* Fix Studio silently exiting on Windows without error output
On Windows, `unsloth studio` launches a child process via
subprocess.Popen to run the server in the studio venv. If the child
crashes (e.g. due to a missing package), the parent just calls
typer.Exit(rc) with no message -- the user sees "Launching Unsloth
Studio... Please wait..." and then the prompt returns with zero
feedback.
Root cause: `data_designer_unstructured_seed` is imported at the top
level in seed.py. If this package is not installed in the studio venv,
the entire import chain (seed.py -> routes/__init__.py -> main.py ->
run_server()) crashes with ModuleNotFoundError. Since run.py has no
try/except around run_server() and studio.py does not report nonzero
exit codes, the failure is completely silent.
Changes:
- run.py: wrap run_server() in try/except, print clear error with
traceback to stderr. Also reconfigure stderr encoding on Windows so
tracebacks with non-ASCII paths do not cause secondary failures.
- studio.py: print an error message when the child process exits with
a nonzero code on Windows, so the user knows something went wrong.
- seed.py: make data_designer_unstructured_seed import optional with
a try/except fallback. The server starts normally and only returns
HTTP 500 if the unstructured seed endpoints are actually called.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Skip Anaconda/Miniconda Python when creating Studio venv on Windows
Conda-bundled CPython ships modified DLL search paths that prevent
torch from loading c10.dll on Windows. The Studio server fails
silently at startup because the venv was created with conda's Python.
Standalone CPython (python.org, winget, uv) does not have this issue.
Both install.ps1 and setup.ps1 now skip any Python binary whose path
contains conda, miniconda, anaconda, miniforge, or mambaforge when
selecting the interpreter for the studio venv. If only conda Python
is available, the scripts print an error with instructions to install
standalone CPython.
* Fix multi-file preview crash and improve setup.ps1 Python discovery
Addresses review findings [10/10] and [8/10]:
1. seed.py: _read_preview_rows_from_multi_files() had a hard import
of build_multi_file_preview_rows inside the function body, bypassing
the optional-plugin guard. Moved it into the top-level try/except
block and added a None guard matching the other functions.
2. setup.ps1: Python discovery now probes py.exe (Python Launcher)
first, uses Get-Command -All to look past conda entries that shadow
standalone CPython further down PATH, skips WindowsApps stubs, and
resolves the actual executable path so venv creation does not
re-resolve back to a conda interpreter.
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* Check sys.base_prefix to catch venvs created from conda Python
A venv created from conda Python (e.g. C:\Users\danie\.venv) has a
path that does not contain "conda", but sys.base_prefix still points
to the conda install (e.g. C:\Users\danie\miniconda3). The previous
path-only check missed this case entirely.
Both install.ps1 and setup.ps1 now use a Test-IsConda helper that
checks both the executable path AND sys.base_prefix against the
conda/miniconda/anaconda/miniforge/mambaforge pattern. This catches:
- Direct conda Python executables
- Venvs created from conda Python (base_prefix reveals the origin)
* Fix install.ps1 passing version string to uv venv instead of resolved path
Find-CompatiblePython returned a bare version string (e.g. "3.13")
which was passed to `uv venv --python 3.13`. uv performs its own
interpreter discovery and can resolve that version string back to a
conda Python, defeating the entire conda-skip logic.
Now Find-CompatiblePython returns a hashtable with both .Version (for
display) and .Path (the resolved absolute executable path). The venv
is created with `uv venv --python <absolute-path>`, ensuring uv uses
the exact interpreter we validated.
* Quote resolved Python path in uv venv call for paths with spaces
---------
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* fix(studio): prevent ModuleNotFoundError in dataset.map() on Windows
On Windows, dataset.map() uses "spawn", which requires workers to
import compiled modules from disk. Previously, clear_unsloth_compiled_cache()
deleted the entire directory, causing workers to crash when looking for
UnslothSFTTrainer.py.
Changes:
1. Added `preserve_patterns` to cache cleanup to keep `Unsloth*Trainer.py`
on Windows while clearing model-specific files.
2. Added the cache directory to PYTHONPATH for spawn workers.
Linux/macOS behavior is unchanged.
