* 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.
The pip scan-packages studio shard is red on main and on every open PR:
the baselined fastapi finding (the benign SSE keepalive `while True:`
loop in fastapi/routing.py, reviewed and suppressed long ago) records
its evidence at L586 with the span digest of the fastapi release current
at baseline time. The latest fastapi shifts that loop to L587 and its
span digest with it, so the evidence hash no longer matches and the
scanner reports the finding as new, failing the shard with one
unsuppressed CRITICAL.
Re-reviewed the flagged code in the current release before refreshing:
L587 is the same keepalive loop inside the streaming response machinery,
not a beacon. Only the one entry's evidence and evidence_hash change.
Verified with the scanner itself: `scan_packages.py fastapi
--no-baseline` reproduces the exact CI evidence string, and with the
updated baseline the same scan exits 0 with the finding suppressed as
1 CRITICAL baselined.
Ninth review round; each item reproduced before fixing.
The inner WSL install ran install.sh without /usr/lib/wsl/lib on PATH,
so its GPU detection (which checked PATH and /usr/bin only) could pick
CPU torch wheels on the exact Spark/N1X path this PR exists for, failing
the later torch.cuda probe. The forwarded env now appends
/usr/lib/wsl/lib to PATH (appended, so a PATH nvidia-smi still wins),
and install.sh's _has_usable_nvidia_gpu and torch-index _smi resolution
gained the same location fallback for direct WSL runs.
Three WSL failure paths in install.ps1 (WSL-not-installed deferral, the
download sentinel, and the final torch.cuda failure) set LASTEXITCODE
and returned, bypassing the round-eight Exit-InstallFailure fix, so
powershell -Command automation using the published pipe form still saw
success on those failures. All three now route through
Exit-InstallFailure, which restores the rolled-aside venv and fails the
process in every invocation mode.
The uninstall.ps1 WSL cleanup removed /root/.unsloth before killing and
matched only full argv, so cmake/nvcc children of a live CUDA build
(relative argv after the provisioner cds into the tree) survived the rm
and recreated files. The cleanup now signals each matched PID's whole
process group (guarded against the shell's own pgid, direct children
via pkill -P as fallback) before any rm; the /proc cmdline greps are
unaffected by kill order since they read process state, not files.
The round-eight same-group fallback called pkill -P without a guard;
under this script's set -e a matched provisioner with no children at
that instant (TERM pass already reaped them) aborted the whole
uninstaller before any cleanup. Now || true, like the kill beside it.
Reproduced in a dash sandbox with set -e: a childless matched PID
previously killed the harness, now dies cleanly while setsid-group and
same-group scenarios keep passing.
Verified: bash -n on both shell scripts, sh -n on the extracted WSL
clean snippet, PowerShell AST parse on both ps1 files, the three-
scenario kill sandbox, gpu-detection and installer-index pytest suites
pass, and the sh battery matches the branch baseline.
Eighth review round; each item reproduced before fixing.
Exit-InstallFailure under irm-pipe-iex set LASTEXITCODE and returned, so
powershell -Command automation using the published pipe form exited 0 on
fatal installer errors (verified: a -Command run whose last call only
assigns LASTEXITCODE exits 0, while one that throws exits 1). The iex
branch now sets the var for callers that check it and then raises a
terminating error, matching the pre-existing throw behavior there:
interactive shells survive and print it, automation gets exit 1, and the
-File branch keeps carrying the specific code via exit.
The uninstall group kill could signal the uninstaller's own process
group: in a non-interactive session without job control a lingering
provisioner can share the script's pgid, and kill(-pgid) would TERM the
cleanup mid-run. The helper now compares each match's pgid against its
own and falls back to the PID plus its direct children in that case.
Both scenarios exercised in a sandbox: a setsid provisioner group still
dies whole, and a same-group provisioner dies without taking the
harness.
detect_host in install_llama_prebuilt.py resolved nvidia-smi only via
shutil.which, so the root WSL sessions this PR creates (PATH without
/usr/lib/wsl/lib) classified ARM NVIDIA WSL hosts as non-NVIDIA and took
the CPU prebuilt path before setup's provisioning logic could run. It
now falls back to /usr/lib/wsl/lib/nvidia-smi then /usr/bin/nvidia-smi,
the same order as setup.sh's resolver.
Verified: bash -n, Python AST parse, PowerShell AST parse, the pwsh
exit-code experiments above, the two-scenario kill sandbox, and the sh
test battery matches the branch baseline.
Seventh review round; each item reproduced against the live tree first.
The aarch64 bitsandbytes step gated on a bare nvidia-smi, which root login
shells cannot see under WSL2 GPU-PV (the binary lives only in
/usr/lib/wsl/lib, dropped from PATH by the /etc/profile reset), so Spark
and N1X WSL installs finished with CUDA torch but no 4-bit QLoRA. The
gate now resolves nvidia-smi explicitly with the same PATH,
/usr/lib/wsl/lib, /usr/bin order as setup.sh's resolver.
uninstall.sh's CUDA-build kill matched patterns against argv, but the
provisioner cds into the tree before `cmake --build build`, so cmake and
make children carry relative argv no pattern can match; killing only the
wrapper orphaned them mid-build. Each match's whole process group is now
signalled (TERM then KILL), with a plain PID kill as fallback when the
pgid is unreadable or shared with init. Verified in a sandbox: a child
with unmatchable argv in the wrapper's group dies with it.
The WSL shim dir was appended to user PATH while the native installer
prepends its own %USERPROFILE%\.unsloth\studio\bin, whose unsloth.exe
outlives the venv the fallback rolls aside, so on a native-to-WSL rerun
a new terminal resolved unsloth to the dead native launcher. The shim is
now prepended via Add-ToUserPath (which de-dupes and hoists), and the
dead default-root native shim is removed when the venv binary it targets
is gone; custom-root shims are left alone since the prepend outranks
them.
UNSLOTH_NPM_REGISTRY was not forwarded into the inner WSL shell even
though setup.sh threads it into every npm/bun install, so mirror-required
networks failed the frontend step (and with it the install) while the
outer installer honored the mirror. It is now forwarded with the same
strict http(s) allow-list and single-quoting as UNSLOTH_PYTORCH_MIRROR.
Verified: bash -n on both shell scripts, PowerShell AST parse on
install.ps1, the group-kill sandbox above, resolver smoke tests for the
bitsandbytes gate, and the sh test battery matches the branch baseline.
Sixth review round; every item reproduced against the live scripts first.
The WSL fallback tolerated a nonzero inner exit (the optional llama.cpp
step legitimately fails), so a run whose installer died mid-way could pass
the torch and CLI probes on a stale venv from a previous install and be
reported as success. setup.sh now stamps /root/.unsloth/.install-ok after
the core venv and Studio deps complete, just before its tolerated
llama-only nonzero exit; install.ps1 clears the stamp before the run and
requires it to exist afterwards (existence only, no mtime compare, so
WSL/Windows clock skew cannot bite). uninstall.sh removes the stamp and
the downloaded installer file so the trailing rmdir can still prune.
Root login shells reset PATH via /etc/profile and drop /usr/lib/wsl/lib,
the only location of nvidia-smi under WSL2 GPU-PV, so every bare
nvidia-smi probe in setup.sh and the provisioner could silently misreport
"no GPU". Both now resolve nvidia-smi explicitly (PATH, then
/usr/lib/wsl/lib, then /usr/bin) via a shared-resolver pattern, and the
provisioner's driver-major and compute_cap reads use the resolved path.
My round-five uninstall fix inserted the CUDA-build kill block after the
llama.cpp tree was already removed, so a live cmake/nvcc kept running
against deleted paths; the block now runs before the removal.
uninstall.ps1 gated its legacy marker-less WSL cleanup on the process
PROCESSOR_ARCHITECTURE, which reports AMD64 under an x64-emulated
PowerShell on ARM64, skipping exactly the machines the fallback installs
on. It now uses the same triple detection as install.ps1 (OSArchitecture,
Win32_Processor.Architecture 12, machine-level registry arch), factored
into one helper used at both gate sites.
The nvidia-smi capture helper retried twice with a 60s timeout
everywhere, so off WSL a hung nvidia-smi stalled three successive
detect_host probes for about two minutes each; the generous retry now
applies only under WSL (where GPU-PV load slowness is real) and bare
metal keeps a single short attempt.
The generated WSL Desktop launcher hardcoded port 8888 for launch, health
poll, and browser open, so with Jupyter or a second Studio on 8888 the
poll waited on the wrong server forever; it now scans 8888..8908 with a
TcpListener, mirroring the native launcher's free-port window, and passes
the winner via -p everywhere.
Verified: bash -n on all shell scripts, Python AST parse, PowerShell AST
parse on install.ps1, uninstall.ps1, and the generated launcher; the
launcher port scan exercised free, busy, and exhausted cases; the capture
helper unit-tested for WSL and bare-metal attempt/timeout splits; sh test
battery matches the branch baseline.
Fifth review round; each item traced through the live scripts before fixing.
A provisioner fresh clone that failed to produce a server was left behind as
a markerless git tree; under a custom UNSLOTH_STUDIO_HOME the next run's
ownership assert refuses the unmarked dir and aborts the whole install until
the user deletes it by hand. _restore_prev now removes a clone this script
created when no server came out of it (backed-up dirs restore as before).
The CUDA provision gate ignored --with-llama-cpp-dir linked mode, so a
linked user tree with a CPU-only server could be checked out to a pinned
ref, rebuilt in place, or moved aside entirely and replaced by a fresh
clone. The gate now skips linked local dirs.
uninstall.sh removed the CUDA build artifacts without stopping a running
detached build; _pkill_studio only matches Studio roots, so live cmake/nvcc
kept burning thermals, recreated build files, and defeated the trailing
rmdir. The runner, provisioner, and llama.cpp-path processes now get
TERM-then-KILL with the same escape helper and grace the Studio kill uses.
The worker's memory-fraction guard classified Spark purely from device
props, so UNSLOTH_FORCE_DGX_SPARK=1 on an unlisted name got no fraction
guard (and the fraction env was dead), while FORCE=0 could not disable it;
the guard now honors the same force semantics as the detectors.
UNSLOTH_LLAMA_TAG / UNSLOTH_LLAMA_PR were interpolated into the runner
script's single-quoted exports unvalidated while every sibling forward has
an allow-list; they now get the INSTALL_REF ref allow-list and a digits-only
check respectively (own-machine robustness, not a trust boundary).
On WSL-fallback success with a custom UNSLOTH_STUDIO_HOME, the installer
deleted the rolled-aside custom-root venv right after telling the user that
root is not used by the WSL install; a custom root now restores the previous
venv instead (the WSL shim does not depend on the Windows venv), while the
default root keeps dropping the vestigial backup.
Verified: bash -n on all three shell scripts, AST parse on worker.py,
PowerShell AST parse on install.ps1, icon suites pass, sh battery matches
the branch baseline. Two resurfaced anchors (build/bin backup, --package
forwarding) confirmed already fixed at head.
Fourth review round; each item verified against the live scripts and the CUDA
compatibility documentation before fixing.
The provisioner installed (and, since the stale-toolkit change, preferred)
CUDA 13.3 without ever consulting the driver, but cu13 binaries need a 580+
driver and minor-version compatibility never crosses majors, so a GH200-class
host on a 5xx driver got an unloadable llama-server that the structural
acceptance check then stamped as ready. The driver's supported CUDA major is
now read from nvidia-smi and enforced three ways: the stale-toolkit upgrade
only fires when the driver can run cu13, a fresh install on a sub-13 driver
bails to the existing no-toolkit message instead of installing 13.3, and a
final guard swaps a too-new selected toolkit for the newest one the driver
supports (or refuses to build). Spark-class hosts (580+ drivers) behave
exactly as before; unparseable output keeps the previous behavior.
The WSL install pipeline ended in curl | sh, so a failed download fed sh an
empty stdin and exited 0; on a rerun the stale venv then passed the torch
probe and the installer reported success without ever running. install.sh is
now downloaded to a file with exit 86 as the never-ran sentinel, checked
before any probe (rollback + non-zero). The --package splice moved onto the
file invocation.
When the Studio web-server dep repair failed its re-verify, the installer
still created shims and reported success; the missing set includes typer, so
even the plain unsloth CLI dies. A failed repair now routes to the existing
failure path (rollback + non-zero), mirroring the CLI-missing case.
If all three provision-script resolutions fail (unpackaged wheel + GitHub
unreachable), the provision block silently skipped and, with the CPU build
now deferred on native Spark hosts, the install could report success with no
GGUF server; that case is now marked degraded so the CPU-prebuilt last
resort and failure exit fire.
flex_attention.py's Spark sniff gets the same /usr/lib/wsl/lib/nvidia-smi
fallback as the other two detectors (grep confirms these are the only three),
and uninstall.sh removes the remaining WSL-side build artifacts
(run_llama_build.sh, llama_cuda_build.log, the shortcut-skip marker) so the
.unsloth directory can actually be removed.
Verified: bash -n on all three shell scripts, AST parse on flex_attention.py,
PowerShell AST parse on install.ps1, the toolkit-picker awk exercised against
a fake /usr/local tree (driver 12 picks cuda-12.8 over 13.0, driver 11 picks
none), icon suites pass, sh test battery matches the branch baseline.
Third review round; each item re-verified against the live scripts.
A stale CUDA < 13 toolkit was kept forever: the 13.3 install was gated on
nvcc being absent, so a host with CUDA 12.x failed the sm_121 configure (or
the glibc >= 2.41 rsqrt clash) on every rerun and always exited with the CPU
server. When apt can provide 13.3 the provisioner now installs it alongside a
stale toolkit; find_nvcc's sort -V prefers the new install, and a failed
install leaves the old toolkit as the last resort, so non-Spark hosts that
build fine on cu12x are unaffected.
llama.cpp pins only applied to fresh clones; an existing checkout rebuilt
whatever commit it had while the log claimed a release pin. Existing
checkouts now fetch and check out the pinned (or resolved-latest) ref, best
effort with the current commit as fallback, and the UNSLOTH_LLAMA_PR handling
moved out of the fresh-clone branch so it applies to both paths.
The WSL fallback silently dropped a non-default --package and reported
success with stock unsloth; it is now spliced into the curl | sh invocation
(the name is regex-validated at parse time).
setup.sh's CUDA provision gate used raw nvidia-smi and ignored the
_setup_nvidia_usable computation that honors CUDA_VISIBLE_DEVICES=""/-1, so a
mixed-GPU host that hid its NVIDIA card still got a system CUDA install; the
gate now requires the flag. On native Linux Spark hosts without nvcc, setup.sh
also no longer does the multi-minute CPU source build that the CUDA provision
in the same run immediately replaces (mirroring the existing WSL deferral
arm); provision failure still cascades to the CPU-prebuilt last resort.
uninstall.ps1's distro extraction truncated quoted names at the first space
(-d "Ubuntu Preview" matched as "Ubuntu"), wrongly keeping or removing
shortcuts; the regex now matches a full quoted token first. And the profile
icon (%USERPROFILE%\.unsloth\unsloth.ico) was removed unconditionally while
the sweep above deliberately keeps launchers for non-evidenced WSL installs,
blanking their icons; removal is now gated on no surviving Unsloth shortcut,
mirroring uninstall.sh's _drop_shared_icon_if_unused guard.
Verified: bash -n on both shell scripts, PowerShell AST parse on both ps1
files, the new distro regex proven on spaced and unspaced names, icon suites
pass, sh test battery matches the branch baseline.
Second review round on the Windows-on-ARM + NVIDIA path; each item verified
against the live code (and torch where relevant) before fixing.
The native-CUDA probe ran uv --dry-run against the venv interpreter without
checking its architecture. uv resolves for the interpreter's platform tags, so
an x64-emulated python resolved existing win_amd64 CUDA wheels and "proved" a
native wheel WoA cannot use, skipping the WSL fallback entirely. The probe now
requires platform.machine() ARM64 from the venv python first; anything else
keeps the WSL routing.
The Studio worker appended PYTORCH_CUDA_ALLOC_CONF next to its memory-fraction
logic, 550 lines after detect_hardware() had already initialized CUDA, where
the allocator config is latched (verified on torch 2.9.1: expandable_segments
set after get_device_properties is a no-op in memory snapshots). The CUDA-free
Spark sniff now runs immediately before detect_hardware(), and it honors the
documented UNSLOTH_FORCE_DGX_SPARK=1/0 override the library detectors support,
closing the older force-flag item on the same block.
setup.sh's _have_cuda_llama_server accepted any co-located libggml-cuda.so,
re-opening the interrupted-relink hole the provisioner's completion stamp was
added to close: in exactly that state setup.sh skipped provisioning and
reported CUDA ready over the old CPU binary. The split-.so branch now also
requires the stamp; monolithic ldd-linked builds are unaffected.
The provisioner builds llama-quantize but never created the repo-root shim
that unsloth_zoo's check_llama_cpp needs (it only searches the root, which is
why setup.sh symlinks it in all three of its own paths). The success branch
now mirrors that symlink.
CMAKE_CUDA_ARCHITECTURES=native needs CMake >= 3.24, but this script installs
distro cmake (Ubuntu 22.04 apt ships 3.22), so the N/A-compute_cap fallback
aborted configure, wiped build/, and aborted again. The fallback now omits the
flag and lets ggml's version-guarded CMake defaults pick the arches.
Fresh clones tracked ggml-org master, bypassing setup.sh's newest-release pin
policy (its own header warns master bypasses the pin). An unset or "latest"
ref now resolves to the newest release tag via the GitHub API, keeping the
default-branch clone as the best-effort fallback when the API is unreachable.
install.sh writes the WSL shortcut icon to the Windows profile
(%USERPROFILE%\.unsloth\unsloth.ico) because the WoA icon broker cannot read
AppData\Local, but both uninstall.sh cleanup sites only cleaned the
AppData\Local icon. Both now clean the profile icon and drop the directory
when empty.
Verified: bash -n on all four shell scripts, AST parse on worker.py,
PowerShell AST parse on both ps1 files, the icon suites pass, and the sh test
battery matches the branch baseline (test_install_host_defaults.sh fails
identically on the clean tree).
Review round on the Windows-on-ARM + NVIDIA WSL2 path; each item reproduced
against the live scripts before fixing.
provision_llama_cuda.sh now serializes with install_llama_prebuilt.py on the
same <parent>/.<name>.install.lock file (its filelock backend is flock(2), so
shell flock interoperates; append-mode open so the Python O_EXCL fallback's
PID file is never truncated). The detached background builder could otherwise
race an installer rerun or `unsloth studio update`, both of which mv/rm -rf
inside the llama.cpp dir. Losing the 2h wait exits 0: another provisioner is
already doing the job.
The step-0 early-skip trusted a co-located libggml-cuda.so alone, which
wrongly skips one case: an in-place rebuild interrupted after the .so links
but before llama-server relinks leaves new .so + old CPU server. A completion
stamp (build/bin/.unsloth-cuda-ok) written only after the script's own final
CUDA check closes that window; skip now requires ldd evidence or the stamp.
The rejected functional --list-devices probe stays rejected: the stamp does
not gamble thermals on an env-fragile probe.
The WSL shortcut skip (install.ps1 owns the canonical WoA .lnk) was only a
transient env var, so the first `unsloth studio update`, whose wsl.exe shim
carries no env into install.sh --shortcuts-only, recreated the duplicate
blank-icon shortcut. The skip is now also persisted as
/root/.unsloth/.skip-wsl-windows-shortcut, checked by install.sh and removed
with the install by both uninstallers.
--with-llama-cpp-dir (and UNSLOTH_LOCAL_LLAMA_CPP_DIR) were parsed but
silently ignored on the WSL fallback path, which builds its own llama.cpp
inside the distro. Reject with guidance (UNSLOTH_LLAMA_TAG / UNSLOTH_LLAMA_PR
pin the WSL-side build), mirroring the --local reject.
uninstall.sh's Windows shortcut sweep only removed wsl.exe-target .lnks, so
the WoA fallback shortcuts (powershell.exe + launch-studio-wsl.ps1) survived
while their launcher dir was deleted, leaving dangling shortcuts. The
owner-matched cleanup now removes them first.
uninstall.ps1 swept every "Unsloth Studio (*.lnk" as legacy, but install.sh
creates exactly that per-distro name for current WSL installs, and the WSL
cleanup below only removes evidenced distros. The sweep now keeps a live
wsl.exe launcher whose distro is not in the same evidence set, so a surviving
WSL install keeps its shortcut; everything else is still swept.
Verified: bash -n on all three shell scripts, PowerShell AST parse on both
ps1 files, flock mutual-exclusion and stamp skip/rebuild decisions exercised
standalone, and the uninstall icon suites (sh + ps1) pass. The
test_install_host_defaults.sh failure pre-exists on the branch merge base.
The supply-chain scan gates on non-baselined CRITICAL/HIGH findings. A newer
sentencepiece release reindented the stdout/stderr fd-redirect helper in
sentencepiece/__init__.py (the os.dup2 pair the heuristic flags as a
reverse/bind-shell pattern), moving it from L1221/L1226 to L772/L777 and
changing its leading indentation.
The baseline key is (package, package-relative file, check, evidence_hash),
where evidence_hash is over the matched code with the L<NN>: markers stripped
but the code's own indentation preserved. The reindent therefore changed the
hash (bba233.. -> 65b5a11c..), so the existing entry no longer suppressed the
finding and it resurfaced as a blocking CRITICAL in the hf-stack and studio
scan legs.
Add the new indentation variant to the allowlist. The calls are sentencepiece
redirecting stdout/stderr file descriptors to capture its C++ logs, not a
shell; no socket or networking is involved. The old L1221 entry is kept so
both versions stay covered.
New releases of huggingface-hub (1.23.0) and openai (2.45.0) shifted or
added polling loops that the C2 polling/beaconing check flags, failing
all three pip scan-packages shards (studio 1, hf-stack 1, extras 3 new
CRITICAL findings) org-wide including on main.
Regenerated with scan_packages.py --write-baseline per CI shard (same
shard-to-requirements mapping and --with-deps as security-audit.yml)
and merged. All entries were manually reviewed at the resolved versions:
- huggingface-hub hf_api.py: create_repo 409-concurrency retry loop
body changed in 1.23.0; refreshed evidence hash. The loop POSTs to
the canonical Hub endpoint and retries only on a specific conflict
error. Benign client retry.
- openai beta/threads/runs/runs.py: create_and_poll run-status helper
refactored in 2.45.0 (Assistants deprecation annotations); refreshed
evidence hash. Documented polling helper against api.openai.com.
- openai beta/responses/responses.py: new beta websocket client whose
__aiter__ yields server events until the connection closes. New
entry; standard event-stream iterator, not beaconing.
- openai resources/responses/responses.py: evidence line number
refreshed only, hash unchanged.
The two dropped entries are the pre-refactor hashes of the same two
loops above; they no longer occur at the resolved versions. Verified
locally: all three shards exit 0 with 0 unsuppressed CRITICAL/HIGH
(hf-stack 120, studio 151, extras 99 suppressed).
* scripts: refresh scan_packages allowlist baseline
Regenerate scripts/scan_packages_baseline.json against the current
resolved dependency set so the blocking pip scan-packages gate matches
what the scanner now finds. Refreshes evidence hashes for benign
findings whose code shifted lines (unsloth-zoo mlx loader, gguf/mlx
test /tmp fixtures) and adds two mainstream-library entries that were
newly surfaced (torch inductor codecache base64+subprocess compile
cache, torch testing common_utils socket import). Stale entries whose
matching code changed and no longer triggers are dropped.
All entries remain CRITICAL/HIGH findings manually judged benign;
matched on (package, file, check, evidence_hash).
* ci(security-audit): re-run scan when the allowlist baseline changes
The security-audit pull_request trigger listed the scanners but not
their allowlist baselines, so a baseline-only edit never re-ran the
scan that consumes it. A refreshed baseline could therefore merge
without CI confirming its evidence hashes match what the scanner finds.
Add scan_packages_baseline.json and scan_npm_packages_baseline.json to
the paths filter so baseline changes are validated on their own PR.
* WSL ROCm: generalize ROCm-on-WSL bootstrap from Strix-only to any RDNA arch
install_rocm_wsl_strixhalo.sh hardcoded gfx1151, so its verify step died on
discrete Radeon cards even though the ROCm + librocdxg setup is arch-agnostic.
Auto-detect the GPU arch from rocminfo (override via UNSLOTH_WSL_GFX), verify any
GPU agent enumerates over DXG, and map the arch to AMD's per-arch wheel family for
the optional smoke test (injecting librocdxg into torch/lib so torch's bundled
ROCr finds the DXG bridge). Verified on gfx1200 (Radeon RX 9060 XT) in WSL2 +
Ubuntu 24.04 -- torch.cuda now enumerates the GPU.
* WSL ROCm: trigger the ROCm-on-WSL bootstrap for discrete Radeon GPUs too
_maybe_bootstrap_rocm_wsl only fired for Strix APUs (matched via /proc/cpuinfo,
which discrete cards don't appear in). Add _wsl_amd_gpu_name() -- queries the
Windows host via WMI -- and broaden the trigger gate plus the 'already-usable
ROCm' rocminfo check from gfx1151-only to any real GPU agent (gfxNNNN, excluding
the gfx11-generic fallback ISA). The generalized bootstrap then auto-detects the
arch. Enables 'curl install.sh | sh' to set up ROCm-on-WSL on discrete Radeon RX
7000/9000 in WSL2 + Ubuntu 24.04, not just Strix Halo/Point.
* WSL ROCm: address review -- filter generic ISA in bootstrap, bound the host GPU query
- install_rocm_wsl_strixhalo.sh: exclude the gfx11-generic fallback ISA in arch
detection (grep -v generic), matching install.sh's rocminfo check, so a generic
agent listed before the real one can't be picked as the arch.
- install.sh: wrap the powershell.exe Win32_VideoController query in _run_bounded
(10s timeout) so an unstable WSL-interop / busy host can't hang the installer.
* WSL ROCm: harden arch-detect + librocdxg copy under set -eo pipefail (review)
- _detected_gfx: append '|| true' so a no-GPU rocminfo (empty pipeline, non-zero
under pipefail) doesn't abort the assignment before the '[ -z ]' branch prints
the diagnostic + die message.
- smoke-test librocdxg copy: gate on '[ -d "$_tlib" ]' instead of '[ -n ]' so a
non-directory value can't make cp rename librocdxg to 'lib'.
* WSL ROCm: address Codex review (gfx000, 24.04 reroute for discrete, test locator)
- Exclude gfx000 (the CPU agent) from the WSL 'usable ROCm' check and the bootstrap
arch-detect: match gfx[1-9] (nonzero arch), so a partial ROCm install that only
reports the CPU ISA no longer short-circuits the librocdxg setup. (P2)
- Reuse the Ubuntu-24.04 reroute for discrete Radeon: broaden
_maybe_reroute_strixhalo_to_2404's gate with the same _wsl_amd_gpu_name (WMI)
fallback, so a discrete card on 26.04 reroutes to a 24.04 distro like Strix does
instead of falling to CPU. Moved _wsl_amd_gpu_name above the reroute and made it
self-contained + 10s-bounded (it runs before _run_bounded is defined). (P2)
- Update TestInstallShDropinPersistence to locate the gate by its unique
'!/generic/' clause now that the gfx1151 literal is gone. (P1)
* Condense ROCm-on-WSL comments in install.sh and bootstrap helper
* Guard WSL reroute from NVIDIA hybrid hosts and fix GFX-override pipefail check
* Honor CUDA_VISIBLE_DEVICES-hidden NVIDIA in the WSL reroute guard
* Reuse _has_usable_nvidia_gpu in the WSL reroute guard
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Studio: exclude mlx-lm 0.31.3 (broke gemma4/qwen3_5 QK-norm load)
mlx-lm 0.31.3 regressed the QK-norm archs: its strict load_weights rejects the
q_norm/k_norm tensors with "Received N parameters not in model", so gemma4 and
qwen3_5 checkpoints fail to load. Studio installs the MLX stack unpinned at
latest, which pulls 0.31.3. Verified on a real macos-14 runner: gemma4 fails to
load on 0.31.3 but loads and generates coherently on 0.31.2 and on git-main
(future 0.31.4). See mlx-lm #1242.
Exclude just that release (!=0.31.3) in the installer and the self-heal floor so
--upgrade still resolves to the newest good build, and treat an already-installed
0.31.3 as unsatisfied so the self-heal replaces it.
* Studio MLX: cover fresh-install path + robust bad-version compare
Address PR review:
- Fresh install.sh (Apple Silicon) runs the base 'uv pip install unsloth' with
SKIP_STUDIO_BASE=1, skipping the guarded MLX-stack step, so transitive
resolution could still pull mlx-lm 0.31.3. install.sh already exports
UV_OVERRIDE -> overrides-darwin-arm64.txt before that install, so exclude
mlx-lm 0.31.3 there too; this also strengthens the self-heal (same override).
- Match the known-bad version with parsed packaging.Version so 0.31.3 == 0.31.3.0
(trailing-zero normalization) instead of raw string equality.
* Studio: exclude mlx-lm 0.31.3 on the fresh Apple Silicon install too
The overrides file only applies via UV_OVERRIDE when it exists relative to the
script, which is not true for a curl-piped install, and the guarded MLX step in
install_python_stack.py is skipped there (SKIP_STUDIO_BASE=1). So the base
install could still resolve the transitive mlx-lm to the broken 0.31.3. Append
mlx-lm!=0.31.3 to the base install on Apple Silicon (empty elsewhere), so the
fresh path pins away from 0.31.3 without waiting for the runtime self-heal.
* Studio: exclude mlx-lm 0.31.3 on the migrated install; keep the >=0.22.0 floor
The with-deps migrated install did not append ${_MLX_LM_EXCLUDE_ARG:-}, so a
curl-piped Apple Silicon migration (no repo overrides file, UV_OVERRIDE unset)
could resolve mlx-lm 0.31.3 transitively. Append the exclusion there, matching
the fresh install path. The no-torch migration is left alone since --no-deps
never resolves mlx-lm (same as the fresh no-torch path).
Also restore the >=0.22.0 floor in overrides-darwin-arm64.txt: a uv override
replaces the transitive constraint, so a bare !=0.31.3 could let the resolver
drop below the supported minimum that mlx_repair.py enforces at runtime.
* Triage huggingface_hub 1.22.0 / fastapi / multiprocess scanner false positives
The scan-packages gate red-failed on all three shards after transitive deps
bumped. Every new CRITICAL is a benign false positive, verified against upstream:
- huggingface_hub 1.22.0 added _sandbox.py for the remote HF sandbox feature.
Its job-startup bootstrap string (fetch sbx-server into the container /tmp and
exec it) and the SandboxPool host-reservation loop trip the staged-dropper and
C2-loop heuristics; that script runs inside a remote HF container, not on the
user machine. The bump also re-hashed the already-reviewed benign polling loops
in hf_api.py and utils/_http.py. The PyPI artifact is byte-identical to the
official v1.22.0 tag.
- fastapi 0.139.0 routing.py re-hashed the websocket keepalive while-True loop;
byte-identical to upstream 0.139.0.
- multiprocess 0.70.19 forkserver.py and tests/__init__.py re-hashed the AF_UNIX
fork-server IPC and fd-inheritance tests; genuine uqfoundation release, local
IPC not network.
Added 7 reviewed allowlist entries (no blind regenerate). All three shards
(hf-stack, studio, extras) exit 0 locally.
* Tighten mlx-lm 0.31.3 exclusion comments
* Trim mlx-lm 0.31.3 exclusion comments
The pip scan-packages gate (SCAN_ENFORCE=1) blocks on non-baselined
CRITICAL/HIGH findings. Recent upstream releases of transitive
dependencies added new files/loops that trip the pattern scanner, so all
three shards (extras, hf-stack, studio) red-failed on legitimate library
code. Add the 7 reviewed findings to scripts/scan_packages_baseline.json.
Each entry is genuine upstream code from the official PyPI archive:
- huggingface-hub huggingface_hub/_sandbox.py (staged dropper + C2 loop):
the HF Jobs sandbox bootstrap string and its host-pool reservation
loop. New in huggingface_hub 1.x (pulled via huggingface_hub>=0.34.0).
- huggingface-hub huggingface_hub/hf_api.py, utils/_http.py (C2 loop):
standard polling / retry while True loops.
- fastapi fastapi/routing.py (C2 loop): websocket receive loop.
- fastmcp-slim fastmcp/cli/apps_dev.py (fs enum + network): the FastMCP
dev CLI (PrefectHQ) making httpx/socket calls.
- cffi cffi/_cffi_gen_src.py (compile + exec): cffi generating and
running C extension source, its core purpose.
Additive only: no existing baseline entry is changed or removed. Verified
by re-running the scanner over the full closure on Python 3.12.13 (the CI
interpreter); it now exits 0 with only MEDIUM findings remaining.
* studio: tool calling for Llama-3, Mistral, Gemma 4 on safetensors + MLX (#5615)
Adds tool calling for Llama-3, Mistral (pre-v11 + v11+ + [ARGS]), and Gemma 4 to the safetensors / transformers and MLX backends. Parser patched against llama.cpp / vLLM / SGLang per-family parsers and normalises to OpenAI shape. 96 targeted unit tests + cross-OS staging CI (ubuntu / macos-14 / windows) green on the multi-format probe.
* studio: tool-call healing parity between safetensors / MLX and GGUF
After the multi-format parser landed in #5615, the safetensors / MLX
agentic loop and the GGUF loop still differed on healing behaviour.
This commit closes the gaps in both directions so the two backends
react the same way to identical model output.
Changes:
1. core/inference/llama_cpp.py -- the GGUF BUFFERING state machine
now wakes on every emission marker the shared parser knows. Was
("<tool_call>", "<function="); is now the five-tuple imported
from core.inference.tool_call_parser (Qwen / Qwen3.5 / Llama-3
<|python_tag|> / Mistral [TOOL_CALLS] / Gemma 4 <|tool_call>).
Stream cleanup is delegated to the same shared strip_tool_markup
so leaked markup from any family is removed from assistant
content.
2. core/inference/llama_cpp.py -- per-tool canonical heal key. When
a tool arguments field is a bare string and JSON parsing fails,
the GGUF path now heals to {"code": raw_args} for python,
{"command": raw_args} for terminal, and {"query": raw_args} for
everything else. Was hard-coded to {"query": raw_args}, which
silently routed every python / terminal emission through
web_search. Mirrors safetensors_agentic._CANONICAL_HEAL_ARG.
3. core/inference/safetensors_agentic.py -- re-prompt on plan-
without-action. When the model emits a short forward-looking
intent ("I'll search for that", "Let me check", "First, I
will...") and no tool call, the loop nudges the model to act
instead of silently returning a plan-only answer. Up to
_MAX_REPROMPTS=3 (matches GGUF). The intent regex, character
cap, and instruction text are byte-identical to the GGUF path.
The buffer-end fall-through is unified so a buffered intent
emission that never exits the BUFFERING state still triggers
the re-prompt.
4. core/inference/safetensors_agentic.py -- extra iteration slots
for re-prompts. The loop now budgets max_tool_iterations +
_MAX_REPROMPTS + 1 total iterations and tracks the tool-call
count separately, so a stalling model can be nudged 3x without
eating the caller's tool-call budget. Mirrors the _extra slot
reservation in the GGUF path.
Tests (14 new safetensors-side units; 5 GGUF parity pins):
TestLoopRePrompt -- intent-trigger, plain-answer,
no-tools, cap-at-three, budget
preserved, buffer-end intent.
TestLoopCanonicalHealKey -- python / terminal / unknown.
TestGGUFSafetensorsHealingParity -- shared markers used, shared
strip used, canonical heal keys
identical, intent regex matches
same phrases, _MAX_REPROMPTS
equal on both backends.
All 110 targeted tests pass locally; the broader tool / inference /
model-config / sandbox / anthropic / mlx suites stay green.
Why this matters
Without this parity, Llama-3.2 / Mistral / Gemma 4 emissions on Mac
(MLX) and Linux-safetensors stop the agentic loop as soon as the
model says "Let me...", because the GGUF re-prompt logic never
existed on these backends. The two-marker GGUF BUFFERING tuple also
let non-Qwen tool emissions stream out as plain prose when
llama-server's structured channel did not pick them up. Both paths
now drain the same way, heal the same way, and re-prompt the same
way -- so a tool call that works on GGUF works identically on
safetensors / MLX.
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* studio: fix tool-call parser bugs from gemini review on #5620
Three high-priority gemini findings on the tool-call parsing additions:
1. unicode_escape on UTF-8 bytes corrupts non-ASCII literals
(e.g. ✨ becomes â\x9c¨). Replace with json.loads on a quoted
string -- preserves emoji / CJK / RTL while still handling
\n \t \uXXXX escapes.
