18 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Daniel Han
|
a56c959233 |
Add Studio PR-time CI: pin enforcement, frontend, backend, wheel smoke (#5298)
* Add Studio PR-time CI: pin enforcement, frontend, backend, wheel smoke
The repo currently has no PR-time CI; only release-desktop.yml (manual) and
stale.yml (issue pinger). studio/backend/tests/ has 35 test files (~860
tests collected) that never run automatically. Frontend lint/typecheck/build
scripts exist in package.json but are not gated on PRs either. This is the
gap that let 2026.5.1 ship with the broken Studio chat-history bundle.
Adds four ubuntu-latest workflows, all CPU-only and free for public repos:
studio-pin-enforce.yml
Greps studio/frontend/package.json for caret/tilde ranges on the
@assistant-ui surface (and assistant-stream). Blocks the exact regression
vector that produced 2026.5.1 (^0.12.19 resolving to a breaking 0.12.28).
studio-frontend-ci.yml
npm ci (strict lockfile), tree-clean check after, typecheck, vite build,
bundle grep for the Studio unstable_Provider call site (<= 3 hits = OK,
>= 4 = the 2026.5.1 regression), 75 MB dist budget, biome non-blocking.
Uploads dist on failure.
studio-backend-ci.yml
Runs the existing studio/backend/tests/ suite on Python 3.10/3.11/3.12.
Excludes test_studio_api.py (live model + GGUF download) and
llama_cpp_load_progress_live (spawns a real llama.cpp). Local run on this
branch: 861 pass, 4 skipped, 5 deselected. ruff non-blocking.
wheel-smoke.yml
python -m build, then verifies the produced wheel:
- ships studio/frontend/package-lock.json
- ships studio/frontend/dist/index.html
- does NOT ship studio/frontend/node_modules/
- does NOT ship studio/frontend/bun.lock
- main JS bundle has < 4 unstable_Provider hits
Then installs the wheel into a fresh venv with a lightweight dep set and
imports studio.backend.main. Locally validated against the wheel built
from this branch.
Each workflow has concurrency cancellation on the same ref. biome and ruff
are gated as non-blocking until the existing accumulated drift is cleared
(~470 biome errors today); remove the bypass in a follow-up.
Notes verified locally:
- pin enforcement: PASS (carets dropped on this branch)
- frontend npm ci -> typecheck -> build -> grep -> budget: PASS
- bundle: 48 MB, hits=1
- backend pytest: 861 pass, 1 GPU-pollution failure not reproducible on
GPU-less runners (won't reproduce on ubuntu-latest)
- wheel build: 13s, produces unsloth-2026.5.2-py3-none-any.whl
- wheel content sanity: all five checks PASS
* CI: install full backend dep set + refine pytest filter for CPU runners
First CI run on PR #5298 surfaced two real gaps:
1. pytest collection failed at `import yaml` in utils/models/model_config.
Locally my workspace venv had pyyaml from a transitive; CI's clean Python
3.10/3.11/3.12 didn't, so collection hit ModuleNotFoundError on the very
first test module. Same blew up the wheel-smoke `from studio.backend.main
import app` step.
2. Once the import chain was complete, ~9 tests still failed because they
exercise GPU-only paths or live transformers introspection that can't run
on a GPU-less `ubuntu-latest` runner regardless of code correctness:
- TestGpuAutoSelection
- TestPreSpawnGpuResolution
- TestPerGpuFitGuardAllCounts
- TestTransformersIntrospection
- test_returns_cuda_when_cuda_available
- test_calls_cuda_cache_when_cuda
Fix:
- Backend CI installs `studio/backend/requirements/studio.txt` (the
declared backend dep set) + the extras the import chain needs but
studio.txt omits (python-multipart, sqlalchemy, cryptography, pyyaml,
jinja2, mammoth, unpdf, requests, etc.) + torch CPU wheel + transformers.
- Refine the pytest -k filter to deselect the GPU/introspection-bound
classes by name. Deselections are commented inline with the reason.
- wheel-smoke uses the same dep set so the import smoke matches.
Locally validated against the freshly-built unsloth-2026.5.2 wheel:
831 passed, 5 skipped, 35 deselected, 0 failed in 47s
Studio backend imports cleanly in a fresh venv after the wheel install.
* CI: collapse multiline pytest -k expression to a single line
YAML's | block-scalar fed the newlines verbatim into the -k argument and
pytest rejected it as 'Wrong expression passed to -k'. Same logical filter
on one line.
