* studio: shard export checkpoint loads across all visible GPUs
Export checkpoint loading always used unsloth's from_pretrained default of
device_map="sequential", which stacks the whole model on GPU0. On a multi-GPU
host this OOMs GPU0 while the other GPUs sit empty, so a GGUF export that would
comfortably fit across the machine fails with CUDA out of memory (#7053).
Add _multi_gpu_device_map_kwargs(): when the CUDA/ROCm host exposes more than
one visible GPU and get_device_map resolves to "balanced" (the same policy the
inference loader already uses), pass device_map="balanced" to every
from_pretrained in load_checkpoint. In every other case -- single GPU, CPU,
MLX, or any probe failure -- it returns {} so the loader default is untouched.
Fixes#7053
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* studio/save: reach the UUID/MIG fallback, release sharded models before quantize
Two review fixes on the multi-GPU export sharding:
1. UUID/MIG CUDA_VISIBLE_DEVICES masks resolve to no numeric ids, so the
len(visible) > 1 gate skipped get_device_map entirely and large exports on
those hosts still stacked onto GPU0. An empty id list now routes to
get_device_map(None), whose visible-count fallback exists for exactly this
case; a genuinely GPU-less host still resolves "sequential" and keeps the
loader default.
2. The compressed (FP8/NVFP4) export freed GPU memory before its llm-compressor
subprocess only for single-device models -- a plain .to("cpu") is invalid on
an accelerate-dispatched model, so a multi-GPU-sharded checkpoint stayed
resident on every GPU while the subprocess loaded a second copy. The release
is factored into _offload_model_for_quantize_subprocess /
_restore_model_after_quantize_subprocess: dispatched all-GPU shards get their
accelerate hooks removed, move to CPU, and are re-dispatched over the
recorded hf_device_map afterwards. Maps with cpu/disk targets (already
offloading) and quantized models are left alone, as before.
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* studio/save: budget merged tensors per device, restore hooks if CPU offload fails
Two review fixes on the multi-GPU export path:
1. The LoRA-merge save path budgeted every merged tensor against GPU0
(get_device_properties(0) + unqualified memory_allocated()). A merged tensor
lives on the GPU of its source layer, so for a model sharded across GPUs
(the device_map="balanced" this PR enables) GPU1+ could OOM as their weights
accumulated while only GPU0's headroom was checked. Budget against W's own
device via a per-device cache; single-GPU behavior is unchanged (W on GPU0).
2. _offload_model_for_quantize_subprocess removed the accelerate hooks and then
moved a dispatched model to CPU; if that move raised (host RAM too small for
the sharded checkpoint) the model was left hookless and half-moved, breaking
later exports in the same worker. It now re-dispatches (or, for the
single-device path, moves back) on a failed move before aborting the offload.
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* studio/save: release sharded models before the torchao reload too
The portable torchao FP8/INT8 export freed the in-memory model only when every
parameter sat on one device, then reloaded a second copy with
device_map="auto". A checkpoint loaded through the new multi-GPU export map is
accelerate-dispatched across several GPUs, so that single-device gate never
fired and the original stayed resident on every GPU during the reload -- an OOM
for exactly the models large enough to have needed the sharded load.
It now uses the same _offload_model_for_quantize_subprocess /
_restore_model_after_quantize_subprocess pair as the compressed export, which
removes the accelerate hooks, moves to CPU, and re-dispatches over the recorded
hf_device_map afterwards. Those helpers are extended to XPU as well, since
torchao also runs on Intel GPUs and the path they replace covered both.
* studio/save: release quantized and cpu-spilled shards before quantize reloads
Two cases the release helper skipped outright, both of which leave GPU memory
held while the compressed subprocess or the torchao device_map="auto" reload
allocates a second copy:
- Quantized models. ExportBackend.load_checkpoint loads 4-bit by DEFAULT, so the
common Studio export hit the is_loaded_in_4bit guard and kept a quantized shard
on every visible GPU. They are now attempted like any other model: transformers
refuses .to() for some bitsandbytes builds, but that refusal raises before
anything moves, so the existing recovery path restores the model and returns
None -- best-effort where the stack allows it, old behaviour where it does not.
- Maps that spill to CPU. Any non-GPU target disqualified the whole model even
though the GPU-mapped modules were still resident and are exactly what needs
reclaiming. A cpu spill is safe to move (those weights are already in host RAM)
and is now released; only disk/meta targets are still skipped, because
accelerate keeps those parameters off the model and moving would try to
materialize the whole checkpoint. An all-CPU map is skipped as a no-op.
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* Fix multi-GPU offload for PEFT exports and fall back when sharding OOMs (#7215)
The dispatch branch of _offload_model_for_quantize_subprocess never ran for a
PEFT model: the wrapper proxies _hf_hook, so remove_hook_from_submodules raised
AttributeError and the bare except returned None. Studio always loads adapters,
so the new balanced map turned the offload off (0 percent freed against 91.8 on
the sequential path it replaces).
- resolve the real dispatch root before removing or replaying hooks
- snapshot and replay hooks, tensor placements and instance forwards; a plain
re-dispatch rebuilds hooks against the post-PEFT tree (395 to 1379) and drops
the fused kernels accelerate captured into _old_forward before unsloth patched
- drop the accelerator side of tied_params_map so the offload actually frees
- pass skip_keys on the fallback dispatch_model
- log the swallowed exception instead of returning None silently
- guard _unsloth_save_torchao_with_given_config like its two siblings
- retry the export load once on the loader default when the balanced map OOMs,
which happens when a training or chat job already owns the other GPUs
Measured on 4x B200 with Qwen3-0.6B: 89.9 percent freed bf16 and 79.7 percent
4bit under balanced, logits bit-identical, hooks and placements restored
exactly, 184 Params4bit round-tripped unchanged including nested state2.
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* Keep the original offloaded until the torchao copy is released, and retie shared weights (#7215)
Two follow-ups from review of 8b6b4ca0b.
_unsloth_save_torchao_with_given_config restored the original inside a finally
that ran as soon as from_pretrained returned, so the original and the quantized
copy were both resident while the copy was still being saved. The restore now
sits in an outer finally that covers saving and releasing quantized_model, which
is what the two sibling paths already do.
The dispatch replay did not preserve tied embeddings. A CPU round trip repoints
every tensor and accelerate's tied_params_map is keyed on the old pointer, so
replaying the hooks produced two independent parameters. Reproduced on a tied
Llama: lm_head picked up its own storage, the embedding was duplicated in VRAM,
and an update to one no longer reached the other. The snapshot now records tied
groups (named_parameters(remove_duplicate=False), since the default hides one
half of every pair) and re-ties them after placements are restored.
Verified: tie preserved, no extra storages, live CUDA storage census identical
before and after, updates propagate again, logits bit-identical, and the 4 GPU
invariants unchanged at 89.9 percent freed bf16 and 79.7 percent 4bit.
* Keep meta tensors out of tie groups, restore accelerate move guards, retry CPU spills (#7215)
Four follow-ups from review of a58f1086b.
Meta tensors all report storage pointer 0, and accelerate parks every
CPU-offloaded parameter on meta, so grouping by pointer collapsed them into one
fake tied group. Reproduced with a balanced map that spills two blocks to CPU:
18 meta parameters in a single group with shapes 64x64, 32x64 and 128x64, which
the retie step would have overwritten with the first one. Meta and null-pointer
tensors are now skipped, and the retie also checks shape.
remove_hook_from_submodules deletes the to/cuda/xpu wrappers dispatch_model
installs to stop a caller moving an offloaded model. The snapshot now records
and replays those alongside forward and _old_forward.
The single-device retry only matched OOM, but a balanced map that spills to CPU
is refused by bitsandbytes with a plain ValueError saying modules were dispatched
to the CPU or the disk (transformers quantizers/quantizer_bnb_4bit.py:128), with
no memory wording. That is now retryable too, which matters because Studio loads
4-bit by default and busy secondary GPUs are exactly when balanced spills.
The torchao path dropped the quantized copy at the end of the try, so a failure
in save_pretrained left it resident while the original was restored. The del
moved into the finally, ahead of the restore.
Four regression tests added; suites now 25 and 9.
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* Retry exports whose multi-GPU load silently offloads to CPU, and clear the failed torchao traceback (#7215)
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* Tighten comments for PR #7215
* Keep gradients across the export offload and release the failed torchao copy (#7215)
* Tighten comments for PR #7215
---------
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: Daniel Han <unslothai@gmail.com>
* fix(studio): support hostname-based enterprise proxies
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for more information, see https://pre-commit.ci
* fix(studio): strip userinfo from proxy fetch targets
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* ROCm/AMD CI coverage: arch-table parity, native-Linux lib prepend, RDNA4 grouped_mm, discovery-based shell suite
Three merged ROCm fixes shipped without tests, and the CI wiring that
would have run them was gated on files the fixes do not touch.
Tests added (113):
tests/studio/install/test_rocm_arch_table_parity.py (27)
diffs the four duplicated gfx -> AMD pip-index tables across
install.sh, install.ps1, studio/setup.ps1 and install_python_stack.py,
plus the GPU-name -> arch tables and the torch 2.11 pin allowlist.
tests/studio/install/test_rocm_native_linux_lib_dirs.py (26)
covers #7233: system-ROCm lib dirs prepended ahead of bundled
libggml-hip, the /dev/kfd + not-WSL + libhsa gate, the opt-out env
var, root resolution order, and source parity between the two copies.
studio/backend/tests/test_grouped_mm_rdna4_fallback.py (46)
covers #7292: registration on the CUDA dispatch key, grouped and
ungrouped numerics, bias/dtype promotion, and the Linux HIP<7.13 +
RDNA4 name gate, executed from the shipped source rather than a copy.
tests/studio/test_ci_shell_suite_coverage.py (14)
fails if either shell runner goes back to a hardcoded list or skips
a file without a recorded reason.
CI wiring:
studio-backend-ci.yml: add install.sh / install.ps1 to the path filter
(the suites it runs assert against those two files, so install-only
changes -- the shape most AMD/ROCm routing fixes take -- skipped it),
and replace the 13-file hardcoded shell list with directory
discovery. That list had fallen seven files behind, including
test_strixhalo_wsl_reroute.sh, the only shell coverage of the ROCm
WSL reroute, which had never run on a PR.
tests/run_all.sh: same discovery loop so local and CI agree.
* Test review fixes: assert on outcomes, not on the code under test
Self-review of the previous commit found four tests that passed for the
wrong reason.
1. The arch-table parity test pinned expected gfx ids copied out of the
shipped tables, which enshrined three upstream inaccuracies as
correct: RX 9070 (non-XT) is gfx1201 not gfx1200, RX 7800 XT is
gfx1101 not gfx1100, and PRO V710 is gfx1101 not gfx1102 per AMD's
ROCm compatibility matrix. The expectation is now the AMD pip index
leaf -- the thing the tables exist to produce, and what a wrong
answer costs the user. The three known drifts are listed explicitly
with a test asserting they stay cosmetic, i.e. that the wrong and
right ids still map to the same wheel index. That test turns red the
day one of them starts routing users to the wrong wheel.
2. The RDNA4 device-name test extracted the regex from worker.py and
then matched with it, so it could not fail. Widening the pattern --
the dangerous edit, since it forces the slow Python mm fallback onto
RDNA3 users -- would have been silently accepted. It now reads the
live pattern and checks it against fixed cases, plus asserts the
name match stays guarded by `not _lin_arch` and that the name is
lowercased before matching.
3. The CI-coverage test matched a verbatim line of studio-backend-ci.yml,
so reindenting the step would fail the build while a real regression
to a hardcoded list could slip past a reformat. It now parses the
YAML, finds the step by name, and asserts on the glob plus the
absence of individual filenames. The path-filter test likewise reads
the parsed trigger instead of scanning raw text.
4. A set comprehension in the parity helper had a ternary whose branches
were identical.
Mutation-tested: widening the RDNA4 regex, desyncing one copy of the
name table, dropping install.sh from the path filter, and re-skipping
the ROCm WSL shell suite each fail at least two tests. Verified on
Linux (WSL Ubuntu 24.04) with CI's torch pin: 86 + 48 pass.
* Fix three wrong gfx ids in the GPU-name arch tables
The name -> gfx tables disagreed with AMD's ROCm compatibility matrix on
three entries. Corrected against the "Radeon GPU" list at
rocm.docs.amd.com/en/latest/compatibility/compatibility-matrix.html:
RX 9070, RX 9070 GRE gfx1200 -> gfx1201 (Navi 48, same die as the XT)
RX 7800 XT, RX 7700 XT gfx1100 -> gfx1101 (Navi 32, not Navi 31)
PRO W7700 gfx1100 -> gfx1101
PRO V710 gfx1102 -> gfx1101 (Navi 32, not Navi 33)
No wheel changes for anyone: gfx1200/gfx1201 both resolve to gfx120X-all
and gfx1100/gfx1101/gfx1102 all resolve to gfx110X-all, in all four copies
of the index-family map. That collapse is why the errors survived being
copied into six places -- the leaf-level tests could not see them.
It was not purely cosmetic, though. install.sh's second copy feeds
"Tip: set UNSLOTH_ROCM_GFX_ARCH=<arch>", so a 7800 XT user following the
printed advice exported gfx1100 and made a wrong id authoritative for
every later run. It would also have become a real misroute the moment AMD
split a family across index leaves, as they already do for gfx1151/gfx1150.
Fixed in all six places, which is two more than the table's own "kept in
sync with" comments claim exist:
install.sh _infer_amd_gfx_arch_from_gpu_name
install.sh case "$_gpu_disp_mkt" (banner + env tip; undocumented)
studio/setup.sh
install.ps1
studio/setup.ps1
studio/install_python_stack.py
Ordering is preserved: the gfx1102 arm still precedes gfx1101 in the shell
copies so "RX 7700S" cannot fall onto the "RX 7700" glob, and the
PowerShell copies keep the (?!S) lookahead.
Test changes:
- test_rocm_arch_table_parity.py gains _AMD_DOCUMENTED_ARCH, exact gfx
ids transcribed from AMD rather than from the tables. Agreement between
six copies proves nothing when all six were transcribed from the same
mistake, so the ground truth has to come from outside. Verified it
catches the bug: against the pre-fix tables it fails 6 tests.
- The parity check now covers all six copies. It had four; the two
install.sh copies were being treated as one, and
_WIN_GPU_NAME_ARCH_TABLE was not checked at all.
- test_rocm_support.py's TestGfxArchNameFallback pinned two of the wrong
ids as expected values; updated, and extended with a 9060 XT and a
7900 XTX case so each RDNA3/4 die is represented.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Guard against unregistered copies of the GPU-name arch table
Counting the copies by hand is what let them drift: the in-code "kept in
sync with" comments claimed four, the arch-id fix found six, and scanning
the tree turns up a seventh.
TestNoUnregisteredArchTable rediscovers the copies from the source tree
instead of trusting a hand-maintained list. A table line is one that names
a card and gives its arch; real tables score 9-17 such lines and the only
other hits in the repo are two single-line prose comments, so the
three-line threshold is not load-bearing. A companion test asserts the
scan still finds the known copies, so the heuristic cannot go blind and
pass by finding nothing.
The seventh copy is tests/_zoo_rocm_spoof.py, the fixture other ROCm tests
build their fake AMD host from. It states the mapping backwards (gfx ->
the name torch should report), which makes it an independent witness: it
had gfx1101 -> RX 7800 XT and gfx1201 -> RX 9070 XT right while all six
installer copies were wrong, and nothing compared the two. Now they are
round-tripped against each other.
RX 6700 XT is pinned as a known divergence rather than normalised. AMD's
compatibility matrix documents no consumer RX 6000 card and no gfx1031 at
all, the installer arm is commented "gfx103X family", and gfx1031 appears
only as an index-family key, never as a value a name table emits. With no
external source to correct against, changing shipped behaviour would be
guesswork. A test fails if the divergence ever disappears, so the
exemption cannot go stale.
Also adds the reverse of the AMD-matrix check: a documented card that
matches no arm anywhere is a silent CPU fallback rather than a wrong id.
This cannot detect hardware nobody transcribed, which would need a live
fetch of AMD's matrix and a non-hermetic suite; the docstring says so
rather than implying coverage that is not there.
Verified on Linux: 478 passed, plus all five new guards mutation-tested
to confirm each fails when its invariant is broken.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Docstring said six copies; the list under it now has seven
* tests: run discovered shell tests with bash, not sh
tests/run_all.sh discovered tests/sh/ instead of listing files, but still
invoked each one with sh. Every file there declares a bash shebang, and on
Debian/Ubuntu /bin/sh is dash: test_apt_distro_prompt.sh,
test_studio_home_node_dir.sh and test_with_llama_cpp_dir_link_behavior.sh
fail on bashisms under dash and pass under bash. The old hand-written list
happened to name only dash-clean files, so switching to discovery is what
surfaced it. Backend CI already used bash, so this was a local-only break.
Guarded by a new test asserting both runners invoke tests/sh/ with bash.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix Krackan Point (Radeon 860M/840M) routed to the gfx1150 wheel index
The GPU-name tables map 860M/840M and the Ryzen AI 7 350 / AI 5 340 CPU
strings to gfx1150, but Krackan Point is gfx1152. AMD's own lemonade table
(src/cpp/server/system_info.cpp) maps both Krackan iGPUs to gfx1152.
Unlike the three ids already fixed here, this one is not wheel-neutral:
repo.amd.com publishes gfx1150 and gfx1152 as separate index leaves with
separately built torch wheels, so these laptops were installing wheels
built for a different LLVM target. gfx1152 was absent from the codebase
entirely, so it needed the index-family maps, the torch 2.11 floor lists
(same _grouped_mm bug as gfx1150/1151), the Strix reroute set and the
Windows arch allowlist as well as the seven name tables.
The parity test added in this PR did not catch it because its AMD-matrix
expectations stopped at 890M/880M. Added the APU rows, so the case that
actually changes a wheel is now covered: reverting the tables fails 9
tests naming 860M, 840M and Krackan.
gfx1153 (Ryzen AI 5 430 era) is left alone; AMD publishes no gfx1153
wheel family, so there is nothing to route it to.
Verified: bash -n on both shell installers, PowerShell AST parse on both
.ps1 files, python ast.parse on all touched modules, install suite 1334
passed with no new failures against main, shell suite 20 files.
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* Add gfx1152 to unified-memory classifiers, make parity allowlist set-based
Krackan Point (gfx1152, Radeon 860M/840M) is the third RDNA 3.5 APU and
shares one GPU/system-RAM pool exactly like Strix Point (gfx1150) and
Strix Halo (gfx1151), but only the installers knew about it. The two
runtime classifiers still had two-element arch sets, so a Krackan laptop
got the 0.90 discrete headroom factor on a shared pool and ran llama.cpp
without GGML_CUDA_ENABLE_UNIFIED_MEMORY.
- worker.py _rocm_classify_unified_memory: add gfx1152 to the arch set,
and 860m/840m to the device-name fallback. The NVIDIA GeForce 840M
cannot collide there: the function is only reached under _hw.IS_ROCM.
- llama_cpp.py _amd_apu_wants_unified_memory: add gfx1152 to the arch set.
- Tests for both, including the :sramecc-:xnack- suffix form.
TestGfx211AllowlistParity compared four hardcoded allowlist strings, so
adding gfx1152 to all four installers correctly turned three assertions
red without any installer actually disagreeing with another. Each test
now extracts the set its installer holds and compares it to one EXPECTED
constant. Order and spacing are free, membership is not, and the next
leaf is a one-line edit instead of four.
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---------
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* Studio: reset quantized KV cache to f16 when flash-attn-off fallback fires
Studio force-enables --flash-attn on for GGUF launches. On a hard startup
or first-decode crash it retries via _with_flash_attn_off, which flipped FA
off but left --cache-type-k/-v untouched. A quantized KV cache (q8_0, q4_0,
q4_1, q5_0, q5_1, iq4_nl) requires flash attention in llama.cpp, so the retry
itself aborted at init with 'V cache quantization requires flash_attn' instead
of recovering.
Reset any quantized --cache-type-k/-v to f16 in the FA-off fallback path so
the retry can actually launch. Non-quantized types (f16, bf16, f32) run fine
without flash attention and are left unchanged. Handles long and short flag
forms and both space and equals syntax, rewriting in place to preserve list
length. Adds pytest coverage.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: FA-off fallback resets only the quantized V cache and drops env-only V cache
Only the V cache requires flash attention in llama.cpp; a quantized K cache
runs fine without it. Restrict the FA-off crash-recovery reset to the V axis
(main and draft) so a memory-constrained config keeps its quantized K cache
instead of risking an OOM on the recovery. Also drop an inherited quantized V
cache set purely through the environment (LLAMA_ARG_CACHE_TYPE_V /
LLAMA_ARG_SPEC_DRAFT_CACHE_TYPE_V) at the FA-off retry sites, which the argv
rewrite cannot reach, so the child falls back to the f16 default rather than
aborting.
* Studio: normalize underscore V-cache aliases in the FA-off fallback
llama.cpp rewrites '_' to '-' for any '--' long option before matching,
so a pass-through --cache_type_v q8_0 enables a quantized V cache just
like --cache-type-v. The FA-off crash-recovery reset only matched the
hyphenated spelling, so the underscore alias slipped through and the
retry still aborted with "V cache quantization requires flash_attn".
Canonicalize the flag name the same way before matching (short flags and
the type value are untouched).
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* Fix reasoning-only Qwen3.6 completions in Studio
* Address reasoning-only review findings
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* feat(studio): add DoRA support to studio
* fix: added use_dora fast encoder LoraConfig and gated use_dora on AdapterMethod
* fix(studio) serverside normalization for use_dora=true - add note documenting use_dora is silently dropped on diffusion
* fix: dora button disabled on mac, add preflight guard on GGUF lora export, mismatch now correctly falls through to existing error instead of silently no-opping
* Studio: add dora to the WizardState LoRA variant union for consistency
* Reject --use_dora on the MLX (Apple Silicon) CLI path
---------
Co-authored-by: danielhanchen <unslothai@gmail.com>
* fix(studio): stop false MTP/vision capability reports (#7302)
MTP probing only inspected the first physical --spec-type help line and
treated empty/crash --help output as "lacks MTP", which false-warned on
otherwise capable builds. Parse the full --spec-type help block, fail open
when the probe is inconclusive, and stop blaming bare mmproj crashes on a
projector-format mismatch when the text-only retry also fails.
Fixes#7302
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix(studio): tighten MTP probe semantics per Codex review (#7302)
Treat nonempty --help without --spec-type as definitive no-MTP, keep only
empty/crash probes inconclusive, skip binary_no_mtp UI hint on inconclusive
loads, and stop reporting supports_mtp=True in /status for unknown probes.
* Treat failed llama-server --help probes as inconclusive (#7302)
Gate definitive no-MTP results on a zero exit code so crash diagnostics with
nonempty stderr do not re-enable the false lacks-MTP warning path.
* Add returncode to probe test mock so probe_ok gating passes
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fail open in /status when the MTP probe is inconclusive
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Report missing llama-server as lacking MTP in /status
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Tighten comments in MTP/mmproj probe changes
---------
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Co-authored-by: Daniel Han <danielhanchen@gmail.com>
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
Co-authored-by: oobabooga <112222186+oobabooga@users.noreply.github.com>
* fix(studio): resolve bare git on Windows sandbox PATH
Sandboxed terminal tools rebuilt PATH as venv + System32 only, so
user-installed Git under Program Files never resolved by bare name.
Append absolute host PATH dirs after the curated prefix and inherit
PATHEXT on Windows (#7317).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix(studio): restrict sandbox PATH inheritance to Windows Git dirs (#7323)
Only append Git-for-Windows install directories from the host PATH on
Windows, instead of every absolute entry. This fixes bare `git` resolution
(#7317) without letting user-writable dirs (venv, node_modules/.bin)
shadow auto-safe terminal commands.
* Pin sandbox PATHEXT to block cwd script hijacks (#7317)
Use a fixed .EXE;.COM list instead of inheriting the host PATHEXT so
cmd cannot resolve auto-approved bare names from workdir .BAT/.CMD stubs.
* Resolve sandbox git dir via shutil.which and disable cwd exe lookup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Keep non-exe git launchers resolvable under restricted PATHEXT
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Restrict inherited sandbox git dir to system install roots
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Drop SystemRoot trust and canonicalize short paths for sandbox git
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Resolve Program Files via known-folder API and append canonical git dir
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Trust native Program Files on 32-bit Windows and stub program roots in tests
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Scan PATH for a trusted git and derive native Program Files root
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Drop ProgramFiles env from the trusted-root fallback
* Fail closed when trusted Program Files root cannot be resolved
---------
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 STT: only load safetensors weights for custom dictation models
The STT sidecar accepts arbitrary Hugging Face owner/model repos for
custom dictation models and, when safetensors were absent, downloaded
and loaded pytorch_model.bin through WhisperForConditionalGeneration
.from_pretrained. PyTorch checkpoints are pickles that execute code
during deserialization, and this path does not run the malware gate the
normal model loader applies, so an authenticated client on an exposed
Studio instance could load a crafted Whisper-looking repo and run code
in the backend.
Restrict custom STT repos to safetensors: the snapshot selector no
longer falls back to pytorch_model.bin(.index.json), the cached-snapshot
completeness check ignores pickle weights, and the load forces
use_safetensors so a stray cached pickle still cannot execute. The five
curated Whisper defaults already ship safetensors only, so this changes
nothing for the built-in models.
* STT: reject safetensors indexes that reference non-safetensors shards
A safetensors index (model.safetensors.index.json) is attacker-supplied
JSON and can name pytorch_model-*.bin shards in its weight_map.
Transformers dispatches shard loading per file by extension, so those
.bin shards still load through torch.load (pickle) even with
use_safetensors set. Require every weight_map value to end in
.safetensors in both the snapshot selector and the completeness check so
no pickle shard is downloaded or reused.
* Studio: add Voice settings tab (dictation, dictionary, read aloud)
New Voice tab in Settings, placed just before About:
- Dictation: microphone picker, browser STT engine, recognition language,
and an inline mic test with a live transcript
- Dictation dictionary: entries rewrite matching speech to their exact
spelling and casing, applied in both dictation paths
- Recent dictations: last 20 final transcripts with copy and clear, so
text can be recovered if it lands in the wrong place
- Read aloud: optional button on assistant responses with two engines,
curated system voices (novelty and legacy voices filtered, quality
ranked, capped at 20) or the TTS audio model loaded in Unsloth via
/audio/generate (e.g. Orpheus), plus speed, pitch, volume and preview
Settings persist in localStorage (unsloth_voice_settings) and are read
at call time so changes apply without reloading the runtime. Adds en
keys plus the tab label for ja, zh-CN and pt-BR.
* Studio: drop the single option STT engine select, rename TTS option
The STT engine dropdown only had one entry, so it added noise without
giving a real choice. The engine row can come back once local STT
models land. Also renames the TTS engine option Unsloth TTS model to
Load TTS model to make the action clearer.
* Studio: harden Voice settings against edge cases found in simulation
Simulated the feature across Chromium, Firefox and WebKit plus node
level unit runs and backend contract checks. Fixes from the findings:
- Dictionary rewrite used a replacement string, so entries containing
dollar patterns corrupted transcripts (A$$AP became A$AP, $& injected
the match). Switched to the callback form of String.replace
- Persisted voice settings now validate types on hydration: non string
micDeviceId, dictationLanguage and ttsVoiceURI, and non boolean
ttsEnabled fall back to defaults instead of flowing into the UI
- Dictionary entries are trimmed, capped at 120 chars and re-sanitized
on hydration
- The Test dictation panel now falls back to the default microphone
when the saved device is unplugged, matching the composer adapter
Test coverage: 46 unit assertions (dictionary regex edge cases across
unicode, word boundaries and injection, voice curation for simulated
macOS, Windows and Linux voice inventories, corrupt storage merge),
13 backend contract checks against /audio/generate on an isolated
instance, and 60 browser assertions across the three engines covering
rendering, degradation without SpeechRecognition, curation in a real
DOM, dictionary persistence with unicode and dollar entries, the
no-model preview error path and corrupt localStorage recovery.
* Studio: address Voice settings review feedback
Verified each review comment before acting. Confirmed and fixed:
- Editing a dictionary entry was broken in two ways: the store trimmed
on every keystroke so spaces could not be typed, and clearing the
field deleted the entry and unmounted the input mid edit. Updates now
keep the raw value and a blur commit trims or removes the entry
- The unplugged mic fallback checked instanceof DOMException, but a
cross browser probe showed Firefox and WebKit throw
OverconstrainedError objects that are not DOMExceptions, so the
fallback never fired there. Matching on the error name now
- When the browser ended a dictation test on its own (silence timeout),
the mic stream stayed open. All recognition end paths now stop the
tracks and save the transcript through a single finalize path
- The studio TTS audio element now releases its WAV data URL as soon as
playback ends, fails or is cancelled
- Allow microphone now reports insecure contexts (no mediaDevices)
accurately instead of claiming access was blocked
- Voice tab copy moved into i18n keys per src/i18n/AGENTS.md, so locale
overlays can translate it; en is the baseline and parity passes
- unsloth_voice_settings added to the Reset all local preferences key
list so voice preferences obey the reset
- Non default microphones note that the system default is used when the
browser speech engine cannot bind a specific device, since browsers
without the start(track) overload ignore the argument silently
Re-ran the full simulation set after the changes: 46 unit assertions,
13 backend contract checks and 60 browser assertions across Chromium,
Firefox and WebKit all pass, plus a dedicated browser probe for the
dictionary editing behavior.
* Studio: use the chat mic icon in Voice settings for consistency
The Voice tab and its buttons used the hugeicons Mic02 glyph while the
chat composer uses a custom filled mic. Extract that composer icon into
a shared lib/mic-icon component, drop the duplicate inline copies in
thread.tsx and shared-composer.tsx, and use it for the Voice tab icon
and the tab's mic buttons so the microphone looks the same everywhere.
* Studio: address second round of Voice settings review feedback
Verified each new comment against the current code first. One item was
already fixed in the previous round (recording transcripts when the
browser ends a dictation test on its own). Confirmed and fixed:
- The microphone row showed a picker with generic names when browsers
enumerate unlabeled devices before permission, leaving no way to
grant access from the row. It now branches on whether labels are
visible and shows Allow microphone otherwise
- Compare chat dictation ignored the selected microphone. It now opens
the chosen device with the same fallback rules as the main adapter,
passes the track to recognition where supported and releases the
stream when recognition ends
- Closing the Voice tab cancelled the shared speechSynthesis even when
read aloud was playing a chat message. Cleanup now only cancels when
the tab owns an active preview
- Double clicking Start test could race two recognizers and leak the
first stream. A starting flag set before the getUserMedia await makes
start reentrancy safe
- Turning off the read aloud setting mid playback removed the only stop
control. The stop button now renders whenever a message is speaking
- When an engine lacks the start(track) overload, both dictation paths
now release the selected device stream before retrying with the
default microphone instead of holding it open
- Read aloud support no longer requires Web Speech synthesis: the
Unsloth TTS engine only needs audio playback, so it stays available
in WebViews without speechSynthesis, with a clear error if the system
engine is chosen there
Not addressed here: cancelling in flight backend TTS generation on
stop. The route runs generation in a worker thread without a
cancellation path, which is shared pre existing behavior with audio
chat generation and belongs in a backend change.
All suites re-run green: 46 unit, 13 backend contract and 60 browser
matrix assertions across Chromium, Firefox and WebKit, plus probes for
the unlabeled device branch and the double click race.
* Studio: drop empty and duplicate voiceURIs so the Voice tab never renders a crashing Select item
* Studio: guard dictation mic lifecycle in Voice test and Compare composer
Release a microphone opened after the component unmounts, and stop Compare
dictation on a permission or security failure instead of silently recording
from the default device, matching the main chat adapter.
* Studio: fix dictation and read-aloud lifecycle edge cases in Voice settings
- Join final dictation chunks with a space so recorded transcripts do not merge words
- Ignore a stale recognizer onend so a quick stop then restart is not torn down
- Use previewingRef so a double click on TTS preview does not orphan the first request
- Keep the read-aloud stop control visible when a new run starts while a message is spoken
- Stop the dictionary remove button from deleting an adjacent entry on a blur then click race
* Studio: trim redundant Voice settings comments
* Studio: fix Voice preview and Compare dictation edge cases
- Only cancel the shared speechSynthesis for a system-voice preview, so stopping
a Studio preview no longer stops an unrelated chat read-aloud
- Release the Studio preview audio and its WAV data URL on normal completion
- Iterate every finalized result in Compare dictation so batched phrases are kept
- Cap persisted recent dictations to the last 20 on hydration
* Studio: use clipboard fallback for recents and release failed preview audio
- Copy recent dictations via the copyToClipboard helper so the execCommand
fallback works in Safari and insecure http LAN contexts
- Release the Studio preview audio when play() rejects, not just on ended/error
* Studio: add local speech-to-text dictation engine
Add an offline dictation engine that transcribes with a local faster-whisper
model, alongside the existing browser (Web Speech) engine. The browser engine
streams audio to Apple or Google speech services and needs internet; the new
engine runs on the server, works offline, and drives any chat model without
evicting it (it loads in the backend process, separate from the model
subprocess). It also gives Firefox dictation, which has no Web Speech support.
Backend: a lazily-loaded, kept-warm faster-whisper sidecar and three routes
under /api/inference/audio (stt/status, stt/load, transcribe). faster-whisper
is torch-free, so this does not disturb the existing model stack.
Frontend: a Dictation engine setting (browser or local model), a curated model
picker with sizes, and MediaRecorder capture posted to the transcribe route.
The model warms automatically when the engine is selected, with live status.
* Studio: stream local STT transcription as you speak
Local dictation showed nothing until you stopped, because the whole clip was
transcribed once on stop. Now the growing recording is re-transcribed on a
fast pass every second and emitted as live interim text, with an accurate
final pass on stop. Partial recordings decode fine, and the model refines
earlier words as more audio arrives.
Adds an interim flag to the transcribe route (beam 1, no VAD) for the fast
preview pass; the final stop uses the accurate path.
* Studio: make local dictation stop instant and reliable
Stopping local dictation waited for a final network transcription before the
session ended, so the stop button did not flip and a second click ended the
session early and dropped the text. Now stop commits the live transcript
immediately, releases the mic at once, and ignores a second stop while
finalizing. Previews run more often so the committed text is current.
* Studio: record local dictation in short clips for reliable streaming
Re-transcribing a growing buffer every second got slower as it grew, flooded
the backend, showed stale words, and could leave the stop button stuck waiting
on a backlog. Record short independent clips instead and transcribe each once,
appending the text as you speak. Work per clip is bounded, so stopping is
prompt (with a hard timeout as a safety net) and long dictations stay smooth.
* Studio: dictate then transcribe once on stop, ChatGPT style
Local STT dictation streamed by re-transcribing the growing clip, which
was quadratic and saturated the backend (multi-second lag), and stop only
halted the recorder without releasing the mic, so it kept recording. Record
the microphone continuously, release it the instant the user stops, and
transcribe the whole clip once. Stopping is immediate and the transcript
lands in about a second. Also add the tiny model for the fastest option.
* Studio: surface dictation and read-aloud failures instead of failing silently
- Compare dictation reports microphone and speech-recognition errors via toast,
reusing the main chat adapter's describeMediaError and describeSpeechError
- Read-aloud toasts genuine model or synthesis failures while ignoring cancellations
* Studio: ChatGPT-style recording bar for dictation
Clicking the mic now drops the composer into a dedicated recording bar
with a live waveform, a discard (X) and a confirm (tick), instead of a
plain stop button. The tick stops recording and transcribes the clip;
the X throws the recording away and keeps whatever text was already in
the composer. The model adapter taps the mic with an analyser to drive
the waveform, and the router tracks the live session so the X can cancel
it without transcribing.