2. Llama-3 sentinel stripping is order-dependent. A leading
`<|eot_id|><|begin_of_text|>` left `<|begin_of_text|>` behind
because the loop had already passed that sentinel. Loop until
no sentinel matches at the start.
3. Mistral v11+ `[TOOL_CALLS] name { json }` regex uses non-greedy
`\{.*?\}` which truncates at the first `}` of a nested JSON
argument, leaking the tail (e.g. `}}`) into user-visible
streamed text. Same problem for the v0.3 array pattern with
nested brackets. Strip those with balanced brace/bracket
scanning via a new `_strip_mistral_closed_calls` helper called
from `strip_tool_markup`.
Also fix the inference routes' parallel `_TOOL_XML_RE`:
- Same nested-JSON truncation in the Mistral patterns; route the
strip through the parser's balanced-scan helper via a thin
`_strip_tool_xml` wrapper that all existing callers now use.
- Llama-3 `<|python_tag|>[^\n<]*` stopped at any `<`, leaking the
tail of any tool call whose argument contained a literal `<`
(queries, code snippets). Relax to `[^\n]*` which keeps the
strip confined to the actual end-of-line.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* studio: tool calling for DeepSeek (R1/V3/V3.1), GLM 4.x, Kimi K2
Adds three more emission-family parsers to tool_call_parser.py so the
shared safetensors / MLX / GGUF agentic loop covers the major open-
weight reasoning families. Patterns ported from llama.cpp
(common/chat-parser.cpp legacy pre-PEG branch), vLLM
(tool_parsers/deepseekv3*, glm4_moe, kimi_k2), and SGLang
(function_call/deepseekv31_detector, glm4_moe_detector, kimik2_detector).
All three references are MIT (llama.cpp) or Apache-2.0 (vLLM, SGLang).
Formats covered:
DeepSeek R1 <|tool▁calls▁begin|><|tool▁call▁begin|>function
<|tool▁sep|>NAME\n```json\n{...}\n```<|tool▁call▁end|>
<|tool▁calls▁end|>
-- args wrapped in a Markdown json fence, ``function``
literal prefix per llama.cpp common_chat_parse_
deepseek_r1 (chat-parser.cpp:801-820)
DeepSeek V3/V3.1
<|tool▁calls▁begin|><|tool▁call▁begin|>NAME
<|tool▁sep|>{json}<|tool▁call▁end|><|tool▁calls▁end|>
-- bare JSON, no code fence, no ``function`` prefix
per llama.cpp common_chat_parse_deepseek_v3_1
(chat-parser.cpp:822-879)
GLM 4.5/4.6/4.7 <tool_call>NAME\n<arg_key>k1</arg_key>
\n<arg_value>v1</arg_value>...</tool_call>
-- strings raw, non-strings JSON-encoded per
chat_template.jinja; multi-call is back-to-back
blocks. Per llama.cpp common_chat_parse_glm_4_5
(chat-parser.cpp:1040-1052)
Kimi K2 <|tool_calls_section_begin|><|tool_call_begin|>
functions.NAME:IDX<|tool_call_argument_begin|>{json}
<|tool_call_end|><|tool_calls_section_end|>
-- bare name recovered by stripping ``functions.``
prefix and ``:IDX`` suffix; full id preserved as
tool_calls[i].id so the roundtrip replays verbatim.
Per llama.cpp common_chat_parse_kimi_k2
(chat-parser.cpp:896-913)
Marker collisions
GLM uses the same ``<tool_call>`` opener as Qwen but with a bare
function name + ``<arg_key>`` body (Qwen has ``\s*{`` after the tag).
The dispatch keeps Qwen first; Qwen's _TC_JSON_START_RE returns no
matches on a GLM emission, so the fall-through to _parse_glm_tool_
calls handles it correctly. Existing Qwen tests confirm zero
regression.
Streaming buffer
TOOL_XML_SIGNALS extended from 5 markers to 12 so the BUFFERING state
machine wakes on every new family's section opener. Added the
DeepSeek alternative markers (ASCII underscores, short ``<|tool▁calls|>``
form) because real checkpoints emit those variants.
Strip patterns
_TOOL_CLOSED_PATS adds DeepSeek envelope (``<|tool▁calls▁begin|>...
<|tool▁calls▁end|>``) and Kimi section (``<|tool_calls_section_begin|>
...<|tool_calls_section_end|>``). _TOOL_ALL_PATS adds the same plus
the unclosed-tail variants so a truncated stream does not leak
markup.
Route gate
_detect_safetensors_features._PARSER_MARKERS grows to include
DeepSeek and Kimi markers plus ``<arg_key>`` (the unique GLM signal).
_TOOL_XML_RE (the route-layer markup-strip regex) gets DeepSeek and
Kimi closed-pair patterns. _TOOL_TEMPLATE_MARKERS in llama_cpp.py
adds ``message['role'] == 'tool'``, ``message['tool_calls']``, and
``tool_calls is defined`` so the classifier recognises DeepSeek's
subscripted-access template style (it has no top-level
``{% if tools %}`` block).
Tests (39 new):
TestParserDeepSeek (7) -- R1 fence, short-form opener, V3.1 bare,
multi-call, with-reasoning, strip,
signal-wakes-streaming
TestParserGLM (6) -- single, mixed types, multi-call,
unclosed-heal, no-Qwen-regression, strip
TestParserKimi (6) -- single, multi-call, dotted-name, unclosed,
strip, signal-wakes-streaming
TestParserCrossFormatRouting (2) -- dispatch routing, signal coverage
TestLoopBasic loop integration (3) -- DeepSeek / GLM / Kimi end-to-end
Capability advertise (3) -- DeepSeek / GLM / Kimi templates flip
supports_tools=True
All 398 targeted tests pass locally (115 safetensors + 27 capability
+ rest of tool / inference / sandbox / model-config suites). Builds
on PR #5620 (parser + healing parity for Llama-3 / Mistral / Gemma 4);
will rebase cleanly onto main once #5620 lands. PR opened as draft -
do not merge until validated against real models for each family.
Sources
- llama.cpp common/chat-parser.cpp lines 801-913, 1040-1052 (MIT)
- vLLM vllm/tool_parsers/deepseekv31_tool_parser.py (Apache-2.0)
- vLLM vllm/tool_parsers/glm4_moe_tool_parser.py (Apache-2.0)
- vLLM vllm/tool_parsers/kimi_k2_tool_parser.py (Apache-2.0)
- SGLang python/sglang/srt/function_call/{deepseekv31,glm4_moe,kimik2}_
detector.py (Apache-2.0)
- Live chat templates: deepseek-ai/DeepSeek-V3.1, zai-org/GLM-4.6,
moonshotai/Kimi-K2-Instruct, unsloth/DeepSeek-V3-0324,
unsloth/GLM-4.5-Air, unsloth/Kimi-K2-Instruct
* studio/routes: make python_tag strip multi-line aware
Earlier revisions of _TOOL_XML_RE in studio.backend.routes.inference
oscillated between two bug shapes:
5615 r"<\|python_tag\|>[^\n<]*" -- stopped at any literal "<"
so code='if x < 10: pass'
leaked '< 10: pass)' to the
user.
5620.1 r"<\|python_tag\|>[^\n]*" -- single-line only; the second
line of
python.call(code="a\nb")
leaked.
The full parser (_parse_llama3_python_tag) already handles both via
balanced-brace scanning, so the parsing path was fine; the LEAK was
in the streaming strip path that runs on every cumulative emission
while content is still arriving.
Switch to r"<\|python_tag\|>(?:[^<]|<(?!\|))*" so the strip consumes:
* any character that is not a "<" (newlines, JSON, code, ...),
* a "<" only when it is NOT followed by "|" (i.e. NOT a Llama-3
sentinel start like <|eot_id|>, <|eom_id|>, <|begin_of_text|>).
This means:
* code='if x < 10' stays inside the strip (5615 fix preserved),
* multi-line code stays inside the strip (5620 round 2),
* the strip terminates at the next Llama-3 sentinel so trailing
assistant content survives.
Tests: TestRoutesPythonTagStrip (8 cases)
pytest test_safetensors_tool_loop.py test_safetensors_capability_advertise.py
-> 118 passed in 1.81s (was 110).
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* studio: review follow-ups for DeepSeek / GLM / Kimi tool calling
Four fixes addressing review of the parent commit:
1. GLM <arg_value> coercion: tighten the
json.loads -> ast.literal_eval -> raw cascade to only deserialize
when the body unambiguously looks like a JSON literal (object,
array, JSON-encoded string, true/false/null, or numeric). Strings
like ``True`` / ``None`` (Python literals, not JSON) and arbitrary
prose now stay raw. The bare-numeric / bare-boolean ambiguity with
string args remains an inherent limitation of the template without
schema access -- documented in the new comment. Drops the ast
import entirely (closes Gemini's :1036 suggestion).
2. Kimi K2 bare-counter ids (e.g. ``<|tool_call_begin|>3``) are now
dropped rather than surfaced as a tool literally named "3". Matches
vLLM behaviour; SGLang's schema-infer fallback is out of scope at
the parse site. Real Kimi K2 emissions use ``functions.NAME:IDX``
so this is the exception path.
3. Restore the elaborate ``<|python_tag|>(?:[^<]|<(?!\|))*`` clause in
routes.inference._TOOL_XML_RE -- the simpler ``[^\n<]*`` form
regressed PR #5620's multi-line / literal-``<`` python_tag fix.
Restore ``TestRoutesPythonTagStrip`` (8 tests) adapted to call
``_TOOL_XML_RE.sub`` directly since the ``_strip_tool_xml`` helper
was inlined this PR.
4. Add the spaced and backslash-escaped DeepSeek opener variants
(``<|tool calls begin|>``, ``<|tool\_calls\_begin|>``) to
``TOOL_XML_SIGNALS`` for streaming-gate parity with
``_DEEPSEEK_BEGIN_RE``.
Also updates the llama.cpp / vLLM citations in the parser docstrings:
``common/chat-parser.cpp`` was split into ``common/chat.cpp`` +
``common/chat-peg-parser.cpp`` by llama.cpp PR #18675, and vLLM
moved the tool parsers from ``vllm/entrypoints/openai/tool_parsers/``
to ``vllm/tool_parsers/``. Pin to pre-refactor commit ``51fa458a92d6``
where the cited line numbers still resolve.
New regression tests in ``test_pr5624_regressions.py`` cover the GLM
coercion heuristic shapes, GLM literal-``<`` in arg_value, Kimi K2
dotted name, Kimi K2 bare-counter drop, DeepSeek V3.1 truncated
mid-stream, and routes-layer strip across all three new families.
Tests:
pytest studio/backend/tests/test_safetensors_tool_loop.py
studio/backend/tests/test_safetensors_capability_advertise.py
studio/backend/tests/test_pr5624_regressions.py -q
-> 170 passed in 1.91s
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* studio: tighten verbose comments in tool-call parser sections
Comments were narrating what the code already says. Cut historical
"earlier revisions used X, then Y" narratives down to one-line WHY
notes where the footgun still matters (canonical heal-key parity,
balanced-brace vs non-greedy regex, ``(?:[^<]|<(?!\|))*`` over
``[^\n<]*``/``[^\n]*``). Drop section-header banners.
No behaviour change. Re-ran:
pytest studio/backend/tests/test_safetensors_tool_loop.py \
studio/backend/tests/test_safetensors_capability_advertise.py -q
-> 118 passed.
Regression replay (parser + _coerce_arguments on the 5 #5615 inputs)
-> 21/21.
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* studio: GLM 4.7 no-newline emission + Kimi multi-section parity
Two fixes surfaced by triple-confirm verification against the live
HF chat templates and upstream llama.cpp / vLLM / SGLang parsers.
1. GLM 4.7 silent drop
``zai-org/GLM-4.7/chat_template.jinja`` line 65 uses
``{{- '<tool_call>' + tc.name -}}`` which Jinja strips trailing
whitespace from, so the first ``<arg_key>`` follows the function
name with NO ``\n`` between them. Real emissions look like
``<tool_call>get_weather<arg_key>city</arg_key><arg_value>London
</arg_value></tool_call>``. The previous ``_GLM_TC_OPEN_RE`` ended
the name with ``\n`` so GLM-4.7 calls were silently dropped
(parser returned ``[]``).
Fix: relax the name terminator to a lookahead that accepts EITHER
``\n`` OR the next ``<arg_key>``:
_GLM_TC_OPEN_RE = re.compile(
r"<tool_call>\s*([^\n<{][^\n<]*?)\s*(?=\n|<arg_key>)"
)
The first-char restriction ``[^\n<{]`` still excludes Qwen's
``<tool_call>{json}`` form so the Qwen-vs-GLM dispatch remains
mutually exclusive.
2. Kimi multi-section parity with vLLM / SGLang
``vllm/tool_parsers/kimi_k2_tool_parser.py`` and SGLang's
``kimik2_detector.py`` both use ``re.findall`` and so collect every
``<|tool_calls_section_begin|>...<|tool_calls_section_end|>`` block
in a single stream. The previous implementation stopped at the
first ``<|tool_calls_section_end|>``. Kimi K2 doesn't emit
multi-section in practice, but parity is cheap.
Fix: wrap the existing per-call body parser in an outer loop that
advances past each ``<|tool_calls_section_end|>`` and continues to
the next ``<|tool_calls_section_begin|>``. Body parsing extracted
to ``_parse_kimi_section_body`` for clarity. Truncated final
section is still surfaced via the existing in-body balanced-brace
walk.
Verified independently against the live HF templates:
* GLM-4.7 emission constructed from the live template parses to the
expected ``{name, arguments}`` shape.
* GLM-4.5 / 4.6 newline shape continues to parse (the lookahead also
matches ``\n``).
* Qwen ``<tool_call>{json}`` still dispatches to the Qwen path -- the
first-char restriction stops the GLM regex from biting JSON bodies.
* Kimi two-section stream surfaces both calls in order with full ids
preserved.
* Bare-counter Kimi ids still drop.
Tests added in ``test_pr5624_regressions.py``:
* ``test_glm_4_7_no_newlines_between_name_and_arg_key``
* ``test_glm_4_7_no_newlines_multi_call``
* ``test_glm_4_7_does_not_break_qwen_path``
* ``test_kimi_two_sections_in_one_stream_both_parse``
pytest studio/backend/tests/test_safetensors_tool_loop.py
studio/backend/tests/test_safetensors_capability_advertise.py
studio/backend/tests/test_pr5624_regressions.py -q
-> 174 passed in 1.93s
pytest studio/backend/tests/ -q -k 'not gpu and not llama_cpp_integration'
-> 2038 passed, 15 failed (pre-existing CI gaps).
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* studio: parser robustness fixes for PR #5620
Three surgical extensions to the multi-format tool-call parser, each
covering a real fine-tune / template emission shape that the current
parser silently drops. No path narrows; all changes widen what is
accepted.
1. `_parse_tool_call_json` now accepts both `arguments` and
`parameters` keys. A Hermes / Qwen `<tool_call>{json}</tool_call>`
wrapper around a Llama-3.2 fine-tune that emits the `parameters`
key was extracting the tool name and silently discarding the
args, producing a working-shaped call with an empty payload. The
bare-JSON and python_tag paths already accepted both keys; this
path now matches them.
2. `_TC_FUNC_START_RE`, `_TC_PARAM_START_RE`, and `_TC_PARAM_CLOSE_RE`
now also match the attribute form
`<function name="..."><param name="...">v</param></function>` used
by MiniCPM-5 and MiniMax-M2. Names land in either capture group,
and `</param>` is accepted as a short close.
3. `_parse_llama3_bare_json` sentinel-strip now consumes the role
label inserted between `<|start_header_id|>` and
`<|end_header_id|>` by Meta's official Llama-3.x chat template.
Without this, every assistant turn re-fed through the template
prefix `<|start_header_id|>assistant<|end_header_id|>\n\n{json}`
parsed to zero calls, so any history-with-tool-call round-trip
in production silently dropped.
Tests in `studio/backend/tests/test_safetensors_tool_loop.py`:
* `TestParserRobustness::test_tool_call_json_accepts_parameters_key`
* `TestParserRobustness::test_function_xml_attribute_form`
* `TestParserRobustness::test_function_xml_attribute_form_multi_param`
* `TestParserRobustness::test_function_xml_legacy_equals_form_still_works`
(regression guard for the existing `<function=name>` syntax)
* `TestParserRobustness::test_llama3_chat_template_round_trip`
* `TestParserRobustness::test_llama3_round_trip_all_roles`
* `TestParserRobustness::test_llama3_round_trip_with_eot_prefix`
`pytest studio/backend/tests/test_safetensors_tool_loop.py
studio/backend/tests/test_safetensors_capability_advertise.py -q`
goes from 118 to 125 passed.
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* Trim verbose comments in tool-call parser sections for PR #5624
Pure comment / docstring tightening on top of the GLM 4.7 + Kimi
multi-section fixes. No behavioural change.
* Drop multi-paragraph prelude and post-refactor citation chatter in
the DeepSeek, GLM and Kimi parser docstrings; keep the shape and
upstream-commit pin.
* Collapse ``parse_tool_calls_from_text``'s 9 per-family blocks into
a single ordered loop with one combined comment.
* Tighten the GLM coercion, Kimi bare-counter and ``_TOOL_XML_RE``
comments to one or two lines each.
* Same trim pass on ``_PARSER_MARKERS`` and the regression-test
docstrings.
Tests:
pytest studio/backend/tests/test_safetensors_tool_loop.py
studio/backend/tests/test_safetensors_capability_advertise.py
studio/backend/tests/test_pr5624_regressions.py -q
-> 174 passed in 2.00s
* Fix O(N^2) DeepSeek V3.1 backtracking for PR #5624
Adversarial input ``<|tool▁calls▁begin|><|tool▁call▁begin|>fn<|tool▁sep|>``
followed by a long body that does NOT contain a closing brace caused
the V3 path's ``([^\n<]+?)<|tool▁sep|>`` regex to backtrack
quadratically: at each position the lazy quantifier extends one char
at a time looking for a sep that isn't there, taking ~19s on 50k
chars.
Replace the regex search with ``str.find`` on the sep marker plus a
left-walk to recover the name. ``str.find`` is O(N); the walk stops
on ``\n`` (turn boundary), ``<`` (start of a tag), or ``>`` (end of
an optional ``<|tool▁call▁begin|>`` prefix). Same observable
behaviour as the regex on every canonical input.
Tests:
test_deepseek_v3_1_huge_truncated_body_is_linear (new) -- 50k chars
must parse in < 1s.
pytest studio/backend/tests/test_safetensors_tool_loop.py
studio/backend/tests/test_safetensors_capability_advertise.py
studio/backend/tests/test_pr5624_regressions.py -q
-> 175 passed in 1.97s
pytest studio/backend/tests/ -q -k 'not gpu and not llama_cpp_integration'
-> 2038 passed, 15 pre-existing failures unchanged.
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* studio: terminate function-XML body at </function>, not just </tool_call>
`_parse_function_xml` was looking for `</tool_call>` (the Hermes
wrapper) as the body terminator. When a model emits a standalone
`<function=NAME><parameter=K>v</parameter></function>` followed by
explanatory prose (which models routinely do), no `</tool_call>` is
present, so the body extended to end-of-string and the trailing
prose leaked into the LAST parameter value.
Pre-existing on main (the legacy `<function=NAME>` form had this
bug too). Same affects PR #5620's new attribute-form
`<function name="NAME"><param name="K">v</param></function>`
emission used by MiniCPM-5 / MiniMax-M2.
Fix: `_TC_END_TAG_RE` now matches either `</tool_call>` OR
`</function>`. The existing `_TC_FUNC_CLOSE_RE` / `_TC_PARAM_CLOSE_RE`
strips are unchanged. Multi-call inputs still bound each function
at the next `<function=` start, so no over-eager consumption.
New tests:
* `test_function_xml_followed_by_prose` (legacy form + prose)
* `test_function_attribute_xml_followed_by_prose` (attribute form + prose)
Existing `test_code_with_embedded_xml` still passes (a parameter
value containing literal `<a></a>` is preserved because the
embedded close tag is `</a>`, not `</function>`).
`pytest studio/backend/tests/test_safetensors_tool_loop.py
studio/backend/tests/test_safetensors_capability_advertise.py -q`
goes from 125 to 127 passed.
* Studio: tighten Llama-3.2 bare-JSON guard
A fuzz pass on PR #5811 turned up that ``_parse_llama3_bare_json``
accepted ``parameters`` as a string, contradicting the docstring's
"parameters or arguments is a dict" guard. Prose JSON like
``{"name":"foo","parameters":"a sentence"}`` would wrongly fire the
parser, which the agentic loop would then heal into a real
``foo(query="a sentence")`` call.
Same code lives on this branch, so the same fix applies here.
Tightened guard:
- ``parameters`` must be a dict (Llama-3 spec).
- ``arguments`` may be a dict, or a JSON-encoded string that
decodes to a dict (OpenAI shape, e.g.
``"arguments":"{\"q\":\"x\"}"``). Plain non-JSON strings or
JSON-strings of lists / scalars / null no longer pass.
Mirrors the fix landed in PR #5811 commit 615b8608. Adds the same
4 regression tests under TestParserMultiFormat.
Existing test suite stays green: 127 -> 131 passing.
* Studio: skip non-scalar args in python_tag JSON form
The JSON sub-path of ``_parse_llama3_python_tag`` was fabricating
``{"value": args}`` when the model emitted a non-dict / non-string
``arguments`` value (e.g. ``42``, ``[1,2,3]``, ``null``, ``true``).
This silently turned a malformed emission into a real tool call,
which the agentic loop would then execute with arguments the model
never intended.
Tightened: skip the call instead of fabricating. The same
behaviour now matches the bare-JSON guard tightened earlier
(strict-guard merge from PR #5620, inherited via merge here).
Added a regression test covering the four non-scalar shapes.
Pass count on this branch: 158 -> 159.
Sites in ``_parse_tool_call_json`` and ``_consume_mistral_call``
keep the existing looser behaviour for now; both are reached
only after explicit ``<tool_call>`` / ``[TOOL_CALLS]`` markers
so the false-positive surface there is much narrower.
* studio: fix safetensors tool-call parser gaps vs llama.cpp (Mistral CALL_ID / THINK, attribute-form signal)
Three GGUF-parity fixes to the safetensors tool-call parser, each matching
llama.cpp's reference behaviour:
- Mistral Small 3.2 emits [TOOL_CALLS]name[CALL_ID]<id>[ARGS]{json}. The
parser stopped after the name on seeing [CALL_ID] (neither [ARGS] nor {),
dropping the call. Skip an optional [CALL_ID]<id> segment in both the
parse and strip paths. llama.cpp parses this (test-chat.cpp:4785).
- Magistral wraps reasoning in [THINK]...[/THINK]. A [TOOL_CALLS] inside the
reasoning was parsed as a real call, producing a phantom call. Strip a
leading [THINK] block before scanning so only the post-reasoning call
counts (test-chat.cpp:2285); a literal [THINK] inside a later argument is
left intact.
- The standalone MiniCPM-5 / MiniMax-M2 <function name="..."> attribute form
parsed correctly but was absent from TOOL_XML_SIGNALS and the markup strip
patterns, so the streaming safety-net parse was gated off (dropping the
call) and markup leaked into displayed text. Add the signal and broaden
the strip regexes.
Adds regression tests for all three.
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* studio: fix GLM and Kimi K2 safetensors tool-call parser gaps vs llama.cpp
Four GGUF-parity fixes for the GLM and Kimi K2 families:
- GLM 4.7 zero-argument inline call <tool_call>name</tool_call> was dropped:
the open-tag lookahead only allowed \n or <arg_key> after the name. Allow
</tool_call> too so a no-arg call parses to empty args (vLLM / SGLang /
llama.cpp all parse it).
- GLM string argument values were stripped, losing significant leading /
trailing whitespace in code / diff arguments. Keep the raw value for the
string fallback and only strip the copy used to probe for a JSON literal,
matching vLLM glm4_moe which never strips string args.
- Kimi K2 calls emitted without the <|tool_calls_section_begin|> wrapper
were dropped. llama.cpp makes the section optional (Kimi can call a tool
straight after reasoning without opening a section); parse a bare
<|tool_call_begin|> when no section is present.
- Kimi K2 malformed / truncated JSON in one call dropped every later call in
the section. Skip the bad call and keep parsing so valid subsequent calls
are recovered (vLLM parity).
Adds regression tests for all four.
* studio: fire safetensors tool calls for the bare-JSON (Llama-3.2) form
The agentic loop's streaming safety-net parse was gated on
has_tool_signal(), which is False for the Llama-3.1 / 3.2 bare-JSON tool
form {"name":..,"parameters":..} (no XML marker). Real tool calls were
therefore dropped: the loop logged "model planned without calling tools",
re-prompted three times, then gave up with zero tool calls, while GGUF's
llama-server parses the same emission natively.
Run parse_tool_calls_from_text() unconditionally in the safety net. The
parser is strict (only fires on a valid tool-call shape) so plain answers
are unaffected. Reproduced on a real unsloth/Llama-3.1-8B-Instruct run:
the model emits {"name":"web_search","parameters":{...}} which now
executes the tool instead of being re-prompted into a no-op.
Adds a loop regression test for the bare-JSON form.
* studio: fire safetensors tool calls for Gemma 4 (native template + stripped parser)
Gemma-4 safetensors fired no tools while its GGUF fired reliably. Three gaps:
- The Studio swaps in the Unsloth "gemma-4" chat template, which does not
render the tools schema (the model's native template does), so the model
never saw the tools. Fall back to the model's native template when the
override template renders identically with and without tools. Same fix
helps any family whose override template drops tools.
- skip_special_tokens strips the <|tool_call> wrapper and <|"|> string
markers, so a streamed Gemma-4 call arrives as a bare call:NAME{k:v, ...}
with unquoted values. Parse that form, keeping commas/braces inside a
code or command value, normalising surrounding quotes, and stripping the
leaked markup from the final answer.
- Without a grammar a small model can loop, repeating one call for the whole
tool budget. Collapse exact-duplicate calls within a turn and force a final
answer after a turn that made no new tool progress (llama-server's lazy
grammar prevents this loop on the GGUF side).
Adds parser tests for the bare/stripped Gemma-4 form.
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* Studio: complete strict-mode contract and fix parser import paths
Address review findings on the multi-format tool-call parser:
- Honor allow_incomplete=False in the remaining sub-parsers. The Llama-3
<|python_tag|>NAME.call(...) parser, the pre-v11 Mistral [TOOL_CALLS] array
parser, and the Gemma 4 <|tool_call> parser ignored strict mode, so a
truncated call (missing closing paren, ], or <tool_call|>) was still healed
and executed with Auto-Heal disabled. Thread strictness through and reject
the unclosed forms, matching the JSON and function-XML paths.
- Drop the duplicate tool_call_parser import block in llama_cpp.py and the
redundant un-aliased TOOL_XML_SIGNALS; only the _SHARED_TOOL_XML_SIGNALS
alias is used as a value.
- Import _strip_mistral_closed_calls from core.inference.tool_call_parser in
routes/inference.py instead of studio.backend.core... The self-contained
run.py launch mode only puts studio/backend on sys.path, so the absolute
package path raised ModuleNotFoundError on the server-tool strip path.
Add strict-mode regression tests for the truncated Llama-3 dot-call and the
unclosed Mistral array.
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* Studio: harden DeepSeek/Kimi tool-call parsing and strip
Address review findings on the DeepSeek and Kimi parsers:
- Honor allow_incomplete=False for DeepSeek. An envelope with no closing
<|tool▁calls▁end|> is truncated mid-stream; reject it in strict mode
instead of healing the body out to EOF, matching the strict XML and Mistral
paths.
- Do not skip a following tool call when the current call's end marker is
missing. The DeepSeek V3 and Kimi loops advanced by searching forward for the
next <|tool▁call▁end|> / <|tool_call_end|>, which could land on a later
call's end marker and drop the call in between. Advance by the JSON end; the
loop re-locates the next call marker from there.
- Strip truncated DeepSeek and Kimi section blocks in the route-level display
regex. The patterns required the closing marker; add the end-of-text
alternative so a block truncated by EOS does not leak raw markup to the UI.
Add regression tests for the truncated DeepSeek envelope, and for DeepSeek and
Kimi multi-call recovery when the first call's end marker is missing.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: preserve XML param indentation and alias Mistral array parameters
Two parser-correctness fixes found by auditing against the model chat templates
and the SGLang / vLLM reference parsers:
- Qwen3.5 XML parameter values lost their leading indentation. The chat template
emits <parameter=k>\nVALUE\n</parameter>, but the parameter-start regex ate the
wrapping newline AND the value's first-line indentation with a trailing \s*,
then str.strip() removed the rest. Narrow the trailing class to horizontal
whitespace only and trim exactly one wrapping newline (via _trim_param_value),
preserving indentation in code/diff arguments. Matches SGLang's qwen3_coder
detector. Applies to both _parse_function_xml (tool_call_parser.py) and the XML
path in tool_healing.py.
- Mistral pre-v11 array objects keyed on parameters dropped their payload.
_consume_mistral_call read only the arguments key; alias parameters the same way
the JSON/XML paths and SGLang's base detector do.
Add regression tests for preserved multi-line indentation and the array
parameters alias.
* Studio: DeepSeek strip sync, Gemma nested args, GLM/Kimi strict mode
Parser-correctness fixes found by auditing DeepSeek/GLM/Kimi against vLLM,
SGLang, and the model chat templates:
- DeepSeek: the short <|tool▁calls|> opener (and the space / escaped-underscore
spellings) was parsed but never stripped, so a short-opener envelope leaked raw
markup to the UI. Share one opener alternation between _DEEPSEEK_BEGIN_RE and
the strip patterns (and the route-level display regex) so a signal we parse can
never be left un-stripped.
- Gemma wrapper-less stream: a nested object/array argument (loc:{city:NYC},
labels:[bug,ui]) was kept as a literal string. Parse it recursively when the
bare value is a balanced {} / [], falling back to the raw string for a
truncated value.
- GLM and Kimi ignored allow_incomplete. With Auto-Heal off, a GLM block with no
</tool_call>, a Kimi section with no <|tool_calls_section_end|>, or a Kimi call
with no <|tool_call_end|> are truncated and must be rejected, matching the
strict behavior of the JSON/XML/Mistral/DeepSeek paths and vLLM/SGLang.
Add regression tests for the short-opener strip, the Gemma nested args, and GLM /
Kimi strict-mode rejection.
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* Studio: tighten tool-call parser comments
Make the comments in the multi-format tool-call parser and its callers succinct:
compress verbose docstrings/blocks to one or two lines, drop ones that restate the
code, and trim the tiny balanced-scanner helpers. Correctness rationale and
upstream provenance (SGLang/llama.cpp parity, the strict-mode / Auto-Heal
contract, whitespace-preservation, and the Unicode / full-width-pipe notes) are
kept in compact form.
Comment-only: no code or behavior change (verified with comment_tools.py check
--strip-docstrings; parser suite green).
* Studio: tighten DeepSeek/GLM/Kimi parser comments
Compress the comments added for the DeepSeek/GLM/Kimi parsers and the Gemma
wrapper-less helpers to one or two lines, keeping the upstream provenance
(llama.cpp 51fa458a92d6), the O(N^2) / strict-mode rationale, and the vLLM parity
notes intact.
Comment-only: no code or behavior change (verified with comment_tools.py check
--strip-docstrings; parser suite green).
* Studio: make DeepSeek R1 / GLM parsing linear and close routes strip gaps
Review follow-up for the DeepSeek/GLM/Kimi parser:
- DeepSeek R1 detection used a greedy ``([^\n]+)\n```json`` regex that backtracks
O(N^2) on a fence-less truncated body; scan with str.find instead (mirrors the
V3 path).
- GLM arg pairs used a lazy-group finditer that rescanned to EOF from each bare
<arg_key> in an unclosed body (O(N^2)); walk pairs with str.find.
- The route display strip (_TOOL_XML_RE) accepted fewer DeepSeek openers than the
parser (missed the space / escaped-underscore spellings) and missed bare
section-less Kimi calls, so a call we parse could leak raw markup to the UI.
Reuse the parser's shared _DEEPSEEK_OPEN_RE_SRC and add a bare-Kimi arm.
Add ReDoS-linearity regressions for the R1 and GLM paths, a positive R1
fenced-json parse test, and routes-strip tests for the space/escaped DeepSeek
openers and the bare Kimi call.
* Studio: fix test_mcp_servers _TOOL_XML_RE reconstruction after _DS_OPEN_SRC reuse
The routes strip fix made _TOOL_XML_RE reference the module-level
_DS_OPEN_SRC variable. test_mcp_servers reconstructs the regex by exec-ing
the extracted compile() source in a namespace that only defined _re, so it
raised NameError. Inject _DS_OPEN_SRC into that namespace, matching the same
fix already applied in test_tool_xml_strip.
* Studio: make Llama-3 .call and Mistral-array healing parsing linear
Two more O(n^2) ReDoS paths in the multi-format parser, both reachable from
the agentic loop on a long truncated body with no length cap:
- _LLAMA3_KV_RE.finditer over a .call(...) body retried at every offset of a
long word run / unterminated quote (40K -> 14s). Replace with a hand-scan
that reuses the same key/number/literal sub-regexes via anchored match and
walks the string body by hand, so an unterminated quote is O(n). Verified
byte-identical to the old regex over 200K fuzzed inputs.
- _parse_mistral_array healing ran _balanced_brace_end from every { in the
body (20K -> 17s). Walk top-level objects, advancing past each balanced
{...}; this also drops the phantom call the old scan emitted from a nested
argument object.
Add adversarial-length linearity regressions plus positive .call kwargs and
unclosed-array recovery coverage.
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* Studio: strengthen #5624 regression assertions and strip-test harness guards
- test_strip_tool_markup_handles_deepseek_envelope used `A or B` where B was the
preservation property the next line already asserts, masking the real check.
Replace with an explicit assertion that the call name and args are stripped.
- The test_tool_xml_strip source-extraction harness reconstructs _TOOL_XML_RE and
_strip_tool_xml_for_display from routes/inference.py via lazy regexes that could
silently grab a shorter slice. Assert the extracted regex carries the DeepSeek /
bare-Kimi arms and the helper body reached the _TOOL_XML_RE.sub call.
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* Studio: honor strict mode in safety-net, keep empty Gemma args, strip attribute-form function XML
- safetensors safety-net parser now forwards allow_incomplete=auto_heal_tool_calls,
matching the draining path, so a late incomplete tool call is not healed and
executed when Auto-Heal is off.
- Gemma empty bare value ({k:}) now serialises as "" instead of invalid {"k":},
which previously dropped the whole call.
- Route _TOOL_XML_RE also strips the <function name="..."> attribute form
(MiniCPM-5 / MiniMax-M2) so it no longer leaks to the UI.
* Studio: linearize wrapper-less Gemma nested-arg parsing and correct parser provenance
- _gemma_parse_value/_gemma_parse_mapping/_gemma_parse_array now parse nested
{}/[] in a single forward pass instead of pre-scanning each subtree with a
balanced-brace walk and re-parsing it. Deeply nested wrapper-less Gemma args
were O(n^2); they are now ~linear (and ~40x faster at depth 400).
- Correct the DeepSeek/GLM/Kimi provenance comments: the cited commit
51fa458a92d6 is unrelated, and GLM/Kimi were never standalone
common_chat_parse_* functions (llama.cpp uses common_chat_params_init_glm_4_5
plus a generalized XML parser, PRs #15904 / #16932).
- Add tests: Gemma deep-nesting linearity, nested object/array preservation,
same-turn distinct-call cap, and the native-template tool-render fallback.
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* Studio: guard Gemma value parser against non-advancement and missing tokenizer
Addresses Gemini review:
- _gemma_parse_value now consumes one character when a stray }/]/, sits where a
value is expected, so _gemma_parse_array can never stall at the same index on
malformed input (a latent infinite loop).
- _render_with_native_template returns None when neither a tokenizer nor a
processor is present instead of raising AttributeError.
- Tests for both.
* Studio: fix attribute-form function-XML literal close tag and zero-arg strict call
Addresses Codex review of the <function name="..."> attribute form in
_parse_function_xml (MiniCPM-5 / MiniMax-M2):
- End the call body at the LAST </function> / </tool_call> within the call's
window, so a literal close tag inside a code/search argument (e.g.
print("</function>")) is preserved instead of truncating the call.
- Accept a closed call with no parameters as a valid zero-argument call in strict
mode (the function close is already required), instead of rejecting it as a
truncated call.
- Tests for both, mirroring the legacy <function=...> coverage.