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* Fix spawn-platform coverage, CWD path mismatch, and race condition for PR #4473
- Extend platform guard from win32-only to include macOS (also uses spawn
since Python 3.8, same ModuleNotFoundError would occur)
- Replace fragile CWD-based PYTHONPATH registration with centralized
register_compiled_cache_on_path() that uses the same __file__-relative
_CACHE_DIRS already used by cache_cleanup -- fixes path mismatch when
studio is launched from a directory other than the repo root
- Move PYTHONPATH registration to the top of _train_worker(), before any
dataset.map() call (previously it ran late in config assembly, after
dataset formatting which also calls dataset.map())
- Update inference.py model-unload to preserve trainer files on spawn
platforms, preventing a race where unloading a model via inference tab
would delete UnslothSFTTrainer.py while training workers are importing it
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* Fix cache-dir precedence reversal in register_compiled_cache_on_path()
Iterating _CACHE_DIRS in forward order while calling insert(0) each time
reverses the declared priority: later entries shadow earlier ones. When
multiple compiled-cache directories exist, spawned workers could import a
stale trainer from the wrong cache.
Fix: iterate in reverse so that the highest-priority entry (first in
_CACHE_DIRS) is inserted last and ends up at position 0 in sys.path and
PYTHONPATH.
* fix: harden worker-count helpers against cpu_count=None and desired<=0
- safe_num_proc: guard os.cpu_count() with `or 1`, clamp multi-GPU
path with max(1, min(4, desired)), clamp return with max(1, desired)
- safe_thread_num_proc: same os.cpu_count() guard and return clamp
- Add regression tests (31 L1 unit + 10 sandbox edge-case tests)
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* remove regression tests from PR
---------
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Co-authored-by: Daniel Han <danielhanchen@gmail.com>
The previous prompt "Show me a live weather dashboard, no API key needed"
was too vague. The new wording explicitly asks for HTML code, which
produces more useful and consistent responses.
* fix(install.ps1): split torch+unsloth install to fix non-NVIDIA package resolution
--torch-backend=auto on a non-NVIDIA Windows machine causes uv to resolve
unsloth==2024.8 (pre-CLI, no unsloth.exe). Fix: detect GPU robustly (PATH +
hardcoded fallback paths, mirrors setup.ps1), install torch first with an
explicit --index-url (CUDA variant for NVIDIA, CPU for everyone else), then
install unsloth separately without --torch-backend so the solver always picks
a modern release that ships the Studio CLI.
Closes the remaining gap flagged in #4478.
* fix(install.ps1): align warning with setup.ps1, add --upgrade, handle CUDA 11.x
- Match the no-GPU warning message to studio/setup.ps1 wording
(chat-only GGUF mode, driver download link)
- Add CUDA 11.x floor check in Get-TorchIndexUrl so old drivers
fall back to CPU wheels instead of silently getting cu124
- Log a warning when nvidia-smi output cannot be parsed
- Add --upgrade to both uv pip install calls so re-runs pick up
newer package versions
* revert --upgrade from uv pip install calls
uv pip install already resolves to the latest satisfying version;
--upgrade is unnecessary and could force unwanted re-installs.
* fix: replace frozen cu124 fallbacks with cu126, guard CUDA 11.x
cu124 wheels are frozen at torch 2.6.0 -- falling back to them pins
users to an outdated PyTorch. Three issues fixed in both install.ps1
and setup.ps1:
1. CUDA 12.0-12.5 now maps to cu126 (was cu124).
2. CUDA 11.x and older now falls back to cpu (was cu124, which would
silently install incompatible GPU wheels).
3. Parse-failure and no-nvidia-smi fallbacks updated to cu126/cpu.
Adds tests/test_cuda_wheel_mapping.py covering the mapping logic,
nvidia-smi parsing, PS1 file sync, PyTorch index URL validation,
and sandbox torch installs.
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* remove test file from PR branch
Test file kept locally, not needed in the PR.
* fix: map CUDA 11.x to cu118 instead of cpu
PyTorch still publishes cu118 wheels (up to torch 2.7.1), so CUDA 11.x
users get GPU-accelerated torch rather than being forced to CPU-only.
Only CUDA 10.x and older fall back to cpu.
* fix: revert CUDA 12.0-12.5 to cu124, handle cpu tag in setup.ps1
CUDA 12.0-12.5 drivers only support up to their reported CUDA version,
so cu126 wheels (built with CUDA 12.6) fail to load. Revert the catch-
all for 12.0-12.5 back to cu124.
Also fix setup.ps1 caller: when Get-PytorchCudaTag returns "cpu" (e.g.
CUDA 10.x driver), the installer now correctly skips Triton and prints
"CPU-only" instead of "CUDA support (cpu)".
* fix: add --upgrade to unsloth install for stale venv repair
On reruns against an existing venv, uv pip install unsloth makes no
changes if unsloth==2024.8 is already installed (it satisfies the
constraint). Adding --upgrade only to the unsloth install ensures
stale installs get repaired without forcing a multi-GB torch
re-download.