* Studio: transcribe dictation while speaking, ChatGPT layout
Match ChatGPT's recording layout: the bar now renders in place of the
input with the left plus button kept, the waveform in the middle, and
the discard and confirm buttons together on the right.
Cut the post-confirm delay by transcribing in the background as the user
talks. The audio is split at natural pauses (voice-activity detection off
the same analyser that drives the waveform) and each clip is transcribed
as it is cut, so confirming only has to finish the short final tail. The
model is also warmed when recording starts so the first run never pays a
cold load.
* Studio: ChatGPT waveform, hide tools while dictating, faster STT
Make the recording UI read like ChatGPT: the waveform is now a dense row
of round dots that rise into thin centered bars, and while dictating only
the plus button shows, with the mode badge and tool toggles hidden so the
bar is just the waveform and controls.
Speed up transcription: decode greedily (beam_size=1), which is several
times faster on CPU with negligible accuracy loss on short dictation
clips, and cap background segments at 6s so the final tail after confirm
stays short.
* Studio: finish ChatGPT voice bar and low-latency STT
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* Studio: full-width waveform with a timer that freezes on stop
Use the full-width waveform for the recording bar: brighter, bigger bars
that advance on a fixed cadence (keeping peaks between advances) so they
glide instead of racing by, inset from the composer edges. Keep a visible
timer and the green confirm button, matching the ChatGPT reference, and
freeze the timer and waveform the moment the user confirms.
* Studio: fix multilingual local dictation
* Studio: speed up dictation and release local STT
* Studio: harden dictation finalization and STT decoding
* Studio: restore Firefox dictation fallback
* Studio: add dictation history manager
* Studio: manage speech model downloads
* Studio: remove em dash from voice model label
* Studio: move dictation history into Voice
* Studio: source local STT from Unsloth Whisper models
Point the dictation STT sidecar and its Model Hub download entries at
Unsloth's Hugging Face Whisper repos (small, large-v3-turbo, large-v3)
and run them through Transformers, so Studio only ever downloads
Unsloth-uploaded weights. Drop faster-whisper and the Systran/mobiuslabs
repos; keep the Model Hub as the only download path via local_files_only,
and keep PyAV for audio decoding.
Device selection uses float16 on CUDA and float32 on MPS and CPU, since
Whisper's decoder is unstable in float16 on MPS and repeats tokens.
Shorten the model picker labels to name plus download size and update the
STT tests for the new backend.
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* Studio: smooth dictation waveform and keep pill height
* Studio: align STT model dropdown width and tidy voice copy
* Studio: guide to local engine when browser dictation is offline
* Studio: clarify voice section and STT model copy
* Studio: keep STT warm with training-aware eviction
* Harden STT lifecycle and browser compatibility
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* Fix model discovery test lint
* Harden cross-browser microphone errors
* Harden cross-browser microphone errors
* Surface voice test recognition errors and fall back to Studio TTS
- Voice test now toasts non-abort speech-recognition failures instead of
ending silently, matching the main and Compare dictation paths.
- Read-aloud routes to the backend model when the runtime lacks Web Speech
synthesis (audio-only WebView), so it no longer errors immediately.
* Fix reviewed STT lifecycle races
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* Fix read-aloud fallback controls
* Guard read-aloud stop when deleting a non-speaking message
aui.message().stopSpeaking() throws unless this message is the one being
read aloud, so calling it unconditionally rejected the delete handler before
the message was removed. Only stop speech when this message is speaking.
* Cap recent dictation transcript length before persisting
Recent dictations only limited entry count, so a long transcript stored the
full text in the persisted voice settings and a few could exceed the
localStorage quota, throwing synchronously from the uncaught dictation cleanup
path. Truncate each entry on save and on hydration, matching the dictionary cap.
* Studio: keep dictation mic clickable and guide to local model
Register the dictation adapter unconditionally so the mic stays enabled
for any engine and starts working right after switching to the local
model on an already-open thread.
When the browser engine cannot run (Firefox, Brave, non-secure origins),
clicking the mic shows a toast that points to the local speech-to-text
model instead of leaving a disabled button. The toast stacks its action
below the text with a fully rounded button.
* Studio: add bottom padding below the dictation guidance toast button
* Studio: increase bottom padding under the dictation toast button
* Studio: add bottom padding inside the dictation toast button
* Studio: add five Whisper defaults and custom model search
Add private UnslothAI Tiny and Base mirrors to the curated local STT choices while keeping Small as the default. Let users search or paste a Transformers-compatible Whisper repository and validate it end to end.
Keep short dictations in one clip to avoid repeated padded encoder work, then split longer recordings near Whisper's 30-second boundary.
Update hidden model filters and tests, including the CPU-only CI runtime stub for PyAV.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: use public Unsloth Whisper repositories
Point the Tiny and Base dictation defaults to the public unsloth repositories and remove the private mirror references from model filtering and tests.
* Studio: update Whisper download sizes
Reflect the cleaned public Tiny and Base repositories in the curated model labels.
* Studio: right-align STT model size, fix dropdown wheel scroll, refresh sizes
- Show the download size on the right of each model row so long names
like Whisper Large v3 Turbo no longer hide it
- Update curated Whisper sizes to the safetensors weights actually
downloaded: Tiny 151 MB, Base 290 MB, Small 967 MB
- Drive the model list scroll from a wheel handler so the mouse wheel
scrolls it inside the Settings dialog, not just the scrollbar
- Add a search icon and shorten the placeholder to Search model
* Studio: do not search when a dictation model is picked, shrink repo label
- Treat the filled-in model text as a selection, not a query, so choosing
a model no longer kicks off a Hugging Face search
- Make the repository line under each model name smaller
* Studio: tighten dictation model and local engine descriptions
* Studio: keep model display on pick instead of the query, shrink row text
- Guard the combobox input so selecting a model shows its name and does
not echo the typed query back or start a search
- Map the item label to the friendly display so picks fill the field
- Reduce the model name and size text in each row
* Studio: show only the model name in the dictation field, shrink size label
- Drop the download size from the search field; the name alone is shown
once a model is selected, with sizes kept in the dropdown list
- Reduce the size label text in each row
* Studio: clarify the dictation model description
* Studio: drop Hugging Face from the dictation model description
* Studio: move the dictation dictionary to its own Manage subpage
- Replace the inline entry list with a Manage row, matching Dictation
history, so a long dictionary no longer crowds Voice settings
- Add a DictationDictionaryView subpage that holds the entry editor
* Studio: match STT field font, use best voice for System default
- Bump the dictation model field text to text-sm so it matches the
engine dropdown next to it
- Resolve the System default read-aloud voice to the top curated voice
instead of the browser default, which is a robotic legacy voice on macOS
* Studio: rerank read-aloud voices and drop duplicate voice entries
- Rank by vendor quality, then the user's locale, then a preferred list of
natural voices, so the best voice leads instead of the first alphabetically
- Collapse voices that macOS reports twice under one name and language
* Studio: fold dictionary and recents into the dictation section
- Drop the separate Dictation dictionary and Recent dictations headings;
their Manage rows now sit under Dictation, split by the row divider
- Shorten the custom spellings description
* Studio: add search and sort to dictation history
- Filter saved dictations by text with a search field
- Sort by newest, oldest, or A to Z; show a no-matches message
- Keep Clear all available regardless of the current filter
* Studio: settle cancelled STT loads before training and fix dictation review items
Wait for a cancelled STT load to exit and release its memory before
reporting it freed for training, so the loader cannot still be inside
from_pretrained()/.to(device) holding VRAM when the training subprocess
starts. A load that finishes before observing the cancel now gets
unloaded so the memory is actually reclaimed.
Clear the accelerator cache before the CPU fallback in load() so a failed
CUDA/MPS load does not strand reserved VRAM once the sidecar is marked
CPU-resident.
Send the saved Hugging Face token when polling STT download progress so a
gated or private repo resolves and shows the correct Load/Downloaded
state instead of reporting missing.
Mark the composer Dictate button as type="button" so clicking it does not
also submit the draft when the composer already has text or attachments.
* Studio: pin dictation settings per session and close STT startup races
Capture the STT model and language when a dictation session starts and
pass them to every queued segment and the warm-up load, so changing the
model or language mid-recording no longer transcribes the same clip with
the wrong model or a model that is not downloaded.
Check the local runtime at the top of transcribe(), before the model
cache lookup and the bounded audio decode, so a server missing PyTorch or
Transformers returns 501 up front instead of decoding a long clip first.
Treat the training startup window as active for STT device selection.
start_training frees VRAM in before_spawn but only assigns _proc later, so
a concurrent STT load could take the GPU that was just cleared. A startup
flag now reports training active from the free until the process is live,
forcing those loads to CPU; a finally clears it on every exit.
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* Studio: stub the STT runtime check in transcribe orchestration tests
transcribe() now verifies the local runtime up front, so the unit tests
that exercise transcription orchestration must treat the runtime as
present to keep passing where PyTorch, Transformers, and PyAV are not
installed. Stub ensure_stt_available in the shared fixture and restore
the real check in the availability and load-rejection tests.
* Harden custom Whisper dictation models
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* Add whisper.cpp dictation engine with per-engine downloads and history rework
Engines
- New GGML STT sidecar that runs a managed whisper-server subprocess with
idle unload, plus a pinned static build script (scripts/build_whisper_cpp.sh)
- Dictation engine picker now offers Browser, Local transcription
(whisper.cpp), and Local transcription (Transformers)
- Both local engines serve the same five curated Whisper models and download
them directly with byte-level progress reported by /audio/stt/status
- Models auto load on selection and when their download finishes
- Unload and training admission account for both engines
Benchmarks (Apple Silicon, greedy, warm, same checkpoints)
- whisper.cpp transcribes 2.4x to 5x faster than Transformers and loads in
about 0.45s vs 0.86s for Whisper Small
- whisper.cpp GGUF path is unchanged by the Transformers addition
(load 0.445s -> 0.444s, short clip 0.391s -> 0.347s, long 1.197s -> 1.129s)
Voice settings UI
- Plain curated model select replaces the searchable combobox
- Single download progress bar with transfer rate for both engines
- Dictation history now stores every dictation with Show more pagination,
a top Clear history action, and links back to the chat it was spoken into
- Archived chats dialog gets the same pagination
- Delete dialog offers deleting a dictation together with its chat
Tests: 88 backend STT tests pass, including new snapshot download coverage.
Frontend typecheck, lint, i18n parity, and production build pass.
* Merge local engines into one option and source GGML models from unslothai
Engine selection
- The dictation engine dropdown is back to two choices: Browser and Local
transcription. The selected model decides the backend: curated ids run
GGML checkpoints through whisper.cpp, searched Hugging Face repositories
run safetensors through Transformers
- Model picker lists the curated models and searches Hugging Face for other
Whisper repositories, validating them before selection. The trigger is a
plain button so the selection never renders inside a text input
- /audio/stt/status accepts a model query param so downloaded state works
for custom repositories; the engine param on load, transcribe, and
download routes is derived from the model everywhere
Model source
- Curated GGML checkpoints now download from the Unsloth-hosted
unslothai/whisper-*-GGUF repositories (one repo per model) instead of
ggerganov/whisper.cpp; cache lookups, progress totals, and in-flight blob
tracking are per-model
Fixes
- Voice settings and dictation history were not persisting: the quota-safe
localStorage wrapper was declared after the store that uses it, so the
persist storage factory failed silently. Every settings write also threw
mid-click, which kept the model picker popover from closing on selection
- is_model_downloaded now verifies config, preprocessor config, and real
weight files instead of trusting an offline snapshot lookup, so a partial
download left by an aborted fetch shows the Download button instead of
failing to load
- Removed whisper.cpp mentions from user-facing text: the ready status
shows Loaded instead of the runtime name, picker rows show the source
repository, and runtime error messages say local transcription runtime
Verified with automated browser sessions and live API checks: selection
closes the picker with no page errors, persisted settings hydrate on
reload, a stale partial snapshot triggers download then loads on MPS and
transcribes, and curated models download from the unslothai repos. 88
backend STT tests, typecheck, lint, i18n parity, and build pass.
* Skip the duplicate source line for custom models in the STT picker
A custom repository's display name is its id, so search results and the
appended current selection rendered the same string twice. The source
line now only renders when it differs from the name; curated rows keep
their name, unslothai source repository, and download size.
* Verify every shard of a sharded checkpoint in the downloaded check
A snapshot holding one of N shards (or a corrupt shard index) passed the
downloaded check and then failed at load. When model.safetensors.index.json
exists, every shard in its weight map must now be present. Found by
simulation; covered by a regression test.
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* Rename stale _starting references in the pump resilience tests
The startup flag on TrainingBackend was renamed to _spawn_in_progress but
two tests added alongside it still asserted on the old name, failing the
Python 3.11 to 3.13 CI jobs.
* Make the selected model row clearly highlighted in the STT picker
The current selection was a faint background tint. It now uses the accent
background with a medium weight name. Two line rows use a small corner
radius; single line custom repo rows keep the pill shape.
* Address review feedback on STT snapshot checks, VRAM release, and dictation UX
Verify snapshot completeness in the load preflight so a partial download
fails before the audio is decoded, for curated and custom repos alike.
Drop the failed accelerator traceback before the CPU retry so the cache
clear can actually release that memory. Keep unloading the GGUF sidecar
after cancelling an in-flight Transformers load; both engines can hold
memory at once. Allow Auto language with English-only .en checkpoints,
matching the backend which sends no forced language. Keep the discard
button usable while a transcription is pending so a slow or hung request
cannot trap the composer in dictation mode. Stop linking Compare and
settings test dictations to the unrelated active single chat thread.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Move the CPU retry out of the exception handler
On Python 3.10 the interpreter exception state keeps its own reference
to the traceback, so dropping it from the caught exception was not
enough to release the failed accelerator load during the retry. Leaving
the handler before clearing the cache works on every supported version.
* Address review feedback on session handoff, chat pinning, and server lifetime
Starting a dictation from a second entry point now cancels the session
it replaces, so the old recording cannot keep the microphone open or
save a transcript with no discard button pointing at it. The linked
chat is pinned when recording starts, so switching threads while a
transcription finalizes cannot relink the transcript to the newly
opened chat. whisper-server is now bound to Studio's lifetime like the
other long-lived children: PDEATHSIG on Linux, the parent job object on
Windows, and pid adoption so the shutdown sweep reaps it; before this
it survived a Ctrl+C exit as an orphan still holding the model.
* Remove the dictation mic test from Voice settings
The composer dictate button covers the same check, so the test row, its
transcript panel, the unsupported fallback row, and their strings and
search entry are gone.
* Studio STT: gate GGUF whisper-server on training and fix dictation retry and dictionary edits
GGUF (whisper.cpp) sidecar:
- Launch whisper-server with --no-gpu while training is active, mirroring the Transformers sidecar's CPU device choice, so a mid-training dictation cannot reclaim the VRAM training just freed.
- Report is_loading() during whisper-server startup so training VRAM admission accounts for the accelerator memory it is about to bind.
- Require PyAV in is_available() so /audio/stt/status reports the engine unavailable when uploads cannot be decoded, instead of loading fine and then 501ing at transcription.
- Reject a missing model before decoding audio, matching the Transformers download preflight.
Voice settings:
- The download Retry button now restarts the download; the sidecar error is sticky until a new start(), so re-polling alone never cleared it.
Dictation dictionary:
- Tabbing from an emptied entry to its remove button no longer commit-splices the row first, which shifted indices and deleted the wrong entry.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio STT: fix curated GGUF whisper filenames to match hosted repos
The unslothai/whisper-*-GGUF repos host the checkpoint as whisper-<id>.bin,
not ggml-<id>.bin, so every curated dictation download and cached-path
lookup 404'd and the whisper.cpp engine could never load a model. Point
GGML_STT_MODELS at the real filenames and guard the naming with a test.
* Studio STT: validate a custom dictation repo before downloading it
The Transformers STT engine accepts an arbitrary owner/model repo, but the
download route handed it straight to snapshot_download, pulling a possibly large
non-Whisper repository into the shared HF cache. Confirm the repo is a Whisper
checkpoint first with the existing metadata-only validate_remote_model (no
weights); curated ids short-circuit and the GGUF engine (curated-only) is
unaffected. A non-Whisper repo now 422s before any download.
* Studio STT: preempt a still-loading GGUF server for training admission
A whisper-server still in its startup window binds accelerator memory but has no
loaded_model yet, so training admission could miss it and launch into an OOM.
Make the GGUF startup cancellable (cancel_pending_load signals an abort event and
terminates the starting process without the load lock; _wait_for_server observes
it and raises SttLoadCancelledError; wait_for_load_to_settle blocks on the lock
until the killed server is reaped), and always fold the GGUF sidecar into the
resident-STT summary so a resident Transformers model cannot mask a loading GGUF
server. free_stt_model_for_training now cancels an in-flight load and waits for it
to settle before training claims the memory.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio STT: fall back to Transformers when whisper-server is absent
A curated dictation model (including the default small) hard-pinned the GGUF
engine, but standard installs do not ship whisper-server, so every recording
501'd instead of using the Transformers engine that serves the same checkpoint
-- the GGUF sidecar's own documented contract. Add _resolve_serving_stt_engine:
a GGUF request for a curated id (the only ids GGUF accepts, all Transformers-
servable) downgrades to Transformers when whisper-server is unavailable, applied
consistently to download, load and transcribe (not unload, which targets a
specific engine). The Voice tab likewise falls back to the Transformers status so
the model is not shown unavailable and download is not blocked.
* Studio STT: hide custom Whisper caches from the legacy model pickers
The legacy /cached-models (and /cached-gguf) routes called is_hidden_model with
only the owner/model id, which cannot reach the config-based Whisper check, so a
downloaded custom (non-curated) Whisper checkpoint was still offered as a chat
model. Pass the cached snapshot path so _path_is_whisper_model inspects the repo
config and hides it, matching the discovery route.
* Studio STT: hide GGUF dictation repos, lock-free status, unload fallback, split training eviction
- Hide the curated GGUF dictation repos (unslothai/whisper-*-GGUF) from the chat
model inventory and pickers, backend and frontend. Only their Transformers
safetensors companions were hidden; the GGUF repos use a different org and a
-GGUF suffix and carry a raw .bin with no whisper config.json, so they leaked
into chat pickers.
- Make the GGUF sidecar loaded_model/device accessors lock-free, mirroring the
Transformers sidecar. transcribe() holds self._lock across the whole inference
call, so /audio/stt status polls and training admission previously blocked
behind an in-flight transcription.
- stt_unload resolves through the serving resolver: a "gguf" pick on a host
without whisper-server is served by the Transformers fallback, so unload must
target that engine or the resident model is never freed. Unload also attempts
every engine even if one raises, so a failure freeing one backend no longer
skips the other.
- free_stt_model_for_training frees the Transformers and GGUF sidecars under
independent exception boundaries so a failure unloading one no longer skips
the other before training claims the memory.
Adds tests/test_stt_review_fixes.py covering all four.
* Studio STT: resolve Auto dictation language for the model engine + snapshot process liveness
- The model dictation adapter sent the raw setting (the literal "auto") to the
backend, while the browser engine resolves Auto via resolveDictationLanguage.
A batch of non-English voice notes came back mostly English on Auto. Add
resolveModelDictationLanguage: only the literal "auto" is resolved to a
concrete locale, gated so it becomes a language the model AND Whisper can
honor (mirroring the backend's known-whisper-languages set); an explicit
language, or a locale Whisper cannot honor, stays unchanged/auto-detect. Wire
it into both adapter call sites.
- GgmlSttSidecar._process_alive() read self._process twice; a concurrent
unload() nulls it under the lock while loaded_model/device read lock-free, so
a null between the two reads called None.poll(). Snapshot once. Adds a
deterministic regression test.
* studio: tighten comments and docstrings in the dictation modules
* studio: harden dictation model downloads, GGML readiness, and recording paths
Address review findings on the STT dictation feature:
- build_whisper_cpp.sh refuses to delete a whisper.cpp tree under a custom
Studio home unless it carries the Studio ownership marker, matching the
setup.sh policy, and marks trees it creates
- _snapshot_is_complete validates every shard of a sharded PyTorch
(pytorch_model.bin.index.json) checkpoint like the safetensors path, and
requires tokenizer assets (tokenizer.json or vocab.json + merges.txt)
- custom-repo downloads pin the revision resolved at validation time and
restrict snapshot_download to the model/tokenizer/config/preprocessor file
classes Studio loads
- the GGML sidecar holds its port reservation until just before spawning
whisper-server and only accepts readiness from a responder that both looks
like whisper.cpp's server and belongs to the still-running managed child,
probing twice, so mic audio cannot be posted to a foreign local process
- the recording adapter transcribes every non-empty segment; the RMS meter
only shapes segment boundaries and can no longer discard quiet speech
- Compare-pane dictation can cancel a pending transcription on second click,
with the button relabeled while finalizing
- localStorage quota recovery halves the dictation history until the save
fits, so small histories shrink too
- the System default TTS voice resolves to the platform default voice
- new dictation UI imports go through the chat and hub feature barrels
Regression tests cover the build-script gate, sharded PyTorch and tokenizer
completeness, revision pinning and allow patterns, and the whisper-server
readiness probe.
* Fix STT download and voice picker follow-ups
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add dictation button regression coverage
* Studio: prebuilt whisper.cpp via the shared llama.cpp install core, slim bundles paired to the llama prebuilt (#7294)
* Studio STT: add prebuilt whisper.cpp (whisper-server) installer
New install_whisper_prebuilt.py downloads a per-platform whisper-server
bundle published by the unslothai/whisper.cpp prebuilt CI into the managed
whisper.cpp dir (build/bin/whisper-server) so local dictation needs no
compiler. Mirrors install_node_prebuilt.py / install_llama_prebuilt.py:
host + backend detection, sha256 pins (whisper_prebuilt_pins.json) as the
trust anchor, staging + install lock + atomic swap, traversal-safe extract,
co-located shared libs (RUNPATH=$ORIGIN), an UNSLOTH_WHISPER_PREBUILT_INFO.json
marker with idempotent "already matches", and exit codes 0/1/2/3. Not wired
into setup yet; the pins ship empty so every asset fails closed until the
first fork release is published and its digests are reviewed in.
* Studio STT: install prebuilt whisper.cpp during setup and update
Add a fail-open whisper.cpp block to setup.sh after the llama.cpp section so
`unsloth studio update` (and a fresh install) fetch the prebuilt whisper-server
into the managed whisper.cpp dir the sidecar discovers. It skips a user-set
WHISPER_SERVER_PATH/UNSLOTH_WHISPER_CPP_PATH, honors UNSLOTH_SKIP_WHISPER_INSTALL,
forwards the resolved ROCm gfx, and never aborts setup: a busy install keeps the
existing runtime, and an unavailable prebuilt stays quiet (source build is opt-in
via UNSLOTH_WHISPER_FORCE_COMPILE) since Transformers STT and browser dictation
remain. Register UNSLOTH_WHISPER_PREBUILT_INFO.json as Studio-owned evidence.
* Studio STT: harden whisper-server child env + WSL ROCm detection
- Sidecar spawns whisper-server with a scrubbed child env that prepends the
binary dir (co-located GPU libs) to the loader path, and on WSL2 ROCm loads
the system HIP first (HSA_ENABLE_DXG_DETECTION=1) so a bundle's bare-metal HIP
does not segfault on /dev/dxg. Secret-bearing vars are dropped from the child.
- find_whisper_server_binary now requires an executable, not just a file.
- Installer rocm probe passes HSA_ENABLE_DXG_DETECTION and falls back to
/opt/rocm/bin/rocminfo so a WSL ROCm host is not misdetected as CPU-only;
gfx parsing skips the gfx000 CPU agent and generic ISA lines.
- Tests for the child env (secret scrub, lib dir, WSL HIP precedence), the
executable check, and the WSL rocm detection.
* Studio STT: in-app whisper.cpp prebuilt update stack + ship pins in the wheel
Mirror the llama.cpp update stack for the whisper.cpp prebuilt so Studio can
detect and install a newer whisper-server release from inside the app:
- backend/utils/whisper_cpp_freshness.py: read UNSLOTH_WHISPER_PREBUILT_INFO.json
and compare the installed release against the newest unslothai/whisper.cpp
release. Whisper tags are v<upstream>-unsloth.<N>, so is_behind compares a
(major, minor, patch, serial) key with a strict downgrade guard; 24h cache;
fail-open.
- backend/utils/whisper_cpp_update.py: run install_whisper_prebuilt.py to fetch
and atomically swap the newest bundle, unloading the warm GGUF sidecar first.
- backend/routes/whisper.py mounted at /api/whisper (update-status + update).
- pyproject: add whisper_prebuilt_pins.json to studio package-data so the
installer's trust anchor ships in the wheel (it is a data file, not a .py
module, so package discovery alone does not include it; node_prebuilt_pins.json
is listed for the same reason). Without this a pip-installed wheel had no pins
and the prebuilt install aborted to Transformers STT.
Adds test_whisper_cpp_freshness.py (version parser, is_behind matrix + downgrade
guard, marker layouts, stale decision, fail-open).
* Studio STT: verify whisper prebuilts via the release checksum index, like llama.cpp
Re-align the whisper.cpp prebuilt installer to install_llama_prebuilt.py's trust
model: instead of a committed whisper_prebuilt_pins.json, verify every download
against the release's own whisper-prebuilt-sha256.json checksum index, fetched
from the same GitHub release.
- parse_release_checksums / fetch_release_checksums / expected_sha256_for replace
the pins layer. The index is validated for schema/component and that its
release_tag matches the resolved release; an asset absent from it, a release
that does not publish it, or a manifest sha256 that disagrees with it all fail
closed to a source build.
- resolve_release_tag now resolves the newest published release at runtime (or an
explicit --published-release-tag), matching llama and the freshness check;
removed the pinned-default and the UNSLOTH_WHISPER_ALLOW_UNVERIFIED opt-in.
- Delete studio/whisper_prebuilt_pins.json and drop its pyproject package-data
entry (nothing to ship now, same as llama which has no committed pins).
- Adds test_install_whisper_prebuilt_checksums.py (index parser, fail-closed on
uncovered asset, tampered-manifest guard, newest-release resolution).
This is a same-origin checksum (integrity, not authenticity), identical to the
llama.cpp installer; pair releases with GitHub artifact attestations for provenance.
* Resolve whisper prebuilt release via the download host (no GitHub API)
Mirror install_llama_prebuilt.py's fast path: resolve the release tag from
the releases/latest redirect and fetch the manifest + checksum index from
constructed releases/download URLs, so the common install path makes zero
api.github.com calls (unauthenticated api.github.com is capped at 60 req/hour
per IP; the download host is not). Fall back to the GitHub API only on a 404,
malformed asset, or tag mismatch.
* Studio STT: coverage-aware whisper prebuilt selection via a shared core
whisper's select_artifact returned the first os/arch/backend manifest match and
ignored the SM-coverage fields the release manifest already carries, so a
Blackwell B200 (sm_100) was served cuda12-legacy (sms 50-61) -- runnable only via
forward PTX JIT. install_llama_prebuilt.py on the same host correctly picks
cuda13-newer.
Extract the coverage-aware selection into a shared, component-agnostic core under
studio/backend/utils/prebuilt/ (selection + GPU host-capability detection), lifted
from llama's linux_cuda_choice_from_release / _artifact_covers_sms / _sm_range and
generalised over a normalised artifact. whisper's HostInfo now records the GPU
compute caps + driver CUDA version (honoring CUDA_VISIBLE_DEVICES), and
select_artifact routes CUDA/ROCm through the shared selector: every visible SM
must be covered, the tightest-covering profile wins (Blackwell-aware runtime-line
ordering), ROCm matches the gfx target exactly, and an uncovered GPU falls back to
the CPU bundle. CPU/Metal/Vulkan keep first-match. The resolver JSON, exit codes,
and "already matches" contract are unchanged.
On the B200 the installer now resolves cuda13-newer, matching llama.
* Studio STT: gate whisper CUDA selection on the on-disk runtime, like llama
The prebuilt CUDA bundles are dynamically linked and intentionally do NOT ship
libcudart/libcublas -- they load the same runtime the host already has. So the
driver's advertised CUDA version is only an upper bound: a cuda13 bundle still
needs cuda13 runtime libraries present on disk. Port llama's on-disk runtime
scan (detected_linux_runtime_lines / detected_windows_runtime_lines) into the
shared core and intersect it with the driver-compatible lines in
select_cuda_attempts. A host with a cuda13 driver but only cuda12 runtime (e.g.
torch-cuda12) now correctly gets a cuda12 bundle instead of an unloadable cuda13
one; a host with no CUDA runtime at all falls back to CPU.
Fixes a glob bug in the port (any(Path(d).glob(p) for d in dirs) tests generator
truthiness, not a match) that made every major report present; add a real
filesystem test that exercises the scan.
* studio: harden shared prebuilt core to full llama parity
Apply the review findings on the shared coverage-aware prebuilt-consumer
core so whisper.cpp selection is exactly equivalent to the llama.cpp path.
hosts.py: port llama's CUDA_VISIBLE_DEVICES handling. A GPU hidden by an
index/UUID selector now reports has_usable_nvidia False instead of staying
usable, via supports_explicit_visible_device_matching plus the physical /
explicit-match branches, and _select_visible_rows now matches rows the way
llama does (index or UUID, gpu- prefix optional) and skips unmatched tokens
rather than keeping all rows. Adds the Linux /proc/driver/nvidia/gpus
fallback and has_physical_nvidia. Adds parse_macos_version.
runtime_libs.py: the Linux on-disk scan now requires the exact libcudart /
libcublas SONAME (libcudart.so.13), not a libcudart.so.13* glob, so a bare
versioned file without the SONAME symlink no longer counts as loadable.
Hardens the ldconfig parse against an empty left-hand side.
selection.py: fix the Blackwell/torch reordering so it keys on the covering
runtime lines (falls through to the torch preference when the covering lines
were filtered out), matching linux_cuda_choice_from_release. Corrects the
compatible_runtime_lines_for_driver docstring: the bundles do not ship the
CUDA runtime, so the driver version is only an upper bound and the caller
must intersect with the on-disk scan.
install_whisper_prebuilt.py: enforce a macOS artifact's min_os (new
HostInfo.macos_version) so a bundle that cannot load on the host OS version
is dropped. Keep resolver stdout to only the JSON line by leaving logs on
stderr in --resolve-prebuilt mode, and map an unexpected probe failure to
prebuilt_available False instead of a traceback.
Tests: new host-probe suite for the visible-device logic, exact-SONAME
runtime-scan cases, macOS min_os filtering, resolver stdout-only-JSON,
exit-code mapping, and the repo key.
* studio: fix whisper prebuilt selection + launch parity gaps from review
A parallel review surfaced integration defects where the whisper path could
select or launch a bundle that cannot run on a concrete host. Each is fixed to
match install_llama_prebuilt.py.
macOS min_os: the manifest labels macOS requirements as macos-<version>
(e.g. macos-14.0), which the version parser could not read, so the guard was a
no-op and a macOS-13 host would install the macos-14 Metal bundle. Strip the
platform prefix before parsing.
ROCm gfx detection: _detect_rocm_gfx returned the first gfx token and ignored
HIP_VISIBLE_DEVICES / ROCR_VISIBLE_DEVICES / CUDA_VISIBLE_DEVICES. Since exact
ROCm matching treats that token as the active GPU, a mixed APU + dGPU host
(gfx1151 + gfx1100) with HIP_VISIBLE_DEVICES=1 installed the wrong archive. Route
through a shared pick_rocm_gfx_target (lifted from llama) that parses per-GPU
sections and honors the visibility vars (empty / -1 -> no AMD GPU).
--rocm-gfx override: recording the arch without setting has_rocm left the host on
its CUDA/CPU path so the ROCm bundle was never picked. --rocm-gfx now implies
has_rocm and clears NVIDIA state, like llama's _apply_host_overrides.
CUDA launch env: a CUDA bundle ships the ggml CUDA backend but not
libcudart/libcublas, and the sidecar launch env exposed only the bundle dir, so
on a host whose CUDA runtime lives only in the PyTorch wheels the selection would
gate cuda usable but the server could not load it. Add the CUDA-from-PyTorch
runtime dirs to the child loader path for CUDA bundles (bundle dir still first),
mirroring binary_env.
Also normalize a manifest artifact's supported_sms defensively (parity with
llama's parser) and document that blackwell_min_toolkit_for_caps is retained for
the Phase B llama Windows path.
Not changed (verified parity, not defects): Linux/Windows min_os is enforced
nowhere in llama (macOS only); the resolver is optimistic about the checksum
index and the install path verifies.
* studio: tighten prebuilt-core code comments
* studio: lift shared prebuilt installer core out of the whisper installer
* studio: reuse the llama.cpp prebuilt installer machinery for whisper
* studio: unify llama and whisper prebuilt installers on a shared descriptor core
* studio: consolidate prebuilt installer tests into the shared core suite
Grow tests/studio/install/test_prebuilt_core.py from 62 to 164 tests so every
component-agnostic behavior runs against both descriptors: the full seven
profile CUDA release matrix (multi-GPU, on-disk runtime gating, shuffle
stability, missing SM metadata, dotted SM normalization, no-driver fallback
policy), the ROCm gfx family matrix, macOS min_os gating and its helper,
backend resolution incl. cpu-fallback precedence and Intel-mac auto detect,
checksum-index non-object and plain-lookup cases, the tar symlink/hardlink
extraction guards moved from the llama suite, and the compute-cap, visible
device, runtime-line and Blackwell helper value tables moved verbatim from
the llama characterization suites.
Delete only tests whose exact behavior the master now asserts for the same
component: 40 pure-alias helper cases in test_selection_logic.py (replaced by
value-identical master tables plus an alias-identity pin), 6 extraction moves
and the master-absorbed zip-symlink case in the llama logic suite, 3 routing
twins in test_rocm_support.py already pinned byte-for-byte in
test_selection_logic.py, the 2 Blackwell helper tables in the backend resolve
suite, 28 whisper logic tests and 10 whisper checksum tests re-asserted by
the master whisper parameterization. Wrapper wiring pins, the llama release
plan dialect, fingerprints and every llama-only behavior stay untouched.
* studio: dedupe sidecar and update helpers into the backend prebuilt package
* studio: chain whisper.cpp prebuilt updates onto the llama.cpp update flow
* studio: consume paired slim whisper prebuilts via the llama ggml runtime
* studio: serve every whisper backend from slim prebuilts
* studio: drop the whisper fat per-accelerator selection chain
unslothai/whisper.cpp releases are slim-only from v1.9.1-unsloth.2: one
ggml-less bundle per os/arch, paired to the llama.cpp prebuilt that provides
every ggml backend. Delete the whisper-side fat CUDA/ROCm/metal/vulkan
selection glue; keep slim selection + pairing, link_ggml_runtime, and one
legacy shape, the published fat CPU bundle of an explicitly pinned pre-slim
release. Exit 2 now reads as prebuilt unavailable (whisper never source
builds); setup already treats it that way.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Wire libomp runtime DLL alongside ggml in slim whisper installs
llama's clang-built windows-arm64 ggml-base.dll imports
libomp140.aarch64.dll, shipped in the llama bundle but not a system DLL.
Without it next to whisper-server.exe the loader fails with
STATUS_DLL_NOT_FOUND before main. MSVC x64 links vcomp140.dll from
System32 and Linux ggml uses system libgomp.so.1, so only windows-arm64
was affected. The empty-runtime guard still requires a real ggml
library; libomp alone is not a pairing.