* Studio: drop scratch review/planning artifacts from the branch
* Studio: fix tool-call parser/loop review findings on the multi-format path
Address the live code-review findings on the safetensors/MLX + GGUF tool path:
- routes: include the attribute form <function name="..."> in the safetensors
capability whitelist so MiniCPM-5 / MiniMax-M2 templates keep the tool pill
(parser already handles the form; the post-filter wrongly suppressed it).
- safetensors loop: build the plan-without-action re-prompt from the active
tools instead of a hardcoded web_search/python string, and gate it on
auto_heal_tool_calls, matching the GGUF loop.
- safetensors loop: hold a leading bare-JSON object ({"name":..,"parameters":..})
during BUFFERING until it closes, then drain it as a tool call instead of
streaming the raw JSON to clients. The DRAINING/STREAMING resolvers still
recover a plain JSON answer, so this can never drop content.
- parser: anchor the Llama-3 <|python_tag|>NAME.call(...) scan to the tag and
chain ; -separated calls, so all semicolon-separated built-ins parse and a
literal <|python_tag|>x.call(...) inside a JSON string argument no longer
fires the wrong tool.
- parser: consume the optional trailing </s> after a named Mistral
[TOOL_CALLS]name{json} call, mirroring the array shape.
- GGUF streaming strip: use the shared parser patterns (which know
[TOOL_CALLS] and <|python_tag|>) so a textual tool call entering DRAINING is
stripped instead of leaking the marker to streaming clients.
- routes: hoist the _strip_mistral_closed_calls import to module level.
Adds regression tests covering each fix; existing parser suite stays green.
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* Studio: fix DeepSeek/GLM/Gemma tool-call review findings
Address the live code-review findings specific to the DeepSeek / GLM / Kimi
and native-template additions:
- parser: in strict mode (Auto-Heal off) require the per-call
<|tool▁call|end|> terminator for DeepSeek V3 calls instead of executing on
a bare balanced object closed only by the envelope end.
- parser: keep GLM string arguments that begin with a quote verbatim (drop
the leading-quote case from the JSON-decode probe) so a quoted search query
is not decoded down to its inner text.
- parser: reject a GLM call with an unclosed <arg_value> in strict mode, and
under Auto-Heal keep the partial value rather than dropping it to a no-arg
call.
- parser: add a balanced wrapper-less Gemma strip (call:NAME{...}) so a nested
object/array argument is removed whole instead of leaving a trailing brace;
run the balanced Mistral and Gemma strips on the streaming display paths too.
- safetensors loop: buffer a leading wrapper-less Gemma call:NAME{...} so it
drains and executes instead of streaming the raw call text.
- inference: render the native-template fallback on a shallow tokenizer copy
instead of mutating the shared tokenizer outside the generation lock, and
load the native template from base_model for LoRA adapters.
Adds regression tests for each; existing parser suite stays green.
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* Studio: harden multi-format tool-call detection from review findings
Apply five targeted fixes from the review pass over the multi-format tool
path:
- routes: route display strip delegates to _strip_tool_xml so Mistral
[TOOL_CALLS] blocks with nested JSON are removed from streamed display
text, not just the XML forms.
- tool_call_parser: skip function/parameter starts that fall inside an
already-open parameter block (_inside_open_parameter) so nested example
payloads are not mis-parsed as new calls; extract
strip_llama3_leading_sentinels so the bare-JSON guard is shared.
- safetensors_agentic: probe bare JSON through strip_llama3_leading_sentinels
before the balanced-brace check so a leaked header sentinel does not defeat
the guard.
- tool_healing: allow dotted tool names in the Gemma wrapped start pattern.
- llama_cpp (GGUF): buffer wrapper-less Llama-3.2 {"name":..} calls that carry
no XML signal, drain a complete object silently and hold an incomplete one,
and run the end-of-stream safety net unconditionally so markerless calls are
detected and never leak the raw JSON (including truncated fragments).
Adds regression tests for the GGUF bare-JSON streaming path and the Mistral
display strip.
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* Studio: stop bare-JSON tool calls leaking at EOF, oversized, and into history
The second review pass flagged that the Llama-3.2 bare-JSON tool-call handling
still leaked raw JSON in several spots; ``strip_tool_markup`` only knows
XML/bracket markup, so the bare-JSON form survived it. Fix them symmetrically
across the safetensors and GGUF loops:
- Safetensors stream-end resolver now routes a held bare-JSON fragment to
DRAINING (mirroring GGUF) so a truncated ``{"name":..`` cut off by the end of
the stream is dropped instead of flushed as assistant content. The 7/10
reviewer finding.
- Both loops now drain (suppress) an oversized still-open bare-JSON call once it
passes ``_MAX_BARE_JSON_BUFFER`` instead of streaming the raw prefix, gated on
a ``"name"`` key so a giant plain JSON answer still streams; a complete
oversized call still executes via the safety net.
- Add a shared ``strip_leading_bare_json_call`` helper and apply it to the
content kept for the assistant turn in both loops, so an executed bare-JSON
call is not replayed as visible text or fed back as next-turn history.
Plain JSON answers without a ``"name"`` key are untouched throughout. Adds
regression tests for the EOF, oversized, and next-turn cases on both backends
plus unit tests for the helper.
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* Studio: bound the Llama-3 python_tag strip on real control sentinels
The route display strip's <|python_tag|> arm ran to the next <| of any kind.
A tool-call argument carrying a literal <|...|> token (for example <|cite|>
inside a string value) truncated the strip early and leaked the call tail into
the visible response. Narrow the stop condition to the genuine Llama control
sentinels (eot_id, eom_id, python_tag, start/end_header_id, begin_of_text,
finetune_right_pad_id) so embedded markup and JSON are consumed while real
header/turn boundaries still bound the strip.
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* Studio: harden GLM/Gemma parsing, cap GGUF textual calls, share native-template fallback
GLM 4.x parser walked a body pre-bounded by the first </tool_call>, so a string
argument containing a literal </tool_call> (e.g. code that prints it) was
truncated. Walk arg_key/arg_value pairs against the full content instead, since
each <arg_value> is delimited by its own </arg_value> and the call's real close
is the </tool_call> that precedes the next <arg_key>.
Add a truncated wrapper-less Gemma pattern (call:NAME{... with no closing brace)
to the markup strip so a call cut off mid-arguments does not leak raw into the
visible stream. It runs after the closed form, so a complete call keeps trailing
prose.
Cap and dedup tool calls parsed from the GGUF TEXTUAL fallback at
_MAX_TOOL_CALLS_PER_TURN, mirroring the safetensors loop. Structured
delta.tool_calls are grammar-bounded by llama-server, but text parsed straight
from content is not, so one runaway turn could fan out into dozens of
executions.
Extract the native-chat-template fallback into chat_template_helpers
(render_native_template / render_with_native_template_fallback) so the
transformers and MLX text backends share one implementation. The MLX text path
now applies it too, so an Unsloth override template that drops the tools schema
no longer silently stops MLX from advertising tools. The MLX VLM path renders
via the processor for image tokens and is intentionally left on its own render.
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* Studio: gate markerless bare JSON on enabled tools and close parser/strip asymmetries
The Llama-3.2 custom_tools bare-JSON form has no marker, so any JSON object with a
name key was read as a tool call. An ordinary JSON answer like
{"name":"Alice","parameters":{"age":30}} was misclassified as a call to a
disabled tool and dropped from the visible response. Gate the markerless form on
the enabled tool names (threaded through parse_tool_calls_from_text and
strip_leading_bare_json_call, supplied by both streaming loops): an object whose
name is not an enabled tool is ordinary content. The marker-based forms keep
their name-agnostic behaviour (an explicit signal is a real call attempt), and
unrestricted mode stays ungated.
Also fix two parser/strip asymmetries the parser already tolerated:
- A literal </function> inside a parameter value (print("</function>")) truncated
both the core and route strips at the first close, leaking the tail. Extend the
strip to the call's real close (last </function> before the next opener),
mirroring the parser, without merging separate calls.
- The single-object Mistral [TOOL_CALLS]{...} shape parsed but _strip_mistral_closed_calls
left it, leaking the raw object into display. Strip the balanced object while
keeping trailing prose, matching the array and name shapes.
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* Studio tools: fix strip/parse symmetry and native-template token for DeepSeek/GLM/Kimi
Pass-3 review follow-ups on the multi-format tool parser:
- Bare Kimi call (<|tool_call_begin|>...<|tool_call_end|> with no section
wrapper) is accepted by the parser, so add it to the closed strip patterns
so the streaming (non-final) display strip removes it instead of leaking the
markup mid-generation.
- Route display strip now also runs the wrapper-less Gemma cleanup, so a
Gemma 4 call:NAME{..} no longer leaks into the visible answer.
- MLX model record carries base_model for a LoRA adapter so the native-template
fallback loads the base repo template rather than the adapter's
(often template-less) tokenizer.
- Native-template reload forwards the load-time HF token so a gated/private
model's repo template can still be fetched (transformers and MLX text paths).
- GGUF end-of-stream bare-call heuristic is gated on the enabled tool names so a
truncated ordinary JSON object ({"name":"Alice","age":) streams as the answer
instead of being dropped as a tool call.
Adds regression tests for each case.
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* Studio tools: gate GGUF bare-JSON suppression on enabled tools and fix python-tag exponent parsing
Pass-4 review follow-ups on the GGUF tool loop and Llama-3 parser:
- The GGUF bare-JSON suppression sites still keyed off a raw "name" substring,
so an ordinary JSON answer whose name is not an enabled tool was dropped when
it was truncated, oversized, or reached the no-tool DRAINING fallback (the
parser, helper, and safetensors paths were already gated). All three sites now
use the shared enabled-name gate, and a held bare-JSON buffer that turns out not
to be an enabled call is shown as the answer instead of dropped at stream end.
- The Llama-3 python-tag numeric kwarg regex matched only the mantissa, so
scientific notation was truncated to its leading digits (1e-3 parsed as 1) and a
tool executed with the wrong value. The regex now accepts exponent and decimal
forms, and the int/float classification keys off the exponent too.
Adds regression tests for the truncated / oversized disabled-name JSON cases (and
a counterpart that a truncated enabled call still does not leak) plus the
scientific-notation kwargs.
* Studio: drop accidentally committed async worker transcripts
Eight generated reviewer / async-worker transcripts were committed under
studio/backend/async_task_outputs/. They are not imported or referenced by any
code and carry only internal task state, so they should never ship in the repo.
Remove them and gitignore the directory so they cannot be re-added.
* Studio tools: gate safetensors bare-JSON drain, fix nested-name gate and function-XML strip
Pass-4 review follow-ups on the shared parser / safetensors loop:
- The safetensors oversized and end-of-stream bare-JSON drain branches keyed off
a raw "name" substring, so a large or truncated ordinary JSON answer whose name
is not an enabled tool was drained instead of streamed. Both now use the shared
enabled-tool-name gate, matching the GGUF path.
- strip_leading_bare_json_call matched the first "name" anywhere, so a plain JSON
answer with a nested name equal to an enabled tool ({"result":{"name":"web_search"}})
was wrongly suppressed. It now extracts the TOP-LEVEL name only, walking past
nested objects/arrays and keeping the text when a top-level value is truncated.
- The function-XML display strip used a regex negative-lookahead that stopped at a
literal <function=...> opener inside a parameter value and then dropped the rest
of the answer to EOF. A scan-based strip mirrors the parser (ignores openers
inside an open <parameter> via _inside_open_parameter) and closes each call at its
real </function>, so trailing assistant text after such a call survives.
Adds regression tests for each.
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* Studio: keep tools prompt when native-template probe raises; make helper tests hermetic
Pass-4 review follow-ups on the native-template fallback:
- render_with_native_template_fallback re-renders the live template with tools=None
to detect whether it dropped the schema. A template that requires tools can raise
on that probe; that must not discard the already-valid tools prompt. The probe is
now wrapped so any error returns the original formatted_prompt (transformers would
otherwise fall back to manual formatting and lose the schema; MLX would let the
exception escape).
- The native-template helper tests imported InferenceBackend just to reach the
thin wrapper, which pulls in unsloth and its optional vllm package metadata. They
now call the dependency-light render_native_template helper directly so they pass
in a backend/test environment without vllm. Adds a probe-raises regression test.
* Tool parsing: 3.9 import safety, disabled-Auto-Heal contract, capability gate
Round-2 review follow-ups on the multi-format tool-call parser:
- tool_call_parser: add `from __future__ import annotations`. The module
is dependency-light by design (external llama-server wrappers import it
standalone) and the package targets python >=3.9, where its PEP 604
`int | None` return annotations would raise TypeError on import.
- safetensors + GGUF drain fallback: gate the leading bare-JSON strip on
auto_heal_tool_calls. With Auto-Heal off, a truncated enabled-name
fragment that did not parse now stays visible, matching the XML strip
in the same branch and the disabled-Auto-Heal contract. With Auto-Heal
on it is still suppressed.
- safetensors capability gate: match the bare-JSON `{"name":` template
marker with a whitespace/escape-tolerant regex so a pretty-printed
`{ "name" :` or JSON-escaped `{\"name\":` template is not mis-classified
as tool-less. The parser already accepts that whitespace via
raw_decode, so the gate must too.
Regression tests added for each case.
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* GLM tool-call display strip: treat literal close tag in arg value as data
Round-2 review follow-up on the GLM 4.x tool-call format.
The GLM call shape is <tool_call>NAME<arg_key>k</arg_key><arg_value>v
</arg_value>...</tool_call>. The parser was hardened to walk arg_key /
arg_value pairs so a literal </tool_call> inside an argument value (e.g.
print("</tool_call>")) is treated as data and the call's real close is the
</tool_call> that precedes the next <arg_key>. The display strips still used a
non-greedy <tool_call>.*?</tool_call> regex, which stopped at the literal and
leaked the call's tail into visible content and stale history.
Add _strip_glm_calls, a scan that mirrors the parser's close detection, and run
it before the regex arms in every strip pipeline: the core strip_tool_markup,
the route _strip_tool_xml display/history cleanup, and the safetensors + GGUF
streaming strips. Qwen / Hermes <tool_call>{json} has no NAME token after the
opener, so it is left to the regex arms unchanged.
Regression tests cover the literal-close-tag leak (core + route), normal GLM
calls, back-to-back GLM calls, zero-arg GLM, truncated GLM, and untouched Qwen.
* Tool parsing: symmetric "function" bare-JSON alias and route strip parity
Round-3 review follow-ups, all parser/strip symmetry fixes.
- Bare-JSON "function" alias: the markerless parser accepts a call name via
obj.get("name") or obj.get("function"), but the strip/gates only knew "name",
so a {"function":<enabled tool>} call executed while its raw JSON leaked. Teach
_top_level_bare_json_name the alias (with "name" precedence and the same nested
and truncated-name guards), and widen the guards in strip_leading_bare_json_call,
the safetensors and GGUF _looks_like_enabled_bare_json gates, and the route
capability marker regex.
- Route display/history cleanup: strip a tail-only </param> alias close (the
parser accepts <param name="...">...</param>), and run the parser's guarded
function-XML scan (_inside_open_parameter) before _TOOL_XML_RE so a literal
nested <function=...></function> inside an argument value does not truncate the
strip and leak the tail.
Regression tests added for each.
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* Studio tools: fix DeepSeek strict recovery, Kimi dotted names, Gemma spaced streaming
Round 3 review fixes for the DeepSeek / GLM / Kimi tool-call parsing path.
- DeepSeek R1 and V3/V3.1 strict parsing (Auto-Heal off): when a call is
truncated (missing closing fence or <tool_call_end> terminator), skip it
and keep scanning for later well-formed calls instead of breaking out and
dropping the rest of the envelope. This matches the Kimi strict parser's
recovery behaviour.
- Kimi dotted tool names: keep the full name after stripping only the
functions. prefix and :idx suffix, e.g. functions.mcp.server-list:0 stays
mcp.server-list. The previous split on "." truncated dotted MCP names to
their last segment. This matches current vLLM
(tool_id.split(":")[0].removeprefix("functions.")) and SGLang
(^(?:functions\.)?(?P<name>[\w.\-]+):(?P<index>\d+)$).
- Gemma wrapper-less call streaming: hold the whitespace-tolerant prefix
(call : NAME) in the streaming suppression buffer, matching the parser's
_GEMMA_BARE_TC_RE, so the spaced spelling split across chunks is buffered
instead of leaking as visible text. Applied to both the safetensors and
llama.cpp streaming paths.
- Remove dead _render_with_native_template method and the now-unused copy
import from inference.py; the live path uses render_with_native_template_fallback.
Adds regression tests for DeepSeek R1/V3 strict recovery, Kimi full dotted
name preservation, and the Gemma spaced-call streaming suppression.
* Studio tools: honor tool budget in GGUF loop and guard function-XML streaming strip
Round 4 review fixes. Both are asymmetric-fix bugs where the final/steady path got a
guard the analogous streaming/loop path did not.
- GGUF tool-call budget: the safetensors loop counts real tool-call turns against
max_tool_iterations (re-prompt stalls excepted), but the GGUF loop only bounded the
turn count by the enlarged range (max_tool_iterations + _MAX_REPROMPTS). Since this
PR raised _MAX_REPROMPTS from 1 to 3, a model that keeps making valid tool calls
could run up to three extra tool rounds (with max_tool_iterations=1, four rounds
instead of one). Add a _tool_iters_done counter that increments only when a tool
actually executed in the turn, and stop once the caller's budget is spent so the
post-loop final-answer nudge fires. A duplicate/disabled no-op turn is a correction
turn (like a plan-without-action re-prompt) and does not consume budget, preserving
the existing "already completed" re-prompt behavior.
- Streaming display strip: the final strip runs the guarded _strip_function_xml_calls
scanner (a literal <function=...> inside a parameter value is data, not a nested
call), but the GGUF and safetensors streaming strips still used only the open-ended
regex arms. When a tool-call argument contained literal function markup, the regex
tail ate everything to end-of-text and dropped the real trailing prose after the
call's true </function>. Run the guarded scanner (and the balanced Mistral strip)
before the regex arms in both streaming paths so streaming and final display agree.
Adds regression tests: GGUF valid tool calls respect max_tool_iterations, and the
streaming strip keeps trailing prose after a function-XML call with a literal marker.
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* Studio tools: safetensors tool budget counts only executed turns (GGUF parity)
Follow-up to the GGUF budget fix. The safetensors loop charged max_tool_iterations
per non-re-prompt iteration (iteration + 1 - reprompt_count), so a duplicate/disabled
no-op turn spent a budget slot even though no tool ran. With a small cap this dropped
real work: for max_tool_iterations=2, a model that made a valid call, repeated it (an
internal no-op correction turn), then made a distinct valid call executed only the
first -- the third turn was sent with no tools and the distinct call was ignored.
Track whether a turn actually executed a tool (set on record_result) and count only
those turns against the cap, matching the GGUF loop. A duplicate/disabled no-op is a
correction turn -- like a plan-without-action re-prompt -- and no longer consumes
budget, so the model still gets its "already completed" nudge and another tool-enabled
turn. Adds a regression test for the small-cap duplicate-then-distinct-call flow.
* Studio tools: fix stale Kimi dotted-name regression test
test_pr5624_regressions.py still expected functions.my.tool:0 to resolve to the last
segment (tool). The parser now preserves the full dotted name (my.tool) after removing
only the functions. prefix and :idx suffix, matching current vLLM/SGLang so dotted MCP
names like mcp.server-list survive. Update the assertion, name, and module docstring to
the corrected contract (the raw id is still preserved on the call).
* Studio: render the reasoning block for safetensors and MLX like GGUF
enable_thinking chat templates (Qwen3/Qwen3.5/GLM) prefill an unclosed <think>
into the generation prompt, so the model emits only the closing </think> then
the answer. The safetensors/MLX chat stream emitted that as plain content, so
the reasoning showed inline with no collapsible thinking block, while GGUF
(which surfaces reasoning via reasoning_content) rendered one. This brings
safetensors and MLX to parity.
- _ResponsesReasoningExtractor gains a reasoning_prefilled mode that starts
inside the reasoning block and splits on the first </think>; default False
keeps GGUF and every existing caller byte-identical. It suppresses a stray
re-emitted <think> and holds partial markers back across chunk boundaries.
- _sf_reasoning_prefill_mode gates the mode on reasoning being enabled for the
request, an enable_thinking or enable_thinking_effort style, and the template
actually using the standard <think>/</think> markers. Models with a bespoke
reasoning channel (e.g. gemma's <|think|>/<|channel>) are excluded so their
answer is never swallowed; gpt-oss (Harmony) and thinking-off requests are
excluded too.
- sf_tool_stream and stream_chunks (the latter also serves MLX) feed text
through the extractor, emitting reasoning_content then content deltas, with a
per-turn reset in the tool loop and a flush before each tool_start; only the
visible delta reaches the monitor reply. The two non-streaming drains split
reasoning_content the same way.
- Tests: extractor prefilled mode (streaming and edge cases), the gate matrix
including the gemma-style exclusion, and a route-replay of the tool-loop
reasoning stream.
* Studio: render the reasoning block for safetensors and MLX like GGUF
enable_thinking chat templates (Qwen3/Qwen3.5/GLM) prefill an unclosed <think>
into the generation prompt, so the model emits only the closing </think> then
the answer. The safetensors/MLX chat stream emitted that as plain content, so
the reasoning showed inline with no collapsible thinking block, while GGUF
(which surfaces reasoning via reasoning_content) rendered one. This brings
safetensors and MLX to parity.
- _ResponsesReasoningExtractor gains a reasoning_prefilled mode that starts
inside the reasoning block and splits on the first </think>; default False
keeps GGUF and every existing caller byte-identical. It suppresses a stray
re-emitted <think> and holds partial markers back across chunk boundaries.
- _sf_reasoning_prefill_mode gates the mode on reasoning being enabled for the
request, an enable_thinking or enable_thinking_effort style, and the template
actually using the standard <think>/</think> markers. Models with a bespoke
reasoning channel (e.g. gemma's <|think|>/<|channel>) are excluded so their
answer is never swallowed; gpt-oss (Harmony) and thinking-off requests are
excluded too.
- sf_tool_stream and stream_chunks (the latter also serves MLX) feed text
through the extractor, emitting reasoning_content then content deltas, with a
per-turn reset in the tool loop and a flush before each tool_start; only the
visible delta reaches the monitor reply. The two non-streaming drains split
reasoning_content the same way.
- Tests: extractor prefilled mode (streaming and edge cases), the gate matrix
including the gemma-style exclusion, and a route-replay of the tool-loop
reasoning stream.
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* studio: don't force a tool re-prompt on a negated intent (safetensors parity)
The safetensors _INTENT_SIGNAL claimed to mirror GGUF but was missing the
negative lookahead, so a refusal like "I will not search the web for that"
matched the "i will" intent and triggered the plan-without-action re-prompt
(STOP... you MUST call a tool), overriding a valid no-tool answer. GGUF already
excludes not/never. Add the same (?!\s+(?:not|never)\b) lookahead so both
backends agree. Extends the intent parity test with negated refusals.
* studio: parse the outer envelope before DeepSeek/Kimi markers embedded in its args
parse_tool_calls_from_text ran the DeepSeek/Kimi marker pre-pass before the shared
<tool_call>/<function=...> parser. When a Qwen/Hermes call's argument contained
literal Kimi/DeepSeek markup (for example a user asking the model to explain that
syntax), the pre-pass matched the embedded marker and returned it, executing the
wrong tool and dropping the real call. Skip the pre-pass when a <tool_call> or
<function=...> envelope opens before the first DeepSeek/Kimi marker, so the shared
parser takes the outer call; a genuine marker-led call (no leading envelope) still
goes through the pre-pass. Tests for the embedded-marker case and the control.
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* Studio: trim redundant comments (comment-only, AST-verified)
* Studio: trim redundant comments (comment-only, AST-verified)
* Studio: prevent Gemma tool-parser DoS on stray delimiters
_gemma_parse_value returned the input index unchanged when text[i] was a
stray delimiter (,}]), so the list and mapping caller loops that advance
on the returned index spun forever at 100% CPU on malformed input such as
[},]. Advance past the delimiter so parsing always terminates.
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* Studio: strip Magistral [THINK] reasoning from final display/history
strip_tool_markup removed [TOOL_CALLS] and <function> markup but left a
leading Magistral [THINK]...[/THINK] block intact, so its bracket-form
reasoning (not the <think> the reasoning channel renders) leaked into the
safetensors display and conversation history while GGUF/llama.cpp routes
it natively. Drop the leading reasoning block at end-of-turn (final=True)
via the existing _strip_mistral_reasoning helper; streaming is untouched.
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* Studio: keep times in wrapper-less Gemma tool arguments
The wrapper-less Gemma value scanner used _GEMMA_KEY_RE = [\w.\-]+ for keys,
which also matches a digit-leading token, so a comma followed by a time or
ratio inside a value (call:web_search{query:meet at 10:00, 11:00 tomorrow})
was misread as a new 11: key, truncating the query and injecting a bogus
argument. Require keys to start with a letter or underscore, matching the
identifier-start rule the wrapped path already uses (_GEMMA_NEXT_KEY_RE).
Add a regression test.
* Studio: treat markers/close-tags inside tool-call arguments as data
Four parser correctness fixes where a valid argument string was mistaken for
structure:
- DeepSeek: find the envelope-end token outside JSON strings, so a query/code
argument containing the literal token no longer truncates the body and drops
the whole call.
- GLM: locate the real </arg_value> as the one whose next token is <arg_key> /
</tool_call> / end, so a value containing a literal </arg_value> (or
</tool_call>) is kept instead of executing the tool with corrupted arguments.
- Attribute-form <function name="..."> envelopes now count in the embedded-marker
guard, so a DeepSeek/Kimi marker inside a parameter value does not hijack the
outer call and run the wrong tool.
- Wrapper-less Gemma call:NAME{...} is gated on the enabled tool names (parse and
display strip), mirroring the Llama bare-JSON gate, so a disabled/example name in
prose is not stolen as a call and the real answer is preserved.
Add regression tests for each.
* Gate route Gemma wrapperless strip by enabled tools; make Kimi section-end search string-aware
Route-level display stripping now threads the enabled tool-name set into the
Gemma wrapperless-call strip, so prose that mentions a disabled tool
(call:foo{...}) is preserved while active tool calls are still stripped. This
mirrors the parser-level gate already used in tool_call_parser.
The Kimi section-end lookup now searches outside JSON string literals, so a
section-end marker appearing inside an argument string no longer triggers a
false truncation that drops a valid tool call.
* Run DeepSeek/Kimi pre-pass when a closed tool-call example precedes a real block
The marker pre-pass was skipped whenever any <tool_call>/<function> opener
appeared before the first DeepSeek/Kimi marker, even when that opener was a
CLOSED syntax example in prose that ends before the real block. In that case
parse_tool_calls_from_text skipped the DeepSeek/Kimi parsers and the genuine
tool call was dropped while a phantom tool named in the example ran instead.
Only treat a marker as embedded in a leading envelope when removing the closed
outer <tool_call>/<function> envelopes also removes every marker (the marker
actually sat inside one). A marker left standing is a real call, so the pre-pass
runs. The legitimate case of a marker inside a closed outer envelope's arguments
is preserved.
* Honor reasoning_effort none in safetensors prefill; strip Magistral reasoning while streaming
Two safetensors/MLX reasoning fixes surfaced in review:
_sf_reasoning_prefill_mode only checked enable_thinking, so an
enable_thinking_effort (GLM-5.2) request that disables thinking via
reasoning_effort=none (without enable_thinking=False) still began in
prefilled-<think> mode. A plain answer with no </think> was then swallowed
whole into reasoning_content and the visible response came back empty. Thread
reasoning_effort into the predicate and treat none as disabled, mirroring
_request_reasoning_kwargs.
strip_tool_markup_streaming stripped tool markup but not the leading Magistral
[THINK]...[/THINK] bracket block, so the raw chain-of-thought leaked into the
streamed safetensors content instead of the reasoning drawer (GGUF routes it
natively). Apply _strip_mistral_reasoning first, matching the final strip; an
unclosed [THINK] is held from the marker on so nothing flickers.
* Heal truncated outer tool envelopes and keep quoted Gemma args intact
Two follow-ups from review of the marker pre-pass and Gemma parsing:
The leading-envelope guard only removed CLOSED outer <tool_call>/<function>
envelopes before deciding whether a DeepSeek/Kimi marker was embedded, so a
truncated outer call missing its close tag (whose argument embeds a marker) was
treated as a standalone marker and the embedded sample ran instead of the
intended outer call being Auto-Healed. Decide on the last outer opener before the
marker and whether it closed before the marker instead, so a closed syntax
example still runs the pre-pass while a real closed-or-truncated outer call keeps
it.
The wrapper-less Gemma argument scan tracked bracket depth but not quotes, so a
quoted value containing a comma followed by a key-like token (a search query such
as "weather, location: Boston") was split mid-string, truncating the value and
fabricating an extra argument. Track quote state (with escapes) so the top-level
comma boundary is only taken outside quoted spans.
* Span outer envelopes to their real close when locating embedded markers
Locating the DeepSeek/Kimi marker relative to a leading outer envelope used the
FIRST close tag after the opener, so a literal </function> or </tool_call> inside
an argument value (for example python code that contains the text) was mistaken
for the envelope boundary. The marker after it was then treated as a standalone
call and the embedded sample ran instead of the intended outer call.
Match the closed outer envelopes with the shared patterns that already extend to
the real final close (a literal close inside a value is data), and treat a marker
that survives their removal as embedded only when a still-open (truncated) outer
opener precedes it, so Auto-Heal still repairs a truncated outer call. A closed
syntax example before a genuine block still runs the pre-pass.
* Span the tool_call outer envelope to its real close in the marker guard
The leading-envelope check reused the lazy <tool_call>.*?</tool_call> strip
pattern, so a Qwen/Hermes JSON argument containing a literal </tool_call> ended
the span early. A DeepSeek/Kimi sample later in that same string then survived
the closed-envelope removal, and the pre-pass executed the embedded call instead
of the outer <tool_call>. The <function> arm already spanned to its real close;
give <tool_call> the same real-close pattern (with the negative lookahead that
keeps back-to-back calls separate) so a literal close inside a value is data.
* Preserve no-tool Gemma prose and keep later R1 calls when healing a close
Two review follow-ups:
_gemma_strip_gate returned None when no tools were enabled, and None means
strip every markerless call:NAME{...} block, so a no-tool answer that documents
the syntax (or the Anthropic display path, which passes an empty tool list as
None) had that prose deleted. It is a display/history gate, so return the
enabled-name set instead -- an empty set when no tool is enabled, which strips
nothing because every call:NAME{...} is then prose.
The DeepSeek R1 heal path located the close fence with an unbounded forward
search, so when a first call had balanced JSON but omitted its fence the search
landed on a LATER call's terminator and pos advanced past that valid call,
dropping it. Match the close immediately after the JSON (whitespace-skipped) like
the strict path, and advance by just the JSON when it is absent, so a multi-call
turn keeps its later well-formed calls (heal is now a superset of strict).
* Resume wrapper-less Gemma scan past a consumed call's balanced body
The markerless call:NAME{...} scan used finditer, which resumes right after the
opening call: token, so a nested call:OTHER{...} mentioned inside the first
call's own quoted string argument (for example a web_search query that quotes the
Gemma tool syntax) was re-matched and returned as a spurious second tool call,
executing an unintended tool. Walk with a manual cursor that resumes after the
outer call's balanced body (brace matching already skips quoted braces), so a
call's arguments are never rescanned. Genuinely separate back-to-back calls and
disabled/example prose are unaffected.
* Mistral outer call wins over XML literals; align healer signals with its parser
Two follow-ups on the shared-parser ordering after the healing-passthrough
merge:
- A well-formed [TOOL_CALLS] call whose JSON arguments quote tool XML parsed
the literal instead of the outer call (executing the wrong tool). When the
first XML signal sits inside a leading balanced Mistral body it is argument
data, so the Mistral parser now runs first; an XML signal before the trigger
keeps the normal order, so a [TOOL_CALLS] literal inside an XML call's
arguments still stays data.
- passthrough_healing buffered streams on the parser module's broadened signal
list (now including <|python_tag|> and [TOOL_CALLS]) but promotes with
core.tool_healing, which does not parse those forms: a streamed Mistral or
Llama text call was held until finalization and flushed as prose. The healer
keeps its own signal list limited to the formats it can promote, restoring
immediate streaming for the rest.
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* Address review: Gemma wrapper-less marker literals and quotes, GLM embedded close pair
- The Gemma fallback deferral now keys on an actual wrapped opener
(_GEMMA_TC_RE), not the wrapper literal anywhere in content: a wrapper-less
call whose argument merely mentions <|tool_call> has nothing tool_healing
can parse, and deferring it lost the call entirely (not executed and
stripped from display).
- New _gemma_body_brace_end boundary scanner honors single- and double-quoted
strings like _gemma_parse_stripped_body, shared by parse and strip, so a
quoted brace in a code argument (code:print('}')) no longer truncates the
executed arguments or the strip span.
- _glm_value_close now requires a structural </arg_value> to sit at balanced
quote state: the full pair </arg_value></tool_call> embedded inside a string
literal is data, not an early close. When no candidate balances, the first
token-valid close wins as before.
* Address review: leading envelopes win over rehearsed literals
- New _first_foreign_tool_signal shared by the leading-envelope guards adds
<|python_tag|> to the protected signal set: the spelled-out literal inside a
Mistral call's arguments (a query about Llama built-in tool syntax) executed
the inner literal instead of the outer call.
- New _xml_signal_inside_leading_bare_json guard, sibling of the Mistral one:
a leading bare-JSON call whose string argument quotes tool XML (a code value
citing <function=...>) had the literal promoted by the shared XML pass
before the bare-JSON parser ran.
- Magistral [THINK]...[/THINK] is dropped once at parse entry instead of only
inside the Mistral parser, so a call rehearsed in the think block in a
foreign format can no longer be promoted while the real call after the
block is lost. Parse now agrees with the display strip.
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* Address review: a disabled leading bare-JSON object keeps its literals as data
When the leading bare-JSON object is ordinary content (name not an enabled
tool), the guard proved the first tool signal sits inside it, so falling
through to the XML/python_tag passes promoted quoted string data as a real
call. Drop the object and parse only the tail: a real call after the object
still parses, nothing inside it can be promoted.
* Address review: apostrophes in raw Gemma values, GLM strict key contract, per-model template token
- Quote openers in the wrapper-less Gemma boundary and body scanners now
require value-start context (after : { [ ( , =): an apostrophe inside an
unquoted value (query:what's the weather) opened quote mode, swallowed the
real closing brace, and lost the whole call on common contraction queries.
Quoted values keep hiding delimiters as before.
- A GLM <arg_key> with no <arg_value> tag now rejects the call in strict
mode, matching the unclosed-value contract, instead of executing the tool
with the argument silently dropped; Auto-Heal keeps the lenient skip.
- The native-template fallback reads the hf_token stored on the model record
instead of the instance-wide last-load token, so a later token-less load
cannot break template fetches for a previously loaded gated model (both
the transformers and MLX backends).
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* Address review: Mistral literals inside leading JSON, whitespace-tolerant wrapped Gemma opener
- The leading bare-JSON guard now treats the [TOOL_CALLS] trigger as a
foreign signal: the Mistral parser runs before the bare-JSON one, so a
literal quoted inside the leading object's strings was promoted over the
outer call (or over ordinary JSON content).
- tool_healing's wrapped Gemma opener tolerates whitespace around call and
the colon: sampling drift emits call: name{ and call : name{, and
rejecting those lost the call entirely because no fallback re-parses the
wrapped form. Strict mode still requires the closing tag.
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* Address review: DeepSeek/Kimi markers inside leading JSON and Mistral envelopes stay data
The DeepSeek/Kimi pre-pass runs before the outer-call parsers, and
_marker_inside_leading_envelope only protected XML envelopes: a marker
quoted inside a leading bare-JSON or Mistral call's argument strings was
promoted as a separate no-arg call and the real outer call dropped. The
guard now recognizes those two leading envelopes as well; standalone
DeepSeek/Kimi calls keep parsing.
* Address review: accept dotted Gemma argument keys in the key-quoting scanner
The scanner quoted keys of [alnum_-] only, so a dotted key (user.name:...)
was left unquoted, json.loads failed, and the whole wrapped call was lost
(parse empty, strip wipes the markup). Dots now match the parser's own
key/name charset.
* Address review: a real DeepSeek/Kimi call after a disabled leading JSON object still parses
DeepSeek/Kimi markers are foreign signals for the leading bare-JSON guard
too: a marker literal inside a disabled leading object made the envelope
guard skip the pre-pass for the whole message, so a real DeepSeek/Kimi call
after the object was dropped. Routing the case through the guard's
drop-and-parse-the-tail recursion reaches the real call while the literal
inside the object stays data.
