* studio: pin peft to 0.18.1 to fix export subprocess issues
peft 0.19.0 causes export subprocess shutdown failures in Studio.
Reverting to 0.18.1 resolves the issue.
* studio: move peft pin to extras-no-deps to prevent torch upgrade
Installing peft via overrides.txt would resolve its deps and pull in
torch>=0.11.0, breaking other pinned packages. Moving the pin to
extras-no-deps.txt ensures --no-deps is used during install.
Revert the >= loosening from f9c4b08 back to exact pins.
Using transformers>=4.57.6 allows pip to install 5.x into the main
Studio venv, which breaks huggingface_hub imports
(is_offline_mode removed in newer hub versions).
The main venv must stay on transformers==4.57.6 and
huggingface-hub==0.36.2. The 5.x version lives only in .venv_t5/
and is dynamically switched via sys.path at runtime.
* UI Changes
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Remove unrelated test file
---------
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* fix: add tokenizers to no-torch runtime deps and add TORCH_CONSTRAINT for arm64 macOS py313+
Two installer fixes:
1. Add `tokenizers` to `no-torch-runtime.txt` before `transformers`.
Without it, `from transformers import AutoConfig` crashes on startup
because `--no-deps` skips transitive dependencies.
2. Add `TORCH_CONSTRAINT` variable to `install.sh`. On arm64 macOS with
Python 3.13+, tighten the torch requirement to `>=2.6` since torch
<2.6 has no cp313 arm64 wheels. The variable replaces the previously
hard-coded constraint in the uv pip install line.
Includes 66 tests (42 pytest + 24 bash) covering:
- Structural checks on install.sh, install.ps1, no-torch-runtime.txt
- Shell snippet tests with mocked python for 13 platform/version combos
- Mock uv integration verifying correct constraint string
- E2E venv tests on Python 3.12 and 3.13 confirming AutoConfig works
- Negative control proving AutoConfig fails without tokenizers
- Full no-torch sandbox regression guards (safetensors, huggingface_hub)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix incomplete no-torch manifest and align E2E tests with real --no-deps path
- Add missing transitive deps to no-torch-runtime.txt that are required
under --no-deps: regex, typing_extensions, filelock, httpx, httpcore,
certifi, idna, anyio, sniffio, h11. Without these, `from transformers
import AutoConfig` still fails after install.sh --no-torch.
- Change all E2E tests to use --no-deps (matching what install.sh does)
instead of normal dep resolution. Previous tests passed even with an
incomplete manifest because uv backfilled transitive deps.
- Rewrite negative control to derive from the real no-torch-runtime.txt
with tokenizers stripped, proving the specific fix matters.
- Replace GNU-only sed -i with heredoc in shell test for macOS compat.
- Remove unused os/sys imports from Python test file.
- Quote SKIP_TORCH and mock uv paths in bash -c strings.
* Assert install succeeds before checking import results in E2E tests
Address review feedback: test_torch_not_importable and
test_tokenizers_directly_importable in Group 3 now assert that
uv pip install returns 0 before checking import behavior. This
prevents false positives when the install itself fails silently.
* Assert install succeeds in negative control and tighten error check
- Add missing install-success assertion in test_negative_control_no_tokenizers
to prevent false positives from network/install failures.
- Tighten error message check to look for "tokenizers" in stderr or
ModuleNotFoundError, rather than the generic "No module" substring
which could match unrelated import failures.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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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
* fix: avoid _yaml.pyd lock on Windows during dependency overrides
* fix: move pytorch_tokenizers and kernels to no-deps install to avoid Windows _yaml.pyd loc
* Bump Data Designer to 0.5.4 (removes litellm dependency)
NVIDIA Data Designer v0.5.4 removes litellm entirely and replaces it
with native OpenAI and Anthropic adapters. This follows the litellm
supply chain incident where versions 1.82.7 and 1.82.8 were compromised
with a credential stealer.