* studio: drop whisper-side fat-selection support structure
Slim whisper bundles are selected per os/arch only; all accelerator
capability comes from the installed llama.cpp prebuilt, whose installer
already did the coverage-aware selection. Remove the machinery that only
existed to pick among fat per-accelerator whisper bundles:
- prebuilt_core: delete the generic CUDA/ROCm coverage selection
(select_cuda_artifact, select_rocm_artifact, ArtifactView adapters,
detected_cuda_runtime_lines, the exact-SONAME linux probe) that no
shipped component routes through; llama keeps its own selection chain
and whisper shadows select_artifact with the slim-only version.
select_artifact is now a plain os/arch/backend first-match.
- install_whisper_prebuilt: drop the HostInfo CUDA fields
(compute_caps, driver_cuda_version, torch_runtime_line) and the torch
runtime probe that populated them; nothing reachable reads them, and
the resolver payload sources runtime_line from the artifact.
- whisper_cpp_update: delete the standalone start_update job worker;
whisper applies only run as the chained phase of the combined
llama+whisper update. The status payload keeps its job field (idle).
- routes/whisper: drop the progress logger that could never fire.
- tests: remove tests of the deleted paths and tests duplicating the
descriptor-parameterized core suite or the llama freshness suite.
Contracts unchanged: resolver JSON keys, exit codes, marker fields,
pairing logs, and the pinned pre-slim fat CPU escape hatch.
* Address review feedback on the whisper prebuilt update and install paths
- Pin the chained whisper phase to the release the freshness check
offered, so the download-host latest pointer cannot reinstall an
older build in a loop
- Wire the whisper prebuilt install into setup.ps1 (Windows setup
previously skipped it entirely)
- Treat a non-executable server or missing wired ggml libraries as a
broken install instead of reporting already matches
- Keep whisper sidecar reloads out of the job-level reload flag and
resync chat state after a partial chained update that unloaded llama
- Repoint home and profile vars for the whisper-server subprocess at a
managed scratch dir and drop credential-store pointers
- Clear the prebuilt marker before the opt-in source build overwrite
- Write the prebuilt marker with explicit utf-8 encoding
* Tighten comments in the whisper prebuilt consumer
* Harden the Windows whisper setup phase and the chained update edges
- setup.ps1: honor WHISPER_SERVER_PATH / UNSLOTH_WHISPER_CPP_PATH /
UNSLOTH_SKIP_WHISPER_INSTALL, run the custom-home ownership guard
before the atomic install, and forward the release-tag pin and ROCm
hints like setup.sh
- sidecar: a cpu-selected install launches whisper-server with --no-gpu
(slim wiring links every llama backend, so the flag is what keeps a
deliberate CPU choice off the GPU)
- chained update: leave whisper unpinned on macOS (the llama phase can
walk back there, and a newest-tag pin could be an impossible pairing
on every retry) and treat installer exit 2 as kept-existing-runtime
instead of failing the combined job
- job.to_tag now comes only from the llama phase, so a whisper-only
round cannot report a llama update that never ran
* Fix slim whisper runtime follow-ups
* Address remaining whisper update reviews
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address remaining prebuilt update reviews
* Fix remaining chained update reviews
* Fix remaining whisper runtime review edges
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: danielhanchen <unslothai@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: oobabooga <112222186+oobabooga@users.noreply.github.com>
---------
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Unsloth <michaelhan@Michaels-MacBook-Pro.local>
Co-authored-by: oobabooga <112222186+oobabooga@users.noreply.github.com>
Adds a configurable Hugging Face model download cache location to Unsloth Studio, selectable from Settings, with per-cache download manifests, scoped deletion, and read-only inventory of previously selected caches.
* Studio: mask AMD GPU pins via ROCR so an unsupported iGPU can't crash llama-server
On a mixed AMD host (e.g. a discrete gfx1102 GPU next to a gfx1103 iGPU)
the bundled rocm-gfx110X llama.cpp build segfaults during HSA device
enumeration on the unsupported iGPU -- before llama-server prints a line,
so every model load fails with a bare signal and empty logs.
The GPU-subset pin masked visibility with HIP_VISIBLE_DEVICES, but HIP
filtering runs only after the HSA runtime has already enumerated (and
crashed on) every agent. Mask the subset via ROCR_VISIBLE_DEVICES (the
ROCr/HSA layer) instead, so a deselected/unsupported GPU is never
enumerated. Exactly one layer is masked (HIP cleared) to avoid the
double-mask reindex that would otherwise drop the child to CPU. The
whole-set tensor-split path and the CPU-only sentinel keep their existing
HIP behavior.
Also stop misreporting the resulting startup segfault as a vision
projector incompatibility: when the text-only mmproj retry also hard-
crashes with a signal, surface a GPU/driver init crash (with the ROCR
hint) instead of blaming the projector.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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* Tighten _emit_child_gpu_visibility comments for #7272
Comment and docstring only: condense the ROCR-vs-HIP masking rationale from ~22 to ~14 lines and the call-site note from 5 to 3, keeping every technical point (HSA enumeration segfault, physical ids, the -1 sentinel). Logic is unchanged, verified by an AST compare with docstrings stripped and by exercising _emit_child_gpu_visibility against a torch/HIP stub.
* Detect AMD SDK ROCm wheels (hip=None) in _emit_child_gpu_visibility (Codex P2)
The ROCm branch gated only on torch.version.hip, but AMD SDK wheels leave that unset while encoding 'rocm' in __version__ (detect_hardware handles this the same way). On such a wheel the masking was skipped entirely, leaving only CUDA_VISIBLE_DEVICES, so on a mixed AMD box the unsupported deselected iGPU still enumerated and could crash llama-server. Now the branch also treats 'rocm' in torch.__version__ as ROCm, mirroring detect_hardware. Adds tests for the hip=None SDK wheel (ROCR + default paths) and a CUDA guard so the version-string check can't false-positive.
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* Remap CUDA_VISIBLE_DEVICES to post-ROCR ordinals on prefer_rocr for PR #7272 (Codex P1)
On the prefer_rocr path _emit_child_gpu_visibility set ROCR_VISIBLE_DEVICES to the
physical id and cleared HIP_VISIBLE_DEVICES, but left CUDA_VISIBLE_DEVICES at the
physical id. ROCR re-indexes the visible agents from 0 and, with HIP cleared, HIP
honours CUDA_VISIBLE_DEVICES -- so a non-zero pick (e.g. GPU 1) pointed out of
range, HIP saw 0 devices, and the child fell back to CPU, defeating GPU-picker
selections other than physical GPU 0. Remap CUDA to the post-ROCR ordinals
(0..N-1); GPU 0 is unchanged, the default (HIP) path and the CPU sentinel are
untouched, and non-AMD wheels never enter this branch.
* Detect AMD SDK wheels in _resolve_visible_physical_ids for PR #7272 (Codex P2)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Keep the HIP mask on Windows ROCm in prefer_rocr for PR #7272 (Codex P2)
* Ignore ROCR_VISIBLE_DEVICES in _resolve_visible_physical_ids on Windows for PR #7272 (Codex P2)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Preserve inherited ROCR masks in the tensor-split pin for PR #7272 (Codex P2)
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Leo Borcherding <borchborchmail@gmail.com>
* studio: classify embedding models from the HF cache and honor offline mode
is_embedding_model() went straight to huggingface_hub.model_info() for any repo
id, so in offline mode (no DNS, or HF_HUB_OFFLINE set) selecting an
already-downloaded model hung on network retries that could never succeed and
training/export never started (#6817).
Check the local HF cache first: a sentence-transformers repo carries
modules.json in its snapshot (the same marker used for local paths), so a cached
model is classified with no network call. When HF_HUB_OFFLINE / TRANSFORMERS_OFFLINE
is set, anything not positively an embedding model returns False without a
network call instead of retrying a doomed request. Online, uncached lookups still
fall through to model_info(), so tag-only embedding models (feature-extraction)
are unaffected.
Adds _embedding_marker_in_hf_cache() over the existing _iter_hf_cache_snapshots.
* studio: judge the active cached revision, harden the cache probe, stop stub leaks
Three review fixes on the cache-first embedding detection:
1. Prefer the revision refs/main resolves to. The HF cache keeps snapshots of
older revisions, so an any-snapshot scan could classify a repo by a stale
revision -- e.g. a repo that used to be a sentence-transformers model would
short-circuit even the online lookup. When refs/main is recorded, only its
snapshot is consulted; the newest-first scan remains the fallback for caches
with no ref.
2. Keep the cache probe inside the detection error boundary. The snapshot
iterator stat()s entries and could raise if a cached model is deleted
concurrently, propagating a 500 out of the config/check-embedding routes.
_embedding_marker_in_hf_cache now catches everything and reads as
not-cached, so callers keep their normal Hub/offline fallback.
3. Stub loggers/structlog in the test only when the real modules are absent
(try-import, mirroring test_windows_gpu_detection_mock), so collecting this
file first can no longer shadow the real packages for later tests in the
same pytest process.
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* studio: treat a missing active-ref snapshot as a cache miss, don't cache offline misses
Two review fixes on the cache-first embedding detection:
1. When refs/main is recorded but points at a commit whose snapshot dir is
absent (partial download / cache pruning), the recorded ref is still
authoritative: return None (cache miss) instead of falling through to scan
older snapshots, which could report a stale historical revision's
modules.json as the active one -- the same stale-cache class this helper
avoids.
2. Do not cache the offline negative. When HF_HUB_OFFLINE/TRANSFORMERS_OFFLINE
is set and the repo is not positively an ST model from modules.json,
is_embedding_model stored False under the (model_name, hf_token) key shared
with online lookups; after the env var cleared in the same process, a
tag-only (feature-extraction) embedder returned the cached False and never
reached model_info(). The offline negative is now returned without caching.
* studio: defer online embedding detection to the Hub, re-probe offline
The local modules.json marker short-circuited is_embedding_model() even
online, so a repo that dropped (or added) the marker since it was cached
was judged by its stale local revision instead of the current remote one.
Online now treats model_info() as authoritative and uses the cache marker
only as an uncached fallback when the Hub is unreachable, so a transient
failure never poisons the memo. Offline re-probes the marker on every call
without consulting or populating the memo, so a model downloaded later in
the session (or a cached online negative that predates the download) is
detected. _embedding_marker_in_hf_cache() now treats an unreadable refs/main
(a non-FileNotFoundError OSError) as a cache miss rather than scanning stale
history -- only a genuinely missing ref enables the fallback scan.
* studio: harden offline embedding detection against empty refs, offline flips, and cache casing
- _embedding_marker_in_hf_cache: an existing-but-empty/whitespace refs/main
(a partial write or in-progress truncate-and-rewrite) now reads as a cache
miss (None) instead of falling through to scan stale snapshots; only a
genuinely missing ref enables the historical scan.
- is_embedding_model: while offline, retain a positive already confirmed online
this session (model_info only ever memoizes Hub-derived results), so
_hf_offline_if_dns_dead() flipping the process to offline mid-load can't
downgrade a verified tag-only embedder to False. Cached negatives are still
bypassed and re-probed.
- resolve_cached_repo_casing + settings route: persist the embedding model in
the casing its local HF cache dir uses. Validation accepts a case-insensitive
cache hit, but an offline SentenceTransformer load resolves the cache by exact
case, so storing the requested spelling (baai/bge-m3 vs models--BAAI--bge-m3)
made the model fail to load on a case-sensitive filesystem.
* studio: reuse the exact-match-first case resolver and preserve the default
Replace the ad-hoc resolve_cached_repo_casing with the existing
resolve_cached_repo_id_case, which already prefers the exact-case cache dir
before any case variant and tie-breaks variants deterministically -- so an
exact requested id is never rewritten to a differently cased directory just
because iterdir() happened to yield it first.
Skip the normalization entirely when the submitted model equals the default:
rewriting its casing would make set_rag_embedding_model()'s exact-string
default comparison treat it as a custom override, pinning it so later changes
to the configured default stop taking effect.
* studio: don't let a stale cache marker mask a permanent Hub error
is_embedding_model's Hub-failure fallback consulted the local modules.json
marker for ANY model_info() exception, so a permanent error -- a deleted repo,
a gated repo without credentials, or a typo that matches stale cache casing --
could pass online validation on a stale marker instead of returning the
documented 409, and the persisted model could then fail when the loader
refreshes from the Hub. Classify permanent Hub errors (RepositoryNotFound,
GatedRepo, RevisionNotFound, EntryNotFound) as False, matching the nearby
GGUF/vision detectors, and reserve the cache fallback for transient/5xx failures.
* studio: honor TRANSFORMERS_OFFLINE in the embedding preflight, skip casing for local paths
- The embedding-model save reached the offline-aware is_embedding_model() only
after two preflight helpers made direct huggingface_hub calls that honor just
HF_HUB_OFFLINE: _st_module_subdirs() downloads modules.json and the security
scan fetches Hub metadata twice. In a TRANSFORMERS_OFFLINE-only session those
blocked on network timeouts before the offline return, so saving an already
cached model stalled. Both now consult a canonical hf_env_offline() helper --
the download passes local_files_only, and the metadata-only security scan
short-circuits to its documented fail-open instead of burning both timeouts.
- Skip cache-casing normalization for local paths: a relative directory such as
"org/model" is loaded from disk, so rewriting it to a case-insensitive HF
cache collision ("Org/model") would stop resolving to that directory and be
read as a Hub repo id instead.
* studio: never skip the security scan on TRANSFORMERS_OFFLINE alone
The previous commit skipped the Hub security scan whenever either offline flag
was set, but huggingface_hub honors only HF_HUB_OFFLINE: under a
TRANSFORMERS_OFFLINE-only session the later SentenceTransformer load still
reaches the network, so the scan was being skipped while the repo's pickle could
still be downloaded and deserialized -- waving through exactly what
_guard_model_security exists to block.
Split the flags: hf_hub_offline() (HF_HUB_OFFLINE, the only one that actually
prevents a fetch) gates the security short-circuit, while hf_env_offline()
(either flag, the user's intent) is used only where local-only behavior is
forced explicitly. The SentenceTransformer load now passes local_files_only from
that intent, so TRANSFORMERS_OFFLINE genuinely stops the loader fetching instead
of merely being assumed to.
* studio: short-circuit the security preflight under either offline flag
With the loader now pinned to the local cache by local_files_only =
hf_env_offline(), a TRANSFORMERS_OFFLINE-only session can no longer fetch
anything -- yet the preflight still fell through to two model_info() attempts on
10s and 20s timeouts, stalling every save and load of an already-cached embedder
for half a minute before failing open anyway.
Skip the metadata-only scan whenever either flag is set. The scan's job is to
stop a poisoned pickle being downloaded and deserialized, and nothing can be
downloaded under that predicate; the residual case -- a model cached BEFORE it
was flagged -- is the same fail-open this function has always documented for an
unavailable scan, and is exactly what HF_HUB_OFFLINE already did.
That safety argument depends on every loader behind the gate honoring the same
predicate, so it is pinned as a test invariant instead of a comment: removing
local_files_only from the SentenceTransformer construction now fails the suite.
Drops the short-lived hf_hub_offline() helper, which no longer has a caller.
* studio: scope the offline scan bypass to callers that load local-only
The previous commit put the offline short-circuit inside _fetch_security_status,
which is the malware gate shared by every loader -- so TRANSFORMERS_OFFLINE=1
disabled it for all of them, while only the RAG embedder had been changed to
pass local_files_only. MLX inference (core/inference/worker.py -> FastMLXModel
.from_pretrained), training and export call from_pretrained with no local-only
argument, and huggingface_hub ignores that flag, so those paths could still
fetch and deserialize an unscanned model with the gate switched off.
The bypass is now an explicit local_only_load argument, defaulting to False, and
only the two RAG embedding callers -- whose loader is pinned to the local cache
by the same predicate -- opt in. Tests pin both halves: the shared gate must
still scan under either offline flag by default, and no other caller may pass
local_only_load without constraining its loader.
* studio: capture offline state once, and probe the ST cache root
Two holes in the offline embedding path:
- _get() read hf_env_offline() twice: once inside _guard_model_security and
again for local_files_only. _hf_offline_if_dns_dead() mutates the process-wide
offline vars and restores them on exit, so a concurrent load could see True in
the guard -- skipping the Hub malware scan -- and False by the time the
constructor ran, fetching and deserializing the unscanned repo and breaking
the very invariant that licenses the bypass. The value is now read once in
_get() and passed to both; _guard_model_security takes it as an argument
instead of re-deriving it.
- The cache probe searched only HF_HUB_CACHE. SentenceTransformer downloads into
SENTENCE_TRANSFORMERS_HOME when that is set, using the same
models--org--name/snapshots layout under a different root, so a model fully
present there looked uncached and was rejected with a 409 offline even though
the local-only loader could load it. Snapshot lookup now covers both roots.
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* studio: probe the cache the ST loader actually uses, and require it be loadable
Adding SENTENCE_TRANSFORMERS_HOME to the shared snapshot iterator was too broad
in one direction and too narrow in another:
- _get() builds SentenceTransformer with no cache_folder, so with ST_HOME set it
searches THAT root only, never the Hub cache. Probing the union let offline
validation pass on a repo cached only in the Hub cache, after which the loader
looked in ST_HOME and failed. The Sentence-Transformers probe now resolves to
exactly one root: ST_HOME when set, the Hub cache otherwise.
- The shared iterator is also used by the GGUF detectors, whose downloads go
through hf_hub_download with no cache_dir and therefore really do use the Hub
cache. It is back to Hub-cache-only so detection cannot pick a snapshot the
GGUF load will not find.
- Casing normalization ran through resolve_cached_repo_id_case, which scans the
Hub cache, so with ST_HOME set the requested spelling was persisted unchanged
and the exact-case offline load missed the differently cased directory that
detection had just accepted. It now resolves against the same roots detection
uses, exact match first.
- A snapshot carrying only modules.json no longer counts as cached: the online
security preflight downloads that single file itself, and a partial download
leaves it behind, so validation passed for a snapshot with no weights and the
first RAG load then failed. A hit now requires the marker plus a config and at
least one weight file.
* studio: thread the captured offline state into the module probe, fix the gate shard
- _st_module_subdirs() re-read the process env for its local_files_only. With
_hf_offline_if_dns_dead() flipping those vars from another thread, a load that
captured local_only=False could still force this probe local-only, get () back
because modules.json is not cached, and leave the scan with NO module load
roots -- a Hub-flagged pickle under 0_Transformer/ would then pass as an
unreferenced nested artifact while the loader fetched and deserialized it. It
now takes the captured predicate as an argument, and the settings route reads
the state once and uses that single value for both the probe and the scan.
- Skip ST-cache casing on the llama-server backend. Nothing there loads through
SentenceTransformer: the embedder derives a GGUF companion from the saved
spelling and fetches it from the HUB cache, so normalizing to an ST_HOME
spelling would point it at a repo _hf_gguf_backend_error() never validated
(BAAI/bge-m3-GGUF instead of the checked baai/bge-m3-GGUF).
- Fix the security-gate shard, which the signature change had broken: the direct
_guard_model_security / _st_module_subdirs callers now pass the new argument
(they were raising TypeError before reaching any assertion), and the casing
tests patch utils.models.resolve_st_cached_repo_id_case, which the route
actually calls, instead of the Hub-only resolver it no longer uses -- those
patches were being silently ignored.
* studio: accept only torch-loadable weights in the offline ST probe; fix re-export lint
_snapshot_is_loadable_st_model accepted a cached snapshot whose only weights
were .onnx (or .pt), but the RAG loader builds SentenceTransformer with the
default torch backend, so such a snapshot passed offline validation and then
failed on the first load, the exact validate-then-fail this helper exists to
prevent. Restrict _ST_WEIGHT_SUFFIXES to .safetensors and .bin and add a
regression test for an ONNX-only snapshot.
Also teach scripts/verify_import_hoist.py that names listed in a module-level
__all__ are uses, so the legitimately added resolve_st_cached_repo_id_case
re-export in utils/models/__init__.py no longer trips HOISTED-IMPORT-UNUSED.
Covered by two new self-test cases.
* studio: probe the exact repo dir and revision an offline load resolves
The cache probe modelled the cache loosely rather than modelling what
SentenceTransformer actually does with local_files_only=True:
- It merged snapshots across every case-variant repo dir and then read refs/main
from whichever held the newest one. With both models--baai--bge-m3 and
models--BAAI--bge-m3 present, a complete embedding snapshot in the directory
the loader opens could be judged by a newer partial snapshot in the other,
failing validation for a usable model. It now selects the ONE directory the
loader opens, by the same exact-case-first rule resolve_st_cached_repo_id_case
uses to choose the spelling that gets persisted.
- It fell back to scanning historical snapshots when refs/main was absent. With
local_files_only the default revision is resolved THROUGH that ref, so a
snapshot directory alone is not discoverable: the settings request succeeded
and the loader then failed at first indexing. A missing, empty or unreadable
ref is now a cache miss, and the historical scan is gone.
The tests exercise the real lookup against a built cache tree instead of
patching the snapshot iterator, so they now cover the directory selection and
ref resolution the loader depends on.
* studio: record refs/main in the ONNX-only probe test
The ONNX-only regression test predates the refs/main requirement, so after that
change it returned None (a cache miss for want of a ref) before ever reaching
the weight-format check it exists to make. Recording the ref restores its
intent: the snapshot resolves, and the answer is False because an ONNX export is
not loadable by the RAG loader's default Torch backend.
* studio: recognize base-model weight files and gate the offline positive on a materialized snapshot
_snapshot_is_loadable_st_model matched any .safetensors/.bin by suffix, so a
partial cache carrying only a commonly published non-weight bin such as
training_args.bin (or an adapter-only artifact) passed offline validation and
then failed the local_files_only load at first indexing. Match recognized Torch
base-model weight filenames (model / pytorch_model, including sharded) by name.
is_embedding_model retained an online-confirmed positive offline even when no
files were cached, so a metadata-only /check-embedding result let an uncached
repo be saved and then fail at first indexing. Retain the positive only when the
active revision is materialized locally, which still covers a downloaded tag-only
embedder whose snapshot carries no modules.json.
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* studio: require a complete weight set offline and persist embedder verdicts across restarts
Two follow-ups to the offline embedding-model classifier:
- _snapshot_is_loadable_st_model now requires a COMPLETE Torch base-model
weight set in one snapshot directory, not just any single recognized weight
file. A partially downloaded sharded model (model-00001-of-00002 without its
sibling) no longer passes offline validation and then fails at first indexing
under local_files_only. Weight files are grouped by directory and a directory
counts only when it holds a single model.safetensors / pytorch_model.bin or a
full shard set whose indices cover 1..total.
- Online-confirmed embedder verdicts are now recorded under the resolved Studio
home (embedding_verdicts.json). The session memo is lost on exit, so a
downloaded tag-only feature-extraction embedder (snapshot present but no
modules.json) was misclassified as non-embedding the first offline call after
a restart. The offline branch consults this durable allowlist in addition to
the memo, still gated on the active revision being materialized on disk, so an
uncached repo is never trusted. Writes are best-effort and only positive
verdicts are stored.
* studio: require complete weights (with shard index) and resolve default casing offline
Follow-ups to the offline embedding-model classifier from the latest review:
- Trust a recorded embedder verdict (session memo or persisted allowlist) offline
only when the active snapshot carries a COMPLETE, loadable weight set, not merely
that it is materialized. A partial download (config present, weights missing or an
incomplete shard set) makes _embedding_marker_in_hf_cache read False rather than
None, so the previous marker-is-not-None gate wrongly returned True and the
local_files_only load then failed. Split out _snapshot_has_complete_weights (config
plus complete weights, modules.json aside) and _active_snapshot_dir, and gate the
known-embedder positive on the weight set.
- Require a sharded checkpoint's index map (model.safetensors.index.json /
pytorch_model.bin.index.json) in addition to every shard before accepting it:
transformers discovers and wires shards through that index, so a complete shard set
without it fails the local-only load.
- Resolve the embedding model name to its exact cache casing in the RAG loader before
constructing SentenceTransformer. The settings route persists that spelling for a
custom override but deliberately leaves the configured default verbatim, so a
default whose casing differs from the cache dir would miss it and fail offline.
Resolving at load time covers the default too; a no-op for a local path or when
nothing case-matching is cached, and idempotent for an already-normalized override.
Adds regression tests for the partial-snapshot verdict, the missing shard index, and
the loader casing resolution; updates the offline-invariant source assertion to the
resolved-name variable.
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* studio: require a tokenizer, case-fold verdict ids, and serialize verdict writes
Three follow-ups to the offline embedding-model classifier from the latest review:
- _snapshot_has_complete_weights now also requires a tokenizer asset. A
SentenceTransformer Transformer module builds an AutoTokenizer, so a snapshot with
a complete weight set but no tokenizer.json / tokenizer_config.json / vocab still
fails the local_files_only load. The check is a permissive union over the common
fast-tokenizer, config, and WordPiece/BPE/SentencePiece assets, so an unusual but
valid layout is not rejected -- only a genuinely tokenizer-less partial download.
- The persisted embedder allowlist is now keyed case-insensitively. model_info() is
queried under the requested casing while the settings route saves the cache-resolved
casing, so an exact-string lookup missed the persisted positive after a restart
(baai/model recorded, BAAI/model looked up) and a loadable tag-only embedder was
rejected. Both persist and lookup case-fold the id.
- _persist_embedder serializes its read-modify-write under a lock and writes through a
per-thread temp file, so concurrent confirmations of different embedders no longer
drop each other's entry or collide on the temp path. Cross-process writers stay
best-effort (os.replace is atomic; a dropped verdict is only an optimization miss a
later online re-confirmation heals).
Adds regression tests for the missing-tokenizer reject, alternate tokenizer assets,
cross-casing verdict match, and concurrent verdict writes; updates the snapshot test
helpers to materialize a tokenizer alongside config and weights.
* studio: tighten comments in the offline embedding-model classifier
Comment-only pass over the PR's changed files. Collapse the long block
comments and docstrings around is_embedding_model, the cache-snapshot and
weight-completeness helpers, the embedder-verdict persistence, the offline
security gate, and the offline/casing tests to short one- or two-line forms.
Preserve the rationale (issue #6817, the local_files_only invariant, the
casing and weight-gate reasons) in far fewer words. No code changes.
* studio: drop redundant comments in the offline embedding-model classifier
Second comment-reduction pass over the offline embedding-model cache work:
delete comments and trailing notes that restate the adjacent code or an
assertion, and trim the remaining docstrings and rationale comments to their
load-bearing invariants. Comments and docstrings only; no code changes.
* studio: pin embedder verdicts to a revision, canonicalize default aliases
- A persisted verdict recorded that the Hub tagged ONE revision an embedder, but
was stored per repo. Once refs/main advanced to a complete but non-embedding
Transformer snapshot, the offline path still returned True: the settings route
accepted the updated model without force and RAG could silently load it as an
embedder. Verdicts now carry the commit they were confirmed at and are trusted
only while the active revision matches. One confirmed before the repo was
cached has no revision to compare, so the first revision observed afterwards is
pinned then -- which is what lets a later advance be caught. The persisted file
gains a {id: commit} form and still reads the previous list format.
- tokenizer_config.json no longer counts as a tokenizer asset. It only DESCRIBES
a tokenizer, so a snapshot with config, weights and just that file passed
validation and then failed AutoTokenizer.from_pretrained(local_files_only=True)
at first indexing for common BERT/GPT-style models.
- A casing-only alias of the default is canonicalized to the default up front.
Repo ids are case-insensitive but every gate here compares exact strings, so
saving "Unsloth/bge-m3" against a default of "unsloth/bge-m3" ran the
verification and scan for a custom model and then persisted an override --
after which later changes to the configured default stopped applying.
- verify_import_hoist.py replays __all__ assignments in order instead of unioning
them. Only the final value exports anything, so a later plain "=" that drops a
name must leave its import counted as unused; "+=" still extends, and an
unreadable rebind keeps the earlier names rather than flagging real re-exports.
* studio: validate the real ST load root, and pin verdicts to the Hub revision
Four ways the offline probe still disagreed with what the loader does:
- Verdicts were pinned to the LOCAL refs/main, but model_info() describes the
current HUB revision. With a stale cache the two differ, so an older snapshot
nobody verified was allowlisted. The pin is now info.sha, taken from the
ModelInfo that produced the positive. A verdict carrying no revision (a legacy
entry) is no longer trusted at all -- trusting it meant pinning whatever
happened to be cached, which is the same bug; the next online check re-records
it properly.
- config, tokenizer and weights had to exist somewhere in the snapshot, not
together. modules.json can send SentenceTransformer at 0_Transformer/, which is
loaded FROM that directory, so a cache with the config at the root and only
0_Transformer/model.safetensors passed and then failed the local-only load.
Each directory is now checked as a complete load root, which covers both the
plain HF layout and the ST module layout.
- vocab.json and merges.txt counted independently, but BPE needs the pair unless
a serialized tokenizer.json is present, so half a pair validated and then
failed AutoTokenizer.from_pretrained(local_files_only=True).
- A slashless short name like all-MiniLM-L6-v2 is a supported ST alias that the
loader resolves through the sentence-transformers/ organization, so its
snapshot is cached under that full id. Probing only the bare name reported a
miss and 409'd a model that was cached and loadable; the bare id is still tried
first, matching the loader's own order.
* studio: fail closed for an offline security scan instead of failing open
A local_only (offline) load cannot fetch Hugging Face's malware scan, and the previous
behaviour skipped the scan and failed OPEN, so a cached repo with a poisoned pickle weight
could deserialize under SentenceTransformer(local_files_only=True). Evaluate it fail-CLOSED
against the cached files instead: block a base-model pickle weight the load would deserialize
(pytorch_model.bin and its shards, in a directory with no safetensors alternative) and allow a
pickle-free (safetensors / gguf are inert) cache. A cached pickle model must be reloaded online
once to be scanned, or shipped as safetensors. Nothing cached is not a security event.
_fetch_security_status no longer needs the local_only_load skip (the offline branch is handled
in evaluate_file_security). Adds a regression test covering the safetensors-allow and
pickle-block paths with no Hub call.
* studio: only suppress an offline pickle when a loadable safetensors weight exists
The offline security gate treated any .safetensors in a directory as covering a
pickle weight, so a cache with pytorch_model.bin beside a bare adapter_model.safetensors
(or an orphan shard with no index) passed the fail-closed check even though
from_pretrained still selects and deserializes the pickle. Require a genuinely loadable
safetensors weight -- an unsharded base file or a complete indexed shard set -- before
treating the pickle as covered.
Also make the import-hoist analyzer preserve uncertainty when __all__ is extended by a
value it cannot read statically (__all__ += dynamic()), matching how it already handles
an unreadable rebind, so a dynamically-supplied re-export is not flagged HOISTED-IMPORT-UNUSED.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: scope the offline pickle scan to load paths; reset __all__ opacity on rebind
Address three review follow-ups on the offline security gate and the import-hoist analyzer:
- The offline pickle scan walked the whole snapshot, so a stray pickle in a non-load
subdirectory (archive/, nemo/) that SentenceTransformer never deserializes was blocked.
Scope it to real from_pretrained load roots -- the snapshot root, or a subdir that holds
its own config.json -- matching the online scan's load-path scoping.
- _collect_dunder_all kept a sticky opaque flag: a readable replacing assignment after an
unreadable extend (__all__ += dynamic(); __all__ = []) still credited every import, so a
genuinely unused hoist went unreported. A replacing assignment now resets opacity.
- A bare __all__: list[str] annotation has no runtime value; it was treated as an unreadable
assignment and marked the export set opaque. Skip annotation-only declarations.
* studio: recase slashless ST aliases and accept a pinned embedder after a transient failure
Two offline-detection gaps on well-formed input:
- resolve_st_cached_repo_id_case bailed on every slashless name, so a differently-cased
short alias (all-minilm-l6-v2) validated case-insensitively but was loaded verbatim; the
SentenceTransformer loader rewrites it to sentence-transformers/all-minilm-l6-v2 and looks
it up case-sensitively, missing the canonical sentence-transformers/all-MiniLM-L6-v2 cache
dir. Resolve through _st_cache_repo_dir, which follows the same org alias, and hand back the
on-disk casing.
- On a transient (non-permanent) Hub failure, is_embedding_model only accepted a cached
modules.json marker, so a downloaded tag-only embedder (no modules.json) with a verdict
pinned to the active revision was rejected even though the offline branch accepts the
identical cache. Mirror the offline branch's pinned-verdict acceptance.
* studio: scan modules.json-declared module roots in the offline pickle gate
The offline pickle scan treated only the snapshot root and config.json-bearing subdirs as
load roots, so a pickle in a non-Transformer SentenceTransformer module directory that has no
config.json (e.g. a 0_WordEmbeddings/ module: wordembedding_config.json + pytorch_model.bin)
was skipped even though the loader deserializes it. Parse modules.json (and thread through
load_subdirs) to treat every declared module directory as a load root, so such a pickle is
scanned and fail-closed offline.
* studio: classify cached non-Transformer SentenceTransformer models offline
_snapshot_has_complete_weights recognized only a Transformer-shaped load root (config +
tokenizer + weights co-located), so a fully-cached model built from a non-Transformer module
(0_WordEmbeddings uses wordembedding_config.json + embedding weights and its own tokenizer, no
HF config.json; BoW keeps its vocab in config.json) was classified non-embedding offline and
the settings endpoint returned 409.
Add _snapshot_modules_all_loadable, which parses modules.json and accepts a snapshot when every
declared module's path directory carries the files that module class's own load() reads (a
Transformer/root module still needs the full HF load root; a WordEmbeddings module needs its
config plus a complete weight set; other modules need their *_config.json), and at least one
embedding-producing module is present. It is OR-ed after the Transformer check, so it only ever
accepts more and cannot regress the existing path or reject a pruned cache.
* studio: scan PEFT adapter pickle weights in the offline security gate
from_pretrained auto-detects an adapter_config.json in the load root and deserializes the
adapter weights on top of the base model, so adapter_model.bin is a separate pickle RCE vector
that a safetensors base weight does not cover. The offline scan matched only base-model pickle
names, so an offline local-only load with safetensors base weights plus a cached
adapter_model.bin was allowed despite the live adapter pickle. Scan adapter pickles too, scoped
to a load root where adapter_config.json is present and no adapter_model.safetensors exists.
* studio: require weights for Dense/CNN/LSTM SentenceTransformer modules offline
_module_dir_is_loadable accepted a Dense, CNN, or LSTM module dir with only its config, but
those modules' load() hard-load model.safetensors else pytorch_model.bin (verified against
sentence-transformers source: no fallback, raises if neither exists) -- exactly like
WordEmbeddings. A cache with such a module's config but no weights would validate and then
fail the local_files_only load. Require a complete weight set for every weighted module, not
just WordEmbeddings.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: scan root-index subdir pickle shards offline; handle __all__.append/.extend
- The offline pickle scan followed only load-root directories, so a shard mapped by a root
pytorch_model.bin.index.json into a non-root subdirectory was skipped even though
from_pretrained follows the index weight_map and deserializes it (a layout an attacker can
craft to evade the scanner). Read the local index and scan its referenced pickle shards,
covered by a loadable base safetensors at the index root -- mirroring the online scan.
- The import-hoist analyzer ignored __all__.append("X") / __all__.extend([...]) runtime
re-export mutators, so an import added solely for one tripped HOISTED-IMPORT-UNUSED. Read
their string args like +=, and treat any other __all__ method call as opaque.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: classify StaticEmbedding offline, require WordEmbeddings tokenizer, bound model_info
- A StaticEmbedding module (e.g. sentence-transformers/static-retrieval-mrl-en-v1's
0_StaticEmbedding/) holds tokenizer.json + weights and NO config, so the config-gated
non-Transformer path 409'd it offline. Recognize it by what StaticEmbedding.load() reads: a
tokenizer.json plus a complete Torch weight set.
- WordEmbeddings.load() rebuilds its tokenizer via the configured tokenizer_class.load() from the
module dir, so a WordEmbeddings module now also requires a tokenizer artifact
(whitespacetokenizer_config.json / phrasetokenizer_config.json, or a shared HF tokenizer asset),
not just its config + weights.