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* Address review: leading Mistral call owns the turn, dotted keys after bare values
- A LEADING parseable [TOOL_CALLS] call now runs the Mistral parser first
unconditionally: literal XML in trailing prose after the call was promoted
by the earlier shared XML pass, executing the quoted example instead of
the real leading call. XML leading keeps the normal order.
- _GEMMA_NEXT_KEY_RE accepts dots so a dotted key after a bare value
(query:foo,user.name:bob) ends the value at the comma instead of being
swallowed into it, matching the round-earlier key-quoting charset.
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* Address review: a leading wrapper-less Gemma call owns the turn
A quoted foreign literal inside a leading wrapper-less Gemma call's
argument (a query citing another tool syntax) was promoted by tool_healing
before the Gemma fallback ran, executing the quoted example and dropping
the outer call. New leading guard, sibling of the Mistral and bare-JSON
ones, gated on an enabled name since the form is markerless. Foreign markup
leading keeps the normal order.
* Fix merge resolution: restore both leading-guard test classes intact
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* Address review: markup quoted inside a nameless leading JSON answer stays data
The leading bare-JSON guard required a top-level name, so a structured JSON
answer quoting tool markup in its strings (a response_format turn
documenting a tool's syntax) had the literal promoted by the later passes.
A nameless leading object that parses as real JSON now routes through the
same decline-then-parse-the-tail path; non-JSON braced prose keeps the old
behaviour, and a real call after the answer still parses.
* Address review: JSON answers stay data, nested Gemma quotes, earliest envelope, no failure caching
- A whole-content JSON value is a structured answer: the markerless Gemma
scan and its strip no longer promote or strip a quoted example of an
enabled tool's syntax inside it.
- Nested stripped-stream Gemma values now unquote quoted string leaves
recursively, so {loc:{city:"New York"}} hands the tool New York, matching
the top-level coercion.
- The DeepSeek/Kimi pre-pass dispatches by earliest envelope opener, so a
leading real call wins over a trailing example of the sibling format in
either direction.
- A failed native-template fetch is no longer cached as no-template: the
next call retries after the model record's token is fixed or a transient
Hub error clears; only definitive loads are cached.
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* Address review: closed calls precede the marker pre-pass, truncated Gemma scan stops, quoted nested delimiters
- A closed non-DeepSeek/Kimi call preceding the first DS/Kimi marker owns
the turn: a trailing syntax example, or one quoted inside a wrapped Gemma
argument, was promoted by the pre-pass and dropped the real leading call.
Wrapped Gemma joins the outer-envelope pattern sets.
- An unbalanced wrapper-less Gemma call now stops the scan (mirroring the
strip contract) instead of resuming inside its own argument text, where a
quoted enabled call would be promoted.
- Raw-quoted strings in nested stripped-stream Gemma values hide delimiters,
so {city:"New, York"} is one value instead of a split pair, returned
unquoted like the top-level coercion.
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* Address review: string-marker literals in wrapper-less args, mid-value quoted phrases
- The wrapper-less deferral guard no longer keys on the <|"|> literal: a
real call whose argument merely mentions the string marker was deferred to
tool_healing, which has no wrapped opener to parse, losing the call. The
wrapped-opener check alone owns the deferral.
- Double quotes now also open at the start of a word, so a quoted phrase
mid-value (query:find "weather, location: Boston", limit:3) hides its
delimiters instead of splitting the value into garbage keys; apostrophes
keep the value-start-only rule so contractions stay prose.
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* Address review: strict GLM refuses in-quote close fallback, Gemma guard covers preambles
- _glm_value_close gains a strict flag: a truncated value whose only close
candidates sit inside a string literal rejects the call in strict mode
(Auto-Heal keeps the lenient partial), restoring the strict contract the
quote-aware fallback had weakened.
- The leading wrapper-less Gemma guard no longer requires the call to open
the response: a visible preamble before call:NAME{...} is the normal
shape, and the quoted foreign literal inside the argument was promoted
again in that shape. An enabled balanced call beginning before the first
foreign signal owns it.
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* Address review: contextual GLM quote openers, disabled Gemma examples stay prose, JSON array answers
- The GLM value-close quote tracker uses the same contextual openers as the
Gemma scanners (single quote after punctuation context, double quote also
at word start), so strict mode accepts a normal apostrophe value again
while still rejecting a truncated value whose only close candidates sit
inside a string literal.
- A disabled wrapper-less Gemma call is prose by design, so a tool literal
quoted inside it no longer promotes: the span is dropped for parsing and
the tail parsed, mirroring the nameless-JSON guard.
- Leading JSON ARRAY answers join the leading-JSON envelope guard, so a
marker quoted inside a structured array response stays data.
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* Align closed-envelope regression test with the document-order contract
The test asserted the pre-round-13 behavior (trailing DeepSeek/Kimi block
wins over a leading closed envelope) while the shipped rule is document
order: the leading closed call owns the turn. Rename the test and assert
the leading call so the suite matches the contract exercised by
test_leading_xml_call_wins_over_trailing_kimi_example.
* Parse a leading Llama-3.2 bare-JSON call before the markerless Gemma scan
The bare-JSON form only ever matches a leading call object, and document
order says that call owns the turn. Running the Gemma wrapper-less scan
first let an enabled call:NAME{...} snippet quoted inside the leading
call's string arguments steal the turn when the JSON was not the whole
content (trailing prose or a second ;-separated call), executing the
quoted tool instead of the real one. Reordering cannot take a leading
Gemma call's turn since that content never starts with an object brace.
* Leading-call ownership: Mistral trigger in Gemma guards, closed bare JSON before markers, depth-aware nested Gemma values
Three parser gaps against the document-order contract:
The wrapperless Gemma leading guards did not count [TOOL_CALLS] as a
foreign signal, so a leading Gemma call quoting a Mistral snippet in its
argument lost the turn to the quoted literal. Both the enabled-call and
disabled-example guards now include the trigger, matching the bare-JSON
guard's local inclusion.
_marker_inside_leading_envelope required the DeepSeek/Kimi marker to sit
inside the first closed bare-JSON or Mistral call. A marker after that
closed call (a trailing example or data in a later ;-chained call's
strings) now also defers to the leading call, the same inside-or-after
rule the closed XML envelope patterns already applied.
The nested Gemma primitive value scan split on every comma, corrupting
arguments like opts:{code:print(1,2),lang:py}. It now applies the same
paren/brace depth, contextual quote openers, and comma-only-before-a-key
mapping rule as the top-level scan.
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* Gemma leading guard: a closed enabled call preceding the signal owns the turn
The wrapperless Gemma guard only claimed the turn when the first foreign
signal sat inside the first enabled balanced call. When that call closed
before the signal (a second call quoting a Mistral or Kimi literal, or a
trailing prose example), the guard forfeited the turn and the foreign
parser promoted the quoted literal, dropping the real Gemma calls. Apply
the same inside-or-after ownership rule as the closed bare-JSON and
Mistral envelopes, gated on an enabled name so the name-agnostic legacy
path is unchanged.
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* Marker guard: only an executable leading bare-JSON call owns the turn
The bare-JSON branch of the leading-envelope marker guard claimed the
turn for any NAMED leading object. A disabled-name object is prose by
design (the bare-JSON parser will not execute it), so deferring the
DeepSeek/Kimi pre-pass to it lost the real later call entirely. Gate the
ownership claim on the enabled set (or the name-agnostic None path). A
marker inside the disabled object's own strings stays data, matching the
tail-exclusion contract; a marker after it now falls through so the
pre-pass parses the real call. The Mistral branch stays ungated since
[TOOL_CALLS] parsing is never name-gated.
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* Gemma scan skips leading JSON answers; GLM heal bounds values at structural tags
Two fixes to the document-order data contracts:
The markerless Gemma scan only exempted whole-content JSON, so a leading
JSON answer followed by prose had an enabled call:NAME{...} snippet
inside its strings promoted to a real executed call and stripped from
the displayed answer. Both the parse and strip scans now start after a
balanced json-valid leading value span, keeping parse and strip
mirrored. Real calls after the answer still parse; mid-prose JSON gets
no exemption.
The GLM heal fallback for a missing closing arg_value tag took the
entire remainder as the value, executing markup-contaminated arguments
like city="NYC</tool_call>" and swallowing trailing prose. The healed
value now stops at the next arg_key or tool_call close and the pair walk
resumes there. EOF-truncated values keep the partial heal, strict mode
still rejects, and closed values holding a literal close tag in quotes
are untouched.
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* Compress docstrings in the multi-format tool parser to their contract essence
* Condense parser guard comments and test narration to contract essentials
* verify_import_hoist: exempt __future__ imports and same-diff relocations
Two false positives fired on this PR's refactor. A from __future__ import
is a compiler directive whose name never appears as a runtime load, so
HOISTED-IMPORT-UNUSED can never see it used, yet the file requires it for
PEP 604 annotations on Python 3.9. TARGET-CHANGED flagged the deliberate
move of the strip-pattern constants into core.inference.tool_call_parser
as a silent re-point even though the old module-level target was removed
and the new one added in the same diff. Both get narrow exemptions; a
re-point to a pre-existing target is still caught, and the self-test
negative controls all pass unchanged.
* Leading bare-JSON calls own the turn; function calls end at the first balanced close
The XML-signal guard for a leading bare-JSON call required the signal
strictly inside the object, so a trailing XML example stole the turn
from the leading call; it now applies the same inside-or-after rule as
the Mistral guard. Function-XML calls also ended at the LAST close tag,
which let prose after a closed call that mentions a literal close tag
get swallowed into the final parameter value; calls now end at the
first close tag that is not inside an open parameter, and the strip
mirrors the same rule so parse and strip agree.
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* Attribute-form calls end at the first balanced close; bare-JSON strip requires the call shape
The attribute form parser still kept the last close tag in the call
window, folding prose after a closed call into the final parameter
value. It now takes the first close not inside an open parameter, the
same rule the equals form and the strip already use.
The leading bare-JSON strip deleted any closed object whose top-level
name matched an enabled tool, including plain JSON answers the parser
correctly rejects as non-calls. The strip (and the drain gate that
delegates to it) now requires the parser's exact call shape, so answers
like {"name":"web_search","result":...} stream and display intact.
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* False-alarm markers keep the answer; the bare-JSON strip consumes the whole chain
The trailing strip arms dropped everything from a bare marker to EOF,
so a normal answer that mentions [TOOL_CALLS] or another marker
literally was truncated (or fully swallowed when it started with the
literal) after the no-call drain fallback. Those arms now require a
call-shaped lookahead or marker-at-EOF before dropping; truncated real
calls still strip.
Chained bare-JSON turns executed both calls but stripped only the first
object, so the second call's raw JSON replayed into the next assistant
history message alongside the structured tool_calls. The strip now
consumes the entire chained run of call-shaped enabled objects while
non-call answers, disabled names, and trailing prose stay intact.
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* DeepSeek and Kimi trailing strip arms require a call-shaped lookahead
Same false-alarm rule as the bare-word markers: a prose answer that
mentions a DeepSeek or Kimi marker literally keeps its tail, while
truncated real envelopes and bare end-of-text fragments still drop.
* Attribute-form containment, parameter-close-decides rule, preamble-tolerant Mistral guard, strict strip shape
Four document-order and containment fixes. A leading attribute-form
call now parses before the shared XML pass, so markup quoted in its
parameter stays data. The open-parameter scan lets the parameter's own
close tag decide, so any number of literal function closes inside one
value stay data, restoring the pre-close-scan behavior for multi-close
arguments. The leading-Mistral guard tolerates a visible preamble, with
the leading-bare-JSON guard running first so a trigger quoted inside a
leading JSON object stays data. The bare-JSON strip requires the
parser's top-level name in every mode, so nested-name JSON answers
survive name-agnostic stripping.
* Keep buffering long wrapper-less Gemma tool names instead of leaking the prefix
The streaming buffer stopped holding a call:NAME prefix at a fixed
32-char cap, so a Gemma wrapper-less call to a tool whose name exceeds
that (OpenAI allows 64 chars, MCP names run longer) streamed its raw
call:longname text as visible content before the end-of-turn parser
executed it. Hold the variable-length prefix while it still matches the
call: shape, bounded like the bare-JSON path and self-terminating into
prose, draining once the opening brace arrives.
* Keep prose that only mentions DeepSeek/Kimi markers in the route display strip
The route-level _TOOL_XML_RE DeepSeek/Kimi arms consumed from an opener up to
the end of text whenever the marker appeared, so an answer that merely refers
to a marker (for example "See <|tool_call_begin|> in the docs") had the rest
of the reply truncated. The parser-level _TOOL_ALL_PATS already gates these
arms with a call-shaped lookahead. Mirror it here so a marker is only stripped
when a real call follows it or it is a bare fragment at end of text.
* Tighten tool-calling parser and backend comments
* Pass trust_remote_code when reloading native tokenizers
The native-template fallback re-fetches a model's native chat template from
its repo when an Unsloth override template drops the tools schema. The
secondary AutoTokenizer.from_pretrained threaded hf_token but not
trust_remote_code, so for a model loaded with trust_remote_code=True whose
tokenizer repo carries custom code the reload raised, was swallowed, and the
request silently kept the tool-dropping prompt for a model that supports tools.
Store the loaded trust_remote_code on each backend's per-model info dict and
source it in render_native_template, so the reload re-uses exactly the consent
granted at load. For a LoRA adapter the reload targets the base model, whose
remote code was gated and loaded under the same stored flag, so re-passing it
executes no unconsented code. Falsy stored flag preserves the prior behaviour.
Adds a regression test that fails without the flag (custom-code reload raises,
returns None) and passes with it (tools-advertising native prompt returned).
* Treat <|python_tag|> as an outer marker envelope
A Llama-3 <|python_tag|> tool call (built-in NAME.call(...) or custom
{json} form) whose argument quotes a complete DeepSeek/Kimi example was
hijacked by the DeepSeek/Kimi marker pre-pass: the embedded example (for
example delete_all) executed instead of the real outer call. python_tag
is Llama-3's tool-call envelope, so a marker quoted inside its arguments
is data, the same as for <tool_call>, <function=...>, bare JSON, Mistral
and wrapper-less Gemma, which the guard already covers.
Add <|python_tag|> to _OUTER_ENVELOPE_OPEN_RE with a call-shaped
lookahead (mirroring the _TOOL_ALL_PATS python_tag arm) so the marker
pre-pass is suppressed when a python_tag call opens before the first
marker, while a bare prose <|python_tag|> mention is left untouched.
* Tighten tool-call parser comments
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: Daniel Han <info@unsloth.ai>
Co-authored-by: danielhanchen <danielhanchen@users.noreply.github.com>
* studio: tool calling for Llama-3, Mistral, Gemma 4 on safetensors + MLX (#5615)
Adds tool calling for Llama-3, Mistral (pre-v11 + v11+ + [ARGS]), and Gemma 4 to the safetensors / transformers and MLX backends. Parser patched against llama.cpp / vLLM / SGLang per-family parsers and normalises to OpenAI shape. 96 targeted unit tests + cross-OS staging CI (ubuntu / macos-14 / windows) green on the multi-format probe.
* studio: tool-call healing parity between safetensors / MLX and GGUF
After the multi-format parser landed in #5615, the safetensors / MLX
agentic loop and the GGUF loop still differed on healing behaviour.
This commit closes the gaps in both directions so the two backends
react the same way to identical model output.
Changes:
1. core/inference/llama_cpp.py -- the GGUF BUFFERING state machine
now wakes on every emission marker the shared parser knows. Was
("<tool_call>", "<function="); is now the five-tuple imported
from core.inference.tool_call_parser (Qwen / Qwen3.5 / Llama-3
<|python_tag|> / Mistral [TOOL_CALLS] / Gemma 4 <|tool_call>).
Stream cleanup is delegated to the same shared strip_tool_markup
so leaked markup from any family is removed from assistant
content.
2. core/inference/llama_cpp.py -- per-tool canonical heal key. When
a tool arguments field is a bare string and JSON parsing fails,
the GGUF path now heals to {"code": raw_args} for python,
{"command": raw_args} for terminal, and {"query": raw_args} for
everything else. Was hard-coded to {"query": raw_args}, which
silently routed every python / terminal emission through
web_search. Mirrors safetensors_agentic._CANONICAL_HEAL_ARG.
3. core/inference/safetensors_agentic.py -- re-prompt on plan-
without-action. When the model emits a short forward-looking
intent ("I'll search for that", "Let me check", "First, I
will...") and no tool call, the loop nudges the model to act
instead of silently returning a plan-only answer. Up to
_MAX_REPROMPTS=3 (matches GGUF). The intent regex, character
cap, and instruction text are byte-identical to the GGUF path.
The buffer-end fall-through is unified so a buffered intent
emission that never exits the BUFFERING state still triggers
the re-prompt.
4. core/inference/safetensors_agentic.py -- extra iteration slots
for re-prompts. The loop now budgets max_tool_iterations +
_MAX_REPROMPTS + 1 total iterations and tracks the tool-call
count separately, so a stalling model can be nudged 3x without
eating the caller's tool-call budget. Mirrors the _extra slot
reservation in the GGUF path.
Tests (14 new safetensors-side units; 5 GGUF parity pins):
TestLoopRePrompt -- intent-trigger, plain-answer,
no-tools, cap-at-three, budget
preserved, buffer-end intent.
TestLoopCanonicalHealKey -- python / terminal / unknown.
TestGGUFSafetensorsHealingParity -- shared markers used, shared
strip used, canonical heal keys
identical, intent regex matches
same phrases, _MAX_REPROMPTS
equal on both backends.
All 110 targeted tests pass locally; the broader tool / inference /
model-config / sandbox / anthropic / mlx suites stay green.
Why this matters
Without this parity, Llama-3.2 / Mistral / Gemma 4 emissions on Mac
(MLX) and Linux-safetensors stop the agentic loop as soon as the
model says "Let me...", because the GGUF re-prompt logic never
existed on these backends. The two-marker GGUF BUFFERING tuple also
let non-Qwen tool emissions stream out as plain prose when
llama-server's structured channel did not pick them up. Both paths
now drain the same way, heal the same way, and re-prompt the same
way -- so a tool call that works on GGUF works identically on
safetensors / MLX.
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* studio: fix tool-call parser bugs from gemini review on #5620
Three high-priority gemini findings on the tool-call parsing additions:
1. unicode_escape on UTF-8 bytes corrupts non-ASCII literals
(e.g. ✨ becomes â\x9c¨). Replace with json.loads on a quoted
string -- preserves emoji / CJK / RTL while still handling
\n \t \uXXXX escapes.
2. Llama-3 sentinel stripping is order-dependent. A leading
`<|eot_id|><|begin_of_text|>` left `<|begin_of_text|>` behind
because the loop had already passed that sentinel. Loop until
no sentinel matches at the start.
3. Mistral v11+ `[TOOL_CALLS] name { json }` regex uses non-greedy
`\{.*?\}` which truncates at the first `}` of a nested JSON
argument, leaking the tail (e.g. `}}`) into user-visible
streamed text. Same problem for the v0.3 array pattern with
nested brackets. Strip those with balanced brace/bracket
scanning via a new `_strip_mistral_closed_calls` helper called
from `strip_tool_markup`.
Also fix the inference routes' parallel `_TOOL_XML_RE`:
- Same nested-JSON truncation in the Mistral patterns; route the
strip through the parser's balanced-scan helper via a thin
`_strip_tool_xml` wrapper that all existing callers now use.
- Llama-3 `<|python_tag|>[^\n<]*` stopped at any `<`, leaking the
tail of any tool call whose argument contained a literal `<`
(queries, code snippets). Relax to `[^\n]*` which keeps the
strip confined to the actual end-of-line.
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* studio/routes: make python_tag strip multi-line aware
Earlier revisions of _TOOL_XML_RE in studio.backend.routes.inference
oscillated between two bug shapes:
5615 r"<\|python_tag\|>[^\n<]*" -- stopped at any literal "<"
so code='if x < 10: pass'
leaked '< 10: pass)' to the
user.
5620.1 r"<\|python_tag\|>[^\n]*" -- single-line only; the second
line of
python.call(code="a\nb")
leaked.
The full parser (_parse_llama3_python_tag) already handles both via
balanced-brace scanning, so the parsing path was fine; the LEAK was
in the streaming strip path that runs on every cumulative emission
while content is still arriving.
Switch to r"<\|python_tag\|>(?:[^<]|<(?!\|))*" so the strip consumes:
* any character that is not a "<" (newlines, JSON, code, ...),
* a "<" only when it is NOT followed by "|" (i.e. NOT a Llama-3
sentinel start like <|eot_id|>, <|eom_id|>, <|begin_of_text|>).
This means:
* code='if x < 10' stays inside the strip (5615 fix preserved),
* multi-line code stays inside the strip (5620 round 2),
* the strip terminates at the next Llama-3 sentinel so trailing
assistant content survives.
Tests: TestRoutesPythonTagStrip (8 cases)
pytest test_safetensors_tool_loop.py test_safetensors_capability_advertise.py
-> 118 passed in 1.81s (was 110).
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* studio: tighten verbose comments in tool-call parser sections
Comments were narrating what the code already says. Cut historical
"earlier revisions used X, then Y" narratives down to one-line WHY
notes where the footgun still matters (canonical heal-key parity,
balanced-brace vs non-greedy regex, ``(?:[^<]|<(?!\|))*`` over
``[^\n<]*``/``[^\n]*``). Drop section-header banners.
No behaviour change. Re-ran:
pytest studio/backend/tests/test_safetensors_tool_loop.py \
studio/backend/tests/test_safetensors_capability_advertise.py -q
-> 118 passed.
Regression replay (parser + _coerce_arguments on the 5 #5615 inputs)
-> 21/21.
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* studio: parser robustness fixes for PR #5620
Three surgical extensions to the multi-format tool-call parser, each
covering a real fine-tune / template emission shape that the current
parser silently drops. No path narrows; all changes widen what is
accepted.
1. `_parse_tool_call_json` now accepts both `arguments` and
`parameters` keys. A Hermes / Qwen `<tool_call>{json}</tool_call>`
wrapper around a Llama-3.2 fine-tune that emits the `parameters`
key was extracting the tool name and silently discarding the
args, producing a working-shaped call with an empty payload. The
bare-JSON and python_tag paths already accepted both keys; this
path now matches them.
2. `_TC_FUNC_START_RE`, `_TC_PARAM_START_RE`, and `_TC_PARAM_CLOSE_RE`
now also match the attribute form
`<function name="..."><param name="...">v</param></function>` used
by MiniCPM-5 and MiniMax-M2. Names land in either capture group,
and `</param>` is accepted as a short close.
3. `_parse_llama3_bare_json` sentinel-strip now consumes the role
label inserted between `<|start_header_id|>` and
`<|end_header_id|>` by Meta's official Llama-3.x chat template.
Without this, every assistant turn re-fed through the template
prefix `<|start_header_id|>assistant<|end_header_id|>\n\n{json}`
parsed to zero calls, so any history-with-tool-call round-trip
in production silently dropped.
Tests in `studio/backend/tests/test_safetensors_tool_loop.py`:
* `TestParserRobustness::test_tool_call_json_accepts_parameters_key`
* `TestParserRobustness::test_function_xml_attribute_form`
* `TestParserRobustness::test_function_xml_attribute_form_multi_param`
* `TestParserRobustness::test_function_xml_legacy_equals_form_still_works`
(regression guard for the existing `<function=name>` syntax)
* `TestParserRobustness::test_llama3_chat_template_round_trip`
* `TestParserRobustness::test_llama3_round_trip_all_roles`
* `TestParserRobustness::test_llama3_round_trip_with_eot_prefix`
`pytest studio/backend/tests/test_safetensors_tool_loop.py
studio/backend/tests/test_safetensors_capability_advertise.py -q`
goes from 118 to 125 passed.
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* studio: terminate function-XML body at </function>, not just </tool_call>
`_parse_function_xml` was looking for `</tool_call>` (the Hermes
wrapper) as the body terminator. When a model emits a standalone
`<function=NAME><parameter=K>v</parameter></function>` followed by
explanatory prose (which models routinely do), no `</tool_call>` is
present, so the body extended to end-of-string and the trailing
prose leaked into the LAST parameter value.
Pre-existing on main (the legacy `<function=NAME>` form had this
bug too). Same affects PR #5620's new attribute-form
`<function name="NAME"><param name="K">v</param></function>`
emission used by MiniCPM-5 / MiniMax-M2.
Fix: `_TC_END_TAG_RE` now matches either `</tool_call>` OR
`</function>`. The existing `_TC_FUNC_CLOSE_RE` / `_TC_PARAM_CLOSE_RE`
strips are unchanged. Multi-call inputs still bound each function
at the next `<function=` start, so no over-eager consumption.
New tests:
* `test_function_xml_followed_by_prose` (legacy form + prose)
* `test_function_attribute_xml_followed_by_prose` (attribute form + prose)
Existing `test_code_with_embedded_xml` still passes (a parameter
value containing literal `<a></a>` is preserved because the
embedded close tag is `</a>`, not `</function>`).
`pytest studio/backend/tests/test_safetensors_tool_loop.py
studio/backend/tests/test_safetensors_capability_advertise.py -q`
goes from 125 to 127 passed.
* Studio: tighten Llama-3.2 bare-JSON guard
A fuzz pass on PR #5811 turned up that ``_parse_llama3_bare_json``
accepted ``parameters`` as a string, contradicting the docstring's
"parameters or arguments is a dict" guard. Prose JSON like
``{"name":"foo","parameters":"a sentence"}`` would wrongly fire the
parser, which the agentic loop would then heal into a real
``foo(query="a sentence")`` call.
Same code lives on this branch, so the same fix applies here.
Tightened guard:
- ``parameters`` must be a dict (Llama-3 spec).
- ``arguments`` may be a dict, or a JSON-encoded string that
decodes to a dict (OpenAI shape, e.g.
``"arguments":"{\"q\":\"x\"}"``). Plain non-JSON strings or
JSON-strings of lists / scalars / null no longer pass.
Mirrors the fix landed in PR #5811 commit 615b8608. Adds the same
4 regression tests under TestParserMultiFormat.
Existing test suite stays green: 127 -> 131 passing.
* studio: fix safetensors tool-call parser gaps vs llama.cpp (Mistral CALL_ID / THINK, attribute-form signal)
Three GGUF-parity fixes to the safetensors tool-call parser, each matching
llama.cpp's reference behaviour:
- Mistral Small 3.2 emits [TOOL_CALLS]name[CALL_ID]<id>[ARGS]{json}. The
parser stopped after the name on seeing [CALL_ID] (neither [ARGS] nor {),
dropping the call. Skip an optional [CALL_ID]<id> segment in both the
parse and strip paths. llama.cpp parses this (test-chat.cpp:4785).
- Magistral wraps reasoning in [THINK]...[/THINK]. A [TOOL_CALLS] inside the
reasoning was parsed as a real call, producing a phantom call. Strip a
leading [THINK] block before scanning so only the post-reasoning call
counts (test-chat.cpp:2285); a literal [THINK] inside a later argument is
left intact.
- The standalone MiniCPM-5 / MiniMax-M2 <function name="..."> attribute form
parsed correctly but was absent from TOOL_XML_SIGNALS and the markup strip
patterns, so the streaming safety-net parse was gated off (dropping the
call) and markup leaked into displayed text. Add the signal and broaden
the strip regexes.
Adds regression tests for all three.
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* studio: fire safetensors tool calls for the bare-JSON (Llama-3.2) form
The agentic loop's streaming safety-net parse was gated on
has_tool_signal(), which is False for the Llama-3.1 / 3.2 bare-JSON tool
form {"name":..,"parameters":..} (no XML marker). Real tool calls were
therefore dropped: the loop logged "model planned without calling tools",
re-prompted three times, then gave up with zero tool calls, while GGUF's
llama-server parses the same emission natively.
Run parse_tool_calls_from_text() unconditionally in the safety net. The
parser is strict (only fires on a valid tool-call shape) so plain answers
are unaffected. Reproduced on a real unsloth/Llama-3.1-8B-Instruct run:
the model emits {"name":"web_search","parameters":{...}} which now
executes the tool instead of being re-prompted into a no-op.
Adds a loop regression test for the bare-JSON form.
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* Studio: complete strict-mode contract and fix parser import paths
Address review findings on the multi-format tool-call parser:
- Honor allow_incomplete=False in the remaining sub-parsers. The Llama-3
<|python_tag|>NAME.call(...) parser, the pre-v11 Mistral [TOOL_CALLS] array
parser, and the Gemma 4 <|tool_call> parser ignored strict mode, so a
truncated call (missing closing paren, ], or <tool_call|>) was still healed
and executed with Auto-Heal disabled. Thread strictness through and reject
the unclosed forms, matching the JSON and function-XML paths.
- Drop the duplicate tool_call_parser import block in llama_cpp.py and the
redundant un-aliased TOOL_XML_SIGNALS; only the _SHARED_TOOL_XML_SIGNALS
alias is used as a value.
- Import _strip_mistral_closed_calls from core.inference.tool_call_parser in
routes/inference.py instead of studio.backend.core... The self-contained
run.py launch mode only puts studio/backend on sys.path, so the absolute
package path raised ModuleNotFoundError on the server-tool strip path.
Add strict-mode regression tests for the truncated Llama-3 dot-call and the
unclosed Mistral array.
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* Studio: preserve XML param indentation and alias Mistral array parameters
Two parser-correctness fixes found by auditing against the model chat templates
and the SGLang / vLLM reference parsers:
- Qwen3.5 XML parameter values lost their leading indentation. The chat template
emits <parameter=k>\nVALUE\n</parameter>, but the parameter-start regex ate the
wrapping newline AND the value's first-line indentation with a trailing \s*,
then str.strip() removed the rest. Narrow the trailing class to horizontal
whitespace only and trim exactly one wrapping newline (via _trim_param_value),
preserving indentation in code/diff arguments. Matches SGLang's qwen3_coder
detector. Applies to both _parse_function_xml (tool_call_parser.py) and the XML
path in tool_healing.py.
- Mistral pre-v11 array objects keyed on parameters dropped their payload.
_consume_mistral_call read only the arguments key; alias parameters the same way
the JSON/XML paths and SGLang's base detector do.
Add regression tests for preserved multi-line indentation and the array
parameters alias.
* Studio: tighten tool-call parser comments
Make the comments in the multi-format tool-call parser and its callers succinct:
compress verbose docstrings/blocks to one or two lines, drop ones that restate the
code, and trim the tiny balanced-scanner helpers. Correctness rationale and
upstream provenance (SGLang/llama.cpp parity, the strict-mode / Auto-Heal
contract, whitespace-preservation, and the Unicode / full-width-pipe notes) are
kept in compact form.
Comment-only: no code or behavior change (verified with comment_tools.py check
--strip-docstrings; parser suite green).
* Studio: make Llama-3 .call and Mistral-array healing parsing linear
Two more O(n^2) ReDoS paths in the multi-format parser, both reachable from
the agentic loop on a long truncated body with no length cap:
- _LLAMA3_KV_RE.finditer over a .call(...) body retried at every offset of a
long word run / unterminated quote (40K -> 14s). Replace with a hand-scan
that reuses the same key/number/literal sub-regexes via anchored match and
walks the string body by hand, so an unterminated quote is O(n). Verified
byte-identical to the old regex over 200K fuzzed inputs.
- _parse_mistral_array healing ran _balanced_brace_end from every { in the
body (20K -> 17s). Walk top-level objects, advancing past each balanced
{...}; this also drops the phantom call the old scan emitted from a nested
argument object.
Add adversarial-length linearity regressions plus positive .call kwargs and
unclosed-array recovery coverage.
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* Studio: honor strict mode in safety-net, keep empty Gemma args, strip attribute-form function XML
- safetensors safety-net parser now forwards allow_incomplete=auto_heal_tool_calls,
matching the draining path, so a late incomplete tool call is not healed and
executed when Auto-Heal is off.
- Gemma empty bare value ({k:}) now serialises as "" instead of invalid {"k":},
which previously dropped the whole call.
- Route _TOOL_XML_RE also strips the <function name="..."> attribute form
(MiniCPM-5 / MiniMax-M2) so it no longer leaks to the UI.
* Studio: fix attribute-form function-XML literal close tag and zero-arg strict call
Addresses Codex review of the <function name="..."> attribute form in
_parse_function_xml (MiniCPM-5 / MiniMax-M2):
- End the call body at the LAST </function> / </tool_call> within the call's
window, so a literal close tag inside a code/search argument (e.g.
print("</function>")) is preserved instead of truncating the call.
- Accept a closed call with no parameters as a valid zero-argument call in strict
mode (the function close is already required), instead of rejecting it as a
truncated call.
- Tests for both, mirroring the legacy <function=...> coverage.
* Studio: fix tool-call parser/loop review findings on the multi-format path
Address the live code-review findings on the safetensors/MLX + GGUF tool path:
- routes: include the attribute form <function name="..."> in the safetensors
capability whitelist so MiniCPM-5 / MiniMax-M2 templates keep the tool pill
(parser already handles the form; the post-filter wrongly suppressed it).
- safetensors loop: build the plan-without-action re-prompt from the active
tools instead of a hardcoded web_search/python string, and gate it on
auto_heal_tool_calls, matching the GGUF loop.
- safetensors loop: hold a leading bare-JSON object ({"name":..,"parameters":..})
during BUFFERING until it closes, then drain it as a tool call instead of
streaming the raw JSON to clients. The DRAINING/STREAMING resolvers still
recover a plain JSON answer, so this can never drop content.
- parser: anchor the Llama-3 <|python_tag|>NAME.call(...) scan to the tag and
chain ; -separated calls, so all semicolon-separated built-ins parse and a
literal <|python_tag|>x.call(...) inside a JSON string argument no longer
fires the wrong tool.
- parser: consume the optional trailing </s> after a named Mistral
[TOOL_CALLS]name{json} call, mirroring the array shape.
- GGUF streaming strip: use the shared parser patterns (which know
[TOOL_CALLS] and <|python_tag|>) so a textual tool call entering DRAINING is
stripped instead of leaking the marker to streaming clients.
- routes: hoist the _strip_mistral_closed_calls import to module level.
Adds regression tests covering each fix; existing parser suite stays green.
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* Studio: harden multi-format tool-call detection from review findings
Apply five targeted fixes from the review pass over the multi-format tool
path:
- routes: route display strip delegates to _strip_tool_xml so Mistral
[TOOL_CALLS] blocks with nested JSON are removed from streamed display
text, not just the XML forms.
- tool_call_parser: skip function/parameter starts that fall inside an
already-open parameter block (_inside_open_parameter) so nested example
payloads are not mis-parsed as new calls; extract
strip_llama3_leading_sentinels so the bare-JSON guard is shared.
- safetensors_agentic: probe bare JSON through strip_llama3_leading_sentinels
before the balanced-brace check so a leaked header sentinel does not defeat
the guard.
- tool_healing: allow dotted tool names in the Gemma wrapped start pattern.
- llama_cpp (GGUF): buffer wrapper-less Llama-3.2 {"name":..} calls that carry
no XML signal, drain a complete object silently and hold an incomplete one,
and run the end-of-stream safety net unconditionally so markerless calls are
detected and never leak the raw JSON (including truncated fragments).
Adds regression tests for the GGUF bare-JSON streaming path and the Mistral
display strip.
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* Studio: stop bare-JSON tool calls leaking at EOF, oversized, and into history
The second review pass flagged that the Llama-3.2 bare-JSON tool-call handling
still leaked raw JSON in several spots; ``strip_tool_markup`` only knows
XML/bracket markup, so the bare-JSON form survived it. Fix them symmetrically
across the safetensors and GGUF loops:
- Safetensors stream-end resolver now routes a held bare-JSON fragment to
DRAINING (mirroring GGUF) so a truncated ``{"name":..`` cut off by the end of
the stream is dropped instead of flushed as assistant content. The 7/10
reviewer finding.
- Both loops now drain (suppress) an oversized still-open bare-JSON call once it
passes ``_MAX_BARE_JSON_BUFFER`` instead of streaming the raw prefix, gated on
a ``"name"`` key so a giant plain JSON answer still streams; a complete
oversized call still executes via the safety net.
- Add a shared ``strip_leading_bare_json_call`` helper and apply it to the
content kept for the assistant turn in both loops, so an executed bare-JSON
call is not replayed as visible text or fed back as next-turn history.
Plain JSON answers without a ``"name"`` key are untouched throughout. Adds
regression tests for the EOF, oversized, and next-turn cases on both backends
plus unit tests for the helper.
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* Studio: bound the Llama-3 python_tag strip on real control sentinels
The route display strip's <|python_tag|> arm ran to the next <| of any kind.
