Addresses review findings from parallel reviewers on PR #4720:
- install.sh: add _has_usable_nvidia_gpu() helper requiring nvidia-smi -L
to actually list a GPU before treating the host as NVIDIA. Fixes the
stale-nvidia-smi-on-PATH regression where AMD-only hosts fell into the
CUDA branch.
- install.sh: fix hipconfig awk blocks to propagate a non-zero exit code
when the output is not a recognisable version string, so the ||-chain
continues to dpkg-query / rpm instead of terminating early.
- install.sh: fail-closed on Radeon wheel fallback. When torch,
torchvision or torchaudio is missing from the Radeon repo for the
active Python tag, fall back to the standard ROCm index instead of
silently mixing Radeon wheels with PyPI defaults. Quote all wheel
arguments individually so wheel filenames cannot be word-split or
glob-expanded.
- install_llama_prebuilt.py: detect_host() now requires nvidia-smi -L to
list a GPU before setting has_physical_nvidia. Routes AMD ROCm hosts
with a broken leftover nvidia-smi to the ROCm path instead of
misclassifying them as NVIDIA.
- install_llama_prebuilt.py: scan upstream assets for any rocm-<version>
prebuilt instead of hard-coding rocm-7.2, so ROCm 6.x / 7.0 / 7.1 / 7.3+
users pick up a matching upstream prebuilt when one exists.
- install_llama_prebuilt.py: validate_server() adds --n-gpu-layers 1 for
linux-rocm and windows-hip hosts, so new HIP prebuilts are preflighted
on the GPU path instead of passing validation on CPU only.
- install_llama_prebuilt.py: restore the published windows-cpu fallback
for AMD Windows hosts without a HIP prebuilt so hash-approved bundles
are still preferred over the raw upstream CPU asset.
- install_python_stack.py: drop the /opt/rocm / hipcc gate in
_ensure_rocm_torch() and rely on _has_rocm_gpu(). Runtime-only ROCm
installs (package-managed minimal installs, Radeon software) that ship
amd-smi / rocminfo without hipcc can now repair a CPU-only venv via
"unsloth studio update". Adds an explicit IS_WINDOWS / IS_MACOS guard.
- studio/backend/utils/hardware/amd.py: honour HIP_VISIBLE_DEVICES /
ROCR_VISIBLE_DEVICES / CUDA_VISIBLE_DEVICES in
get_primary_gpu_utilization(). A process restricted to GPU 2 now
reports metrics for GPU 2 instead of physical GPU 0. Tighten the plain
bytes unit detection to an explicit allowlist.
- studio/backend/utils/hardware/hardware.py: route
get_backend_visible_gpu_info()'s backend_cuda_visible_devices field
through a helper that reads HIP_VISIBLE_DEVICES on ROCm. Drop the
unconditional "(rocm=False)" suffix in apply_gpu_ids() logs.
- install.sh: replace weak amd-smi list check (awk 'NR>1 && NF') with
strict pattern matching GPU data rows (/^GPU[[:space:]]*[:\[]/)
- All files: reject rocminfo gfx000 (CPU HSA agent) by requiring
gfx[1-9] instead of gfx[0-9] in the rocminfo GPU probe
- Fixes false positives on hosts with ROCm tools but no AMD GPU
Older amd-smi versions output "GPU[0] : Card series: ..." instead of
"GPU: 0". The regex now matches both "GPU: <digit>" and "GPU[<digit>"
formats to detect actual GPU data rows.
- _ensure_rocm_torch: only skip when HIP is already present, not for
CUDA builds (which are unusable on AMD-only hosts). Fixes the case
where a venv has a stale CUDA wheel and the repair step is skipped.
- Windows AMD warning: use GPU data row check (same as Linux fix) to
avoid false positives from amd-smi list header-only output.
- Fix _has_rocm_gpu() false positive: require "GPU: <number>" data rows
from amd-smi list, not just header containing "gpu"
- Apply same fix in detect_host() in install_llama_prebuilt.py
- Add runtime_payload_health_groups for linux-rocm and windows-hip so
partial/corrupt ROCm/HIP prebuilt installs are properly detected
- Add bitsandbytes install to Radeon fallback paths (was only in the
success path, skipped when repo.radeon.com was unreachable)
- Keep DEVICE/CHAT_ONLY as direct imports in __init__.py (matching main)
and only use __getattr__ for IS_ROCM
- Fix empty _tri_arg passed to uv pip install in Radeon path (causes
"Empty field is not allowed for PEP508" error)
- Fix Radeon fallback: use ROCm index instead of CPU-only when
repo.radeon.com is unreachable (TORCH_INDEX_URL already has ROCm)
- Use $TORCH_CONSTRAINT in fallback paths instead of hardcoded strings
- Fix _pick_radeon_wheel: relax suffix to match manylinux_2_28_x86_64
wheels (AMD Radeon repo does not use bare linux_x86_64 platform tag)
- Fix IS_ROCM export: use __getattr__ so callers always see the live
value after detect_hardware() runs
- Fix apply_gpu_ids: set HIP_VISIBLE_DEVICES and ROCR_VISIBLE_DEVICES
on ROCm so _get_parent_visible_gpu_spec picks up narrowed GPU set
- Fix _parse_memory_mb: distinguish GB (1000 MB) from GiB (1024 MiB)
- Add amd-smi version as a fallback in _detect_rocm_version
- Fix trailing whitespace and missing newline at EOF in install.sh
- Cap torchvision<0.26.0 and torchaudio<2.11.0 alongside torch<2.11.0 in
both install.sh and install_python_stack.py to prevent resolver from
selecting incompatible companion packages from ROCm wheel index
- Remove amdhip64.dll fallback in Windows ROCm detection (DLL presence
without hipinfo/amd-smi is not proof of GPU existence)
- Fix get_visible_gpu_count() to use _get_parent_visible_gpu_spec() which
respects HIP_VISIBLE_DEVICES/ROCR_VISIBLE_DEVICES on ROCm hosts
- hardware.py: check HIP_VISIBLE_DEVICES and ROCR_VISIBLE_DEVICES on ROCm
before falling back to CUDA_VISIBLE_DEVICES, so multi-GPU AMD setups with
HIP-specific env vars report the correct visible device set
- amd.py: add _parse_memory_mb() that reads "unit" from dict-shaped amd-smi
JSON (e.g. {"value": 192, "unit": "GiB"}) and converts to MB correctly;
fixes MI300X VRAM misreported as 0.19 GB instead of 192 GB
- install_python_stack.py: Windows AMD warning now validates actual GPU
presence via hipinfo/amd-smi output markers before printing
- install_llama_prebuilt.py: restore amdhip64.dll fallback for Windows HIP
detection after tool-based checks, so Windows HIP installs without CLI
tools on PATH are still detected
- hardware.py: fix IS_ROCM comment to accurately describe its role
- Windows ROCm detection: validate actual GPU presence via hipinfo/amd-smi
output markers instead of just checking tool existence on PATH
- _ensure_rocm_torch: validate nvidia-smi actually reports a GPU before
giving NVIDIA precedence (fixes AMD-only hosts with stale NVIDIA tools)
- amd.py _parse_numeric: handle dict-shaped metric objects from newer
amd-smi versions ({"value": 10, "unit": "W"}) and strip MiB/GiB units
- amd.py VRAM heuristic: raise threshold from 100k to 10M to correctly
handle MI300X (192 GB = 196608 MB) and other high-VRAM GPUs
- amd.py visible GPU: use AMD-reported GPU IDs instead of enumerate index
so non-dense sets like CUDA_VISIBLE_DEVICES=1,3 report correctly
- install.sh: add ROCm <6.0 minimum version guard (no PyTorch wheels
exist for older versions); fix rocm7.1* glob to not match rocm7.10+
- is_rdna: add gfx1033-1036 for RDNA2 mobile GPUs (RX 6600M etc.)