* fix: use --upgrade-package to avoid clobbering torch CUDA wheels
`--upgrade unsloth` re-resolves torch from default PyPI, stripping the
+cuXXX suffix installed in step 1. `--upgrade-package unsloth unsloth`
upgrades only unsloth (and pulls missing deps like transformers, trl)
while preserving the pinned torch from the CUDA-specific index.
* docs: explain why split-install and --upgrade-package are needed
Expand the inline comment block to document both design decisions:
1. Why torch is installed separately (solver fallback to 2024.8)
2. Why --upgrade-package is used instead of --upgrade (preserves CUDA wheels)
---------
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Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Fix Studio crash on Anaconda Python due to platform._sys_version() parse failure
Anaconda and conda-forge modify sys.version to include distributor
metadata between pipe characters, e.g.:
3.12.4 | packaged by Anaconda, Inc. | (main, ...) [MSC v.1929 ...]
Python's platform._sys_version() has a hardcoded regex that cannot
parse this format, raising ValueError. CPython closed this as "not
planned" (cpython#102396) since Anaconda modified the binary.
This breaks the import chain: run.py -> structlog -> rich -> attrs,
which calls platform.python_implementation() at module scope.
Fix: before any library imports, strip the pipe segments, parse the
cleaned version string via the standard parser, and cache the result
under the original sys.version key so all subsequent platform calls
hit the cache.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Add defensive fallback for unpaired pipe edge cases in version patch
Address Gemini review suggestion: if the paired-pipe regex leaves
residual pipes (hypothetical single-pipe distributor metadata), fall
back to extracting the version number and the parenthesized build
info directly. Wrap the entire patch in try/except so unexpected
version string formats degrade gracefully instead of crashing the
patch itself.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Refactor into shared _platform_compat module, cover colab.py entrypoint
Address reviewer feedback:
1. Extract the Anaconda/conda-forge sys.version fix into a shared
_platform_compat.py module that wraps platform._sys_version() with
a retry-on-ValueError fallback. This is more robust than cache-seeding
because it handles all future platform._sys_version() calls, not just
the first one.
2. Import the fix from both run.py and colab.py entrypoints, so Studio
no longer crashes on Anaconda Python regardless of the launch path.
3. The wrapper is idempotent (guarded by a flag) and handles edge cases:
paired pipes (Anaconda, conda-forge), unpaired pipes (hypothetical),
and standard CPython strings (no-op since ValueError is never raised).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Replace monkey-patch with cache-prime, fix colab.py duplicate sys.path, cover main.py
- Rewrite _platform_compat.py: replace function-wrapping monkey-patch with
one-shot cache seed (_seed_sys_version_cache). Parses cleaned sys.version
once and seeds platform._sys_version_cache so the stdlib parser never sees
the problematic Anaconda/conda-forge pipe-delimited string. No function
replacement, no idempotency flag, no reload edge cases.
- colab.py: remove duplicate backend_path sys.path insertion after
_bootstrap_studio_venv(). The early insertion (before _platform_compat
import) already covers it. This also fixes backend/ ending up behind
venv site-packages in sys.path ordering.
- run.py: move PYTHONWARNINGS=ignore before _platform_compat import to
preserve original intent of suppressing warnings early.
- main.py: add sys.path + _platform_compat import before route imports,
covering the direct `uvicorn main:app` launch path.
- Add test_platform_compat.py with 7 tests covering Anaconda, conda-forge,
and standard CPython version strings, plus the loggers import chain.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Remove test_platform_compat.py from PR
* Handle Format B conda-forge version strings with duplicate paren groups
Some conda-forge builds produce sys.version with the build info both
before and after the pipe label (e.g. "3.9.7 (default, ...) | packaged
by conda-forge | (default, ...) \n[GCC 7.5.0]"). After stripping the
pipe segment, two consecutive (...) groups remain, which still fails
platform._sys_version(). Add a second regex pass to drop the duplicate
paren group.
* Guard _sys_version call with try/except to avoid making things worse
If the cleaned version string is still unparseable by the stdlib regex
(e.g. nested parens, exotic multi-pipe formats), silently give up
instead of letting ValueError propagate at import time -- which would
be a worse crash than the original deferred one.
---------
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* fix: handle Windows subprocess crash during dataset.map()
Windows uses spawn (not fork) for multiprocessing. Spawned workers
cannot resolve Unsloth's dynamically compiled cache modules from
unsloth_compiled_cache/, causing ModuleNotFoundError and RuntimeError
during dataset.map() tokenization.
