* Raise the opencode invoke timeout in Local Agent Guides CI
The connection (opencode) cell flakes with a 600s timeout reported as guide drift, but it is not a hang: in a passing run the same opencode run finishes in ~482s (08:12:31 to 08:20:33), right against the shared AGENT_INVOKE_TIMEOUT of 600s, so about one run in six drifts past the cap.
opencode is the slow outlier. The print-mode agents (claude -p, codex exec) run one turn against a minimal injected system prompt, while opencode run runs its own full turn with opencode's large system prompt plus a separate small_model call to name the session (start.py pins small_model to the same 4B the server hosts). On a CPU-served gemma-4-E4B that is about 8 minutes, leaving no margin under 600s.
Double opencode's per-invoke timeout in agent-guides-drive.sh and keep the tight 600s cap for the fast agents, so a genuine headless-TTY hang still fails quickly. 1200s stays well under the 40-minute job budget.
* Normalize the agent invoke timeout before doubling it for opencode
Strip an optional trailing 's' from AGENT_INVOKE_TIMEOUT so the opencode
arithmetic, and the "${TIMEOUT}s" timeout message, stay valid if a
timeout(1)-style suffix is ever configured.
* Only double the opencode timeout for a bare-integer seconds value
Guard the arithmetic so a GNU timeout(1) duration suffix (s/m/h/d, including
floats like 0.5s) is passed through unchanged instead of breaking the
expansion; timeout(1) parses those directly. Bare seconds still double.
---------
Co-authored-by: danielhanchen <unslothai@gmail.com>
* Studio: GPU memory dropdown — llama.cpp --fit on and manual gpu-layers/cpu-moe
* Studio: simplify GPU memory changes (reuse ParamSlider, GPU_LAYERS_ALL, loadedGpuMemoryFields helper)
* Studio: GPU picker — choose which GPUs a GGUF model loads on (gpu_ids)
* Studio: simplify GPU picker (share /api/system fetch, validate gpu_ids)
* Studio: GPU picker review fixes (gate relative indices, no cross-model leak, validate, types)
* Studio: group GPU controls under a collapsible GPU section
* Studio: GPU feature review fixes (fix fit-ctx test, behavior-test the floor, comment accuracy)
* Studio: make GPU a top-level settings section (not nested under Model)
* Studio: flatten GPU controls into the Model section, group by GPU/context/generation
* Studio: move GPU Memory to the bottom of Model with its dependent controls beneath it
* Studio: move GPU Memory below Tensor Parallelism and GPUs below GPU Memory
* Studio: tighten GPU Memory and GPU Layers tooltip copy
* Studio: fix fit-mode context slider track-click, restore GPU Memory tooltip, shorten fit dropdown label
* Studio: GPU Memory tooltip one mode per line, briefer
* Studio: note HIP_VISIBLE_DEVICES (ROCm) in the GPUs picker tooltip
* Studio: narrow the GPU Memory dropdown to fit the shortened label
* Studio: use 'llama.cpp --fit' in the GPU Memory tooltip for consistency
* Studio: allow Tensor Parallelism in Manual GPU mode
* Studio: graduated MoE-on-CPU offload (--n-cpu-moe) replacing the all-or-nothing toggle
* Studio: size the MoE-offload slider for staged (deferred-load) models
* Studio: share one GGUF header walk for the context-length and MoE-count readers
* Studio: size the GPU Layers slider for staged models (one staged-header read)
* Studio: move Tensor Parallelism below the GPUs picker
* Studio: GPU split (--tensor-split) per-GPU model share in Manual mode
* Studio: tolerate whitespace in GPU split input, move it below GPU Layers
* Studio: rename the GPU split control to "Split ratio"
* Studio: Split ratio sends explicit even input; fix blank=free-VRAM (not even) copy
* Studio: tighten llama.cpp --fit VRAM margin with --fit-target 512
* Studio: GPU memory review fixes (rollback re-baseline, single-GPU TP gate, accurate copy)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: move Split ratio below MoE Layers on CPU
* Studio: address PR review (fix GPU-info hydration race, share fit context-length across load paths)
* Studio: address codex review (manual single-GPU TP guard, GPU-aware spec defaults in fit/manual, GGUF-only context/preference)
* Studio: address codex review round 2 (gpu_present seed, single-GPU tensor-split guard, staged manual-knob reset, strip inherited offload flags)
* Studio: address codex review round 3 (strip inherited --n-cpu-moe, CPU-fallback warning in Manual mode)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: address codex review round 4 (preserve pinned fit context across a later Apply)
* Studio: address codex review round 5 (honor GPU picker for diffusion GGUFs, clear fit pin on cross-model switch)
* Studio: preserve the pending GPU Memory mode when staging a model
* Studio: pin diffusion GPU device order and reset GPU-memory state for diffusion loads
* Studio: address codex review round 6 (fit-Auto rollback context, preserve manual non-tensor split modes, persist GPU mode on load not select)
* Studio: persist the applied GPU Memory mode, not the requested one (skip diffusion loads)
* Studio: replace Manual-mode split-ratio field with per-GPU layer sliders
* Studio: clarify per-GPU layer split hint for tensor-parallel mode
* Studio: address codex review round 7 (allow GGUF gpu_ids past the legacy guard, replay GPU-memory fields on respawn)
* Studio: address codex review round 8 (size the validate preflight like the load in fit mode, across both load paths)
* Studio: skip the training-OOM guard for llama.cpp --fit GGUF loads (they spill to RAM)
* Studio: drop the now-redundant compare-path validate sizing (the --fit guard skip makes it moot)
* Studio: address codex review round 9 (keep the training guard for fit loads, forward gpu_ids to validate, strip inherited manual tensor-split)
* Studio: address codex review round 10 (gate GPU-memory adoption on is_gguf, record manual knobs only in Manual mode)
* Studio: handle diffusion GGUFs symmetrically in the GPU Memory controls (preserve the standing mode preference, hide the inapplicable mode/TP controls)
* Studio: remember the GPU Memory settings per model
* Studio: consolidate --fit mode and Manual mode into a single Manual mode
* Studio: preserve the per-GPU layer split across GPU Layers changes
* Studio: trim overly long GPU Memory comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* address GPU memory config review comments
* trim redundant GPU memory tests
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Reconcile manual-mode TP drops with the #6659 drop-site invariants
* Preserve quantized KV in manual --fit, charge GGUF companions in full, reconcile GPU pick on load
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Clear stale GPU baseline on non-GGUF loads so it can't read as dirty
* Fix no-context-shift test for the conditional -c flag
* Credit manual GPU-layer offload for cached HF GGUFs
* Reset per-model load knobs on GGUF quant switch
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Strip inherited tensor-split when manual ratio is cleared
* Match auto-load validation to safetensors placement
* Reset editable manual knobs after Auto GGUF loads
* Record a single device for diffusion GPU picks
* Reset per-model GPU knobs before applying saved settings
* Address review comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Guard manual tensor splits and keep remembered context on auto-load
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Snapshot compare knobs, seed splits from free VRAM, flag zero-offload loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Exempt CPU-only loads from the guard floor and harden compare and reseed paths
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reach full offload from the layers slider and charge extras drafters in the guard
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Warm the GPU device cache before pick reconciles and disable staged GPU controls
* Align the training guard with inherited extras, spec mode, and compare targets
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Hide GPUs from companion-less zero-offload loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Size diffusion picks per device, own manual offload flags, reject XPU picks
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Drop tensor flags at zero layers and exempt CPU-pinned drafters
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Allowlist the zero-layer tensor parallel drop site
* Keep validate and load guards on the same extras and refresh stale baselines
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Drop mismatched manual tensor splits before launch
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Gate XPU picks on the real backend field and harden split and hydration paths
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Weight full GPUs as zero, clamp split shares, and refine the zero-layer mask gate
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Carry fit context across mode changes and align drafter and picker gates
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Catch variant switches, uncached diffusion repos, and text-only mmproj skips
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Check companions on the first device and size native and remote zero-layer loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Replace the training guard's precise VRAM modeling with a conservative bound
* Baseline context pins on non-GGUF hydration and reprobe list-seeded staged GGUFs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Size manual splits by their largest share and preserve resolved context from Default
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Default-deny unsized required companions and price KV at the effective cache dtype
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reserve MTP draft KV and MLA target-copy in the training guard
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Size tensor-parallel loads per device and show GPU controls for native GGUFs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Reserve MTP overhead for uncached remote GGUFs and the mmproj runtime factor
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Drop the training-coexistence VRAM estimation this PR added
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Gate remembered load settings to GGUF picks
* Lock the remaining load-time controls during a staged load
* Clear the stale native-path token on compare loads
* Drop a stale guard reference from the zero-offload masking comment
* Seed GPU baselines from the rollback response and drop never-emitted offload flags
* Match validate's training guard to load and keep the native reload token
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Trim verbose GPU-memory comments
* Thread the variants header walk off the event loop, honor device pins on zero-offload, and hold staged GPU edits
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Honor manual placement and classify pinned zero-offload loads
* Close diffusion admission and status hydration gaps
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Check the actual diffusion GPU during training
* Align staged baselines and manual reload dedupe
* Fix GGUF placement and rollback state
* Harden manual GGUF placement boundaries
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Remove unused resolve_tensor_parallel import in llama_cpp.py
The name is used only in llama_server_args.py, routes/inference.py, and tests,
not in llama_cpp.py; the unused hoisted import trips the import-hoist verifier
in the source-lint CI job.
* Fix diffusion GPU dedup and training guard for non-numeric device tokens
The diffusion runner drives only its single lowest device and the backend
records that one device (self._gpu_ids = [sorted(gpu_ids)[0]]), but the reload
dedupe compared it against the full requested list, so a multi-GPU pick that
resolves to the same device forced a needless reload. Normalize the request the
same way for a loaded diffusion model in both _already_in_target_state and the
route _request_matches_loaded_settings.
The chat-during-training coexistence guard called int() on the single-device
token and hard-rejected when it could not parse. A non-numeric token (a CUDA
UUID / MIG handle) now sizes against the whole visible pool like the GGUF guard
instead of falsely blocking the load, and an empty token (a CPU-only runner such
as a CPU diffusion GGUF) is allowed outright since it uses no GPU VRAM.