- worker.py: increase ROCm source build timeout from 600s to 1800s;
fix success log message for ROCm source builds
- Tests: update mocks for _has_usable_nvidia_gpu, add RDNA2 target asserts
- worker.py: Add HIP detection to causal-conv1d/mamba-ssm probe, check
for hipcc before ROCm source builds, improve status messages and error
reporting, add timeout and uv support for the source build fallback
- amd.py: New AMD GPU monitoring module via amd-smi metric --json,
mirroring nvidia.py structure (utilization, temperature, power, VRAM)
- hardware.py: Branch to amd.py when IS_ROCM is True for GPU utilization,
visible GPU queries, and physical GPU count
- install_python_stack.py: Detect AMD GPUs on Windows and warn that
ROCm-enabled PyTorch must be installed manually
- kernels/utils.py: Expand is_rdna() to cover RDNA2 (gfx1030-1032),
RDNA3 (gfx1102-1103), RDNA3.5 (gfx1150-1152) alongside existing entries
- tests: Add 32 new tests covering all changes (95/95 pass)
- Change amd-smi list detection from any-non-empty-output to requiring
"gpu" marker in output, matching the shell-side NR>1 check. Prevents
false positives from header-only amd-smi list output.
- Add nvidia-smi check at the top of _ensure_rocm_torch() so mixed
AMD+NVIDIA hosts preserve NVIDIA precedence (matching install.sh and
install_llama_prebuilt.py behavior).
- Apply the same amd-smi marker fix to install_llama_prebuilt.py
detect_host() for consistency.
- Add parts[1].isdigit() check in hipconfig version parsing to handle
versions like "6.3-HIP" where the minor component has non-numeric
suffix (strip "-" prefix before int() conversion)
- Use getattr() in torch probe subprocess to safely handle old or
custom torch builds that may lack torch.version.hip/cuda attributes
All 8 reviewers across 2 cycles independently flagged that ROCm
detection used toolkit/filesystem hints (hipcc, /opt/rocm, rocm-core)
as a proxy for GPU presence, which would misroute CPU-only or NVIDIA
hosts that happen to have ROCm tools installed.
Now all 3 detection points (install.sh, install_python_stack.py,
install_llama_prebuilt.py) probe for an actual AMD GPU before
entering the ROCm path:
- install.sh: check rocminfo for gfx* GPU names, or amd-smi list
for device rows, before version detection
- install_python_stack.py: new _has_rocm_gpu() function probes
rocminfo and amd-smi list before _ensure_rocm_torch() proceeds
- install_llama_prebuilt.py: detect_host() probes rocminfo/amd-smi
list instead of just checking tool existence or directory paths
Also:
- Shell test mock amd-smi now handles "list" subcommand
- Python tests updated to mock _has_rocm_gpu where needed
- Added test_no_gpu_with_rocm_tools_skips to verify the new guard
- Test index lookups now use sorted() to match production code
Address review findings from 8 independent reviewers:
- Wrap _ensure_rocm_torch() torch probe in try/except for
TimeoutExpired and OSError so a hung or broken torch import does not
crash the installer (8/8 reviewers flagged this)
- Add torch>=2.4,<2.11.0 version cap to the ROCm reinstall path to
prevent installing unsupported torch 2.11.0 from the rocm7.1 index
- Use with-statement for file reads in _detect_rocm_version() to avoid
resource leaks
- Handle ROCM_PATH="" correctly (use `or "/opt/rocm"` instead of
default parameter to avoid relative path resolution)
- Strengthen shell validation guard from rocm[0-9] to rocm[1-9] to
reject rocm0.x tags that would produce nonexistent PyTorch index URLs
- Switch shell version cap from blocklist to allowlist (rocm6.*|rocm7.0*
|rocm7.1* pass through, everything else caps to rocm7.1) so future
ROCm 10+ does not fall through to a nonexistent index
- Add sorted() to _ROCM_TORCH_INDEX lookup for defensive ordering
- Fix test_probe_timeout_handled: replace zero-assertion test with
proper assertions verifying reinstall proceeds after timeout
Add _detect_rocm_version() and _ensure_rocm_torch() to detect when a
Linux host has ROCm but the venv received CPU-only torch, and reinstall
with the correct ROCm wheels. Covers ROCm 6.0 through 7.1 with a
30-second timeout on the torch GPU probe subprocess.
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* refactor(studio): unify setup terminal output style and add verbose setup mode
* studio(windows): align setup.ps1 banner/steps with setup.sh (ANSI, verbose)
* studio(setup): revert nvcc path reordering to match main
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio(setup): restore fail-fast llama.cpp setup flow
* studio(banner): use IPv6 loopback URL when binding :: or ::1
* Fix IPv6 URL bracketing, try_quiet stderr, _step label clamp
- Bracket IPv6 display_host in external_url to produce clickable URLs
- Redirect try_quiet failure log to stderr instead of stdout
- Clamp _step label to column width to prevent negative padding
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add sandbox integration tests for PR #4494 UX fixes
Simulation harness (tests/simulate_pr4494.py) creates an isolated uv
venv, copies the real source files into it, and runs subprocess tests
for all three fixes with visual before/after demos and edge cases.
Standalone bash test (tests/test_try_quiet.sh) validates try_quiet
stderr redirect across 8 scenarios including broken-version contrast.
39 integration tests total (14 IPv6 + 15 try_quiet + 10 _step), all
existing 75 unit tests still pass.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Truncate step() labels in setup.sh to match PS1 and Python
The %-15s printf format pads short labels but does not truncate long
ones. Change to %-15.15s so labels wider than 15 chars are clipped,
matching the PowerShell .Substring(0,15) and Python label[:15] logic.
* Remove sandbox integration tests from PR
These test files are not part of the styling fix and should not
ship with this PR.
* Show error output on failure instead of suppressing it
- install_python_stack.py: restore _red for patch_package_file
warnings (was downgraded to _dim)
- setup.ps1: capture winget output and show on failure for CUDA,
Node, Python, and OpenSSL installs (was piped to Out-Null)
- setup.ps1: always show git pull failure warning, not just in
verbose mode
* Show winget error output for Git and CMake installs on failure
Same capture-and-print-on-failure pattern already used for
Node, Python, CUDA, and OpenSSL winget installs.
* fix: preserve stderr for _run_quiet error messages in setup.sh
The step() helper writes to stdout, but _run_quiet's error header
was originally sent to stderr (>&2). Without the redirect, callers
that separate stdout/stderr would miss the failure headline while
still seeing the log body on stderr. Add >&2 to both step calls
inside _run_quiet to match main's behavior.
* feat: add --verbose flag to setup and update commands
Wire UNSLOTH_VERBOSE=1 through _run_setup_script() so that
'unsloth studio update --verbose' (and the deprecated 'setup')
passes the flag to setup.sh / setup.ps1 / install_python_stack.py.