Add two platform-guarded patches for sys.platform == "win32":
1. Force HF_DATASETS_MULTITHREADING_MAX_WORKERS=1 and set spawn method
2. Monkey-patch Dataset.map() to force num_proc=None
Fixes#4490
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* address review: extend spawn fix to macOS, add multiprocess fallback
- Change platform checks from sys.platform == "win32" to
sys.platform != "linux" so macOS (also spawn-based) is covered
- Wrap multiprocess import in try/except falling back to stdlib
multiprocessing when the multiprocess package isn't installed
- Rename _win32_safe_map to _spawn_safe_map to reflect broader scope
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix: replace global Dataset.map monkey-patch with targeted num_proc routing
The previous approach had issues: Patch 1 set HF_DATASETS_MULTITHREADING_MAX_WORKERS
and forced set_start_method (dead code on platforms already using spawn), and Patch 2
globally monkey-patched Dataset.map() (too broad, missed Dataset.filter()).
Replace with a two-layer fix:
1. Studio layer: Add dataset_map_num_proc() that returns None on spawn platforms
(Windows, macOS). Unlike num_proc=1 which still creates Pool(1) and spawns a
worker, num_proc=None runs Dataset.map()/filter() truly in-process.
Update all dataset.map() callsites to use it. ThreadPoolExecutor callers
(format_conversion.py) keep using safe_num_proc() since threads are unaffected.
2. Root-cause layer: Propagate UNSLOTH_COMPILE_LOCATION via PYTHONPATH on spawn
platforms so spawned workers can import compiled modules. Mirrors the .venv_t5
pattern in worker.py. Does not import unsloth_zoo.compiler (heavy torch/triton
imports). Completely skipped on Linux.
Also extend safe_num_proc() to return 1 on macOS (was only guarding Windows),
and narrow the transformers 5.x dataloader guard from != "linux" to explicit
("win32", "darwin").
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* fix: add safe_thread_num_proc() for ThreadPoolExecutor callsites
safe_num_proc() correctly caps to 1 on macOS/Windows for process-based
multiprocessing, but format_conversion.py reuses it for ThreadPoolExecutor
workers. Threads share address space and are unaffected by spawn, so
capping to 1 makes image URL downloads sequential -- a real regression.
Add safe_thread_num_proc() that skips the platform guard but keeps the
cpu_count heuristic, and switch both ThreadPoolExecutor callsites in
format_conversion.py to use it.
* fix: remove double-wrap in dataset_num_proc + fix num_proc=1 in datasets route
- trainer.py:3009: Replace safe_num_proc(max(1, os.cpu_count() // 4))
with max(1, (os.cpu_count() or 1) // 4) to avoid double-wrapping
inside dataset_map_num_proc which already calls safe_num_proc
- trainer.py:15-20: Clarify comment on PYTHONPATH propagation
- datasets.py:445: Change num_proc=1 to num_proc=None for 10-row
preview slice (avoids unnecessary multiprocessing overhead)
* fix: guard os.cpu_count() against None in worker-count helpers
os.cpu_count() can return None on some platforms. Use (os.cpu_count() or 1)
to prevent TypeError in safe_num_proc() and safe_thread_num_proc().
---------
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Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* gate on min uv version and shortcut python candidate search if known
* fix sort -V cross compat issue, run_quiet early exit on llamacpp, autolaunch
* update launch message
* Fix PR comments
* auto launch and find open port
* remove dev install
* Fix review findings: major-version guard, non-fatal port fallback, tty comment, restore local
* Remove autolaunch, clean up dead state and debug noise
- Remove find_open_port, TTY-gated autolaunch, and </dev/tty
redirection from install.sh; just print launch instructions
- Remove unused BEST_MAJOR variable from studio/setup.sh
- Remove stray "finished finding best python" debug echo
- Fix stale comment "below 3.12" to "below 3.11"
* Reject prerelease uv at exact minimum version boundary
* Remove 2>/dev/null from version_ge numeric comparisons
Let non-numeric version parts surface errors on stderr
instead of being silently swallowed.
---------
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* fix: reconfigure stdout UTF-8 on Windows to prevent UnicodeEncodeError from emoji
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: default frontend_path when None to fix blank page when venv is pre-activated
* Restore Windows UTF-8 stdout fix dropped in earlier commit
The cp1252 console encoding on Windows cannot render emoji characters
used in startup messages (e.g. print("✅ Frontend loaded ...")).
This causes UnicodeEncodeError and crashes the server before it starts.
Place sys.stdout.reconfigure(encoding="utf-8", errors="replace") at the
top of run_server(), unconditionally before any print() or structlog
call, so all emoji output is covered -- including the frontend status
messages and silent=True paths that the original placement missed.