A tool-call argument carrying a literal <|...|> token (for example <|cite|>
inside a string value) truncated the strip early and leaked the call tail into
the visible response. Narrow the stop condition to the genuine Llama control
sentinels (eot_id, eom_id, python_tag, start/end_header_id, begin_of_text,
finetune_right_pad_id) so embedded markup and JSON are consumed while real
header/turn boundaries still bound the strip.
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* Studio: gate markerless bare JSON on enabled tools and close parser/strip asymmetries
The Llama-3.2 custom_tools bare-JSON form has no marker, so any JSON object with a
name key was read as a tool call. An ordinary JSON answer like
{"name":"Alice","parameters":{"age":30}} was misclassified as a call to a
disabled tool and dropped from the visible response. Gate the markerless form on
the enabled tool names (threaded through parse_tool_calls_from_text and
strip_leading_bare_json_call, supplied by both streaming loops): an object whose
name is not an enabled tool is ordinary content. The marker-based forms keep
their name-agnostic behaviour (an explicit signal is a real call attempt), and
unrestricted mode stays ungated.
Also fix two parser/strip asymmetries the parser already tolerated:
- A literal </function> inside a parameter value (print("</function>")) truncated
both the core and route strips at the first close, leaking the tail. Extend the
strip to the call's real close (last </function> before the next opener),
mirroring the parser, without merging separate calls.
- The single-object Mistral [TOOL_CALLS]{...} shape parsed but _strip_mistral_closed_calls
left it, leaking the raw object into display. Strip the balanced object while
keeping trailing prose, matching the array and name shapes.
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* Studio tools: gate GGUF bare-JSON suppression on enabled tools and fix python-tag exponent parsing
Pass-4 review follow-ups on the GGUF tool loop and Llama-3 parser:
- The GGUF bare-JSON suppression sites still keyed off a raw "name" substring,
so an ordinary JSON answer whose name is not an enabled tool was dropped when
it was truncated, oversized, or reached the no-tool DRAINING fallback (the
parser, helper, and safetensors paths were already gated). All three sites now
use the shared enabled-name gate, and a held bare-JSON buffer that turns out not
to be an enabled call is shown as the answer instead of dropped at stream end.
- The Llama-3 python-tag numeric kwarg regex matched only the mantissa, so
scientific notation was truncated to its leading digits (1e-3 parsed as 1) and a
tool executed with the wrong value. The regex now accepts exponent and decimal
forms, and the int/float classification keys off the exponent too.
Adds regression tests for the truncated / oversized disabled-name JSON cases (and
a counterpart that a truncated enabled call still does not leak) plus the
scientific-notation kwargs.
* Studio tools: gate safetensors bare-JSON drain, fix nested-name gate and function-XML strip
Pass-4 review follow-ups on the shared parser / safetensors loop:
- The safetensors oversized and end-of-stream bare-JSON drain branches keyed off
a raw "name" substring, so a large or truncated ordinary JSON answer whose name
is not an enabled tool was drained instead of streamed. Both now use the shared
enabled-tool-name gate, matching the GGUF path.
- strip_leading_bare_json_call matched the first "name" anywhere, so a plain JSON
answer with a nested name equal to an enabled tool ({"result":{"name":"web_search"}})
was wrongly suppressed. It now extracts the TOP-LEVEL name only, walking past
nested objects/arrays and keeping the text when a top-level value is truncated.
- The function-XML display strip used a regex negative-lookahead that stopped at a
literal <function=...> opener inside a parameter value and then dropped the rest
of the answer to EOF. A scan-based strip mirrors the parser (ignores openers
inside an open <parameter> via _inside_open_parameter) and closes each call at its
real </function>, so trailing assistant text after such a call survives.
Adds regression tests for each.
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* Tool parsing: 3.9 import safety, disabled-Auto-Heal contract, capability gate
Round-2 review follow-ups on the multi-format tool-call parser:
- tool_call_parser: add `from __future__ import annotations`. The module
is dependency-light by design (external llama-server wrappers import it
standalone) and the package targets python >=3.9, where its PEP 604
`int | None` return annotations would raise TypeError on import.
- safetensors + GGUF drain fallback: gate the leading bare-JSON strip on
auto_heal_tool_calls. With Auto-Heal off, a truncated enabled-name
fragment that did not parse now stays visible, matching the XML strip
in the same branch and the disabled-Auto-Heal contract. With Auto-Heal
on it is still suppressed.
- safetensors capability gate: match the bare-JSON `{"name":` template
marker with a whitespace/escape-tolerant regex so a pretty-printed
`{ "name" :` or JSON-escaped `{\"name\":` template is not mis-classified
as tool-less. The parser already accepts that whitespace via
raw_decode, so the gate must too.
Regression tests added for each case.
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* Tool parsing: symmetric "function" bare-JSON alias and route strip parity
Round-3 review follow-ups, all parser/strip symmetry fixes.
- Bare-JSON "function" alias: the markerless parser accepts a call name via
obj.get("name") or obj.get("function"), but the strip/gates only knew "name",
so a {"function":<enabled tool>} call executed while its raw JSON leaked. Teach
_top_level_bare_json_name the alias (with "name" precedence and the same nested
and truncated-name guards), and widen the guards in strip_leading_bare_json_call,
the safetensors and GGUF _looks_like_enabled_bare_json gates, and the route
capability marker regex.
- Route display/history cleanup: strip a tail-only </param> alias close (the
parser accepts <param name="...">...</param>), and run the parser's guarded
function-XML scan (_inside_open_parameter) before _TOOL_XML_RE so a literal
nested <function=...></function> inside an argument value does not truncate the
strip and leak the tail.
Regression tests added for each.
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* Studio tools: honor tool budget in GGUF loop and guard function-XML streaming strip
Round 4 review fixes. Both are asymmetric-fix bugs where the final/steady path got a
guard the analogous streaming/loop path did not.
- GGUF tool-call budget: the safetensors loop counts real tool-call turns against
max_tool_iterations (re-prompt stalls excepted), but the GGUF loop only bounded the
turn count by the enlarged range (max_tool_iterations + _MAX_REPROMPTS). Since this
PR raised _MAX_REPROMPTS from 1 to 3, a model that keeps making valid tool calls
could run up to three extra tool rounds (with max_tool_iterations=1, four rounds
instead of one). Add a _tool_iters_done counter that increments only when a tool
actually executed in the turn, and stop once the caller's budget is spent so the
post-loop final-answer nudge fires. A duplicate/disabled no-op turn is a correction
turn (like a plan-without-action re-prompt) and does not consume budget, preserving
the existing "already completed" re-prompt behavior.
- Streaming display strip: the final strip runs the guarded _strip_function_xml_calls
scanner (a literal <function=...> inside a parameter value is data, not a nested
call), but the GGUF and safetensors streaming strips still used only the open-ended
regex arms. When a tool-call argument contained literal function markup, the regex
tail ate everything to end-of-text and dropped the real trailing prose after the
call's true </function>. Run the guarded scanner (and the balanced Mistral strip)
before the regex arms in both streaming paths so streaming and final display agree.
Adds regression tests: GGUF valid tool calls respect max_tool_iterations, and the
streaming strip keeps trailing prose after a function-XML call with a literal marker.
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* Studio tools: safetensors tool budget counts only executed turns (GGUF parity)
Follow-up to the GGUF budget fix. The safetensors loop charged max_tool_iterations
per non-re-prompt iteration (iteration + 1 - reprompt_count), so a duplicate/disabled
no-op turn spent a budget slot even though no tool ran. With a small cap this dropped
real work: for max_tool_iterations=2, a model that made a valid call, repeated it (an
internal no-op correction turn), then made a distinct valid call executed only the
first -- the third turn was sent with no tools and the distinct call was ignored.
Track whether a turn actually executed a tool (set on record_result) and count only
those turns against the cap, matching the GGUF loop. A duplicate/disabled no-op is a
correction turn -- like a plan-without-action re-prompt -- and no longer consumes
budget, so the model still gets its "already completed" nudge and another tool-enabled
turn. Adds a regression test for the small-cap duplicate-then-distinct-call flow.
* Studio: render the reasoning block for safetensors and MLX like GGUF
enable_thinking chat templates (Qwen3/Qwen3.5/GLM) prefill an unclosed <think>
into the generation prompt, so the model emits only the closing </think> then
the answer. The safetensors/MLX chat stream emitted that as plain content, so
the reasoning showed inline with no collapsible thinking block, while GGUF
(which surfaces reasoning via reasoning_content) rendered one. This brings
safetensors and MLX to parity.
- _ResponsesReasoningExtractor gains a reasoning_prefilled mode that starts
inside the reasoning block and splits on the first </think>; default False
keeps GGUF and every existing caller byte-identical. It suppresses a stray
re-emitted <think> and holds partial markers back across chunk boundaries.
- _sf_reasoning_prefill_mode gates the mode on reasoning being enabled for the
request, an enable_thinking or enable_thinking_effort style, and the template
actually using the standard <think>/</think> markers. Models with a bespoke
reasoning channel (e.g. gemma's <|think|>/<|channel>) are excluded so their
answer is never swallowed; gpt-oss (Harmony) and thinking-off requests are
excluded too.
- sf_tool_stream and stream_chunks (the latter also serves MLX) feed text
through the extractor, emitting reasoning_content then content deltas, with a
per-turn reset in the tool loop and a flush before each tool_start; only the
visible delta reaches the monitor reply. The two non-streaming drains split
reasoning_content the same way.
- Tests: extractor prefilled mode (streaming and edge cases), the gate matrix
including the gemma-style exclusion, and a route-replay of the tool-loop
reasoning stream.
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* studio: don't force a tool re-prompt on a negated intent (safetensors parity)
The safetensors _INTENT_SIGNAL claimed to mirror GGUF but was missing the
negative lookahead, so a refusal like "I will not search the web for that"
matched the "i will" intent and triggered the plan-without-action re-prompt
(STOP... you MUST call a tool), overriding a valid no-tool answer. GGUF already
excludes not/never. Add the same (?!\s+(?:not|never)\b) lookahead so both
backends agree. Extends the intent parity test with negated refusals.
* Studio: trim redundant comments (comment-only, AST-verified)
* Studio: prevent Gemma tool-parser DoS on stray delimiters
_gemma_parse_value returned the input index unchanged when text[i] was a
stray delimiter (,}]), so the list and mapping caller loops that advance
on the returned index spun forever at 100% CPU on malformed input such as
[},]. Advance past the delimiter so parsing always terminates.
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* Studio: strip Magistral [THINK] reasoning from final display/history
strip_tool_markup removed [TOOL_CALLS] and <function> markup but left a
leading Magistral [THINK]...[/THINK] block intact, so its bracket-form
reasoning (not the <think> the reasoning channel renders) leaked into the
safetensors display and conversation history while GGUF/llama.cpp routes
it natively. Drop the leading reasoning block at end-of-turn (final=True)
via the existing _strip_mistral_reasoning helper; streaming is untouched.
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* Honor reasoning_effort none in safetensors prefill; strip Magistral reasoning while streaming
Two safetensors/MLX reasoning fixes surfaced in review:
_sf_reasoning_prefill_mode only checked enable_thinking, so an
enable_thinking_effort (GLM-5.2) request that disables thinking via
reasoning_effort=none (without enable_thinking=False) still began in
prefilled-<think> mode. A plain answer with no </think> was then swallowed
whole into reasoning_content and the visible response came back empty. Thread
reasoning_effort into the predicate and treat none as disabled, mirroring
_request_reasoning_kwargs.
strip_tool_markup_streaming stripped tool markup but not the leading Magistral
[THINK]...[/THINK] bracket block, so the raw chain-of-thought leaked into the
streamed safetensors content instead of the reasoning drawer (GGUF routes it
natively). Apply _strip_mistral_reasoning first, matching the final strip; an
unclosed [THINK] is held from the marker on so nothing flickers.
* Mistral outer call wins over XML literals; align healer signals with its parser
Two follow-ups on the shared-parser ordering after the healing-passthrough
merge:
- A well-formed [TOOL_CALLS] call whose JSON arguments quote tool XML parsed
the literal instead of the outer call (executing the wrong tool). When the
first XML signal sits inside a leading balanced Mistral body it is argument
data, so the Mistral parser now runs first; an XML signal before the trigger
keeps the normal order, so a [TOOL_CALLS] literal inside an XML call's
arguments still stays data.
- passthrough_healing buffered streams on the parser module's broadened signal
list (now including <|python_tag|> and [TOOL_CALLS]) but promotes with
core.tool_healing, which does not parse those forms: a streamed Mistral or
Llama text call was held until finalization and flushed as prose. The healer
keeps its own signal list limited to the formats it can promote, restoring
immediate streaming for the rest.
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* Address review: leading envelopes win over rehearsed literals
- New _first_foreign_tool_signal shared by the leading-envelope guards adds
<|python_tag|> to the protected signal set: the spelled-out literal inside a
Mistral call's arguments (a query about Llama built-in tool syntax) executed
the inner literal instead of the outer call.
- New _xml_signal_inside_leading_bare_json guard, sibling of the Mistral one:
a leading bare-JSON call whose string argument quotes tool XML (a code value
citing <function=...>) had the literal promoted by the shared XML pass
before the bare-JSON parser ran.
- Magistral [THINK]...[/THINK] is dropped once at parse entry instead of only
inside the Mistral parser, so a call rehearsed in the think block in a
foreign format can no longer be promoted while the real call after the
block is lost. Parse now agrees with the display strip.
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* Address review: a disabled leading bare-JSON object keeps its literals as data
When the leading bare-JSON object is ordinary content (name not an enabled
tool), the guard proved the first tool signal sits inside it, so falling
through to the XML/python_tag passes promoted quoted string data as a real
call. Drop the object and parse only the tail: a real call after the object
still parses, nothing inside it can be promoted.
* Address review: Mistral literals inside leading JSON, whitespace-tolerant wrapped Gemma opener
- The leading bare-JSON guard now treats the [TOOL_CALLS] trigger as a
foreign signal: the Mistral parser runs before the bare-JSON one, so a
literal quoted inside the leading object's strings was promoted over the
outer call (or over ordinary JSON content).
- tool_healing's wrapped Gemma opener tolerates whitespace around call and
the colon: sampling drift emits call: name{ and call : name{, and
rejecting those lost the call entirely because no fallback re-parses the
wrapped form. Strict mode still requires the closing tag.
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* Address review: accept dotted Gemma argument keys in the key-quoting scanner
The scanner quoted keys of [alnum_-] only, so a dotted key (user.name:...)
was left unquoted, json.loads failed, and the whole wrapped call was lost
(parse empty, strip wipes the markup). Dots now match the parser's own
key/name charset.
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* Address review: leading Mistral call owns the turn, dotted keys after bare values
- A LEADING parseable [TOOL_CALLS] call now runs the Mistral parser first
unconditionally: literal XML in trailing prose after the call was promoted
by the earlier shared XML pass, executing the quoted example instead of
the real leading call. XML leading keeps the normal order.
- _GEMMA_NEXT_KEY_RE accepts dots so a dotted key after a bare value
(query:foo,user.name:bob) ends the value at the comma instead of being
swallowed into it, matching the round-earlier key-quoting charset.
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* Address review: markup quoted inside a nameless leading JSON answer stays data
The leading bare-JSON guard required a top-level name, so a structured JSON
answer quoting tool markup in its strings (a response_format turn
documenting a tool's syntax) had the literal promoted by the later passes.
A nameless leading object that parses as real JSON now routes through the
same decline-then-parse-the-tail path; non-JSON braced prose keeps the old
behaviour, and a real call after the answer still parses.
* Compress docstrings in the multi-format tool parser to their contract essence
* verify_import_hoist: exempt __future__ imports and same-diff relocations
Two false positives fired on this PR's refactor. A from __future__ import
is a compiler directive whose name never appears as a runtime load, so
HOISTED-IMPORT-UNUSED can never see it used, yet the file requires it for
PEP 604 annotations on Python 3.9. TARGET-CHANGED flagged the deliberate
move of the strip-pattern constants into core.inference.tool_call_parser
as a silent re-point even though the old module-level target was removed
and the new one added in the same diff. Both get narrow exemptions; a
re-point to a pre-existing target is still caught, and the self-test
negative controls all pass unchanged.
* Leading bare-JSON calls own the turn; function calls end at the first balanced close
The XML-signal guard for a leading bare-JSON call required the signal
strictly inside the object, so a trailing XML example stole the turn
from the leading call; it now applies the same inside-or-after rule as
the Mistral guard. Function-XML calls also ended at the LAST close tag,
which let prose after a closed call that mentions a literal close tag
get swallowed into the final parameter value; calls now end at the
first close tag that is not inside an open parameter, and the strip
mirrors the same rule so parse and strip agree.
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* Attribute-form calls end at the first balanced close; bare-JSON strip requires the call shape
The attribute form parser still kept the last close tag in the call
window, folding prose after a closed call into the final parameter
value. It now takes the first close not inside an open parameter, the
same rule the equals form and the strip already use.
The leading bare-JSON strip deleted any closed object whose top-level
name matched an enabled tool, including plain JSON answers the parser
correctly rejects as non-calls. The strip (and the drain gate that
delegates to it) now requires the parser's exact call shape, so answers
like {"name":"web_search","result":...} stream and display intact.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* False-alarm markers keep the answer; the bare-JSON strip consumes the whole chain
The trailing strip arms dropped everything from a bare marker to EOF,
so a normal answer that mentions [TOOL_CALLS] or another marker
literally was truncated (or fully swallowed when it started with the
literal) after the no-call drain fallback. Those arms now require a
call-shaped lookahead or marker-at-EOF before dropping; truncated real
calls still strip.
Chained bare-JSON turns executed both calls but stripped only the first
object, so the second call's raw JSON replayed into the next assistant
history message alongside the structured tool_calls. The strip now
consumes the entire chained run of call-shaped enabled objects while
non-call answers, disabled names, and trailing prose stay intact.
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* Attribute-form containment, parameter-close-decides rule, preamble-tolerant Mistral guard, strict strip shape
Four document-order and containment fixes. A leading attribute-form
call now parses before the shared XML pass, so markup quoted in its
parameter stays data. The open-parameter scan lets the parameter's own
close tag decide, so any number of literal function closes inside one
value stay data, restoring the pre-close-scan behavior for multi-close
arguments. The leading-Mistral guard tolerates a visible preamble, with
the leading-bare-JSON guard running first so a trigger quoted inside a
leading JSON object stays data. The bare-JSON strip requires the
parser's top-level name in every mode, so nested-name JSON answers
survive name-agnostic stripping.
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* Let a leading <|python_tag|> call own the turn over quoted XML literals
The leading-call ownership contract (a leading executable call owns the turn;
foreign markup quoted in its string arguments or trailing prose stays data) was
enforced for the bare-JSON, Mistral and attribute-form leading calls but not
for the Llama-3 <|python_tag|> form. The shared tool_healing XML pass runs
before _parse_llama3_python_tag and does not recognise <|python_tag|>, so a
<function=...> / <tool_call> / [TOOL_CALLS] literal quoted inside a
<|python_tag|> .call(...) string argument (or its JSON parameters) was promoted
and the wrong tool executed. Well-formed single-format examples:
<|python_tag|>web_search.call(query="... <function=foo> ...") -> foo
<|python_tag|>python.call(code="<function=render_html>..</function>") -> render_html
both returned the phantom inner tool instead of the real leading call.
Add a leading-<|python_tag|> guard mirroring the other leading-call guards:
when the tag is the first tool signal, parse it before tool_healing so quoted
foreign markup stays data. A foreign signal before the tag keeps normal
document order. Added TestPythonTagOuterOverXmlLiteral (7 cases).
* studio: tighten tool-calling comments to be shorter and clearer
* studio: shorten tool-format comments in changed files
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: Daniel Han <info@unsloth.ai>
Co-authored-by: danielhanchen <danielhanchen@users.noreply.github.com>
* scan_packages: key baseline on matched-code hash
The baseline matched on (package, package-relative file, check), which
excluded the matched code, so a future finding of the same check in the
same file was suppressed regardless of what the code did. A malicious
future version of an already-baselined package could place a payload in
the same file under the same check and pass the enforcing gate.
Key the baseline on a hash of the matched code too. The hash is over the
deduped, sorted set of matched spans with L<NN>: line markers stripped, so
version bumps, line shifts and match reordering stay stable while new or
changed flagged code reopens the finding. Version is left out of the key so
routine dependency bumps do not reopen every entry. The hash is capped and
recomputable from the stored evidence.
Regenerate scan_packages_baseline.json against the current dependency set;
the hf-stack, studio and extras scan shards pass enforcing (no active
CRITICAL or HIGH).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* scan_packages: refresh baseline for newer unsloth-zoo release
A newer unsloth-zoo published after the first regenerate added
tests/test_mlx_save_export_regressions.py, a benign test fixture
(temporary_location="/tmp/ignored") that trips the /tmp dropper check.
Regenerate the hf-stack shard against the current set so the entry is
allowlisted; studio and extras are unchanged.
* scan_packages: harden baseline loading against malformed JSON
Guard against a non-dict top-level baseline and non-dict entries so a
corrupt or hand-edited allowlist warns and fails closed instead of
crashing with AttributeError, and treat an explicit evidence: null as
empty.
* scan_packages: hash the full match set, keep indentation, strip only the marker
Address the evidence-hash review feedback:
- Capture every matching line, not the first three, so a payload appended
after existing matches in a baselined file and check reopens the finding
instead of riding the sample.
- Preserve leading indentation so a flagged line moved out of a guarded block
reads as changed.
- Strip only each span's prefix up to the first L<NN>: marker, so an L<NN>:
inside the matched code is kept and a change to it reopens the finding.
Evidence and its hash are stored in full and stay recomputable from the stored
field. Regenerate the baseline; hf-stack, studio and extras pass enforcing with
no active CRITICAL or HIGH.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* scan_packages: bind baseline evidence to full matched code
Address review feedback on the evidence-hash baseline key:
- Split evidence only on real span delimiters (" | " before an L<NN>:
marker, or a newline), so a bitwise-or or union type in matched code
is no longer split apart into separate spans.
- Record matched lines in full (drop the 160-char per-line cap) and
record every distinct multiline match, so code appended past the cap
or a second cross-line match reopens the finding instead of riding the
first one.
- Give the large-JS-bundle and .pth base64-blob findings a content
digest instead of empty or prefix-only evidence, and record all .pth
import lines, so a changed bundle, blob or import no longer inherits a
baselined empty or truncated key.
- Warn when a loaded baseline has entries without evidence_hash so a
legacy baseline is regenerated rather than silently degraded.
Regenerate scripts/scan_packages_baseline.json against the current dep
set and add regression tests for each case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* scan_packages: harden multiline and duplicate evidence handling
Follow-up hardening so the evidence hash tracks the full matched code:
- For DOTALL patterns that match across lines, record every line the match
spans (not just the start line), so a change on a continuation line (the
URL inside a baselined C2 loop, a swapped credential path) reopens the
finding. A pathological greedy span is bounded to its head line plus a
digest of the rest.
- Keep duplicate spans in the canonical evidence so a second identical
matched line in a new code path changes the key instead of deduping away.
- Anchor the evidence prefix to strip only a genuine leading label or
line-number marker, leaving a marker-like "L<NN>:" inside raw .pth code
intact.
- Make the legacy-baseline warning explicit that entries without an
evidence_hash reopen rather than suppress under a coarse key.
Regenerate scripts/scan_packages_baseline.json (same finding set; entries
for same-file repeated checks are now tracked separately) and add tests.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* scan_packages: bind every combo and large finding to its full content
Close the remaining asymmetric-evidence gaps so a changed payload cannot
ride a reviewed baseline entry:
- Digest a capped multiline span from the code without line markers, so a
pure line shift stays stable while a continuation-line change reopens.
- Give the "Unusually large executable .pth" finding a content digest
instead of keying on byte size and import-line count alone.
- Record both contributing signals for the JS credential+network stealer,
the shell credential+network and persistence-hook combos, and the hidden
network+exec docstring payload, so changing the network/exec side reopens.
- Allow punctuation in an evidence label prefix so a "network+exec:" label
is stripped and line shifts do not change the key.
Regenerate scripts/scan_packages_baseline.json and add tests for each case.
* scan_packages: bind remaining Python combos; key npm baseline on evidence
Python scanner: the openssl+key, anti-analysis, DNS-exfil and base64+exec+blob
combos recorded only one contributing signal, so a changed payload on the other
side could ride a reviewed baseline entry. Each now binds every co-occurring
signal (and the blob is digested, since it can sit on a separate line from the
decode call).
npm scanner: scan_npm_packages.py keyed its allowlist on (package, path,
pattern) only, the same coarse-key bypass the Python scanner just closed. Add an
evidence hash to the key (schema v3, fail-closed on older baselines) and store
full evidence. The committed baseline stays empty by design.
Regenerate scripts/scan_packages_baseline.json and add tests for each case.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* scan_npm_packages: bind full blob evidence and harden baseline loader
Follow-up on the npm evidence-hash key:
- _evidence now records every match and, when a snippet is truncated for
display, appends a digest of the full match. The obfuscated-blob key was
hashing only the truncated first-match snippet, so a changed payload tail or
an appended blob in the same package/file/pattern could ride a reviewed entry.
- _load_baseline guards that the root is an object, entries is a list, and each
entry is a dict before reading it, so a malformed baseline warns and fails
closed instead of raising AttributeError.
Add tests for a changed blob tail reopening the key and for malformed entries.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* scan_packages: symmetric baseline-loader guards; bind npm outbound host context
- Python _load_baseline now rejects a non-list "entries" with a warning instead
of raising TypeError, matching the npm loader.
- npm cred-surface-host (outbound) records the host with its URL path / fetch
call / host config, so a changed outbound path, headers or body reopens the
key rather than riding the bare host literal.
Add tests for both.
* scan_npm_packages: migrate v2 baselines and bind host-config outbound context
- _load_baseline now migrates schema v2 entries by recomputing the evidence
hash from stored evidence (with a legacy warning), matching the Python
loader, instead of discarding them; only pre-v2 basename schemas are rejected.
- The cred-surface-host (outbound) host-config branch now captures the whole
line (path, headers, body), so a changed outbound payload on the same
hostname line reopens the key instead of riding the bare host snippet.
Add tests for v2 migration and the host-config context binding.
* scan packages: bind PEM key bodies and npm windowed evidence to baseline keys
scan_packages: embedded-key findings now pin the full PEM block (BEGIN..END)
via a content digest, so a key body swapped under the same marker reopens the
finding instead of riding the unchanged BEGIN line. Single-line and DER keys
were already bound by their full matched line; marker-only references with no
END block (validation header lists) are unaffected, so the committed baseline
is unchanged.
scan_npm_packages: _evidence now digests the full containing line whenever the
shown snippet is only a window into it (short match on a long line, or a
truncated payload), so a changed payload tail outside the display window
reopens the key. The npm baseline is empty, so this changes no suppressions.
Adds regression tests for both cases.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* scan packages: bind multi-line evidence and every blob to baseline keys
_extract_evidence now extends each single-line match over its bracket
continuations, so a multi-line call binds its argument lines and a changed
URL or body on a continuation line reopens the key. After the per-line pass it
also records cross-line matches the scan cannot otherwise see (a DOTALL regex,
or a multi-line construct appended under a check that already had a one-line
match), so an appended multiline payload reopens instead of riding the key.
_blob_digest hashes every large base64 blob (not just the first) for the
base64+exec finding and the .pth large-blob finding, so an appended or swapped
second encoded payload reopens; single-blob files keep the same digest.
scan_npm_packages _evidence digests the full logical line (the matched line
plus its bracket-continuation lines), so a multi-line fetch's option and header
lines bind and a changed payload on a following line reopens the outbound key.
Regenerated the Python baseline: same package/file/check set, 24 entries pick
up the wider multi-line evidence. Adds regression tests for each case.
* scan packages: stop giant greedy spans from binding a whole-file digest
When a greedy DOTALL pattern (reverse shell socket...subprocess, C2 loop) has
its anchor tokens far apart, the match span covers the whole file. Digesting
that span bound thousands of unrelated lines, so the evidence hash drifted on
any edit between the anchors (a dependency bump reshuffling the file), which
made a baselined finding reopen on an upstream release. The multiline pass now
skips an oversized span when the per-line pass already bound the signal lines,
so the evidence is the stable matched lines; a genuinely appended multi-line
construct stays under the cap and is still recorded.
Regenerated the Python baseline against Python 3.12 (the version the scan CI
shards run) so the resolved dependency set matches CI. Same package/file/check
set. Adds a regression test.
* scan packages: tighten evidence binding (order, string brackets, span size)
Address review follow-ups on the evidence extraction:
- _canon_evidence keeps discovery (line) order instead of sorting. Line-shift
stability already comes from stripping the L<NN>: markers, so order stays
significant and reordering matched lines (a multi-line call's arguments)
reopens the finding.
- _logical_line_end (Python) and _logical_line_text (npm) blank string literals
before counting brackets, so a ) inside a string argument does not close the
logical line early and drop later argument lines.
- The oversized-span skip now only drops a giant whole-file bridge (over 60
lines); a genuinely appended multi-line construct is recorded so its payload
reopens, rather than riding an existing one-line match.
- npm _logical_line_text binds the enclosing bracket group, so a host-config
object whose { is on a prior line binds its path/headers/body lines.
Regenerated the Python baseline (Python 3.12, matching the scan CI shards):
same package/file/check set. Adds regression tests for each.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* scan npm packages: normalize and bound the logical-line digest
- _evidence whitespace-normalizes the logical line before digesting (matching
_evidence_hash), so a formatter-only reindent of the bound continuation lines
does not change the sha256 suffix and reopen an unchanged finding.
- _logical_line_text follows a bracket group to its close up to a hard 200-line
cap (digest input only), so a config object longer than the backward window
still binds its whole tail instead of silently truncating.
Adds regression tests. npm baseline is empty, so no regeneration is needed.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* scan: cap single-line evidence and widen npm opener window
Cap each rendered evidence line at 200 chars in scan_packages.py: a long
or minified one-line file is shown as a bounded prefix plus a sha256 of the
full line, so a packed payload cannot dump unbounded content into the CI
logs or baseline while a change past the cutoff still changes the digest
and reopens the finding. Mirrors how the npm scanner bounds its snippets.
Widen the npm backward opener window (_MAX_CONT_LINES 12 to 200, symmetric
with the forward cap) so a host deep inside a large options object binds
the whole object, not just its own line; a changed path, header, or body on
any property reopens.
Regenerate the Python baseline with Python 3.12: only the protobuf
nspkg.pth and unsloth-zoo compiler.py evidence change, both from the new
line cap; the package/file/check key set is unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* scan: bind all host contexts, deep call continuations, far-back npm openers
Three fail-closed evidence gaps surfaced by review of the previous round.
scan_npm_packages.py: measure the forward bracket-group cap from the matched
line (idx + _MAX_GROUP_LINES) instead of the opener, so an opener found near
the widened backward limit no longer consumes the forward budget and drops
the path, headers, or body that follow the host.
scan_npm_packages.py: _outbound_host_evidence now records every outbound
context form for a host (URL, fetch-context, host-config), claiming each
non-overlapping match in form order, so a separate host-config request added
beside an already-baselined URL changes the evidence and reopens the key.
The common single-context case keeps its existing snippet.
scan_packages.py: follow a matched Python call over its continuations up to a
separate _MAX_CALL_LINES (40), decoupled from the 12-line display threshold,
so a multi-line requests.post( binds its whole argument list in the digest
and a changed body deep in the call reopens; bounded so a miscounted bracket
cannot swallow unrelated code. No baseline change: the current dependency set
has no matched call that closes between 13 and 40 lines, confirmed by a
Python 3.12 regenerate that produced a byte-identical baseline.
* scan: clamp npm depth, pin large bundles, follow backslash and bound .pth dump
Four fail-closed evidence gaps surfaced by review of the previous round.
scan_npm_packages.py: clamp the backward opener scan at depth 0 so a leading
unmatched closer (a preceding block whose opener is outside the backward
window) no longer drives depth negative and masks the real enclosing opener
that follows; a host-config object after such a block now binds and a changed
path reopens.
scan_packages.py: a large JS bundle now pins its whole content even when
another JS heuristic already fired. The bundle digest was only added when no
other finding existed; it is now appended to every finding's evidence on a
large bundle, so an unchanged obfuscation signature no longer lets changed
payload elsewhere ride the matched-line key.
scan_packages.py: _logical_line_end follows explicit backslash line
continuations, so a call split with a backslash before its parenthesis binds
the continuation line (URL/body) instead of returning at the zero-depth API
line.
scan_packages.py: the catch-all .pth import evidence is bounded through
_cap_line (prefix plus a digest of every line) so a large .pth of benign
imports cannot dump the whole member into the logs or baseline while an
appended or swapped import still reopens.
Baseline regenerated with Python 3.12: key set unchanged; one entry
(unsloth-zoo compiler.py) gains the backslash-continued banner lines now
bound by the continuation fix.
* scan: handle multi-line strings, lifecycle bodies, and de-quadratic evidence
Addresses a review round plus a performance audit of the evidence extractor.
Correctness (fail-closed):
- Bind the UNION of the single-line-blanked and multi-line-blanked bracket spans
in both scanners. The multi-line view blanks a triple-quoted Python string or a
backtick template literal that spans lines, so a `)` inside such a string no
longer closes the enclosing call early and drop later arguments. The single-line
view still counts a payload embedded INSIDE a string, so a dropper that hides a
call in a string keeps its argument lines bound. Taking the larger span never
shrinks the binding below either view, avoiding a fail-open regression.
- cred-env-in-lifecycle now pins the whole lifecycle script body via a digest, so
a changed non-token line (e.g. adding a curl exfil beside the token reference)
reopens, not just a change on the token line.
Performance / DoS (the scanner runs on attacker-controlled package files up to the
64 MiB / 16 MiB member caps, with no per-file time budget):
- _extract_evidence precomputes newline offsets once and maps match offsets with
bisect, removing the O(matches) whole-file content.count per match that made the
finditer fallback quadratic (a crafted minified file went from ~13 s/MiB and
hours at the cap to linear).
- npm _index_text splits and string-blanks the file once per evidence call instead
of per match (was O(matches x file) time and allocation).
- Bound evidence output: _MAX_EVIDENCE_SPANS (Python) and _MAX_EVIDENCE_MATCHES
(npm) fold the remainder into a digest so a file with thousands of matches cannot
build a multi-megabyte evidence/baseline blob while an added/removed match past
the cap still changes the key.
- _outbound_host_evidence caps matches per form and bounds the overlap claim so a
host repeated many times cannot make it quadratic.
No baseline change: a Python 3.12 regenerate is byte-identical (the union equals the
legacy single-line span for every current dependency file; the cap thresholds sit
above the largest real entry), so these are forward-looking hardening with no drift.
* scan: count all overflow matches, bind their context, blank JS regex literals
Follow-ups on the evidence output caps from the previous commit.
- _outbound_host_evidence no longer truncates each pattern's match iterator with
islice; it iterates every match and runs the overlap dedup only while the
display list is below the cap (so claimed stays bounded and the check is O(cap)
per match, not quadratic), folding every match past the cap into the overflow
digest. A host context beyond the 64th is counted again, so it reopens.
- The overflow digest (both scanners, via a shared _overflow_digest) binds each
overflow match's logical-line context, not just the regex match text, so a
changed payload on an over-cap line reopens even with the matched token
unchanged.
- The multi-line JS blanked view now blanks regex-literal bodies (tracking the
previous significant char for regex-vs-division and char classes for a literal
`/` inside `[...]`), so a `)` inside `/)/` no longer closes an outbound call
early. The bound span is the union of the single-line and multi-line views, so
an imperfect regex decision only ever grows the span, never shrinks it.
- The Python overflow digest canonicalizes spans (strips L<NN>: markers via
_canon_evidence) before hashing, restoring line-shift stability for the
over-cap region.
No baseline change: the overflow branches only trigger above the per-finding caps
(above the largest real entry), and the npm baseline is empty, so a Python 3.12
regenerate is byte-identical.
* scan: refresh baseline for ipython interactiveshell.py span drift
A newer ipython release changed the filesystem-enumeration span in
IPython/core/interactiveshell.py, so its content digest no longer matched the
baselined evidence and the studio scan shard flagged it as a non-baselined
CRITICAL. Regenerated with Python 3.12: only the ipython entry's evidence_hash
changes; the package/file/check key set is unchanged, and a studio enforcing
spot-check exits 0.