Release notes: https://github.com/NVIDIA-NeMo/DataDesigner/releases/tag/v0.5.4
Changes:
- Bump data-designer, data-designer-config, data-designer-engine to 0.5.4
- Sync data-designer-deps.txt with 0.5.4 engine requirements:
- Added: chardet, fsspec, mcp
- Removed: python-json-logger, pymupdf, pymupdf4llm, mammoth
(these remain in the unstructured-seed plugin which still needs them)
- duckdb constraint relaxed from <1.5 to <2 (upstream fixed record_batch)
- Bump plugin lower bound to >=0.5.4
* Keep pymupdf, pymupdf4llm, mammoth in data-designer-deps
The unstructured-seed plugin is installed with --no-deps, so its
pyproject.toml dependencies are not auto-resolved. These three
packages are needed by the seed route (studio/backend/routes/
data_recipe/seed.py) and must remain in the explicit deps list.
litellm has been quarantined on PyPI due to a supply chain attack
in version 1.82.8 (malicious credential-stealing .pth file).
No versions are currently installable, which blocks
`unsloth studio setup` at step 8/11 (data-designer deps).
Remove litellm from the single-env data-designer requirements
so setup completes. litellm can be re-added once PyPI lifts the
quarantine.
Ref: https://github.com/BerriAI/litellm/issues/24512
* 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
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* 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
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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.
---------
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Comment out large unused packages from Studio setup requirements
Audited all packages installed by `unsloth studio setup` against actual
imports in unsloth, unsloth_zoo, and studio/backend. The following have
zero imports anywhere and are the largest offenders by disk size:
- gradio (148 MB) in studio.txt -- Studio uses React + FastAPI, not Gradio
- executorch (41.5 MB) in extras-no-deps.txt -- no imports found
- scikit-learn (31.8 MB) in extras.txt -- no imports found
- MeCab (19.9 MB) in extras.txt -- Japanese tokenizer, no imports found
- coremltools (10.2 MB) in extras.txt -- Apple CoreML, no imports found
- uroman (4.0 MB) in extras.txt -- romanization tool, no imports found
Total savings: ~255 MB (~32% of the 805 MB installed by setup).
Each line is commented out with the package size annotated so they can be
re-enabled easily if needed in the future.
* Restore scikit-learn -- needed by sentence_transformers
sentence_transformers is installed with --no-deps in extras-no-deps.txt,
so its sklearn dependency is not auto-resolved. Multiple modules in
sentence_transformers import sklearn at the top level (evaluation,
util/similarity), so removing scikit-learn would break embedding jobs.
## Summary
- Add web search tool calling for GGUF models (Search toggle, DuckDuckGo via ddgs)
- Add KV cache dtype dropdown (f16/bf16/q8_0/q5_1/q4_1) in Chat Settings
- Fix Qwen3/3.5 inference defaults per official docs (thinking on/off params)
- Enable reasoning by default for Qwen3.5 4B and 9B
- Replace "Generating" toast with inline spinner
- Fix stop button via asyncio.to_thread (event loop no longer blocked)
- Fix CUDA 12 compat lib paths for llama-server on CUDA 13 systems
- Fix auto-load model name not appearing in selector
- Training progress messages + dataset_num_proc fix
Integrated PRs:
- #4327 (imagineer99): BETA badge alignment (already in tree)
- #4340 (Manan Shah): prioritize training models in model selection
- #4344 (Roland Tannous): setup.sh macOS python version compatibility
- #4345 (Manan Shah): revamp model+dataset checking logic
* fix: quotation marks
* diceware passphrase generation
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
- Added constrained dependency files for single-env installations: `constraints.txt`, `data-designer.txt`, and `data-designer-deps.txt`.
- Implemented a `patch_metadata.py` script to resolve metadata conflicts between dependency versions.
- Updated `setup.sh` to integrate single-env setup, including dependency installation and metadata patching.
- Upgraded `fastmcp` and `websockets` versions in `extras.txt` for compatibility.
- Commented out unused "Start Tutorial" button in `data-recipes-page.tsx`.