* fix(studio): honor verbose logging and keep llama.cpp failures non-blocking
* fix(studio): switch installer to 'studio update' and normalize Windows setup logs
* chore(studio): refine localhost tip and remove skip-base setup nois
* fix(studio): align Windows setup logs with Linux style and improve startup tips
* fix(studio): align Windows setup logs with Linux style
* refactor(windows-installer): align install/setup logs with Linux style and silence auto-launch output
* refactor(windows): align installer/setup output with Linux style and reduce default verbosity
* refactor(windows): match install.ps1 output style/colors to setup and quiet default logs
* fix(studio-banner): update personal-computer localhost tip
* fix(setup.sh): restore verbose llama.cpp build output while keeping default quiet mode
* fix(install.sh): align installer logging with setup style and restore POSIX-safe color output
* fix(install.sh): preserve installer reliability and launch visibility
Export verbose mode for child setup processes, harden install command handling under set -e, and keep first-run studio launch non-silent so users can always see URL and port fallback output.
* fix(windows installer): keep exit semantics and degrade status accurate
Use quiet command redirection that preserves native exit codes, keep startup output visible on first launch, and report limited install status when llama.cpp is unavailable.
* fix(setup.sh): improve log clarity and enforce GGUF degraded signaling
Restore clean default setup output, add verbose-only diagnostics, fail fast on Colab dependency install errors, and return non-zero when GGUF prerequisites or llama.cpp artifacts are unavailable.
* fix(installer): harden bash preflight and PowerShell GPU checks
Fail fast when bash is unavailable before invoking setup.sh, and replace remaining nvidia-smi pipeline checks with stream redirection patterns that preserve reliable native exit-code handling.
* fix(windows): keep verbose output visible while preserving exit codes
Ensure PowerShell wrapper helpers in install/update stream native command output to host without returning it as function output, so npm logs no longer corrupt exit-code checks in verbose mode.
* fix(windows): avoid sticky UNSLOTH_VERBOSE and gate studio update verbosity
* Fix degraded llama.cpp exit code, PS verbose stderr, banner URLs, npm verbose
- setup.sh: Do not exit non-zero when llama.cpp is unavailable; the footer
already reports the limitation, and install.sh runs under set -e so a
non-zero exit aborts the entire install including PATH/shortcuts/launch.
- setup.ps1: Remove $? check in Invoke-SetupCommand verbose path; PS 5.1
sets $? = $false when native commands write to stderr even with exit 0.
Merge stderr into stdout with 2>&1 and rely solely on $LASTEXITCODE.
- startup_banner.py: Show the actual bound address when Studio is bound to
a non-loopback interface instead of always showing 127.0.0.1/localhost.
- setup.sh: Use run_quiet_no_exit instead of run_quiet_no_exit_always for
npm install steps so --verbose correctly surfaces npm output.
* Fix install.ps1 verbose stderr, propagate UNSLOTH_VERBOSE, fix git clone verbose
- install.ps1: Apply same Invoke-InstallCommand fix as setup.ps1 -- merge
stderr into stdout with 2>&1 and drop the $? check that misclassifies
successful native commands on PS 5.1.
- install.ps1 + setup.ps1: Export UNSLOTH_VERBOSE=1 to the process env
when --verbose is passed so child processes like install_python_stack.py
also run in verbose mode.
- setup.sh: Use run_quiet_no_exit for git clone llama.cpp so --verbose
correctly surfaces clone diagnostics during source-build fallback.
* Surface prebuilt llama.cpp output in verbose mode, remove dead code, fix banner
- setup.sh: Use tee in verbose mode for prebuilt llama.cpp installer so
users can see download/validation progress while still capturing the log
for structured error reporting on failure.
- setup.ps1: Same fix for Windows -- use Tee-Object in verbose mode.
- setup.sh: Remove run_quiet_no_exit_always() which has no remaining callers.
- startup_banner.py: Avoid printing the same URL twice when Studio is
bound to a specific non-loopback address that matches the display host.
* Fix run_install_cmd exit code after failed if-statement
The previous pattern 'if "$@"; then return 0; fi; _rc=$?' always captured
$? = 0 because $? reflects the if-statement result, not the command's exit
code. Switch to '"$@" && return 0; _rc=$?' which preserves the actual
command exit code on failure. Applies to both verbose and quiet branches.
* Fix _run_quiet exit code, double uv install, missing --local flag
- setup.sh: Fix _run_quiet verbose path that always captured exit code 0
due to $? resetting after if-then-fi with no else. Switch to the same
'"$@" && return 0; exit_code=$?' pattern used in install.sh.
- setup.sh: Consolidate the two uv install branches (verbose + quiet)
into a single attempt with conditional output. Previously, when verbose
mode was on and the install failed, a second silent attempt was made.
- install.ps1: Pass --local flag to 'unsloth studio update' when
$StudioLocalInstall is true. Without this, studio.py's update() command
overwrites STUDIO_LOCAL_INSTALL to "0", which could cause issues if
setup.ps1 or install_python_stack.py later checks that variable.
* Revert SKIP_STUDIO_BASE change for --no-torch, restore install banners
- Revert SKIP_STUDIO_BASE from 0 to 1 for --no-torch. install.sh already
installs unsloth+unsloth-zoo and no-torch-runtime.txt before calling
setup.sh, so letting install_python_stack.py redo it was redundant and
slowed down --no-torch installs for no benefit.
- Restore the "Unsloth Studio installed!" success banner and "starting
Unsloth Studio..." launch message so users get clear install completion
feedback before the server starts.
* Make llama.cpp build failure a hard error with proper cleanup
- setup.sh: Restore exit 1 when _LLAMA_CPP_DEGRADED is true. GGUF
inference requires a working llama.cpp build, so this should be a
hard failure, not a silent degradation.
- install.sh: Catch setup.sh's non-zero exit with '|| _SETUP_EXIT=$?'
instead of letting set -e abort immediately. This ensures PATH setup,
symlinks, and shortcuts still get created so the user can fix the
build deps and retry with 'unsloth studio update'. After post-install
steps, propagate the failure with a clear error message.
* Revert install.ps1 to 'studio setup' to preserve SKIP_STUDIO_BASE
'studio update' pops SKIP_STUDIO_BASE from the environment, which
defeats the fast-path version check added in PR #4667. When called
from install.ps1 (which already installed packages), SKIP_STUDIO_BASE=1
must survive into setup.ps1 so it skips the redundant PyPI check and
package reinstallation. 'studio setup' does not modify env vars.
* Remove deprecation message from 'studio setup' command
install.ps1 uses 'studio setup' (not 'studio update') to preserve
SKIP_STUDIO_BASE. The deprecation message was confusing during first
install since the user never typed the command.
* Fix stale env vars, scope degraded exit, generic error message for PR #4651
- install.ps1: Always set STUDIO_LOCAL_INSTALL and clear STUDIO_LOCAL_REPO
when not using --local, to prevent stale values from a previous --local
run in the same PowerShell session. Fix log messages to say 'setup' not
'update' since we call 'studio setup'.
- setup.sh: Only exit non-zero for degraded llama.cpp when called from the
installer (SKIP_STUDIO_BASE=1). Direct 'unsloth studio update' keeps
degraded installs successful since Studio is still usable for non-GGUF
workflows and the footer already reports the limitation.
- install.sh: Make the setup failure error message generic instead of
GGUF-specific, so unrelated failures (npm, Python deps) do not show
misleading cmake/git recovery advice.
* Show captured output on failure in quiet mode for PR #4651
Both Invoke-InstallCommand (install.ps1) and Invoke-SetupCommand
(setup.ps1) now capture command output in quiet mode and display it
in red when the command fails. This matches the behavior of
run_install_cmd in install.sh where failure output is surfaced even
in quiet mode, making cross-platform error debugging consistent.