* CI: rename jobs so the GitHub UI shows what each check actually does
Adds a per-job 'name:' to all four workflows so the PR check list reads:
Studio pin enforcement / @assistant-ui must be pinned exactly
Studio frontend CI / Frontend build + bundle sanity
Studio backend CI / Backend pytest (Python 3.10|3.11|3.12)
Studio backend CI / Backend ruff lint (non-blocking)
Wheel build + smoke / Wheel build + content sanity + import smoke
Instead of the default '<workflow> / <job-key>' which was opaque
('check', 'build', 'pytest (3.10)', 'ruff', 'wheel').
* CI: add Python 3.13 to backend pytest matrix
Verified locally: 831 backend tests pass under Python 3.13 with the same
filter set used for 3.10 / 3.11 / 3.12.
* CI: add Studio inference smoke + Tauri build smoke
Two new workflows. Both CPU-only, both free on `ubuntu-latest`.
studio-inference-smoke.yml
The only workflow we have that proves "Studio actually works", as opposed
to "the bundle parses" or "the imports succeed":
- runs install.sh --local --no-torch (lean Studio install)
- downloads unsloth/gemma-4-E2B-it-GGUF UD-IQ3_XXS into actions/cache
- boots Studio in api-only mode
- logs in with the bootstrap password, changes it, re-logs
- POST /api/inference/load on the GGUF
- POST /api/inference/chat/completions and asserts a non-empty
assistant response
Validated end-to-end locally on a fresh main install: model loaded,
chat completion returned `Hello!` against the same GGUF the workflow
uses.
studio-tauri-smoke.yml
PR-time variant of release-desktop.yml. Linux-only debug build
(`tauri build --debug --no-bundle`) on ubuntu-22.04. Catches
src-tauri Cargo.toml / Rust source breakage, tauri.conf.json drift,
and frontend-distDir wiring. Pinned to the same Tauri CLI version
(2.10.1) as release-desktop.yml so CLI bumps surface in CI before
they break the release pipeline. Mac and Windows desktop builds
stay manual via release-desktop.yml because they need code-signing
secrets.
* CI: use 'hf download' instead of deprecated 'huggingface-cli download'
huggingface_hub 1.13.0 dropped the huggingface-cli entrypoint. The
replacement is the 'hf' CLI shipped with the same package. Same args,
just s/huggingface-cli/hf/.
* CI: assert llama.cpp prebuilt path was used on ubuntu-latest
The inference-smoke job runs on ubuntu-latest (CPU-only, x86_64), which
is exactly the host shape that should pick up ggml-org/llama.cpp's
bin-ubuntu-x64.tar.gz prebuilt directly. If install.sh ever falls back
to a source build on this runner, the studio/setup.sh routing has
regressed and every CPU-only Linux user is paying a 3 minute compile
cost again.
Tee install.sh output to logs/install.log, then fail the job if the log
contains "falling back to source build" or is missing the success
marker "prebuilt installed and validated" / "prebuilt up to date and
validated".
Also include logs/install.log in the failure artifact so the prebuilt
diagnostics are uploaded alongside studio.log when the job fails.
* Tighten prebuilt-assertion comment in studio-inference-smoke
* CI: switch inference-smoke model to Qwen3.5-2B UD-IQ3_XXS
Drops the Gemma 4 E2B GGUF (~2.3 GB) for unsloth/Qwen3.5-2B-GGUF
(UD-IQ3_XXS, ~890 MiB). Cache-miss download is roughly a third of
what it was, and CPU inference on ubuntu-latest finishes well
inside the 25 minute job budget.
Verified locally: load via /api/inference/load returns
status=loaded, is_gguf=true, supports_reasoning=true,
supports_tools=true; chat completion returns a non-empty assistant
message ("Hello!").
* CI: add workflow_dispatch to inference-smoke for manual cache pre-warm
* CI: fold pin-enforce grep into studio-frontend-ci, drop standalone workflow
The "@assistant-ui must be pinned exactly" check was its own ~7 second
workflow, doing a single grep on studio/frontend/package.json. Move it
into studio-frontend-ci.yml as a pre-install step (right after
checkout, before any node setup so a violation fails fast). One fewer
top-level check row on every PR, same coverage.
Add a FIXME so this step is dropped once @assistant-ui/* and
assistant-stream leave 0.x: on 1.x, caret ranges are conventional and
this becomes overzealous.
* CI: add Repo tests (CPU) job, mirroring unsloth-zoo PR #624 conftest
The top-level tests/ tree was previously not run anywhere. 23 of its
files are CPU-friendly with the right harness: pure-Python helpers,
ast walks, installer logic, and CLI shape tests. Locally validated:
302 passed, 9 skipped, 12 deselected in ~7 seconds on Python 3.12.