- With neither offline env var set, an unbounded model_info() could hang on connect/DNS retries
for networkless users (the #6817 symptom). Bound it with a 15s timeout so a dead network fails
fast and the existing transient-failure cache fallback resolves a cached model, while a
reachable Hub still wins. (Documented caveat: a stalled DNS getaddrinfo may exceed this.)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Resolve indexed safetensors shards relative to their index
_safetensors_index_complete compared shard basenames against the flat
set of files in the index directory, so an index whose weight_map names
shards in a subdirectory was treated as incomplete whenever a legacy
pytorch_model.bin sat beside it. That falsely blocked a snapshot whose
pickle weights are fully covered by a complete, loadable safetensors
shard set. Resolve each shard path relative to the index directory
instead, and add a regression test for the subdir-mapped shard case.
* Restrict offline weight-completeness check to declared load roots
_snapshot_has_complete_weights scanned every directory in a snapshot and
accepted it when ANY directory was a complete Transformer load root. When
modules.json is present a SentenceTransformer load only opens the declared
module paths, so a snapshot whose declared modules are incomplete but which
happens to contain an unrelated complete directory was accepted offline and
then failed at the first local_files_only load. Restrict the candidate
directories to the roots a load actually opens: the snapshot root plus each
modules.json module path. For a well-formed snapshot the verdict is
unchanged; only a complete directory at an undeclared path no longer vouches
for an otherwise-incomplete snapshot.
* Scan SentenceTransformer Router child module weights offline
A Router (legacy Asym) snapshot declares its child sub-modules only in
router_config.json, not the top-level modules.json, and Router.load()
deserializes each child's weights from its own subdir. A config.json-less
child such as query_0_WordEmbeddings (wordembedding_config.json plus a
pickle pytorch_model.bin loaded via torch.load) was therefore neither a
modules.json-declared load root nor a config.json-bearing dir, so the
offline gate skipped its pickle even though the loader deserializes it.
Parse router_config.json at each load root and treat every declared child
subdir as a load root (bounded BFS, so nested routers are covered), so
those child pickles are scanned. Add Router regression tests: a pickle
child blocks, a safetensors child is allowed, and a Router in a declared
subfolder is followed.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Do not treat an unreferenced config subdir as an offline load root
The offline pickle gate skipped a directory only when it was neither a
declared load root nor held a config.json. Because _st_load_roots already
resolves every real load root (snapshot root, modules.json / load_subdirs
dirs, Router children), the config.json fallback only ever promoted an
UNREFERENCED subdir -- a nested checkpoint-500/ or archive/ that ships its
own config.json + pytorch_model.bin -- to a load root. from_pretrained
never descends into such a subdir and the online scan ignores the same
unindexed pickle, so offline mode wrongly blocked a model the loader reads
from a clean safetensors root. Scope the pickle to directory in roots
only, and add a regression test (a stray checkpoint-500/ no longer blocks;
a modules.json-declared module dir still does).
* Classify a root Router (Asym) model as loadable offline
_module_dir_is_loadable applied Transformer root requirements (config +
tokenizer + weights) to every root module, so a Router saved at the
snapshot root -- which carries only modules.json + router_config.json and
loads its weights from child subdirs -- was classified not loadable
offline, and is_embedding_model missed a cached Router embedder. Dispatch
on the module class before the root Transformer fallback: a Router/Asym
dir is loadable when router_config.json parses and every declared child
subdir is loadable (validated recursively through _module_dir_is_loadable,
so nested routers and every child type are covered) with at least one
embedding-producing child. This also tightens a non-root Router, which
previously validated on the mere presence of router_config.json without
checking its children. Add Router regression tests (root and declared
subfolder, complete and incomplete-child).
* Require every declared module before accepting an offline cache
_snapshot_is_loadable_st_model returned has_complete_weights OR
modules_all_loadable, so a complete 0_Transformer short-circuited the or
and vouched for the whole snapshot even when a declared sibling module was
missing its serialized weights; SentenceTransformer builds every module in
modules.json, so that snapshot passed offline validation and then failed
the local-only load. When modules.json declares a non-empty list it is now
authoritative (modules_all_loadable validates every declared module);
has_complete_weights stays the fallback only for an empty/non-list
modules.json (the plain from_pretrained root). Also add the weight-bearing
modules whose load() hard-loads via load_torch_weights and previously fell
to the config-only path -- LayerNorm, WeightedLayerPooling, SparseAutoEncoder
-- to _ST_WEIGHTED_MODULE_NAMES, with source citations and the deliberate
exclusions (Pooling/Normalize/BoW/WordWeights read no weights on load).
Add parametrized regression tests over LayerNorm/WeightedLayerPooling/Dense
(a weightless sibling rejects, a complete sibling accepts).
* Reject self-referential Router children instead of recursing forever
_router_dir_is_loadable validates each router_config.json child through
_module_dir_is_loadable, which re-enters _router_dir_is_loadable for a
Router child. A malformed types entry naming the router's own directory
(a key of ".", which normalizes to the same dir) made that recursion
never descend, so it looped until RecursionError -- breaking the
documented never-raises contract and turning a crafted/corrupted cached
model into a 500 from is_embedding_model instead of a graceful
unverifiable result. A real child reference is a subdir and always
resolves deeper, so reject any child whose resolved path is the router
dir itself. Add a regression test (a router_config naming "." as a
Router child returns False without raising).
* Treat a destructuring __all__ assignment as opaque
_collect_dunder_all detected __all__ only as a direct ast.Name assignment
target, so a binding through a destructuring target (__all__, meta = [...],
v -> an ast.Tuple) was skipped entirely, leaving an empty, non-opaque
export set. A newly hoisted import re-exported only through that assignment
was then falsely flagged HOISTED-IMPORT-UNUSED. Its value cannot be mapped
statically, so mark the export set opaque when __all__ is reached only
through a destructuring / item / attr target, matching how the collector
already handles other unreadable __all__ forms. Add a self-test case.
* Canonicalize declared module paths before scoping the offline pickle gate
A repo could declare a traversing module path such as 0/../evil in
modules.json (or a router_config child), which SentenceTransformer resolves
to evil/ and deserializes evil/pytorch_model.bin. _st_load_roots recorded
the raw snap/"0/../evil", which never equals the snap/evil that rglob
yields, so the offline pickle gate skipped that directory and a malicious
repo slipped a pickle past the newly added gate. Add _canonical_load_dir
to collapse ./ and ../ components lexically and reject an upward escape,
and route the modules.json paths, load_subdirs and router children through
it so the gate scopes the same normalized directory the loader opens. Add
regression tests for a traversing modules.json path and router child.
* Close offline embedding-classification completeness gaps
Five real offline misclassifications, each a false negative (the #6817 hang
recurs) or false positive (accepted then 409s at the local_files_only load).
Dispatch _module_dir_is_loadable on the module class before the root
Transformer fallback. A module with save_in_root=True (every InputModule:
WordEmbeddings, StaticEmbedding, SparseStaticEmbedding, Transformer, Router)
is saved at the snapshot root, so a root WordEmbeddings was wrongly held to
Transformer requirements (an HF tokenizer it never writes) and classified not
loadable.
CLIPModel is Transformer-shaped: CLIPModel.load() reads AutoModel weights plus
AutoProcessor, so a config-only CLIP dir must not validate.
SparseStaticEmbedding needs a tokenizer plus either idf.json or a complete
torch weight set (conditionally weight-bearing); a config alone is not enough.
A present but empty or malformed modules.json is not loadable and does not fall
back to a root Transformer: with modules.json present the loader never takes
the plain-Transformer path (base/model.py _load_config_modules). The tag-only
no-modules.json embedder is classified separately via
_snapshot_has_complete_weights.
Validate a sharded weight index against its weight_map (every mapped shard
present, resolved relative to the index dir) instead of trusting the index
file's mere existence, mirroring the security-side check.
Add regression tests for all five.
* Close case-folding and online-traversal holes in the offline pickle gate
Two gate bypasses where the security scan credited or scoped a path
differently from what the loader actually resolves:
The safetensors credit was case-folded. _cached_pickle_weight_files lowercases
every filename, and the loadable-safetensors and adapter checks tested those
folded keys against the exact-lowercase names. On a case-sensitive filesystem
(Linux, the Studio default) a crafted repo shipping Model.SafeTensors plus a
malicious pytorch_model.bin makes transformers and sentence-transformers miss
the exact-name model.safetensors and deserialize the pickle, while the gate
credited an inert safetensors and did not block. Credit safetensors
case-sensitively against real filenames, and drop pytorch_model.safetensors
from the credit set (transformers loads only model.safetensors, never that
name). Pickle matching stays case-insensitive (over-blocking a mis-cased
pickle the loader would not load is the safe direction).
The online scan did not canonicalize traversing paths while the offline gate
did. A repo-controlled modules.json path (threaded into the online scan via
the RAG guard) or a weight_map shard entry like 0/../evil / ../evil was
compared verbatim, so a flagged evil/pytorch_model.bin never matched and
evaded the online scan though the loader resolves and deserializes it.
Canonicalize the repo-controlled load-subdir prefixes and weight_map shards
the same way the offline gate does, so offline and online agree.
Add regression tests for both bypasses.
* Treat a conditional __all__ mutation as opaque in the import-hoist linter
_collect_dunder_all replayed only top-level module statements, so an __all__
assignment or mutation inside a module-level if / try / for / while / with /
match (or a deeper scope) was ignored, leaving the export set understated. A
newly hoisted import re-exported only through such a conditional __all__ was
then falsely flagged HOISTED-IMPORT-UNUSED, blocking a valid change. A
conditional value cannot be replayed statically, so mark the export set opaque
when __all__ is bound or mutated anywhere other than a top-level statement.
Add a self-test case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Scope Router child sub-modules as load roots in the online embedding scan
The RAG embedding security guard unions the SentenceTransformer module dirs
from modules.json into the load roots it scopes for the Hub scan, so a flagged
pickle directly under a Transformer module blocks. A Router (legacy Asym)
module declares its child sub-modules only in router_config.json, not in
modules.json, and Router.load() deserializes each child from its own subdir.
The online scan therefore dropped a flagged child pickle (for example
query_0_WordEmbeddings/pytorch_model.bin) as an unreferenced nested shard while
the loader still deserialized it, the counterpart to the offline gate which
already expands router children via _router_child_dirs.
_st_module_subdirs now reads router_config.json for any Router-typed module and
adds each declared child (joined onto the module path, canonicalized so a
traversing entry is dropped) to the load roots. The config is read only for a
Router-typed module, so a plain embedder pays no extra fetch, and every failure
path still returns () so the guard never bricks the embedder.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Allow a recorded-clean pickle embedder to load offline
The offline embedding security gate is fail-closed: with no network to reach
Hugging Face's scan, a cached pickle weight cannot be verified, so it is blocked
and a model the user already downloaded and used online will not load offline.
This adds a persistent cache of clean Hub verdicts so that exact content can load
offline, without weakening the gate for an unknown or never-scanned pickle.
When an embedding repo is loaded online and HF's scan returns a completed clean
verdict, the load roots are hashed and recorded under the scanned commit as an
exact map of snapshot-relative pickle name to sha256, in a per-user JSON store at
studio_root()/security/embedding_scan_verdicts.json (atomic write, 0600, thread
and cross-process locked, 30-day TTL). Offline, a cached pickle model loads only
when the active cached commit and every load-root pickle's sha256 match the
recorded verdict; a missing record, moved commit, changed or added pickle,
expired record, or any error keeps blocking. Online loads always re-query the
Hub and an authoritative unsafe verdict deletes any stale record, so a
now-flagged commit cannot keep loading on an old clean record.
The store binds repo id, full commit, and a per-file sha256 map so a locally
swapped pickle at the same commit, a branch advance, or an added load-relevant
pickle is detected. A same-user attacker who can rewrite the model cache or the
store is outside the enforceable boundary and this is documented; the sha256 is
computed just before load, so a narrow verify-to-load window remains, and a Hub
scanner false negative is recorded faithfully (safetensors stays the stronger
defense).
Recording is triggered post-load in the RAG embedder because the settings route
only validates and the pre-load guard runs before the constructor downloads;
recording is skipped when the loaded commit differs from the scanned commit. The
blocked-pickle enumerator now returns snapshot-relative Paths so two module dirs
that ship the same pickle basename are hashed and reported distinctly.
* Harden the embedding verdict cache against review findings
Tighten the offline verdict cache and its enumeration so every uncertain or
malformed input fails closed and the recorded hashes always match the files the
loader reads:
- Hash every case-colliding pickle in a load root, not one representative. On a
case-sensitive filesystem pytorch_model.bin and PYTORCH_MODEL.BIN are distinct
files; keying by lowered name dropped one and could hash a decoy instead of the
loader's target. The enumerator now returns every variant Path.
- Only persist a clean verdict for a COMPLETED, entirely-benign scan. Require
scansDone to be the boolean True (not a truthy string), filesWithIssues to be a
well-formed list, and every flagged file to be a definitively-safe level; a
pending, error, unknown, or malformed entry no longer records as clean. The
online block decision is unchanged.
- Fail closed when the offline cache cannot be inspected: an rglob error now
propagates and blocks instead of reading as pickle-free, and a snapshot that
errors on resolution (vs a clean not-cached) blocks. The offline guard also
raises instead of returning when its own inspection throws, so the constructor
never deserializes an unverified cached pickle.
- Expand online Router children recursively (bounded BFS with a seen set),
mirroring the offline load-root expansion, so a flagged grandchild pickle is
scoped online and cannot be recorded clean.
- Reject absolute and drive/UNC declared paths in the load-root canonicalizers;
the loader would resolve them outside the snapshot, so collapsing them to an
in-snapshot relative dir scoped the wrong place.
- Pin verdict recording to the scanned commit's snapshot and take the offline
verify commit from the snapshot directory name, removing a second refs/main read
and the skew it allowed.
- Drop the now-unused pickle-name wrapper.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Tighten offline embedding classification and the pickle gate
Close a set of offline edge cases where validation accepted a cache the
local_files_only load then rejects, and one gate bypass:
- Credit a sharded model.safetensors.index.json for a pickle sibling only at a
from_pretrained root. A non-Transformer SentenceTransformer module (Dense,
WordEmbeddings, StaticEmbedding) loads via Module.load_torch_weights, which
reads model.safetensors then pytorch_model.bin and never the index, so a sharded
safetensors index in such a module dir must not vouch for its pytorch_model.bin.
- Stop counting pytorch_model.safetensors as loadable in the offline classifier:
the loader probes model.safetensors (then its index) or pytorch_model.bin, never
pytorch_model.safetensors, matching the gate that already treats it as a decoy.
- Treat a present but unreadable weight index as incomplete: transformers opens
and parses any present index, so a malformed one or one without a weight_map
fails the load rather than falling back to filename-numbered shards.
- Require the CLIP image-processor config (preprocessor_config.json) for a CLIP
module: CLIPModel.load builds a CLIPProcessor that needs it, so a tokenizer
alone is not enough.
- Require a SparseStaticEmbedding config to actually select idf.json (a path
ending .json) or ship loadable weights; a bare idf.json the config does not name
falls through to load_torch_weights and raises.
- Do not use the tag-only recorded-verdict fallback when modules.json is present:
with the file present the loader takes the modules.json path, so a present but
empty or malformed manifest must not be validated as a plain root Transformer.
- Import-hoist linter: only a module-level conditional mutation or a function that
declares global __all__ makes the export set opaque; a __all__ bound as a local
in a nested function or class no longer masks a genuinely unused hoisted import.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Scope Router-child pickles to their deepest load root and gate the ST offline kwarg
The online scan stripped the first matching load-subdir prefix from a flagged file, so a
nested Router child pickle (0_Router/query_0_WordEmbeddings/pytorch_model.bin) matched the
parent 0_Router root, looked like an unreferenced nested shard, and slipped the gate even
though Router.load() deserializes that child directly. Match the deepest (longest) load
subdir instead, so the child becomes root-level under its own load root and blocks.
pyproject sets no lower bound on sentence-transformers and the local_files_only constructor
arg is absent on older releases, so always forwarding it broke every embedder warm on those
installs. Pass it only for an offline load; an online warm never forwards it and works as
before, while the offline capability still requires a version that supports it.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reject snapshot-escaping shard paths and credit Transformer submodule safetensors
The offline pickle enumerator joined a weight-index weight_map value straight to the load
root and followed it, so a repo-controlled index mapping "../.." into a sibling snapshot
made an offline from_pretrained deserialize an out-of-snapshot pickle, and an online load
would then hash and record that external file as the scanned commit's clean content. Reject
any shard path that escapes the snapshot root and fail closed, mirroring the canonical-root
check the online shard scan already applies.
A complete model.safetensors.index.json was credited over a sibling pickle only at the
snapshot root, but a Transformer module subdirectory (0_Transformer/) is loaded via
AutoModel.from_pretrained, which honors that shard set and never reads the pickle. Credit the
sharded index for Transformer-typed modules declared in modules.json so a cached model that
ships both a sharded safetensors checkpoint and an unused PyTorch checkpoint is no longer
falsely blocked offline. Non-Transformer modules (Dense, WordEmbeddings, StaticEmbedding) read
a flat weight with no index and keep their pickle blocked.
Limit the import-hoist verifier's global __all__ scan to the declaring function's own scope so
a nested inner-scope local __all__ no longer marks the module export set opaque and mask an
unused hoisted import.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Scope Router children against the snapshot and mirror the ST alias rewrite
Router.load resolves each child at Path(subfolder, model_id) relative to the Router dir, so a
nested 1_Router with a "../evil" child points at evil/ inside the snapshot and the loader
deserializes evil/pytorch_model.bin. The offline enumerator canonicalized the child against
the Router dir alone and dropped anything with "..", so that pickle was never scanned and the
gate reported the cache pickle-free. Canonicalize router children against the snapshot,
retaining in-snapshot siblings as load roots and failing closed on a child that escapes the
snapshot itself, matching the online scan which already joins the prefix before normalizing.
The security gate resolved a slashless model id by probing the bare cache dir first, but the
SentenceTransformer constructor rewrites a non-basic slashless name to sentence-transformers/
<name> and loads THAT snapshot (only the basic ORIGINAL_TRANSFORMER_MODELS load bare). With
both models--<name> and models--sentence-transformers--<name> cached, the gate inspected the
bare dir while the loader read the namespaced one, so a pickle there bypassed the local-only
gate. Mirror the constructor: try the namespaced candidate first for non-basic slashless names.
Add the same not (snapshot / modules.json).is_file() guard to the transient-Hub-failure
tag-only fallback that the offline branch already carries, so a cache whose present manifest is
empty or malformed is no longer reported as a loadable embedder.
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* Tighten root shard credit, module-path escapes, and weight-set probe order
Credit the sharded safetensors index at the snapshot ROOT only when the root is actually loaded
through an AutoModel/from_pretrained path. A modules.json root module of a non-Transformer type
(StaticEmbedding / WordEmbeddings / Dense) loads via load_torch_weights, which reads
pytorch_model.bin and ignores the index, so crediting a root shard index there suppressed a live
root pickle and let the offline gate report the cache pickle-free.
Recognize the Transformer subclasses CLIPModel and MLMTransformer as index-honoring load roots
(they load via from_pretrained), so a sharded-safetensors CLIP/MLM submodule with a legacy
pytorch_model.bin sibling is no longer falsely blocked offline. Mirrors the classifier dispatch.
Fail closed on an absolute or snapshot-escaping modules.json module path (or load_subdirs entry)
instead of silently dropping it: SentenceTransformer resolves such a path outside the snapshot and
would deserialize an external pytorch_model.bin the gate cannot scan.
On the classifier side, walk the weight set in the exact from_pretrained probe order
(model.safetensors, its index, pytorch_model.bin, its index) so a pickle behind a malformed
safetensors index is no longer accepted as complete, and restrict shard names to the loader-probed
stem/ext pairs so a decoy model-*.bin / pytorch_model-*.safetensors set is not treated as loadable.
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* Restore scripts/verify_import_hoist.py to main
The offline embedding cache fix does not depend on the __all__ scope
handling that had accumulated in this linter, so revert the file to its
main version and keep the PR focused on the feature. The feature modules
still pass the existing import hoist check unchanged.
* Reuse a shared HF cache skeleton in the offline classification tests
Extract _mk_repo and _activate helpers for the repeated snapshot cache
setup that every per-type builder duplicated, and fold the two
StaticEmbedding missing-asset cases into one parametrized test. Same 125
collected items, all still passing.
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* Reclassify embedding models from the cache on every offline call
is_embedding_model consulted its process memo before the offline branch, so an
online lookup that memoized True from tags (without caching any weights) was returned
unchanged once the session went offline -- the studio flips HF_HUB_OFFLINE in-process
on a dead DNS, and the ungated check-embedding route can populate the memo. Settings
would then accept a repo the offline loader cannot open. Run the offline
cache-marker reclassification ahead of the memo and never record it, so an offline
verdict always reflects the local cache and a later cache materialization is not
masked by a stale negative. Add regression tests.
* Tighten comments on the offline embedding path
Condense the offline-embedding helper docstrings and inline comments added in
this PR to fewer, clearer lines, keeping the non-obvious security and offline
rationale. Comments and docstrings only; no code change.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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* Studio: reuse MLX prompt cache across turns instead of re-prefilling
* clean up
* key prompt cache on what the KV covers
* skip windowed KV caches past their window
* verify prefix coverage before caching KV
* Recognize Radeon 8065S (Gorgon Halo / Ryzen AI Max 400) as gfx1151
* Classify Radeon 8065S (Gorgon Halo) as unified memory in ROCm OOM guard
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* studio: extend the _grouped_mm null-kernel guard to Linux ROCm RDNA4
torch._grouped_mm has a null HIP kernel on RDNA4 (gfx1200/gfx1201) at
ROCm <= 7.12 (fixed in 7.13; ROCm/TheRock #5284). The existing guard that
registers a Python mm/bmm fallback was win32-only, so Linux gfx1201 (e.g.
R9700 Pro on Ubuntu) hits the null kernel -> illegal instruction during
training.
Extract the fallback registration into a module-level helper
(_install_grouped_mm_cpu_fallback) and add a Linux branch that installs it,
gated on gfx1200/gfx1201 AND HIP < 7.13 so NVIDIA/CUDA and every non-RDNA4
AMD arch are untouched, and it is a no-op on fixed runtimes. The Windows
path now calls the same helper with identical behavior.
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* Resolve HIP version from torch.__version__ when version.hip is unset for PR #7292
AMD SDK / Radeon ROCm wheels leave torch.version.hip empty and encode the
version only in torch.__version__ (e.g. +rocm7.12). The Linux gfx120X guard
parsed version.hip only, so those affected installs skipped the fallback and
still hit the null _grouped_mm kernel. Mirror the Windows parse: version.hip,
then the embedded rocmX.Y, then assume affected unless a post-fix rocmsdk wheel.
* Scan all GPUs and add RDNA4 name fallback for _grouped_mm guard in PR #7292
* worker.py: tighten gfx120X Linux guard comments (no code change)
---------
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* fix(rocm): prepend system ROCm libs on native Linux to avoid bundled HIP crash
Prebuilt llama.cpp bundles ship their own ROCR/HIP runtime which can be
incompatible with the host's amdkfd kernel driver, causing hsa_init()
to crash or report zero devices. The llama-server then silently falls
back to CPU while the UI reports GPU.
The existing workaround (_wsl_system_rocm_lib_dirs) that prepends
/opt/rocm/lib to LD_LIBRARY_PATH was gated on WSL (/dev/dxg) only,
leaving native Linux AMD hosts unprotected.
This commit adds _native_linux_system_rocm_lib_dirs(), a parallel
helper gated on:
- Linux platform (not WSL)
- /dev/kfd present (bare-metal AMD compute)
- Bundle contains bundled HIP libs (libggml-hip.so)
- System has libhsa-runtime64.so(.1)
It is called from both _llama_server_env_for_binary (serve-time)
and binary_env (install-time validation), directly after the WSL
block in both paths.
Fixes#7208Fixes#7208
* Add UNSLOTH_LLAMA_NO_SYSTEM_ROCM opt-out to native-Linux system ROCm preference for PR #7233
Lets a host where the bundled runtime works but system ROCm is mismatched keep
the bundle. Mirrored in llama_cpp.py and install_llama_prebuilt.py.
* Prefer env-configured ROCm root over /opt/rocm fallback for PR #7233
Put HIP_PATH/HIP_PATH_57/ROCM_PATH-derived roots before /opt/rocm so a stale
/opt/rocm can't shadow the driver-matching install the env vars point at.
Mirrored in llama_cpp.py and install_llama_prebuilt.py.
* Match versioned libggml-hip.so via glob so the native-Linux ROCm fix fires for PR #7233
* Clarify native-Linux ROCm prepend uses the consistent system stack for PR #7233
* llama_cpp: tighten native-Linux ROCm prepend comments (no code change)
---------
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* Fix resume training crash recovery and MLX checkpoints
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* Address review: preserve interrupted stop-and-save output_dir, verify MLX checkpoint
- finish_run: add clear_output_dir flag; preserve output_dir for stopped/error
unless cancel explicitly clears it (fixes pump finalization wiping persisted path).
- training pump: pass interrupted stop-and-save context into finalize_run_in_db.
- MLX stop-and-save: verify resumable checkpoint exists before sending complete;
return bool from _write_mlx_stop_checkpoint and add regression tests.
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* Address Codex review: MLX current-step checkpoint and cancel error finalize
- Only skip MLX stop checkpoint write when checkpoint-{current_step} exists;
stale periodic checkpoints no longer mask missing stop saves.
- Pass clear_output_dir through error-event finalization so Stop-without-save
cannot leave a persisted output_dir that still offers Resume.
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* Address review
* Address more reviews
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* more reviews
* clear in-memory output_dir on interrupted cancel
* allow resuming errored runs at the final step
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* Clear persisted output_dir in cancel watchdog path
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Write MLX stop checkpoint in stop path, keep output_dir on crash finalize
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* fix(studio): harden resumable run finalization
* fix(studio): defer safetensors checkpoint import
* fix(studio): reject stale training cancellation
* fix(studio): replay null resume targets
* fix(studio): serialize terminal cancellation
* Harden resume checkpoint validation and fix stop-save cleanup
- Reject unrecognized shard formats and keep indexed shard paths inside the checkpoint dir
- Require a non-empty tensor record when validating .pt/.bin optimizer and model state
- Always finalize TensorBoard and W&B on stop-save-failure exits
- Refuse writing an MLX stop checkpoint through a symlinked directory
- Clarify the resume rejection message to cover errored runs
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* Tighten resume/checkpoint comments
* Recover resumability when a valid stop checkpoint landed
- Re-validate the current-step checkpoint in the dead-worker and error finalization paths so a stop-and-save that actually wrote a valid checkpoint is not wrongly marked error/resume_blocked
- Accept a valid tensor-free optimizer state (e.g. SGD without momentum); the model-state check still requires real tensors
- Include errored runs in the frontend resume rejection message
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---------
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Co-authored-by: Lyxot <longyixing331@gmail.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
* Studio (Windows): keep prompt caching on full GPU offload (#5692 follow-up)
The #5692 full-offload tuning also added --no-cache-prompt, which disables
in-VRAM prompt-prefix reuse. That is unrelated to the host-RAM KV checkpoints
#5692 fixed (--cache-ram 0 / --ctx-checkpoints 0): a fully offloaded model keeps
its KV cache in VRAM, so reusing a common prefix does not copy to system RAM and
does not cause the PCI-E overhead. --no-cache-prompt only forces every request to
re-prefill the whole prompt, which is small for short chats but severe for large
stable system prompts reused across calls (coding agents, long multi-turn chats).
Remove --no-cache-prompt; keep the checkpoint disables and the thread/OMP tuning.
_prompt_cache_disabled stays False (its default), so slot save/restore is intact.
Verified on a fully offloaded gemma GGUF: an identical repeated prompt reprefills
1 token instead of 2220.
* Guard against re-adding --no-cache-prompt to any llama-server command
Add a backend-wide test that AST-scans studio/backend and fails if
--no-cache-prompt is appended/extended/+= into a command. This locks in
the #7260 fix across every code path, not just load_model. Detecting the
flag or honouring a user-supplied one stays allowed.
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* Studio: make Stop and stall deadlines interrupt a wedged stream portably
The cancel watcher unblocks a stalled read by shutting the socket down from
another thread, which works on POSIX but not reliably on native Windows, where
Winsock does not dependably wake a recv() already in progress on another thread.
Wrap the httpcore network stream so the reader loops each read in short slices
and polls the cancel event itself. Stop and the stall deadlines now interrupt a
wedged mid-stream read without any cross-thread socket teardown, and a slow but
still-alive stream is never torn down. The POSIX shutdown path is preserved.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Honor the post-first-token stall timeout in the cancel-aware read
httpcore snapshots request.extensions timeout read once when the body
starts, so lowering it to the stall timeout after the first token never
reached the socket read and a one-token-then-silent server hung for the
full prefill window. Re-read the live extensions timeout per call and
bound each read by it, falling back to the httpcore-passed timeout when
absent so prefill and normal completion are unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: tighten comments in the llama.cpp stall timeout path
* Tighten comments in the stream stall cancel path
---------
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Co-authored-by: danielhanchen <unslothshared@gmail.com>
* Studio: Data settings tab, uploaded files manager, quant pinning, image preview fix
Settings
- New Data tab in the settings sidebar, under Connections. Chat data
management (archived chats, confirm before deleting, exports, import,
clear all) moved there from the Chat tab.
- New Archive all chats action with confirmation. Archives every chat in
Recents and Projects; compare pairs count as one chat.
- New Uploaded files manager listing RAG documents (chats, projects,
knowledge bases) and chat message attachments with location, size and
date. Files can be opened in a new tab or deleted. Deleting a chat
attachment keeps the message text.
Backend
- GET /api/rag/documents lists all uploaded RAG documents with file size
plus KB and project names.
- GET /api/chat/attachments lists chat message attachments; per
attachment file and delete endpoints included.
Model selector
- Downloaded GGUF quants can be pinned from the quant row (next to the
settings and delete actions). Pinned quants show at the top of On
Device under a Pinned heading as model name plus a grey quant chip and
load directly with one click. Non GGUF cached repos pin as a whole.
- Toned down the green of the downloaded label.
Fix
- Clicking an image attachment in chat now opens the preview overlay.
The tooltip trigger wrapper called preventDefault before composed
handlers ran, which made Radix DialogTrigger skip opening.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: image previews and file type chips in uploaded files list
Image attachments now show a small thumbnail (lazy loaded from the
stored bytes, object URL revoked on unmount) and every row shows a grey
uppercase type chip derived from the extension or content type. Non
image rows keep a file icon. Name cell floors its width and clips
overflow so narrow dialogs stay aligned.
* Harden attachment serving, add tests, and polish pinned rows and previews
- Strict base64 decoding for attachment files: corrupt payloads now return
422 instead of silently serving empty or garbled bytes; whitespace,
missing padding, the URL-safe alphabet, and RFC 2397 percent-encoded
data URLs are all handled
- New backend test suite covering attachment listing, size accounting,
malformed rows, deletion semantics, and every file-serving edge case
- Pinned quant rows show a Loaded tag when that exact quant is active,
and reveal unpin, settings, and delete actions on hover
- Uploaded files dialog is wider and chat locations link straight to the
thread the attachment belongs to
- Chat image preview is now a chrome-free lightbox: dimmed backdrop,
rounded image, corner close button, click outside to dismiss
- File opens go through a synchronous window.open so Safari and Firefox
popup blockers do not eat them
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Uploaded files: click a file to jump to its chat, square thumbs, new Data icon
- Clicking a file row (thumbnail or name) now goes straight to the chat it
belongs to; files without a chat open directly as before
- File thumbnails pin a small 7px radius: the theme scales rounded-md up
to a near circle at this size
- Settings Data tab now uses the database-setting icon
* Uploaded files is now a Data tab subpage instead of a popup
- Manage swaps the tab body for an inline Uploaded files page with a back
header, matching the rest of settings navigation
- Size column header and values are left aligned like the other columns
- Column widths tightened so the table fits the settings panel
* Lightbox polish and Data tab row order
- Image preview close button is transparent until hovered
- Preview image no longer rounds its corners
- Import chats now sits below Clear all chats in the Data tab
* Data tab: export chats as fine-tuning data and open them in Recipes
- New Fine-tuning section in Settings > Data converts every chat into a
JSONL dataset in the OpenAI messages format, one conversation per line
with string-only system/user/assistant turns
- The Train tab detects this file as chatml natively: no column mapping
and no standardization pass, and it works with train on completions
since every assistant turn sits behind the chat template response marker
- Consecutive same-role turns merge, trailing turns without an assistant
reply drop, and reasoning, tool calls, and images are excluded so chat
templates format the data cleanly
- Open in Recipes stages the JSONL as a local seed upload, creates a new
Data Recipe with the seed block preconfigured, and jumps to the editor
* Data tab: load chats straight into the Train tab, row moved to the top
- New Load in Train tab button uploads the fine-tuning JSONL through the
training dataset endpoint, selects it in the training config store, and
opens the Train tab with the dataset loaded and format-checked
- Use chats as training data now sits at the very top of the Data tab
- The Chats subheading is gone; chat rows flow directly under it
* Address review findings on the uploads manager and quant pins
- Deleting the last attachment stores '[]' instead of NULL: a NULL reads
back as a missing field and triggers the legacy IndexedDB backfill,
which resurrected the deleted attachment on the next chat load
- The attachment file endpoint now serves audio: adapter parts store
{data, format} raw base64 and compare chats store a bare base64 string;
media type comes from the attachment contentType or the format
- Compare-chat uploads live in message content parts, not attachments;
the uploads list now includes those blobs via synthetic content-part
ids that the same get and delete routes resolve
- Deleting a quant from the expanded repo row also unpins it so a pinned
row cannot try to load a file that no longer exists
- Thumbnails in the uploads list fetch their blob only once the row is
visible, so a long screenshot history does not download everything
- Nine new backend tests cover audio serving, content-part listing,
serving, deletion, and the empty-list delete behavior
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* Data tab: single action dropdown with format choices for chat training data
- The three fine-tune buttons collapse into one dropdown plus a run
button; pick Load in Train tab, Open in Recipes, or Export JSONL,
then click the arrow to run it
- The dropdown's Format section adds ShareGPT and Alpaca alongside the
default OpenAI messages format, ticked like a checklist; all three
shapes are auto-detected by the Train tab's format check
- Alpaca is single-turn, so each user to assistant pair becomes its own
record with the system prompt and earlier turns carried in the input
column
- Shorter description on the training data row
- Uploaded files rows show the size under the file name instead of a
separate column, matching the tighter layout
* Polish the training data action control
- Run button is a true circle (icon-sm plus rounded-full) with a
heavier arrow stroke
- Dropdown trigger uses the shared standard chevron and a fixed width
so switching actions no longer resizes the control
* Shorten the training data row description
* Use the standard chevron for the run button and enlarge the ticks
- Run button uses the shared standard right chevron so it matches the
dropdown chevron instead of the hugeicons arrow
- Dropdown ticks bumped up a size for legibility
* Reword the training data row description
* Shorten Data Recipes to Recipes in the training data description
* List Export JSONL first and rename the default format to Chat Completions
* Handle legacy string content in fine-tune exports and gate Train on chat-only hosts
- messageToPlainText now accepts plain-string message content, the shape
legacy and imported histories store, so those conversations export
instead of being skipped as having no exchange
- The Load in Train tab action is disabled on chat-only hosts the same
way the sidebar gates Train; the default action falls back to Export
JSONL there so the run button never uploads a dataset that /studio
would immediately redirect away from
* Narrow the training data action dropdown slightly
* Drop the format picker from the training data dropdown
Chat Completions (OpenAI messages) is the only export format we ship, so
the ShareGPT and Alpaca options and the Format section are removed. The
export always uses the OpenAI messages shape.