* Tighten comments added by the GPU memory config changes
* Harden GGUF placement from independent review: VRAM sizing, diffusion TP reset, tensor_split validation
- Training coexistence guard: a single-device runner pinned through an
unresolvable UUID/MIG token was sized against the aggregate visible-VRAM pool,
so a load could pass on capacity it cannot use and then OOM active training.
Size against the worst-case visible device (min free) instead, keeping the
guard's documented default-deny contract. The empty-token (CPU-only runner)
allow path is unchanged.
- Diffusion startup: _start_diffusion_server now resets self._tensor_parallel to
False alongside the other placement resets. A prior tensor-parallel chat load
(process killed but not fully unload-reset) otherwise left /status misreporting
tensor parallelism and made an identical diffusion re-Apply reload against the
stale state.
- tensor_split: reject negative / non-finite / all-zero splits up front. They
were dropped at launch but still compared raw in the reload dedupe, so an
identical Apply reloaded indefinitely.
- Tests: the shared httpx stub was incomplete and, installed via setdefault
before real httpx loaded, broke a combined pytest run (collection errors on
httpx.Response). Import the real installed httpx instead.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
* test(version-compat): keep GRPO fake-run logits finite on CPU
The GRPO fake-run test samples completions from a tiny untrained model on
CPU. Such a model can emit non-finite logits, so torch.multinomial inside
generate() intermittently raises "probability tensor contains either inf,
nan or element < 0" -- a nondeterministic sampling failure, not a regression
(the Trainer already fixes the seed, but CPU reduction order is not
bit-reproducible). Add a forward hook that sanitizes the LM head logits to a
finite bounded range before sampling, so the fake run reliably exercises the
whole train loop; the test checks the loop runs, not the numerics.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* test(version-compat): drop redundant nan_to_num bounds (clamp handles them)
* test(version-compat): scope GRPO finite-logits guard to the GRPO test
Only test_grpo_trains_on_cpu autoregressively samples completions, so it is
the only canary that can hit the non-finite-logits torch.multinomial crash.
Move the _guard_finite_logits hook out of the shared _load_plain() and into
test_grpo_trains_on_cpu so the SFT and DPO canaries keep asserting against the
model's true, unclamped logits.
---------
Co-authored-by: Daniel Han <unslothai@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* studio: show the active run's saved config in the Training Progress popover
The Training Config popover on the live Training Progress page read the
editable form store (useTrainingConfigStore), so it showed stale/static values
whenever the form changed after the run started; only the History view read the
run's saved config snapshot, which is why re-opening the same run from Recents
showed the correct values (#6853).
Wire the live view to the same authoritative source History already uses:
- Extract History's field mapping into sections/run-config-override.ts
(mapRunConfigToOverride) so both views share one mapper over
GET /api/train/runs/{id} config.
- LiveTrainingView fetches the run record as soon as the job id is known and
passes the mapped override to ProgressSection; the fetched config is keyed
by job id, and until it loads (or if the fetch fails) the form store remains
the fallback. The run record is created at job start, so it is available
while the run is live.
- ProgressSection prefers configOverride whenever one is present instead of
only when isHistorical, so the live override takes effect.
Adds a source-level regression test pinning the wiring and the mapper's
backend config keys.
Fixes#6853
* studio: retry the run-config fetch after the first step, carry the saved method
Two review fixes on the live Training Config popover source:
1. The backend creates the run row only on the first progress event, so the
fetch issued as soon as the job id appeared commonly 404'd during
model/dataset preparation and never retried -- leaving the popover on the
form store for the whole run. The effect is now also keyed on
firstStepReceived (and skips once resolved for the job), so it re-fetches
exactly when the row is guaranteed to exist.
2. The popover's method label and LoRA-row visibility came from
viewData.trainingMethod, still read from the editable form store; changing
the form (e.g. LoRA -> Full) after starting a run relabeled it and hid its
saved LoRA rows. The run-config mapper now derives trainingMethod from the
snapshot's training_type/load_in_4bit (via parseBackendTrainingMethod, now
exported from the feature index) and the live view prefers it.
* studio: fetch the run config on a terminal phase too, not just the first step
The live config-popover fetch was keyed on firstStepReceived, which the runtime
store sets only when step > 0. A run that fails or completes during preparation
(before step 1) creates and finalizes its row from the terminal error/complete
event, but neither the job id nor firstStepReceived changed, so the fetch never
ran and the popover stayed on the editable form store -- showing the wrong
config/method if the form was edited afterward (Configure re-enables on failure).
Gate the fetch on a runRowReady signal = firstStepReceived OR a terminal phase
(completed/error/stopped), the states in which the backend guarantees the row
exists. This also stops the earlier fetch-then-404 churn during preparation and
lets the effect depend only on values it reads (no lint suppression needed).
* studio: retry the run-config lookup and accept a hydrated step as row-ready
Two ways the popover could stay stuck on the editable form store for a whole
run:
- The backend publishes the progress event that reveals the run before
create_run commits, so the first lookup can lose that race and 404. The catch
changed neither runRowReady nor fetchedRunConfig, leaving every effect
dependency identical, so no further attempt was ever made for that job. The
failure path now schedules an explicit retry, bounded and keyed by job id, so
a genuinely absent row falls back to the form store instead of polling.
- A run recovered through status/metrics polling (SSE unavailable or blocked)
has currentStep restored by applyStatus/applyMetrics but never
firstStepReceived, and the phase stays training, so the row was treated as
not ready even at step > 0. currentStep > 0 is now a readiness signal of its
own.
* studio: fetch the saved run config as soon as the job id exists
start_training() inserts the run row before the pump can consume any event --
deliberately, so the run appears in history during model loading -- and /status
exposes the job id throughout the pre-step phases. Gating the lookup on a first
step or a terminal phase therefore held the popover on the editable form store
for the whole configuring/loading/downloading window, which on a long model or
dataset load is minutes, and indefinitely for a run adopted from another client.
The job id is now the entire readiness condition; the existing bounded retry
still covers the instant before the insert commits.
* Fix Training Config popover fallback for history runs without a saved config; tighten popover comments
---------
Co-authored-by: danielhanchen <unslothai@gmail.com>
* fix(registry): don't register deepseek models at import time
`_deepseek.py` called `register_deepseek_models(include_original_model=True)`
at module scope, so merely importing `unsloth.registry` registered models
(and reached the hub via `list_models`) as a side effect. None of the other
five families (`_gemma`/`_llama`/`_mistral`/`_phi`/`_qwen`) do this; they only
register when `register_models()` asks them to.
Two consequences:
- Importing the registry populated MODEL_REGISTRY on its own (32 entries,
including 10 `deepseek-ai` original models that no other family leaks) and
did network I/O at import time.
- Because the import-time call set the `_IS_DEEPSEEK_*_REGISTERED` guards with
`include_original_model=True`, the later `register_models()` call (which uses
the default `include_original_model=False`) early-returned, so the
original-model set won permanently.
Remove the stray module-level call. The `if __name__ == "__main__"` block below
still registers with `include_original_model=True` for standalone use, so the
generator script is unaffected.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* test(registry): make import-side-effect test pass on CPU-only runners
The new test spawned a fresh `python -c "import unsloth.registry"` that did
not inherit tests/conftest.py's GPU-free harness, so on no-accelerator CI
runners the child raised NotImplementedError from unsloth_zoo.device_type
before printing REGISTRY_SIZE. With check=True this surfaced only as an
opaque CalledProcessError, turning the "Repo tests (CPU)" job red even
though the registry fix is correct.
Import this directory's conftest inside the child first so it applies the
same device_type stubs and torch.cuda probe patches. Also use check=False
and include the child stdout/stderr in the assertion message so a future
import regression is legible instead of an opaque non-zero exit.
* test(registry): assert register_models() leaks no upstream originals
Adds a fresh-interpreter test that register_models() registers only
unsloth-org models (deepseek still present via the normal path) and never
leaks the upstream deepseek-ai originals that the import-time guard poisoning
used to leak (129 -> 139). Factors the conftest-harness subprocess runner
into a shared helper reused by both registry import tests.
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <unslothai@gmail.com>
* Studio: hide infra models from the hub cached inventory
The hub inventory scans behind /api/hub/cached-gguf and /api/hub/cached-models
returned the llama.cpp install validation probe (ggml-org/models) and the RAG
embedder (unsloth/bge-small-en-v1.5[-GGUF]) as on-device models. Share the
hidden-model check from routes/models.py via utils/models/hidden_models.py and
apply it in both scans. A GGUF infra repo stays visible when the user
explicitly downloaded a variant through the Hub, since variant manifests only
exist for user-initiated downloads.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: make On Device trust the hub inventory, match repo ids exactly, lighten the hidden-model import
Follow-up on the hub cached-inventory hidden-model change, addressing the review.
On Device now trusts the Hub inventory API for cached rows. The backend already
hides the RAG embedder and the llama.cpp probe and re-includes a GGUF infra repo
once the user downloads a variant through the Hub, but the frontend was
re-hiding it by repo id, so the user-downloaded variant never appeared in the On
Device list or the count. isVisibleInventoryRow now short-circuits cached rows
(kind === "cache") to visible and keeps client-side needle hiding only for local
filesystem rows and Discover.
is_hidden_model matches Hub repo ids exactly (case-insensitive) against the probe
plus the effective embedder and its GGUF companion, instead of substring
matching the configured-embedder basename. A custom embedder with a generic
basename like org/model no longer hides unrelated cached repos such as
user/model-chat or org/model-instruct. The probe filename and local-path
embedders keep exact matching.
The helper moves to utils/hidden_models.py and is imported at module scope in the
hub cache scanner, so it no longer pulls in utils/models/__init__ (the eager
model-config/checkpoint stack) and a broken import fails at startup instead of
being swallowed per-repo and silently emptying the inventory. routes.models
keeps the _is_hidden_model and _safe_resolve aliases and drops the unused
_HF_REPO_ID_RE re-export that was failing source lint.