Three pieces:
1. tests/conftest.py -- GPU-free harness, mirrors the conftest landed
in unslothai/unsloth-zoo PR #624. Pre-loads unsloth_zoo.device_type
and unsloth.device_type under a temporarily-mocked
torch.cuda.is_available() so each module's @cache permanently
captures "cuda" and the import chain succeeds on a CPU runner.
Also stubs torch.cuda.get_device_capability /
is_bf16_supported / mem_get_info, which unsloth/__init__.py and
unsloth_zoo.temporary_patches probe at import time when
DEVICE_TYPE == "cuda". On a real accelerator the harness is
skipped and detection runs normally.
2. Two existing tests were leaking sys.modules state across the
session because they injected stubs without an __spec__ and
without restoration:
- tests/test_raw_text.py shoved a "datasets" stub into
sys.modules. transformers' import_utils later did
importlib.util.find_spec("datasets") and got
ValueError: datasets.__spec__ is None.
- tests/python/test_fast_sentence_transformer_redirect_lifecycle.py
shoved "transformers", "sentence_transformers", and
"sentence_transformers.models" stubs in. Subsequent tests
that did `import transformers` got the non-package stub.
Fix: set __spec__ on stubs, plus an autouse fixture in the
sentence-transformer test file that restores the three keys
after each test.
3. .github/workflows/studio-backend-ci.yml gains a third job,
`Repo tests (CPU)`, that installs the same dep set as the
backend-pytest matrix (Python 3.12 only -- the tests are
version-independent), exports PYTHONPATH=studio so tests/python/*
can import install_python_stack, and runs the 23-file subset
above with `-m 'not server and not e2e'`.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* CI: install unsloth_zoo for Repo CPU tests, harden conftest fallback
The CPU job at run 25422050018 broke at conftest collection: the
preload of unsloth.device_type pulled in `from unsloth_zoo.utils import
Version` and ubuntu-latest didn't have unsloth_zoo on the path because
it is an optional dep of unsloth. Two fixes:
1. Install unsloth_zoo>=2026.5.1 alongside the other deps in the Repo
tests (CPU) job (it's also what unsloth's optional `huggingface`
extra pins).
2. Wrap the body of _preload_device_type in conftest.py in a try/except
so any import failure (missing prereq, broken module, etc.) cleanly
returns False instead of aborting the entire collection. The caller
already falls back to the stub device_type module on False, so the
net behavior is "best effort: real device_type if possible, stub
otherwise" instead of "abort the test session".
* kernels.utils: guard CUDA_STREAMS / XPU_STREAMS init for DEVICE_COUNT==0
When DEVICE_COUNT is 0 (CPU host: no visible NVIDIA / AMD / Intel GPU)
the dict comprehension {... for i in range(0)} was empty and the
subsequent max(_CUDA_STREAMS.keys()) raised
ValueError: max() iterable argument is empty
during module import. That made unsloth.kernels.utils unimportable on
any CPU runner, which in turn blocked all of tests/saving/**, three
top-level tests/test_*.py, and tests/qlora/test_unsloth_qlora_train_and_merge.py
from even collecting on CPU CI.
Wrap the per-device-index dict comprehension and max() machinery in
a DEVICE_COUNT > 0 guard. When DEVICE_COUNT is 0 fall back to empty
containers (CUDA_STREAMS = (), WEIGHT_BUFFERS = [], ABSMAX_BUFFERS = []).
The consumer functions further down in this module index these arrays
by device_index but only during real GPU work, so the empty fallbacks
never get touched on a CPU host.
GPU-safety verified locally: with 8 visible CUDA devices, CUDA_STREAMS
has 8 entries (identical to before this PR). With CUDA_VISIBLE_DEVICES=""
the module imports cleanly, CUDA_STREAMS is (), and the previously
blocked tests now collect (test_get_model_name passes 38 subtests,
test_resolve_model_class passes 9, test_model_registry collects all 8
parametrizations).
Same shape applied to the DEVICE_TYPE == "xpu" branch for symmetry.
* CI: switch Repo tests (CPU) to auto-discovery + isolate flakes
Three changes, locally validated end-to-end (779 passed, 11 skipped,
23 deselected, 0 failed across all three steps):
1. Repo tests (CPU, auto-discovered): replace the explicit 23-file
list with `pytest tests/` plus a small set of `--ignore` and
`--deselect` flags. New tests under tests/python, tests/studio
(excluding the two state-sensitive files), and top-level
tests/test_*.py are picked up automatically with no workflow edit.