* Address the second round of review findings
Security
- Chat attachment data URLs no longer echo their embedded media type:
anything that is not a plain raster image serves as octet-stream, so
imported text/html or SVG payloads cannot render under the app origin
- Uploaded .html/.htm RAG documents serve as text/plain for the same
reason; the preview sheet only uses the file URL for PDFs
Uploads manager
- Remote image URLs in imported chats are no longer listed as stored
uploads (nothing to serve, and delete would strip the chat reference);
the delete guard mirrors the same data:-only rule
- Deleting a content-part upload refetches the list since the remaining
parts re-index, keeping sibling row ids current
- Deleting a project document from the Data tab invalidates the project
sources cache like the sources panel does
- Data-tab deletions now patch the loaded thread's in-memory copy via a
small event, so a later repo sync cannot write the attachment back
Fine-tune export
- Branch siblings from retries stay out of the exported conversation;
only the selected chain converts (full exports still keep everything)
- Assistant turns before the first user turn drop, preserving leading
system prompts, so no unconditioned assistant targets are emitted
Four new backend tests cover the media type clamp and remote-URL rows;
two existing tests updated for the clamped types
* Fix uploaded file lifecycle and model state
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Make archived chats a Data settings subpage
* Studio: fix attachment route tests and pinned quant edge cases
- test_chat_attachments: drop asyncio.run around the synchronous
/attachments routes (list/get/delete are plain def, so asyncio.run
raised 'a coroutine was expected' and failed the Repo tests CI job).
- test_chat_attachments: align compare-chat content-part assertions with
the stable content-hash id scheme (content-part-sha256-...) instead of
the removed array-index ids; resolve ids from the listing.
- pickers: pass disabled={deleteDisabled} to the pinned-quant delete
action so a quant cannot be deleted mid model-load, matching the
expanded variant rows.
- pickers: build the pinned-quant existence set from the query-unfiltered
cached GGUF repos (format filter still applied) so a pinned quant stays
findable when the search term matches only its quant name.
* Fix Studio review regressions
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* Guard fine-tune export content blocks
* Add Export button for archived chats
Adds an Export action to the Archived chats view in Settings > Data that
downloads only the archived chats as a JSON backup (their threads, messages
and projects). The button sits in the archived header row and appears only
when archived chats exist.
* Refactor archived export into pure, testable units
Split the archived-chats export into a dependency-free filter
(archived-chat-export.ts) and a shared JSON download helper
(download-json.ts). Skip the download when nothing is archived so a
stray call never drops an empty file. No behavior change to the button.
---------
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Co-authored-by: Unsloth <michaelhan@Michaels-MacBook-Pro.local>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* Fix text-only VLM CPT packing truncation
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* Handle streaming vision datasets in packing
* Harden multimodal packing detection
* Preserve safe packing boundaries
* Scope stream packing checks to VLMs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Narrow VLM packing detection
* Align packing mode and eval safety
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* Add qwen3_5/qwen3_next to PADDING_FREE_BLOCKLIST to avoid packed-sequence contamination
* Detect hybrid linear-attention models structurally instead of by name for packing guard
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* Install wrapped-packing setup at the signature, not the Zoo license comment
The _unsloth_wrapped_packing / _inspect setup block was injected by matching the
exact 'All Unsloth Zoo code licensed under LGPLv3' comment line in the sourced
sft_prepare_dataset. The unsloth_zoo dependency is only lower-bounded, so a newer
Zoo that moves or drops that header made the setup a silent no-op while the
truncation and pack_dataset rewrites still emitted references to those names,
raising NameError on every SFT dataset preparation.
Anchor the setup on the function signature instead (a structural location that
always exists) and fail loudly if it cannot be found, so the helper variables are
always defined before they are referenced across Zoo versions.
Adds a regression test that patches in a Zoo source without the license header.
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Co-authored-by: danielhanchen <danielhanchen@gmail.com>
* Studio: persist llama.cpp KV cache across idle auto-unload (slot save/restore)
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* Studio: address KV persistence review feedback
* Studio: guard KV restore on launch config
* Studio: fix KV resume purge race, fingerprint requested ctx, purge on disable
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: re-check idle/keep-KV settings after slot save, ns file identity
* Studio: shard-aware KV guard, honor user --no-cache-prompt, early save cap
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: honor LLAMA_ARG_CACHE_PROMPT env in slot-save guard
* Studio: derive prompt-cache state from final argv for slot saves
* Studio: stat LoRA/control-vector sidecars in KV restore fingerprint
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: parse csv and FNAME:SCALE sidecar syntax in KV fingerprint
* Studio: address codex review on idle-unload KV resume
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: harden slot-save cleanup, cap accounting, stale-KV guard, save timeout
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: treat unavailable KV estimate as full-cap for slot-save disk check
---------
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Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Studio: GPU memory dropdown — llama.cpp --fit on and manual gpu-layers/cpu-moe
* Studio: simplify GPU memory changes (reuse ParamSlider, GPU_LAYERS_ALL, loadedGpuMemoryFields helper)
* Studio: GPU picker — choose which GPUs a GGUF model loads on (gpu_ids)
* Studio: simplify GPU picker (share /api/system fetch, validate gpu_ids)
* Studio: GPU picker review fixes (gate relative indices, no cross-model leak, validate, types)
* Studio: group GPU controls under a collapsible GPU section
* Studio: GPU feature review fixes (fix fit-ctx test, behavior-test the floor, comment accuracy)
* Studio: make GPU a top-level settings section (not nested under Model)
* Studio: flatten GPU controls into the Model section, group by GPU/context/generation
* Studio: move GPU Memory to the bottom of Model with its dependent controls beneath it
* Studio: move GPU Memory below Tensor Parallelism and GPUs below GPU Memory
* Studio: tighten GPU Memory and GPU Layers tooltip copy
* Studio: fix fit-mode context slider track-click, restore GPU Memory tooltip, shorten fit dropdown label
* Studio: GPU Memory tooltip one mode per line, briefer
* Studio: note HIP_VISIBLE_DEVICES (ROCm) in the GPUs picker tooltip
* Studio: narrow the GPU Memory dropdown to fit the shortened label
* Studio: use 'llama.cpp --fit' in the GPU Memory tooltip for consistency
* Studio: allow Tensor Parallelism in Manual GPU mode
* Studio: graduated MoE-on-CPU offload (--n-cpu-moe) replacing the all-or-nothing toggle
* Studio: size the MoE-offload slider for staged (deferred-load) models
* Studio: share one GGUF header walk for the context-length and MoE-count readers
* Studio: size the GPU Layers slider for staged models (one staged-header read)
* Studio: move Tensor Parallelism below the GPUs picker
* Studio: GPU split (--tensor-split) per-GPU model share in Manual mode
* Studio: tolerate whitespace in GPU split input, move it below GPU Layers
* Studio: rename the GPU split control to "Split ratio"
* Studio: Split ratio sends explicit even input; fix blank=free-VRAM (not even) copy
* Studio: tighten llama.cpp --fit VRAM margin with --fit-target 512
* Studio: GPU memory review fixes (rollback re-baseline, single-GPU TP gate, accurate copy)
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* Studio: move Split ratio below MoE Layers on CPU
* Studio: address PR review (fix GPU-info hydration race, share fit context-length across load paths)
* Studio: address codex review (manual single-GPU TP guard, GPU-aware spec defaults in fit/manual, GGUF-only context/preference)
* Studio: address codex review round 2 (gpu_present seed, single-GPU tensor-split guard, staged manual-knob reset, strip inherited offload flags)
* Studio: address codex review round 3 (strip inherited --n-cpu-moe, CPU-fallback warning in Manual mode)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: address codex review round 4 (preserve pinned fit context across a later Apply)
* Studio: address codex review round 5 (honor GPU picker for diffusion GGUFs, clear fit pin on cross-model switch)
* Studio: preserve the pending GPU Memory mode when staging a model
* Studio: pin diffusion GPU device order and reset GPU-memory state for diffusion loads
* Studio: address codex review round 6 (fit-Auto rollback context, preserve manual non-tensor split modes, persist GPU mode on load not select)
* Studio: persist the applied GPU Memory mode, not the requested one (skip diffusion loads)
* Studio: replace Manual-mode split-ratio field with per-GPU layer sliders
* Studio: clarify per-GPU layer split hint for tensor-parallel mode
* Studio: address codex review round 7 (allow GGUF gpu_ids past the legacy guard, replay GPU-memory fields on respawn)
* Studio: address codex review round 8 (size the validate preflight like the load in fit mode, across both load paths)
* Studio: skip the training-OOM guard for llama.cpp --fit GGUF loads (they spill to RAM)
* Studio: drop the now-redundant compare-path validate sizing (the --fit guard skip makes it moot)
* Studio: address codex review round 9 (keep the training guard for fit loads, forward gpu_ids to validate, strip inherited manual tensor-split)
* Studio: address codex review round 10 (gate GPU-memory adoption on is_gguf, record manual knobs only in Manual mode)
* Studio: handle diffusion GGUFs symmetrically in the GPU Memory controls (preserve the standing mode preference, hide the inapplicable mode/TP controls)
* Studio: remember the GPU Memory settings per model
* Studio: consolidate --fit mode and Manual mode into a single Manual mode
* Studio: preserve the per-GPU layer split across GPU Layers changes
* Studio: trim overly long GPU Memory comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* address GPU memory config review comments
* trim redundant GPU memory tests
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reconcile manual-mode TP drops with the #6659 drop-site invariants
* Preserve quantized KV in manual --fit, charge GGUF companions in full, reconcile GPU pick on load
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Clear stale GPU baseline on non-GGUF loads so it can't read as dirty
* Fix no-context-shift test for the conditional -c flag
* Credit manual GPU-layer offload for cached HF GGUFs
* Reset per-model load knobs on GGUF quant switch
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Strip inherited tensor-split when manual ratio is cleared
* Match auto-load validation to safetensors placement
* Reset editable manual knobs after Auto GGUF loads
* Record a single device for diffusion GPU picks
* Reset per-model GPU knobs before applying saved settings
* Address review comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Guard manual tensor splits and keep remembered context on auto-load
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Snapshot compare knobs, seed splits from free VRAM, flag zero-offload loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Exempt CPU-only loads from the guard floor and harden compare and reseed paths
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reach full offload from the layers slider and charge extras drafters in the guard
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Warm the GPU device cache before pick reconciles and disable staged GPU controls
* Align the training guard with inherited extras, spec mode, and compare targets
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Hide GPUs from companion-less zero-offload loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Size diffusion picks per device, own manual offload flags, reject XPU picks
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Drop tensor flags at zero layers and exempt CPU-pinned drafters
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Allowlist the zero-layer tensor parallel drop site
* Keep validate and load guards on the same extras and refresh stale baselines
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Drop mismatched manual tensor splits before launch
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Gate XPU picks on the real backend field and harden split and hydration paths
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Weight full GPUs as zero, clamp split shares, and refine the zero-layer mask gate
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Carry fit context across mode changes and align drafter and picker gates
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Catch variant switches, uncached diffusion repos, and text-only mmproj skips
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Check companions on the first device and size native and remote zero-layer loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Replace the training guard's precise VRAM modeling with a conservative bound
* Baseline context pins on non-GGUF hydration and reprobe list-seeded staged GGUFs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Size manual splits by their largest share and preserve resolved context from Default
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Default-deny unsized required companions and price KV at the effective cache dtype
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reserve MTP draft KV and MLA target-copy in the training guard
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Size tensor-parallel loads per device and show GPU controls for native GGUFs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reserve MTP overhead for uncached remote GGUFs and the mmproj runtime factor
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Drop the training-coexistence VRAM estimation this PR added
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Gate remembered load settings to GGUF picks
* Lock the remaining load-time controls during a staged load
* Clear the stale native-path token on compare loads
* Drop a stale guard reference from the zero-offload masking comment
* Seed GPU baselines from the rollback response and drop never-emitted offload flags
* Match validate's training guard to load and keep the native reload token
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Trim verbose GPU-memory comments
* Thread the variants header walk off the event loop, honor device pins on zero-offload, and hold staged GPU edits
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Honor manual placement and classify pinned zero-offload loads
* Close diffusion admission and status hydration gaps
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Check the actual diffusion GPU during training
* Align staged baselines and manual reload dedupe
* Fix GGUF placement and rollback state
* Harden manual GGUF placement boundaries
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Remove unused resolve_tensor_parallel import in llama_cpp.py
The name is used only in llama_server_args.py, routes/inference.py, and tests,
not in llama_cpp.py; the unused hoisted import trips the import-hoist verifier
in the source-lint CI job.
* Fix diffusion GPU dedup and training guard for non-numeric device tokens
The diffusion runner drives only its single lowest device and the backend
records that one device (self._gpu_ids = [sorted(gpu_ids)[0]]), but the reload
dedupe compared it against the full requested list, so a multi-GPU pick that
resolves to the same device forced a needless reload. Normalize the request the
same way for a loaded diffusion model in both _already_in_target_state and the
route _request_matches_loaded_settings.
The chat-during-training coexistence guard called int() on the single-device
token and hard-rejected when it could not parse. A non-numeric token (a CUDA
UUID / MIG handle) now sizes against the whole visible pool like the GGUF guard
instead of falsely blocking the load, and an empty token (a CPU-only runner such
as a CPU diffusion GGUF) is allowed outright since it uses no GPU VRAM.
* Tighten comments added by the GPU memory config changes
* Harden GGUF placement from independent review: VRAM sizing, diffusion TP reset, tensor_split validation
- Training coexistence guard: a single-device runner pinned through an
unresolvable UUID/MIG token was sized against the aggregate visible-VRAM pool,
so a load could pass on capacity it cannot use and then OOM active training.
Size against the worst-case visible device (min free) instead, keeping the
guard's documented default-deny contract. The empty-token (CPU-only runner)
allow path is unchanged.
- Diffusion startup: _start_diffusion_server now resets self._tensor_parallel to
False alongside the other placement resets. A prior tensor-parallel chat load
(process killed but not fully unload-reset) otherwise left /status misreporting
tensor parallelism and made an identical diffusion re-Apply reload against the
stale state.
- tensor_split: reject negative / non-finite / all-zero splits up front. They
were dropped at launch but still compared raw in the reload dedupe, so an
identical Apply reloaded indefinitely.
- Tests: the shared httpx stub was incomplete and, installed via setdefault
before real httpx loaded, broke a combined pytest run (collection errors on
httpx.Response). Import the real installed httpx instead.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
* Studio: hide infra models from the hub cached inventory
The hub inventory scans behind /api/hub/cached-gguf and /api/hub/cached-models
returned the llama.cpp install validation probe (ggml-org/models) and the RAG
embedder (unsloth/bge-small-en-v1.5[-GGUF]) as on-device models. Share the
hidden-model check from routes/models.py via utils/models/hidden_models.py and
apply it in both scans. A GGUF infra repo stays visible when the user
explicitly downloaded a variant through the Hub, since variant manifests only
exist for user-initiated downloads.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: make On Device trust the hub inventory, match repo ids exactly, lighten the hidden-model import
Follow-up on the hub cached-inventory hidden-model change, addressing the review.
On Device now trusts the Hub inventory API for cached rows. The backend already
hides the RAG embedder and the llama.cpp probe and re-includes a GGUF infra repo
once the user downloads a variant through the Hub, but the frontend was
re-hiding it by repo id, so the user-downloaded variant never appeared in the On
Device list or the count. isVisibleInventoryRow now short-circuits cached rows
(kind === "cache") to visible and keeps client-side needle hiding only for local
filesystem rows and Discover.
is_hidden_model matches Hub repo ids exactly (case-insensitive) against the probe
plus the effective embedder and its GGUF companion, instead of substring
matching the configured-embedder basename. A custom embedder with a generic
basename like org/model no longer hides unrelated cached repos such as
user/model-chat or org/model-instruct. The probe filename and local-path
embedders keep exact matching.
The helper moves to utils/hidden_models.py and is imported at module scope in the
hub cache scanner, so it no longer pulls in utils/models/__init__ (the eager
model-config/checkpoint stack) and a broken import fails at startup instead of
being swallowed per-repo and silently emptying the inventory. routes.models
keeps the _is_hidden_model and _safe_resolve aliases and drops the unused
_HF_REPO_ID_RE re-export that was failing source lint.
Tests: exact repo-id matching with a custom embedder, the cached-models scan
keeping an unrelated repo, and a clean-interpreter check that the helper imports
without the model-config stack.
* Studio: match the llama.cpp probe filename on both path separators
The hidden-model check compared the probe's on-disk filename with
Path(value).name, which on a POSIX interpreter does not split a Windows-style
path ("...\stories260K.gguf") and would let the probe through. Split on both
separators so the probe is matched regardless of which OS produced the path,
matching the tolerance of the previous substring check. Adds a Windows-path
assertion to the probe test.
* Studio: harden hidden infra model handling
* Fix hidden cache row confirmation
* Fix hidden local rows and confirmed hint merges
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Handle snapshot-configured hidden models
* Hide basename-only default embedders
* Fix dynamic embedder inventory filtering
* Studio: hide the configured RAG embedder from Discover and feed rows
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
Co-authored-by: Daniel Han <23090290+danielhanchen@users.noreply.github.com>
* Replace standalone Studio wording with Unsloth
Replace the single word Studio with Unsloth wherever it is used as
shorthand for Unsloth Studio in docs, CLI output, UI strings, i18n
locales, workflow display names, comments and docstrings.
Kept unchanged: the full name Unsloth Studio, third party product
names (LM Studio, Visual Studio, Mac Studio), feature names
(Recipe Studio, Fine-tuning Studio and its translations), and all
identifiers such as env vars, commands, paths and filenames.
* Address review feedback on the Studio wording rename
Use "an" before Unsloth where the rename left the article as "a".
Restore the split brand where Unsloth and Studio render as two halves
of the full product name: the onboarding sidebar subtitle and the
IPv6 localhost warning. Scope two messages to the full name Unsloth
Studio where plain Unsloth was misleading: the AMD README bullet and
the CLI studio setup error.
* fix(studio): add MLX adapter state control
* fix(studio): honor MLX adapter comparison state
* fix(studio): keep enabled MLX adapters permissive
* Studio: preserve public error message on MLX compare-mode adapter failures
generate_with_adapter_control raised a plain RuntimeError, which the compare
route handled with the generic handler that drops the operational message.
Raise GenStreamErrorRaised(public=chunk.public) instead and catch it in the
streaming and non-streaming consumers, matching the safetensors tool loop, so
errors like 'model is being unloaded' surface their real message.
* Studio: re-emit VLM think prefill inside the adapter context
The compare-mode merge dropped _generate_vlm's upfront yield of the prefilled
<think> block. Restore it as the first snapshot inside the lock+adapter context
(matching _generate_text) so the UI renders the thinking block during prefill
and a cancel/error before the first token does not drop it. Adds a regression
test asserting the prefill is emitted first, after entering the adapter context.
---------
Co-authored-by: danielhanchen <unslothshared@gmail.com>
The Connections form hid the API key field for the Ollama preset, which
blocked Ollama cloud (it requires a key). Show the optional field for
Ollama; the backend already sends Authorization: Bearer when a key is
set and omits the header when empty, so local keyless servers are
unaffected.
Fixes#7163
* Make the Inkling reasoning-effort coercion a module-level helper so duck-typed engine stand-ins keep working
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* Align Inkling minimal reasoning effort with the reference implementation (0.1)
---------
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* Studio: Inkling support fixes (context sizing, tool-call healing, reasoning effort, audio icon)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: reject binary web_search fetches instead of decoding them into replacement chars
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Match web-fetch MIME subtypes exactly and detect control-char binary
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Sniff binary magic bytes and retry undeclared non-UTF-8 pages as text
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Harden web fetch binary sniffing
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Simplify web fetch binary guard
* Sniff unknown MIME types and handle Latin-1
* Sniff ambiguous Office MIME and prefixed magic
* Decode BOM-marked Unicode web content
* Studio: require ASCII evidence for declared Latin-1/cp1252 web fetches
Latin-1 and cp1252 decode every byte to a printable character, so a high-byte
binary body declared as iso-8859-1/windows-1252 decoded cleanly and slipped
past the control-character binary check. Apply the existing ASCII-structure gate
to those declared decodes as well. Scoped to the Latin family so legitimate
non-Latin single-byte pages (Cyrillic, Greek) are not rejected.
* Revert "Studio: require ASCII evidence for declared Latin-1/cp1252 web fetches"
This reverts commit c7fbec216c.
* Studio: tighten web-fetch binary guard comments
---------
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Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
* Studio: stream live tool output with SSE heartbeats and fix web page extraction
Server-side python/terminal tools now stream incremental stdout to the chat
UI while running (new tool_output SSE event), and every blocking tool
execution emits heartbeat keepalives so reverse proxies (Cloudflare tunnels
cap idle streams at ~100s) cannot drop the connection mid-turn. The tool
loop routes also emit a stall keepalive during silent prompt prefill between
tool iterations. The final role=tool message the model sees is byte-identical
to before, so tool-call parsing, nudging, and healing are untouched.
web_search page fetches now extract main content: GitHub repo root pages are
rewritten to the README API (with HTML fallback), hidden/aria-hidden client
error placeholders are dropped, conversion scopes to article/main, and known
boilerplate fragments are stripped. Non-HTML responses are returned raw
instead of being run through the HTML converter.
The frontend renders live-scrolling tool output inside running python and
terminal cards, and a chat stream that ends without a terminal signal now
surfaces an explicit interrupted state with a Retry action instead of
silently ending the turn.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: fix content-type sniffing, unlimited-timeout drain, and env parity in tool streaming
Content-Type sniffing: get_content_type() defaults to text/plain when the
header is absent, so the sniffing fallback never fired and header-less HTML
came back as raw markup. Report an empty type for a missing header and sniff
the body whenever the declared type is not HTML, so mislabeled text/plain
HTML pages are converted like before the extraction change.
Unlimited timeout drain: with tool_call_timeout disabled the old path used
communicate(timeout=None) and waited for EOF, but the streaming drain capped
the post-exit drain at a 5 second join, truncating output from a grandchild
that holds stdout open. When timeout is None, drain until EOF or the cancel
event fires; finite timeouts keep the bounded remaining-budget join.
Env parity: drop the PYTHONUNBUFFERED=1 injection on the streaming path so
the child invocation is byte-identical with and without streaming (the env
var was model-visible via os.getenv). Live streaming granularity now depends
on the child flushing; unflushed output arrives in ~8 KB chunks or at exit
and the final result is unchanged, with SSE heartbeats covering the gaps.
* Studio: stream tool-call arguments while the model writes them
A model writing a large tool call (a full python game is minutes of
generation) produced nothing on the stream: the structured path
accumulated delta.tool_calls fragments silently after the provisional
card, and the text path's DRAINING state consumed everything until
stream end. The user saw a dead Running spinner while the model was in
fact writing code, and the byte-silent SSE segment was also the window
where proxies drop the connection.
New tool_args SSE events stream the arguments as they generate. The
structured path forwards each fragment once a provisional card exists
(backlog first, so the card starts from the top of the call). The text
path sniffs the drained call for an enabled tool name and streams the
raw call text under the id the stream-end parser assigns its first call
(call_0), so the final tool_start reconciles the same card; the sniff is
gated on enabled names plus the provisional size floor, and prose or
ordinary JSON answers never spawn a card. The safetensors loop streams
the drained render_html call to its existing provisional card the same
way.
The chat adapter accumulates the raw stream per card and feeds a partial
JSON parse (call envelopes and stringified arguments unwrapped) into the
part's args, so the python and terminal cards render the code live and
the render_html canvas builds while streaming; both cards now say
Writing code / Writing command during this phase via useToolArgsStatus.
Display only: the parser input, the executed call, and the conversation
the model sees are byte-identical, covered by new loop-level tests for
the structured path, the text path, and the no-tool JSON answer.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: keep full tool output visible past the model cap; heal /mnt/data habits
Live testing surfaced two issues in the tool streaming UX.
First, a long python stdout ended in '... (truncated' in the finished
card: the model-visible result is capped by tools._truncate
(_MAX_OUTPUT_CHARS, previously 8000 chars) to protect the context
window, and the card rendered that capped text even though the live
stream had already shown everything. The cap stays (raised to 16000,
overridable via UNSLOTH_TOOL_RESULT_MAX_CHARS) but display and model
concerns are now split: the adapter preserves the accumulated live
stream on tool_end whenever it captured more than the final result, and
the finished python/terminal cards prefer it. The live-stream ceiling
rises from 16 KB to 400 KB (chunks batch per poll, so SSE stays cheap),
and both the live pane and the finished card render only the last 2000
lines with a Show all control so a huge output cannot jank the DOM. The
truncation notice now tells the model the user saw the full output and
that written files persist in the working directory. The final result
string remains byte-identical with and without streaming.
Second, models trained on ChatGPT code-interpreter transcripts write to
/mnt/data, which does not exist here (the sandbox CWD is a per-thread
persistent dir). Three layers, all identical across streaming and
non-streaming paths: the python/terminal tool descriptions gain one
sentence saying to use relative paths in the persistent CWD; a failed
execution whose output shows a missing-file error on a known
code-interpreter prefix (/mnt/data, /mnt/outputs, /home/sandbox,
/workspace) gets a model-visible retry hint appended after truncation
so it always survives; and a sitecustomize shim on the sandbox
PYTHONPATH remaps those prefixes onto the CWD in open()/os.makedirs()
with a one-line stderr notice, covering the python tool and any Python
launched from the terminal tool without touching the exec wrapper (so
tracebacks keep their line numbers). Bash-level file operations cannot
be redirected without root or mount namespaces, so they rely on the
description and the hint.
* Studio: fix hidden-element parsing, heartbeat gaps, and tool output id collisions
Review follow-ups on the tool streaming work:
- _html_to_md: treat any present hidden attribute value as hidden (it is an
enumerated attribute whose invalid value default is the Hidden state, so
hidden="false" is still hidden), and implement HTML5 optional end tags so
an unclosed <p hidden> or <li hidden> ends at the next sibling start tag
instead of swallowing every following sibling until the parent closes
- tool_stream_exec: keep heartbeats flowing after the live-output cap; a
tool that keeps printing past the cap kept the queue non-empty, so neither
tool_output nor heartbeat events were emitted and the SSE stream went
silent past proxy idle timeouts
- routes/inference: forward tool heartbeats before the
disable_parallel_tool_use drop window swallows events, so a dropped call
that executes server-side cannot leave the Anthropic stream silent
- llama_cpp: close the provisional text tool card with a tool_end when the
drained call fails to parse (DRAINING false-positive path), so the card
cannot spin forever while the text is delivered as content
- tools: decode terminal output as utf-8 with errors=replace like the python
tool; invalid bytes used to raise UnicodeDecodeError from communicate() on
the non-streaming path and silently truncate the streaming reader, so the
two paths diverged
- sitecustomize: patch io.open alongside builtins.open; pathlib Path.open,
read_text and write_text call io.open directly and bypassed the remap
- frontend: scope the toolLiveOutput/toolFullOutput store keys by pane
(modelType and pairId) and clear stale entries on tool_start; backend ids
like call_0 repeat across turns and across concurrently streaming panes
(compare mode), so a later turn or another pane could display the wrong
preserved output, and run-end cleanup now clears only its own keys
Each backend fix carries a regression test that fails on the previous code;
the byte-identity tests between streaming and non-streaming stay green.
* Studio: keep tool failure status visible and truncation/remap notices truthful
Finished python/terminal cards preferred the fuller live stream by length
alone, so a tool that printed a lot then timed out or exited non-zero showed
the captured stdout but dropped the final result's status (timeout notice,
Exit code N). preferFullToolOutput now shows the stream when the result is
just its truncated prefix, and appends the result otherwise so the failure
tail always survives and the copy button copies both.
The result truncation notice claimed the user was shown the full output, but
the same wrapper serves non-streaming chat/API and direct execute_tool()
callers where nothing is streamed to anyone. The notice is now mode-neutral
and stays byte-identical with and without an output_callback, keeping the
streaming vs non-streaming invariant intact.
The sandbox sitecustomize shim now remaps /tmp/outputs into the working
directory only while it does not already exist, so a real /tmp/outputs the
user's own code created is never shadowed; /tmp/outputs also joins the
missing-path retry-hint list.
* Studio: suppress hidden void elements and keep live output scroll pinned only when at bottom
* Studio: drop capped tool output without concatenating; remap pathlib mkdir
Past the live-output cap stream_tool_execution built item + _drain_pending()
(the current chunk joined with every queued sibling) only to discard it in the
capped branch, so a chatty tool (yes, a tight print loop) could enqueue far
more than one poll interval of text and blow past the memory/CPU ceiling the
cap exists to enforce. Drain and drop queued items without building a combined
string, still counting each drain toward the heartbeat cadence so the SSE
keepalive survives.
Generated code often prepares code-interpreter paths with
Path('/mnt/data').mkdir(parents=True, exist_ok=True); pathlib drives that
through os.mkdir (not the patched os.makedirs) per component and, on
FileExistsError, probes the unpatched os.stat via Path.is_dir(), so the setup
raised before open() ever ran. Patch os.mkdir with the same remap and patch
Path.mkdir so the whole parents/exist_ok dance lands on the mapped working
directory and stays idempotent; real paths still pass through.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: generalize sandbox write remap and hint to any hallucinated absolute path
Models invent absolute paths from seeing their CWD (a DeepSeek run did
open('/home/ubuntu/Sandbox/flappy_bird.html', 'w') and died with
FileNotFoundError). A prefix list cannot enumerate these, so the sitecustomize
shim gains a write-mode fallback in open()/io.open(): when a write/create-mode
open targets an absolute path outside the CWD whose parent directory does not
exist, redirect it to the basename in the CWD and emit the same one-line stderr
notice, echoing the original path. The prefix remaps still run first (they cover
reads and preserve subpaths); read modes never hit the fallback so real system
files fail or succeed truthfully; bytes paths pass through. The fallback is not
applied to mkdir/makedirs/Path.mkdir, since creating an arbitrary absolute
directory can legitimately succeed on the host, and that decision is documented
in a comment.
The model-visible retry hint now echoes the real failing path (parsed from the
traceback tail) instead of the canned /mnt/data example, and fires for any
absolute path outside the working directory, not just the enumerated prefixes,
while a relative miss still gets no hint.
The shim wrapper still adds one frame to tracebacks that surface open() errors;
suppressing only our frame has no clean standard mechanism (a wrapper always
adds a frame), so the frame is left as an accepted compromise.
Tests: hallucinated absolute write remaps to the CWD basename across w/a/x/w+;
reads of a missing absolute path pass through untouched; writes to an existing
external dir pass through; prefix subpaths still preserved; end-to-end write
fallback lands the file in the sandbox workdir identically with and without
streaming; the hint echoes the actual path for convention and non-convention
absolute paths alike.
* Studio: kill exited process groups on drain; bound the over-cap output batch
_drain_process_output killed the process only via _kill_process_tree, which
short-circuits once the parent has exited, so a grandchild that inherited
stdout and outlived the parent was never signaled: a finite-timeout run could
return while it kept holding the pipe, and a timeout=None cancel left it
behind. Capture the setsid process group before waiting and SIGKILL that group
at both give-up points so the whole tree is torn down.
The streaming wrapper's first over-cap batch joined the current chunk with the
entire pending backlog before enforcing the live-output cap, so a chatty tool
could allocate far past the cap on the crossing batch. Bound the drain to the
remaining budget and drop the surplus in place, keeping the truncated output
byte-identical to joining everything.
* Studio: harden sandbox path healing and process/generator cleanup
Sandbox sitecustomize shim:
- Make the generalized write fallback collision-safe: never redirect an
invented absolute path onto an already-present CWD file (refuse and let the
original open raise FileNotFoundError, preserving the workspace file).
- Only w/a/x create a file; r+/rb+ are read-update modes that require the
target to exist, so a bare + no longer trips the write fallback.
- Gate every convention-prefix remap (/mnt/data, /mnt/outputs, /home/sandbox,
/workspace) on the prefix root being absent, so a real host mount is never
shadowed; a miss under an existing real prefix passes through.
- Patch os.open so Path.touch and other low-level creators heal convention
paths too, matching the Path.mkdir patch.
Local code execution (tools.py):
- Capture the setsid process group right after Popen (before any watcher can
poll/reap the leader) and thread it through the cancel watcher and drain.
- Kill the captured group in the non-streaming python/terminal timeout branch
so an exited leader no longer leaks a stdout-holding grandchild (matches the
streaming drain path).
- Guard os.getpgid/os.killpg by platform so streamed execution no longer
raises on Windows; fall back to single-pid kill.
- Judge missing-path hints against the executor's real workdir so a legitimate
miss inside a project workspace outside the sandbox root is not mislabeled.
Tool streaming routes (routes/inference.py):
- Drain a pending next(gen) worker before closing the generator in the
safetensors and Anthropic tool streams, so a disconnect no longer races
gen.close() (generator already executing) or leaks the thread/generator.
HTML to markdown:
- Only drop boilerplate lines composed entirely of known furniture phrases so
real prose that merely quotes one (for example "we use cookies to
authenticate requests") is preserved.
Adds hermetic tests for each change.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: keep aside callouts, contain sandbox path remaps, and keepalive dropped Anthropic tool events
_html_to_md: stop dropping <aside> unconditionally. Documentation pages
render notes/warnings/examples as aside admonition callouts; those inside
the selected article/main scope are real content. A furniture aside outside
the scope is already excluded by the main-content pass.
sitecustomize: contain the code-interpreter path remap under the sandbox
CWD. A hallucinated habit path such as /mnt/data/../other_session/file no
longer escapes the per-conversation workdir; parent-traversal components in
the suffix are dropped and a '.'/'..' write-fallback basename is refused.
routes/inference: emit a rate-limited comment keepalive when the Anthropic
Messages stream drops tool_output/tool_args events. A chatty tool keeps the
generator busy so the stall keepalive never fires and the tool wrapper emits
heartbeats only while idle, which left the SSE stream silent past proxy idle
caps; the OpenAI passthrough paths forward these events, this path now keeps
the connection alive.
* Studio: bound the tool-output chunk that first crosses the live cap
_drain_queue joined the entire chunk that first crossed the live-output
cap before dropping the rest, so a single multi-megabyte line (or any
chunk dequeued once the budget was already met at max_chars <= 0) was
materialized in full only to be truncated away, defeating the memory
ceiling the cap enforces. Slice the crossing chunk to one character past
the budget: that preserves the caller's overflow signal and its
byte-identical truncation while dropping the arbitrarily large remainder
in place.
* Studio: scope missing-path hint to the failing line, keepalive dropped-call output, and preserve truncated tool streams over byte length
- tools._missing_path_hint: the code-interpreter convention-prefix trigger
scanned the whole output, so a convention prefix mentioned only in a
traceback frame (a /workspace project root) or printed by the user's code
would add a misleading 'use a relative path' hint even when the actual
FileNotFoundError was a relative or in-workdir path. Scope the convention
test to the failing-path error line(s), matching _extract_missing_abs_path.
- _anthropic_tool_stream: the tool_output/tool_args rate-limited keepalive sat
after the drop_until_tool_end skip, so under disable_parallel_tool_use a
chatty second-or-later tool call was dropped whole with no keepalive, letting
an idle proxy kill the SSE stream. Check the keepalive branch before the drop
skip (like the heartbeat branch) so dropped-call output keeps the stream alive.
