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3 commits

Author SHA1 Message Date
Anish Umale
d0f8d40c36
studio: allow updating HF models through UI (#5388)
* add models for /update endpoint

* add logic for identifying out of date hf models

* add endpoint for updating hf models

* add relevant field to GgufVariantDetail

* make exception handling better

* add update_available flag for cached_models, and moved /update endpoint from inference -> models

* hook up /update endpoint on the frontend

* implement update scenarios for the model picker

* fix bug where downloaded flag for an older revision was being wrongly set to false

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* fix import and make hf calls async

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* remove has_vision from UpdateRequest

* fix ci

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* clear cancel event before updating gguf variant

* set _cancel_event back if it was set initially

* add hf_token to get_paths_info

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* studio: harden model update endpoint and update checks

- update_hf_model: pass snapshot_download local_dir (local_path is not a
  valid kwarg and 500s when updating bicodec audio models)
- get_gguf_variants: wrap the remote update check so a network, rate-limit,
  gated, or offline failure degrades to "no update info" instead of failing
  the whole variant listing, matching list_cached_models
- add regression tests for both paths

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* Studio: HF model update detection and Update action for cached models

Surface an "Update available" cue and a managed Update action for cached
on-device models. /api/hub/update-status compares each cached main GGUF
file's local blobs against the remote main revision using set membership
across all cached revisions, so a repo that was already updated (and still
holds the old snapshot alongside the new one) is not falsely flagged.

The Update action re-downloads through the download manager so it shows in
the Downloads panel with progress and cancel. The frontend wires the Update
button into the GGUF, on-device, and model-selector cards and keeps the
quant label fully visible when the action buttons crowd the row.

Adds regression tests for the multi-revision update check.

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* Studio: accept force_download kwarg in hf_xet_fallback test double

The download seam now passes force_download to the attempt callable; the _FakeAttempt mock did not accept it, failing 6 tests with TypeError. Add the keyword (default False) so the scripted-results double matches the seam.

* Fix Studio model update regressions

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* Address Studio update review feedback

* Address Studio update edge cases

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* Share GGUF update status helper

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* Fix GGUF update detection and cache cleanup

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* Fix cached GGUF update badges

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: shimmyshimmer <107991372+shimmyshimmer@users.noreply.github.com>
Co-authored-by: Etherll <61019402+Etherll@users.noreply.github.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
2026-07-01 01:54:57 +03:00
Daniel Han
8e0d082c92
Reap Studio child processes when the parent dies abnormally (#6425)
* Reap Studio child processes when the parent dies abnormally

Standalone `unsloth studio` launches orphaned cloudflared and llama-server when
the parent exited without running the cooperative shutdown path (terminal-window
close, Task Manager End Task, SIGKILL): the children reparented to init and kept
running, leaving an authenticated Cloudflare tunnel up for days.

Add utils/process_lifetime.py: a parent-owned Windows Job Object
(JOB_OBJECT_LIMIT_KILL_ON_JOB_CLOSE, children auto-inherit) plus Linux
PR_SET_PDEATHSIG, behind a best-effort helper that mirrors the desktop app's
windows_job.rs. initialize_parent_lifetime() runs at the top of run_server;
long-lived spawns (cloudflared, llama-server, RAG embedder, llama.cpp updater)
get the PDEATHSIG preexec, multiprocessing workers are adopted into the job, and
_graceful_shutdown plus atexit gain a terminate_all() backstop sweep. The
cooperative shutdown path is otherwise unchanged.

Verified on Linux: killing the parent now reaps cloudflared and llama-server
within ~2s instead of orphaning them.

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* test: add real Windows kill-on-job-close integration test

Spawn a parent that installs the job and a child that inherits it, terminate
the parent, and assert the child is reaped. Skipped off Windows. Also make the
liveness probe Windows-safe (os.kill(pid, 0) terminates on Windows).

* Fix Win64 handle truncation in the Job Object calls

Set explicit argtypes so the 64-bit job/process handles are not marshaled as
c_int (which truncated them on Win64, failing AssignProcessToJobObject). Assert
install success in the Windows integration test.

* Bind multiprocessing workers to parent death; harden the sweep

Review follow-ups:
- Multiprocessing workers (inference/export/training/data-recipe/Xet) cannot be
  given a preexec_fn by the parent, so adopt_pid alone left them orphanable on a
  Linux SIGKILL. They now bind themselves with PR_SET_PDEATHSIG at startup via
  bind_current_process_to_parent_lifetime(), wired into the shared
  run_without_native_path_secret entrypoint and the Xet child entry.
- Wire the previously-missed data-recipe worker through adopt_pid.
- terminate_all now honors its timeout: SIGTERM, wait, then SIGKILL the
  survivors, so cooperative children can exit cleanly.
- Track adopted pids with a /proc starttime identity and add forget_pid, so the
  shutdown sweep never signals a recycled pid.