--ignore covers:
- tests/qlora and tests/saving: GPU-bound by design
- tests/utils: helpers folder, not tests
- tests/sh: shell suite handled in its own step
- two state-polluting hardware-spoof files (next step)
-m 'not server and not e2e': honours markers already declared
in tests/python/conftest.py
--deselect: test_model_registration / test_all_model_registration
hit huggingface_hub live; they belong on a network job
2. Hardware-spoof tests (state-sensitive, run in isolation):
tests/studio/test_hardware_dispatch_matrix.py and
tests/studio/test_is_mlx_dispatch_gate.py mutate module globals
in studio.backend.utils.hardware.hardware (IS_ROCM, DEVICE) via
their spoof fixtures, and the leak crosses file boundaries.
Running them in their own pytest invocation avoids polluting the
main sweep. Both pass cleanly in isolation: 28 passed, 1 skipped.
3. Shell installer tests: explicitly enumerated subset that does not
depend on install.ps1 layout (test_install_host_defaults.sh has
drifted; that's a separate followup).
Test fixes folded in to keep the run green:
- tests/studio/install/test_rocm_support.py::TestAmdGpuMonitoring
::test_amd_primary_gpu_with_mock now clears
HIP/ROCR/CUDA_VISIBLE_DEVICES via monkeypatch so
_first_visible_amd_gpu_id() does not short-circuit when the runner
sets CUDA_VISIBLE_DEVICES="" to suppress CUDA.
- tests/studio/test_hardware_dispatch_matrix.py::spoof_hardware
fixture now stubs torch.cuda.get_device_properties when
cuda_available is True so detect_hardware()'s device_name probe
does not call into _cuda_init() on a CPU runner.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* CI: install torchvision (CPU) so unsloth_zoo.vision_utils can import
Run 25430652224 collected three test modules that import unsloth and
crashed at unsloth_zoo/vision_utils.py:68 with
ModuleNotFoundError: No module named 'torchvision'
unsloth_zoo.vision_utils unconditionally imports torchvision at module
scope, and unsloth.models._utils pulls vision_utils in. The Repo tests
(CPU) job installed torch from the CPU index but not torchvision, so
any test that imports unsloth.models.* failed at collection.
Add torchvision<0.26 to the same pip install --index-url
https://download.pytorch.org/whl/cpu line.
* CI: install bitsandbytes (CPU build) for unsloth.models._utils import
Run 25430982243 collected three test modules that import unsloth and
crashed at unsloth/models/_utils.py:1166 with
ModuleNotFoundError: No module named 'bitsandbytes'
The bnb import there is unconditional. Recent bnb versions (>=0.45)
ship a CPU build so the wheel installs on a free Linux runner and the
import resolves; the kernels still raise on use but the module
collects, which is enough for these CPU tests.
Add 'bitsandbytes>=0.45' to the Repo tests (CPU) deps.
* CI: rename workflows + guard kernels.utils CPU-torch binding
Workflow renames (top-level `name:` keys; affects PR check rows):
Studio backend CI -> Backend CI
Studio frontend CI -> Frontend CI
Studio inference smoke -> Studio GGUF CI
Studio Tauri smoke -> Studio Tauri CI
Wheel build + smoke -> Wheel CI
Backend CI's matrix job goes from "Backend pytest (Python 3.10)" to
just "(Python 3.10)" so the GitHub UI row reads
"Backend CI / (Python 3.10)" rather than the old verbose form.
Production guard for CPU torch (run 25431126138):
unsloth/kernels/utils.py:165 was an unconditional
_gpu_getCurrentRawStream = torch._C._cuda_getCurrentRawStream
which raised AttributeError on a CPU-only torch wheel because the
compiled CUDA backend is absent. Three test modules (test_get_model_name,
test_model_registry, test_resolve_model_class) crashed at collection
because their import chain reaches this line.
Add a hasattr probe: when torch is built without CUDA, fall through to
a no-op binding that returns 0. _get_tensor_stream is only invoked
during real GPU work, so the no-op is never executed on a CPU host.
GPU-safety verified locally: with 8 visible CUDA devices the binding
still resolves to the real torch._C._cuda_getCurrentRawStream
(behaviour identical to before this PR). The XPU branch is untouched.