Tests: exact repo-id matching with a custom embedder, the cached-models scan
keeping an unrelated repo, and a clean-interpreter check that the helper imports
without the model-config stack.
* Studio: match the llama.cpp probe filename on both path separators
The hidden-model check compared the probe's on-disk filename with
Path(value).name, which on a POSIX interpreter does not split a Windows-style
path ("...\stories260K.gguf") and would let the probe through. Split on both
separators so the probe is matched regardless of which OS produced the path,
matching the tolerance of the previous substring check. Adds a Windows-path
assertion to the probe test.
* Studio: harden hidden infra model handling
* Fix hidden cache row confirmation
* Fix hidden local rows and confirmed hint merges
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Handle snapshot-configured hidden models
* Hide basename-only default embedders
* Fix dynamic embedder inventory filtering
* Studio: hide the configured RAG embedder from Discover and feed rows
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
Co-authored-by: Daniel Han <23090290+danielhanchen@users.noreply.github.com>
* Replace standalone Studio wording with Unsloth
Replace the single word Studio with Unsloth wherever it is used as
shorthand for Unsloth Studio in docs, CLI output, UI strings, i18n
locales, workflow display names, comments and docstrings.
Kept unchanged: the full name Unsloth Studio, third party product
names (LM Studio, Visual Studio, Mac Studio), feature names
(Recipe Studio, Fine-tuning Studio and its translations), and all
identifiers such as env vars, commands, paths and filenames.
* Address review feedback on the Studio wording rename
Use "an" before Unsloth where the rename left the article as "a".
Restore the split brand where Unsloth and Studio render as two halves
of the full product name: the onboarding sidebar subtitle and the
IPv6 localhost warning. Scope two messages to the full name Unsloth
Studio where plain Unsloth was misleading: the AMD README bullet and
the CLI studio setup error.
* Studio: enforce 60s minimum on idle auto-unload TTL (0 stays off)
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* Drop decorative section separator from idle TTL floor tests
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
The pip scan-packages studio shard is red on main and on every open PR:
the baselined fastapi finding (the benign SSE keepalive `while True:`
loop in fastapi/routing.py, reviewed and suppressed long ago) records
its evidence at L586 with the span digest of the fastapi release current
at baseline time. The latest fastapi shifts that loop to L587 and its
span digest with it, so the evidence hash no longer matches and the
scanner reports the finding as new, failing the shard with one
unsuppressed CRITICAL.
Re-reviewed the flagged code in the current release before refreshing:
L587 is the same keepalive loop inside the streaming response machinery,
not a beacon. Only the one entry's evidence and evidence_hash change.
Verified with the scanner itself: `scan_packages.py fastapi
--no-baseline` reproduces the exact CI evidence string, and with the
updated baseline the same scan exits 0 with the finding suppressed as
1 CRITICAL baselined.
* fix(studio): add MLX adapter state control
* fix(studio): honor MLX adapter comparison state
* fix(studio): keep enabled MLX adapters permissive
* Studio: preserve public error message on MLX compare-mode adapter failures
generate_with_adapter_control raised a plain RuntimeError, which the compare
route handled with the generic handler that drops the operational message.
Raise GenStreamErrorRaised(public=chunk.public) instead and catch it in the
streaming and non-streaming consumers, matching the safetensors tool loop, so
errors like 'model is being unloaded' surface their real message.
* Studio: re-emit VLM think prefill inside the adapter context
The compare-mode merge dropped _generate_vlm's upfront yield of the prefilled
<think> block. Restore it as the first snapshot inside the lock+adapter context
(matching _generate_text) so the UI renders the thinking block during prefill
and a cancel/error before the first token does not drop it. Adds a regression
test asserting the prefill is emitted first, after entering the adapter context.
---------
Co-authored-by: danielhanchen <unslothshared@gmail.com>
With 5 or more pills active the composer collapses every pill to an
icon, which hid the Bypass permissions label behind a small glyph.
Exempt the permission pill via data-keep-label so it always shows its
label, with the collapsed icons lining up to its right. Since the pill
is never icon-only now, drop the compact-mode fallthrough in the glyph
off switch so it works while the other pills are collapsed.
The Connections form hid the API key field for the Ollama preset, which
blocked Ollama cloud (it requires a key). Show the optional field for
Ollama; the backend already sends Authorization: Bearer when a key is
set and omits the header when empty, so local keyless servers are
unaffected.
Fixes#7163
* fix(dataprep): skip .jsonl lines that are valid JSON but not objects
`_read_file_by_format` json.loads each line and hands the result to
`_extract_text_from_json`, which assumes a dict:
for field in self._TEXT_FIELDS:
if field in data and isinstance(data[field], str):
A JSON line does not have to be an object -- `"context"`, `["text"]` and
`42` are all valid JSON. For those, `field in data` stops being a key
lookup and becomes a substring/membership test, so `data[field]` raises:
"context" -> "text" in "context" is True (substring!)
-> TypeError: string indices must be integers
["text", "foo"] -> TypeError: list indices must be integers
42 -> TypeError: argument of type 'int' is not iterable
The TypeError escapes past `except json.JSONDecodeError: continue`, so the
whole load dies on one odd line.
That except clause is also the tell: a *malformed* line is already skipped
gracefully. A *well-formed* line that happens not to be an object should be
too -- it carries no text either way. This makes the two agree.
Reachable from `unsloth-cli.py:253` (`--dataset foo.jsonl` auto-detect) and
`RawTextDataLoader` is exported from `unsloth/__init__.py`.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Slim the non-object jsonl regression test and shorten the guard comment
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Stabilize Studio regression tests
Rebuild on current main. Restore the set-membership sidebar account-block matcher
(#6647, which fixed the same order-sensitive regex, was reverted on main, so the
guard is failing on main again) and keep the watchdog replacement-race fix, whose
blocked-watchdog stub now waits without a timeout so a superseded watchdog stays
alive until cleanup regardless of scheduler load.
* Tighten the blocked-watchdog stub comment
---------
Co-authored-by: Daniel Han <unslothshared@gmail.com>
* fix(tokenizer): check for tokenizer.model after saving it, not before
`fix_sentencepiece_tokenizer` creates its temporary directory, then returns
early unless that directory already contains a tokenizer.model:
if not os.path.exists(temporary_location):
os.makedirs(temporary_location) # fresh, empty
if not os.path.isfile(f"{temporary_location}/tokenizer.model"):
return new_tokenizer # always true
old_tokenizer.save_pretrained(temporary_location) # writes that file
The file only appears on the line after the check, so the guard is always
true and the body never runs. Nothing else writes that path either --
`convert_to_fast_tokenizer` saves into a per-name subdirectory, not
`{temporary_location}/tokenizer.model`.
Both call sites are in `get_chat_template` and are commented "Must fix the
sentence piece tokenizer since there's no tokenizer.model file!" -- the
guard defeats the exact intent the caller states. The effect is silent: the
caller still gets a working `new_tokenizer`, but the sentencepiece piece
rename is skipped, so the mapped token (e.g. the eos token remapped to
`<|im_end|>`) is missing from tokenizer.model and GGUF/llama.cpp exports
carry the old piece.
`check_if_sentencepiece_model` in save.py does the same probe in the right
order -- makedirs, save_pretrained, then isfile. Match it.
Tests are added under tests/saving/ next to the existing sentencepiece
coverage, and to the two Bucket-A lists in consolidated-tests-ci.yml, since
Repo tests (CPU) --ignores tests/saving and these need protobuf.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Clear stale tokenizer.model before the sentencepiece guard
The guard now runs after old_tokenizer.save_pretrained, but the default
temporary_location is a fixed reusable directory. A fast-only tokenizer writes
no tokenizer.model, so a stale file from an earlier sentencepiece call could
pass the guard and patch the wrong model (e.g. mixing models in one process,
like a long-running server). Remove any existing tokenizer.model first, and add
a regression test.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Empty the reusable sentencepiece scratch directory each call
The final AutoTokenizer.from_pretrained reloads the whole temporary_location, so
removing only a stale tokenizer.model still let other artifacts from a previous
tokenizer (added_tokens.json, chat template, etc.) leak into the reload when the
default reusable directory is used across models in one process. Recreate the
directory instead, and add a regression test for the leaked-artifact case.
* Clear only top-level scratch files, keep subdirectories
Recreating the whole reusable directory deleted the {name} subtree that
convert_to_fast_tokenizer stores a converted tokenizer's source vocab in, so
old_tokenizer.save_pretrained could not copy tokenizer.model and the guard
returned the tokenizer unpatched for those legacy converted tokenizers. Remove
only stale top-level files (all the final reload reads) and leave subdirectories
intact. Add a regression test for the converted-source subdirectory.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Keep the current tokenizer's own source vocab when clearing
On a repeated get_chat_template(map_eos_token=True) call, the returned tokenizer's
vocab_file points back at the top-level tokenizer.model, and the cleanup deleted
that source before old_tokenizer.save_pretrained could re-emit it, so the guard
returned the tokenizer unpatched. Skip removing the old tokenizer's own source
vocab while still clearing stale files from a different tokenizer, and add a
regression test.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Use a per-call temporary directory for the sentencepiece fix
The scratch directory defaulted to a single shared path, so concurrent or repeated
get_chat_template(map_eos_token=True) calls could delete or overwrite each other's
tokenizer.model between save and reload (tripping the piece assertion or reloading
the wrong model), and stale files from an earlier tokenizer could leak into the
reload. Work in a unique per-call subdirectory instead: this isolates every call
without deleting anything the caller owns, and replaces the earlier per-file cleanup.
Tests updated to read the patched model from the reloaded directory and to cover
isolation and source-vocab preservation.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Pass only the applied token mappings into the sentencepiece fix
get_chat_template mirrors token remaps into tokenizer.model via
fix_sentencepiece_tokenizer, but two caller paths passed a mapping that did not
match what they wrote to the fast tokenizer JSON, so once the sentencepiece patch
runs the model and JSON disagree:
- the mapped-token path skipped entries whose target already existed but still
passed the full mapping, renaming a piece the JSON never changed;
- the EOS-swap path swapped both tokens in the JSON but passed only one direction,
leaving two stop_word pieces and no old EOS piece.