- preferFullToolOutput / chat-adapter: a truncated result can be longer than
the live stream by byte count once its footer, an 'Exit code N:' notice, or an
__IMAGES__ base64 tail is appended, so the length-only gate discarded the full
stream and the finished card fell back to the truncated text. Add a shared
truncation-aware shouldPreserveFullOutput used by both the write and read
sites: preserve the stream whenever the result carries the truncation footer.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: skip the habit-path hint for real project paths under a convention prefix
* Kill captured process group on streamed wait-timeout
The streamed drain path's proc.wait() timeout branch only called
_kill_process_tree(proc). If the leader exits in the narrow window between
the wait timing out and _kill_process_tree sampling its pgid, that helper
short-circuits on the reaped leader and a stdout-holding grandchild in the
same group survives. Also kill the captured pgid there, matching the
non-streaming communicate() timeout path. Adds a hermetic regression test
that models the reaped-leader race by stubbing _kill_process_tree.
* Fix 3.10 pathlib write_text remap and honor cancel in finite drain
On Python < 3.11 pathlib routes Path.open / read_text / write_text through
a module-level accessor singleton whose open attribute captured the original
io.open at import time (_NormalAccessor.open = io.open). Patching io.open in
the sandbox shim therefore never reached that captured reference, so a
Path('/mnt/data/x').write_text(...) raised FileNotFoundError on 3.10 while
passing on 3.11+ (which dropped the accessor and calls io.open at call time).
Repoint _NormalAccessor.open at the same io.open wrapper via a staticmethod,
guarded so it is an idempotent no-op on 3.11+. Keep the test save/restore
helpers symmetric so the accessor is restored too, and add a hermetic
write_text/read_text remap test that covers every version.
Also honor cancellation while draining inherited stdout after the leader
exits. Once the leader is reaped the cancel watcher returns (its loop is
while proc.poll() is None), so the finite-timeout drain did one blocking
reader.join(timeout=remaining) that ignored cancel_event and kept draining a
chatty grandchild for the whole budget after a disconnect/Stop. Poll
cancel_event in 0.5s slices against a deadline like the timeout=None branch
and kill the captured process group promptly on cancel. The normal path still
reaches EOF on its own, so the streamed vs non-streamed result is unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: port no-tool stream keepalive/drain and fix subprocess/queue/extraction asymmetries
Streaming no-tool paths now match their tool twins:
- _anthropic_plain_stream, safetensors/MLX no-tool stream, and standard GGUF
no-tool stream run next(gen) in a worker with a timed SSE keepalive loop so a
long prompt prefill cannot leave the stream idle past a proxy cap.
- The Anthropic plain and safetensors/MLX no-tool teardowns now drain the
pending next(gen) worker and close the generator on disconnect instead of
leaking the suspended generator.
Other asymmetries:
- Non-streaming _python_exec/_bash_exec always drain via _drain_process_output
(output_callback may be None) so a cancelled run reaps a stdout-holding
grandchild that outlived the leader instead of blocking in communicate(). The
joined bytes are identical to communicate(), so streamed vs non-streamed
results stay byte-identical.
- _build_bypass_env installs the sitecustomize path shim on PYTHONPATH (prepend,
keeping the operator's entries) so /mnt/data remap works in bypass mode too.
- GGUF forwards output_callback to execute_tool only when the callable accepts
it (shared accepts_output_callback), matching safetensors and preserving
legacy monkey-patched signatures.
- tool_stream_exec bounds accepted live output at the producer boundary so a
chatty tool cannot grow the queue without limit under consumer backpressure
and cannot keep the drain spinning and starve heartbeats.
- html_to_md implicit-close now searches past unclosed inline descendants so a
hidden <p>/<li> is closed by a following block; main-content scoping gates on
the largest single <article>/<main> so a swarm of tiny cards cannot pass the
threshold in aggregate and displace the real main.
- preferFullToolOutput re-attaches the "Exit code N:" prefix to the fuller
stream instead of appending the still-prefixed result, so a failed truncated
tool no longer duplicates its stdout in the finished card.
Adds hermetic tests for each.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Preserve short live output on timed-out tools; strip inline-CSS-hidden subtrees and score truncated main-content scopes
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Tighten chat tool streaming comments and docstrings
* Keep HTML READMEs from the GitHub API and preserve interrupted tool output
Convert a 200 HTML README body from the GitHub README API to Markdown
instead of discarding it and falling back to the repo page chrome, and
promote captured live stdout to full output when a tool never reaches
tool_end (stream interrupted or cancelled) so the partial diagnostics
stay on the finished card.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: anchor HTML sniff, keep repeated sandbox writes, reuse textual tool ids
Anchor _looks_like_html to the leading doctype/tag so a Markdown README that
opens with a fenced HTML example stays Markdown (no html_to_markdown
corruption), while bare HTML fragments (<body>/<article>/<section>) are still
detected and converted on a missing/wrong Content-Type.
Let the sandbox write fallback re-serve a target it already healed for the same
invented absolute path, so iterative overwrites of a generated artifact stop
failing with FileNotFoundError while the anti-clobber guard still refuses
unrelated same-basename files.
Reconcile the first textual tool call carrying an explicit id onto the open
provisional TEXT card instead of spawning a duplicate card under that id.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: run implicit-close before skipping tags and keep leading README tables as Markdown
A skipped block (<nav>/<footer>) is an HTML5 optional-end-tag closer of an
open <p>, but handle_starttag returned before the implicit-close bookkeeping,
so a never-closed <p hidden> kept its hidden mark and swallowed every following
sibling. Run _close_implicit before the skip decision so the hidden mark is
released and trailing content renders.
Drop <table> (and its <thead>/<tbody>/<tr>/<td>/<th> children) from the
_looks_like_html leading set: Markdown READMEs routinely open with a raw HTML
<table> badge/layout row, and sniffing that as HTML collapsed the whole
Markdown body through html_to_markdown, exactly like the already-excluded
<div align>/<p align> layout headers.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: make bypass-permissions Popen double faithful to the unified drain path
The non-streaming _python_exec/_bash_exec now share _drain_process_output,
which reads proc.stdout in a reader thread and calls proc.wait(); the test
double only implemented communicate(), so bypass-mode bash returned an
AttributeError instead of the faked output. Give _FakeProc a readable stdout
pipe (yields the fake line then EOF), wait()/poll()/pid, so the test exercises
the real drain path on both the python and bash bypass branches.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: persist sandbox path heals across runs and suppress nested hidden lists
* Studio: run tool Python child unbuffered (-u) so unflushed prints stream live
A long-running snippet doing bare print() without flush=True never reached
the live-output pane: CPython block-buffers stdout when writing to a pipe, so
_drain_process_output's readline() saw nothing until the buffer filled or the
process exited. Launch the child with the interpreter -u flag so stdout is
unbuffered and each print streams as it is produced.
-u is applied unconditionally on both the streaming and non-streaming path, so
the child invocation stays byte-identical with and without streaming and the
final joined result is unchanged (buffering/timing only). Unlike the earlier
PYTHONUNBUFFERED=1 env injection that was removed, -u does not pollute the
child's os.environ and is not visible via os.getenv.
* Render only the selected main-content subtree in html_to_markdown
The main-content heuristic sized each <article>/<main> candidate
individually to pick the largest subtree, but then rendered every
matching tag in the document. A page with one real article plus
sibling related-post cards or comment threads passed the size gate on
the real article yet still emitted the unrelated siblings.
Size and render the same chosen subtree so only the selected
main-content subtree reaches the output.
* Studio: tighten chat-tool-streaming fix comments
* Studio: store tool-output-scope separators as unicode escapes
The pane-scope and tool-output-key separators were literal NUL (0x00) bytes, which made git treat the file as binary and hide its diff and blame. Write them as \u0000 escapes instead; the runtime key value is unchanged.
* Studio: bound tool-stream teardown when the client disconnects
stream_tool_execution ran its yield loop with no try/finally, so a gen.close() on client disconnect (GeneratorExit at a yield) skipped the worker join and never signalled cancellation. A tool that does not poll cancel_event mid-flight (web_search, MCP, search_knowledge_base) then kept request teardown blocked until the tool's own timeout. Thread the request cancel_event into the wrapper, set it only on the abnormal-exit path so a clean multi-tool turn is unaffected, and bound the worker join to a few seconds; the daemon worker cannot outlive the process.
* Studio: sandbox path remap no longer masks missing reads
The sandbox sitecustomize shim remapped code-interpreter prefixes (/mnt/data, /workspace, ...) onto the working directory for every open mode, including reads. A read of a path that truly did not exist was silently redirected onto a same-basename workdir file instead of raising on the path the model used, hiding real missing-input errors. Remap writes and creates as before, but remap a read only when the mapped workdir target already exists (re-reading a just-written artifact); otherwise keep the original absolute path so the failure stays truthful.
* Studio: bound web fetch with one overall deadline and cancellation
The web fetch applied timeouts per network operation, so a GitHub README API attempt plus its HTML fallback plus up to five redirect hops could run well past the tool timeout, and nothing aborted once the client had disconnected. Add a single wall-clock deadline shared across the API attempt, the fallback, every redirect hop and the body read, cap each hop's socket timeout at the time left on the budget, and poll cancel_event. SSRF host pinning, per-hop redirect revalidation, the five-hop cap and the size cap are unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: keep tool-stream teardown off the event loop on disconnect
The bounded worker join added for disconnect safety still ran on an abnormal close, so a client disconnect could wait the full join timeout; and the safetensors and Anthropic tool streams closed their generator synchronously on the event loop, unlike the GGUF path. On abnormal exit the daemon worker is abandoned, so join with a zero timeout instead of waiting; offload the safetensors and Anthropic gen.close to a thread to match GGUF; and surface a heartbeat as soon as cancel_event is set while the worker is silent so the route regains control at once instead of after a heartbeat interval.
* Studio: extend the web-fetch deadline to DNS, the body read, and search
The overall fetch deadline did not cover host resolution or the response body read, and query-mode web_search ignored cancellation. Resolve hosts (initial and every redirect) on a budget-polled helper so a slow or pre-cancelled getaddrinfo aborts on time; read the capped body in chunks with the budget re-checked between them so a slow-drip server cannot stretch a single read past the deadline; and gate the blocking DDGS query on cancel_event on both sides. SSRF host pinning, per-hop redirect revalidation, the five-hop cap and the size cap are unchanged.
* Studio: defer the sandbox remap notice and tighten os.open create flags
The one-shot remap notice fired while computing the mapping, so a read that kept its original path emitted a false notice and spent the notice a later genuine remap needed. Only emit it once _remap_open commits to the redirect. Separately, os.open classified O_TRUNC / O_APPEND without O_CREAT as creating, but those cannot create a missing file, so a missing target now stays truthful (only O_CREAT maps to the creating mode).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: convert only genuine HTML README bodies, not Markdown with a leading block tag
The GitHub README API returns the raw file, almost always Markdown. _looks_like_html classified a Markdown README opening with a block tag (<ul>, <ol>, <dl>, <pre>, <blockquote>) as HTML, so _fetch_page_text ran it through html_to_markdown and collapsed its headings, lists and fenced code into a single line. Sniff the README body with a stricter document-level check (doctype or a leading <html>/<head>/<body>) so only a real .html README is converted; the general page path is unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Surface unclassified mid-stream Anthropic errors as SSE error events
The local Anthropic tool-stream and plain-stream paths called
_anthropic_stream_error_event(e) with force defaulting to False, so an
unclassified mid-stream failure (llama-server crash, decode OOM, a
dropped upstream socket) returned no event. The except block then fell
through to emitter.finish(), emitting a normal message_delta and
message_stop that masked a truncated turn as a clean finish.
Pass force = True at both fall-through sites so an unclassified failure
emits a 500 SSE error event and returns, matching the Anthropic
passthrough path that already forces it. Add regression tests covering
both stream paths.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: give each tool run a unique part id so finished cards keep their own output
Backend tool ids restart at call_0 every assistant response, and the
transient toolLiveOutput/toolFullOutput store maps were keyed by pane
scope plus that bare backend id. Two turns in the same pane therefore
shared one key: the stale-clear at tool_start only guards the forward
direction, so when a later call_0 finished and wrote its preserved full
output, every earlier still-mounted finished card reading the same key
re-rendered and displayed the newer tool's output instead of its own.
Mint one per-run-unique part id per backend id (call_0:<uuid>) and route
tool_start/output/args/end through a single resolver so all events for a
call resolve the same id. The durable part carries the unique id, so the
finished-card readers derive a collision-free key with no change, and the
awaiting-confirmation path keeps its own synthesized id. Outbound replay
stays paired (the assistant tool_call id and the role=tool result
tool_call_id both come from the part id) and gains unique ids across
turns, which strict providers require.
* Studio: tighten PR comments
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Studio: exclude /api/export/status from request access logs
The frontend polls /api/export/status every 5s to detect export start, so it
fires continuously even when idle. Each poll emitted an info request_completed
access line, making up most of the server access logs. Add it to _EXCLUDED_PATHS
alongside /api/train/status. The endpoint is unchanged; export state is still
logged by the export modules and streamed over SSE, so no signal is lost.
* Studio: collapse hub download-progress polls in the access log
download-status and gguf-download-progress (plus the dataset equivalents)
are polled about twice a second for the whole download, so each emitted an
info request_completed line. Add them to _QUIET_POLL_PATHS so they collapse
to one heartbeat line per 10s instead of one per poll.
* Studio: log hub download progress at 10% steps
The access log carried no real progress, only poll pings. Emit one
hub_download_progress line per 10% step from the shared snapshot progress
reader, so an active download shows actual percentage without a line per
poll. Throttled per job and resynced if the same download restarts.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: drop successful chat thread/project CRUD from the access log
A single chat turn fans out about twenty requests under /api/chat/threads
and /api/chat/projects (list, fetch, per-message forks, and the message
writes) that only reflect the UI re-rendering. Suppress their 2xx access
line so the log keeps the signal (generation, tool calls, code execution,
engine stats) and errors. Non-2xx on these paths still log.
* Studio: silence transformers torch_dtype deprecation warning
transformers logs "`torch_dtype` is deprecated! Use `dtype` instead!" once at
model-config load via logger.warning_once (logging, not warnings), so a warnings
filter cannot catch it. Attach a small logging.Filter in setup_logging, which
runs before any model config is parsed, to drop that record on the transformers
loggers that emit it.
* Studio: quiet inference load-progress polls and log throttled load progress
The frontend polls /api/inference/load-progress about twice a second for the
whole model load, so each emitted a request_completed line. Add it to
_QUIET_POLL_PATHS (heartbeat) and emit one inference_load_progress line per 10%
step from the load-progress route, so a load shows real percentage instead of a
line per poll.
* Studio: fully suppress download/load progress poll access lines
The download-status, download-progress, gguf-download-progress, active-downloads
and transport-status polls (model and dataset), plus inference load-progress,
fire ~2x/s for the whole download or load. Their progress is now reported by the
hub_download_progress / inference_load_progress events (and the viewer's progress
line), so the per-poll access line adds nothing. Drop it on 2xx and keep it on
errors, instead of the prior 10s heartbeat. Chat CRUD suppression is folded into
the same _is_quiet_success helper.
* Studio: suppress training-tab model/dataset download-progress polls
The training tab polls /api/models/download-progress and
/api/datasets/download-progress about twice a second for the whole prep phase.
These are separate routes from the /api/hub equivalents and only scan the cache,
so their 2xx access line adds nothing (on Windows they always read 0 since the
bytes live in snapshots/, not blobs/). Suppress the 2xx line and keep errors,
alongside /api/models/gguf-download-progress.
* Studio: drop transient pre-auth 401 on chat thread/project polls
On first load the SPA fires chat thread/project GETs before the initial token
refresh, so they 401 until /api/auth/refresh runs and the retries succeed. That
pre-auth 401 is a bootstrap artifact, not an error; suppress it alongside the
already-quiet 2xx line. Genuine 4xx/5xx on these paths, the download/load poll
401s, and all /api/auth/* still log.
* Studio: quiet tab-switch list polls and per-poll scan/reconnect logs
Switching between the Train, Export, and Chat tabs refetches list endpoints on a
timer, and each hit re-logs internal detail. Heartbeat /api/train/runs,
/api/models/checkpoints, /api/models/local and /api/rag/knowledge-bases (10s
window, first hit and errors still log), and downgrade two per-poll INFO lines to
debug: the checkpoints scan summary ("Found N training runs") and the
per-reconnect SSE resume line. The meaningful "replayed N missed steps" line,
logged only when steps were actually replayed, stays at info.
* Studio: enable tokenizer parallelism for dataset prep on Windows/macOS
TOKENIZERS_PARALLELISM was forced off everywhere to stop datasets' forked map()
workers from deadlocking, but that fork only happens on Linux. On spawn platforms
(Windows/macOS) dataset.map() runs in-process (dataset_map_num_proc returns None),
so disabling tokenizer parallelism leaves the fast tokenizer single-threaded and
dataset prep runs serially on one core. Keep it off on Linux (fork safety) and on
for spawn platforms, where there is no fork to deadlock. Measured ~7x faster
tokenization (12.5s -> 1.7s for 20k rows on a 32-core Windows box).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: log throttled training status to the server log
Training step/loss/epoch only went to the UI via SSE, so the server log showed
inference engine_stats and train/runs heartbeats but nothing about the actual
run. Emit one throttled training_progress line (step/total, percent, loss, epoch,
eta) from the CUDA event pump: the first step, then at most every 30s, plus the
final step, resyncing when a new run restarts the counter. Per-step UI streaming
is unchanged.
* Studio: quiet llama.cpp update-status polls and log throttled update progress
The prebuilt llama.cpp update polls /api/llama/update-status about twice a second
for the whole download and install. Suppress its 2xx access line (errors still
log) and emit one throttled llama_update_progress line per 10% step from the
status route, so the update shows progress without a line per poll. The existing
"llama update: installing" and "llama update: success" events still bracket it.
* Studio: quiet the export log-tail poll
The Export tab polls /api/export/logs about once a second to stream the export
subprocess output into the UI panel. Suppress its 2xx access line; the real
progress is already logged as event-driven "Export subprocess status: <phase>"
lines plus the subprocess start and checkpoint-loaded events, and errors still log.
* studio: keep errors and mutations visible in access-log suppression
Make the quiet-success access-log suppression GET-only so chat thread/project
mutations (POST/PUT/DELETE) still log; only their list-poll 2xx and the
transient pre-auth 401 are dropped.
Suppress /api/export/status 2xx only (move it out of the all-status exclude
set) so a 401/403/500 on it stays visible.
Legacy /api/models and /api/datasets download-progress polls emit no
hub_download_progress events, so heartbeat them via the 10s quiet-poll window
instead of suppressing outright, keeping download visibility (notably on
Linux). The event-emitting /api/hub download polls stay fully suppressed.
Update and extend the middleware tests to cover GET-only suppression, the
export-status error path, and the legacy download heartbeat.
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* studio: tighten access-log and training-progress comments
Comment-only pass: collapse the multi-line explanations in the logging
middleware and the throttled training-progress logger to fewer lines while
keeping the rationale. No behavior change.
* studio: log structured export_progress phases
Emit a structured export_progress event per phase (consolidated in the server
log like training and download progress) instead of a plain status string, and
add a phase milestone at the start of the heavy export step so the
merge/save/convert is visible in the server log, not only in the forwarded
stdout panel.
* Studio: reset training-progress log throttle on each new run
start_training rebuilds the per-run progress state but left _last_progress_log_ts/_last_progress_log_step at their prior values. A run started within 30s of a previous one whose last logged step matched the new run's first step would hit the step == prev short-circuit and drop the promised first training_progress line, then stay suppressed until the old 30s window expired. Reset both fields when a new job is accepted.
* Studio: keep post-bootstrap chat 401s visible in the access log
The chat thread/project 401 suppression dropped every GET 401 on those prefixes, so a genuine expired-session 401 vanished alongside the transient pre-auth race. Gate the 401 drop on a per-middleware bootstrap latch that flips once /api/auth/refresh first succeeds: before that the 401s are the pre-refresh race and are suppressed; after it any chat 401 is a real failure and logs. Add a test for the post-refresh case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: limit chat access-log suppression to the exact list polls
The chat thread/project suppression matched by startswith, so it also dropped the 2xx access line for detail and message reads (/threads/{id}, /threads/{id}/messages, /threads/{id}/messages/{id}, /projects/{id}) that are not the high-frequency list polls, losing their access and latency logging. Match the two list paths exactly instead, so only the intended list polls (and their pre-auth 401 race) are suppressed while detail and message reads keep their access line. Add a regression test.
* Studio: reset inference load-progress throttle for each load
The load-progress throttle (_last_load_progress_step) is a module global that persisted across loads, so a cached or small load whose first sampled /api/inference/load-progress response already reported fraction=1.0 hit step == prev (10) from a prior completed load and emitted no inference_load_progress line, while that endpoint's access log is suppressed, leaving the new load with no progress signal. Arm the throttle at load initiation in _load_model_impl so each load's first step always logs. Add a regression test.
* Studio: tighten logging comments
Collapse a few verbose comments (tokenizer-parallelism note, torch_dtype filter, legacy download-poll heartbeat, chat list-path suppression) to fewer lines without changing intent or code.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: permission levels for chat tool calls (Ask, Approve for me, Off, Full access)
Replace the Bypass permissions on/off toggle with a four level permission
selector, available in Settings > General (new Permissions section above
Notifications), the chat settings panel, the composer plus menu, and a new
always visible composer pill.
Levels:
- Ask for approval: every local tool call pauses for allow/deny.
- Approve for me: only calls detected as potentially unsafe pause; the
python/terminal sandbox stays on.
- Off: never pauses; sandbox stays on (previous default behavior).
- Full access: never pauses and the sandbox is disabled. Still requires
the danger confirmation and is never restored across reloads.
Backend adds permission_mode to the OpenAI compatible and Anthropic
passthrough payloads and threads it through both tool loops. Auto mode
uses a fail closed classifier in tools.py: terminal commands must be on
a read only allowlist with no redirection or substitution, python code
is AST scanned for writes, exec, process and network use, MCP tools
auto run only with read only style names. Unknown tools always ask.
Legacy bypass_permissions and confirm_tool_calls keep their exact
behavior for existing API callers.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio permissions: Off is a plain toggle below Full access
Off moves to the bottom of the level menu with a short description and
acts as the feature-off state: the composer pill is hidden entirely
while Off, and reselecting the active level toggles back to Off.
* Studio permissions: higher contrast composer pill text
The permission pill uses a foreground based grey instead of the shared
muted pill color, so it reads darker in light mode and lighter in dark
mode. Full access keeps the danger yellow.
* Studio permissions: panel dropdown layout and shorter tooltip
Chat settings panel: the Bypass permissions label sits on one line with
a full width dropdown underneath, styled like the other panel selects.
Tooltip shortened and wording uses Unsloth instead of Studio.
* Studio permissions: harden auto-mode unsafe detection
Extend the Approve for me classifier to catch write and exec paths that
slipped through:
- terminal: sort -o, tree -o, xxd -r, find -exec/-execdir/-ok/-delete
and find -fprint/-fprintf/-fls now ask; plain read-only forms still
auto-run. awk is no longer allowlisted since its program can write and
call system().
- python: from-imports of mutating names (from os import remove [as rm])
and star imports now ask.
Found by a fuzz and edge-case simulation matrix; pinned in
test_permission_mode.py.
* Studio permissions: split multi-line terminal commands in auto detection
A shell runs each line as its own command, but shlex reads newlines as
whitespace, so "ls\nrm -rf x" demoted rm to argument position and
auto-ran. Normalize newlines and CR to separators, and treat any all
separator token as a command boundary so runs of blank lines still
split. Found by the simulation matrix; pinned in tests.
* Studio permissions: address review feedback on auto-mode detection
Auto-mode (Approve for me) safety classifier hardening:
- Python: flag any reference to a mutating attribute, not only direct
calls, so indirect refs (f = os.remove; f(x)) and aliases ask. Detect
Path.open(mode) write modes and wrap the AST walk to fail closed.
- Terminal: match attached short output flags (sort -o/tmp/out) and keep
find context across grouping parens so find ( -delete ) asks.
- Both: ask before reads that escape the sandbox workdir via parent
traversal or hit credential paths (.ssh, .aws, id_rsa, .pem, etc.).
permission_mode plumbing:
- Fold permission_mode=full into bypass_permissions at the request model
so route-level confirm-gate guards see it as bypass.
- Reject ask/auto on the Anthropic Messages server-tools path, which has
no confirmation channel (mirrors the confirm_tool_calls rejection).
- Keep forced RAG autoinject in auto mode: the safe search_knowledge_base
retrieval never gates, so derive the skip from the real confirm need.
- Reset all local preferences now also clears the legacy confirm key so a
reset restores the fresh default instead of the old level.
Regression tests added for each case.
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* Studio permissions: close auto-mode classifier gaps from review round 2
Auto mode ("Approve for me") let a few mutating calls through as safe:
- os.open(...) always creates/writes a descriptor, so treat it as unsafe
even though builtin open in read mode stays safe.
- fd -x/--exec/-X/--exec-batch runs a command per match; scan for these
alongside find's -exec/-delete.
- tempfile writes artefacts and hands back writable handles, so importing
it now asks.
- Calling the result of a call (getattr(os, "remove")("x"), partials) is a
dynamic target the AST can't vet, so fail closed.
- An MCP tool whose name pairs a read verb with a mutating one
(get_or_create_issue, read_and_delete_file) no longer auto-runs on the
read prefix alone.
Also fold permission_mode="off" into confirm_tool_calls=False on both
request models so the non-stream route guard sees the disabled gate, and
drive the Confirm tool calls toggle off permission_mode="ask" so auto no
longer shows it on.
* Harden auto-mode classifier and normalize bypass to full for PR #7079
Approve for me now asks for a few cases it previously auto-ran:
- os.open via an os alias (import os as o; o.open(path, O_CREAT))
- pathlib symlink_to / hardlink_to / link_to
- importlib.import_module dynamic imports
- os.mkfifo / os.mknod / os.utime
Also fold bypass_permissions into full when a stale ask/auto permission_mode
is sent alongside it, so the Anthropic route guard no longer 400s those legacy
callers. Adds classifier and request-model regression tests.
* Close more auto-mode classifier gaps for PR #7079
Approve for me now asks for cases the review surfaced:
- builtin open aliased to a name (f = open; from builtins import open as w)
or looked up dynamically (globals()['open'])
- pickle / marshal / shelve / dill deserialization
- io.FileIO write handles
- sort --compress-program (runs an external program)
- MCP names carrying save/archive/submit/commit/push/sync/register verbs
Also refine the attribute open() write check so an explicit read mode
(ZipFile.open(name, "r")) stays auto while os.open flags still ask. Adds
test coverage for each case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Close three more auto-mode gaps for PR #7079
- rg runs an arbitrary program per file via --pre / --hostname-bin, so
"Approve for me" now asks for those flags (rg is on the read-only
allowlist).
- A path-qualified command token (./ls, /tmp/cat) is an arbitrary
executable, not the trusted utility its basename matches, so it asks
before running.
- A direct /chat/completions caller that sets permission_mode ask/auto
but omits the legacy confirm_tool_calls flag now self-enables the
confirmation gate, so tools can no longer run ungated on that path.
Adds classifier and request-model tests for each case.
* Close auto-mode classifier gaps from review round 3 for PR #7079
Approve for me now asks for cases the latest pass surfaced:
- short-option clusters bundling a write flag (sort -uo out => -u -o)
- procfs reads that leak a process env/args/memory
(cat /proc/self/environ, /proc/PID/cmdline, maps)
- env-assignment prefixes that change command lookup/loading
(LD_PRELOAD=x ls, PATH=. ls, IFS=x ls); benign FOO=1 cmd stays auto
- os.open imported as a bare callable (from os import open as o)
Also drops ps from the safe terminal allowlist: its BSD environment
flags (ps auxe, ps eww) dump a parent process's unscrubbed env and
cannot be flag-parsed reliably, so ps always asks now. Adds classifier
tests for each case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Close auto-mode classifier gaps from review round 4 for PR #7079
Terminal (Approve for me now asks for these):
- cd dropped from the safe allowlist: cd /; cat etc/passwd moves the
shell out of the session workdir so a later relative read escapes it
- env -C/--chdir (workdir escape) and -S/--split-string (builds a fresh
command line); wrapper flags are now checked
- /etc//passwd and /etc/./passwd normalize to /etc/passwd before the
sensitive-path scan
- a sensitive path split across an assignment and an argument
(p=/etc; cat $p/passwd) via best-effort NAME=value expansion
Python:
- builtins.exec / builtins.eval attribute calls (dynamic code execution)
- destructured open aliases (f, _ = (open, print); f('out', 'w'))
- a sensitive path composed from literals (os.path.join('/etc','passwd'),
'/etc' + '/passwd')
- ZipFile/TarFile write modes (ZipFile(name, 'w')); the reader stays auto
Adds classifier tests for each case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Close auto-mode classifier gaps from review round 5 for PR #7079
Terminal (Approve for me now asks for these):
- procfs reads hidden by shell quotes (cat /proc/$PPID/enviro''n) or
quoted/nested-variable assignments (p="/proc/$PPID"; cat $p/environ):
quotes are stripped and NAME=value prefixes expanded before the scan
- LESSOPEN/LESSCLOSE, which make less run an input preprocessor command
Python:
- os.chdir / os.fchdir, which move the cwd so a later relative read
escapes the sandbox workdir
- sensitive paths composed via a pathlib / chain (Path('/etc') / 'passwd')
or an f-string of literals (f'/proc/{pid}/environ')
- runpy (import) and runpy.run_path / run_module, which run arbitrary code
Adds classifier tests for each case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Close auto-mode classifier gaps from review round 6 for PR #7079
Approve for me now asks for these:
- a mutating callable reached through a getattr alias
(rm = getattr(os, "remove"); rm("f")): calls through a getattr-bound
name fail closed
- compound MCP tool names carrying clone/checkout/comment/fork/tag/
invite/share, which start with a read verb but still mutate
- a sensitive path hidden behind a glob (cat /e??/passwd,
cat /e[t]c/passwd): a ? / * / [..] token is matched against the
sensitive-file set and bracket classes are de-obfuscated; benign
globs (ls *.py) stay auto
Also run first-pass RAG retrieval in off mode: like auto, off never
prompts, so a direct caller passing a stale confirm flag should not lose
document retrieval (both tool loops).
Adds classifier tests for each case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Close auto-mode classifier gaps from review round 7 for PR #7079
Approve for me now asks for these:
- __builtins__.exec / __builtins__.eval (dynamic code via the dunder)
- terminal reads that hide a credential path behind a backslash escape
(cat /et\c/passwd)
- read-named MCP filesystem calls pointed at a credential path
(mcp__fs__read_file {"path": "/etc/passwd"})
- compound MCP names carrying append / prepend
- open aliased through a subscript or builtins attribute
(f = globals()["open"]; f = builtins.open) then called to write
- open(..., **{"mode": "w"}) where a kwargs splat hides the write mode
- a sensitive path with a dynamic segment (open(f"/etc/{name}"),
os.path.join("/etc", name)); /tmp/{name} stays auto
- urllib3 networking
Also stop folding permission_mode ask/auto into confirm_tool_calls for
external-provider requests: that branch rejects confirm_tool_calls with
tools, and the mode only governs local tool calls. Local requests still
self-gate. Adds tests for each case.
* Close auto-mode classifier gaps from review round 8 for PR #7079
Approve for me now asks for these:
- dbm on the unsafe-module list: dbm.open(file, "c"/"n") creates files,
and importing the family signals a persistence writer
- reads of ~/.azure and ~/.config/gh credential stores (Azure/GitHub
tokens), in terminal, MCP arguments, and Python literals
- compound MCP names carrying upsert / assign
Adds classifier tests for each case.
* Gate secret mounts and fix the composer pill count for PR #7079
- Add Docker/Kubernetes secret mount dirs (/run/secrets,
/var/run/secrets) to the sensitive-path checks, so Approve for me asks
before reading injected credentials (terminal, MCP args, Python).
- Count the always-visible permission pill in the composer's compact
threshold so labels collapse at the intended width instead of
overflowing by one pill.
Adds classifier tests for the secret mount paths.
* Close auto-mode classifier gaps from review round 10 for PR #7079
Approve for me now asks for these:
- qualified pathlib constructors (pathlib.Path('/etc') / name), folded
the same as bare Path(...), so a dynamic sensitive path is detected
- open aliased through an annotated assignment (f: object = open;
f('out', 'w')), tracked like a plain assignment
- recursive searches rooted at an absolute path (grep -R TOKEN /home,
rg TOKEN /, fd pattern /etc), which read host files outside the
sandbox tree; sandbox-relative searches stay auto
Adds classifier tests for each case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Close auto-mode classifier gaps from review round 11 for PR #7079
Approve for me now asks for these terminal reads, which bash would
expand into a sensitive path only after the classifier had approved:
- a glob that resolves into a secret mount or credential dir
(cat /r?n/secrets/hf_token, cat /root/.s??/id_rsa)
- a recursive search rooted at a tilde home (grep -R TOKEN ~root,
grep -R TOKEN ~/logs)
- a brace expansion that builds a credential path (cat /etc/pass{w,}d)
- a default/alternate parameter expansion that builds one
(cat /etc/pass${x:-wd})
- an input redirection that hides a glob (cat </e??/passwd)
And these python calls:
- a str.format-built sensitive path (open('/etc/{}'.format('passwd')))
- writer methods that persist to disk without open() (numpy.save,
Image.save, plt.savefig, DataFrame.to_csv, json.dump)
Segment-wise directory matching keeps benign globs (ls /home/*/projects)
auto. Adds regression tests for each case and its safe counterpart.
* Close auto-mode classifier gaps from review round 12 for PR #7079
Approve for me now asks for these too:
- a terminal read whose parent traversal hides behind a redirection with
no following space (cat <../../notes)
- a python read whose path is built with str.join
(open(''.join(['/etc', '/passwd']))), told apart from os.path.join
- a dynamic-code builtin reached through an alias
(from builtins import eval as e; e(...); x = builtins.exec; x(...))
Adds regression tests for each case and its safe counterpart.
* Close auto-mode classifier gaps from review round 13 for PR #7079
Approve for me now asks for these too:
- a recursive search whose root is hidden behind an assignment
(p=/; grep -R TOKEN $p): the recursive-root test now runs on the
assignment-expanded tokens as well
- a python read whose sensitive path is split through a literal variable
(base = '/etc'; open(base + '/passwd')), including via an f-string
- numpy ndarray.tofile, which persists without open()
- a sequence brace read (cat /etc/pass{w..w}d), expanded alongside the
comma brace form before the sensitive-path scan
Adds regression tests for each case and its safe counterpart.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Close auto-mode classifier gaps from review round 14 for PR #7079
Approve for me now asks for these python reads that assemble a sensitive
path in a form the fold did not yet recognize:
- a pathlib object reused through a name (p = Path('/etc'); p / 'passwd')
- old-style percent formatting ('%s/%s' % ('/etc', 'passwd'))
- Path.joinpath ('/etc'.joinpath('passwd'))
- a bytes path literal (open(b'/etc/passwd'))
And these terminal reads, which bash expands into a sensitive path only
after the classifier had approved:
- a substring parameter expansion off an assignment
(p=passwd; cat /etc/${p:0:6})
- an ANSI-C quoted path (cat $'/etc/pass\x77d')
- a glob into an Azure or GitHub CLI config dir
(cat /home/*/.az?re/..., cat /home/*/.config/g?/...)