* [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>
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Wasim Yousef Said
|
507417579f |
Fix Studio desktop tray installer and titlebar and bux fixes (#5179)
* fix(tauri): dedupe tray and brand nsis installer * feat(tauri): add linux windows custom titlebar * Fix desktop auth gate after backend startup * Fix desktop installer assets and setup script skew * Scope setup failure exit to Tauri installer * fix desktop updater production channel * fix desktop auth runtime installer regressions * fix desktop dev cors retry * fix tauri process generation race * feat desktop diagnostics support report * fix tauri apt update best effort * Fix Windows desktop NSIS installer upgrades * Start managed backend after desktop install * Improve NSIS installer branding resolution * Fix assistant-ui internal import * Fix desktop release workflow * Keep desktop auth retry on cached backend --------- Co-authored-by: wasimysaid <wasimysaid@users.noreply.github.com> |
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Wasim Yousef Said
|
a5eb2e3d50 |
Add tauri (#5144)
* add unsloth studio desktop app
* Fix review findings
- studio/src-tauri/tauri.conf.json: retarget updater to staging repo
(danielhanchen/unsloth-staging-2); switch to unslothai/unsloth on upstream merge.
- studio/src-tauri/linux/postremove.sh: drop the interactive read loop and the
/home/* iteration. Package maintainer scripts must stay non-interactive and
must not touch other users' data.
- studio/frontend/src/app/auth-guards.ts: honor tauriAutoAuth() boolean. Failed
auto-auth now redirects to /login; requireGuest/requirePasswordChangeFlow
only redirect to /chat when auth succeeds. The new early-return on failed
auth is intentional so the login / change-password flows remain reachable
when desktop auth is not yet established.
- studio/frontend/src/config/env.ts: keep fetched=false on health failure so
later calls retry instead of caching the client-side platform guess.
- studio/src-tauri/src/install.rs: pick the available system package manager
(apt-get, dnf, zypper, pacman); AppImage bundles run on non-Debian distros.
- studio/frontend/src/lib/open-link.ts + markdown-text/sources callers: return
boolean from openLink so callers only preventDefault on handled URLs; relative
hrefs now navigate natively.
- studio/frontend/src/features/settings/tabs/about-tab.tsx: fetch(apiUrl(...))
so the version request targets the backend port in desktop mode. The bare
/api/health predates the Tauri webview (blame: the earlier onboarding commit,
which ran with same-origin frontend/backend); in desktop mode the webview
origin is tauri://localhost so the bare path fails.
- install.ps1: gate the install_python_stack.py hotfix on a sentinel comment
instead of a content regex; append the sentinel after applying so reruns
are unambiguous.
- unsloth_cli/commands/studio.py _write_auth_secret: use the atomic mkstemp +
os.replace path on Windows too; chmod calls are wrapped in try/except OSError.
- studio/src-tauri/src/preflight.rs probe_existing_backends: fan out the health
probes concurrently; desktop-auth status still runs sequentially per candidate.
reqwest::Client is internally Arc-wrapped so the in-loop .clone() is a
refcount bump, not a deep clone; annotated inline.
- studio/src-tauri/src/preflight.rs run_cli_probe: wait() after kill() to reap
the child, matching probe_cli_capability.
- studio/src-tauri/src/process.rs + main.rs: add stop_backend_detached and use
it from the tray quit handler so the 5s graceful-wait does not block the
Tauri main loop. RunEvent::Exit keeps the synchronous safety-net call.
- studio/backend/main.py: drop the permissive localhost CORS regex in
api-only mode; the explicit allow_origins list is sufficient.
- .github/workflows/release-desktop.yml: drop max-parallel: 1 so platform
builds run in parallel, and lift releaseBody to an env var so the three
tauri-action invocations share one source of truth.
* Fix review findings (loop 2)
- studio/backend/auth/storage.py update_password: clear_desktop_secret()
alongside clear_bootstrap_password() so rotating the admin password
also revokes any previously provisioned .desktop_secret. Without this,
an old local desktop credential keeps minting fresh admin tokens via
/api/auth/desktop-login after a password rotation.
- studio/src-tauri/src/desktop_auth.rs provision_desktop_auth: wrap
cmd.output().await in tokio::time::timeout(30s). DESKTOP_AUTH_LOCK is
held across the whole desktop_auth flow, and previously a hanging
`unsloth studio provision-desktop-auth` subprocess would pin the lock
indefinitely and freeze every subsequent desktop_auth call.