Pass the applied mapping (and both swap directions) instead. Add regression tests.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Tighten sentencepiece guard comments
* Add SPDX license identifier to sentencepiece guard test
* Reclaim the per-call sentencepiece scratch directory
The per-call tempfile.mkdtemp fixed the shared-directory race but never cleaned
up, so a long-running process leaked one scratch dir per call. The dir cannot be
deleted eagerly for sentencepiece tokenizers because the returned tokenizer's
vocab_file points into it (a later save_pretrained copies the patched
tokenizer.model from there). Reclaim it correctly instead: remove the dir right
away on the fast-only path (the returned tokenizer never references it), and
attach a weakref.finalize so the sentencepiece dir is removed once its tokenizer
is garbage collected. Add regression tests for both.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Tighten the scratch-dir reclaim comment
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
* feat(studio): expose opt-in MCP control plane
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Harden Studio MCP tools: byte-safe auth, page clamping, forward export/checkpoint fields
Follow-up hardening on the opt-in MCP control plane. All changes are additive
and backwards compatible.
- BearerTokenMiddleware now compares the Authorization header on raw bytes.
A non-ASCII bearer value previously reached str-based hmac.compare_digest,
which raises TypeError and surfaced as a 500 instead of a clean 401. The
constructor also rejects an empty or whitespace-only token so an empty token
can never match an empty "Bearer " header.
- MCP tools call the route functions directly, which skips FastAPI Query
validation. list_training_runs and get_recipe_job_dataset now clamp limit and
offset to the same bounds the HTTP routes enforce (a negative SQLite LIMIT
otherwise means "no limit").
- export_gguf forwards hf_token (the backend rejects a Hub upload without it),
accepts a list of quantization methods, and exposes imatrix / imatrix_path so
the IQ low-bit quants are reachable.
- load_checkpoint forwards hf_token and approved_remote_code_fingerprint so
gated checkpoints and the remote-code approval retry work. Its docstring is
corrected: the export backend coexists with training and inference rather than
freeing GPU work.
- start_training passes via_api_key=False explicitly instead of relying on the
unfilled Depends default.
Tests: add coverage for non-ASCII and empty-token auth, the correct-token pass
through, non-http scope pass through, pagination clamping, and the forwarded
export/checkpoint fields.
* Harden Studio MCP: cap /mcp request bodies, reject unusable tokens, fix docs
Follow-up hardening from a full review pass. All changes are additive and
backwards compatible.
- Add "/mcp" to _BODY_PROTECTED_PREFIXES so MaxBodyMiddleware enforces the same
request-body cap it already applies to every other write endpoint (/api/train,
/api/export, /api/data-recipe, ...). The MCP endpoint accepts authenticated
POST tool-call bodies; without this an authenticated client could send an
unbounded body. The middleware only buffers the request body (not the SSE
response), so streaming is unaffected, and the 500MB default cap never affects
a real JSON-RPC tool call (verified live).
- Reject a non-ASCII UNSLOTH_STUDIO_MCP_TOKEN at construction. HTTP header values
are ASCII, so a non-ASCII token cannot be sent by a standard client and would
silently lock out the endpoint; fail fast instead.
- MCP.md: document the canonical /mcp/ endpoint and note that /mcp redirects to
it, so clients that do not follow redirected POSTs still connect.
Tests: add non-ASCII token rejection coverage.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Tighten MCP server comments
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
* Propagate fp8 block_size before the early return in get_lora_parameters_bias
get_lora_parameters_bias set the fp8 block_size on W/W_quant only after the
disable_adapters/merged early return, so on the merged or disabled path (merged
inference, DPO reference model) a block-fp8 weight lost its real block_size and
downstream fp8 kernels fell back to [128, 128]. The non-bias sibling
get_lora_parameters already sets block_size before its early return; move the
block so both behave the same.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Guard the fp8 block_size against a missing quant state
A decompressed compressed-tensors layer keeps quant_method == "fp8" while its
weight is back to bf16, so it has no quant state and get_lora_parameters_bias
must still return W_quant None for fast_linear_forward to fall back to a plain
matmul. Only attach block_size when a quant state was actually found.
* Guard the sibling get_lora_parameters fp8 block_size against a missing quant state
Mirror the get_lora_parameters_bias guard so a decompressed compressed-tensors
layer (quant_method fp8, bf16 weight, no quant state) does not raise
AttributeError on the fused-LoRA path. Add a CPU-only regression test.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Studio: don't apply nest_asyncio on plain CLI starts (breaks asyncio on Python 3.14+)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Skip nest_asyncio on Python 3.14+ so notebook and embedded Studio starts also work
* Tighten the nest_asyncio gate comment
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
* fix(studio): recover stalled Hub downloads over HTTP
* fix(studio): preserve retry generation and progress baseline
* fix(studio): keep XET retry handoff nonterminal
* fix(studio): preserve retry cancellation on claim failure
* fix(studio): make retry failure cancellation atomic
* fix(studio): close skipped retry state gaps
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Stabilize chat-only export gate detection on Windows
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Retrigger CI on a user-authored head
* fix(studio): serialize XET HTTP retry handoff
* List XET to HTTP retries that are briefly released from the repo guard as active downloads for PR #6858
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Settle no-process active downloads on shutdown so a parked XET retry cannot spawn after cleanup for PR #6858
* Settle exited-error and no-process downloads on shutdown and persist their cancel markers for PR #6858
* Keep terminal HTTP failures uncancelled and block companion deletion for released retry peers for PR #6858
* Trim download lifecycle test coverage
* [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>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Etherll <61019402+Etherll@users.noreply.github.com>
* refactor(studio): move chat model picker into features/model-picker
Relocate model-selector + its support files from components/assistant-ui
into a self-contained features/model-picker feature (own barrel), mirroring
the modular Hub layout. Pure move + import repoint; no behaviour change.
* feat(model-picker): add per-model config persistence layer
Superset PerModelConfig (customContextLength, kvCacheDtype, speculativeType,
specDraftNMax, tensorParallel, chatTemplateOverride, trustRemoteCode) persisted
to localStorage (unsloth_model_configs) with schema versioning + LRU budget.
KV-dtype and speculative value sets match main's sidebar (no q4_0/ngram-simple).
Reuses features/hub/lib/model-identity for normalization; adds storage-key layer
and applyPerModelConfigToRuntime (sets tensorParallel, which the old PR omitted).
* feat(picker): modular backend for chat-template validate + default fetch
New studio/backend/picker package (schemas/service/routes) mounted at /api/picker:
- POST /api/picker/validate-chat-template (Jinja syntax validation, no false positives)
- GET /api/picker/chat-template/{model_name} (default template from tokenizer_config.json,
reusing get_cache_path/resolve_cached_repo_id_case; graceful null, no model-code exec)
Frontend api/templates.ts client + hooks/use-model-defaults lazy cache. No backend
changes to the existing inference load route (per-model load fields already supported).
* feat(model-picker): bind picker on-device list to shared hub inventory
Picker now sources cached + local models from useHubInventory (the Hub's shared
store) via a thin adapter, replacing its own /api/models/* fetchers + module
caches. Hub, download manager, and picker now share one source of truth, so
completed downloads reflect in the picker automatically. Partial/live-download
rows are filtered from the cached lists (unchanged rendering). Local naming/search
preserved via additive LocalInventoryRow modelId/displayName. Variant expander,
scan-folder management, recommended-fit, search, external providers untouched.
Known minor: cached 'Downloaded date' sort tiebreak degrades to alphabetical
(hub cached rows carry no mtime); default 'recent' (load-time) sort preserved.
* feat(model-picker): per-model config step inside the picker
Picking a (non-external) model now opens an in-picker config view built from
main's current load controls (context length, KV cache dtype, speculative
decoding, draft tokens, tensor parallel) plus a chat-template editor backed by
the picker validate/default endpoints. 'Remember for this model' persists the
config per model+variant; Run forwards the config to the existing load flow via
meta.config. External models bypass the step. Two-view orchestration lives in
model-selector (single interception point); pickers.tsx call sites untouched.
trustRemoteCode dropped from PerModelConfig to preserve main's per-load consent.
* feat(chat): apply/persist per-model config through the load flow
handleCheckpointChange threads meta.config into the selection; stageOrLoad and
the autoload/Hub-run paths now apply the picker config (explicit pick or saved
remembered config) via applyPerModelConfigToRuntime before staging/loading, with
keepSpeculative set so a remembered speculative mode survives the model switch.
Replaces the old remembered-load-settings seeding (resolveInitialConfig now the
single source). SelectedModelInput carries config.
* refactor(chat): remove per-model load config from the right sidebar
The load knobs (context, KV cache, speculative, draft tokens, tensor parallel)
and the chat-template editor now live only in the picker config step. The sheet's
Model section keeps the staged Load/Cancel flow (config is applied at pick time);
sampling params, system prompt, and RAG are unchanged. Deletes the superseded
remembered-load-settings module + the store's applyRememberedLoadSettings action,
removes the now-dead sheet state/imports, and points the settings reset at
unsloth_model_configs. Delete-cleanup deferred (stale config is LRU-capped).
* fix(model-picker): remove leftover sidebar-staging cogwheel + empty Model section
The downloaded-variant gear (ModelLoadSettingsAction) staged a model straight
into the right-sidebar Run-settings flow -- the old 'configure before load' path
now fully replaced by the in-picker config step. Removed the gear + its component.
Also gate the sheet's 'Model' section to staged picks only (pendingSelection):
after the load-knob strip its content is staged-only, so it was rendering an
empty section header whenever a model was merely loaded.
* chore(chat): remove dead per-model-config setters + modelControlsDisabled
After the load-config UI moved into the picker, the store's per-model setters
(setKvCacheDtype/setSpeculativeType/setSpecDraftNMax/setTensorParallel/
setCustomContextLength/setChatTemplateOverride) had zero callers
(applyPerModelConfigToRuntime writes via setState), and the sheet's
modelControlsDisabled was unreferenced. Verified dead across the whole tree.