Guarded by sys.platform == "win32" and hasattr check, so it is a no-op
on Linux/macOS and safe in non-standard stdout environments (Jupyter,
piped IO).
* fix: preserve run_server(None) as headless, fix CLI frontend kwarg
Remove the frontend_path=None fallback in run_server() that changed
None from "headless/API-only" to "mount bundled frontend", breaking
backwards compatibility for embedders.
The blank-page bug was actually caused by the CLI wrappers always
passing frontend_path=frontend (even when frontend=None), which
overrode run_server()'s default. Fix studio.py and ui.py to only
pass frontend_path when the user explicitly sets --frontend.
* fix: use timeout loop for shutdown event in ui command
Match studio_default()'s shutdown loop that uses a 1-second timeout
on Event.wait(). Without a timeout, the bare wait() blocks at the C
level on Linux, preventing Python from delivering SIGINT (Ctrl+C).
---------
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* fix: add CUDA minimum version check and abort for llama.cpp (>= 12.4)
- setup.ps1/setup.sh: abort with clear error if CUDA toolkit < 12.4
(llama.cpp requirement); link to cuda-toolkit-archive for upgrade
- setup.ps1: promote CUDA VS integration copy failure from WARN to
ERROR + exit 1; remove manual-copy hack instructions per Roland —
correct fix is re-installing CUDA/MSBuild, not a manual workaround
Fixes: https://github.com/unslothai/unsloth/issues/4437
Reported by: Sebastien
* fix: wipe stale studio venv when torch CUDA tag changes
When the NVIDIA driver is updated, the required PyTorch CUDA tag changes
(e.g. cu124 -> cu130) but setup.ps1 was silently reusing the existing
.venv, leaving the old torch wheel in place and breaking the UI for
everyone on the next setup run.
Before creating/reusing the venv, inspect the installed torch version
string. If its CUDA tag does not match what the current driver requires,
wipe the venv so we always get a clean, correct install.
* Fix CUDA version check: portability, non-fatal fallback, stale venv detection
- setup.sh: Replace grep -oP with POSIX sed for macOS compatibility
- setup.sh: Replace exit 1 with NVCC_PATH="" to fall back to CPU-only build
- setup.sh: Move version check before -DGGML_CUDA=ON append
- setup.sh: Add else branch warning when nvcc version is unparseable
- setup.ps1: Replace exit 1 with $NvccPath=$null for non-fatal CUDA fallback
- setup.ps1: Add driver vs toolkit guidance in version warning
- setup.ps1: Guard CUDA env/VS integration setup with if ($NvccPath)
- setup.ps1: VS integration catch: downgrade to WARN, restore source/dest paths
- setup.ps1: Stale venv: detect CPU torch and untagged wheels, not just +cuNNN
- setup.ps1: Stale venv: rebuild on failed torch import
- setup.ps1: Stale venv: wrap Remove-Item in try/catch for locked files
* Remove incorrect CUDA >= 12.4 check, keep only stale venv detection
llama.cpp has no hard minimum CUDA version -- it builds with CUDA as old
as 11.2 and degrades features gracefully via #if CUDART_VERSION guards.
The 12.4 figure was the default Docker/CI baseline, not a build requirement.
Reverted:
- CUDA version check in setup.sh (entirely removed)
- CUDA version check in setup.ps1 (entirely removed)
- VS integration catch block cosmetic changes (restored to main)
- if ($NvccPath) guard around CUDA env setup (not needed without version check)
Kept:
- Stale venv detection in setup.ps1: detects torch CUDA tag mismatch
(cu124 vs cu130, cpu vs cuXXX, broken torch import) and rebuilds venv
* Fix stale venv detection: incomplete venvs, timeout, fatal delete failure
- Add 30s timeout for torch import probe via ProcessStartInfo/WaitForExit
- Use Test-Path -PathType Container to reject files masquerading as venv dir
- Trigger rebuild when python.exe is missing (incomplete venv)
- Make Remove-Item failure fatal ([ERROR] + exit 1) instead of warn-and-continue
- Move $expectedTorchTag computation inside -not $shouldRebuild guard
---------
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Co-authored-by: Daniel Han <danielhanchen@gmail.com>
The ruff pre-commit hook runs on all file types by default, including
.ipynb notebooks. Colab notebooks are authored in Colab's editor and
can contain IPython magics (%cd, !git) that ruff cannot parse. This
causes pre-commit.ci to fail on unrelated PRs when a notebook on main
has syntax ruff does not understand.
Add `exclude: '\.ipynb$'` to the ruff hook so notebooks are skipped.