* Match degraded llama.cpp exit on Windows, fix --local recovery hint for PR #4651
- setup.ps1: Exit non-zero for degraded llama.cpp when called from
install.ps1 (SKIP_STUDIO_BASE=1), matching setup.sh behavior. Direct
'unsloth studio update' keeps degraded installs successful.
- install.sh: Show 'unsloth studio update --local' in the recovery
message when the install was run with --local, so users retry with
the correct flag instead of losing local checkout context.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Use --no-deps for ALL packages (unsloth, unsloth-zoo, and runtime deps)
since the current PyPI metadata for unsloth still declares torch as a
hard dependency. Runtime deps (typer, pydantic, safetensors,
transformers, etc.) are installed from no-torch-runtime.txt with
--no-deps to prevent transitive torch resolution from accelerate, peft,
trl, and sentence-transformers.
no-torch-runtime.txt now includes unsloth's own direct deps (typer,
pydantic, pyyaml, nest-asyncio) since --no-deps skips those too.
install.sh installs no-torch-runtime.txt directly (via helper function
_find_no_torch_runtime). install.ps1 does the same via
Find-NoTorchRuntimeFile. SKIP_STUDIO_BASE stays at 1 to avoid setup.sh
fast-path issues.
install_python_stack.py NO_TORCH branch does the same for unsloth
studio update, using package_name instead of hardcoded "unsloth".
The [huggingfacenotorch] extras only exist in pyproject.toml but are
NOT published on PyPI, so uv pip install "unsloth[huggingfacenotorch]"
fails on fresh installs from the registry.
Fix: add studio/backend/requirements/no-torch-runtime.txt with the
runtime deps (safetensors, transformers, datasets, accelerate, etc.)
that mirror [huggingfacenotorch] from pyproject.toml. In no-torch mode:
1. install.sh/ps1 install unsloth + unsloth-zoo with --no-deps
2. SKIP_STUDIO_BASE=0 so install_python_stack.py's NO_TORCH branch runs
3. install_python_stack.py installs no-torch-runtime.txt
* refactor(studio): unify setup terminal output style and add verbose setup mode
* studio(windows): align setup.ps1 banner/steps with setup.sh (ANSI, verbose)
* studio(setup): revert nvcc path reordering to match main
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio(setup): restore fail-fast llama.cpp setup flow
* studio(banner): use IPv6 loopback URL when binding :: or ::1
* Fix IPv6 URL bracketing, try_quiet stderr, _step label clamp
- Bracket IPv6 display_host in external_url to produce clickable URLs
- Redirect try_quiet failure log to stderr instead of stdout
- Clamp _step label to column width to prevent negative padding
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add sandbox integration tests for PR #4494 UX fixes
Simulation harness (tests/simulate_pr4494.py) creates an isolated uv
venv, copies the real source files into it, and runs subprocess tests
for all three fixes with visual before/after demos and edge cases.
Standalone bash test (tests/test_try_quiet.sh) validates try_quiet
stderr redirect across 8 scenarios including broken-version contrast.
39 integration tests total (14 IPv6 + 15 try_quiet + 10 _step), all
existing 75 unit tests still pass.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Truncate step() labels in setup.sh to match PS1 and Python
The %-15s printf format pads short labels but does not truncate long
ones. Change to %-15.15s so labels wider than 15 chars are clipped,
matching the PowerShell .Substring(0,15) and Python label[:15] logic.
* Remove sandbox integration tests from PR
These test files are not part of the styling fix and should not
ship with this PR.
* Show error output on failure instead of suppressing it
- install_python_stack.py: restore _red for patch_package_file
warnings (was downgraded to _dim)
- setup.ps1: capture winget output and show on failure for CUDA,
Node, Python, and OpenSSL installs (was piped to Out-Null)
- setup.ps1: always show git pull failure warning, not just in
verbose mode
* Show winget error output for Git and CMake installs on failure
Same capture-and-print-on-failure pattern already used for
Node, Python, CUDA, and OpenSSL winget installs.
* fix: preserve stderr for _run_quiet error messages in setup.sh
The step() helper writes to stdout, but _run_quiet's error header
was originally sent to stderr (>&2). Without the redirect, callers
that separate stdout/stderr would miss the failure headline while
still seeing the log body on stderr. Add >&2 to both step calls
inside _run_quiet to match main's behavior.
* feat: add --verbose flag to setup and update commands
Wire UNSLOTH_VERBOSE=1 through _run_setup_script() so that
'unsloth studio update --verbose' (and the deprecated 'setup')
passes the flag to setup.sh / setup.ps1 / install_python_stack.py.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
The previous --no-deps approach skipped ALL dependencies, not just
torch. This left safetensors, transformers, datasets, accelerate, etc.
missing, causing PackageNotFoundError at runtime.
Fix: in no-torch mode, install unsloth[huggingfacenotorch] (which pulls
all runtime deps except torch), then install unsloth-zoo with --no-deps
(since zoo's published metadata still declares torch as a hard dep).
This gives a working no-torch environment with all non-torch packages.
Applied to all three installer files: install.sh, install.ps1, and
studio/install_python_stack.py.
* fix: install.sh Mac Intel compatibility + Studio no-torch support (#4621)
On Intel Macs (x86_64), PyTorch has no wheels for torch >= 2.3, so the
installer crashes. Even when torch is absent, Studio crashes on startup
because two files have bare top-level torch imports.
Studio's GGUF inference (llama.cpp) does not need PyTorch. Training and
HF-inference already isolate torch to subprocesses. Only 2 files in the
server startup chain had top-level torch imports preventing startup.
Changes:
- install.sh: detect architecture, default to Python 3.12 on Intel Mac,
skip torch install, add Python 3.13.8 guard for arm64, pass
UNSLOTH_NO_TORCH env var to setup.sh
- data_collators.py: remove unused `import torch` (no torch.* refs)
- chat_templates.py: lazy-import IterableDataset into function bodies
- install_python_stack.py: add IS_MACOS/NO_TORCH constants, skip
torch-dependent packages, skip overrides.txt, skip triton on macOS
No existing working flow changes. Linux/WSL and macOS arm64 behavior is
identical.
