* Add process-level tool_policy state for unsloth run
* Apply tool_policy override at chat/completions, /messages, and tool pass-through gates
* Add pure resolver for unsloth run --enable-tools/--disable-tools
* Wire --enable-tools/--disable-tools into unsloth run
* Color tool-policy notices and confirmation prompt in Claude orange
* Always show tool-status notice; print URL + API key in silent mode
* Treat any non-loopback bind as external; forward --yes after parent prompt
* Fix tool_policy double-module bug: import via state.tool_policy to share global with routes
* Fix DPO trainer multi process hang
* Fix datacollator error
* further dpo vision changes
* cleanup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Harden DPO vision row processing and source rewrites
- dpo_trainer_vision_signature_columns: also match TRL 0.22.x layout
(image_sizes followed by ref_chosen_logps), so vision keys are not
stripped via remove_unused_columns on the originally-affected version.
- dpo_trainer_concatenated_inputs: fall back to inserting after the
image_sizes block when no token_type_ids anchor follows it.
- Apply the same vision model_kwargs forwarding rewrite to
_compute_loss_liger via dpo_trainer_compute_loss_liger so the Liger DPO
path does not drop pixel_position_ids/image_position_ids/
mm_token_type_ids when args.use_liger_loss is true.
- dpo_trainer_vision_process_row:
- guard chosen/rejected EOS append with tokenizer.eos_token_id is not None
- use features.get("images") and features.get("prompt") to match the
existing get on line 164 and avoid KeyError on rows without those keys
- drop the torch.is_tensor gate so list-form pixel_position_ids/
image_position_ids returned without return_tensors are still aliased
- skip the loop entry for image_position_ids when it was already
promoted to pixel_position_ids, so the output dict no longer carries
both keys with identical data
- dpo_trainer_data_collator_vision_keys: switch from pad_sequence to
trl.trainer.utils.pad with padding_side='left' (matches the DPO
collator's prompt left-pad) and padding_value=-1 for *_position_ids
keys (sentinel for padded patches), 0 otherwise. Skip the key when not
every example carries it. Falls back to pad_sequence if trl.pad is
unavailable or the tensor rank is too high.
- dpo_trainer_prepare_dataset: keep TRL's writer_batch_size=10 when
popping num_proc; removing it defaults to 1000 and reintroduces the
vision OOM risk that writer_batch_size=10 was set to avoid.
* DPO vision row: keep upstream-facing keys and fix patch padding
- dpo_trainer_vision_process_row: no longer aliases image_position_ids
to pixel_position_ids. Each upstream-emitted vision key is forwarded
under its own name. Gemma4 ForConditionalGeneration.forward accepts
image_position_ids directly and renames it to pixel_position_ids only
at the vision-tower call site, so aliasing in the row helper hid the
kwarg the model actually consumes.
- dpo_trainer_vision_process_row: extract pixel_values via "in"
membership instead of unconditional indexing. With the missing-images
path returning [] to the processor, modern processors no longer emit
a pixel_values key, and the previous indexing raised KeyError.
- dpo_trainer_data_collator_vision_keys: pick padding_side per key
family. *_position_ids tensors are patch-aligned to pixel_values
(TRL's DataCollatorForPreference right-pads pixel_values), so pad
them right with the -1 sentinel; mm_token_type_ids is token-aligned
to prompt_input_ids (left-padded by TRL), so pad it left with 0.
* DPO vision: handle multi-image prompts and arbitrary-rank collator pad
- dpo_trainer_vision_process_row: when a prompt is missing vision
placeholders, insert one placeholder per missing image instead of
always inserting a single token. Multi-image rows now satisfy the
processor's token-vs-image count check rather than under-inserting
and tripping the placeholder/feature mismatch.
- dpo_trainer_data_collator_vision_keys: drop the dim()<=2 gate around
trl.trainer.utils.pad. trl.pad handles arbitrary rank correctly,
while the previous fallback to torch.nn.utils.rnn.pad_sequence
raised RuntimeError on rank-3 patch-position tensors with mismatched
non-leading dimensions. The pad_sequence path remains as a degraded
fallback only when trl.pad is unavailable or raises.
* DPO vision row: support scalar images and align prompt-aligned aux ids
- dpo_trainer_vision_process_row: type-aware normalization of the
features['images'] column instead of a truthiness/len check that
raised on single image objects (PIL.Image has no __len__) and on
numpy ndarrays (truthiness ambiguous). Lists/tuples count as their
length, scalar image objects count as one, None counts as zero, and
the original value is forwarded to the processor.
- dpo_trainer_vision_process_row: when max_prompt_length truncates
prompt_input_ids, also slice token_type_ids and mm_token_type_ids
by the same [-max_prompt_length:] suffix. Those keys are 1:1 token
aligned to prompt_input_ids (Gemma 4 vision attention keys off
mm_token_type_ids per modular_gemma4.py), so leaving them at the
original length silently misaligned the multimodal mask.
* DPO vision row: stop synthesizing vision-token placeholders
Pass features['prompt'] and features['images'] straight to the
processor without inserting any extra placeholder tokens. The previous
helper used processing_class.image_token, which is the right prompt
placeholder for Gemma 4 but the wrong one for Gemma 3 (whose prompt
placeholder is boi_token while image_token is the inner expansion
target). Synthesizing that token also broke multi-image rows: text
ended up with N placeholders while the row helper only forwarded the
first image's pixel_values via the standard [0] indexing that mirrors
upstream TRL process_row, so token vs image-feature counts diverged.
Removing the synthesis matches stock TRL behavior; users provide the
correct placeholders for their processor in the prompt.
* Add tests for DPO vision row processor passthrough
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
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Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Add configurable PyTorch mirror via UNSLOTH_PYTORCH_MIRROR env var
When set, UNSLOTH_PYTORCH_MIRROR overrides the default
https://download.pytorch.org/whl base URL in all four install scripts
(install.sh, install.ps1, studio/setup.ps1, studio/install_python_stack.py).
When unset or empty, the official URL is used. This lets users behind
corporate proxies or in regions with poor connectivity to pytorch.org
point at a local mirror without patching scripts.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add pytest for UNSLOTH_PYTORCH_MIRROR in install_python_stack.py
Tests that _PYTORCH_WHL_BASE picks up the env var when set, falls back
to the official URL when unset or empty, and preserves the value as-is
(including trailing slashes).
* Remove stale test assertions for missing install.sh messages
* Fix GPU mocking in test_get_torch_index_url.sh
Extract _has_usable_nvidia_gpu and _has_amd_rocm_gpu alongside
get_torch_index_url so the GPU-presence checks work in tests.
Add -L flag handling to mock nvidia-smi so it passes the GPU listing
check. All 26 tests now pass on CPU-only machines.
* Strip trailing slash from UNSLOTH_PYTORCH_MIRROR to avoid double-slash URLs
---------
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* [Studio] Install flash attn at setup time for linux
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* cleanup changes
Signed-off-by: Datta Nimmaturi <venkatadattasainimmaturi@gmail.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Test cases
* wheel_utils: narrow url_exists exceptions and log at debug level
---------
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
* 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
for more information, see https://pre-commit.ci
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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.
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Roland Tannous