* fix(chat): config-step Load actually loads (ignore Load-on-selection)
Root cause: with Settings > Chat > 'Load on selection' turned OFF, the config
step's load went down the deferred-staging path -- opening the right sidebar with
'<model> is staged, not loaded yet / Choose Load model'. The in-picker config step
IS the deliberate load action, so its Load now loads immediately (or downloads +
auto-loads when not cached) regardless of the toggle. Renamed the button
'Run model' -> 'Load model' to match. Native/dropped picks still honor the toggle.
* refactor(chat,hub): retire 'Load on selection' — config step is the only load flow
The in-picker config step (and the Hub Run button) now fully supersede the old
stage-to-sidebar flow, so the Load-on-selection toggle is removed everywhere:
- chat stageOrLoad: every pick loads immediately, or downloads + auto-loads when
not cached (the previous default behaviour, now universal).
- hub Run: drops the stage branch; downloaded GGUFs load directly with their saved
per-model config (no collision with the chat config step — both end at selectModel).
- store: removed loadOnSelection field/setter/key/default; Settings>Chat toggle and
its settings-reset entry removed.
- staged sidebar section is now a download-progress view (auto-loads on completion).
No manual staging remains; stageModel is used only for background auto-load downloads.
* feat(model-picker): default chat template from GGUF + thread variant through config flow
Read the embedded tokenizer.chat_template from GGUF files (read_gguf_chat_template
in gguf_metadata) and use it as the per-model default. Plumb gguf_variant through
the picker service, /api/picker/chat-template route, frontend templates API, and
use-model-defaults so the right variant's template is fetched.
Also refine the picker config-page/model-selector wiring, drop the dead
ggufNativeContextLength runtime path, and add the per-model-config storage keys to
the settings prefs export.
* feat(model-picker): read safetensors chat template + hide editor where it has no effect
Resolve the default chat template for safetensors models: prefer the modern
chat_template.jinja, fall back to the tokenizer_config.json chat_template field,
then chat_template.json (multimodal processor), then the GGUF embedded template.
Applied to local dirs, the HF cache snapshot scan, and the HF remote fetch.
Hide the chat-template editor in the picker for safetensors models — the override
is only applied at load by the GGUF/llama.cpp backend, so editing it on safetensors
currently has no effect. GGUF keeps the editor. Nothing removed; the dialog stays
for when the safetensors apply path is wired up in a later branch.
* fix(model-picker): set legacy-migration flag only after the write succeeds
Set unsloth_model_configs_migrated only once writeMap confirms the migrated
map persisted, so a quota/storage failure no longer marks migration done and
silently drops the user's pre-existing remembered settings — the next load retries.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* MVP model picker fixes
* MVP picker config fix
* MVP safetensors config
* MVP max seq config
* MVP max seq fix
* Fix static max tokens cap ignoring model context
* Fix picker GGUF scan parity
* fix(studio): harden model picker config loading
Apply remembered per-model configs consistently from picker and Hub loads, keep default configs from overriding standing speculative settings, add config access for direct local GGUF files, and support saving or forgetting active model settings without a reload.
* Fix model picker config flow
* Fix model picker config loads
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Avoid recursive per-model config migration reads
* Apply the displayed context length when loading a GGUF
* Fix template validation, cached template lookup, and failed load rollback
- Validate chat templates with the loopcontrols extension so templates
that use break or continue tags pass the picker validator, matching the
inference renderer that already accepts them.
- Read the default chat template from the newest cache snapshot rather than
an arbitrary iterdir order, so an older cached revision no longer prefills
a stale template.
- Capture the runtime per-model config before a load and reapply it when the
load fails, so a failed switch leaves the active model context, KV cache,
template, and speculative settings as they were.
* Make chat template view only for safetensors models
Custom chat template overrides are applied at inference only for GGUF
models, which pass the template to llama-server. The safetensors backend
renders with the model built-in template and ignores the override, so
editing it would save a value that never loads. For safetensors the
config page now opens the template as a read-only preview with a note
that editing is not available yet. This can become editable once
inference support for custom safetensors templates lands in main.
* Fix model picker config edge cases
- Restore prior runtime config when a load no-ops for the active model
- Cap the picker validator request body via the protected prefixes
- Keep the GGUF context slider max above the loaded context
- Fetch subfolder chat templates for uncached Hub repos
- Show the compare side config when reopening the picker
* Keep saved GGUF context above the fallback ceiling
* Show the model config in the run settings sidebar
* Fix model config sidebar reset and context slider
- Stack the remember toggle and action buttons in the sidebar
- Reset the config to defaults instead of the loaded values
- Fetch the native context so the slider max is not the loaded value
* Fix model picker config and download regressions
- Run picker chat template routes off the event loop
- Depth and root guard local template directory scans
- Restore download manager flow for uncached hub picks
- Apply per model context length on reload
- Import model picker symbols from the feature barrel
* Fix model picker config and cached download sorting
- Restore load settings when a Hub run is rejected mid load
- Reuse one NumericValueInput instead of a duplicate copy
- Fix double decode of the model name in the template route
- Remove the unused reset-to-loaded settings action
- Fix cached model download sorting
* Fix model picker per-model config edge cases
Honor a saved or typed max seq length above the model's native context so
RoPE extended values are no longer clamped and silently overwritten. Allow
typing past native while the slider keeps native as a soft ceiling.
Guard the fetch success paths in use-model-defaults against an aborted
signal, and refetch when the HF token changes.
Hash the chat template content in the sidebar remount key instead of its
length. Enable reset for a GGUF whose native context is unknown, and floor
the context slider max so it can never fall below the min.
* Fix GGUF context auto-fit and gated model config token
Stop forcing a 32768 context when a GGUF native context is unknown so the backend auto-fits to VRAM again, while still honoring an explicit context edit.
Send the HF token as a query param so gated safetensors models resolve their max position embeddings.
Derive model default state during render to drop the set-state-in-effect calls.
* Fix native GGUF context ceiling and guard picker template reads
Restore the native context store field so the sidebar slider keeps the
full ceiling for drag and drop GGUFs. Limit local chat template reads to
the browse allowlist, skip malformed repo ids, and drop unused model
picker exports.
* Fix model picker lint boundaries
* Fix model picker review findings
Chat template editor never seeded its draft. Radix only calls onOpenChange
from internal events, so the seed in the nextOpen branch was dead and a model
with a saved override opened empty. Saving then cleared the override. Drop the
dead branch, treat draft as an untouched sentinel, and reset it on every close.
Uncached Hub picks could auto load a model after the user left the chat. Main
detached the staged pick on route exit and on chat context change. Carry the
context key on the pending pick and skip the load when it no longer matches.
Also clear configTarget when the picker closes, restore the onUpdated ref so
variant rows stop resubscribing on every parent render, skip the LRU write when
the entry is already most recent, import NumericValueInput relatively, and drop
the unused ModelUpdateAction barrel export.
* Preserve GGUF context on active reload
* Fix model picker per-model config regressions
- Stop reloading the already loaded model on re-pick
- Hide infra models from the chat picker
- Detect vision support on cached GGUF repos
- Honor saved maxSeqLength on auto load
- Restore default chat template for local GGUFs
- Warn on save failure and revert config on cancel
- Refetch picker inventory on open
- Persist read only per model config safely
* Fix stale model auto load
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* Fix model picker numeric input sizing and constraints
Size value inputs to their content so long context lengths are not clipped,
restrict them to numeric characters, and stop the speculative decoding label
from truncating in the sidebar.
* Fix picker CI tests and harden chat template resolution for PR #6647
- tests: point the descender guard at the moved model-selector.tsx path
- tests: exclude the disabled Reload model button from the regenerate locator so .first targets the real Regenerate
- picker/service.py: reject symlinked template/gguf leaves that resolve outside the browse allowlist (HF cache reads unchanged)
- compare mode: resolve each pane's own remembered chat template instead of inheriting the other pane's from the store
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* Protect future-schema per-model configs from deletion for PR #6647
savePerModelConfig already refuses to overwrite a stored config whose schema version is newer than this client understands, but deletePerModelConfig did not. Unchecking Remember on an older client therefore silently destroyed a newer client's saved config. Apply the same guard on delete and surface the blocked case through the existing saveFailed toast.
* Protect future-schema per-model configs from quota eviction for PR #6647
The save and delete guards already refuse to touch a stored config whose schema version is newer than this client understands, but the quota-eviction path did not, so a full store on an older client could still evict a newer client's config. Skip future-schema entries when evicting and fail the save if the budget cannot be met without them.
* Fix GGUF context persistence, compare context, and rollback settings for PR #6647
Persist a GGUF context override from the user's intent instead of collapsing it against the loaded context, which reintroduced the context-reset (f4838782cb reverted the native-baseline fix). model-config-page now collapses the saved value against native, and use-chat-model-runtime and chat-adapter retain the requested context on load so re-saving another setting keeps the override; a null request stays null so a VRAM auto-fit never becomes a stored override.
shared-composer: a compare pane with no explicit GGUF context now loads at native (0) like single-view, not the session maxSeqLength that silently shrank the shown context.
use-chat-model-runtime: restore the previous model's KV cache dtype and chat template on a failed-load rollback so it runs as it was, not with backend defaults.
* Preserve native path token when reloading the active model for PR #6647
handleReloadActiveModel rebuilt the selection without the store's activeNativePathToken, so reloading a file-picked GGUF after a settings change validated the display label as a repo/path and failed. Thread the active native token through the reload selection so native-loaded models reopen correctly.
* Make picker template validation resilient and accept HF generation tags for PR #6647
Import Jinja lazily inside validate_chat_template so a backend without the optional jinja2 package (GGUF-only installs) still starts instead of raising ModuleNotFoundError at import time. Register a no-op extension for the Transformers {% generation %} assistant-mask tag so pasting a valid HF chat template validates, matching the renderer, rather than being rejected as an unknown tag.
* Honor remembered compare config and parse processor chat_template.json for PR #6647
* Fix failed-load rollback context and processor template map fallback for PR #6647
* Restore speculative decoding config on failed-switch rollback
When a model switch fails after the previous model was unloaded, the
rollback reload restored tensor_parallel, KV cache dtype and the chat
template override, but omitted speculative_type and spec_draft_n_max and
cleared their loaded shadows to null. The previous model therefore came
back running at backend defaults (speculation off) while the UI still
showed it enabled, and the status resync confirmed the off state. Resend
the previous model's speculative settings in the rollback load and keep
the store's active and loaded speculative fields in sync with them.