* feat(chat): add server-side timings and context display for GGUF
Extract timings/usage metadata from llama-server SSE stream and forward
through the full stack. Replace client-side estimates with accurate
server-reported metrics (prompt eval, tok/s, token counts, cache hits).
Add context window usage bar to chat top nav.
* feat(chat): source badges with hover cards and 2-row collapse
- Add hover cards to source badges showing favicon, title, URL and
snippet description on hover
- Limit source badges to 2 rows with +X more expand/collapse
- Parse snippet from web search results for hover card descriptions
- Replace individual Source rendering with grouped SourcesGroup component
* fix(chat): add null guards for server timings edge cases
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix(chat): reset contextUsage on thread switch, remove unused context-display
* fix(chat): stop double-counting completion tokens in tool-calling path
* fix(chat): skip metadata events in llm_assist consumers
* fix(chat): hide context usage bar in compare mode
* fix(chat): harden timings pipeline and context usage persistence
Accumulate prompt_ms, predicted_ms, and predicted_n from intermediate
tool-detection passes so the final metadata reflects total server work.
Persist contextUsage in message metadata (Dexie) and restore on thread
load. Add type guard in gguf_stream_chunks for unexpected dict events.
Clear contextUsage when entering compare mode.
* feat(chat): make GGUF stream metadata OpenAI-compatible
* fix(chat): address PR review feedback
* feat(chat): address PR review feedback
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix(recipe-studio): prevent fitView from zooming to wrong location on recipe load
* feat: add pymupdf/python-docx deps and unstructured uploads storage root
* feat: add POST /seed/upload-unstructured-file endpoint
* feat: add multi-file chunking with source_file column
* feat: update frontend types and API layer for multi-file upload
* feat: round-robin preview rows across source files
Ensures every uploaded file is represented in the preview table
by cycling through sources instead of just taking the first N rows.
* fix: disable OCR, fix auto-load timing, fix persistence on reload
- Disable pymupdf4llm OCR with write_images=False, show_progress=False
- Replace onAllUploaded callback with useEffect that detects uploading→done
transition (avoids stale closure reading empty file IDs)
- Fix importer to preserve file IDs from saved recipes instead of clearing
(clearing only happens at share time via sanitizeSeedForShare)
* fix: harden unstructured upload with input validation and state fixes
Validate block_id/file_id with alphanumeric regex to prevent path
traversal, use exact stem match for file deletion, add error handling
for metadata writes and empty files, fix React stale closures and
object mutations in upload loop, and correct validation logic for
unstructured seed resolved_paths.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: address PR review - legacy path import, share sanitizer, sync effect
Promote legacy source.path into resolved_paths for old unstructured
recipes, clear source.paths in share sanitizer to prevent leaking local
filesystem paths, and gate file sync effect to dialog open transition
so users can actually delete all uploaded files.
* fix: CSV column fix (BOM + whitespace + unnamed index re-save) for #4470
* fix: harden unstructured upload flow and polish dialog UX
* [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 Windows installer Python detection and winget error handling
The PowerShell installer crashes on some Windows machines due to two
issues:
1. Windows Store App Execution Aliases: Get-Command finds the stub at
WindowsApps\python.exe, then python --version writes to stderr.
With $ErrorActionPreference = "Stop" on PowerShell 5.1, stderr
from native commands becomes a terminating error, killing the
script before it tries to install Python.
2. winget "already installed" exit code: winget returns -1978335189
(APPINSTALLER_CLI_ERROR_UPDATE_NOT_APPLICABLE) when the package is
already at the latest version. The script treated any non-zero exit
as failure. The fallback Get-Command check could also find the
Store stub or fail if Python was partially uninstalled.
Changes:
- Add Find-CompatiblePython helper that tries the py launcher first,
then python3/python via Get-Command -All, explicitly skipping any
WindowsApps stubs. All invocations wrapped in try-catch so stderr
never triggers ErrorActionPreference.
- Replace exit-code-based winget error handling with outcome-based:
re-detect Python after install, retry with --force if not found,
show actionable manual install instructions on final failure.
- Deduplicate PATH entries in Refresh-SessionPath to prevent unbounded
growth from repeated machine+user path prepending.
* Address reviewer feedback: wrap winget calls, remove blanket WindowsApps filter
Three fixes based on code review:
1. Wrap all winget install calls in $ErrorActionPreference = "Continue"
blocks so that winget stderr (progress bars, warnings) does not
become a terminating error on PowerShell 5.1. This matches the
pattern already used in studio/setup.ps1 line 983.