Adds regression tests for each case and its safe counterpart.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Close auto-mode classifier gaps from review round 15 for PR #7079
Approve for me now asks for these terminal reads, which bash expands into
a sensitive path only after the classifier had approved:
- a per-thread procfs env alias (cat /proc/$PPID/task/$PPID/environ)
- a recursive root behind a default parameter (grep -R TOKEN ${root:-/home})
- a path built by pattern replacement (p=passXd; cat /etc/${p/X/w})
And these python reads:
- a pathlib .parent/.parents chain that escapes the session workdir
((Path.cwd().parent / 'other' / 'notes').read_text())
- a sensitive path resolved through glob (glob.glob('/e??/passwd')[0])
Adds regression tests for each case and its safe counterpart.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Close auto-mode classifier gaps from review round 16 for PR #7079
Approve for me now asks for these terminal reads, which bash expands into
a sensitive path only after the classifier had approved:
- a case-modifying parameter expansion (p=PASSWD; cat /etc/${p,,})
- a mutating find action hidden behind an assignment (f=-delete; find . $f)
- a glob assembled through an assignment (g=e??; cat /$g/passwd)
- a POSIX bracket class glob (cat /etc/pass[[:lower:]]d)
And these python reads/writes:
- a glob pattern folded from a literal variable
(base='/e??'; glob.glob(base + '/passwd'))
- a directly imported os.path.join (from os.path import join; join('/etc', 'passwd'))
- a directly imported writer (from numpy import save; save(...))
- an aliased pathlib constructor (from pathlib import Path as P; P('/etc') / 'passwd')
The find/fd and glob scans now run on the assignment/parameter-expanded
command, and pathlib/join/writer import aliases are tracked. Adds
regression tests for each case and its safe counterpart.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Close auto-mode gaps from review round 17 for PR #7079
Two fixes:
- Gate sqlite3 in auto mode. sqlite3.connect(path) creates or mutates a
database file (and runs DDL/DML) with no open()/writer attribute for
the AST checks to catch, so treat the module like dbm and ask.
- Only self-enable confirm_tool_calls for Studio's own tool loop. The
ask/auto fold previously set confirm on every non-provider request,
including a plain client-tool passthrough (client-supplied tools that
Studio does not execute), which then tripped the local-tool
streaming-confirm route guard and rejected the passthrough. Restrict
the fold to requests that actually ask Studio to run tools
(enable_tools / enabled_tools / mcp_enabled).
Adds regression tests for the sqlite3 write and for the passthrough vs
tool-loop confirm behavior.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Close auto-mode gaps from review round 18 for PR #7079
Classifier (auto mode asks for these):
- os.open through a module alias (import os as o; o.open(...)); os/posix
aliases are tracked like the literal module name.
- less/more pagers, whose escapes (+cmd, !shell, -o/--log-file, LESSOPEN)
can run a command or write a file the command-name allowlist cannot
see, so they are no longer auto-approved.
- a read-named MCP tool carrying a mutating query
(query_database {"query": "DELETE FROM runs"}); DML/DDL statements are
matched as whole statements so a natural-language query that merely
contains "delete" stays safe.
- ML persistence helpers (save_pretrained / save_file / save_model /
save_weights / save_lora / save_checkpoint) that export weights to disk.
Route:
- Honor CLI-forced tools when deriving the confirm gate. When a process
policy (unsloth run --enable-tools) opens the local tool loop without a
request-level tool signal, a permission_mode ask/auto request now
derives confirm at the route (GGUF and safetensors paths) so the mode
still gates the call, and a non-streaming ask/auto request is rejected
rather than running unprompted. A plain client-tool passthrough (no
local loop) is unaffected.
Adds regression tests for each case and its safe counterpart.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Close auto-mode classifier gaps from review round 19 for PR #7079
Approve for me now asks for these too:
- a terminal read whose path is built by indirect parameter expansion
(x=passwd; p=x; cat /etc/${!p})
- a bash /dev/tcp or /dev/udp redirection, which opens a network socket
(cat </dev/tcp/host/port)
- a python read via pathlib's receiver-plus-pattern glob
(Path('/etc').glob('passw?'))
- a python read whose sensitive root passes through a normalizer
(os.path.abspath('/etc'), Path('/etc').resolve())
- a pickle-backed loader that can execute code on load
(torch.load, joblib.load, pandas.read_pickle), tracked through module
import aliases
- compiled code wrapped into a callable (compile(...) + types.FunctionType)
Adds regression tests for each case and its safe counterpart.
* Honor unset permission_mode as ask across the local tool loop for PR #7079
Three gaps where an omitted permission_mode did not behave as the
documented default ("ask"):
- The frontend only sent permission_mode / confirm_tool_calls /
bypass_permissions when a tool pill was on. A process policy
(unsloth run --enable-tools) can open the tool loop with no pill, so
the backend never saw the selected gate. Send the three permission
fields at the top level of every local chat payload instead.
- The backend read payload.confirm_tool_calls directly at the
pre-switch guard and both late per-backend derivations, so an unset
mode fell through as no-gate even for an explicit ask/auto. Add
_permission_mode_confirm(payload): explicit confirm_tool_calls wins,
explicit ask/auto engage the gate, off/full never prompt, and an
unset mode defaults to ask only where realizable (streaming), keeping
the legacy no-gate run for non-streaming unset requests.
- A forced ask/auto tool loop (CLI --enable-tools) with no stream now
400s at the pre-switch guard before evicting the resident model,
matching the existing confirm-without-stream rejection.
Adds test_permission_mode_confirm_derivation covering the derivation
truth table.
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* Declare permission_mode and bypass_permissions on the local chat request type
The previous change moved permission_mode, confirm_tool_calls and
bypass_permissions to the top level of the local chat payload. They had
lived inside a conditional spread, which is not subject to excess
property checking, so the fields were never declared on
OpenAIChatCompletionsRequest. At the top level tsc flagged
permission_mode as unknown (TS2322), failing the frontend build and
every job whose Studio install builds the frontend.
Add permission_mode and bypass_permissions to the request interface
(confirm_tool_calls was already present).
* Close auto-mode classifier gaps from review round 21 for PR #7079
Auto mode ("Approve for me") now asks for these too:
- a pathlib read built from a concrete constructor (PosixPath, WindowsPath
and their Pure* forms), which the folder previously ignored so
PosixPath('/etc') / 'passwd' lost its /etc root and ran unprompted
- a terminal or python read of the ssh host keys under /etc/ssh, which
the sensitive-path regex only covered for passwd/shadow/sudoers
- a read whose path variable is reassigned: the whole-tree pre-scan kept
the last binding, so base = '/etc'; open(base + '/passwd'); base = 'data'
folded to data/passwd and ran even though execution reads /etc/passwd;
any multiply-bound name now folds to the escape sentinel and asks
Also stop the pre-switch guard from rejecting a plain client-tool
passthrough. permission_mode only implies the confirm gate for Studio's
own local tool loop (enable_tools / enabled_tools / mcp_enabled); a
non-streaming client-tool passthrough that carries permission_mode
ask/auto (confirm_tool_calls left unset by the validator) must forward to
the provider branch. Only an explicit confirm_tool_calls=True still forces
the local-confirm rejection there.
Adds regression tests for each case and its safe counterpart.
* Fix permission-pill compaction count and Full-access confirm sync for PR #7079
Two frontend consistency issues in the permission-level UI:
- The composer collapses tool pills to icons above four, but the count
left out the permission pill, which renders in every mode except off.
With one optional pill also shown the row reached five pills without
collapsing and could overflow. Count the pill when it is visible
(permission_mode != off).
- Entering Full access via setPermissionMode('full') or
setBypassPermissions(true) left confirmToolCalls at its previous value,
so a Full-access run (which sends confirm_tool_calls=false) could still
report confirmations as enabled in response metadata. Set
confirmToolCalls false at both entry points.
* Close auto-mode classifier gaps from review round 23 for PR #7079
Auto mode ("Approve for me") now asks for these too:
- a command using an abbreviated GNU long option that reaches a
write/exec action (sort --out= for --output, env --ch= for --chdir,
fd --base-dir= for --base-directory); a prefix of an unsafe long flag
now fails closed
- printf -v NAME, which assigns to a shell variable, so
printf -v PATH %s .; ls can rewrite PATH and run ./ls unprompted
- fd --base-directory / --search-path, which move the search root
outside the session workdir without any positional slash token
- an MCP tool whose compound read name carries a copy-style mutator
(read_and_copy_file, get_and_snapshot_volume): copy, duplicate,
import, export, download, backup, restore, snapshot, mirror
Also treat an omitted permission_mode as its documented default ("ask")
on the Anthropic Messages server-tool path. That branch has no
confirmation channel and already rejects explicit ask/auto, so an
omitted mode now falls into the same rejection instead of silently
running server tools unprompted, unless the caller opted out with
confirm_tool_calls=false (the legacy equivalent of "off"). off/full and
that opt-out still run; the two routing tests that relied on the old
implicit run now set permission_mode="off".
Adds regression tests for each case and its safe counterpart.
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* Refine permission gating from review round 24 for PR #7079
Four fixes from the latest review:
- Anthropic Messages server tools: an omitted permission_mode no longer
rejects a request that only runs safe server tools (web_search), so
existing Anthropic callers keep working. It still rejects an omitted
mode when a local tool (terminal/python) is selected, and an explicit
ask/auto is still rejected outright. off/full and a
confirm_tool_calls=false opt-out always run.
- Pre-switch confirm-without-stream guard: use
_explicit_studio_tool_loop_requested (the same predicate the
passthrough router uses) instead of the policy-inclusive
_effective_enable_tools, so a process --enable-tools policy no longer
turns a client-tool passthrough into a local-loop rejection.
- Auto mode now asks for `uniq INPUT OUTPUT`: uniq writes its second
file positional, so a second positional (numeric flag values skipped)
is treated like `sort -o`. A lone `uniq file` or piped `... | uniq`
stays safe.
- MCP mutation check now strips SQL comments before matching, so
DELETE/**/FROM and UPDATE/**/users (comment-as-whitespace) no longer
slip past the DML/DDL denylist.
Adds regression tests for each case and its safe counterpart.
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* Close auto-mode gaps from review round 25 for PR #7079
Auto mode ("Approve for me") now asks for these Python cases too:
- a bare archive constructor with a write mode (from zipfile import
ZipFile; ZipFile('out.zip', 'w')), tracked through import aliases like
the zipfile.ZipFile attribute call already was
- a dynamic lookup aliased through getattr (g = getattr;
rm = g(os, 'remove'); rm('file')), not just direct getattr(...) calls
- a callable that wraps open or a writer via functools.partial
(w = partial(open, mode='w'); w('out.txt')), which hides the write mode
Also:
- Always-safe tools (render_html) stream their early provisional canvas
card in auto mode again. The provisional-card guard mirrored the raw
confirm flag, which suppressed the early card under Approve-for-me; it
now reuses the auto-mode safety decision (is_always_safe_tool).
- The assistant-ui composer no longer counts the permission pill toward
its collapse threshold when the level is Off (the pill renders null
there), matching the other composer.
Adds regression tests for each case and its safe counterpart.
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* Align permission-mode confirm guards with the router (review round 26)
Three pre-switch confirm-gate checks disagreed with how the tool
loop actually enters, so a valid request could 400 (or an invalid
one could evict the resident model) at the wrong point:
- The /chat/completions pre-switch guard only looked at explicit
request fields, so a process --enable-tools policy that forces the
loop on (request omits enable_tools, no client tools) slipped past
it and only 400ed after _maybe_auto_switch_model had swapped the
model. It now mirrors the router's own loop-entry gate
(_effective_enable_tools or mcp, tool_choice="none" disabling it
unless explicitly asked) while still deferring to client-tool
passthrough, so the policy-forced case is caught before the switch.
- The ChatCompletionRequest full/off fold treated enabled_tools by
itself as a local-loop request and set confirm_tool_calls=True.
The router never starts the loop on enabled_tools alone (it only
filters which tools run), so a non-streaming passthrough carrying
client tools plus enabled_tools 400ed instead of routing verbatim.
The fold now keys off the same enable_tools / mcp_enabled signals.
- The Anthropic /v1/messages unsupported-mode rejection (ask/auto,
or an omitted mode selecting terminal/python) ran inside the
post-switch server-tools block, so an invalid request evicted the
resident model before the 400. It now runs before the auto-switch,
determined from the requested server tools, like the neighboring
malformed- and mixed-tool guards.
Adds regressions for each: a policy-forced non-streaming ask/auto
guard rejection that never reaches the switch, an enabled_tools-only
passthrough that keeps confirm unset, and an Anthropic rejection that
precedes _maybe_auto_switch_model.
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* Close auto-mode classifier gaps from review round 27 for PR #7079
Auto mode ("Approve for me") now asks for these host-mutating or
host-reading cases it previously ran unprompted (the sandbox does not
jail filesystem reads, and terminal commands can change host state):
- Destructured string literals fold into the scanned path now, so
base, leaf = ('/etc', 'passwd'); open(base + '/' + leaf).read()
resolves to /etc/passwd and asks, like the single-assignment form
already did. The tuple/list unpacking branch tracked only aliases to
open; it now also binds literal and folded-path elements.
- pathlib name rewrites fold to the rewritten path:
Path('/etc/x').with_name('passwd').read_text() (and with_stem /
with_suffix) spell no literal /etc/passwd but resolve to it, so they
are folded and caught. Benign in-sandbox rewrites stay safe.
- hostname NAME (or -F/--file, -b/--boot) sets the hostname, so a
positional or a set flag asks; bare hostname and the display flags
(-f/-i/-I/...) stay read-only.
- date -s/--set STRING and the bare MMDDhhmm... positional set the
system clock and now ask; the display forms stay read-only (+FORMAT,
-u/-R, and -d/-r/-f whose following value is skipped so date -d
tomorrow is not mistaken for a clock-setting positional).
Adds regression rows for each gap and its safe counterpart.
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* Close more auto-mode classifier gaps from review round 28 for PR #7079
Auto mode ("Approve for me") now asks for these cases too:
- Mapping-style %-formatted paths. '/etc/%(f)s' % {'f': 'passwd'} folds
to /etc/passwd and asks; a dynamic value or a non-literal mapping
leaves the NUL marker so /etc/<dynamic> still fails closed. The path
folder previously handled only tuple/scalar % right-hand sides and
returned None for a dict, hiding the sensitive segment.
- A read-named MCP database tool carrying PostgreSQL COPY. COPY ... FROM
bulk-loads a table and COPY ... TO writes a server-side file, so both
are matched as mutating queries like DELETE/UPDATE already were. A
'copy' substring in a column name stays safe (word boundary).
- logging file handlers. logging.FileHandler('out.log', mode='w') (and
the default append mode, RotatingFileHandler/TimedRotatingFileHandler/
WatchedFileHandler, and the bare from-import form) create or truncate
a file like open(..., 'w'), so they are classified as writer calls.
StreamHandler / NullHandler and logging reads stay safe.
Adds regression rows for each gap and its safe counterpart.
* Fix writer aliases, GraphQL mutations, and auto server tools (review round 29)
- Auto-mode Python: an aliased writer or archive constructor is tracked
like the existing open alias, so from numpy import save; s = save;
s('out.npy', arr) (and z = ZipFile; z('a.zip', 'w'), incl. the
destructured forms) ask instead of running the write unprompted. A
benign builtin alias (x = len) stays safe.
- Auto-mode MCP: a read-named tool carrying a GraphQL mutation now asks.
query_graphql {"query": "mutation { deleteIssue(id: 1) }"} matches a
leading mutation keyword (GraphQL uses # comments, so it scans the raw
payload); GraphQL read queries stay safe.
- Anthropic /v1/messages: permission_mode "auto" no longer 400s a
safe-only server-tool selection. auto only needs a confirmation
channel for an unsafe call, so like the omitted default it runs for
web_search / RAG / render and rejects only when a gate-needing local
terminal/python tool is selected. ask still always rejects (it asks
per call, which this passthrough cannot honor). The rejection stays
ahead of the model auto-switch.
Adds regression rows/cases for each.
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* Gate asyncio spawn, net clients, default-captured open; allow safe-only auto (round 30)
Auto-mode Python now asks for more process/network/write vectors:
- asyncio process spawners (asyncio.create_subprocess_exec/shell and a
loop's subprocess_exec/shell) run an arbitrary program without the
terminal blocklist, so they gate like os.system/subprocess.
- stdlib network clients imaplib / poplib / nntplib / xmlrpc(.client) /
webbrowser open outbound connections the sandbox does not namespace
off, so their import asks like the other network modules.
- a callable captured as a function or lambda parameter default
(def f(o=open): o('out', 'w')) now binds that parameter into the same
alias set, so the later write through it is gated. A benign default
(o=len) stays safe.
Also, permission_mode "auto" no longer 400s a non-streaming local tool
request whose selection is always-safe-only (web_search / RAG / render).
auto only prompts for a classifier-flagged call, so a safe-only auto
request needs no stream, while ask, an explicit confirm_tool_calls=true,
MCP, and an unrestricted or unsafe selection still require it. Applied
via a shared _confirm_gate_needs_stream helper at the pre-switch, GGUF,
and safetensors confirm-stream guards; the loop's per-call confirm flag
is unchanged.
Adds regression rows/cases for each.
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* Catch brace-glob paths and attribute writer aliases; unfold auto (round 31)
- Terminal auto mode now runs the glob-sensitive scan over every
expansion candidate, so a brace-expanded glob (cat /e{t,}c/pass?d,
which bash expands to /etc/pass?d and then globs to /etc/passwd) asks.
Brace expansion alone spells no literal /etc/passwd and the glob only
resolves once the brace group is expanded, so scanning both together
is required. A benign brace + glob stays safe.
- Python auto mode now tracks a mutating attribute captured as a plain
name: s = np.save; s('out.npy', arr) binds a writer alias, a captured
.open bound method (p = Path('out').open; p('w')) fails closed on any
call since its mode position varies, and z = zipfile.ZipFile is gated
like the bare import. A benign attribute alias (x = np.mean) stays safe.
- permission_mode "auto" is no longer folded to confirm_tool_calls=true
on the request model. Folding it defeated the safe-only-selection
exception in _confirm_gate_needs_stream (an explicit confirm forces
stream=true), so a non-streaming safe-only auto request was rejected.
Leaving it unset lets the route apply the exception; the mode still
drives the loop's per-call gate. "ask" still folds (it gates every
call).
Adds regression rows/cases for each.
* Harden SQL/GraphQL/writer classification and passthrough guards (round 32)
MCP argument mutation detection (read-named query tools):
- CREATE DDL now matches modifiers and the broader object set, so
CREATE OR REPLACE VIEW, CREATE UNIQUE INDEX, CREATE TEMP TABLE,
CREATE MATERIALIZED VIEW and CREATE FUNCTION ask.
- Stored-procedure invocation (CALL proc(...), EXEC/EXECUTE) and VACUUM
ask; a natural-language "call me back" stays safe via the trailing
"(" / ";" / end lookahead.
- GraphQL # comments are stripped before the mutation match, so
mutation # note\n { deleteIssue(id: 1) } no longer hides the mutation.
Python auto-mode classification:
- numpy.memmap / open_memmap and pandas ExcelWriter / HDFStore create or
truncate a file on construction, so they gate like open(..., "w").
- asyncio networking (asyncio.open_connection, loop.create_connection /
create_server and unix variants) opens outbound connections/listeners
the sandbox does not isolate, so it gates like socket.connect.
Terminal auto-mode: file -C / --compile writes a compiled magic database.
Routing:
- A JSON-schema response_format is guided-decoding passthrough, not a
local tool loop, so a --enable-tools policy no longer 400s a
non-streaming ask/auto structured-output request at the confirm guard.
- An explicit confirm_tool_calls=False opts out of the Anthropic Messages
server-tool gate entirely (it wins over the mode, mirroring
_permission_mode_confirm and the GGUF path), so it runs even under ask.
Adds regression rows/cases for each.
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* Track path-ctor aliases, exempt empty selection and safe safetensors card (round 33)
- Python auto mode now propagates path constructor / join aliases, so
assigning Path or os.path.join to another local name is still folded:
P = Path; (P('/etc') / 'passwd').read_text() and j = os.path.join;
open(j('/etc', 'passwd')) ask, while a benign /tmp alias stays safe.
- _confirm_gate_needs_stream now distinguishes an omitted enabled_tools
(None, all tools) from an explicit empty list ([], no tools). An empty
selection runs no built-in tool and cannot prompt, so a non-streaming
auto request with enable_tools=true, enabled_tools=[] is no longer
400ed under a --enable-tools policy.
- The safetensors provisional render_html card now uses permission_mode:
render_html is always safe and never prompts, so its early canvas card
streams under auto (which ships confirm_tool_calls=true) instead of
being suppressed, matching the GGUF path's is_always_safe_tool exemption.
Adds regression rows/cases for each.
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* Extend auto-mode classifier: SQLite mutations, more net/xattr/compressed writers
Additional fail-closed gaps found by a fresh adversarial pass, each with a
reproduction and a benign control:
- MCP read-named tools now ask on SQLite-flavored writes the base DML/DDL regex
missed: ATTACH / DETACH DATABASE, a write-form PRAGMA (PRAGMA journal_mode=WAL
/ user_version=42 / foreign_keys(0), while the read-form PRAGMA journal_mode
stays safe), and load_extension() which loads and runs an arbitrary shared
library.
- Python auto mode now gates the remaining asyncio network entry points
(start_server, open_unix_connection, loop.create_datagram_endpoint,
sock_connect), os.setxattr / os.removexattr metadata writes, the gzip / bz2 /
lzma single-stream writers (GzipFile / BZ2File / LZMAFile, mode-gated like
ZipFile so a read stays safe), pandas to_xml, and the websockets client.
Benign controls (SELECT 1, read-form PRAGMA, asyncio.sleep, gzip read, numpy
read, natural-language "attach"/"analyze") stay safe. Regression rows added to
test_permission_mode.py.
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* Close follow-up auto-mode gaps: SQLite/GraphQL variants, more writers and net
A fresh adversarial pass on the previous round found consistent extensions of
the same fail-closed rules, each reproduced with a benign control:
- MCP read-named tools: DROP / ALTER now cover the same broad object set as
CREATE (DROP FUNCTION, ALTER INDEX, DROP MATERIALIZED VIEW); ATTACH is caught
without the optional DATABASE keyword via its quoted-path form; a
schema-qualified write PRAGMA (PRAGMA main.user_version=1) is matched; and a
GraphQL mutation carrying directives (mutation M @audit { ... }) is treated as
a mutation.
- Python auto mode: os.startfile (Windows program launch), asyncio
start_unix_server, and the socketserver framework now ask; a gzip/bz2/lzma
open imported under an alias (from gzip import open as gopen) is gated like
builtin open; and a dynamic path prefix that can form a sensitive absolute
root (open(chr(47) + "etc/passwd"), open(os.sep + "etc/passwd")) is treated as
sensitive, while a dynamic prefix with a benign suffix stays safe.
Benign controls (read-form PRAGMA, natural-language "attach ... as", "drop the
idea", SELECT dropped_at, query @cached, gzip read alias, dynamic prefix +
data/file suffix) stay safe. Regression rows added to test_permission_mode.py.
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* Gate GNU time -o, basicConfig/methodcaller/fileinput, and more SQL mutations
Another adversarial pass surfaced further consistent fail-closed gaps, each
reproduced with a benign control:
- Terminal: GNU time -o/--output/-a/--append truncate or append to a file with
timing output; time is a wrapper, so the flag is checked before the wrapped
command like env -C.
- Python auto mode: logging.basicConfig(filename=...) opens a log file for
write; operator.methodcaller("write_text"/...) hides a writer method behind a
string and is now treated as dynamic dispatch (like getattr/partial);
fileinput.input(..., inplace=True) rewrites a file in place (the default read
form stays safe).
- MCP read-named tools: UPDATE now matches quoted, bracketed, and
schema-qualified targets (UPDATE "users" / public.users / ONLY public.users /
[users] / `users` SET); SELECT ... INTO OUTFILE/DUMPFILE writes a server file;
and state-changing SQL functions inside a SELECT (pg_terminate_backend,
setval, pg_write_file, lo_export, ...) ask.
Benign controls (time ls / time -p, basicConfig(level=), methodcaller("upper"),
fileinput read, NL "update ... set", setval_col column, PL/pgSQL SELECT INTO
var) stay safe. Regression rows added to test_permission_mode.py.
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* Tighten auto-mode classifier comments
Collapse the multi-line rationale blocks in the permission classifier to one or
two lines each without dropping the exploit each branch closes. Comments and
whitespace only (no code change); the classifier tests are unchanged and pass.
* Retry transient SSE stalls in the tool-calling smoke probes
The tool-calling job flaked with a bare "TimeoutError: timed out": the
server-side python/bash probes stream over post_sse(), which (unlike
post()) had no transport-level retry, so a single stalled stream on a
shared CI runner hard-failed the whole step even though function calling
had already passed.
post_sse() now mirrors post(): a transport-level stall (stream open or a
mid-stream read timing out) is retried once with a fresh request capped
at 300s, while HTTP status errors still surface immediately. The
Linux _run_tool_probe caps each attempt at 360s and treats a stall that
outlives the retry as a failed attempt (rotate to the next seed) instead
of raising, and the web_search probe uses the same 360s cap. A genuine
server wedge still fails (the retry also times out), so real regressions
are not masked. Applied to the Linux, macOS, and Windows inference-smoke
workflows, which share the probe.
* Close five more auto-mode classifier gaps from review
Each reproduces with a benign control:
- Path constructor aliased through an attribute (P = pathlib.Path) now folds
like the bare-name alias, so (P('/etc') / 'passwd').read_text() asks while a
/tmp alias stays safe.
- Callable defaults that are not plain names now bind the parameter: an
attribute writer (def f(s=np.save)), an archive constructor, a captured .open,
and partial(open, mode='w') fold like the equivalent assignment; a benign
default (np.mean) does not.
- A dynamic piece inside a sensitive name (open('/et' + chr(99) + '/passwd'),
which folds to '/et\x00/passwd') now asks: the literals around each dynamic
segment are matched against a credential target with the segment as any run of
non-separator chars, so an all-dynamic ('1 + 1') or segment-spanning
(a + '/' + b) path stays safe.
- MCP read-named tools now ask on REFRESH MATERIALIZED VIEW and REINDEX; a
'refresh' column or natural-language 'refresh' stays safe.
- A writer/open alias handed to a higher-order invoker (map(open, names, modes),
starmap(np.save, ...)) is gated even without a direct call site; a benign
map(len, ...) is unaffected.
Regression rows added to test_permission_mode.py.
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* Default tool pills off on model load so tool execution is opt-in
resolveToolsEnabledOnLoad turned the web-search and code pills on for
any tool-capable model when the user had expressed no preference. Default
them off instead, so tool execution is enabled only when the person
clicks the pill to turn it on; a saved preference (on or off) is still
honoured, so a user who already enabled tools keeps them on.
* Gate mark/subscribe MCP verbs and qualified higher-order writer invokers
- A read-prefixed MCP tool name carrying mark / subscribe / unsubscribe
(get_and_mark_read, get_and_subscribe) now asks; a 'mark' substring inside
one token (list_bookmarks) stays safe.
- The higher-order writer check now also fires for a qualified invoker
(itertools.starmap(open, ...), functools.reduce(open, ...)), matching the
bare-name map/filter form; the writer-check on the first arg keeps a benign
itertools.starmap(len, ...) or itertools.chain(...) safe.
Regression rows added to test_permission_mode.py.
* Close more auto-mode gaps and align the ask confirm fold across paths
Each classifier change reproduces with a benign control:
- MCP read-named tools now ask on reply / notify verbs (get_and_reply_email,
list_and_notify_users), on catalog writes COMMENT ON / SECURITY LABEL / LOCK
TABLE and CREATE|DROP|ALTER POLICY, and on state-changing PostgreSQL functions
inside a read-shaped SELECT (nextval, set_config, pg_notify, the advisory-lock
family). A 'comment' column, a 'locks' table, and a 'nextval' column prefix
stay safe; the natural-language NOTIFY/SET ROLE statement forms are left out
because SET/NOTIFY overlap ordinary prose.
- Python auto mode now gates loader.exec_module (runs a module's code), archive
extractall (zip-slip file writes), the ensurepip / venv modules (install pip /
build an environment), and pydoc.writedoc. The Hugging Face login token
(~/.cache/huggingface/token and stored_tokens) is now a sensitive path, while
the rest of that cache (model data) stays readable.
- ChatCompletionRequest no longer overwrites an explicit confirm_tool_calls=false
when permission_mode='ask': the fold only self-enables the gate when the flag
is unset, so an explicit opt-out wins on the chat path exactly as it already
does via _permission_mode_confirm and the Anthropic pre-switch guard.
Regression rows added to test_permission_mode.py.
* Gate sort -T, xxd outfile positional, and the legacy HF token path
- sort -T / --temporary-directory writes spill files to a caller-chosen dir,
so it joins -o / --output in sort's unsafe-flag set.
- xxd [infile [outfile]] writes its second positional, like uniq; xxd now uses
the same second-positional-write handling (xxd in.bin out.hex asks, xxd
in.bin and xxd -c 16 in.bin stay read-only).
- The sensitive-path regex now also covers the legacy ~/.huggingface/token
location (optional leading dot), not just ~/.cache/huggingface/token; an
unrelated dir like myhuggingface/token stays safe.
Regression rows added to test_permission_mode.py.
* Catch multi-char SQL mutation targets, globbed credential names, digit outfiles
Three fail-open gaps in the auto-mode classifier, each with a benign control:
- SQL: the trailing word boundary on the MCP mutation regex meant a bare \w
stopped at the first character, so TRUNCATE users, GRANT SELECT ON t, and
REVOKE ALL ON t (multi-character names) slipped through while single-letter
targets matched. Match the whole identifier instead, and accept an explicit
AS alias on UPDATE (UPDATE users AS u SET). The implicit-alias form is left
out because it is indistinguishable from the prose "update <noun> <noun> set".
A truncate_log column and a grants table stay safe.
- A glob that resolves to a credential basename anywhere (cat ~/.huggingface/tok?n
-> token, cat proj/.netr? -> .netrc, cat repo/.aws/cred*) now asks; the fixed
target list only covered a handful of home paths. notes/dra?t.txt and
token_counts.tx? stay safe.
- uniq / xxd counted file positionals but skipped every numeric token to ignore
a flag value, so a file literally named with digits (uniq 123 out) hid the
output positional. Track each command's value-taking flags and consume only
the value, so uniq -f 2 in stays safe while uniq 123 out asks.
Regression rows added to test_permission_mode.py.
* Isolate the permission-mode loop tests from process-global state
The loop-driving tests (auto/off/full/bypass) drove run_safetensors_tool_loop
against a process-global approval registry (state.tool_approvals._pending)
keyed by a single shared session id, and read os.environ. Other backend test
modules mutate both, some at import time, so in the full-suite ordering a stale
pending approval or a leaked env var could make the loop deny or skip a call
these tests expect to run. It passed when the file ran alone but failed only in
the complete tests/ run on CI.
Add an autouse fixture that snapshots and restores os.environ and the approval
registry around each test, and give every _drive call a unique session id so a
leaked approval can never collide. Attach a compact event-stream dump to the
loop assertions so any residual full-suite-only failure reports what the loop
actually did instead of a bare diff.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: harden auto-mode classifier for recursive listers, sort file lists, aliased invokers, single-member extract
Close four fail-open gaps in is_potentially_unsafe_tool_call:
- terminal: tree/du (always recursive) and ls -R rooted at an absolute or
tilde path now ask, matching the existing grep/rg/find recursive-read gate;
relative walks stay safe.
- terminal: sort --files0-from=F reads the file list named in F, so it can
read arbitrary host files indirectly; added to sort's unsafe flags.
- python: track aliases of the higher-order invokers (m = map;
from itertools import starmap as sm) so an aliased invoker handed open/a
writer is still gated; a benign callable (map(len, ...)) stays safe.
- python: single-member archive extract (ZipFile/TarFile.extract) writes to
disk like extractall and is vulnerable to a crafted member path, so gate it.
Also update the stale _FakeExecuteTool in test_permission_mode.py to accept
the thread_id keyword that run_safetensors_tool_loop now forwards to
execute_tool after the main merge, which had broken the five tool-loop tests.
Adds regression rows covering each gap plus benign controls.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: normalize unknown permission_mode to 'ask' instead of a 422
The request models validated permission_mode with Literal[ask, auto, off,
full], so an unrecognized value from a newer UI/client was rejected with a 422
before the tool loops could apply their unknown -> ask fallback
(safetensors_agentic.py:464, llama_cpp.py:9001). That made the intended
forward-compat degradation unreachable at the API boundary for both Chat
Completions and the analogous Anthropic field.
Accept a plain string on both ChatCompletionRequest and AnthropicMessagesRequest
and normalize in a before-validator: None stays unset, the four known modes pass
through, and any other value degrades to the safest gate ('ask'), matching the
loops. Adds a regression test covering unknown/None/known across both models.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: close five more auto-mode classifier gaps
- terminal: xargs is no longer a safe wrapper. It appends arguments read from
stdin that the scan never sees, so `echo -o out /etc/passwd | xargs sort`
forwards to `sort -o out /etc/passwd` (a write + sensitive read) while only
the allow-listed literals are visible. Any xargs command now asks.
- terminal: ionice -p/-P/-u change the I/O priority of an already running
process / group / user instead of forwarding to a wrapped read-only command,
so `ionice -c 3 -p <pid>` now asks. ionice -c 3 <cmd> stays safe.
- MCP: gate ALTER SYSTEM, which persists PostgreSQL server configuration and was
not one of the DDL objects the mutation detector matched.
- MCP: a credential noun in a read-named tool (read_secret, list_tokens,
get_credentials, fetch_api_key) is a sensitive disclosure, so it asks even
without a mutating verb or a path/SQL argument. Scoped *_key nouns keep a
primary_key / keyboard lookup safe.
- render_html: no longer unconditionally safe. A static canvas still auto-runs,
but one whose HTML/JS reaches the network (fetch/WebSocket/remote script) asks,
since it can egress under the canvas CSP when artifact network access is on.
Its early provisional card is suppressed under the auto confirm gate, and the
confirm-without-stream guard now requires a stream when render_html is
selectable.
Adds regression rows and benign controls for each, and updates the render_html
provisional-card and confirm-gate tests to the new behavior.
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* Studio: extend auto-mode gates for indirect file lists, dynamic lookups, HTML network loads, and Anthropic render_html
Follow-ups on the previous classifier round:
- terminal: wc/du/find --files0-from (and find's -files0-from primary) read a
NUL-separated list of input paths from a file, the same indirect mechanism as
sort --files0-from, so a crafted list reads arbitrary host files past the
literal path/root checks. Gate them like sort.
- python: a namespace lookup through a dict-style call (f =
__builtins__.__dict__.get('open'), globals().get('open'), vars(x).get(...))
can return open/eval/a mutator, so poison the bound name like getattr/subscript
lookups already are. An ordinary dict .get or os.environ.get stays safe.
- render_html: broaden the network detector so a canvas that loads a resource
via CSS url()/@import, srcset, or a root-relative (/path) or protocol-relative
(//host) src/href is treated as networked, not just fetch/WebSocket/remote
script. Relative ./x and url(#id)/data: refs stay static/safe.
- Anthropic /v1/messages: drop render_html from the unprompted-safe server-tool
set. Since it can prompt (networked canvas) and this channel invokes the loop
without confirm, selecting it under ask/auto/omitted now rejects like
terminal/python; off/full (or an explicit confirm opt-out) run it.
Adds regression rows and benign controls for each, plus an Anthropic route test.
* Studio: close six more auto-mode classifier gaps
- terminal: a glob that expands to a project .env (cat .e?v) now asks; .env
joins the sensitive glob-basename set, matching the literal-path gate.
- python: an open bound onto an attribute (box.f = open; box.f('out','w'))
is tracked by attribute name, and open invoked via .__call__
(open.__call__('out','w'), unwrapped to the underlying callable) is gated,
so neither slips past the name-based open-alias checks. Benign attribute
callables and .__call__ on non-writers stay safe.
- python: a namespace lookup via .get/.pop/.setdefault already covered the
builtins case; unchanged here.