* Reset max sequence length when a model has no saved config
applyPerModelConfigToRuntime reset every per-model field except
maxSeqLength, which it only wrote when the incoming config had one.
maxSeqLength is the sole field carried on store.params, so selecting a
model with no remembered config left the previous model's value in place
and later loaded the new model at that leaked length. Fall back to the
standing default so an unremembered model loads at its own default.
* Surface a message when a variant update cannot start
startManagedUpdate handled the conflict and error start outcomes but let
busy fall through as if the update began, so the confirm dialog closed
with no job created and the cached variant stayed stale. Show an info
message when the repo is busy with a sibling transfer so the click is
not silently dropped.
* Keep per-model speculative choices out of the global default
A staged load with a per-model or one-off config sets keepSpeculative,
which already skips reading the global speculative preference. The
matching save still ran unconditionally, so the model-specific choice was
written to the global unsloth_chat_speculative_type and a later model with
no saved config started from it instead of Auto. Skip saveSpeculativeType
when keepSpeculative so the per-model choice stays isolated.
* Seed non-active model settings from the app default max length
The Run settings page captured initialMaxSeqLength from the loaded
model's runtime params and fell back to it for a model with no saved
config. Opening settings for a different, unloaded model and clicking
Load then sent the active model's context (for example 64k) instead of
the 4096 default, risking validation failures or OOMs. Seed the default
for non-active models and keep the runtime value only for the active one.
* Prefer sidecar tokenizer chat template over the GGUF copy for variants
_chat_template_from_dir returned the embedded GGUF template first when a
variant was selected, reversing the tokenizer-first precedence of the
no-variant path. A model whose chat_template.jinja or tokenizer_config.json
supersedes a stale embedded template then got the wrong template on
variant selection. Keep tokenizer files first regardless of variant; the
variant only picks which GGUF is the fallback. Adds regression tests for
both the tokenizer-wins and gguf-fallback cases.
* Keep per-model speculative choices load-local in autoload and compare
The interactive load path treats a per-model speculative choice as
load-local and skips writing it to the global default. Autoload and
generalized compare still called saveSpeculativeType unconditionally, so a
remembered off or ngram setting leaked into unsloth_chat_speculative_type
and later models with no saved config inherited it. Persist the global
preference only when the value came from the global settings.
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* Studio: record the compare pane's loaded context in runtime state so the active model's settings and any reload or save use it, not the previous context
* Studio: notify the user when a Hub autoload can't start because another download for the model is already running, instead of silently dropping it
* Studio: drop the merge's orphaned staged-model store helpers and unused alert imports
The main merge left isPendingGguf and pendingSelectionMatches referencing the
removed PendingModelSelection type, and the alert-dialog/alert imports unused
after the permission-mode dropdown replaced the bypass dialog, so tsc -b failed.
* Studio: cache a null default chat template so the viewer stops re-fetching it
A model with no sidecar or embedded template resolves to a terminal null, but
that result was never cached, so reopening the template viewer re-ran the
backend and Hugging Face lookup every time.
* Studio: detect direct-file GGUFs in run settings so Max Tokens uses their context
A GGUF loaded from a local file or custom folder has no variant label, so the
run-settings panel treated it as non-GGUF and clamped Max Tokens to the session
max_seq_length instead of the loaded GGUF context. Detect it via the reported
GGUF context and the .gguf checkpoint suffix, matching the chat page.
* Studio: prompt to re-select a local model file when its lease expired before reload
A file-picked GGUF is reachable only through a native path token that the
desktop host prunes after a TTL. Reloading reused that token blindly, so a
reload long after the initial load failed with an opaque error. Track the
token's expiry and, when it has passed, ask the user to re-select the file
instead of attempting a doomed reload.
* Fix descender-clipping test to tolerate sidebar layout utilities
The sidebar account-block div carries layout utilities (min-w-0, flex-1)
between 'flex' and 'flex-col', so the descender-clipping guard's regex,
which required 'flex' immediately followed by 'flex-col', no longer matched
and the test failed to locate the account-block div. Generalize the prefix
to allow intervening flex utilities while still capturing the leading-*
class before the collapsible visibility utility and asserting leading-tight,
so the guard against clipped glyph descenders is fully preserved.
* Harden picker chat-template resolution
Enforce the 64 KiB chat-template contract at the validate endpoint's request
model so a direct caller cannot submit a template far larger than the frontend
allows (MaxBodyMiddleware only bounds the whole request body, not this field);
oversized templates now return a clean 422.
Apply sidecar-over-GGUF template precedence globally across cached snapshots
instead of per snapshot. A repo with multiple cached revisions previously
returned the first snapshot's template, so a newer GGUF-only revision could
win over an older revision's maintained chat_template.jinja sidecar, which
contradicted the documented intent that sidecars supersede the embedded copy.
* Guard per-model config against future-schema and lossy migration
Two forward-compatibility gaps in the versioned per-model config store:
- The load/apply path returned and normalized a stored record without checking
its schema version, so a record written by a newer client was reinterpreted
under the current schema and applied to a live model load, even though save,
delete and eviction all refuse to touch future-schema records. Reject
future-schema records on load too.
- The one-time legacy migration enforced the storage budget without protecting
the entries it had just migrated and set the completion flag unconditionally.
When storage was already full of future-schema records (which are unevictable
by an older client), the migrated entries were the only evictable ones and
could be dropped while migration was still marked complete. Protect the
migrated keys during eviction and only mark migration complete when they
survive, so it retries once space frees up.
* Discard chat-template validation results after the dialog closes
Server-side template validation is async, but closing or cancelling the editor
did not abort it, so a late-arriving valid response still called onSave and
applied a template the user had already dismissed. Track a validation token
that is bumped on close and ignore any validation result whose token is stale.
* Record native lease expiry when loading a picked GGUF from the chip
The pending-native-model chip loaded via stageOrLoad directly, bypassing
loadNativeModelIntent, so activeNativePathExpiresAtMs was never recorded for a
chip-loaded file. A later reload then either skipped the lease-expiry guard
entirely (expiry left null) or compared against a previously loaded file's
stale expiry, so reload could reuse an already-pruned token or wrongly block a
still-valid one. Route the chip through loadNativeModelIntent, which builds the
same selection and records the expiry.
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* Prefer sidecar template for a directly selected local GGUF file
A direct .gguf file path read its embedded chat template without checking the
parent directory for a maintained sidecar (chat_template.jinja /
tokenizer_config.json), while directory and variant selections already prefer
the sidecar. That let the config editor preview or save a stale embedded
template for the same model depending on how it was selected. Check the parent
directory sidecars first, then fall back to the embedded copy, and cover both
paths with tests.
* Resolve cached chat template per revision, newest first
The earlier change searched every cached snapshot for a sidecar before
considering any snapshot's embedded GGUF template, which let an obsolete sidecar
from an older revision override the newest revision's template. Restore
per-snapshot resolution (newest first): a revision's sidecar still supersedes
its own embedded GGUF copy, but a newer revision is no longer overridden by an
older revision's sidecar.
* Preserve autoload transport conflicts and surface background busy downloads
- When a Hub autoload hits a transport conflict, keep pendingHubAutoLoad bound
instead of clearing it. Clearing it re-keyed the download surface and its
cleanup cancelled the conflict the toast tells the user to resolve, so the
Hub resume affordance was gone the moment it appeared. Return early on
conflict, mirroring the started branch, so resolving it from the Hub still
auto-loads on completion.
- The background-download branch handled started and conflict but silently
dropped a busy outcome, leaving the user with no feedback when a peer variant
of the same repo was already downloading. Surface the same busy toast the
autoload path uses.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* fix(save): unsloth_push_to_hub_gguf(save_method="lora") raises NameError
unsloth_push_to_hub_gguf reads is_main_process at save.py:3181 but never
declares it. Its twin unsloth_save_pretrained_gguf declares it (2783) and
uses it the same way (2839) -- the LoRA branch was copied between the twins,
the parameter it depends on was not. There is no module-level global, so the
name resolves as a global load and the branch raises NameError 100% of the
time.
save_pretrained_gguf(save_method="lora", push_to_hub=True) raises a
ValueError that tells users to "use .push_to_hub_gguf(save_method='lora')
instead" -- the documented escape hatch is the broken call.
Add is_main_process to the signature, positioned as in the twin, and forward
it to unsloth_save_pretrained_gguf on the merged path so the parameter is not
silently ignored there. Default stays True, so nothing changes for existing
callers.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* fix(save): preserve GGUF push compatibility
---------
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Co-authored-by: Etherll <61019402+Etherll@users.noreply.github.com>
* Make the Inkling reasoning-effort coercion a module-level helper so duck-typed engine stand-ins keep working
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* Align Inkling minimal reasoning effort with the reference implementation (0.1)
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The permission-levels feature defaults an unset permission_mode to ask on
streaming requests, so the headless smoke probes hang at the approval
prompt until the job timeout. Declare permission_mode full in the tool
probe bodies; the gate itself is covered by unit tests.
* Studio: make sidebar settings cog clickable, opens settings directly
* Studio: truncate long profile names so the settings cog stays visible
* Studio: tighten spacing between profile name and settings cog
* Studio: render settings cog as a sibling button instead of nesting it in the account trigger
* Studio: cap very long names in the welcome greeting
* Studio: hide the Canvas chat menu item by default behind a settings opt-in
* Studio: keep Canvas in the chat menu settings list as the visibility toggle
* Studio: drop the Canvas row description in chat menu settings
* Studio: keep Canvas visible for profiles that pinned it before the visibility flag
* fix(dataprep): smart_chunk_text single-chunk path leaks internal tensor type when eos_token_id is None
RawTextDataLoader.smart_chunk_text()'s single-chunk branch only
converts `tokens` to a plain Python list inside the
`if eos_token_id is not None:` guard. When a tokenizer has no
eos_token_id configured, that conversion is skipped entirely and the
function returns whatever internal tensor-like object came out of
the tokenizer normalization step (e.g. a torch.Tensor) as
"input_ids", instead of a list of ints.