2. Remove the blanket *\WindowsApps\* path filter that rejected all
WindowsApps executables including valid Microsoft Store Python
installs. Instead, rely on the existing try-catch + version regex
probing to determine if a candidate is functional. Non-functional
entries (App Execution Alias stubs) fail the try-catch and are
skipped naturally.
3. Use $pyLauncher.Source (resolved path) instead of bare py name,
add -CommandType Application to avoid matching aliases/functions,
and derive winget package ID from $PythonVersion variable instead
of hardcoding Python.Python.3.13.
* Add back WindowsApps filter for python3/python fallback path
The App Execution Alias stubs in WindowsApps can open the Microsoft
Store as a side effect when invoked, even though the try-catch handles
the error. Since the py launcher (tried first) already detects
legitimate Store Python -- Store packages include py since Python
3.11 -- filtering WindowsApps in the python3/python fallback is safe
and avoids the Store popup.
---------
Co-authored-by: Daniel Han <danielhanchen@users.noreply.github.com>
* fix(install.ps1): detect AMD/no-NVIDIA GPU early and guard unsloth.exe existence
When a user has an AMD GPU (no nvidia-smi), uv's --torch-backend=auto
resolves to CPU torch, which constrains the solver to unsloth==2024.8.
That ancient release has no unsloth.exe CLI entry point, so the subsequent
& \ studio setup call throws a confusing PowerShell
'module could not be loaded' CommandNotFoundException instead of a
clear error.
Two fixes:
- Detect nvidia-smi early; if no NVIDIA GPU is found, print a clear
error explaining AMD/Intel GPUs are unsupported and exit before
wasting time installing the wrong package version.
- Guard Test-Path \ before invoking it, so any future case
where the CLI entry point is missing produces a readable error
instead of a cryptic PowerShell exception.
Fixes: unsloth_studio\Scripts\unsloth.exe CommandNotFoundException
on AMD GPU systems (Windows).
* fix(install.ps1): correct GPU support message - AMD is Linux-only via ROCm
* Slim down to just the unsloth.exe existence guard
Remove the early NVIDIA GPU detection gate -- Studio supports Windows
and Mac without a GPU (finetuning is simply disabled). The GPU gate
was blocking legitimate non-NVIDIA users from installing.
Keep only the Test-Path guard on unsloth.exe before invoking it. This
turns the confusing PowerShell CommandNotFoundException into a clear
error message pointing at the likely cause (older unsloth version
resolved by the package solver that does not include the Studio CLI).
* Fix quickstart link in unsloth.exe guard message
---------
Co-authored-by: LeoBorcherding <LeoBorcherding@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* feat: support full model GGUF export, disable incompatible methods in UI
* fix: resolve base model from config.json for venv_t5 export switching
* feat: detect BNB-quantized models and disable all export methods for quantized non-PEFT checkpoints
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: relocate Ollama Modelfile alongside GGUFs during non-PEFT export cleanup
* [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 macOS install.sh: stdin consumption and Python discovery
Two issues when running `curl | sh` on macOS:
1. Commands like `brew install` consume bytes from the piped stdin,
causing the shell to lose its place in the script. The remaining
source code gets printed as text instead of being executed, so
users have to run the installer twice. Fixed by redirecting stdin
from /dev/null for brew, apt-get, xcode-select, and the uv
installer subprocess.
2. setup.sh searches for Python 3.11-3.13 on the system PATH via
`compgen -c`. On macOS systems that only have Python 3.9 and/or
3.14, this fails with "No Python version between 3.11 and 3.13
found" even though uv already installed Python 3.13 into the
venv. Fixed by adding the venv's bin/ to PATH before invoking
`unsloth studio setup`.
* Guard PATH export against empty VENV_ABS_BIN
If cd into the venv bin/ fails, VENV_ABS_BIN would be empty and
PATH would start with ":", causing the current directory to be
searched for executables. Wrap the export in a non-empty check.
* full finetuning studio
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Update studio/backend/core/training/trainer.py
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
* One liner setup for unsloth studio
* Fix install scripts: system deps, activation bugs, curl/wget support
- install.sh: detect platform (macOS/Linux/WSL) and check for missing
system dependencies (cmake, git, build-essential, libcurl4-openssl-dev).
Prompt user once for permission to install all missing packages via
brew (macOS) or sudo apt-get (Linux/WSL). Add wget fallback via
download() helper since curl is not always present on minimal Linux
installs. Fix nested curl|sh stdin stealing by downloading uv installer
to a tempfile first. Replace venv activation (no-op in a pipe subshell)
with explicit --python flag for uv pip install and direct venv binary
invocation. Add idempotency guard for venv creation. Redirect stdin
on unsloth studio setup to prevent pipe consumption. On macOS, check
for Xcode Command Line Tools and trigger install if missing.
