table
Fleet validation on a Strix Halo WSL2 box showed the system rocminfo
(HSA 1.18, ROCm 7.2.1) only enumerates the GPU over /dev/dxg when
HSA_ENABLE_DXG_DETECTION=1, and that rocminfo can sit at /opt/rocm/bin
off PATH outside login shells. Detection probes that miss either of
these report no GPU on a working ROCDXG host and select the CPU build
even though the lemonade bundle offloads fine (95.7 tok/s measured vs
64.5 CPU on the same laptop). Seed the env (a no-op on bare metal) and
the PATH fallback in install.sh, studio/setup.sh, and the installer's
Linux rocm probe, mirroring what main.py/worker.py already do for the
runtime.
Also sync studio/setup.sh's name->gfx table with install.sh: 890M and
the HX 37/AI 9 HX SKUs are Strix Point (gfx1150, not gfx1151), RX 7700S
must match gfx1102 before the gfx1100 row, and the RDNA2/workstation
rows were missing. New parity test pins the two bash tables together so
they cannot drift again.
* Studio: persist server session logs + native-crash stacks to disk
Field report (Strix Halo, 96 GB UMA carve, WSL and native Windows):
"the studio just terminates without a warning". A native crash in the
GPU runtime kills the process with no Python traceback, and a desktop-
shortcut console closes before anything can be read. The server only
ever logged to the console, so there was nothing to send back.
run_server now tees stdout/stderr to
~/.unsloth/studio/logs/server/server-<ts>-pid<n>.log (console behavior
unchanged; file copy is best-effort), arms faulthandler at the same
file so access violations / SIGSEGV leave a stack trace on disk, and
exports PYTHONFAULTHANDLER=1 so training workers inherit crash dumps
on their captured stderr. Armed before `from main import app` so even
import-time failures leave evidence. Keeps the newest 20 session logs;
opt out with UNSLOTH_STUDIO_NO_FILE_LOG=1. Prints "Session log: <path>"
at startup so users know what to attach.
Verified on this box: a forced real segfault (faulthandler._sigsegv)
leaves the full session output plus "Fatal Python error: Segmentation
fault" and the thread stack in the file while the console shows
nothing; a normal server boot captures the startup banner and serves
health as before.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* AMD probe: honor a pre-set HSA_ENABLE_DXG_DETECTION value
Match the shell helpers, which use the parameter-default form: a user
who exports HSA_ENABLE_DXG_DETECTION=0 to deliberately hide the GPU
from DXG detection should not have the probe override it.
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.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.
* Studio: merge developer prompts for GGUF chat
* [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: fix OpenAI- and Anthropic-compatible API spec compliance
* Studio: fix API spec-compliance gaps on passthrough and streaming paths
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: carry context_length_exceeded through the OpenAI passthrough error path
* Studio: count tool-schema tokens in the Anthropic server-tool stream, and small stream-handling guards
* Studio: guard message_delta usage against None and normalize developer role before proxying
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: honor max_completion_tokens on the external-provider proxy path
* Studio: forward llama-server cached_tokens into OpenAI prompt_tokens_details
* Studio: sanitize messages in count_tokens to match the /v1/messages prompt
* Studio: report max_tokens for truncated tool calls and guard null usage in metadata events
* Studio: drop the request-id middleware (headers aren't declared in either spec)
* Studio: include the required request_id field in Anthropic error bodies
* Studio: honor max_completion_tokens on the audio (TTS / audio-input) paths
* Studio: add the _effective_max_tokens helper and route all max-token sites through it
* Studio: align API compatibility edge cases
* Studio: clarify multi-choice chat support
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: clarify logprobs chat support
* Studio: opt the local chat UI into the streaming usage chunk so the context bar and tok/s repopulate
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: forward seed to llama-server, and fix Anthropic server-tool stop_reason, tool_result id correlation, and parallel-tool execution cap
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: align OpenAI chat completion spec edge cases
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: align backend API compatibility tests
* Studio: honor tool caps and internal stream usage
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: coerce nullable stream usage counts
* Studio: preserve system prompts with developer messages
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
Unify the Studio local tool-call loop (GGUF + safetensors) behind a shared ToolLoopController: ordered preface-then-tool-card rendering, duplicate-call de-looping with a forced final answer, XML-leak containment, and a parser fix that accepts closed <function=...> calls followed by trailing prose. Includes backend tests for the controller, strict parser, and GGUF route cursor reset.
* Studio: make Helper LLM startup pre-cache opt in
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Adds the Studio Hub and download manager: browse Hugging Face models and datasets, download GGUF and safetensors with live progress and cancellation, and manage on-device inventory. The Hub does not require a GPU, so it is available on chat-only hosts.
CI: all substantive checks pass, including the three Core jobs after unsloth-zoo#736. The two red checks are non-code flakes, a transient npm-registry DNS resolution failure in the package scan and one quantized vision-model output assertion whose sibling shards passed.
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.
* fix: persist chat presets with fast mode
* Add schema drift guard test for chat inference settings (#5862)
Asserts ChatInferenceSettings declares every InferenceParams field the
frontend persists (all but checkpoint). With extra="forbid", a field
present in the UI but missing here 400s PUT /api/chat/settings, which is
exactly how fastMode regressed. Catches the next occurrence at CI time.
* [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>
Normalize misplaced system-role messages in /v1/messages by hoisting their content into the top-level Anthropic system field, fixing the 422 that newer Claude Code clients trigger. Null and non-text system content is ignored rather than stringified.
Fixes#6001
* fix: enable GGUF tools with vision inputs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: GGUF vision tool routing
* Dedupe system messages on GGUF vision tool path for PR #6009
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Studio: enable audio input for Gemma 4 GGUF models
Audio file upload was disabled for Gemma 4 vision+audio GGUFs (e.g.
gemma-4-12b-it-GGUF) even though their mmproj carries an audio encoder
(clip.has_audio_encoder, gemma4ua). Two causes:
- Audio-input detection only matched Gemma 3n's <audio_soft_token>;
Gemma 4 uses <|audio|>, so audio_vlm was never detected.
- The GGUF load/status responses hardcoded has_audio_input=False, so the
flag was dropped even when audio_vlm was detected (affected Gemma 3n
GGUFs too).
Changes:
- Recognize <|audio|> alongside <audio_soft_token> in the llama-server
token probe and the tokenizer-config pattern.
- Read clip.has_audio_encoder from the mmproj as an independent,
model-agnostic signal (read_mmproj_audio_capability).
- Emit the computed has_audio_input on the GGUF load/status responses.
- Tests for the new pattern and the mmproj reader.
* Studio: default chat model and dataset helper to Qwen3.5-4B-MTP
Switch the auto-loaded chat default and the dataset-analysis helper GGUF
from gemma-4-E2B-it to unsloth/Qwen3.5-4B-MTP-GGUF (UD-Q4_K_XL).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
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