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Co-authored-by: Michael Han <michaelhan2050@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2026-06-18 05:51:22 -07:00
Daniel Han
58c2ec1ebd
Studio: Xet-primary model downloads with automatic HTTP fallback on stall (#6372)
* Studio: add shared Xet-primary download helper with HTTP stall fallback

Xet is the fast default transport in huggingface_hub, but a stalled Xet
transfer hangs with no progress and no exception, and a blocked native thread
cannot be killed. The safetensors inference path already recovers (subprocess
watchdog + respawn with HF_HUB_DISABLE_XET=1); the GGUF and training paths do
not. Add a reusable helper that the in-process paths can adopt.

utils/hf_xet_fallback.py:
- DownloadStallError (moved here from core/inference/orchestrator.py, which now
  imports it; behavior unchanged, still a RuntimeError subclass).
- get_hf_download_state / start_watchdog: a no-progress watchdog built on the
  sparse-aware hub.utils.hf_cache_state helpers; fires only while a .incomplete
  is present and the on-disk byte total is unchanged for stall_timeout.
- hf_hub_download_with_xet_fallback: cached files short-circuit; otherwise the
  download runs in a spawn child (own process group) supervised by the watchdog.
  On a stall it kills the child, makes the partial safe for HTTP via
  prepare_cache_for_transport, and respawns once with HF_HUB_DISABLE_XET=1. Cancel
  and deterministic errors (auth/missing/disk) propagate without a fallback.

Tests cover the watchdog state machine, the transport decision logic, and a
regression lock that HF_HUB_DISABLE_XET is honored in a fresh interpreter.

* Studio: route GGUF Chat-Mode downloads through the Xet->HTTP fallback

The GGUF load path (_download_gguf main+shards, _download_companion_gguf for
mmproj/MTP) called a bare blocking hf_hub_download with no recovery, so a Xet
stall hung the Chat-Mode load with no fallback. Route those three calls through
hf_hub_download_with_xet_fallback: Xet stays primary, HTTP is used only if Xet
stalls, per-file so finished shards stay cached. The existing _cancel_event is
threaded through, the Cancelled sentinel is preserved, and companions stay
best-effort (a terminal stall is swallowed to None). Cached files short-circuit
in the helper with no subprocess, so the fast path is unchanged.

The two offline mmproj tests are repointed from huggingface_hub.hf_hub_download
to the new call boundary (the helper) since the download now goes through it.

* Studio: recover a stalled training model-load via Xet->HTTP respawn

Training runs in a spawn subprocess and FastModel.from_pretrained downloads
internally, so the download cannot be wrapped per-file like GGUF. Instead the
worker now watches the HF cache during the model-load phase (emitting
model_load_started / model_load_completed and a stall event), and the parent
recovers a stall by terminating the worker and respawning it once with
HF_HUB_DISABLE_XET=1.

worker.py: set HF_HUB_DISABLE_XET=1 before any HF import when the parent passes
disable_xet (respawn), and wrap trainer.load_model with start_watchdog.

training.py: plumb disable_xet through the config; track the model-load window;
on a first-load stall arm a one-shot respawn (handled on the exiting pump thread,
so no pump self-join) that preserves the DB run row (history is not duplicated)
and re-runs the load over HTTP. A second stall, or a stall outside model-load,
surfaces as a normal error. W&B init happens after model-load, so a pre-load
respawn cannot duplicate it; the dataset is re-formatted in the new worker.

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* Studio: add gated test-only fault-injection hook for the Xet stall path

UNSLOTH_HF_XET_FORCE_STALL=1 makes the Xet download attempt write a partial
blob and hang, so the no-progress watchdog and the HTTP fallback can be
exercised end to end against a real repo (never set in production). Used to
verify recovery on real models: a forced Xet stall on a 5.37GB Qwen3.5-35B-A3B
shard triggered the watchdog and the HTTP retry downloaded the correct file
(sha256 verified).

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* Studio: tighten Xet-fallback comments and consolidate its tests

Trim docstrings and inline comments across the Xet->HTTP fallback code to
the non-obvious why (spawn-not-thread, killpg-not-getpgid, the sparse-partial
HTTP-resume hazard); drop comments that merely restate the code. Verified
comment-only with an AST signature check.

Merge the three helper-level test files (watchdog, transport policy, and the
HF_HUB_DISABLE_XET regression lock) into tests/test_hf_xet_fallback.py, and
prefer the real structlog over a bare stub so test collection order cannot
leak an incomplete module to others that log at import.

Full backend suite: 3455 passed, 14 pre-existing flash-attn failures only.

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2026-06-16 06:17:54 -07:00