* Add review tests
* Consolidate review tests
Merge review-added tests into the existing studio/backend/tests/test_desktop_auth.py
(the PR's authoritative desktop-auth test file). Drops three scaffolding files under
tests/python/ in favor of five focused tests next to the tests they extend:
- test_update_password_clears_desktop_secret (runtime)
- test_update_password_on_unknown_user_leaves_desktop_secret_intact (runtime)
- test_cli_provisioning_delegates_to_storage_create_desktop_secret (source-level)
- test_cli_connect_auth_db_reads_storage_db_path (source-level)
- test_desktop_auth_provision_has_bounded_timeout (Rust source-level)
* Revert auth-guards.ts Tauri branches to unconditional form
The review loop on PR 5144 introduced a regression: the isTauri branch of
requireAuth redirected to /login when tauriAutoAuth() returned false, and
requireGuest / requirePasswordChangeFlow silently fell through on the same
condition. The Tauri desktop app authenticates via a local auto-generated
secret; it must never surface /login or /change-password to the user. A
failed auto-auth should let the startup layer retry, not expose a password
form.
Restore the three Tauri branches to the author's original unconditional
form (requireAuth: return; requireGuest / requirePasswordChangeFlow: throw
redirect({to: '/chat'})). Keep the rest of the review fixes -- the
apiUrl() fetch wrapping, authRedirect helper, and fetchAuthStatus refactor
are all legitimate improvements and are preserved.
* Revert release-desktop.yml to author's version
The review loop's workflow-file tweaks (drop max-parallel: 1, lift releaseBody
to an env var) are cosmetic. OAuth tokens cannot push workflow-file changes,
and fine-grained PATs cannot honor maintainerCanModify on a third-party fork.
Reverting the workflow file to wasimysaid's version lets the push go through
without needing a classic PAT with both repo and workflow scopes.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Daniel Han <unslothai@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Daniel Han
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6872c6e850 |
Remove advanced CodeQL workflow in favor of default setup (#4584)
The repo has both the CodeQL "default setup" (configured in repo settings) and this advanced workflow file enabled. GitHub does not allow both simultaneously, causing all PR CI runs to fail with: "CodeQL analyses from advanced configurations cannot be processed when the default setup is enabled" Since the default setup already covers the same languages (Python, JavaScript/TypeScript) with the same build-mode (none), remove the redundant advanced workflow file. |
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dependabot[bot]
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f294161e26 |
build(deps): bump the actions group with 2 updates (#4570)
Bumps the actions group with 2 updates: [actions/checkout](https://github.com/actions/checkout) and [github/codeql-action](https://github.com/github/codeql-action). Updates `actions/checkout` from 4 to 6 - [Release notes](https://github.com/actions/checkout/releases) - [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md) - [Commits](https://github.com/actions/checkout/compare/v4...v6) Updates `github/codeql-action` from 3 to 4 - [Release notes](https://github.com/github/codeql-action/releases) - [Changelog](https://github.com/github/codeql-action/blob/main/CHANGELOG.md) - [Commits](https://github.com/github/codeql-action/compare/v3...v4) --- updated-dependencies: - dependency-name: actions/checkout dependency-version: '6' dependency-type: direct:production update-type: version-update:semver-major dependency-group: actions - dependency-name: github/codeql-action dependency-version: '4' dependency-type: direct:production update-type: version-update:semver-major dependency-group: actions ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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Pete Kloehn
|
efedbe9740 |
Feature/add dependabot and codeql security checks (#4479)
* Add CodeQL analysis workflow configuration * Add Dependabot configuration for package updates Configure Dependabot to check for updates in various ecosystems weekly. * Fix dependabot.yml: bun ecosystem, missing dir, grouping for PR #4479 1. studio/frontend uses bun.lock not package-lock.json, so change npm to bun 2. Add missing studio/backend/requirements/ pip entry (consumed by studio/setup.sh) 3. Add groups with patterns ["*"] to all pip/bun/npm entries to batch updates and avoid 30+ individual Dependabot PRs on the first run * Consolidate pip blocks to fix overlapping directory violation GitHub Dependabot forbids multiple same-ecosystem entries with overlapping directories on the same branch. The root "/" directory overlapped the 3 nested pip dirs. Merge all 4 pip blocks into one using the `directories:` (plural) key. Also remove redundant open-pull-requests-limit from the bun block since grouping with patterns: ["*"] already limits PR count. --------- Co-authored-by: Daniel Han <danielhanchen@users.noreply.github.com> |
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Pádraic Slattery
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a09bdb6adb | chore: Update outdated GitHub Actions version (#3936) | ||
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Dan Saunders