- MCP: a mutating HTTP verb in a method/verb argument (get_url
{"method": "DELETE"|"POST"|"PUT"|"PATCH"}) now asks, so a generic HTTP
tool cannot mutate an external service unprompted; GET/HEAD stay safe.
- MCP: a credential/secret environment-variable value (get_env
{"name": "OPENAI_API_KEY"}) is treated as a sensitive read via the same
credential-noun match used for tool names; PATH/HOME stay safe.
- render_html: self-navigation sinks (location.assign/replace, window.open,
assigning a URL to (window.)location(.href)) join the network detector, so a
canvas that navigates itself to an external URL asks; location.reload() /
history.back() stay static.
Adds regression rows and benign controls for each.
* Studio: gate obfuscated canvas egress, sensitive-dir iteration, and MCP metadata-host reads
- render_html: strip block comments before the network scan so fetch/*x*/(...)
cannot hide egress, and match bracket-access forms (window['fetch'](...),
self['open'](...)). Line // comments are left alone so the // in an https URL
is not eaten. A comment-only canvas stays static.
- python: enumerating a directory outside the sandbox (Path('/etc').iterdir(),
os.scandir('/etc'), os.listdir('/home'), os.walk('/')) reads host filenames
the direct /etc/passwd checks would prompt for, so gate it when the target dir
folds to an absolute/tilde/sensitive path; a relative dir stays safe and an
unresolved dynamic dir is left to other checks.
- MCP: a read-named HTTP tool pointed at a cloud-metadata / link-local host
(fetch_url {"url": "http://169.254.169.254/..."}, metadata.google.internal)
reads instance credentials, so classify those URL arguments as sensitive,
mirroring the sandbox SSRF blocklist; ordinary and localhost URLs stay safe.
Adds regression rows and benign controls for each.
* Studio: gate meta-refresh navigation, pandas HTML/markdown exporters, absolute glob roots, and checksum verify mode
* Studio: gate starred open writes, builtins.__import__, computed render_html sinks, and procfs fd reads in auto mode
* Studio: gate remote worker canvases, huggingface_hub downloads, and write callables passed to user helpers in auto mode
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Unsloth <michaelhan@Michaels-MacBook-Pro.local>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Studio: offer the latest transformers release for brand-new architectures
When a model's config.json model_type is absent from every installed
transformers overlay (base 4.57.x and the .venv_t5_530/550/510 sidecars),
Studio now checks, unauthenticated and cached, whether the newest
transformers ships it:
- utils/transformers_latest.py fetches the latest release version from
https://pypi.org/pypi/transformers/json and the CONFIG_MAPPING_NAMES
sources for that tag and for main from raw.githubusercontent.com
(never api.github.com), parsing them with the same AST extractor the
static router uses (no code execution, no trust_remote_code). Results
are cached in memory and in a JSON snapshot under studio_root()/cache
with a one day ttl; fetches are bounded to 5s with one retry and a
failure backoff, and offline mode or the new kill switch
UNSLOTH_STUDIO_NO_LATEST_TRANSFORMERS=1 short-circuits to None.
- POST /api/inference/validate gains requires_transformers_upgrade plus
a transformers_upgrade payload (model_type, pypi_version,
supported_in_pypi, supported_in_main) so the frontend can raise the
install consent dialog before /load, mirroring the existing
remote-code consent flow. The check fires only when the model_type is
unknown to all installed overlays and the hardcoded tier tables.
- POST /api/inference/install-latest-transformers provisions a new
persistent .venv_t5_latest sidecar after user consent, pinned to the
exact PyPI version (re-verified server-side) with the same
--target/--no-deps recipe as the fixed sidecars. A JSON pin marker
inside the dir records the installed package set, so restarts
revalidate it and routing resolves the new highest-ranked tier
automatically. A dependency preflight (compat_plan) compares the
release's requires_dist against the running env: unsatisfied
tokenizers/safetensors floors are shadow-installed as exact pins into
the sidecar, anything else unsatisfied blocks the install with a
clear message.
Routing for every already-supported model_type is unchanged: the
hardcoded lists and the 530/550/510 static resolver run first, the new
tier only participates once its venv exists, and the probe order gains
the latest sidecar only when provisioned. Verified against live PyPI
and GitHub (transformers 5.13.0: 674 model_types, 26 absent from all
installed overlays, e.g. cosmos3_omni; 4 dev-only on main) and with a
real sidecar install plus restart persistence. 64 new tests; the
existing 200-test transformers_version suite passes unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Latest-transformers check: fetch outside the lock, serialize installs
Release the module lock during the network refresh so a slow fetch cannot
stall other threads in the ASGI pool; concurrent callers during a fetch get
None (the graceful fallthrough) via an in-flight flag instead of stacking
fetches. Serialize install_latest_transformers with an in-progress flag so
concurrent consents cannot race the sidecar delete and recreate; the loser
gets a structured already-in-progress refusal.
* Latest-transformers check: LoRA bases, pin-gated mapping, live reverify
Run the upgrade check over the [adapter, base] target set so a LoRA whose
base model is a brand-new architecture surfaces the prompt (the worker
activates transformers for the base, not the adapter).
Gate the latest overlay's mapping lookup on a valid pin marker, matching
activation and the probe order, so a partial or manual .venv_t5_latest dir
cannot be routed to and then refused at activation.
Re-verify the requested version against a live PyPI snapshot at install
time, falling back to the cached one on fetch failure, so a release
published inside the cache TTL is not silently missed.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Latest-transformers check: nested config types and latest-tier vision probe
Collect every model_type in the config (top level plus each nested
sub-config) and signal on the first one missing from all installed
overlays, so a supported wrapper carrying a brand-new backbone still
surfaces the upgrade prompt; wrappers instantiate sub-configs through
CONFIG_MAPPING and would fail on the nested type.
Route the vision capability subprocess through the pinned latest sidecar
when the model resolves to the latest tier, so latest-only VLMs are not
misclassified as text-only; every other tier keeps the 5.5 sidecar used
today.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Latest tier: nested routing, vision probe after raw miss, safe upgrades
Route by every model_type in the config: a nested sub-config type can raise
the tier (wrappers instantiate sub-configs through CONFIG_MAPPING), so a
supported wrapper with a latest-only backbone routes to latest once
installed instead of staying on default. An unknown nested type never
vetoes; the primary type keeps its previous semantics. The collector is
shared with the upgrade checker.
Vision detection: when the raw heuristics say False for a model that routes
to the latest tier, run the AutoConfig subprocess under the pinned latest
sidecar instead of trusting heuristics built from older transformers.
Provisioning: stage-and-swap. Build the new sidecar in .venv_t5_latest.staging
and swap it in only when the install and pin marker are complete, so a failed
upgrade never destroys a previously working sidecar; restore the old dir if
the final swap fails.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Latest-transformers checker, vision subprocess, and cache fixes
Require the latest release to support every missing model_type (the
primary included) before prompting; a nested-only match cannot make the
model loadable, so no install is offered for it.
The vision-check subprocess now unions the active sidecar's own
registry mappings into the inlined parent-process detection sets, so
architectures only the sidecar knows classify correctly.
A successful sidecar install clears the tier probe cache, the latest
tier's model_type mapping, and the vision-detection cache so the new
venv takes effect without a restart. Tests for all three.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Aggregate upgrade support flags and keep install off /v1
The upgrade signal now reports supported_in_pypi only when the latest
release covers every missing model_type; a mix with a main-only nested
type surfaces as dev-only so no PyPI install is offered that would
still fail at load. The consented install endpoint moves to
studio_router so it is not reachable through the OpenAI-compatible /v1
mount. Tests for both.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Honor the latest-transformers kill switch in routing
With UNSLOTH_STUDIO_NO_LATEST_TRANSFORMERS set after the sidecar was
provisioned, the latest tier still joined mapping and probe routing
because only the pin was checked. Both admission points now also check
the kill switch, so operators can roll back a problematic sidecar
without deleting files.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Repair the latest sidecar through stage-and-swap
The lazy repair path installed into the live .venv_t5_latest, which
_ensure_venv_dir wipes first, so a failed repair deleted the pinned
sidecar and its marker. Both the consented install and the repair now
share one stage-and-swap helper: the incomplete-but-pinned dir survives
any failure and a later attempt can still repair it.
* Tighten comments
* Remove the staging dir when a latest-sidecar install fails
A pip failure inside _ensure_venv_dir returns False without raising, so
the except cleanup never ran and the partial .venv_t5_latest.staging
leaked until a later attempt. Also note on the validate response fields
that frontend consumption ships in the follow-up PR.
* Add the transformers-upgrade consent dialog to the frontend
When /validate reports requires_transformers_upgrade, every explicit load
path (chat runtime and the compare composer) now pauses on a consent
dialog modeled on the remote-code one: it names the model_type and the
latest PyPI transformers version, and on Accept calls
/api/inference/install-latest-transformers itself, shows an installing
state, and resumes the original load automatically on success. Errors
surface in the dialog with a retry; Cancel aborts the load like the
trust dialog's deny path. Architectures shipped only on transformers
main get a dev-only notice with no install button. Background auto-load
skips upgrade-requiring candidates instead of prompting, mirroring the
trust_remote_code rule. The dialog mounts once in the root layout and
runs before the security dialogs, since no load can proceed without the
runtime.
* Route a non-installable new architecture to the custom-code consent as a last resort
When the upgrade dialog has no installable PyPI release (the architecture
is only on transformers main, which Studio never installs), the dialog now
says so explicitly, and when the model also declares custom (auto_map)
code it offers Continue with custom code: resolving the paused load into
the existing trust_remote_code consent gate instead of hard-aborting.
Models with no custom code keep the Cancel-only notice. The backend
returns no upgrade signal at all for architectures unknown to both PyPI
and main, so those still route straight to the unchanged security gate.
* Force a 16-bit load for models on the latest-transformers sidecar
Live validation with Zyphra/ZAYA1-8B (model_type zaya, shipped by
transformers 5.13.1 but unknown to every installed tier) surfaced a
generation crash when the consented sidecar load kept the default bnb
4-bit quantization: transformers' grouped-MoE kernels feed the packed
uint8 expert weights straight into torch._grouped_mm, and generation
dies (plain 16-bit works). New latest_tier_active_for() mirrors the
sidecar activation's tier resolution and never raises; the inference
worker flips load_in_4bit off when it reports true, and the load route
applies the same flip so the pre-load VRAM guard and the worker command
agree. Fixed tiers are untouched. With the guard, ZAYA1-8B loads and
generates correctly in Studio chat.
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* Offer the custom-code fallback when a latest-sidecar install fails
* Fail remote mapping fetches wholesale and mirror the 16-bit flip in validate
A transient fetch or parse failure of one auto-mapping file no longer caches
a partial latest-release map for the TTL (a real 404 on pre-5.10 tags is
still tolerated), and validate_model now applies the same latest-sidecar
16-bit sizing flip as /load before the training guard so the two agree.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Tighten comments in the latest-transformers changes
* Resolve remote LoRA bases, fold nested tiers, and guard the sidecar swap
latest_tier_active_for now resolves a remote adapter's base model the same
way worker pre-activation does (and returns early without a sidecar pin), a
hardcoded fast-path tier is raised when a nested sub-config's model_type
needs a higher sidecar, and the install route refuses to swap .venv_t5_latest
while training runs on it and unloads a latest-tier chat model first.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Gate the sidecar install on worker liveness and size installable upgrades 16-bit
The install route now refuses while any training or export runs (tier
re-resolution without the load token is unreliable for gated repos), holds
the inference lifecycle gate across the unload and the swap so no load can
interleave, and passes the model name to unload_model. validate_model runs
the upgrade check before the training guard and sizes an installable
upgrade as 16-bit, matching what /load and the worker will force after the
consented install.
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* Close the sidecar install races and honor the kill switch over cached mappings
Training starts and mutating export routes now refuse while a transformers
install is in progress (shared is_install_in_progress flag), the chat unload
and idle export-worker teardown moved into a before_swap hook that runs only
once the staged install succeeded, and _config_model_types checks the kill
switch before returning a cached latest mapping.
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* Reserve the sidecar swap before the gate wait and abort it on failed teardown
The install-in-progress flag moved into a shared sidecar swap reservation in
transformers_version, taken by the install route before awaiting the
inference lifecycle gate (so training and export starts see it for the whole
window) and by the lazy .venv_t5_latest repair path. The before_swap hook
now raises when the chat unload or export teardown reports failure, leaving
the previous sidecar untouched.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Back the sidecar swap reservation with a cross-process lock file
The lazy repair runs inside worker subprocesses, where a module-level flag
is invisible to the parent's route checks. The reservation now also creates
a lock file next to .venv_t5_latest (O_EXCL, owner-only removal, stale after
two hours for crashed owners), so is_install_in_progress sees a repair from
any Studio process.
* Hand the swap reservation to the installer thread and harden pre-swap teardown
A cancelled install request no longer releases the reservation while the
installer thread is still staging (the thread owns and releases it, shielded
from cancellation). The route refuses while another inference request is
generating, export teardown runs before the chat unload and is judged by
worker liveness rather than the cleanup return value, and a live inference
worker with no active model (failed load residue) is shut down before the
swap.
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* Keep the lifecycle gate with the installer and recheck the swap at spawn time
The gate moved into the shielded install task so a cancelled POST cannot
release the guard /load honors while the installer still runs, cached latest
probe results are ignored while the kill switch is set, and the training and
export subprocess spawns recheck the sidecar swap reservation right before
spawning (the route-level guards are one-shot and validation can outlast an
install's start).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Close the spawn-registration windows against the sidecar install
Training marks the spawn in progress before its reservation recheck and
is_training_active honors the flag, so the install route sees a start that
has passed proc.start() but not yet recorded _proc. Export load-checkpoint
rechecks the reservation after setting _export_active and before tearing
down the old worker, so losing the race keeps the loaded checkpoint instead
of surfacing a 500.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Refine the install-window interleavings around worker teardown
The inference busy count is rechecked under the lifecycle gate (streams
start by taking that gate, so nothing slips past a held gate), the training
handshake moved ahead of the VRAM-freeing before_spawn hook so a lost race
leaves chat/export intact, the export spawn-time check is op-aware (inside
an active op the install is the side that aborts), and the Xet-stall respawn
waits out a transient reservation instead of stranding the run.
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* Track the install's server-side unload and guard export ops against the swap
The upgrade dialog store records when its install actually ran (the server
unloads the active chat model before swapping), and the load flow then marks
the previous model as unloaded so a later cancelled gate still triggers
rollback; the custom-code fallback leaves the flag unset. _run_export gained
the same reservation handshake as load_checkpoint so an install cannot block
behind an hours-long export op instead of returning 409.
* Tighten comments in the install-guard and upgrade-consent changes
* Surface install-race refusals cleanly and roll back after a failed swap unload
/load refuses while the sidecar swap is reserved so a load cannot succeed
and immediately be unloaded by the pre-swap teardown, worker starts that
lose the install race raise a typed SidecarSwapInProgress mapped to 409
instead of a 500, the install response reports model_unloaded even on a
structured failure so the client can restore its state, and the compare
flow tracks the server-side unload like the primary load path and clears a
stale checkpoint on abort.
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* Type the export install races, scope the lock release, and keep the unload signal
Export load-checkpoint and export ops raise SidecarSwapInProgress (mapped to
409 in every export route) instead of a 400-shaped failure, the export spawn
check distinguishes repair reservations (always refused) from install ones
(op-aware), the swap lock release only unlinks a lock this process wrote so
a stale-superseded owner cannot drop the new owner's live lock, and the
frontend unload signal survives a superseding consent via read-and-clear
consumption instead of a reset.
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* Finalize a stalled run when the respawn loses the install race and latch the unload signal
The Xet-stall respawn timeout now finalizes the run as a failure instead of
raising into the pump's broad finalization catch (which stranded it in a
training state with no worker), and a successful install retry ORs the
model_unloaded signal with the latched value so a failed-after-unload first
attempt still triggers rollback.
* Recheck the swap under the load gate and latch the unload before resolver checks
/load rechecks the sidecar reservation after acquiring the lifecycle gate
(an install can reserve while the load queues on it), and the dialog store
latches model_unloaded as soon as the install response arrives, before any
resolver-identity guard, so a superseded consent's unload still reaches
whichever load consumes the signal next.
* Report cleared-state unload failures, guard queued installs, and fold name tiers
A failed chat unload that still cleared the orchestrator's model state now
reports model_unloaded so the client rolls back, the installer aborts with
a 409 when a model load completed while it waited on the lifecycle gate,
and the fixed-tier name fast path consults the config mapping when a latest
sidecar is pinned so an accepted upgrade routes to the sidecar it installed
(no I/O added to the unpinned path).
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* Report cleared-state unload failures and harden the spawn handshake flag
The failed-unload branch in before_swap now detects that the orchestrator
cleared its model state and reports model_unloaded before aborting (the
earlier commit claimed this fix but a scripting error dropped the edit),
the installer's queued-load check compares a load generation counter so a
same-model reload is caught, and both training spawn sites wrap everything
after the handshake in a guard that resets _spawn_in_progress on any
exception so a failed start cannot wedge is_training_active.
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for more information, see https://pre-commit.ci
* Bump the load generation when the load is published, not at load start
A start-time bump is already visible when the installer snapshots mid-load,
so a same-model reload completing after the snapshot looked unchanged and
could be unloaded by the swap. The counter now increments alongside the
active_model_name publish.
* Self-heal a broken pinned sidecar, guard lazy repairs, and refresh stale retries
A valid pin whose transformers source dir vanished now triggers the repair
from the routing path (with a five minute backoff after failures) instead of
silently routing latest-only models to older tiers, the lazy repair refuses
while parent-visible chat/training/export workers are active since it has no
teardown of its own, and a version-mismatch install failure carries the
superseding release so the dialog's Retry re-requests a version that can
succeed.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Flip latest-tier loads to 16-bit outside chat and protect export state
Training and export workers now apply the same latest-sidecar 16-bit flip
as the chat worker so a brand-new grouped-MoE architecture cannot reach bnb
4-bit through those paths, the latest-tier vision override returns None on
an inconclusive probe so a transient failure is not cached as not-vision,
and the install route refuses while an idle export checkpoint is loaded
rather than discard it with no rollback signal on a failed swap.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address parallel-review findings on the sidecar guards and install checks
The training route sizes latest-tier jobs 16-bit before GPU selection, the
inference subprocess spawn rechecks the swap reservation like training and
export (covering the OpenAI auto-switch path) with the typed error mapped
to a retryable 409, compat_plan blocks the install when dependency metadata
cannot be fetched instead of proceeding unverified, snapshot model-type
lists must contain only strings, and pin-marker package specs are validated
against the sidecar's own package set before ever reaching pip.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Parent-only repairs, live-owner locks, remote-base activation, pre-teardown recheck
Lazy sidecar repairs now refuse inside worker children (whose empty backend
singletons cannot see live siblings) and run only in the parent where the
active-worker guard is real, swap-lock staleness requires the owner pid to
be dead so a slow live install is never superseded, both activation entry
points resolve a remote adapter's base model like the inference worker and
latest_tier_active_for already do, and load_model rechecks the reservation
before tearing down the old worker so losing the race keeps the current
model loaded.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Check workers under the repair reservation and keep state on refused swaps
The lazy repair now reserves first and checks workers under the reservation
(worker starts set their active markers before rechecking, so every
interleaving aborts one side), with export ops and in-flight inference loads
counted as active. The inference pre-teardown and spawn guards refuse only
repair reservations since an install shares the load's lifecycle gate and
aborts via its queued-load snapshot, a SidecarSwapInProgress raised before
teardown no longer clears the live model mirrors, and an export spawn abort
after teardown clears current_checkpoint so the page cannot claim a loaded
checkpoint with no worker.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Repair a present-but-incomplete latest sidecar from routing
The routing self-heal only fired when the pinned sidecar's transformers/
dir was missing. A sidecar that kept transformers/ but lost another pinned
package still routed models to the latest tier, and workers refuse
parent-only repairs, so every load failed until a manual reinstall. Routing
now validates the full pin (via _venv_dir_is_valid) and repairs any
incomplete sidecar under the same swap reservation and 5-minute backoff.
* Treat an unrepaired latest sidecar as unavailable in routing
When the pinned sidecar is incomplete and the lazy repair fails (offline,
pip failure, workers active) or is inside the backoff window, routing
returned the source dir anyway, sending models to a tier whose worker
activation is known to fail. Return None instead so models an older tier
supports keep loading there until a repair succeeds, matching the behavior
when the sidecar dir is missing entirely.
* Harden sidecar swap and repair against crash, survivor, and 16-bit paths
Reclaim a swap lock as soon as its recorded owner PID is dead instead of
waiting out the two-hour cutoff, so a crash mid-install no longer wedges
/load, training, export, and repair for hours. A lock whose PID cannot be
read yet still uses the long cutoff so the create-before-write window is
never mistaken for dead.
Probe process liveness with OpenProcess on Windows: os.kill(pid, 0) there
is CTRL_C_EVENT (a real Ctrl+C via GenerateConsoleCtrlEvent), not a
harmless check, and psutil is not always present.
Return whether _shutdown_subprocess actually killed the worker and keep the
live handle when it survives terminate/kill (an uninterruptible CUDA
syscall can outlive SIGKILL). The pre-swap liveness guard now trusts that
result, so the destructive .venv_t5_latest rename cannot proceed while a
live worker still holds sidecar modules.
Recover a sidecar stranded at .old when a swap's activation rename and its
rollback both fail: reading the pin restores it when no swap holds the
reservation, so latest-tier models are not permanently broken.
Resolve the latest tier in the parent for export loads and for explicitly
16-bit training runs, not only 4-bit ones: tier resolution self-heals an
incomplete sidecar, and repairs are parent-only, so those paths could not
recover before. Sidecar integrity and quantization are independent.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Revert the parent-side latest-tier repair probe on training and export loads
The probe ran before the route freed VRAM, so a resident chat or export worker
made _workers_active_for_repair() refuse the parent-only repair; the route then
tore that worker down and spawned a child that also cannot repair, so an
incomplete sidecar still failed to load. Repairing correctly requires running the
repair between the worker teardown and the child spawn, decoupled from VRAM
sizing, which is a larger change tracked separately. Restore the prior behavior
so these paths match the reviewed form and do not partially attempt a repair that
cannot complete while workers are resident.
* Honor failed worker shutdowns on load and revalidate the cached latest mapping
The fresh-load paths spawned a new worker straight after _shutdown_subprocess
without checking its result, so a worker that outlived terminate/kill (a wedged
CUDA syscall) had its handle overwritten by the replacement while it still held
GPU memory, and is_worker_alive/the pre-swap guard could no longer see it. Both
the inference load and the export checkpoint load now abort when the old worker
did not exit, so the load can be retried once it does.
_config_model_types returned a cached latest mapping without re-checking the
sidecar, so a sidecar deleted or broken in-process after its first parse was
never re-validated: routing kept sending latest-only models to the stale latest
tier while activation failed. The cached latest mapping is now dropped and
re-resolved (self-healing) when the sidecar is no longer intact.
* Drop cached latest mapping when the pin is gone; keep 4-bit for custom-code fallback
_latest_sidecar_intact now returns False when the pin marker itself is gone, not
just when a pinned package is missing. Otherwise a cached latest mapping outlived
a deleted pin: _config_model_types kept returning it, so routing sent latest-only
models to a tier whose worker activation then failed (no pinned version) until
restart. It now drops the cache and re-resolves to no latest tier. The
_overlay_transformers_dir caller already gates on a present pin, so it is
unaffected.
validate_model forced 16-bit sizing whenever a PyPI upgrade was merely offered,
even for a model that can fall back to its own auto_map code. /load loads such a
model 4-bit without the install, and the install route refuses while training is
active, so 16-bit sizing here returned a VRAM 409 for the only viable 4-bit path.
The offered-upgrade flip is now gated on the absence of a custom-code fallback;
an already-active latest sidecar still always sizes 16-bit.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* fix(studio): recover mlx vlm image prompts
* fix(studio): detect serialized vlm media items
* studio: recover MLX VLM prompts when model_type only lives on _config
_mlx_vlm_model_config only fell back to _config when config was entirely
missing, so a model that exposes a config without a model_type (while _config
carries it) skipped model-aware recovery. Prefer whichever of config / _config
actually has a model_type. Adds a focused test.
* [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>
* Studio: force-terminate a stuck training stop after a grace period
A Stop-with-save only signals the worker and waits for it to save and exit;
force_terminate() was reachable only from the /reset cancel path. On Windows +
ROCm the worker saves the adapter fine but then wedges in post-save GPU/HIP
teardown and never exits, so the run stays in "Stopping..." forever, is_training
stays true, and /reset returns 409.
Add a stop watchdog: when a stop is requested, a daemon escalates to
force_terminate() a short grace after the worker's "complete" (save done), or
after an absolute cap covering a hang during save. After escalation the parent
state is finalized (is_training=False, "Training stopped.") even if the OS never
reaps the wedged worker, so the UI leaves "Stopping..." and a new run can start.
No behavior change on a clean quick exit. Grace and timeout are configurable via
UNSLOTH_STUDIO_TRAINING_STOP_GRACE_S (15) and
UNSLOTH_STUDIO_TRAINING_STOP_TIMEOUT_S (120).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: harden the training stop watchdog per review
Address review feedback so a stop can never corrupt a checkpoint or leave the
run stuck:
- Never force-kill an in-progress save. The absolute cap is now a last-resort
backstop: raise the save default to 600s and only kill past that long window;
a not-yet-complete save is not treated as a hang. Cancels have nothing to save,
so they keep a shorter 120s cap via UNSLOTH_STUDIO_TRAINING_CANCEL_TIMEOUT_S.
The save vs cancel path is now explicit and the backstop logs a clear warning.
- Always finalize even if force_terminate raises on a wedged child (try/finally),
so the watchdog never dies leaving the run in "Stopping...".
- Preserve output_dir when the watchdog finalizes so a saved checkpoint is still
recorded in run history.
- Track the watched process per watchdog: a new run always gets its own watcher,
and a stale watchdog on an old proc no longer suppresses it.
- Terminate only the captured proc; force_terminate revalidates under the lock
that it is still the current worker, so it can never kill a fresh run.
- Name the watchdog thread for debuggability.
* studio: tighten training-stop watchdog comments
Comment-only pass: collapse the watchdog docstrings and inline notes to fewer
lines while keeping the rationale. No behavior change.
* Studio: make the stop watchdog safe against concurrent runs and the pump
Target-scope the escalation finalize so a stale watchdog can never clobber a
run that replaced its worker: capture the watched proc and job id, and no-op
the finalize (handle, progress, and DB) when a new run has already taken over.
Honor a later cancel by tightening an in-flight save watchdog to the shorter
cancel cap. Serialize the DB helpers on the lock so the watchdog and pump can
no longer double-create, double-finalize, or corrupt the metric buffer when a
force-terminate hands off to a still-finalizing pump.
Add regression tests: finalize no-ops when superseded, finalize runs for its
own worker, a later cancel tightens the cap, finalize is single-winner under
concurrency, finalize honors expected_job_id, and concurrent flushes claim
each metric exactly once.
* Studio: close the remaining stop-watchdog vs start/pump races
Guard the escalation finalize by the watched job id in addition to the proc:
start_training sets current_job_id before it installs the new _proc, so a stale
watchdog entering during that startup window still sees the old dead handle and
was not caught by the proc-only guard. Capture the job id when the watchdog
starts and require it to still match before touching state.
Snapshot the run id and final progress under the finalize lock and thread them
through the flush and finish_run calls, so a new run that starts between the
finalize claim and the DB writes cannot be flushed or marked stopped under the
old run's finalizer.
Publish _db_run_created only after create_run commits, gated by a dedicated
in-progress flag, so a concurrent finalize can no longer run finish_run against
a not-yet-inserted row and leave the run stuck as running.
Add regression tests for the startup-window job-id guard, run-id pinned flush,
snapshot-based finalize across a new run, and create-not-published-before-insert.
* Studio: finalize a force-stopped run by its captured id
If a new run starts in the gap after the watchdog clears _proc and marks the
backend idle, current_job_id changes, so the previous expected_job_id guard made
the finalize skip and left the stopped run recorded as running. Capture the run
id, metrics, and final progress under the lock (where current_job_id is still the
watched run) and finalize by that captured id via _finish_stopped_run: finish_run
is an idempotent UPDATE and insert_metrics_batch upserts, so a concurrent pump
finalize of the same run is harmless and a newly started run is never touched.
Add a test that the watched run is finalized by id with its buffered metrics, and
update the escalation tests to assert finalize goes through _finish_stopped_run.
* Studio: keep force-stop finalization retryable and unclaimed until the row exists
Only claim _run_finalized in the escalation when the DB row already exists; if an
early create failed and the pump is retrying it, claiming would make the pump's
later finalize no-op and strand the row as running, so leave the finalize to that
create-then-finalize path.
On a DB error in _finish_stopped_run (e.g. a transient SQLite lock), unclaim the
finalize and requeue the drained metrics when the run is still current, so the
pump or a later retry can still record the run stopped instead of leaving history
with an active run and lost metrics. A superseded run's state is never touched.
Add tests: no claim before the row exists, requeue+unclaim on a DB error, and a
superseded run left untouched on error.
* Studio: tighten stop-watchdog comments
Reduce the wording of the docstrings and inline comments added by this PR without
dropping any of the concurrency invariants (dual proc/job-id supersession guard,
finalize-by-captured-id, publish-after-commit, snapshot-under-lock, unclaim and
requeue on error). Comments and docstrings only; no code change.
* Studio: record the stopped run's DB state before dropping _proc
A wedged worker still reports alive, so the pump never reaches its own finalize
and bails on its _proc-is-None guard once the escalation drops the handle. So the
watchdog is the sole finalizer: record the terminal DB state (create the row if a
start-time create failed, then finish by captured id) BEFORE dropping _proc. While
the handle is held is_training_active() stays true, so no new run can start and
current_job_id stays the watched run for the write; _proc is dropped last, guarded
on target_proc so a run that did replace the worker keeps its handle.
_finish_stopped_run retries a transient DB error a few times (the pump can no
longer retry once _proc is gone) and unclaims on final failure only when the run
is still current. Add tests for create-then-finalize, retry-then-unclaim, and not
dropping a new run's handle.
* Studio: job-guard the DB create flags against a racing new run
_ensure_db_run_created publishes backend-wide _db_run_created and
_db_create_in_progress flags. When the watchdog creates a missing row for an
escalated stop, the killed worker lets a new /start proceed mid-create, so the
stale create could publish those flags against the new current_job_id, making the
new run skip inserting its own row (metric/finalize then target a missing run).
Publish the flags only when the captured job id is still current; the row is still
created by id, and the new run owns/creates its own. Also reset
_db_create_in_progress in start_training so a stale claim can't block a new run.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: persistent stdio MCP sessions so server state survives across tool calls
call_tool_sync spawned a fresh stdio subprocess per tool call
(keep_alive=False) and tore it down when the call returned, so any stateful
MCP server lost its state between calls: with @playwright/mcp,
browser_navigate opened the page in one subprocess and
browser_take_screenshot ran in a brand-new one, screenshotting about:blank.
Keep one connected client per (command, env) on a dedicated event-loop
thread and reuse it across calls:
- idle sessions are reaped after 5 minutes (in-flight calls excluded) and
everything closes at exit, preserving the old design's no-orphans property
- a dead subprocess is detected via is_connected() and retried once on a
fresh session; tool-level errors leave the session alone
- cancel and timeout semantics are unchanged, and a timed-out call does not
tear the session down
- updating a server's endpoint/env/enabled state or deleting it closes its
live session
- HTTP/SSE servers stay one-shot per call
* address review feedback
* fix stdio session cleanup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* address review: per-thread MCP scope, close-during-connect and abort races
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* address review: unblock no-limit calls on close, drain borrowers before close, scope closes to url+env
* don't retry sessions closed by config changes, re-verify server row before caching, keep env secrets out of generation keys
* fail fast on connect errors and make the stdio key-lock wait cancellable
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* quote MCP scope parts so IDs with colons can't collide
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* serialize per-session stdio calls, span one timeout budget across connect and call, hash urls in generation keys
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Harden persistent stdio MCP sessions: crash recovery, concurrency, scoping
- Evict a stdio session on any transport-level (non-ToolError) call failure and
do not replay it, so a mid-call subprocess crash can no longer poison the scope.
Never gate liveness on Client.is_connected() (it only reports that a session
object exists, not that the subprocess is alive); add a version-adaptive
dead-transport probe that works on fastmcp 3.0.2 and newer.
- Re-check closed/defunct/config and transport liveness after acquiring the call
lock, and retire a session before releasing the lock, so a queued same-scope
caller never reuses a session that another caller's timeout already retired.
- Force a ProactorEventLoop on Windows so the stdio transport can always spawn
subprocesses regardless of the active event-loop policy.
- Scope stdio sessions per conversation: require thread_id to persist, and tag
the fields so a session_id and a thread_id with the same value cannot collide.
A session_id alone is project-wide, so it now falls back to a safe one-shot
session instead of sharing browser/DB/REPL state across conversations.
- Forward thread_id on the Anthropic Messages path.
- Treat timeout=None as unlimited on connect and the key lock (was capped at 60s).
- Bound the session cache (default 32, override via
UNSLOTH_STUDIO_MAX_STDIO_MCP_SESSIONS) with LRU eviction of idle sessions.
- Run config_check on cache hits, and log a redacted exe#digest label instead of
the raw command so credentials in argv never reach the logs.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Trim the stdio MCP session cache on release and skip close-generation for HTTP servers
Two fixes from review of the persistent stdio session lifecycle:
- Re-enforce the session cap when a session goes idle. A concurrent burst of
distinct-scope calls can overshoot the cap while every cached session is busy
(insert-time eviction only reclaims idle sessions), and the overshoot used to
persist until the 5-minute idle reaper. _release_stdio_session now trims the
idle overshoot back within the cap, without ever evicting an in-flight call.
- close_stdio_sessions() now no-ops for a specific non-stdio (HTTP/SSE) url.
Those transports are never cached as stdio sessions, so calling it on every
HTTP server update or delete used to accrue an unbounded close-generation entry.
Both are covered by regression tests that fail before the change and pass after.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Keep the live stdio MCP session across a display-name rename
The edit dialog resends url, headers, and use_oauth unchanged whenever a
server is saved, so gating the tool-cache invalidation and stdio session
close on field presence dropped the persistent process on a plain rename
or any no-op edit. Gate on a real value change against the stored row so
only a genuine endpoint, auth, or enable change closes the session.
Regression tests: a rename that resends unchanged url/headers/oauth keeps
the session; a real command change still closes it.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Tighten comments in the stdio MCP session lifecycle
Collapse a few verbose comments to fewer lines with the wording preserved,
and drop one that restated the clear_oauth_tokens_async docstring. Comments
only; no code change.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
* MCP image handling
* clean upg
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: return MCP error results so image content is not dropped
FastMCP client.call_tool raises ToolError by default on an is_error
result, so it never reaches _flatten_result and any returned image is
dropped. Pass raise_on_error=False so error results flow through
_flatten_result and keep their images. Transport failures still raise
and hit the existing handler. Add a regression test for the real path.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: accept raise_on_error kwarg in MCP test fake clients
The call_tool_sync fix passes raise_on_error=False to client.call_tool.
Update the fake MCP clients patched into mcp_client._client so their
call_tool signatures accept the keyword, keeping the stdio/servers MCP
test suites green.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: tighten MCP raise_on_error rationale comments
* Studio: only strip MCP image sentinel when suffix is a valid image envelope
* Studio: validate MCP image envelope in chat adapter and keep base64 out of exports
* Studio: sanitize MCP images in all export formats and fall through to sandbox parser on invalid marker
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
Hakan Baysal