* tests: add test suite for Mac Intel compat + no-torch mode
Shell tests (test_mac_intel_compat.sh):
- version_ge edge cases (9 tests)
- Architecture detection for Darwin x86_64/arm64, Linux x86_64/aarch64
- get_torch_index_url returns cpu on simulated Darwin
- UNSLOTH_NO_TORCH propagation to both setup.sh branches
Python unit tests (test_no_torch_filtering.py):
- _filter_requirements with NO_TORCH_SKIP_PACKAGES
- NO_TORCH env var parsing (true/1/TRUE/false/0/unset)
- IS_MACOS constant check
- Overrides skip and triton macOS skip guards
Python import tests (test_studio_import_no_torch.py):
- data_collators.py loads in isolated no-torch venv
- chat_templates.py has no top-level torch imports
- Negative control confirms import torch fails without torch
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* tests: add E2E sandbox tests for Mac Intel no-torch mode
Replace static/synthetic test stubs with real sandbox tests:
- Shell: E2E uv venv creation at Python 3.12, mock uv shim to verify
torch install is skipped when MAC_INTEL=true, dynamic env propagation
test for UNSLOTH_NO_TORCH in both local and non-local install paths
- Python filtering: test real extras.txt and extras-no-deps.txt with
NO_TORCH_SKIP_PACKAGES, subprocess mock of install_python_stack() for
5 platform configs (NO_TORCH+macOS, Windows+NO_TORCH, normal Linux,
Windows-only, macOS-only), VCS URL and env marker edge cases
- Python imports: parametrized Python 3.12+3.13 venv fixture, dataclass
instantiation for all 3 collator classes, chat_templates.py exec with
stubs, negative controls proving import torch and torchao install fail
in no-torch venvs
91 total tests, all passing.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: address reviewer findings for Intel Mac no-torch mode
P1 fixes:
- Auto-infer NO_TORCH in install_python_stack.py via platform.machine()
so `unsloth studio update` preserves GGUF-only mode without needing
the UNSLOTH_NO_TORCH env var (6/10 reviewers)
- Add openai-whisper and transformers-cfg to NO_TORCH_SKIP_PACKAGES
since both have unconditional torch dependencies (4/10 reviewers)
- Skip unsloth-zoo on Intel Mac --local installs (depends on torch)
in both migrated and fresh install paths (1/10)
- Recreate stale 3.13 venvs as 3.12 on Intel Mac re-runs (1/10)
- Detect Apple Silicon under Rosetta via sysctl hw.optional.arm64
and warn user to use native arm64 terminal (1/10)
P2 fixes:
- Wire new test files into tests/run_all.sh (4/10 reviewers)
- Add update-path tests (skip_base=False) for Intel Mac
- Add _infer_no_torch tests for platform auto-detection
P3 fixes:
- Fix macOS progress bar total (triton step skipped but was counted)
- Fix temp file leak when Windows + NO_TORCH filters stack
All tests pass: 30 shell, 66 Python (96 total).
* feat: add --python override flag to install.sh
Lets users force a specific Python version, e.g. ./install.sh --python 3.12.
Addresses M2 Mac users whose systems resolve to a problematic 3.13.x patch.
When --python is set, the Intel Mac stale-venv guard and 3.13.8 auto-downgrade
are skipped so the user's choice is respected.
* tests: add comprehensive E2E sandbox tests for no-torch mode
Add test_e2e_no_torch_sandbox.py with 7 test groups (43 tests total)
covering the full no-torch import chain, edge cases, and install logic:
- Group 1: BEFORE vs AFTER import chain comparison (proves the bug
existed and the fix works by synthetically prepending top-level torch
imports)
- Group 2: Dataclass instantiation without torch
- Group 3: Edge cases with broken/fake torch modules on sys.path
- Group 4: Hardware detection fallback to CPU without torch
- Group 5: install.sh flag parsing, version resolution, arch detection
- Group 6: install_python_stack.py NO_TORCH filtering
- Group 7: Live server startup without torch (marked @server, skipped
when studio venv is unavailable)
All 43 tests pass on both Python 3.12 and 3.13 isolated venvs.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* feat: add --no-torch flag to install.sh/ps1, fix lazy import bug in dataset formatting
- Fix chat_templates.py: narrow torch IterableDataset import into inner
try/except ImportError so dataset.map() works without torch installed
- Fix format_conversion.py: same lazy import fix for convert_chatml_to_alpaca
and convert_alpaca_to_chatml
- Add --no-torch flag to install.sh with unified SKIP_TORCH variable
(driven by --no-torch flag OR MAC_INTEL auto-detection)
- Add --no-torch flag to install.ps1 with $SkipTorch variable
- Print CPU hint when no GPU detected and --no-torch not set
- Replace MAC_INTEL guards with SKIP_TORCH in torch install sections
- Update shell tests (40 pass) and Python tests (90 pass)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: address reviewer findings for --no-torch installer paths
- Fix migrated-env branch in install.sh and install.ps1: check
SKIP_TORCH first, then branch on STUDIO_LOCAL_INSTALL. Previously
SKIP_TORCH+non-local fell into else and installed unsloth-zoo (which
depends on torch), defeating --no-torch mode.
- Fix $env:UNSLOTH_NO_TORCH leak in install.ps1: always set to "true"
or "false" instead of only setting on the true branch. Prevents stale
no-torch state from leaking across runs in the same PS session.
- Fix install_python_stack.py update path: add NO_TORCH guard around
base.txt install so unsloth studio update does not reinstall
unsloth-zoo (which depends on torch) in no-torch mode.
* fix: install unsloth + unsloth-zoo with --no-deps in no-torch mode
Instead of skipping unsloth-zoo entirely (which breaks unsloth's
dependency on it), install both packages with --no-deps so they are
present but torch is not pulled in transitively. Applied consistently
across all no-torch paths: migrated-env, fresh-local, fresh-non-local
in install.sh, install.ps1, and install_python_stack.py.
* chore: temporarily remove test files (will be added in a follow-up)
* refactor: deduplicate SKIP_TORCH conditional branches in installers
Collapse if/else blocks that differ only by --no-deps into a single
branch with a conditional flag variable. Applied to migrated-env and
fresh-local paths in install.sh, install.ps1, and install_python_stack.py.
* fix: apply --no-deps to fresh non-local --no-torch install path
The non-local else branch was missing $_no_deps_arg/$noDepsArg, so
uv pip install unsloth would resolve torch from PyPI metadata (the
published unsloth package still declares torch as a hard dep). Now
--no-deps is applied consistently to all SKIP_TORCH code paths.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Fix Colab huggingface-hub conflict, ensurepip fallback, bump to 2026.3.14
- colab.py / setup.sh: relax == pins to >= when installing studio.txt
on Colab so huggingface-hub does not clobber Colab's bundled version
(breaks transformers is_offline_mode import)
- install_python_stack.py: when uv is unavailable and pip is missing
(uv-created venvs), bootstrap via ensurepip before attempting upgrade
- Bump version to 2026.3.14
- Bump installer min version pins to 2026.3.14
* [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>
* refactor: consolidate dual venvs into single ~/.unsloth/studio/unsloth_studio
* refactor: separate install.sh (first-time) from setup.sh (smart update with PyPI version check)
* fix: install.sh calls setup.sh directly, keep both setup and update CLI commands
* fix: use importlib.resources.files() directly without _path attribute
* fix: bootstrap uv before pip upgrade to handle uv venvs without pip
* fix: frontend 404 when launched via CLI, add global symlink to ~/.local/bin
* feat: add --local flag to install.sh and unsloth studio update for branch testing
* fix: resolve repo root from script location for --local installs
* feat: add --package flag to install.sh for testing with custom package names
* feat: add --package flag to unsloth studio update
* fix: always nuke venv in install.sh for clean installs
* revert: remove Windows changes, will handle in separate PR
* fix: error when --package is passed without an argument
* revert: restore Windows scripts to current main
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: always explicitly set STUDIO_LOCAL_INSTALL and STUDIO_PACKAGE_NAME env vars
* fix: pass explicit STUDIO_LOCAL_REPO env var for --local installs
* fix: align banner box for Setup vs Update labels
* deprecate: hide 'unsloth studio setup' command, point users to update/install.sh
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: check stdout not stdin for auto-launch detection (curl pipe fix)
* fix: update install URL to unsloth.ai/install.sh
* fix: update install.sh usage comments to unsloth.ai/install.sh
* fix: use --upgrade-package for base deps to preserve existing torch/CUDA installs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: --local install now also installs unsloth-zoo via base.txt before editable overlay
* fix: don't skip base packages for --local installs (editable needs unsloth-zoo)
* refactor: move --local full dep install to install.sh, keep SKIP_STUDIO_BASE for all paths
* feat: add migration support for old .venv and CWD-based installs in setup.sh
* Revert "feat: add migration support for old .venv and CWD-based installs in setup.sh"
This reverts commit 301291d002.