* Bound scanner evidence memory: stream overflow spans and cap lifecycle baseline size
scan_packages.py: _extract_evidence no longer materializes a rendered span
per match before slicing at the display cap. Once out holds _MAX_EVIDENCE_SPANS
spans, further spans fold straight into a running digest, so a minified or
padded file with hundreds of thousands of matching lines keeps memory bounded
to the display cap instead of the match count. The fold reproduces
_canon_evidence(" | ".join(overflow)) byte for byte, so the overflow digest and
every baseline key are unchanged.
scan_npm_packages.py: lifecycle-fetch-exec and cred-path-in-lifecycle stored the
entire install script body as evidence, so --write-baseline on a package with a
multi-MiB lifecycle script bloated the baseline JSON. Both now store a bounded
matched snippet plus a body-sha256 digest, matching cred-env-in-lifecycle. The
digest still binds the whole body, so a change to any line reopens the finding.
Adds tests for the streamed overflow bound and the bounded-but-reopens lifecycle
evidence. Baseline unchanged (byte-identical Python evidence; npm baseline empty).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Make npm bracket-group scan order-aware so a same-line close-then-open binds
_scan_group counted brackets with a per-line net (opens minus closes), which
collapses intra-line order: a line that closes a prior block and then opens the
host-config object on the same line, e.g. `}); const opts = {`, nets to <= 0, so
the trailing `{` was dropped and the group started at the hostname line. A
changed path/headers on the following lines then hashed to the same evidence and
could ride an existing baseline key.
Replace the net count with an order-aware (L, R) reduction per line (L closers
needing an opener to the left, R openers needing a closer to the right) and apply
it in order in both the backward and forward scans, clamping stray closers at 0.
The trailing opener now stays visible so the whole object binds and a changed
payload reopens. Per-line cost is unchanged (one C-level bracket findall), so the
existing outbound-host evidence is byte-identical on all prior shapes; only the
previously-dropped same-line case changes. Adds a regression test for it.
* Harden scanner evidence: bound memory and bind Python call tails fail-closed
Five fixes across both scanners, none of which change the committed baseline (a
full regen of all three pip shards produced a byte-identical 185-key set).
scan_npm_packages.py: _evidence and _outbound_host_evidence collected every regex
match into a list before applying the 64-match display cap, so a text file under
the size cap that repeats a cheap signal (such as NPM_TOKEN) millions of times
could allocate a huge list of re.Match objects and stall or OOM before the
overflow digest ran. They now stream from finditer and fold overflow as matches
arrive via a shared _fold_overflow_match helper, byte-identical to the prior
digest.
scan_packages.py:
- _extract_evidence kept inserting every unique over-cap span into the seen set
even after it stopped appending to the display list, so a generated file with
millions of one-line matches still grew that set unbounded. It now tracks spans
only while filling the display list (per-line spans are unique by line number,
so dropping them past the cap cannot miss a dedup).
- _scan_line_end counted brackets with a per-line net, so a continued statement
that closes on the same line it opens a flagged call (a leading "]" before
"requests.post(") had the call's open paren cancelled and bound only the opener
line. It now applies brackets in order via _bracket_lr (leading closers clamp at
0), matching the npm bracket fix.
- a single-quoted string continued by a trailing backslash was not tracked across
lines, so a close paren inside the continued string on the next line closed the
call early; _blank_code_strings now carries the continuation.
- a call with more argument lines than the soft cap was hashed only through the
cap, so a changed data=/headers tail past it stayed suppressed; a closing call
is now followed to its real close under a 200-line hard limit (a never-closing
opener still stops at the 40-line soft cap so it cannot swallow the file).
Adds regression tests for each. npm baseline is empty; the Python baseline is
unchanged (verified byte-identical by regenerating all three shards).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Bind giant DOTALL span anchors and add context to constant IOC evidence
Two fail-closed gaps where a changed payload could keep the same evidence hash
and stay suppressed by the baseline.
scan_packages.py: a giant greedy DOTALL span (a cross-line IOC match bridging
more than 60 lines, e.g. RE_TEMP_EXEC matching a /tmp line and a much-later
subprocess line) was dropped entirely once the per-line pass had any match, so an
appended cross-line payload -- a new /tmp line plus a later subprocess line that
share no single line, so the per-line pass never binds them -- produced the same
evidence and rode the key. The span is no longer dropped: it is bound by its head
and tail anchor lines plus a digest over just those (no line numbers, so a pure
line shift is stable). An added or moved anchor reopens the finding, while churn
in the bridged interior stays stable, so this does not reintroduce whole-file
drift. Two baseline entries (multiprocess test, unsloth-zoo scanner file) carry
such a span and are refreshed; a full three-shard regen confirmed only those two
keys change.
scan_npm_packages.py: known-ioc-string and cred-surface-host (always-bad) recorded
only the bare needle/host as evidence, so a reviewed tarball that kept the IOC
string while altering the adjacent fetch/exfil body produced an identical key.
They now bind matched-line context: known-ioc-string via the matched line and its
bracket-group continuation, cred-surface-host (always-bad) via the outbound call
context (path/headers/body, falling back to the bare host when not in an outbound
call). A changed payload on the same call now reopens.
Adds regression tests for each. npm baseline is empty; the Python baseline updates
only the two giant-span entries.
* Hash giant-span interiors, bind exec/eval trigger, JS content, intra-literal whitespace
Four fail-closed gaps where a changed payload could keep the same evidence hash.
scan_packages.py:
- A giant bridged DOTALL span was bound only by its head and tail anchors, so a
cross-line payload inserted into the bridged interior between unchanged outer
anchors kept the same key. The whole span content is now digested (via _render),
so any interior change reopens; a pure line shift stays stable because the digest
is over the markerless code. Two baseline entries (multiprocess test, unsloth-zoo
scanner file) carry such a span; with full-interior binding, multiprocess
resolved at two versions across shards now yields two distinct entries where the
anchor digest had collapsed them into one.
- The exec/eval-with-hidden-payload findings omitted the visible exec/eval line
that makes the hidden string executable, so flipping a harmless eval("1+1") to
exec(__doc__) kept the same key while arming the payload. The trigger line from
the real-code view is now bound into the evidence.
- check_js_file extracted evidence with the Python-string-aware extractor, which
does not blank JS backtick template literals, so a template containing a close
paren closed a call's bracket span early and omitted later option/body lines. The
full file content digest is now pinned to every JS finding (not just large
bundles), binding the whole call.
scan_npm_packages.py: the evidence canon collapsed all whitespace via split(),
erasing whitespace inside JS string literals along with harmless indentation, so a
changed request body 'a b' -> 'a b' kept the same key. A new _canon_preserve_strings
collapses whitespace only OUTSIDE string literals (reindent-stable) while preserving
it INSIDE single/double/backtick literals (intra-payload edits reopen). Used for the
evidence hash and the logical-line digests.
Adds regression tests for each. npm baseline is empty; the Python baseline updates
the two giant-span entries and adds the second multiprocess version's entry.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
check_js_file put the bundle's KB size inside the finding's check label, which is
part of the baseline match key (package, file, check). When tensorboard's
projector_binary.js grew from 1918 KB to 1933 KB, the reviewed baseline entry stopped
matching and the benign HIGH resurfaced, red-failing the studio and extras
scan-packages shards. Move the size into the evidence field (shown for review, not
matched) and keep the check label constant, then update the one tensorboard baseline
entry to the size-agnostic label. The finding is suppressed again and will not
re-break when the bundle grows by a few KB. Scanner self-tests pass unchanged.
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Studio: drop OpenEnv and unused ExecuTorch/open_spiel install deps
* Studio: drop 8 more unused install deps from extras
* Studio: restore tomli<3.11 for kernels; tidy dep-cleanup comments and tests
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: refresh scan-packages baseline for scipy _external + unsloth-zoo tests
scipy moved its vendored array_api_compat from scipy/_lib to
scipy/_external, so the four allowlisted array_api_compat __init__.py
entries stopped matching and resurfaced as unsuppressed CRITICAL
"Downloads and executes remote code" findings on all three pip
scan-packages shards (extras, hf-stack, studio). Add the _external
paths next to the existing _lib ones so both scipy layouts stay covered.
Allowlist two unsloth-zoo test-file false positives now present in the
hf-stack shard: tests/test_mlx_save_export_regressions.py (writes to
/tmp dropper) and tests/test_mlx_trainer_internals.py (obfuscation plus
exec/eval).
Drop nine stale entries for packages removed from the Studio
requirements and no longer in any shard closure (evaluate, pytest,
hypothesis, kgb, langid), confirmed absent via with-deps resolution of
all three shards.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Three independent upstream CI fixes that currently fail on every open PR:
verify_import_hoist.py: TARGET-CHANGED only flags a genuine swap (a BEFORE
target no longer reachable in AFTER). A pure superset growth such as adding
import urllib.error next to import urllib.request binds the same top-level
package and loses nothing, so it is no longer a blocker (transformers_version.py).
test_vision_cache.py: run each test from a fresh empty cwd. is_vision_model
calls is_local_path first, and a relative model id that happens to exist on
disk short-circuits before the mocked detection runs; the CI cwd and HF cache
can contain dirs colliding with the synthetic ids, causing 'called 0 times'.
Production code is correct; only the test needed cwd isolation.
consolidated-tests-ci.yml: the llama.cpp smoke probes the first of
llama-cli / llama-mtmd-cli / llama-server that exists instead of hard-requiring
llama-cli, which upstream no longer always builds. llama-cli stays first so it
is preferred when present. Adds Windows .exe + build/bin/Release handling.
* Windows installer: fix DiskPart UAC, drive-root cache, spurious rename warning, CPU-base messaging
amd-smi gate (DiskPart UAC mid-install): the AMD torch wheel ships hipInfo.exe
inside the venv, and the bitsandbytes fix prepends that venv Scripts dir to PATH.
shutil.which("hipinfo") then found it and flipped _amd_smi_allowed() to True, so
the post-install AMD probe fell through to `amd-smi list` (the venv hipInfo failed
to report gcnArchName, which is why the arch came from the GPU-name table) and
amd-smi elevated, popping the DiskPart UAC. Fix: a hipinfo resolved inside the
active venv (sys.prefix) is the torch-wheel binary, not a HIP SDK, and must not
open the gate. Mirrored in install_python_stack.py, install_llama_prebuilt.py, and
backend utils/hardware/amd.py (the runtime VRAM poller had the same latent prompt).
TORCHINDUCTOR_CACHE_DIR: move from C:\tc to <StudioHome>\TORCHINDUCTOR_CACHE_DIR so
the inductor/Triton cache lives under the user's Studio home, not the system drive
root. Long paths are already enabled above so deep inductor paths still fit.
unsloth.exe rename: skip the rename (and its "pip may fail with WinError 32"
warning) when SKIP_STUDIO_BASE=1. In the install.ps1 flow base packages are not
reinstalled, so unsloth.exe is never rewritten; the self-rename only failed because
setup runs via unsloth.exe (the running launcher holds its own file). The
'studio update' flow still attempts it.
CPU PyTorch messaging: clarify that the CPU base is temporary and setup replaces it
with GPU ROCm wheels, and print an explicit "GPU ROCm PyTorch installed" line after
the AMD wheels land, so the log makes clear the final install is GPU-accelerated.
Adds two regression tests covering the venv-internal vs external hipInfo gate.
Verified end-to-end on a Strix Halo box (Radeon 8060S / gfx1151): install.ps1
--local from this branch completed exit 0 with no DiskPart prompt, no rename
warning, the cache under the Studio home, and "GPU ROCm PyTorch installed
(gfx1151)"; Studio then booted and detected "ROCm (HIP 7.13.99004) -- AMD Radeon
8060S Graphics".
* Windows installer: drop the unreliable unsloth.exe rename and its WinError 32 warning
setup.ps1 used to rename the running unsloth.exe out of the way before the
base-package upgrade so pip could replace it. That rename never actually
worked: setup runs *via* unsloth.exe, so renaming our own running
uv-trampoline launcher failed with a sharing violation (WinError 32) and only
printed a scary 'could not rename unsloth.exe; pip may fail with WinError 32'
warning on every Windows install and update.
It also was not needed. pip tolerates a running/locked console-script .exe: it
moves the old one aside and writes the new one. The base upgrade routes through
pip on Windows, so the upgrade succeeds (or, in the install.ps1 flow with
SKIP_STUDIO_BASE=1, the base is not touched at all) and unsloth.exe is left
intact either way.
Removing the rename block and its failed-install restore block removes the
false warning for all Windows devices in both the install and update flows.
* Windows installer: gate venv-internal hipInfo.exe in PowerShell amd-smi probe; harden venv path checks
Follow-up to PR #6296.
- install.ps1 and setup.ps1: ignore the AMD torch wheel hipInfo.exe that lives
inside the Studio venv when probing for a HIP SDK, so amd-smi no longer reopens
the DiskPart UAC during install/update. Mirrors _path_inside_venv in the Python
installers, which already do this.
- amd.py, install_llama_prebuilt.py, install_python_stack.py: normcase the venv
containment check (Windows paths are case-insensitive) and run the
HIP_PATH/ROCM_PATH candidate through it too.
- setup.ps1: fall back to a short TORCHINDUCTOR cache dir when long paths are
unavailable, and create the dir wildcard-safely.
- tests: isolate sys.prefix in the gate helper, add HIP_PATH/ROCM_PATH cases, and
assert the PowerShell venv exclusion.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Windows installer: install ROCm PyTorch directly for a known AMD arch
When the GPU arch is known (name-inferred from the GPU-name table) but ROCm
could not be probe-verified (no HIP SDK, no amd-smi), the bootstrap installed
a CPU PyTorch base that setup.ps1 then force-reinstalled as ROCm. The
repo.amd.com wheels bundle their own runtime (no HIP SDK required), which
setup.ps1 already relies on, so the CPU base was a pure wasted download/install.
- Gate the ROCm index on a known arch, not only on probe-verified ROCm, so a
mapped arch installs ROCm torch directly. Unmapped arches and no-GPU hosts
still get CPU (unchanged).
- Fall back to a CPU base if the ROCm-index install fails, so a transient
repo.amd.com outage does not abort the install (setup.ps1 retries ROCm).
- Correct the stale comment that claimed ROCm wheels need a confirmed HIP SDK.
- Add a regression test for the arch-based gate.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Windows installer: correct the unsloth.exe rename-removal comment
The comment claimed the base upgrade 'routes through pip on Windows' and that
pip 'moves the old unsloth.exe aside, then writes the new one'. That is not what
the code does. install_python_stack tries uv first; on a locked launcher uv
aborts and falls back to pip, but the pip fallback strips --upgrade-package and
base.txt lists only bare unsloth/unsloth-zoo, so pip finds them already
satisfied and no-ops. The running unsloth.exe is left intact at its current
version either way. Reword the comment to describe the real uv-first /
pip-fallback-no-op behavior. No functional change.
* Windows installer: close two gaps in the venv-internal hipinfo exclusion
Review follow-up. The amd-smi/DiskPart gate could still reopen in two cases:
- setup.ps1 ran the HIP probe long before $VenvDir is assigned, so without
VIRTUAL_ENV (the `unsloth studio update` path) $venvRoots was empty and the
venv-internal hipInfo.exe was not recognized. Seed the venv root from
UNSLOTH_SETUP_PYTHON and the default Studio home too (both installers).
- The HIP_PATH/ROCM_PATH candidate was accepted without the venv filter, so an
env var pointing into the venv (AMD wheel) still set $HipSdkInstalled. Run
Test-HipinfoIsVenvInternal on the candidate as well (both installers).
Extend the PS gate test to assert both. Both .ps1 parse clean; install tests
pass (the venv-internal / HIP probe coverage at 359 passed).
* Windows installer: correct the CPU-base message for arches with no ROCm wheels
After gating the ROCm index on a known arch, a mapped arch sets $ROCmIndexUrl
and installs ROCm directly, so it no longer reaches the "temporary CPU base"
branch. That branch is now reached only by a name-inferred arch with no ROCm
wheels (e.g. RDNA2 gfx103X), where setup.ps1 does NOT install ROCm. The old
text ("setup replaces it with GPU ROCm wheels ... the final install IS
GPU-accelerated") was therefore always wrong there. Say plainly that PyTorch
stays on CPU for this GPU.
* Windows installer: seed the venv-internal hipInfo check from a custom Studio home
Test-HipinfoIsVenvInternal seeded the venv root from VIRTUAL_ENV, VenvDir, the
setup python, and the default %USERPROFILE% path only. A standalone
`unsloth studio update` with a custom UNSLOTH_STUDIO_HOME (or STUDIO_HOME alias)
and none of those set would not recognize the venv hipInfo on PATH, reopening the
amd-smi/DiskPart gate. Seed the custom home too, in both installers, and assert
it in the gate test.
* Studio installer: resolve venv aliases and expand ~ in the hipInfo venv filter
Two review points on the amd-smi/DiskPart UAC gate:
1. _path_inside_venv compared os.path.abspath of sys.prefix and the hipInfo
path, which does not resolve symlinks, junctions, or 8.3 short names. A venv
reached through an aliased path then fails the check, so its bundled
hipInfo.exe is mistaken for an external HIP SDK and amd-smi runs (the
DiskPart prompt this fix exists to suppress). Switch to os.path.realpath in
all three copies (amd.py, install_llama_prebuilt.py, install_python_stack.py).
2. setup.ps1's early venv-internal hipInfo probe seeded the venv root from a
custom Studio home (UNSLOTH_STUDIO_HOME / STUDIO_HOME) without expanding a
leading ~, while the canonical resolver does. With a tilde form,
[IO.Path]::GetFullPath kept the literal ~ relative to cwd, so the custom-home
hipInfo escaped the filter and reopened the gate. Expand ~ in the probe the
same way as the resolver.
tests/studio/install/test_pr5940_followups.py: 30 passed (adds a symlink
realpath case and a setup.ps1 tilde-expansion guard).
* Studio installer: mirror the hipInfo venv filter and ROCm wheel pins into install.ps1
Follow-up review on the same install.ps1 paths:
1. install.ps1's venv-internal hipInfo probe (Test-HipinfoIsVenvInternal)
seeded the venv root from a custom Studio home without expanding a leading
~, unlike the canonical resolver and setup.ps1. A tilde form left
[IO.Path]::GetFullPath with the literal ~ (relative to cwd), so the
custom-home hipInfo escaped the filter and reopened the amd-smi/DiskPart
gate. Expand ~ in the probe, matching the setup.ps1 fix.
2. The AMD ROCm path installed torchvision/torchaudio bare while pinning torch
to below 2.12. AMD's per-arch index publishes the companions independently
and may ship torchvision 0.27 (for torch 2.12) before removing 0.26, so a
bare resolve can pick an ABI-incompatible set and fall back to CPU. Add
torchvision/torchaudio floor maps and pass the pinned specs, mirroring
setup.ps1 and install_python_stack.py.
3. The ROCm-to-CPU fallback torch install used Invoke-InstallCommand (no
retry), the only torch step in the file without it. Switch to
Invoke-InstallCommandRetry so the recovery path survives a transient index
failure.
tests/studio/install/test_pr5940_followups.py: 33 passed (parametrized tilde
check over both installers, a torch/companion floor-map parity test, and a
CPU-fallback retry guard).
* Studio installer: scan all PATH hipinfo so the venv copy can't shadow a real HIP SDK
The amd-smi HIP-SDK probe used shutil.which("hipinfo") / Get-Command hipinfo,
which return only the first hit on PATH. The AMD torch wheel ships hipInfo.exe
inside the venv and the bnb fix (plus the Studio backend) prepend the venv
Scripts dir to PATH, so that venv-internal copy lands first. When a real HIP SDK
hipinfo sits later on PATH with HIP_PATH/ROCM_PATH unset, the first-hit probe
stopped at the venv copy, treated it as "not a HIP SDK", and closed the amd-smi
gate -- AMD users in that PATH-only SDK setup lost amd-smi telemetry and could
fall back to CPU. Scan every PATH entry and keep the first hipinfo that is not
venv-internal; only the venv copy is ignored, so the UAC/DiskPart suppression is
unchanged.
Applied to all three Python copies (install_llama_prebuilt.py,
install_python_stack.py, backend/utils/hardware/amd.py) via a new
_external_hipinfo_on_path helper, and both PowerShell callers (install.ps1,
setup.ps1) now use Get-Command hipinfo -All filtered by Test-HipinfoIsVenvInternal.
tests/studio/install/test_pr5940_followups.py: 36 passed (real-PATH scan tests, a
shadow-regression test for the exact venv-first ordering, and a parity check that
every Python copy uses the scanning helper).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio uninstallers: fix leftovers (false "removed", shared icon, llama lock)
Auditing a dual native+WSL uninstall on a real device surfaced three leftovers:
1. uninstall.ps1 removed the data dir (which holds unsloth.ico) before the
shortcuts that reference that icon, so Explorer's icon cache briefly held it
open. Remove-Item -Recurse reported success yet left the locked file, and the
dir was never re-attempted, so it orphaned with a false "removed" log.
_RemovePath now verifies the path is actually gone (retrying transient locks)
and reports honestly, and the data dir is re-swept after the shortcuts go.
2. install.sh writes a shared unsloth.ico to %LOCALAPPDATA%\Unsloth Studio for
the WSL shortcut, but uninstall.sh never removed it, orphaning the icon (and
dir) after a WSL uninstall. uninstall.sh now drops that icon and the dir when
empty, in both the powershell.exe and drvfs-fallback paths.
3. ~/.unsloth/.llama.cpp.install.lock was never removed, so the rmdir of
~/.unsloth failed and the dir lingered. Both uninstallers now remove the lock.
Verified by running both uninstallers on a real dual install: device fully clean
(no install dirs, shortcuts, PATH/registry entries, shared icon, or lock left).
* install.sh: auto-route Strix Halo WSL to an existing Ubuntu 24.04
ROCm-on-WSL is the GPU runtime for Strix Halo and only targets Ubuntu
24.04. When the installer runs in a newer default distro (e.g. 26.04) it
cannot enable the GPU and silently falls back to CPU. If a 24.04 distro
already exists, re-run the install there and stop in the current one so the
GPU path is taken without the user having to know about the distro
requirement.
Runs before venv creation so the wrong distro is left untouched, guards
against re-route loops via UNSLOTH_WSL_REROUTED, leaves a working ROCm
distro alone (librocdxg present), and skips the GGUF-only / opt-out /
non-Strix cases. When no 24.04 distro exists we keep today's behaviour:
continue to CPU and print the `wsl --install Ubuntu-24.04` guidance, never
auto-downloading a distro.
Adds tests/sh/test_strixhalo_wsl_reroute.sh (hermetic: extracts the
function, rewrites its paths to fixtures, mocks wsl.exe) covering the full
decision matrix, wired into tests/run_all.sh.
* uninstall.ps1: keep shared unsloth.ico for a surviving WSL shortcut
A dual native+WSL install shares %LOCALAPPDATA%\Unsloth Studio\unsloth.ico:
install.sh points the WSL shortcut's icon there while the native install owns the
dir. The native uninstaller removed the whole dir unconditionally, so uninstalling
native while keeping WSL left the WSL shortcut with a blank icon. The old code only
avoided this when Explorer happened to hold the icon open, which is unreliable; on a
real dual install the dir was deleted and the WSL shortcut went blank.
_RemoveDataDirKeepingWslIcon now scans the Start Menu + Desktop for a surviving
"Unsloth Studio (WSL ...).lnk" and, if found, removes everything in the data dir
except unsloth.ico (keeping the dir) instead of deleting it; with no WSL shortcut it
removes the dir as before. uninstall.sh still drops the icon and the empty dir when
WSL itself is uninstalled, so every uninstall order ends clean.
Adds tests/studio/test_uninstall_dual_install_icon.ps1 (AST-extracts the helper and
runs it against a temp dir with controlled shortcut dirs) covering the dual,
native-only, empty, and missing-dir cases, wired into the windows-inference smoke
workflow. Verified on a real dual install: native uninstall now keeps unsloth.ico
and the WSL shortcut's icon stays intact.
* installer: condense AMD/ROCm code comments (no behavior change)
Tighten the comments added for the Strix Halo native+WSL installer work so
they are shorter and clearer without losing intent: the venv-internal hipInfo
amd-smi gate, the ROCm torch/companion floor maps, the WSL 24.04 reroute, and
the dual-install uninstall icon handling. Comment-only; code paths unchanged.
107 insertions, 166 deletions across 11 files.
* install.sh: run the Strix Halo WSL reroute before any STUDIO_HOME write
The reroute fired after mkdir -p "$STUDIO_HOME" and the legacy-venv migration,
so rerouting 26.04 -> 24.04 left an empty ~/.unsloth/studio stub in the origin
distro (and ran venv migration in the distro about to be abandoned). Move the
reroute ahead of the venv section so the origin distro is left untouched, matching
the function's own comment. Behavior is identical on every non-reroute path.
* installer: fix ROCm CPU-fallback, hipinfo gate edge cases, uninstall icon, WSL 22.04
- install.ps1: clear $ROCmIndexUrl/$ROCmTorchFloor after the CPU fallback so the
flavor-repair block does not retry the failed ROCm index and abort the install;
pin the ROCm companion specs ($visionSpec/$audioSpec) in the repair path too.
- install.ps1 + setup.ps1: skip a bare drive root in Test-HipinfoIsVenvInternal so a
non-venv UNSLOTH_SETUP_PYTHON does not match the whole drive; iterate
HIP_PATH/HIP_PATH_57/ROCM_PATH and take the first non-venv hipinfo.
- amd.py, install_llama_prebuilt.py, install_python_stack.py: strip surrounding
quotes from PATH entries before probing for hipinfo.
- install.sh: pipefail the WSL reroute curl|sh; do not reroute supported Ubuntu 22.04.
- uninstall.sh: keep the shared unsloth.ico while any Unsloth shortcut (native or
another WSL distro) still references it, in both the powershell and drvfs paths.
- tests: regression coverage for all of the above.
* installer: forward reroute options, guard ROCm bootstrap, harden hipinfo gate
- install.sh: forward the caller's --package/--python/--verbose/--tauri and a custom
UNSLOTH_STUDIO_HOME into the WSL reroute (was a bare default install); bail on
--local; run the reroute BEFORE dependency/uv install so the origin distro is left
untouched; set UNSLOTH_SKIP_ROCM_WSL_SETUP after a failed reroute so the later
ROCm-on-WSL bootstrap does not install into the unsupported origin distro.
- install.ps1 + setup.ps1: Get-Command hipinfo -CommandType Application so only real
executables match (not an alias/function named hipinfo).
- uninstall.ps1: guard $env:APPDATA when building the default shortcut search dirs.
- tests: cover option forwarding, --local bail, the bootstrap guard, and the gate change.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* installer: guard origin ROCm bootstrap on every CPU-only fallback; harden ~ expansion
WSL reroute: the no-wsl.exe, no-24.04-target and --local fallbacks all tell the
user the install continues CPU-only, but only the failed-reroute branch set
UNSLOTH_SKIP_ROCM_WSL_SETUP=1. The later _maybe_bootstrap_rocm_wsl gate keys off
that flag, so the other three branches could still install ROCm into the
unsupported origin distro (e.g. 26.04). Set the skip guard on all of them.
Forward UNSLOTH_ROCM_WSL_AUTO into the reroute so a Tauri/consented GPU bootstrap
carries through to the rerouted 24.04 child instead of dropping to the prompt path.
install.ps1/setup.ps1: guard the venv-probe ~ expansion on a non-empty
$env:USERPROFILE so Join-Path does not throw on a profile-less service account.
Tests: add no-wsl.exe and UNSLOTH_ROCM_WSL_AUTO reroute cases, the USERPROFILE
guard assertion, and route shell-test fixtures through a single trap-cleaned root.
* installer: pin + soften Windows ROCm Python repair, reroute to 22.04, harden gates
install_python_stack.py: the Windows AMD ROCm repair in _ensure_rocm_torch()
installed bare torch/torchvision/torchaudio via the fatal pip_install -- the same
asymmetry already fixed on the PowerShell side. A transient repo.amd.com failure
could abort the whole install even after install.ps1/setup.ps1 fell back to CPU.
Pin companions per-arch (gfx120X/Strix -> the rocm7.2 trio, mirroring the PS floor
maps) and make the retry nonfatal: keep the existing build and let the user re-run
update to retry ROCm, so the chain install.ps1 -> setup.ps1 -> stack stays CPU-safe.
install.sh: reroute now targets an installed Ubuntu 24.04 OR 22.04 (24.04 preferred);
both are AMD-supported for ROCm-on-WSL, matching the leave-alone set, so a box with
only 22.04 reaches the GPU instead of staying CPU-only.
install.ps1/setup.ps1: a bare ~ for UNSLOTH_STUDIO_HOME left an empty Join-Path child
(PS 5.1 throws); fall back to USERPROFILE directly and only join a real remainder.
_path_inside_venv (amd.py + both installers): guard a root-dir sys.prefix so commonpath
can't classify every path on the drive as venv-internal (defensive; venv never at root).
uninstall.sh: guard an empty LOCALAPPDATA in the PS-interop icon cleanup (mirror APPDATA).
Tests: add 22.04-target reroute cases, Windows ROCm pin+nonfatal coverage (text +
behavioral), root-dir guard coverage, and bare-~/LOCALAPPDATA guard assertions.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* install.sh: match WSL reroute target by exact distro name, not substring
The 24.04/22.04 reroute target was chosen with grep -F (substring), so a custom
distro such as 'Ubuntu-24.04-test' (with no exact Ubuntu-24.04) was picked as the
target; the later 'wsl -d Ubuntu-24.04' then fails and the Strix Halo install stays
CPU-only. Match whole lines (grep -ixF) and reuse the matched name so only a real
Ubuntu-24.04/22.04 is targeted. Adds substring-rejection + exact-vs-custom tests.
* install.sh: keep the WSL reroute target to Ubuntu 24.04 (helper-supported only)
The ROCm-on-WSL bootstrap (scripts/install_rocm_wsl_strixhalo.sh) dies on any
VERSION_ID other than 24.04 and pins the noble repo, so treating 22.04 as
GPU-supported let the parent report a successful reroute while the child fell
back to CPU. Drop 22.04 from the supported set and the reroute target list;
24.04 stays the sole target (keeping the exact whole-line distro match). An
already-working ROCm on any other version is still left alone by the librocdxg
check above.
tests: reroute 22.04 cases updated to the 24.04-only behavior; make the
"no wsl.exe" case hermetic so a real host wsl.exe can't leak in on dev boxes;
stop the tauri exit-order check from mis-flagging the reroute helper's
[ "$TAURI_MODE" = true ] && ... --tauri one-liner.
* installer: tighten comment wording across the Strix Halo install/uninstall paths
Condense the verbose multi-line comment blocks (amd-smi hipinfo gate, ROCm
torch install + CPU fallback, WSL reroute, uninstall icon-keep) into fewer,
clearer lines. Comments and a few docstrings only; no code, logic, or
behavior change. Verified with bash -n, the PowerShell parser, and ast.parse,
and the installer test suite still passes.
* add AGPL-3.0 SPDX headers to the .sh/.ps1 scripts missing them
Every shell and PowerShell script under the Studio/installer surface now
carries the standard SPDX-License-Identifier: AGPL-3.0-only + copyright
header (after the shebang where present): the installer (install.sh,
install.ps1), build.sh, the .github and src-tauri scripts, the installer
test suite, and the moe kernel test. Header-only, line endings preserved;
bash -n, the PowerShell parser, and the installer tests all pass.
* installer: drop the duplicate AGPL header from install.sh and install.ps1
Both already carry an SPDX-License-Identifier: AGPL-3.0-only header below
their usage comment block; the prior header pass added a second one at the
top because it only scanned the first few lines. Remove the duplicate so each
file keeps a single original header.
* installer: force-reinstall CPU fallback torch; propagate Tauri NEED_SUDO from reroute
install.ps1/setup.ps1: when the AMD ROCm wheel install fails and we fall back to a
CPU base, force-reinstall the torch/vision/audio triplet. A failed ROCm install can
leave an unpinned ROCm torch (e.g. 2.10.0+rocm on gfx110X/gfx90a) that still
satisfies the CPU torch>=2.4,<2.11.0 range, so without --force-reinstall uv keeps the
ROCm build and only swaps the companions -- a mismatched venv the flavor-repair block
won't fix. setup.ps1 scopes the forced reinstall to the ROCm-fallback path
() so the genuine CPU-only install stays fast.
install.sh: the Strix Halo WSL reroute treated every nonzero child exit as a reroute
failure and fell back to CPU. In --tauri mode the child uses exit 2 ([TAURI:NEED_SUDO])
to ask the desktop app to elevate for the target distro; capture the child's exit code
and propagate exit 2 in Tauri mode (the child already printed the NEED_SUDO line)
instead of masking it. CLI mode still falls back to CPU on a generic failure.
Tests: reroute Tauri exit-2 propagation (and non-Tauri CPU-fallback) cases;
run_func now preserves the child exit code; force-reinstall assertions for both
PowerShell installers.
Note: codex's _rr_q apostrophe finding is a false positive -- the helper already
emits POSIX-correct 'O'\''Brien' and round-trips under both sh and bash.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* setup.ps1: fix $cpuForce array collapse in the ROCm->CPU torch fallback
An if-expression assignment ($cpuForce = if ($ROCmCpuFallback) { @("--force-reinstall") })
collapses the single-element array to a scalar string, so @cpuForce splatting enumerated
it character-by-character into broken single-letter args (- - f o r c e ...), which made
uv/pip reject the install and aborted the whole Studio setup on the AMD ROCm->CPU fallback
path. Build $cpuForce as a real array assigned outside the if-expression so the splat passes
a single --force-reinstall arg. Genuine CPU-only installs stay fast (empty array, no flag).
Test now asserts the array-build form and rejects the if-expression form.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* uninstall: remove the isolated Node.js runtime (~/.unsloth/node)
The isolated Node.js runtime (install_node_prebuilt.py, added with the managed-Node
change) installs to ~/.unsloth/node in default mode -- a sibling of studio, so deleting
<studio> leaves it behind (~200MB orphaned after uninstall). Both uninstallers already
remove the other default-mode siblings (llama.cpp/.cache/.staging); add node alongside
them. uninstall.ps1 also adds it to the handle-lock sweep so a held node.exe can't block
the delete. Env/custom mode nests node under the custom root, removed with that root.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Three valid findings from the 06-22 Codex review:
1. provision_llama_cuda.sh: when $LLAMA_DIR holds a .git checkout (a prior CPU
source build), the whole-dir backup was skipped, so a failed CUDA rebuild's
'rm -rf build' destroyed the working CPU server with nothing to restore --
leaving NO llama-server despite the 'keeps the existing server' promise (a
thermal shutdown mid-build is a real failure mode on this hardware). Back up
build/bin before the rebuild and restore it on total failure; idempotent and
self-cleaning (never overwrites a freshly built server). Verified both paths.
2. uninstall.ps1: 'fuser -k 8888/tcp' killed ANY listener on 8888 (Jupyter et al.
default to it), not just Studio. Now only kills a PID whose /proc/cmdline is
under /root/.unsloth -- matching the adjacent pkill scoping.
3. setup.sh: the 'defer to background CUDA build' branch fired even on a direct
in-WSL 'unsloth studio update', where install.ps1 never launched a background
builder -- so the footer claimed a build was running while nothing built. Gate
it on UNSLOTH_WSL_LLAMA_DEFERRED=1 (set only by install.ps1, and already read
elsewhere in setup.sh); a direct run now falls through to a real CPU build.
bash -n + PS parse clean; the common install.ps1 WoA path (prebuilt success,
deferred flag set) is unaffected.
The empty-dir sweep of ~/.unsloth ran before the WoA-fallback block removes
~/.unsloth\unsloth.ico, so on a Windows-on-ARM install the still-present icon
kept the dir non-empty at sweep time and it was skipped -- leaving an empty
~/.unsloth behind after a full uninstall. Re-attempt the empty-only removal
right after the icon is deleted (the last default-mode child). uninstall.sh is
unaffected: its rmdir runs as the final step.
* Package scanners: close fail-open gaps in the sdist fallback and hidden-payload paths
Follow-up hardening on the now-blocking scanners so the enforcing gate cannot
report clean while a malicious artifact goes unscanned.
scan_packages.py
- Hidden payload: also flag a network call AND an os/subprocess exec that live
only in a blanked docstring/string of an exec/eval file (the fetch-then-run
shape of an exec(__doc__) dropper). Either alone in real code was already
covered; hidden together they are the payload.
- Pinned releases fail closed: _release_files no longer falls back to the latest
artifact when a pinned version is missing or empty, so a yanked/bad pin is an
error instead of a different file being scanned in its place.
- requires_dist is read from the pinned release's metadata, not the project-level
(latest) document, so a sdist-only pin follows its own dependency tree.
- Environment markers are evaluated (PEP 508) instead of dropping any marker that
merely contains the word extra, so default-true markers like extra != 'dev' are
kept; conservative fallback keeps a dep on any uncertainty.