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a3ed3c395d | remove pre-commit workflow (covered by pre-commit app) (#3618) | ||
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Daniel Han
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d6bb89ad44 |
Formatting & bug fixes (#3563)
* Update rl.py * Fix CE Loss * Versioning * Update loader.py * Update loader.py * extract_model_type_from_config * Model types * Update loader.py * get_transformers_model_type * Update loader.py * Update loader.py * Update loader.py * Update rl.py * Update pyproject.toml * Update loader.py * Update loader.py * Update loader.py * Update loader.py * Versioning * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update vision.py * Update vision.py * Fix DataParallel * Update _utils.py * Update rl.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update mapper.py * Versioning * Update loader.py * Update loader.py * Update rl.py * Versioning * Update _utils.py * Fix auto_mapping * Update loader.py * Update loader.py * Update vision.py * Update vision.py * Update loader.py * Message * Update vision.py * Update loader.py * Update vision.py * cache_implementation * Update vision.py * Update loader.py * Update vision.py * Update vision.py * Update vision.py * Update loader.py * Update vision.py * Save max_seq_length * Update _utils.py * Update rl.py * Update vision.py * Update llama.py * Mistral3 vllm (#3349) * [WIP] use vLLM for vision language models * Update README.md Editing icon sizes * Update README.md Updating icon sizes * Update README.md (#2885) * MoE kernels AGPLv3 * versioning * Many bug fixes (#2908) * add deepseek v3 * add deepseek r1 base * add deepseek r1 zero * add deepseek distill llama * add deepseek distill models * remove redundant code when constructing model names * add mistral small to registry * rename model registration methods * rename deepseek registration methods * refactor naming for mistral and phi * add global register models * refactor model registration tests for new registry apis * add model search method * remove deprecated registration api * add quant type test * add registry readme * make llama registration more specific * clear registry when executing individual model registration file * more registry readme updates * Update _auto_install.py * Llama4 * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Synthetic data * Update mapper.py * Xet and Synthetic * Update synthetic.py * Update loader.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update pyproject.toml * Delete .gitignore * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update _utils.py * Update pyproject.toml * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update chat_templates.py * Seasame force float16 / float32 * Fix Seasame * Update loader.py * Update vision.py * Update vision.py * Update vision.py * Update loader.py * is_multimodal * Update loader.py * Update loader.py * Update loader.py * Update loader.py * Update vision.py * Update vision.py * Update vision.py * UNSLOTH_DISABLE_STATIC_GENERATION * Update vision.py * Auto vision detection * Sesame * Whisper * Update loader.py * Update loader.py * Update loader.py * Update mapper.py * Update vision.py * Update vision.py * Update vision.py * Update vision.py * Update vision.py * Update vision.py * Update loader.py * Update loader.py * Update loader.py * Update loader.py * Update _utils.py * Update rl.py * versioning * Update rl.py * Update rl.py * Update rl.py * Update rl.py * Update rl.py * logging * Update pyproject.toml * Update rl.py * versioning * Update rl.py * Update rl.py * Update rl_replacements.py * Update rl_replacements.py * Update rl.py * Update rl_replacements.py * Update rl_replacements.py * logits / temperature * Update rl_replacements.py * Update pyproject.toml * Update rl_replacements.py * Update rl_replacements.py * Debugging only * Update llama.py * Update llama.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Generic efficient GRPO * Update rl_replacements.py * Update rl_replacements.py * Remove debugging * Update rl_replacements.py * Update rl_replacements.py * Update vision.py * Update llama.py * Update rl_replacements.py * versioning * Update _utils.py * Update vision.py * Update mapper.py * Update loader.py * Update mapper.py * Update vision.py * Update loader.py * Update vision.py * Update loader.py * Update _utils.py * Update vision.py * gradient checkpointing * Gemma 3N fixes * Update loader.py * Versioning * Gemma 3N fixes * Update vision.py * Update vision.py * Update loader.py * Update vision.py * Fix setup.py * setup.py * Prints * Update setup.py * Update setup.py * Update setup.py * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Update vision.py * Update vision.py * Update pyproject.toml * Update vision.py * Update _utils.py * Update __init__.py * Update __init__.py --------- Co-authored-by: jeromeku <jerome.ku@gmail.com> Co-authored-by: Michael Han <107991372+shimmyshimmer@users.noreply.github.com> * silienty skip falcon h1 import is transformers_version < 4.53.0 (#2912) * Dynamically adjust get_per_token_logps function and patch as well (#2911) * add intel gpu with vllm support (#2903) * [bugs] fix for casual mask (#2868) * fix for casual mask * use un_casual in sdpa * add missing mask * fix for type * Explicitly check if xformers exists for attention (#2889) * Update __init__.py * Update llama.py * if mlp doesn't exist in layer module check for feed_forward name for falcon h1 (#2913) * Move inputs to right devices. (#2919) * Move tensors to right devices * fix multi gpu for non mistral models * multi GPU RoPE for gemma2 * Finish up multi GPU inference * Make multiGPU rope a list * Remove unnecessary transfer to CPU * Remove unnecessary move to CPU * Donot move inputs to device yet will be handled separately in another PR * Move inputs to appropriate decoder device * Make device count global variable * Cleanup RoPE device code * Fixup num_gpu to device count * Cleanup device counts * Use device index for RoPE get_cache * Donot typecast * Use tuple instead of list for tensors. Use device index directly * fixup move to device logic * WIP VLM vLLM * Make vLLM patch a function * Add save and load lora functions * Make fast_inference setup depend on the flag * Improve fast inference patching mechanism * Make vision setting depend on checks in fastbasemodel * Check LoRA and vLLM intercompatibility for vision models * Comment pointing to vLLM LoRA check * Improve lora validation on vLLM * Error out on no vLLM and increase max lora rank * Bug fixes (#3017) * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update pyproject.toml * Delete .gitignore * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update _utils.py * Update pyproject.toml * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update synthetic.py * Update chat_templates.py * Seasame force float16 / float32 * Fix Seasame * Update loader.py * Update vision.py * Update vision.py * Update vision.py * Update loader.py * is_multimodal * Update loader.py * Update loader.py * Update loader.py * Update loader.py * Update vision.py * Update vision.py * Update vision.py * UNSLOTH_DISABLE_STATIC_GENERATION * Update vision.py * Auto vision detection * Sesame * Whisper * Update loader.py * Update loader.py * Update loader.py * Update mapper.py * Update vision.py * Update vision.py * Update vision.py * Update vision.py * Update vision.py * Update vision.py * Update loader.py * Update loader.py * Update loader.py * Update loader.py * Update _utils.py * Update rl.py * versioning * Update rl.py * Update rl.py * Update rl.py * Update rl.py * Update rl.py * logging * Update pyproject.toml * Update rl.py * versioning * Update rl.py * Update rl.py * Update rl_replacements.py * Update rl_replacements.py * Update rl.py * Update rl_replacements.py * Update rl_replacements.py * logits / temperature * Update rl_replacements.py * Update pyproject.toml * Update rl_replacements.py * Update rl_replacements.py * Debugging only * Update llama.py * Update llama.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Generic efficient GRPO * Update rl_replacements.py * Update rl_replacements.py * Remove debugging * Update rl_replacements.py * Update rl_replacements.py * Update vision.py * Update llama.py * Update rl_replacements.py * versioning * Update _utils.py * Update vision.py * Update mapper.py * Update loader.py * Update mapper.py * Update vision.py * Update loader.py * Update vision.py * Update loader.py * Update _utils.py * Update vision.py * gradient checkpointing * Gemma 3N fixes * Update loader.py * Versioning * Gemma 3N fixes * Update vision.py * Update vision.py * Update loader.py * Update vision.py * Fix setup.py * setup.py * Prints * Update setup.py * Update setup.py * Update setup.py * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Update vision.py * Update vision.py * Update pyproject.toml * Update vision.py * Update _utils.py * Update __init__.py * Update __init__.py * Small fixes * Update vision.py * Update vision.py * versioning * Update __init__.py * Update llama.py * Update rl.py * Update rl.py * Update _utils.py * Update vision.py * Update vision.py * compiler stance * Update _utils.py * Update pyproject.toml * Update pyproject.toml * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Update rl.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Update rl_replacements.py * Revert "Revert "Add Qwen2.5-VL-32B-Instruct mapping to fix quantized model me…" (#2990) This reverts commit |
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Daniel Han
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fba0bff2f4 | Remove stale bot | ||
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Daniel Han
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b0088817cd | Update stale.yml | ||
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Daniel Han
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95d2bdbec3 | Create stale.yml (#2836) | ||
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Daniel Han
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550f19fc0d | Delete stale.yml | ||
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Daniel Han
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901c3216d0 | Update stale.yml | ||
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Daniel Han
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cc69f5c3cb | Create stale.yml (#2832) | ||
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Daniel Han
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4d4d5e6da2 | Delete stale.yml | ||
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Daniel Han
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018f7677a5 | Update stale.yml | ||
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Daniel Han
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c396630163 | Create stale.yml |