* feat: migrate old .venv layout in install.sh instead of always nuking
* feat: validate old .venv with torch CUDA test before migration, recovery message on launch failure
* fix: try CUDA then fall back to CPU for migration validation
* fix: upgrade unsloth/unsloth-zoo with --reinstall-package on migration to preserve torch
* remove: delete unused unsloth ui command (use unsloth studio instead)
* Fix Windows venv path mismatch between install.ps1, setup.ps1, and studio.py
install.ps1 was creating the venv CWD-relative ($VenvName = "unsloth_studio"),
setup.ps1 was using an absolute path to ".unsloth\studio\.venv", and studio.py
looks for ".unsloth\studio\unsloth_studio". All three paths were different, so
the Windows installer would never produce a working Studio setup.
install.ps1:
- Use absolute $StudioHome + $VenvDir matching the Linux install.sh layout
- Add 3-way migration: old .venv at STUDIO_HOME, CWD-relative ~/unsloth_studio
from the previous install.ps1, or fresh creation with torch validation
- For migrated envs, upgrade unsloth while preserving existing torch/CUDA wheels
- Set SKIP_STUDIO_BASE=1 before calling setup.ps1 (matches install.sh behavior)
- Fix launch instructions to use the absolute venv path
setup.ps1:
- Change $VenvDir from ".unsloth\studio\.venv" to ".unsloth\studio\unsloth_studio"
- Add SKIP_STUDIO_BASE guard: error out if venv is missing when called from
install.ps1 (which should have already created it)
- Differentiate "Setup" vs "Update" in banners based on SKIP_STUDIO_BASE
* setup.ps1: unconditionally error if venv missing, matching setup.sh
setup.sh always errors out if the venv does not exist (line 224-228),
telling the user to run install.sh first. setup.ps1 was conditionally
creating a bare venv with python -m venv when SKIP_STUDIO_BASE was not
set, which would produce an empty venv with no torch or unsloth. Now
setup.ps1 matches setup.sh: always error, always point to install.ps1.
* Fix --torch-backend=auto CPU solver dead-end on Linux, macOS, and Windows
On CPU-only machines, `uv pip install unsloth --torch-backend=auto`
falls back to unsloth==2024.8 because the CPU solver cannot satisfy
newer unsloth's dependencies. install.ps1 already solved this with a
two-step approach; this applies the same fix to install.sh and
install_python_stack.py.
install.sh: add get_torch_index_url() that detects GPU via nvidia-smi
and maps CUDA versions to PyTorch index URLs (matching install.ps1's
Get-TorchIndexUrl). Fresh installs now install torch first via explicit
--index-url, then install unsloth with --upgrade-package to preserve
the pre-installed torch. All 5 --torch-backend=auto removed from
primary paths.
install.ps1: add fallback else-branch when TorchIndexUrl is empty,
using --torch-backend=auto as last resort (matching install.sh).
install_python_stack.py: remove unconditional --torch-backend=auto
from _build_uv_cmd. Torch is pre-installed by install.sh/setup.ps1
by the time this runs. Callers that need it can set UV_TORCH_BACKEND.
Both install.sh and install.ps1 now share the same three-branch logic:
migrated env (upgrade-package only), normal (torch-first + index-url),
and fallback (--torch-backend=auto if URL detection fails).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Use --reinstall-package for migrated envs on both Linux and Windows
For migrated environments (moved from legacy venv location),
--reinstall-package is better than --upgrade-package because it forces
a clean reinstall even if the same version is already installed. This
ensures proper .dist-info and .pyc state in the new venv location.
--upgrade-package remains correct for the fresh install path where
torch is already installed and we just want to add unsloth without
re-resolving torch.
* Address review findings: portability, parity, and stale comments
- Replace grep -oP (GNU Perl regex) with POSIX sed in
get_torch_index_url() so the script works on BSD grep (macOS is
already guarded by the Darwin early-return, but Alpine/BusyBox
would silently get the wrong CUDA tag)
- Add LC_ALL=C before nvidia-smi invocation to prevent locale-dependent
output parsing issues
- Add warning on stderr when nvidia-smi output is unparseable, matching
install.ps1's [WARN] message
- Add explicit unsloth-zoo positional arg to install.ps1 migrated path,
matching install.sh (--reinstall-package alone won't install it if it
was never present in the migrated env)
- Fix stale comment in install_python_stack.py line 392 that still
claimed --torch-backend=auto is added by _build_uv_cmd
- Add sed to test tools directory (function now uses sed instead of grep)
* Add --index-url to migrated env path to prevent CPU torch resolution
The migrated path runs uv pip install with --reinstall-package for
unsloth/unsloth-zoo. While uv should keep existing torch as satisfied,
the resolver could still re-resolve torch as a transitive dependency.
Without --index-url pointing at the correct CUDA wheel index, the
resolver would fall back to plain PyPI and potentially pull CPU-only
torch. Adding --index-url $TORCH_INDEX_URL ensures CUDA wheels are
available if the resolver needs them.
Applied to both install.sh and install.ps1.
* Revert --index-url on migrated env path
The original install.ps1 on main already handles the migrated path
without --index-url and it works correctly. --reinstall-package only
forces reinstall of the named packages while uv keeps existing torch
as satisfied. No need for the extra flag.
* Fix unsloth studio update --local not installing local checkout
studio.py sets STUDIO_LOCAL_REPO when --local is passed, but
install_python_stack.py never read it. The update path always
installed from PyPI regardless of the --local flag.
Add a local_repo branch that first updates deps from base.txt
(with --upgrade-package to preserve torch), then overlays the
local checkout as an editable install with --no-deps.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* fix: prevent UnicodeEncodeError on Windows CP1252 consoles in studio setup
On Windows, `unsloth studio setup` crashes with a UnicodeEncodeError
when install_python_stack.py tries to print Unicode status glyphs
(✅, ❌, ⚠️) to a console that uses a legacy code page like CP1252.
Add a _safe_print() helper that catches UnicodeEncodeError and
gracefully degrades emoji to ASCII equivalents ([OK], [FAIL], [!]).
Replace all print() calls that emit Unicode glyphs with _safe_print().
Fixes#4509
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Replace Unicode dashes with ASCII in install_python_stack.py
Box-drawing (U+2500) and em dash (U+2014) chars in section dividers
and comments are themselves not representable on CP1252 -- replace
with plain ASCII dashes for consistency with the fix.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Allow Windows setup to complete without NVIDIA GPU
setup.ps1 previously hard-exited if nvidia-smi was not found, blocking
setup entirely on CPU-only or non-NVIDIA machines. The backend already
supports CPU and MLX (Apple Silicon) in chat-only GGUF mode, and the
Linux/Mac setup.sh handles missing GPUs gracefully.
Changes:
- Convert the GPU check from a hard exit to a warning
- Guard CUDA toolkit installation behind $HasNvidiaSmi
- Install CPU-only PyTorch when no GPU is detected
- Build llama.cpp without CUDA flags when no GPU is present
- Update doc comment to reflect CPU support
* Cache frontend build across setup runs
Skip the frontend npm install + build if frontend/dist already exists.
Previously setup.ps1 nuked node_modules and package-lock.json on every
run, and both scripts always rebuilt even when dist/ was already present.