- Transitive recovery is a depth-bounded worklist: a wheel dependency whose own
child is sdist-only is fetched (--no-deps) and scanned, then its children are
recovered in turn, rather than being silently skipped.
scan_npm_packages.py
- Baseline keys use the package-relative path instead of the basename, so the
same basename in a different directory is not over-suppressed.
Tests cover each case; full scripts pass AST and ruff checks.
* Address review: tighten marker scope, decoy-proof the dropper check, fail closed on missing pin metadata
- Markers: keep any dep whose marker can hold on another install target
(sys_platform == 'win32', python_version == '3.13'); only drop a marker that
depends solely on extra and is false with no extra. A scanner runs on one
target but must cover code installed on others. Pure-extra markers are
evaluated against default_environment() with extra unset.
- Hidden dropper: the network+exec docstring check now inspects the removed
(blanked) span directly, so a benign visible network or subprocess call cannot
mask a payload that still lives in a docstring. Carrier checks stay
blanked-only (an in-code carrier is already caught by the normal check), so
corpus findings are unchanged.
- requires_dist: a pinned version whose own metadata cannot be fetched recovers
nothing rather than substituting the latest release's dependency tree.
- Transitive recovery: the last-ditch direct-sdist branch also chases the
recovered package's declared deps, matching the other branches.
- npm baseline: schema bumped to v2 (package-relative keys); a pre-v2 baseline
with entries is ignored (fail closed) instead of mis-applying basename keys.
Tests cover each case; scripts pass AST, ruff, and the import-hoist verifier.
* Scanner: exclude comments from hidden-payload check, flag missing pin metadata as incomplete
Hidden network+exec detection now inspects only docstring/string spans (what exec(__doc__)/exec(<str>) can actually run), so a real exec() beside comments that mention a network and a subprocess call no longer false-positives. Missing pinned-release metadata in transitive recovery records a download_error so the --with-deps path fails closed instead of treating it as no dependencies. Adds regression tests for both.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Fix scan_packages.py --fix crash on download_packages() tuple return
`download_packages()` returns `(results, download_errors)`, but the two
`--fix`-path call sites still treated the return value as the bare results
list. `find_safe_version` did `downloaded = download_packages(...)` followed
by `if not downloaded:` (always false: a 2-tuple is truthy) and
`for _, archive_path in downloaded:`, which unpacked the results list into
two variables -> ValueError in the normal single-archive `--no-deps` case.
`_run_fix` indexed `downloaded[0][1]`, i.e. the second archive of the results
list instead of the first archive's path -> IndexError. So `--fix` crashed
exactly when a CRITICAL finding needed remediation. The main scan path already
unpacks the tuple; this aligns the two `--fix` sites with it.
Adds CPU-only regression tests for both sites.
Closes#6412
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Update scripts/scan_packages.py
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
* Update scripts/scan_packages.py
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
* Package scanners: cut false positives and make the CI gate blocking
scan_packages.py and scan_npm_packages.py red-failed on legitimate
library code, so the security-audit steps were left advisory. Reduce
the false positives at the source and flip both gates to blocking.
scan_packages.py:
- Scan code only: blank comments and bare docstrings/doctests before
matching (line numbers preserved), so prose and >>> examples cannot
trip a finding.
- Drop the platform.system() branch from the anti-analysis regex (under
DOTALL it matched across the whole file, so every cross-platform
library tripped it) and fix the dead /proc/self/status alternative.
- Add a reviewed baseline allowlist (scan_packages_baseline.json) keyed
on (package, basename, check): only non-baselined CRITICAL/HIGH exit
1, and a new kind of finding in a listed file still fails.
- sdist fallback: when --with-deps cannot resolve a shard (a sdist-only
package or a version conflict), drop to per-spec and fetch the raw
sdist from the PyPI JSON API (no pip build, no setup.py), so every
package is still scanned and no shard exits 2.
scan_npm_packages.py:
- Mirror the code-only JS/TS scanning (blank // and /* */ comments,
string/template/regex aware) and the baseline allowlist. The npm
corpus is clean today, so the baseline is empty.
security-audit.yml:
- Flip both scan steps to blocking (SCAN_ENFORCE=1), capturing the
scanner exit via PIPESTATUS so tee does not mask it.
tests/security: add coverage for the strip, baseline and sdist paths.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review feedback on the package scanners
- Do not blank f-strings during code-only scanning (they evaluate at
import); and when a file uses exec/eval, rescan the original for
payload carriers hidden in a docstring/string so exec(__doc__) style
payloads stay visible.
- sdist fallback: recover transitive deps with their version specifier
(fetch the pinned version, not latest), and recover deps in the
--no-deps branch too so a sdist-only transitive dependency is still
scanned instead of silently skipped.
- Baseline: key by package-relative path, not basename, so a future
same-named file in another directory is not auto-suppressed.
Regenerated the baseline accordingly.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
- install.ps1: force WSL2 (`wsl --set-default-version 2`) before installing a
NEW distro, so a host whose default is WSL1 doesn't get a GPU-less distro
that fails only at torch.cuda (the pre-existing-distro branch already
probes/converts).
- install.ps1: forward `UNSLOTH_PYTHON` into the WSL install (install.sh reads
it; a Windows env var isn't visible inside WSL otherwise). Numeric-only guard
rejects shell injection.
- install.ps1: add sqlite-vec / pymupdf / python-docx to the cut-short-install
server-deps repair so RAG/knowledge-base features aren't left broken.
- uninstall.sh: gate the Windows %LOCALAPPDATA%\Unsloth shim removal on the
current distro owning the fallback (wsl-distro.txt), so uninstalling Studio
from a different WSL distro no longer breaks the still-installed shim.
Disproved (no change): worker.py Spark name match is already whole-token
(commit 4cebfab, not substring); the shim's non-login WSL exec DOES have
/usr/lib/wsl/lib on PATH (nvidia-smi resolves -> Spark detector returns True),
verified on N1X.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The Windows uninstaller removed only the exact name "Unsloth Studio.lnk",
orphaning legacy "Unsloth Studio (WSL - <distro>).lnk" shortcuts left by
pre-release dev builds. Glob "Unsloth Studio (*.lnk" across Desktop + Start
Menu so the documented "remove the shortcuts" contract holds regardless of
suffix. Validated on N1X: both canonical and suffixed .lnk removed.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Fix Windows installer winget msstore certificate failure
`winget install` was invoked without `--source winget`, so winget also
queried the msstore source. When msstore fails certificate pinning
(error 0x8a15005e, "The server certificate did not match any of the
expected values") winget aborts and demands `--source`, so the Python
(and uv) install fails even though the package exists in the winget
source.
- Pass `--source winget` to all winget install calls (Python x2, uv).
Both packages live in the winget source, so this is strictly correct
and skips the failing msstore round-trip entirely.
- Add a python.org fallback (Install-PythonFromPythonOrg) that downloads
the official installer and runs it silently per-user (no admin/UAC)
when winget is unavailable or fails for any reason. Mirrors the
existing uv -> astral.sh fallback so Python installs without manual
steps. Resolves the latest 3.13.x from python.org with a pinned
fallback, and selects the amd64/arm64/x86 installer per architecture.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Pin remaining setup.ps1 winget calls to --source winget
Two winget invocations in studio/setup.ps1 still queried all sources and
could hit the same msstore certificate-pinning failure (0x8a15005e) that
broke the Python install in install.ps1:
- `winget show Nvidia.CUDA --versions` (CUDA Toolkit version probe)
- `winget install ... ShiningLight.OpenSSL.Dev` (OpenSSL dev for llama-server)
Every other winget call in this file already passes `--source winget`
(Git, CMake, VS Build Tools, CUDA install, Node.js, and setup.ps1's own
Python 3.12 install), so these two were stragglers. Both packages live in
the winget source; pinning it makes setup robust to an unhealthy msstore
source, matching the rest of the file.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Stop amd-smi GPU probe from popping a DiskPart UAC prompt
On Windows, AMD GPU detection in install.ps1 and studio/setup.ps1 runs
`amd-smi list` / `static --asic` / `version`. amd-smi (shipped in
System32 by the Adrenalin driver) auto-elevates to read GPU/APU memory
details, surfacing a confusing DiskPart UAC prompt mid-install. The
Studio backend already documents and circuit-breaks on this in
studio/backend/utils/hardware/amd.py, but the installers did not.
Add an Invoke-AmdSmiNoElevate helper (both scripts) that runs amd-smi via
Start-Process under __COMPAT_LAYER=RunAsInvoker so it cannot auto-elevate
(no prompt), with a 30s timeout (matching amd.py) so a flaky amd-smi
cannot stall the install for minutes. On failure/timeout the existing WMI
name -> gfx fallback still resolves the arch, so detection is unchanged on
working hosts.
Verified on a Strix Halo (Radeon 8060S / gfx1151) box: the prompt is gone
and the probe is bounded.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Add experimental ROCm-on-WSL setup helper for Strix Halo (gfx1151)
install.sh already routes gfx1151 (Radeon 8060S / Strix Halo) to the
repo.amd.com/rocm/whl/gfx1151 wheels once a ROCm runtime is present, but
it does not install AMD's driver/ROCm stack -- a large, admin-gated
prerequisite. scripts/install_rocm_wsl_strixhalo.sh automates the Linux
side on a dedicated Ubuntu 24.04 WSL2 distro: ROCm 7.2 (wsl usecase), the
rocr4wsl HSA runtime, a librocdxg build, env setup, and a PyTorch gfx1151
GPU smoke test. A hard preflight refuses to run until the Adrenalin
>=26.3.1 driver is actually present, so it cannot half-install.
Procedure adapted from AMD's ROCm-on-WSL docs and community gfx1151 notes.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Detect AMD GPUs by name so native Windows gets a GPU llama.cpp
The gfx-arch inference from the WMI GPU name was gated behind $HasROCm,
which the hipinfo/amd-smi probe leaves false on the common Windows case
(Adrenalin driver only, no HIP SDK -- and amd-smi often cannot read the
arch without elevation). So an AMD GPU was detected by name but never
mapped to a gfx target, --rocm-gfx was not forwarded, and studio setup
fell back to a CPU llama.cpp build.
Un-gate the inference (install.ps1 + studio/setup.ps1) so it runs whenever
an AMD GPU name is available. The inferred gfx is forwarded as --rocm-gfx,
which makes install_llama_prebuilt.py download the matching lemonade-sdk
ROCm prebuilt (e.g. llama-bNNNN-windows-rocm-gfx1151-x64.zip) -- a
GPU-accelerated llama.cpp that bundles its own ROCm runtime, so it runs
with just the Adrenalin driver. PyTorch's ROCm wheels still require a
confirmed HIP SDK ($HasROCm), so this only affects llama.cpp / inference
and never pulls broken ROCm torch.
Also broaden the name->arch table to every family lemonade ships Windows
assets for: gfx120X (RDNA 4), gfx110X (RDNA 3), gfx1151/gfx1150
(RDNA 3.5), and gfx103X (RDNA 2). Unknown names still fall back to CPU.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Suppress amd-smi DiskPart UAC prompt in the Python install/runtime paths
The earlier PowerShell guard covered install.ps1 / setup.ps1, but the
Python installer (install_llama_prebuilt.py detect_host,
install_python_stack.py ROCm probes) and the Studio backend monitor
(amd.py) also shell out to amd-smi on Windows, where it auto-elevates and
pops the same DiskPart UAC prompt mid-install / at runtime.
Inject __COMPAT_LAYER=RunAsInvoker into the amd-smi subprocess env on
Windows so it runs un-elevated (no prompt). Callers already tolerate an
empty/failed result and fall back to WMI / name detection (installer) or
the existing circuit breaker (amd.py). Gated to Windows so Linux/macOS
amd-smi behaviour is unchanged.
- install_llama_prebuilt.py: handled centrally in run_capture (covers
detect_host's `amd-smi list` and the version probe).
- install_python_stack.py: new _amd_smi_env() helper on its 3 raw
subprocess.run amd-smi calls.
- amd.py: merge RunAsInvoker into the existing child env.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Tighten AMD GPU name->arch patterns to avoid mismatches
The W9[0-9]{3} and RX 90[0-9]{2} patterns added for RDNA 4 were
speculative and over-broad: W9xxx would also match old GCN FirePro
W9100/W9000 cards (wrong gfx1201 -> a lemonade gfx120X download that
fails validation), and RX 90[0-9]{2} was redundant with the explicit
9070/9060 entries. Drop both; keep only confirmed RDNA 4 SKUs. Unmatched
AMD names still fall back cleanly to CPU.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Fetch the llama.cpp validation model via huggingface_hub
The prebuilt validation downloads a tiny GGUF test model from huggingface
via bare urllib. On Windows / proxy setups where the server sends an
incomplete TLS chain, urllib cannot complete the Amazon CA chain (it does
no AIA intermediate fetching) and fails with CERTIFICATE_VERIFY_FAILED, so
a perfectly good GPU prebuilt is rejected and the installer falls back to a
CPU source build.
Route the validation-model download through huggingface_hub
(hf_hub_download) -- the same mechanism Studio uses for model downloads,
which completes the chain where urllib cannot -- keeping the direct URL as
a fallback. This lets the lemonade ROCm prebuilt validate and install on
cert-restricted machines (verified: hf_hub_download succeeds where urllib
returns CERTIFICATE_VERIFY_FAILED).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Guard the remaining raw amd-smi version probe via run_capture
A ROCm-version detector in install_llama_prebuilt.py called amd-smi version through a raw subprocess.run that bypassed run_capture's Windows RunAsInvoker guard, so it still triggered the DiskPart UAC prompt during setup. Route it through run_capture like the other amd-smi calls.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Forward --rocm-gfx even when the ROCm runtime is unconfirmed
setup.ps1 forwarded --rocm-gfx (and picked the windows-hip llama.cpp
prebuilt) only inside `if ($HasROCm)`. On Adrenalin-only hosts (amd-smi
present but no HIP SDK, so $HasROCm stays false) the gfx arch was
name-inferred but never forwarded, so install_llama_prebuilt.py saw
has_rocm=False and installed the CPU build -- even though the lemonade
gfx1151 GPU prebuilt runs fine there (it bundles its own ROCm runtime;
verified: llama-cli --list-devices -> ROCm0: AMD Radeon 8060S, 69 GB).
Forward --rocm-gfx whenever a gfx arch is known (it is authoritative and
implies ROCm in install_llama_prebuilt.py), and treat a known gfx arch as
windows-hip in the existing-install mismatch check. --has-rocm stays gated
on the confirmed-runtime signal.
Verified on Radeon 8060S / gfx1151: the installer now selects, validates,
and installs llama-b1286-windows-rocm-gfx1151-x64.zip (ROCm DLLs present)
instead of the CPU build.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Install AMD ROCm PyTorch on name-inferred gfx hosts (enables Train/Export)
setup.ps1 picked the AMD ROCm PyTorch wheels only inside `if ($HasROCm ...)`.
On Adrenalin-only hosts (amd-smi present but no HIP SDK, so $HasROCm is
false) the gfx arch was name-inferred but the ROCm-wheel branch never ran,
so the host got torch+cpu. With CPU torch, torch.cuda.is_available() is
False, so the Studio backend sets CHAT_ONLY=True and hides Train/Export.
Un-gate the ROCm PyTorch index resolution on a known gfx arch (mirrors the
llama.cpp --rocm-gfx fix). AMD's per-arch Windows wheels
(repo.amd.com/rocm/whl/<gfx>) bundle the ROCm runtime, so they work without
a HIP SDK; a failed install still falls back to CPU.
Verified on Radeon 8060S / gfx1151: torch 2.11.0+rocm7.13.0 installs and
torch.cuda.is_available() -> True, device "AMD Radeon(TM) 8060S Graphics",
GPU matmul OK -> CHAT_ONLY=False -> Train/Export enabled.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Force amd-smi un-elevated process-wide in the Python installers
Guarding individual amd-smi call sites kept missing some (install_python_stack.py's probe loop and its Windows GPU re-check), so the DiskPart UAC prompt kept reappearing. Set __COMPAT_LAYER=RunAsInvoker process-wide at the top of install_python_stack.py and install_llama_prebuilt.py on Windows so every amd-smi subprocess (current and future) runs un-elevated with no per-call guard. Safe: these scripts only spawn amd-smi/rocminfo/hipinfo probes and pip/uv. setup.ps1 keeps per-call guards because it also spawns winget installers that need elevation.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Fix Invoke-AmdSmiNoElevate exit code on PS 5.1 + RX 7700S arch match
Start-Process -PassThru leaves the returned process object's .ExitCode
$null after WaitForExit on Windows PowerShell 5.1, so the helper set
$LASTEXITCODE to $null and every caller's `if ($LASTEXITCODE -eq 0 ...)`
was always false -- the amd-smi GPU / gfx-token / ROCm-version detection
branch was effectively dead (masked only because the un-gated WMI
name->gfx inference still ran). Reproduced on PS 5.1.26100.
Rewrite the helper to use [System.Diagnostics.Process]::Start with a
ProcessStartInfo (UseShellExecute=false), whose .ExitCode is reliable,
with async stream reads (ReadToEndAsync) to avoid a pipe-buffer deadlock
and WaitForExit(timeout) to bound a flaky amd-smi. __COMPAT_LAYER=
RunAsInvoker (inherited via the process env) still suppresses the
auto-elevation / DiskPart prompt. Also drops the temp files and the
empty-ArgumentList edge case. Verified: exit code propagates
(7 -> $LASTEXITCODE=7), output captured, env restored.
Also fix the gfx1100 name pattern `RX 7700(?! S)` -> `RX 7700(?!S)` so the
spaceless retail name "RX 7700S" is correctly excluded (it belongs to the
gfx1102 row). Both found by PR review.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Address PR review follow-ups (install.sh table, update path, tests, WSL)
From the multi-agent PR review:
- install.sh: sync the AMD name->arch table with install.ps1 / setup.ps1
(the bash table had drifted to the old narrow patterns). Adds RDNA 2
(gfx103X), workstation PRO W SKUs, and more Strix Halo/Point names, and
orders gfx1102 before gfx1100 so the spaceless retail name "RX 7700S"
resolves correctly (bash case has no negative lookahead). AMD-ROCm-only:
the name inference stays gated behind _has_amd_rocm_gpu(), so NVIDIA /
CPU / macOS are unaffected.
- setup.ps1: the "dependencies up to date" fast path skipped the torch
reinstall, so an existing user who had CPU torch (installed before
ROCm-wheel support) stayed stuck in CHAT_ONLY. Now, when an AMD gfx arch
is known AND the installed torch is CPU-only, don't skip -- force the
dependency pass so the ROCm wheels install.
- scripts/install_rocm_wsl_strixhalo.sh: resolve the real /opt/rocm dir
instead of hardcoding ROCM_VER for LD_LIBRARY_PATH / the librocdxg
symlink (breaks if amdgpu-install lays ROCm under a patch-version dir);
add a LIBROCDXG_REF pin knob and a "verified against" freshness header.
- tests/studio/install/test_pr5940_followups.py: cover _hf_resolve_url_parts,
_fetch_validation_model_bytes (hf path + urllib fallback), run_capture's
Windows-only amd-smi RunAsInvoker injection, and install.ps1 vs setup.ps1
name-table parity (catches future drift). 14 tests, all passing.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix DiskPart UAC prompt: skip amd-smi on Windows without a HIP SDK
On Windows, amd-smi re-initialises the ROCm runtime on every invocation
(even `amd-smi version`) and, on hosts without a working HIP runtime
(consumer APUs/dGPUs with only the Adrenalin driver), elevates a child
process at runtime -- popping a UAC/DiskPart prompt. amd-smi's own
manifest is asInvoker, so __COMPAT_LAYER=RunAsInvoker cannot suppress
that runtime elevation (verified: even `amd-smi version` hangs and
times out with RunAsInvoker set).
Replace the ineffective RunAsInvoker-only approach with a real gate:
only spawn amd-smi on Windows when a HIP SDK is detectable (hipinfo
present, so amd-smi runs un-elevated) or the user opts in with
UNSLOTH_ENABLE_AMD_SMI=1. The gfx arch is already resolved from WMI
name inference (forwarded via --rocm-gfx), so ROCm wheel + lemonade
llama.cpp selection is unaffected. Linux/macOS amd-smi never elevates
and is untouched (no regression). RunAsInvoker is kept as harmless
belt-and-suspenders for tools that DO use manifest elevation.
Applied consistently across:
- studio/backend/utils/hardware/amd.py (runtime GPU polling)
- install.ps1, studio/setup.ps1 (install-time detection)
- studio/install_llama_prebuilt.py (prebuilt arch probe + version)
- studio/install_python_stack.py (ROCm version + arch probe)
Verified live on AMD Radeon 8060S (gfx1151), native Windows: fresh
install detects the GPU, installs ROCm torch (torch.cuda.is_available()
True), launches Studio with no DiskPart prompt, and inference, tool
calling, web search, LoRA finetuning, and GGUF export all run on the GPU.
Tests: add 6 _amd_smi_allowed() gating tests + PowerShell-installer gate
assertions; update the three amd-smi monitoring tests to opt in (they
mock amd-smi as available). Full suite: 267 passed, 2 skipped.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* install.sh: helpful WSL message when the GPU isn't exposed to ROCm
In WSL, an AMD GPU's ROCm-on-WSL runtime is only available with a recent
Adrenalin driver AND a distro AMD supports (currently Ubuntu 24.04). When
neither is in place, GPU detection (rocminfo/_has_amd_rocm_gpu) finds
nothing and we silently fall back to CPU.
Add an actionable hint in the CPU-fallback path, shown only on WSL and
only AFTER detection has already failed -- so it is forward-compatible:
the moment a driver/distro DOES expose the GPU (e.g. if AMD later adds
Ubuntu 26.04 support), detection succeeds and the hint never fires. The
message:
- notes a GPU is plumbed in (/dev/dxg) but no ROCm runtime is exposed,
- lists the two prerequisites (Adrenalin driver + Ubuntu 24.04),
- if the distro is not 24.04, says AMD may not support it yet,
- tells the user to `wsl --install Ubuntu-24.04` and re-run,
- links AMD's ROCm-on-WSL guide + the experimental Strix Halo helper.
Verified live: on Ubuntu-24.04 the hint shows (version-warning omitted)
and the CPU install completes; on Ubuntu-26.04 the extra "this distro may
not be supported" line appears and points to 24.04.
Also fix the experimental scripts/install_rocm_wsl_strixhalo.sh: AMD's
repo.radeon.com/amdgpu-install/ is indexed by unified installer version
(30.30, 31.30, ...), NOT ROCm version, so the hard-coded
amdgpu-install/7.2.0/ path 404'd. Scan the installer dirs newest-first
for a noble .deb matching the target ROCm major.minor (ROCm 7.2 ->
30.30.x/amdgpu-install_7.2.x), falling back to the newest available.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* WSL: fix shortcut collision + pin ROCm-on-WSL driver reqs from AMD docs
Two WSL-related fixes informed by AMD's official ROCm-on-WSL docs and
field reports for Strix Halo / Ryzen AI Max+ (Radeon 8060S, gfx1151):
1. Shortcut collision (real bug). install.sh's WSL branch wrote
"Unsloth Studio.lnk" to the SAME Desktop / Start Menu folder as the
native-Windows installer (install.ps1 New-StudioShortcuts). Running
install.sh in WSL therefore silently retargeted the native shortcut at
the WSL launcher (wt.exe -> wsl.exe), so the desktop/start-menu icon
stopped launching native GPU Studio. Now the WSL shortcut uses a
DISTINCT name -- "Unsloth Studio (WSL - <distro>).lnk" -- and fetches
the Unsloth .ico to %LOCALAPPDATA%\Unsloth Studio so it shows the
proper icon. Native and WSL shortcuts now coexist.
2. Precise ROCm-on-WSL prerequisites. Research (AMD radeon-ryzen WSL
compatibility matrix, gianni.rosagallina.com Feb-2026 guide,
ROCm/ROCm#4952/#5509/#6022) confirms WSL GPU on Strix Halo requires
AMD Adrenalin Edition >= 26.1.1 (26.2.2+ is the first production
ROCDXG/WSL release) + ROCm 7.2.1 + Ubuntu 24.04; an older driver does
not inject the ROCm/DXG runtime into /usr/lib/wsl/lib, so rocminfo sees
only the CPU. install.sh's WSL hint and the experimental
install_rocm_wsl_strixhalo.sh header/preflight now state the exact
driver version (was a guessed ">=26.3.1"), bump ROCM_VER to 7.2.1, link
AMD's radeon-ryzen docs, and document the known librocdxg caveat that
usable VRAM is currently capped at the .wslconfig memory setting.
bash -n clean; install test suite 267 passed, 2 skipped.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: hint when the AMD driver is too old for ROCm-on-WSL
Adds a detect-and-guide hook for the optional WSL-GPU path. An AMD GPU on
native Windows can also be used inside WSL2, but only with AMD Adrenalin
Edition >= 26.2.2 (the first production ROCDXG/WSL release). Native Windows
GPU works with any recent driver, so this is purely about enabling the WSL
path.
We intentionally do NOT auto-install the driver: AMD referrer-gates driver
downloads (scripted curl/Invoke-WebRequest are blocked) and does not publish
Adrenalin via winget, so no installer can reliably fetch it -- and silently
swapping a live display driver is risky. Instead we point the user at AMD's
official download page (one click), after which the existing WSL detection
lights up automatically.
- install.ps1: new Show-AmdWslDriverHint -- when an AMD GPU is present and the
installed driver predates the 26.2.2 release (DriverDate < 2026-02-01),
print a concise tip with the AMD download URL. Handles DriverDate as either
a CIM DateTime or a WMI string. Suppress with UNSLOTH_SKIP_AMD_DRIVER_HINT=1.
- install.sh (WSL hint): add the direct Adrenalin 26.2.2 download URL and note
that AMD downloads are referrer-gated (open in a browser).
Verified: hint fires on a Sept-2025 driver, auto-suppresses on >= 2026-02-01;
install.ps1 parses; install.sh bash -n clean; suite 267 passed, 2 skipped.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* install.ps1: refresh shell icon cache after creating the shortcut
After writing the Desktop / Start Menu .lnk, nudge Explorer to refresh
its icon (ie4uinit.exe -show). Without this, a stale icon cache can show
a blank shortcut icon until the next explorer restart -- most visible
when a shortcut of the same name was rewritten (e.g. a native install
followed by a WSL install, which previously shared the name; now they use
distinct names, but the cache nudge makes the icon appear immediately
regardless). Best-effort and wrapped in try/catch so it never fails the
install. The bundled unsloth.ico itself is valid (verified it renders).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* setup.ps1: don't silently CPU-build llama.cpp on an AMD GPU
For AMD, GPU acceleration comes from the lemonade ROCm prebuilt (it bundles
the ROCm runtime, no HIP SDK needed) and is the preferred/default path. The
source-build fallback is CPU-only -- a HIP/ROCm *source* build would need the
full HIP SDK + ROCm clang toolchain, which the prebuilt exists to avoid.
Previously, if an AMD-GPU host ever fell through to the source build (e.g. the
prebuilt could not be downloaded), it printed "building llama.cpp (CPU-only,
no NVIDIA GPU detected)" and quietly produced a CPU binary -- masking the lost
GPU acceleration. Now that case emits a loud [WARN] explaining the GPU prebuilt
is the AMD path and how to restore it (re-run / check network / set
UNSLOTH_LLAMA_RELEASE_TAG), so AMD never silently degrades to CPU.
No behavior change on the happy path: AMD still gets the GPU prebuilt (verified
on gfx1151: ggml-hip.dll bundled, ~80% GPU compute during inference). NVIDIA
(CUDA source build) and CPU-only hosts are unchanged.
setup.ps1 parses; install suite 267 passed, 2 skipped.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* uninstall: remove shared llama.cpp build, kill lock-holders, match WSL shortcut
Three gaps found by running a real uninstall on a native-Windows + WSL host;
all fixes are scoped to Unsloth-owned paths and no-op on the other pathways
(env/custom-root, NVIDIA/AMD/CPU, Mac) so nothing else regresses.
uninstall.ps1:
- Remove the default-mode SHARED llama.cpp build + cache. setup.ps1 installs
them at ~/.unsloth/llama.cpp and ~/.unsloth/.cache -- SIBLINGS of studio,
not under it -- so deleting <studio> left hundreds of MB behind. Now removed
explicitly, then ~/.unsloth is dropped ONLY if empty (never nukes unrelated
content). No-op in env/custom mode (llama.cpp nests under the custom root,
removed already) and when absent. UNSLOTH_LLAMA_CPP_PATH (user-owned) is kept.
- New _StopProcessesLockingRoots: _StopStudioProcesses only matched the venv
unsloth/python/studio exe, so it missed (a) llama-server.exe under llama.cpp
and (b) an orphaned multiprocessing python fork that ran from the SYSTEM
python but loaded a venv DLL (bitsandbytes) -- on Windows an open DLL handle
blocks the directory delete, leaving a half-removed install. The new helper
kills any process whose image path OR loaded module is under a target root
(module scan scoped to python/unsloth/llama-server names; vendor-agnostic).
- _RemovePath now retries (transient post-kill handle release).
uninstall.sh:
- Remove the default-mode ~/.unsloth/llama.cpp + ~/.unsloth/.cache; rmdir
~/.unsloth only if empty.
- WSL Windows-side shortcut cleanup now matches by TARGET (any
"Unsloth Studio*.lnk" whose target launches wsl.exe), covering both the
legacy "Unsloth Studio.lnk" and the new "Unsloth Studio (WSL - <distro>).lnk"
-- and never removes a native-Windows shortcut (which launches wscript.exe).
uninstall.ps1 parses; uninstall.sh passes sh -n and bash -n.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* install.ps1: invalidate Win11 Start Menu tile cache after creating shortcut
The Start Menu shortcut kept showing a blank/generic icon even after the
Explorer icon-cache rebuild, because Windows 11's StartMenuExperienceHost
keeps its OWN pre-rendered tile-icon cache
(%LOCALAPPDATA%\Packages\Microsoft.Windows.StartMenuExperienceHost_cw5n1h2txyewy\
TempState\TileCache_*.bin + StartUnifiedTileModelCache.dat), separate from
Explorer's iconcache_*.db. ie4uinit and an explorer.exe restart do not touch
it, and they don't recycle the host -- so a rewritten same-name shortcut keeps
showing the first-rendered (often the generic wscript ">") tile until the host
restarts on its own.
Fix: after creating the shortcut, drop only the Start Menu RENDER caches
(TileCache_* + StartUnifiedTileModelCache.dat) and stop StartMenuExperienceHost
(Windows auto-relaunches it), so the tile re-resolves the real icon via the
shell image factory. start2.bin (the user's pinned layout) is deliberately
preserved. Guarded by Test-Path (Windows 10 has no such host -> skipped) and
wrapped in try/catch so it can never fail the install. Windows-only
(install.ps1); no effect on Linux/macOS/Studio.
Verified live: rendering the shortcut via IShellItemImageFactory::GetImage (the
API StartMenuExperienceHost uses) returns the Unsloth sloth icon, color-matched,
after this invalidation -- previously it returned the generic script tile.
install.ps1 parses; install suite 267 passed, 2 skipped.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* ROCm-on-WSL for AMD Strix Halo (gfx1151): auto-setup + runtime enablement
Make Unsloth Studio set up ROCm-on-WSL automatically for AMD Strix Halo
(Radeon 8060S / gfx1151) and use the GPU at runtime, validated end-to-end
on a Ryzen AI Max+ PRO 395 (ROCm 7.2.1 + librocdxg + Adrenalin Apr-2026):
rocminfo enumerates gfx1151, torch.cuda True, ~85.8 GB UMA pool.
Every change is a strict no-op for all other configs (NVIDIA/CUDA,
discrete + native-Linux AMD ROCm, macOS/MLX, Windows, CPU-only, non-Strix
WSL) and can never abort the installer.
- scripts/install_rocm_wsl_strixhalo.sh: rewrite to the validated recipe.
Fixes that would have broken a working box: drop the /usr/lib/wsl/lib
preflight (a working ROCDXG host has only d3d12/dxcore there); remove the
obsolete rocr4wsl step (gone from the 7.2.1 repo; would hard-fail and also
rips out the standard hsa-rocr ROCDXG needs); dynamic librocdxg soname
(was hardcoded 1.1.0; build is 1.2.0); direct apt-repo install; Windows
SDK auto-discovery; persist env to /etc/profile.d + ~/.bashrc; idempotent.
- install.sh: _maybe_bootstrap_rocm_wsl auto-offers/runs the helper when it
detects a Strix Halo APU in WSL (/dev/dxg) with no ROCm runtime, then
loads the env so detection routes to the gfx1151 wheels. Fast-path when
already configured. Fix an inaccurate WSL hint line.
- studio/backend/main.py + worker.py: set HSA_ENABLE_DXG_DETECTION=1
in-process before torch (gated on /dev/dxg AND librocdxg.so), so the
worker uses the GPU even when launched outside a login shell. Mirrors the
existing BNB_ROCM_VERSION injection.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* uninstall: clean up ROCm-on-WSL artifacts + Start Menu tile cache
- uninstall.sh: remove the ROCm-on-WSL helper artifacts -- the librocdxg
build clone (~/.unsloth/librocdxg, which otherwise blocks the empty-dir
rmdir of ~/.unsloth), the throwaway smoke-test venv, the persisted env
(/etc/profile.d/unsloth-rocm-wsl.sh) and the ~/.bashrc block. The system
ROCm userspace is a shared prereq like CUDA and is kept by default;
UNSLOTH_UNINSTALL_ROCM=1 removes it too. No-ops on macOS / non-Strix Linux.
- uninstall.ps1: invalidate the Win11 Start Menu tile cache after removing
the shortcut so its tile disappears promptly (mirrors install.ps1),
preserving start2.bin.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: accurate AMD ROCm messaging (HIP SDK optional, not required)
The Windows installer printed "HIP SDK not found - GPU-accelerated training
unavailable" / "ROCm wheels require the HIP SDK" whenever the HIP SDK was
absent. That is misleading: for a detected AMD GPU arch (gfx1151 etc.),
setup.ps1 installs AMD's bundled-runtime ROCm PyTorch wheels (repo.amd.com)
which ship their own ROCm runtime and do NOT need the HIP SDK -- verified
end-to-end (torch 2.11.0+rocm7.13.0, cuda True, QLoRA training on GPU) on a
Radeon 8060S with no HIP SDK installed.
Gate the GPU-detection + rocm-step messages on a detected gfx arch: when one
is known, state that GPU PyTorch uses bundled-runtime wheels and the HIP SDK
is optional; only when the arch is unknown fall back to the HIP-SDK hint.
Behavior (torch routing) is unchanged; this is messaging only. No-op for
NVIDIA/CUDA, HIP-SDK-present, and CPU paths (they hit earlier branches).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: fix /opt/rocm data-loss + make WSL shortcut create/remove interop-robust
Two fixes from the 3-reviewer regression audit + live testing on a
systemd-enabled WSL distro (interop disabled):
F1 (data-loss, install_rocm_wsl_strixhalo.sh): the /opt/rocm symlink-repair
could force-delete a pre-existing REAL ROCm install. The guard only checked
that /opt/rocm is a real directory, not that it is the stray librocdxg stub.
Now it only touches /opt/rocm when it is NOT a real install (no bin/rocminfo,
bin/hipcc, or .info/version present), and MOVES it aside (rocm.unsloth-stub-bak)
instead of deleting it, so a wrong guess can never lose data.
WSL interop robustness (install.sh + uninstall.sh): both relied on
`command -v powershell.exe`, which is true even when WSL interop cannot EXECUTE
it (on systemd distros powershell.exe fails with "Exec format error"). Result:
the WSL shortcut silently failed to create (install) and to remove (uninstall).
- uninstall.sh: test that powershell.exe actually runs; if not, remove the
"Unsloth Studio (WSL...).lnk" files directly via drvfs (/mnt/<drive>), which
works without interop. The name is WSL-install-specific, so a native install's
"Unsloth Studio.lnk" is never touched.
- install.sh: when the shortcut cannot be created, warn with the manual launch
command + how to re-enable interop, instead of failing silently.
No behavior change on the interop-on path. The regression audit otherwise found
no regressions on Linux/Mac/Windows/CPU/NVIDIA install paths.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* install.sh: fast-path fully restores ROCm-on-WSL env when the drop-in is gone
Reinstall regression found by uninstall->reinstall testing: after a Studio
uninstall that removed /etc/profile.d/unsloth-rocm-wsl.sh but KEPT the shared
ROCm (the default), a non-login reinstall hit the bootstrap fast-path
(librocdxg present) and its else-branch only set HSA_ENABLE_DXG_DETECTION --
NOT PATH/LD_LIBRARY_PATH. So rocminfo was not on PATH, GPU detection failed,
and the installer fell back to CPU-only PyTorch.