The sibling multi-chunk branch a few lines below does the conversion
unconditionally, before checking eos_token_id -- the two branches of
the same method disagree on output type depending purely on whether
the tokenizer has an EOS token. Downstream, create_causal_dataset()
does `labels = [list(ids) for ids in input_ids]`; list()'ing a
tensor produces a list of 0-d tensor elements rather than plain
ints, inconsistent with every multi-chunk sample and liable to break
type inference in Dataset.from_dict()/downstream collation.
Fix: move the list conversion out of the eos_token_id guard,
matching the multi-chunk branch's existing pattern.
Added test_smart_chunk_text_single_chunk_no_eos_returns_plain_list
to tests/test_raw_text.py, confirmed red against unfixed code
(assertion failure: input_ids was a MockTensor, not a list) and
green after the fix. Full tests/test_raw_text.py (both test
functions) passes. ruff check + the repo's ruff-format-with-kwargs
script: clean.
Note: tests/test_raw_text.py does not appear to be wired into any
.github/workflows/*.yml CI job (a pre-existing repo characteristic,
not something introduced by this change) -- verified locally via
`python3 tests/test_raw_text.py`.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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---------
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* Studio: Inkling support fixes (context sizing, tool-call healing, reasoning effort, audio icon)
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* Studio: reject binary web_search fetches instead of decoding them into replacement chars
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Match web-fetch MIME subtypes exactly and detect control-char binary
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Sniff binary magic bytes and retry undeclared non-UTF-8 pages as text
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Harden web fetch binary sniffing
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Simplify web fetch binary guard
* Sniff unknown MIME types and handle Latin-1
* Sniff ambiguous Office MIME and prefixed magic
* Decode BOM-marked Unicode web content
* Studio: require ASCII evidence for declared Latin-1/cp1252 web fetches
Latin-1 and cp1252 decode every byte to a printable character, so a high-byte
binary body declared as iso-8859-1/windows-1252 decoded cleanly and slipped
past the control-character binary check. Apply the existing ASCII-structure gate
to those declared decodes as well. Scoped to the Latin family so legitimate
non-Latin single-byte pages (Cyrillic, Greek) are not rejected.
* Revert "Studio: require ASCII evidence for declared Latin-1/cp1252 web fetches"
This reverts commit c7fbec216c.
* Studio: tighten web-fetch binary guard comments
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Co-authored-by: danielhanchen <danielhanchen@gmail.com>
* Studio: stream live tool output with SSE heartbeats and fix web page extraction
Server-side python/terminal tools now stream incremental stdout to the chat
UI while running (new tool_output SSE event), and every blocking tool
execution emits heartbeat keepalives so reverse proxies (Cloudflare tunnels
cap idle streams at ~100s) cannot drop the connection mid-turn. The tool
loop routes also emit a stall keepalive during silent prompt prefill between
tool iterations. The final role=tool message the model sees is byte-identical
to before, so tool-call parsing, nudging, and healing are untouched.
web_search page fetches now extract main content: GitHub repo root pages are
rewritten to the README API (with HTML fallback), hidden/aria-hidden client
error placeholders are dropped, conversion scopes to article/main, and known
boilerplate fragments are stripped. Non-HTML responses are returned raw
instead of being run through the HTML converter.
The frontend renders live-scrolling tool output inside running python and
terminal cards, and a chat stream that ends without a terminal signal now
surfaces an explicit interrupted state with a Retry action instead of
silently ending the turn.
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* Studio: fix content-type sniffing, unlimited-timeout drain, and env parity in tool streaming
Content-Type sniffing: get_content_type() defaults to text/plain when the
header is absent, so the sniffing fallback never fired and header-less HTML
came back as raw markup. Report an empty type for a missing header and sniff
the body whenever the declared type is not HTML, so mislabeled text/plain
HTML pages are converted like before the extraction change.
Unlimited timeout drain: with tool_call_timeout disabled the old path used
communicate(timeout=None) and waited for EOF, but the streaming drain capped
the post-exit drain at a 5 second join, truncating output from a grandchild
that holds stdout open. When timeout is None, drain until EOF or the cancel
event fires; finite timeouts keep the bounded remaining-budget join.
Env parity: drop the PYTHONUNBUFFERED=1 injection on the streaming path so
the child invocation is byte-identical with and without streaming (the env
var was model-visible via os.getenv). Live streaming granularity now depends
on the child flushing; unflushed output arrives in ~8 KB chunks or at exit
and the final result is unchanged, with SSE heartbeats covering the gaps.
* Studio: stream tool-call arguments while the model writes them
A model writing a large tool call (a full python game is minutes of
generation) produced nothing on the stream: the structured path
accumulated delta.tool_calls fragments silently after the provisional
card, and the text path's DRAINING state consumed everything until
stream end. The user saw a dead Running spinner while the model was in
fact writing code, and the byte-silent SSE segment was also the window
where proxies drop the connection.
New tool_args SSE events stream the arguments as they generate. The
structured path forwards each fragment once a provisional card exists
(backlog first, so the card starts from the top of the call). The text
path sniffs the drained call for an enabled tool name and streams the
raw call text under the id the stream-end parser assigns its first call
(call_0), so the final tool_start reconciles the same card; the sniff is
gated on enabled names plus the provisional size floor, and prose or
ordinary JSON answers never spawn a card. The safetensors loop streams
the drained render_html call to its existing provisional card the same
way.
The chat adapter accumulates the raw stream per card and feeds a partial
JSON parse (call envelopes and stringified arguments unwrapped) into the
part's args, so the python and terminal cards render the code live and
the render_html canvas builds while streaming; both cards now say
Writing code / Writing command during this phase via useToolArgsStatus.
Display only: the parser input, the executed call, and the conversation
the model sees are byte-identical, covered by new loop-level tests for
the structured path, the text path, and the no-tool JSON answer.
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* Studio: keep full tool output visible past the model cap; heal /mnt/data habits
Live testing surfaced two issues in the tool streaming UX.
First, a long python stdout ended in '... (truncated' in the finished
card: the model-visible result is capped by tools._truncate
(_MAX_OUTPUT_CHARS, previously 8000 chars) to protect the context
window, and the card rendered that capped text even though the live
stream had already shown everything. The cap stays (raised to 16000,
overridable via UNSLOTH_TOOL_RESULT_MAX_CHARS) but display and model
concerns are now split: the adapter preserves the accumulated live
stream on tool_end whenever it captured more than the final result, and
the finished python/terminal cards prefer it. The live-stream ceiling
rises from 16 KB to 400 KB (chunks batch per poll, so SSE stays cheap),
and both the live pane and the finished card render only the last 2000
lines with a Show all control so a huge output cannot jank the DOM. The
truncation notice now tells the model the user saw the full output and
that written files persist in the working directory. The final result
string remains byte-identical with and without streaming.
Second, models trained on ChatGPT code-interpreter transcripts write to
/mnt/data, which does not exist here (the sandbox CWD is a per-thread
persistent dir). Three layers, all identical across streaming and
non-streaming paths: the python/terminal tool descriptions gain one
sentence saying to use relative paths in the persistent CWD; a failed
execution whose output shows a missing-file error on a known
code-interpreter prefix (/mnt/data, /mnt/outputs, /home/sandbox,
/workspace) gets a model-visible retry hint appended after truncation
so it always survives; and a sitecustomize shim on the sandbox
PYTHONPATH remaps those prefixes onto the CWD in open()/os.makedirs()
with a one-line stderr notice, covering the python tool and any Python
launched from the terminal tool without touching the exec wrapper (so
tracebacks keep their line numbers). Bash-level file operations cannot
be redirected without root or mount namespaces, so they rely on the
description and the hint.
* Studio: fix hidden-element parsing, heartbeat gaps, and tool output id collisions
Review follow-ups on the tool streaming work:
- _html_to_md: treat any present hidden attribute value as hidden (it is an
enumerated attribute whose invalid value default is the Hidden state, so
hidden="false" is still hidden), and implement HTML5 optional end tags so
an unclosed <p hidden> or <li hidden> ends at the next sibling start tag
instead of swallowing every following sibling until the parent closes
- tool_stream_exec: keep heartbeats flowing after the live-output cap; a
tool that keeps printing past the cap kept the queue non-empty, so neither
tool_output nor heartbeat events were emitted and the SSE stream went
silent past proxy idle timeouts
- routes/inference: forward tool heartbeats before the
disable_parallel_tool_use drop window swallows events, so a dropped call
that executes server-side cannot leave the Anthropic stream silent
- llama_cpp: close the provisional text tool card with a tool_end when the
drained call fails to parse (DRAINING false-positive path), so the card
cannot spin forever while the text is delivered as content
- tools: decode terminal output as utf-8 with errors=replace like the python
tool; invalid bytes used to raise UnicodeDecodeError from communicate() on
the non-streaming path and silently truncate the streaming reader, so the
two paths diverged
- sitecustomize: patch io.open alongside builtins.open; pathlib Path.open,
read_text and write_text call io.open directly and bypassed the remap
- frontend: scope the toolLiveOutput/toolFullOutput store keys by pane
(modelType and pairId) and clear stale entries on tool_start; backend ids
like call_0 repeat across turns and across concurrently streaming panes
(compare mode), so a later turn or another pane could display the wrong
preserved output, and run-end cleanup now clears only its own keys
Each backend fix carries a regression test that fails on the previous code;
the byte-identity tests between streaming and non-streaming stay green.
* Studio: keep tool failure status visible and truncation/remap notices truthful
Finished python/terminal cards preferred the fuller live stream by length
alone, so a tool that printed a lot then timed out or exited non-zero showed
the captured stdout but dropped the final result's status (timeout notice,
Exit code N). preferFullToolOutput now shows the stream when the result is
just its truncated prefix, and appends the result otherwise so the failure
tail always survives and the copy button copies both.
The result truncation notice claimed the user was shown the full output, but
the same wrapper serves non-streaming chat/API and direct execute_tool()
callers where nothing is streamed to anyone. The notice is now mode-neutral
and stays byte-identical with and without an output_callback, keeping the
streaming vs non-streaming invariant intact.