On a git clone editable install, the first setup run still builds the
frontend as before. Subsequent runs skip it, saving several minutes.
To force a rebuild, delete frontend/dist and re-run setup.
* Show pip progress for PyTorch download on Windows
The torch CUDA wheel is ~2.8 GB and the CPU wheel is ~300 MB. With
| Out-Null suppressing all output, the install appeared completely
frozen with no feedback. Remove | Out-Null for the torch install
lines so pip's download progress bar is visible. Add a size hint
so users know the download is expected to take a while.
Also moves the Triton success message inside the GPU branch so it
only prints when Triton was actually installed.
* Guard CUDA env re-sanitization behind GPU check in llama.cpp build
The CUDA_PATH re-sanitization block (lines 1020-1033) references
$CudaToolkitRoot which is only set when $HasNvidiaSmi is true and
the CUDA Toolkit section runs. On CPU-only machines, $CudaToolkitRoot
is null, causing Split-Path to throw:
Split-Path : Cannot bind argument to parameter 'Path' because it is null.
Wrap the entire block in `if ($HasNvidiaSmi -and $CudaToolkitRoot)`.
* Rebuild frontend when source files are newer than dist/
Instead of only checking if dist/ exists, compare source file timestamps
against the dist/ directory. If any file in frontend/src/ is newer than
dist/, trigger a rebuild. This handles the case where a developer pulls
new frontend changes and re-runs setup -- stale assets get rebuilt
automatically.
* Fix cmake not found on Windows after winget install
Two issues fixed:
1. After winget installs cmake, Refresh-Environment may not pick up the
new PATH entry (MSI PATH changes sometimes need a new shell). Added a
fallback that probes cmake's default install locations (Program Files,
LocalAppData) and adds the directory to PATH explicitly if found.
2. If cmake is still unavailable when the llama.cpp build starts (e.g.
winget failed silently or PATH was not updated), the build now skips
gracefully with a [SKIP] warning instead of crashing with
"cmake : The term 'cmake' is not recognized".
* Fix frontend rebuild detection and decouple oxc-validator install
Address review feedback:
- Check entire frontend/ directory for changes, not just src/.
The build also depends on package.json, vite.config.ts,
tailwind.config.ts, public/, and other config files. A change
to any of these now triggers a rebuild.
- Move oxc-validator npm install outside the frontend build gate
in setup.sh so it always runs on setup, matching setup.ps1
which already had it outside the gate.
* Show cmake errors on failure and retry CUDA VS integration with elevation
Two fixes for issue #4405 (Windows setup fails at cmake configure):
1. cmake configure: capture output and display it on failure instead of
piping to Out-Null. When the error mentions "No CUDA toolset found",
print a hint about the CUDA VS integration files.
2. CUDA VS integration copy: when the direct Copy-Item fails (needs
admin access to write to Program Files), retry with Start-Process
-Verb RunAs to prompt for elevation. This is the root cause of the
"No CUDA toolset found" cmake failure -- the .targets files that let
MSBuild compile .cu files are missing from the VS BuildCustomizations
directory.
* Address reviewer feedback: cmake PATH persistence, stale cache, torch error check
1. Persist cmake PATH to user registry so Refresh-Environment cannot
drop it later in the same setup run. Previously the process-only
PATH addition at phase 1 could vanish when Refresh-Environment
rebuilt PATH from registry during phase 2/3 installs.
2. Clean stale CMake cache before configure. If a previous run built
with CUDA and the user reruns without a GPU (or vice versa), the
cached GGML_CUDA value would persist. Now the build dir is removed
before configure.
3. Explicitly set -DGGML_CUDA=OFF for CPU-only builds instead of just
omitting CUDA flags. This prevents cmake from auto-detecting a
partial CUDA installation.
4. Fix CUDA cmake flag indentation -- was misaligned from the original
PR, now consistently indented inside the if/else block.
5. Fail hard if pip install torch returns a non-zero exit code instead
of silently continuing with a broken environment.
* Remove extra CUDA cmake flags to align Windows with Linux build
Drop GGML_CUDA_FA_ALL_QUANTS, GGML_CUDA_F16, GGML_CUDA_GRAPHS,
GGML_CUDA_FORCE_CUBLAS, and GGML_CUDA_PEER_MAX_BATCH_SIZE flags.
The Linux build in setup.sh only sets GGML_CUDA=ON and lets llama.cpp
use its defaults for everything else. Keep Windows consistent.
* Address reviewer round 2: GPU probe fallback, Triton check, stale binary rebuild
1. GPU detection: fallback to default nvidia-smi install locations
(Program Files\NVIDIA Corporation\NVSMI, System32) when nvidia-smi
is not on PATH. Prevents silent CPU-only provisioning on machines
that have a GPU but a broken PATH.
2. Triton: check $LASTEXITCODE after pip install and print [WARN]
on failure instead of unconditional [OK].
3. Stale llama-server: check CMakeCache.txt for GGML_CUDA setting
and rebuild if the existing binary does not match the current GPU
mode (e.g. CUDA binary on a now-CPU-only rerun, or vice versa).
* Fix frontend rebuild detection and npm dependency issues
Addresses reviewer feedback on the frontend caching logic:
1. setup.sh: Fix broken find command that caused exit under pipefail.
The piped `find | xargs find -newer` had paths after the expression
which GNU find rejects. Replaced with a simpler `find -maxdepth 1
-type f -newer dist/` that checks ALL top-level files (catches
index.html, bun.lock, etc. that the extension allowlist missed).
2. setup.sh: Guard oxc-validator npm install behind `command -v npm`
check. When the frontend build is skipped (dist/ is cached), Node
bootstrap is also skipped, so npm may not be available.
3. setup.ps1: Replace Get-ChildItem -Include with explicit path
probing for src/ and public/. PowerShell's -Include without a
trailing wildcard silently returns nothing, so src/public changes
were never detected. Also check ALL top-level files instead of
just .json/.ts/.js/.mjs extensions.
* Fix studio setup: venv isolation, centralized .venv_t5, uv targeting
- All platforms (including Colab) now create ~/.unsloth/studio/.venv
with --without-pip fallback for broken ensurepip environments
- Add --python sys.executable to uv pip install in install_python_stack.py
so uv targets the correct venv instead of system Python
- Centralize .venv_t5 bootstrap in transformers_version.py with proper
validation (checks required packages exist, not just non-empty dir)
- Replace ~150 lines of duplicated install code across 3 worker files
with calls to the shared _ensure_venv_t5_exists() helper
- Use uv-if-present with pip fallback; do not install uv at runtime
- Add site.addsitedir() shim in colab.py so notebook cells can import
studio packages from the venv without system-Python double-install
- Update .venv_t5 packages: huggingface_hub 1.3.0->1.7.1, add hf_xet
- Bump transformers pin 4.57.1->4.57.6 in requirements + constraints
- Add Fast-Install helper to setup.ps1 with uv+pip fallback
- Keep Colab-specific completion banner in setup.sh
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix nvidia-smi PATH persistence and cmake requirement for CPU-only
1. Store nvidia-smi as an absolute path ($NvidiaSmiExe) on first
detection. All later calls (Get-CudaComputeCapability,
Get-PytorchCudaTag, CUDA toolkit detection) use this absolute
path instead of relying on PATH. This survives Refresh-Environment
which rebuilds PATH from the registry and drops process-only
additions.