Fix: when librocdxg is present but the env drop-in is missing, restore the
FULL env inline (HSA + TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL + PATH +
LD_LIBRARY_PATH) so rocminfo is found and detection routes to the GPU, and
recreate /etc/profile.d/unsloth-rocm-wsl.sh so future shells and the Studio
worker get it too. No change to the env-present fast-path or any other host.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: clear Explorer icon cache so shortcut icons aren't blank
Root cause of the persistent blank Desktop + Start Menu icons: Explorer caches
each shortcut's icon in iconcache_*.db and does NOT re-read the .ico when a
same-name .lnk is recreated across reinstalls. The .ico and .lnk are correct
(the shell renders them non-blank via IShellItemImageFactory; the .ico has real
image data at 16/32/48/128 px), but the stale cache entry wins. The previous
fix only ran a weak `ie4uinit -show` + the Start Menu tile-cache clear -- it
never invalidated Explorer's icon cache, so the desktop icon stayed blank.
Fix (native install.ps1 New-StudioShortcuts AND the WSL shortcut path in
install.sh):
- ie4uinit -ClearIconCache (thorough; replaces -show as the primary refresh)
- SHChangeNotify(SHCNE_ASSOCCHANGED) to force a live desktop/taskbar refresh
WITHOUT restarting explorer
- keep the Win11 Start Menu tile-cache invalidation (and add it to the WSL
shortcut path too, preserving start2.bin)
Non-disruptive (no explorer restart). install.ps1 parses clean; install.sh
passes bash -n + dash -n; the heredoc-generated WSL PowerShell parses clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: per-item SHChangeNotify(UPDATEITEM) reliably fixes blank icons
The blank Desktop/Start Menu shortcut icons are a stale Explorer PER-ITEM icon
cache: when a same-name .lnk is recreated across reinstalls, Explorer caches the
previously-resolved (often generic "white page") icon for that item and won't
re-extract the .ico on its own. The .ico and the .lnk's IconLocation are correct
(every icon API renders the sloth) -- only Explorer's cached display is stale.
The previous refresh (ie4uinit -ClearIconCache + a GLOBAL SHCNE_ASSOCCHANGED
broadcast) does NOT recover a stale item -- confirmed by reproduction. The
reliable, NON-disruptive fix (no explorer restart) is a PER-ITEM
SHChangeNotify(SHCNE_UPDATEITEM, SHCNF_PATHW, <lnk path>) for each created
shortcut, which forces Explorer to re-read that exact item's icon.
Verified end-to-end: deliberately staled a shortcut to the generic icon, ran the
installer's exact new refresh code, and the sloth icon recovered with NO explorer
restart (confirmed by capturing the live desktop via PrintWindow).
Applied to both native install.ps1 (New-StudioShortcuts) and the WSL shortcut
path in install.sh. Still clears the on-disk icon cache (ie4uinit) and the Win11
Start Menu tile cache (preserving start2.bin).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* uninstall: remove leftover llama.cpp .staging root so ~/.unsloth is cleaned
The llama.cpp atomic-install staging root (install_llama_prebuilt.py
INSTALL_STAGING_ROOT_NAME=.staging) is a sibling of the llama.cpp install
dir (~/.unsloth/.staging in default mode). It is normally pruned after a
successful activate, but an interrupted or retained build can leave a
<name>.staging-XXXX tree behind. The uninstallers removed llama.cpp and
.cache but not .staging, so the final empty-dir cleanup of ~/.unsloth failed
and the directory lingered. Reproduced on WSL (Ubuntu-24.04) where an empty
llama.cpp.staging-XXXX dir kept ~/.unsloth alive after uninstall.
Remove ~/.unsloth/.staging in both uninstall.sh and uninstall.ps1. No-op in
env/custom mode (staging nests under the custom root removed already) and
when absent. Cross-platform fix (the staging logic is platform-agnostic).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer: WSL-absent hint + fix here-string lint false positive
install.ps1: in the AMD WSL-ROCm driver hint, detect when wsl.exe is absent
and add a one-line "wsl --install -d Ubuntu-24.04" pointer so a Strix Halo
user with no WSL yet gets an actionable next step (the hint previously assumed
an Ubuntu-24.04 distro already existed). Best-effort, informational only.
test_rocm_support.py: test_no_here_strings did a crude substring check that
false-positived on the conda-style block marker
printf '# <<< Unsloth ROCm-on-WSL (gfx1151) <<<' -- a string literal written
into the /etc/profile.d drop-in, also used as a sed delimiter pair by
uninstall.sh, not a here-string. Strip quoted spans before the check so the
lint still catches a real here-string operator but ignores quoted literals.
install.sh remains POSIX-clean (sh -n / dash -n / bash -n all pass).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* installer: address PR review comments (gfx1150 mapping, amd-smi opt-out, WSL bootstrap, SDK path, make)
Apply the valid bot review findings on #5940; reject the ones that don't hold.
Fixed:
- AMD name->gfx table (setup.ps1 + install.ps1): Radeon 890M and Ryzen AI 9 HX
370/375 are Strix POINT (gfx1150), not Strix Halo (gfx1151). Move 890M / HX 37x
/ AI 9 HX to the gfx1150 row and drop the bogus HX 38x pattern (no such Strix
Halo SKU). Matches the runtime classifier in worker.py (890M/880M -> gfx1150;
8060S/8050S -> gfx1151). Prevents Strix Point hosts from getting the wrong ROCm
prebuilt/wheels.
- amd-smi opt-out (setup.ps1 + install.ps1): an explicit UNSLOTH_ENABLE_AMD_SMI=
0/false/no/off now wins over the HIP-SDK heuristic, so a host with a HIP SDK
binary but a broken runtime no longer gets the DiskPart/UAC prompt the opt-out
exists to avoid.
- amd-smi warning probes (install_python_stack.py): _has_rocm_gpu and
_detect_amd_gfx_codes now gate amd-smi behind _amd_smi_allowed() (and pass
_amd_smi_env()), closing the last unguarded amd-smi spawn on Windows.
- WSL ROCm bootstrap (install.sh): the "already-usable ROCm?" early return now
requires rocminfo to enumerate the real gfx1151 agent instead of the generic
_has_amd_rocm_gpu (whose broad gfx[1-9][0-9] match accepts a fallback
"gfx11-generic" ISA), so a Strix Halo box missing the ROCDXG bridge is no longer
skipped. The shared helper is untouched (no gfx90a regression).
- install_rocm_wsl_strixhalo.sh:
* Quote-safe Windows SDK discovery: the old for-in-$(ls -d "...Program Files
(x86)/...") word-split on the space and never matched; use find + read loop.
* Add `make` to apt prereqs (cmake only recommends it; minimal images lacked it
and the librocdxg `make -j` build failed).
* Verification requires gfx1151 exactly (not gfx1[0-9]) so a generic ISA or an
unrelated RDNA GPU can't pass while the real GPU is absent.
Reviewed but NOT changed:
- "Forward inferred ROCm arch without HasROCm" (setup.ps1): already correct --
--rocm-gfx is forwarded under `if ($script:ROCmGfxArch)`, not `if ($HasROCm)`.
- "Route inferred arch into install.ps1 torch path": not a bug -- install.ps1
installs CPU torch as a base by design and setup.ps1 swaps in the ROCm wheel for
the inferred arch (gate `($HasROCm -or $ROCmGfxArch) -and cpu`); verified live
the native install ends on torch 2.11.0+rocm7.13.0.
- "$p null guard after Start-Process" (install.ps1/setup.ps1): redundant -- the
amd-smi runner uses [Process]::Start wrapped in try/catch, so a null process
already returns "" with LASTEXITCODE=1 (no uncaught exception).
- "ls -> find for /usr/lib/wsl/lib" (gemini): stale -- that heuristic was removed;
only a comment about it remains.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer(rocm-wsl): auto-install the Windows 11 SDK via winget (fewer manual steps)
librocdxg's build needs the Windows SDK 'shared' headers on the Windows host.
Previously the helper just die()d with "install the Windows 11 SDK and re-run" if
they were missing -- a manual prerequisite that broke the otherwise-seamless
`curl ... install.sh | sh` one-liner on Strix Halo.
Now, when the headers aren't found, the helper installs the Windows 11 SDK on the
Windows host from inside WSL via winget (powershell.exe interop), then
re-discovers them. The SDK installer elevates -> ONE UAC prompt on the Windows
desktop; the headers appear under /mnt/c immediately (drvfs is live, no reboot).
The user already consented to the ROCm-on-WSL setup, so no extra prompt is added
beyond the OS UAC gate.
- New _find_win_sdk (space-safe find of the newest installed SDK 'shared' dir)
and _install_windows_sdk_via_winget helpers.
- winget IDs tried newest-stable first: Microsoft.WindowsSDK.10.0.26100, then
.22621. The presence of the headers (re-check) is the source of truth, not
winget's exit code. </dev/null so winget never consumes a piped `curl|sh` stdin.
- Best-effort + non-fatal: interop-off / no-winget / declined-UAC all fall
through to the existing clear manual-install die(). Opt out with
UNSLOTH_SKIP_WIN_SDK_INSTALL=1.
Removes the last avoidable manual step from the WSL Strix Halo path; only the AMD
Adrenalin driver (AMD referrer-gates the download) remains manual. Verified
_find_win_sdk resolves the spaced "Program Files (x86)" path; bash -n clean; all
winget flags validated against `winget install --help`.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* installer(amd): gate install-time amd-smi probe to fix DiskPart UAC prompt
install_python_stack.py's Windows "AMD GPU detected but ROCm torch missing"
warning probe ran `amd-smi list` whenever amd-smi was on PATH -- and amd-smi
ships in C:\Windows\System32 with the AMD Adrenalin driver -- without the
_amd_smi_allowed() gate that every other amd-smi call site in the file uses.
On Adrenalin-only hosts (no HIP SDK) amd-smi elevates a child at runtime and
pops a UAC/DiskPart prompt that __COMPAT_LAYER=RunAsInvoker cannot suppress
(amd-smi's manifest is asInvoker). The probe also ran before the
ROCm-torch-installed check, so it fired on every Windows AMD install.
Gate it behind _amd_smi_allowed() and pass _amd_smi_env(), matching
_has_rocm_gpu()/_detect_amd_gfx_codes(). When skipped, the only loss is the
best-effort "AMD GPU detected" note on HIP-SDK-less hosts.
Adds a per-function AST regression test asserting every function in
install_python_stack.py that names the amd-smi command and spawns a subprocess
also references _amd_smi_allowed() (flags the pre-fix code; passes after).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* studio(cli): fix `unsloth studio stop` crashing on Windows
`stop` used the POSIX `os.kill(pid, 0)` liveness probe, but on Windows
CPython raises OSError (WinError 87, "The parameter is incorrect") for
*every* pid -- alive or dead. `stop` only catches ProcessLookupError /
PermissionError, so the OSError propagated and the command crashed with
a traceback before ever reaching its (correct) `taskkill /F` path.
Add a cross-platform `_pid_alive(pid)` helper (tasklist on Windows,
signal-0 elsewhere) and use it for both the pre-check and the post-kill
wait loop. The actual kill path is unchanged.
Verified on Windows (Python 3.13): os.kill(pid,0) raises WinError 87 for
both a live and a dead pid; `_pid_alive` returns True/False correctly and
the full stop() flow (alive -> taskkill -> dead -> "stopped") passes
end-to-end against a throwaway process.
Adds tests/studio/test_cli_studio_stop_windows.py (AST guard against a
bare os.kill(pid,0) liveness probe + mock-only _pid_alive behaviour for
the win32 tasklist branch and the POSIX signal-0 branch).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* installer(amd): fix install.sh name->arch table misrouting Strix Point to gfx1151
The bash name->arch inference table in install.sh placed Strix Point
identifiers (Radeon 890M, "Ryzen AI 9 HX 370/375", "AI 9 HX") in the
gfx1151 (Strix Halo) row, diverging from the install.ps1 / setup.ps1
PowerShell tables which correctly map them to gfx1150. It also carried a
stray "HX 38" token absent from the PowerShell source-of-truth.
Align install.sh with the PowerShell tables:
gfx1151 row: 8060S|8050S|8040S|Strix Halo|Ryzen AI Max|AI Max
gfx1150 row: 890M|880M|860M|840M|Strix Point|Krackan|HX 37|AI 9 HX|...
Impact is low (the bash table only feeds the display label _gpu_disp_gfx
and the "set UNSLOTH_ROCM_GFX_ARCH=..." hint; wheel selection is driven
by the detected ROCm version, not this name string) but a Strix Point
user would otherwise see/copy the wrong gfx arch.
Add a parity test (test_install_sh_name_arch_agrees_with_ps_for_strix_and_non_amd)
that parses install.sh's case table and asserts Strix Halo->gfx1151,
Strix Point->gfx1150, RX 7700S->gfx1102, and NVIDIA/Intel->no match,
cross-checking against install.ps1 (the previous parity test only
compared install.ps1 <-> setup.ps1, missing install.sh).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* setup.ps1: keep prebuilt-llama ownership guard within the test's block window
The AMD additions to the prebuilt-llama.cpp block (the windows-hip vs
windows-cpu existing-install kind validation) pushed the
install_llama_prebuilt.py invocation to ~1999 chars after the
"installing prebuilt llama.cpp bundle (preferred path)" anchor, right at
the edge of the 2000-char window that
test_setup_ps1_prebuilt_llama_cpp_has_ownership_guard slices -- so the
helper string was truncated and the test failed with "substring not
found" (CI: Repo tests (CPU)).
The ownership-guard invariant (Assert-StudioOwnedOrAbsent precedes the
install_llama_prebuilt.py call) was already satisfied; only the proximity
to the anchor regressed. Move the "installing prebuilt..." substep to
immediately before the install (after the existing-install pre-cleanup),
which also reads better (validate/clean existing -> then "installing"),
shrinking anchor->helper from 1999 to 413 chars. Behaviour is unchanged
(console message ordering only).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* install.sh: auto-run Strix Halo ROCm-on-WSL setup by default
`curl -fsSL https://unsloth.ai/install.sh | sh` should make a Strix Halo
(gfx1151) GPU usable inside WSL with no extra commands. Previously the
ROCm-on-WSL bootstrap was opt-in: it required UNSLOTH_ROCM_WSL_AUTO=1 or an
interactive [Y/n] at a TTY, and silently skipped under a pipe (no /dev/tty),
so the piped one-liner never set the GPU up automatically.
Flip it to auto-by-default for the single narrow case the existing guards
allow (WSL + Strix Halo + /dev/dxg + no usable ROCm yet) -- exactly the GPU
setup the user ran the installer for. Opt out with
UNSLOTH_SKIP_ROCM_WSL_SETUP=1. The Tauri desktop app keeps its own consent UI
(only auto-runs when it passes UNSLOTH_ROCM_WSL_AUTO=1). All hardware/OS
guards are unchanged, so non-Strix / non-WSL / NVIDIA / native-Linux / macOS /
CPU paths are unaffected.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* PR comments: condense to be succinct (comments/docstrings only)
Shorten the verbose explanatory comments and docstrings this PR added across
the installer, scripts, backend shims, CLI, and tests -- tighter, fewer lines,
while preserving every non-obvious "why" (os.kill WinError 87, amd-smi
RunAsInvoker/UAC, /dev/dxg + librocdxg gating, the ROCm-on-WSL bootstrap guard
chain, ownership guards, etc.). No executable code, string literals, messages,
or behavior changed.
Verified comments-only: docstring-normalized AST equality (Python, 9 files),
non-comment token equality (PowerShell, 3 files), comment-stripped diff +
sh -n / bash -n (shell, 3 files). Behavior re-confirmed: get_torch_index_url +
gfx name->arch table 44/44 under dash & bash; rocm_support / pr5940_followups /
cli_studio_stop tests green.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Installer: address PR review (amd-smi opt-out, pipefail, multi-distro, non-root)
Fixes valid findings from the Codex/Gemini PR review:
- install.ps1 / setup.ps1: gate the `amd-smi version` ROCm-version fallback with
$amdSmiAllowed so UNSLOTH_ENABLE_AMD_SMI=0 opt-out is honored (the device
probe was gated but this fallback wasn't), avoiding the DiskPart/UAC prompt.
- install_rocm_wsl_strixhalo.sh: make the post-verification rocminfo summary
best-effort (|| true) so head's early pipe-close under `set -o pipefail` can't
fail the bootstrap after gfx1151 was already enumerated; pin the Windows SDK
`winget install` to --source winget (matches the msstore-cert fix rationale).
- install.ps1: python.org fallback installs the py launcher per-user
(InstallLauncherAllUsers=0, avoids admin), and derives the fallback full
version from the requested minor so a non-default UNSLOTH_PYTHON (e.g. 3.12)
isn't silently replaced with 3.13 when the listing is unreachable.
- install.sh: recreate /etc/profile.d/unsloth-rocm-wsl.sh via `sudo tee` for a
non-root reinstall (a plain redirect failed silently, dropping the ROCm env).
- uninstall.sh: scope WSL Windows-side shortcut removal to the current
WSL_DISTRO_NAME (per-distro name or -d "<distro>" arg) so uninstalling one
distro no longer deletes other distros' launchers.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Studio ROCm Windows: fix field-reported issues from Strix Halo testers
Four fixes from PR #5940 field reports (Win11 native, gfx1151):
1. bitsandbytes arch-probe spam: bnb's get_rocm_gpu_arch() runs
hipinfo.exe via subprocess PATH at import; the AMD torch wheel ships
hipInfo.exe in the venv Scripts dir, which is only on PATH for
activated venvs. Every bnb import logged "Could not detect ROCm GPU
architecture: [WinError 2]" ERROR + WARNING (even with the HIP SDK
installed, whose bin dir is not on PATH either). Prepend the Scripts
dir to PATH before bnb imports in main.py, worker.py, and
install_python_stack.py, gated on the file existing (only AMD wheels
ship it). Verified on gfx1151: ROCM_GPU_ARCH now resolves to gfx1151
with zero errors.
2. OOM-guard double-tax on native Windows unified APUs: mem_get_info's
total is the WDDM budget the driver grants HIP (BIOS carve + ~half
of remaining RAM) -- the OS share is already outside it. The 0.80
unified cap on top denied loads that fit (field report: 48.49 GiB
budget -> "38.79 GiB allowed" OOM for a 47.29 GiB load with 48.08
free). Use 1.0 on win32 unified; Linux keeps 0.80, discrete 0.90.
3. "Missing VRAM" confusion: log the WDDM budget vs physical RAM with
the fix (BIOS UMA frame buffer / AMD Software Variable Graphics
Memory) when the grant is under 75% of RAM, so a 48 GiB cap on a
96 GiB box reads as policy, not a Studio bug.
4. llama-server fit-step crash (Qwen3.6-27B-MTP + mmproj, lemonade
gfx1151): --fit defaults to 'on' upstream, so the fit step runs even
when Studio already placed the model via -ngl -1, and aborts in
ggml-cuda.cu on some ROCm hosts. Retry the spawn once with --fit off
when the server crashes during startup and Studio's own VRAM math
had placed the model (never when use_fit or an explicit fit flag was
passed). Also keep the TAIL of crash output in the error log (the
diagnostic line prints last; head-truncation cut exactly that) and
reference the full on-disk log.
Verified live on Radeon 8060S: bnb import clean, Qwen3.5-4B-MTP loads
and generates through the new spawn loop, stub-crash retry appends
--fit off and recovers, fraction probes confirm WDDM overcommit and
sub-1.0-only enforcement on current AMD wheels.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio ROCm Windows: GPU-name fallbacks so nothing depends on amd-smi
amd-smi does not reliably exist on Windows: the HIP SDK never ships a
CLI, inbox Windows Update drivers do not, and only some full Adrenalin
packages drop amd-smi.exe into System32 (field report: fresh Win11 +
Adrenalin + HIP SDK, still no amd-smi anywhere). Make every consumer
work without it:
- install_python_stack._detect_windows_gfx_arch: two new probes after
hipinfo/amd-smi -- (2b) the venv Scripts hipInfo.exe shipped by AMD
torch wheels (drives `studio update` on driver-only hosts), and (4) a
last-resort GPU marketing-name -> gfx table via WMI
(Win32_VideoController), mirroring setup.ps1's $nameArchTable so a
standalone repair resolves the arch with zero AMD tooling installed.
- install_llama_prebuilt._resolve_exe: also probe the venv Scripts dir
so a standalone rerun finds hipInfo.exe without HIP_PATH.
- hardware/amd.py _run_amd_smi: which() guard before spawning --
absence now disables the poller in one step instead of burning the
3-strike circuit breaker on FileNotFoundError; corrected the stale
comment claiming Adrenalin ships amd-smi.
Simulated against the real detection functions on gfx1151: amd-smi
absent, present-but-crashing (exit 1), present-but-hanging (60s sleep
vs 5-10s probe timeouts), and hard opt-out -- all resolve gfx1151, no
exceptions, bounded time. Full adversarial install (broken amd-smi
stub first on PATH + UNSLOTH_ENABLE_AMD_SMI=1, fresh uninstall first):
exit 0, name-table arch inference, lemonade gfx1151 b1292 prebuilt,
torch 2.11.0+rocm7.13.0 cuda_avail=True on the 8060S, Studio boots
healthy and stops cleanly.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: per-attempt llama-server log names + amd-smi test portability
Found by cross-platform simulation of the --fit off retry (Windows +
Linux sandboxes, real load_model with stub servers):
- llama-server log filename now carries the spawn-attempt index. The
retry can respawn within the same epoch second; reusing the name
opened the same file with "w" and truncated the crash log the retry
warning had just pointed the user at (proven with a frozen
time.time: one file, crash evidence gone; with the suffix both
attempts keep their logs). Regression-pinned in
test_llama_cpp_wait_for_health.py.
- test_amd_primary_gpu_with_mock now mocks shutil.which alongside
subprocess.run: the amd-smi absence guard which()-checks before
spawning, so on hosts without a real amd-smi (Linux CI, driver-only
Windows) the subprocess mock was never reached and the test failed.
Surfaced by running the suite in a clean Linux sandbox.
Simulation coverage on both OSes: 67-case platform/edge matrix
(real shipped code blocks under win32/linux/darwin spoofs: OOM-guard
fractions + VGM-hint boundary, bnb PATH-prepend gates, retry
eligibility incl. equals-forms and decoy tokens, GPU-name table
adversarial set, WMI fallback without powershell, monitor absence
semantics), 6-scenario live retry matrix (crash-once/crash-always/
exit-zero/explicit-fit/hang/log-collision) against real llama-server
spawns on Windows and WSL (GPU success legs on the 8060S), and a
3-engine browser matrix (chromium/firefox/webkit) driving the live
backend's health + authed /v1 chat completion.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: classify unified-memory via props.is_integrated first
Align the ROCm OOM-guard classifier with PR #5988's UMA gate: consult
hipDeviceProp_t.integrated (props.is_integrated) before the hardcoded
arch set. Strictly additive -- truthy upgrades to unified; 0/absent
falls through to the existing gfx1150/gfx1151 + device-name logic, so
wheels that omit or zero the field cannot downgrade the known APU set.
Extends correct unified-cap treatment to APUs outside that set (e.g.
gfx1103 Phoenix iGPUs) and keeps Studio's two unified-memory consumers
on one driver signal. Verified live on gfx1151 (is_integrated == 1 on
the AMD Windows wheel -> ('gfx1151', True) via the new path).
* AMD detection: probe rocminfo with HSA_ENABLE_DXG_DETECTION and sync setup.sh gfx table
Fleet validation on a Strix Halo WSL2 box showed the system rocminfo
(HSA 1.18, ROCm 7.2.1) only enumerates the GPU over /dev/dxg when
HSA_ENABLE_DXG_DETECTION=1, and that rocminfo can sit at /opt/rocm/bin
off PATH outside login shells. Detection probes that miss either of
these report no GPU on a working ROCDXG host and select the CPU build
even though the lemonade bundle offloads fine (95.7 tok/s measured vs
64.5 CPU on the same laptop). Seed the env (a no-op on bare metal) and
the PATH fallback in install.sh, studio/setup.sh, and the installer's
Linux rocm probe, mirroring what main.py/worker.py already do for the
runtime.
Also sync studio/setup.sh's name->gfx table with install.sh: 890M and
the HX 37/AI 9 HX SKUs are Strix Point (gfx1150, not gfx1151), RX 7700S
must match gfx1102 before the gfx1100 row, and the RDNA2/workstation
rows were missing. New parity test pins the two bash tables together so
they cannot drift again.
* Studio: persist server session logs + native-crash stacks to disk
Field report (Strix Halo, 96 GB UMA carve, WSL and native Windows):
"the studio just terminates without a warning". A native crash in the
GPU runtime kills the process with no Python traceback, and a desktop-
shortcut console closes before anything can be read. The server only
ever logged to the console, so there was nothing to send back.
run_server now tees stdout/stderr to
~/.unsloth/studio/logs/server/server-<ts>-pid<n>.log (console behavior
unchanged; file copy is best-effort), arms faulthandler at the same
file so access violations / SIGSEGV leave a stack trace on disk, and
exports PYTHONFAULTHANDLER=1 so training workers inherit crash dumps
on their captured stderr. Armed before `from main import app` so even
import-time failures leave evidence. Keeps the newest 20 session logs;
opt out with UNSLOTH_STUDIO_NO_FILE_LOG=1. Prints "Session log: <path>"
at startup so users know what to attach.
Verified on this box: a forced real segfault (faulthandler._sigsegv)
leaves the full session output plus "Fatal Python error: Segmentation
fault" and the thread stack in the file while the console shows
nothing; a normal server boot captures the startup banner and serves
health as before.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* AMD probe: honor a pre-set HSA_ENABLE_DXG_DETECTION value
Match the shell helpers, which use the parameter-default form: a user
who exports HSA_ENABLE_DXG_DETECTION=0 to deliberately hide the GPU
from DXG detection should not have the probe override it.
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Studio: npm v12 readiness for install-script gating
npm 12 (July 2026) stops running dependency install scripts unless they
are approved via allowScripts, and npm 11.16 already warns. Studio has
no git or remote URL deps anywhere, so script gating is the only
exposure:
- commit the allowScripts policy that npm approve-scripts writes for
@biomejs/biome and msw, plus a manual fsevents entry: the tooling
cannot match a darwin-only optional dep from Linux, but the strict
check walks the platform independent ideal tree and flags it anyway
- drop the minimum-release-age npmrc alias; npm >=11.16 flags it as an
unknown project config that stops working in npm 12
- approve bun's postinstall in the setup.sh / setup.ps1 bun bootstrap;
under npm 12 defaults npm install -g bun otherwise leaves a broken
stub and setup falls back to the slower npm install path
- fix the stale esbuild comment in studio-frontend-ci.yml: the vite 8
chain ships napi binaries with no install scripts
* Studio: auto-sync allowScripts pins after dependency bumps
The allowScripts entries from #6128 are version pinned, so a biome or
msw bump strands the pin and the approval silently stops matching.
Dependabot cannot maintain the field, so:
- scripts/sync_allow_scripts_pins.py re-pins existing entries from the
versions package-lock.json actually resolves. It never adds or
removes entries, so approving a new script-bearing package stays a
human decision. Bare names and non-exact specs are left alone.
- a pre-commit hook runs it with --fix; pre-commit.ci pushes the fix
commit to PR branches, Dependabot's included, so stale pins heal
without a human in the loop
- a Frontend CI step runs --check plus the offline unit tests as the
backstop when pre-commit.ci is skipped
No dependabot.yml change needed: the /studio/frontend entry already
suppresses version PRs (security only) behind a 7 day cooldown.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Make the sync hook robust to lost executable bits
The pre-commit.ci autofix commit dropped the script's exec bit, which
breaks a shebang-style entry. Invoke via python instead and restore
the bit.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
The in-distro cleanup probed a hardcoded candidate set ('', Ubuntu,
Ubuntu-24.04, Ubuntu-22.04, Debian) on every Windows uninstall, wiping
/root/.unsloth in any reachable distro even when the WoA fallback never
ran -- on an x86 AMD box this deletes a ROCm-on-WSL Studio the AMD flow
installed. Use the evidence the installer already records: clean only
the wsl-distro.txt marker distro or UNSLOTH_WSL_DISTRO; keep the broad
candidate probe solely for legacy marker-less installs, which can only
exist on ARM64 hosts.
Addresses the open Codex P1 on this path. Verified gating matrix:
x86+no-marker -> no cleanup; marker/env -> that distro only;
ARM64+no-marker -> legacy broad probe unchanged.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Real fixes:
- uninstall.ps1: scope the WSL process kill to argv referencing
/root/.unsloth/ (the fallback's install dir, which its Studio server,
llama-server, and build runner all reference) instead of the bare
'[l]lama-server' / '[u]nsloth_studio' name patterns -- uninstalling the
Windows shim must not kill a user's own unrelated llama.cpp server or a
/home Studio in a probed distro. Proven live: the path pattern matched
exactly the three fallback processes while a planted /tmp/llama-server
decoy matched the old pattern and not the new one. The backslash in
'/root/\.unslot[h]/' keeps the pattern from matching the cleanup
command's own argv.
- install.ps1: bridge UNSLOTH_LLAMA_TAG / UNSLOTH_LLAMA_PR into the
background CUDA-build runner -- the provisioner honors both pins, but
Windows env vars don't cross into WSL on their own, so a user's pin was
silently ignored by the deferred build. (Deliberately NOT forwarded into
the inner install.sh env: setup.sh skips its deferral when a PR pin is
visible there, which would CPU-build the pin in the foreground.)
- kernels/flex_attention.py: make _flex_is_dgx_spark() CUDA-free
(nvidia-smi device names, mirroring _is_dgx_spark_no_cuda_init) -- it
runs at module import and called torch.cuda.get_device_name(), which
initializes the CUDA allocator before patch_dgx_spark_memory_config()
can set PYTORCH_CUDA_ALLOC_CONF on exactly the Spark hosts it targets
(reachable via vision.py importing ..kernels before ._utils). Verified
on the N1X: detects the machine with torch.cuda.is_initialized() still
False.
- _utils.py: the TrainingArguments __post_init__ wrapper now forwards
*args/**kwargs (robustness against future InitVar signatures).
Disproven on hardware (no change): the five "high" PS-5.1 claims --
String.TrimEnd('\', '/') with multiple char args binds fine to
params char[] (verified on PS 5.1.28000.1737, and the uninstaller's PATH
cleanup using exactly that code ran successfully this same day), and
[Text.Encoding] resolves via the System namespace prefix (the background
build dispatch using it has run in every install this week). The worker
"_sp possibly undefined" claim is false: `import subprocess as _sp` is at
worker.py line 25.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- install.sh: gate the new aarch64 bitsandbytes block on SKIP_TORCH=false --
with --no-torch/UNSLOTH_NO_TORCH (GGUF-only install) it would have pulled
torch back into the venv through bitsandbytes' dependencies.
- studio worker: in the new Spark OOM-guard section, decide
PYTORCH_CUDA_ALLOC_CONF (expandable_segments) BEFORE the guard's first CUDA
touch -- get_device_properties initializes the CUDA allocator, after which
the env var is ignored, and the later `import unsloth`
(patch_dgx_spark_memory_config) is too late for the worker process. Uses
the same CUDA-free nvidia-smi name sniff, append-don't-override, and
UNSLOTH_NO_EXPANDABLE_SEGMENTS opt-out as the library patch. Live-verified
on the N1X: env set while torch.cuda.is_initialized() is still False.
- uninstall.ps1: only run `fuser -k 8888/tcp` in a probed WSL distro when an
Unsloth install actually exists there (checked BEFORE the rm deletes the
marker) -- an unrelated listener on 8888 (e.g. Jupyter) in a clean distro
must survive a Windows-side uninstall. The Unsloth-specific pkills stay
unconditional.
- install.ps1 + uninstall.ps1: persist the chosen WSL distro to
%LOCALAPPDATA%\Unsloth\wsl-distro.txt at install; uninstall reads it
(before removing the directory) and prepends it to the cleanup candidates,
so a custom UNSLOTH_WSL_DISTRO install is cleaned without the env var
being set again at uninstall time.
- provision_llama_cuda.sh: honor UNSLOTH_LLAMA_PR (numeric-validated,
best-effort fetch of pull/N/head after clone) so a provisioned tree
matches a PR pin the way setup.sh does; and require only llama-server in
the main cmake build (mirroring setup.sh), building the helper targets
(llama-cli/quantize/mtmd-cli/gguf-split) best-effort afterwards -- an
older UNSLOTH_LLAMA_TAG pin lacking a newer helper target no longer fails
the whole provision.
Not changed: the "--tauri rejection doesn't restore the venv rollback"
comment is incorrect -- the rejection returns through Exit-InstallFailure,
which itself calls Restore-StudioVenvRollback.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Trim and tighten code comments and docstrings across the repository. Comment-only: every changed file verified code-identical to main via AST/token comparison.
install.ps1 (WoA WSL fallback):
- report failure (non-zero) + restore the rolled-aside venv when the WSL GPU
install fails (torch.cuda absent) or when WSL needs enabling+reboot, instead of
returning success — so -File/Tauri callers don't see a broken install as complete
- on WSL success, Complete-StudioVenvRollback so the previous-venv backup isn't orphaned
- refuse under --tauri with a clear "use the CLI installer" message (the desktop
launcher resolves a Windows-venv backend, which a WSL-only install can't provide)
- reset $LASTEXITCODE before each wsl.exe / python probe (a stale 0 could mark WSL
ready / torch OK if the native command fails to launch)
- torch-availability probe: --reinstall so an already-installed CPU torch in a
migrated venv isn't accepted as "satisfied" (would wrongly skip the WSL path)
- treat a null HKCU PATH as empty (fresh profile) so shim PATH update can't throw
- keep apt stderr visible inside WSL (only stdout -> /dev/null) for diagnosability
scripts/uninstall.ps1:
- scope WSL cleanup to /root (the fallback's install location); stop deleting
/home/*/.unsloth, which could erase an unrelated WSL user's own Unsloth/cache
studio/setup.sh:
- direct (non-install.ps1) WSL installs now provision CUDA llama.cpp themselves
instead of being left with no GGUF server: install.ps1 exports
UNSLOTH_WSL_LLAMA_DEFERRED=1, and the aarch64+NVIDIA provision block runs under
WSL only when that marker is absent
- mark a provisioner-built llama.cpp as Studio-owned in custom-STUDIO_HOME mode so
the next setup's _assert_studio_owned_or_absent doesn't abort
- glibc>=2.41 check: also match a future major>2 (e.g. 3.0)
studio/scripts/provision_llama_cuda.sh:
- install base tools (cmake/git/curl) in their own apt transaction before the
best-effort gcc-14/g++-14 (unavailable on Ubuntu 22.04 / Debian 12, where bundling
them aborted the whole transaction and left no build tools)
- back up an existing (e.g. CPU-only) llama.cpp before the destructive clone and
restore it on clone failure, so a failed clone doesn't leave the user with no server
- honor a pinned llama.cpp ref via UNSLOTH_LLAMA_TAG instead of always tracking main
unsloth/models/_utils.py:
- set PYTORCH_CUDA_ALLOC_CONF (expandable_segments) via a CUDA-free Spark detector
(nvidia-smi, not torch.cuda.get_device_name) so it takes effect before CUDA/the
caching allocator initialize — previously it was a silent no-op on auto-detected Spark
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Raise ruff line-length to 100 and extend the local pre-commit format pipeline (def-signature magic-comma normalization, short multi-line assert collapse, kwarg '=' spacing, blank-line-after-short-import removal, adjacent string-literal / f-string+plain merge, redundant-pass pruning). Every transform re-checks the file AST and is dropped if it would differ; the whole-repo reformat is verified AST-identical per file and idempotent.
Root cause (diagnosed live on an N1X WoA box, confirmed by on-screen checks):
the Windows shell's sandboxed icon-extraction broker cannot read a standalone
.ico stored under %LOCALAPPDATA% (it gets a redirected/virtualized view), so
the Desktop + Start Menu shortcuts render BLANK -- regardless of icon format
(BMP vs PNG frames), ACLs, icon cache, or shortcut-creation method, all of
which were ruled out. The IDENTICAL .ico renders correctly from a path under
the user profile. Fix: write unsloth.ico to %USERPROFILE%\.unsloth instead of
%LOCALAPPDATA%\Unsloth (shim/launcher stay in %LOCALAPPDATA%). uninstall.ps1
removes the icon at the new location. Also drops the speculative SHGetFileInfo
"image-list prime" block added while chasing the wrong (format/cache) theory.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>