- install.ps1: wrap script body in Install-UnslothStudio function so
that errors use return instead of exit (exit kills the terminal when
run via irm|iex). Remove activate.ps1 invocation entirely -- use
explicit --python path for uv pip install and & $UnslothExe for
studio setup. This avoids both the child-scope activation bug (& vs
dot-source) and the execution policy error on default Windows systems.
Add winget availability check with clear error message. Fix PATH
refresh to append registry paths instead of replacing the session PATH.
Add uv installer fallback via astral.sh PowerShell script if winget
install does not put uv on PATH. Broaden Python version check to
accept 3.11-3.13. Add idempotency guard for venv creation.
- README.md: add wget one-liner alternative for systems without curl.
* Fix Tailwind CSS v4 .gitignore bug on Windows (#4444)
- Add .gitignore hiding workaround to setup.ps1 (matching existing
setup.sh logic) so venv .gitignore files containing "*" don't prevent
Tailwind's oxide scanner from finding .tsx source files
- Add CSS size validation to setup.sh, setup.ps1, and build.sh to catch
truncated Tailwind builds early
- Remove stray force-rebuild overrides that made the "skip build if
current" cache check dead code in both setup scripts
- Add rm -rf dist to build.sh to force clean rebuilds for wheel packaging
* Change default port 8000 to 8888, fix installer bugs, improve UX
- Change default Studio port from 8000 to 8888 across all entry points
(run.py, studio.py, ui.py, colab.py, vite.config.ts, setup scripts)
- Update launch banner: "Launching with studio venv..." to
"Launching Unsloth Studio... Please wait..."
- Add "Open your web browser" banner and rename labels
(Local -> Local Access, External -> Worldwide Web Address)
- Fix venv idempotency: check for bin/python instead of just directory
existence, clean up partial venvs on retry
- Fix build.sh CSS validation: handle empty CSS case that silently
bypassed the check with "integer expression expected"
- Fix install.sh sudo handling: try apt-get without sudo first (works
when root), then escalate with per-package tracking and user prompt
- Fix install.ps1: check exit code from studio setup, fail on error
- Add pciutils to WSL GGUF build dependencies
- Apply same smart apt-get escalation pattern to studio/setup.sh
* Use detected Python version for venv, abort on non-apt Linux
- install.ps1: detect existing Python 3.11/3.12/3.13 and use that
version for venv creation instead of always forcing 3.13
- install.sh: exit with error on non-apt Linux distros when required
packages cannot be auto-installed, instead of silently continuing
* Make sudo permission prompt more prominent with warning banner
* Add Accept [Y/n] sudo prompt to studio/setup.sh for consistency
* Fix native command exit code handling and sudo decline flow
install.ps1: Add $LASTEXITCODE checks after winget (Python), uv venv,
and uv pip install calls. $ErrorActionPreference only catches PowerShell
cmdlet errors, not native executable failures. The Python check also
handles winget returning non-zero for "already installed".
setup.sh: Skip llama-server build when user declines sudo or sudo is
unavailable. Previously the script continued to section 8 which would
fail with confusing errors (e.g. "gcc: command not found") since
build-essential was never installed.
* Move rm -rf llama.cpp inside build branch to preserve existing install
When _SKIP_GGUF_BUILD is set (user declined sudo or sudo unavailable),
the previous rm -rf would destroy an already-working llama-server before
the skip check ran. Move it inside the else branch so existing builds
are preserved when the rebuild is skipped.
---------
Co-authored-by: Daniel Han <danielhanchen@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Fixing Qwen3.5 bug and adding Outetts dependencies
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Apply suggestion from @danielhanchen
---------
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 studio crash on Mac: vendor check_signal_escape_patterns from unsloth_zoo
Vendor the `check_signal_escape_patterns` function from
`unsloth_zoo.rl_environments` directly into `tools.py`. The function is
pure Python (only uses stdlib `ast`) and has zero GPU dependencies, but
importing it from unsloth_zoo triggers `unsloth_zoo.__init__` which calls
`get_device_type()` at module scope -- raising NotImplementedError on
Apple Silicon Macs.
By vendoring the code, the safety checks still run on all platforms
(Mac, Linux, Windows) without needing unsloth_zoo at all.
* [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>
- tool-ui-python.tsx: use explicit tuple type instead of `as const` to
match the mutable `[BundledTheme, BundledTheme]` expected by Streamdown
- chat-adapter.ts: add missing `argsText` field required by
ToolCallMessagePart and fix `args` type to use ReadonlyJSONObject