2. Make cmake fatal for CPU-only installs. CPU-only machines depend
entirely on llama-server for GGUF chat mode, so reporting "Setup
Complete!" without it is misleading. GPU machines can still skip
the llama-server build since they have other inference paths.
* Fix broken frontend freshness detection in setup scripts
- setup.sh: Replace broken `find | xargs find -newer` pipeline with
single `find ... -newer` call. The old pipeline produced "paths must
precede expression" errors (silently suppressed by 2>/dev/null),
causing top-level config changes to never trigger a rebuild.
- setup.sh: Add `command -v npm` guard to oxc-validator block so it
does not fail when Node was not installed (build-skip path).
- setup.ps1: Replace `Get-ChildItem -Include` (unreliable without
-Recurse on PS 5.1) with explicit directory paths for src/ and
public/ scanning.
- Both: Add *.html to tracked file patterns so index.html (Vite
entry point) changes trigger a rebuild.
- Both: Use -print -quit instead of piping to head -1 for efficiency.
* Fix bugs found during review of PRs #4404, #4400, #4399
- setup.sh: Add || true guard to find command that checks frontend/src
and frontend/public dirs, preventing script abort under set -euo
pipefail when either directory is missing
- colab.py: Use sys.path.insert(0, ...) instead of site.addsitedir()
so Studio venv packages take priority over system copies. Add warning
when venv is missing instead of silently failing.
- transformers_version.py: _venv_t5_is_valid() now checks installed
package versions via .dist-info metadata, not just directory presence.
Prevents false positives from stale or wrong-version packages.
- transformers_version.py: _install_to_venv_t5() now passes --upgrade
so pip replaces existing stale packages in the target directory.
- setup.ps1: CPU-only PyTorch install uses --index-url for cpu wheel
and all install commands use Fast-Install (uv with pip fallback).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix _venv_t5_is_valid dist-info loop exiting after first directory
Remove premature break that caused the loop over .dist-info directories
to exit after the first match even if it had no METADATA file. Now
continues iterating until a valid METADATA is found or all dirs are
exhausted.
* Capture error output on failure instead of discarding with Out-Null
setup.ps1: 6 locations changed from `| Out-Null` to `| Out-String` with
output shown on failure -- PyTorch GPU/CPU install, Triton install,
venv_t5 package loop, cmake llama-server and llama-quantize builds.
transformers_version.py: clean stale .venv_t5 directory before reinstall
when validation detects missing or version-mismatched packages.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix ModuleNotFoundError when CLI imports studio.backend.core
The backend uses bare "from utils.*" imports everywhere, relying on
backend/ being on sys.path. Workers and routes add it at startup, but
the CLI imports studio.backend.core as a package -- backend/ was never
added. Add sys.path setup at the top of core/__init__.py so lazy
imports resolve correctly regardless of entry point.
Fixes: unsloth inference unsloth/Qwen3-8B "who are you" crashing with
"No module named 'utils'"
* Fix frontend freshness check to detect all top-level file changes
The extension allowlist (*.json, *.ts, *.js, *.mjs, *.html) missed
files like bun.lock, so lockfile-only dependency changes could skip
the frontend rebuild. Check all top-level files instead.
* Add tiktoken to .venv_t5 for Qwen-family tokenizers
Qwen models use tiktoken-based tokenizers which fail when routed through
the transformers 5.x overlay without tiktoken installed. Add it to the
setup scripts (with deps for Windows) and runtime fallback list.
Integrates PR #4418.
* Fix tiktoken crash in _venv_t5_is_valid and stray brace in setup.ps1
_venv_t5_is_valid() crashed with ValueError on unpinned packages like
"tiktoken" (no ==version). Handle by splitting safely and skipping
version check for unpinned packages (existence check only).
Also remove stray closing brace in setup.ps1 tiktoken install block.
---------
Co-authored-by: Daniel Han <danielhanchen@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Removing .precommit config
* edited colab comments
* studio: update Unsloth_Studio_Colab.ipynb
* studio: update Unsloth_Studio_Colab.ipynb
* studio: add Colab T4 GPU metadata to force T4 instance
* style: update colab popup to black/white theme with gem icon and play button
* feat: center landscape image in colab notebook
* style: shrink popup to fit content, truncate URL display
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* feat: center landscape image in colab notebook
* feat: use GitHub raw URL for studio landscape image in notebook
* chore: update colab notebook
* feat: add studio landscape colab display image and update notebook
* feat: update notebook with studio landscape image
* style: remove colors, add progress bar, add VERBOSE flag to install output
* docs: add comments explaining VERBOSE flag and progress bar
* chore: update colab notebook
* fix: define VERBOSE, _STEP, _TOTAL at module level to fix NameError
---------
Co-authored-by: LeoBorcherding <LeoBorcherding@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Replace _in_virtualenv() heuristic with a runtime probe. At
bootstrap time, try a dry-run uv install without --system. If
that fails (exit code 2, "No virtual environment found"), retry
with --system to confirm it works. This handles all environments
correctly: venvs, Colab (system Python), local machines, containers.
Three fixes based on review:
1. Make uv truly optional: _bootstrap_uv() now only checks if uv is
already on PATH. It no longer tries to pip install uv. If uv is
not present, pip is used with zero changes to behavior.
2. Add --system flag for Colab: on Colab there is no venv (packages
install into system Python). uv requires --system in this case,
otherwise it errors with "No virtual environment found". Added
_in_virtualenv() check that detects VIRTUAL_ENV, sys.real_prefix,
or sys.base_prefix != sys.prefix.
3. Fix label printed twice on uv fallback: when uv fails and falls
back to pip, the label now says "(pip)" to distinguish from the
initial uv attempt, instead of printing the same label twice.
Tested:
- venv path: no --system flag, uv installs correctly
- no-venv path (Colab sim): --system flag added automatically
- full unsloth studio setup + training run (Llama-3.2-1B, 10 steps)
install_python_stack.py:
- Print uv error output on failure for debuggability
- Refactor pip_install() to use early return after uv success,
removing duplicated pip command path
setup.sh:
- Guard nvidia-smi command substitution with || true so it does
not abort the script under set -euo pipefail when nvidia-smi
fails (e.g., containerized environments, driver quirks)
- Read all GPU compute capabilities and deduplicate, so
mixed-GPU hosts get kernels built for all present architectures
instead of only the first GPU
Replace pip with uv in install_python_stack.py to speed up the Python
dependency installation phase of `unsloth studio setup`.
- Add _bootstrap_uv() that checks for uv on PATH, and if not found,
installs it via pip. Falls back to pip if uv is unavailable.
- Translate pip flags to uv equivalents (--no-cache-dir dropped since
uv caching is fast, --force-reinstall becomes --reinstall).
- Add --torch-backend=auto so uv auto-detects CUDA version for
PyTorch ecosystem packages.
- Per-install fallback: if any uv install step fails, it retries that
step with pip before exiting.
Measured on clean venv setup:
Python packages (pip): 2m 28s
Python packages (uv): 18s
Speedup: ~8x
Total setup time goes from ~4m 35s to ~2m 30s (llama.cpp build is
now the bottleneck at 1m 40s).
Editable installs (-e) work via a .pth file that is only processed at
Python startup. In Colab the kernel is already running when setup.sh
installs the plugin, so the .pth file never gets picked up and
data_designer_unstructured_seed is not importable.
Remove -e so pip copies the package files directly into site-packages,
which the live kernel can find immediately. Local venv installs are
unaffected since the venv is always created fresh before install.