The sandbox sitecustomize shim now remaps /tmp/outputs into the working
directory only while it does not already exist, so a real /tmp/outputs the
user's own code created is never shadowed; /tmp/outputs also joins the
missing-path retry-hint list.
* Studio: suppress hidden void elements and keep live output scroll pinned only when at bottom
* Studio: drop capped tool output without concatenating; remap pathlib mkdir
Past the live-output cap stream_tool_execution built item + _drain_pending()
(the current chunk joined with every queued sibling) only to discard it in the
capped branch, so a chatty tool (yes, a tight print loop) could enqueue far
more than one poll interval of text and blow past the memory/CPU ceiling the
cap exists to enforce. Drain and drop queued items without building a combined
string, still counting each drain toward the heartbeat cadence so the SSE
keepalive survives.
Generated code often prepares code-interpreter paths with
Path('/mnt/data').mkdir(parents=True, exist_ok=True); pathlib drives that
through os.mkdir (not the patched os.makedirs) per component and, on
FileExistsError, probes the unpatched os.stat via Path.is_dir(), so the setup
raised before open() ever ran. Patch os.mkdir with the same remap and patch
Path.mkdir so the whole parents/exist_ok dance lands on the mapped working
directory and stays idempotent; real paths still pass through.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: generalize sandbox write remap and hint to any hallucinated absolute path
Models invent absolute paths from seeing their CWD (a DeepSeek run did
open('/home/ubuntu/Sandbox/flappy_bird.html', 'w') and died with
FileNotFoundError). A prefix list cannot enumerate these, so the sitecustomize
shim gains a write-mode fallback in open()/io.open(): when a write/create-mode
open targets an absolute path outside the CWD whose parent directory does not
exist, redirect it to the basename in the CWD and emit the same one-line stderr
notice, echoing the original path. The prefix remaps still run first (they cover
reads and preserve subpaths); read modes never hit the fallback so real system
files fail or succeed truthfully; bytes paths pass through. The fallback is not
applied to mkdir/makedirs/Path.mkdir, since creating an arbitrary absolute
directory can legitimately succeed on the host, and that decision is documented
in a comment.
The model-visible retry hint now echoes the real failing path (parsed from the
traceback tail) instead of the canned /mnt/data example, and fires for any
absolute path outside the working directory, not just the enumerated prefixes,
while a relative miss still gets no hint.
The shim wrapper still adds one frame to tracebacks that surface open() errors;
suppressing only our frame has no clean standard mechanism (a wrapper always
adds a frame), so the frame is left as an accepted compromise.
Tests: hallucinated absolute write remaps to the CWD basename across w/a/x/w+;
reads of a missing absolute path pass through untouched; writes to an existing
external dir pass through; prefix subpaths still preserved; end-to-end write
fallback lands the file in the sandbox workdir identically with and without
streaming; the hint echoes the actual path for convention and non-convention
absolute paths alike.
* Studio: kill exited process groups on drain; bound the over-cap output batch
_drain_process_output killed the process only via _kill_process_tree, which
short-circuits once the parent has exited, so a grandchild that inherited
stdout and outlived the parent was never signaled: a finite-timeout run could
return while it kept holding the pipe, and a timeout=None cancel left it
behind. Capture the setsid process group before waiting and SIGKILL that group
at both give-up points so the whole tree is torn down.
The streaming wrapper's first over-cap batch joined the current chunk with the
entire pending backlog before enforcing the live-output cap, so a chatty tool
could allocate far past the cap on the crossing batch. Bound the drain to the
remaining budget and drop the surplus in place, keeping the truncated output
byte-identical to joining everything.
* Studio: harden sandbox path healing and process/generator cleanup
Sandbox sitecustomize shim:
- Make the generalized write fallback collision-safe: never redirect an
invented absolute path onto an already-present CWD file (refuse and let the
original open raise FileNotFoundError, preserving the workspace file).
- Only w/a/x create a file; r+/rb+ are read-update modes that require the
target to exist, so a bare + no longer trips the write fallback.
- Gate every convention-prefix remap (/mnt/data, /mnt/outputs, /home/sandbox,
/workspace) on the prefix root being absent, so a real host mount is never
shadowed; a miss under an existing real prefix passes through.
- Patch os.open so Path.touch and other low-level creators heal convention
paths too, matching the Path.mkdir patch.
Local code execution (tools.py):
- Capture the setsid process group right after Popen (before any watcher can
poll/reap the leader) and thread it through the cancel watcher and drain.
- Kill the captured group in the non-streaming python/terminal timeout branch
so an exited leader no longer leaks a stdout-holding grandchild (matches the
streaming drain path).
- Guard os.getpgid/os.killpg by platform so streamed execution no longer
raises on Windows; fall back to single-pid kill.
- Judge missing-path hints against the executor's real workdir so a legitimate
miss inside a project workspace outside the sandbox root is not mislabeled.
Tool streaming routes (routes/inference.py):
- Drain a pending next(gen) worker before closing the generator in the
safetensors and Anthropic tool streams, so a disconnect no longer races
gen.close() (generator already executing) or leaks the thread/generator.
HTML to markdown:
- Only drop boilerplate lines composed entirely of known furniture phrases so
real prose that merely quotes one (for example "we use cookies to
authenticate requests") is preserved.
Adds hermetic tests for each change.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: keep aside callouts, contain sandbox path remaps, and keepalive dropped Anthropic tool events
_html_to_md: stop dropping <aside> unconditionally. Documentation pages
render notes/warnings/examples as aside admonition callouts; those inside
the selected article/main scope are real content. A furniture aside outside
the scope is already excluded by the main-content pass.
sitecustomize: contain the code-interpreter path remap under the sandbox
CWD. A hallucinated habit path such as /mnt/data/../other_session/file no
longer escapes the per-conversation workdir; parent-traversal components in
the suffix are dropped and a '.'/'..' write-fallback basename is refused.
routes/inference: emit a rate-limited comment keepalive when the Anthropic
Messages stream drops tool_output/tool_args events. A chatty tool keeps the
generator busy so the stall keepalive never fires and the tool wrapper emits
heartbeats only while idle, which left the SSE stream silent past proxy idle
caps; the OpenAI passthrough paths forward these events, this path now keeps
the connection alive.
* Studio: bound the tool-output chunk that first crosses the live cap
_drain_queue joined the entire chunk that first crossed the live-output
cap before dropping the rest, so a single multi-megabyte line (or any
chunk dequeued once the budget was already met at max_chars <= 0) was
materialized in full only to be truncated away, defeating the memory
ceiling the cap enforces. Slice the crossing chunk to one character past
the budget: that preserves the caller's overflow signal and its
byte-identical truncation while dropping the arbitrarily large remainder
in place.
* Studio: scope missing-path hint to the failing line, keepalive dropped-call output, and preserve truncated tool streams over byte length
- tools._missing_path_hint: the code-interpreter convention-prefix trigger
scanned the whole output, so a convention prefix mentioned only in a
traceback frame (a /workspace project root) or printed by the user's code
would add a misleading 'use a relative path' hint even when the actual
FileNotFoundError was a relative or in-workdir path. Scope the convention
test to the failing-path error line(s), matching _extract_missing_abs_path.
- _anthropic_tool_stream: the tool_output/tool_args rate-limited keepalive sat
after the drop_until_tool_end skip, so under disable_parallel_tool_use a
chatty second-or-later tool call was dropped whole with no keepalive, letting
an idle proxy kill the SSE stream. Check the keepalive branch before the drop
skip (like the heartbeat branch) so dropped-call output keeps the stream alive.
- preferFullToolOutput / chat-adapter: a truncated result can be longer than
the live stream by byte count once its footer, an 'Exit code N:' notice, or an
__IMAGES__ base64 tail is appended, so the length-only gate discarded the full
stream and the finished card fell back to the truncated text. Add a shared
truncation-aware shouldPreserveFullOutput used by both the write and read
sites: preserve the stream whenever the result carries the truncation footer.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: skip the habit-path hint for real project paths under a convention prefix
* Kill captured process group on streamed wait-timeout
The streamed drain path's proc.wait() timeout branch only called
_kill_process_tree(proc). If the leader exits in the narrow window between
the wait timing out and _kill_process_tree sampling its pgid, that helper
short-circuits on the reaped leader and a stdout-holding grandchild in the
same group survives. Also kill the captured pgid there, matching the
non-streaming communicate() timeout path. Adds a hermetic regression test
that models the reaped-leader race by stubbing _kill_process_tree.
* Fix 3.10 pathlib write_text remap and honor cancel in finite drain
On Python < 3.11 pathlib routes Path.open / read_text / write_text through
a module-level accessor singleton whose open attribute captured the original
io.open at import time (_NormalAccessor.open = io.open). Patching io.open in
the sandbox shim therefore never reached that captured reference, so a
Path('/mnt/data/x').write_text(...) raised FileNotFoundError on 3.10 while
passing on 3.11+ (which dropped the accessor and calls io.open at call time).
Repoint _NormalAccessor.open at the same io.open wrapper via a staticmethod,
guarded so it is an idempotent no-op on 3.11+. Keep the test save/restore
helpers symmetric so the accessor is restored too, and add a hermetic
write_text/read_text remap test that covers every version.
Also honor cancellation while draining inherited stdout after the leader
exits. Once the leader is reaped the cancel watcher returns (its loop is
while proc.poll() is None), so the finite-timeout drain did one blocking
reader.join(timeout=remaining) that ignored cancel_event and kept draining a
chatty grandchild for the whole budget after a disconnect/Stop. Poll
cancel_event in 0.5s slices against a deadline like the timeout=None branch
and kill the captured process group promptly on cancel. The normal path still
reaches EOF on its own, so the streamed vs non-streamed result is unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: port no-tool stream keepalive/drain and fix subprocess/queue/extraction asymmetries
Streaming no-tool paths now match their tool twins:
- _anthropic_plain_stream, safetensors/MLX no-tool stream, and standard GGUF
no-tool stream run next(gen) in a worker with a timed SSE keepalive loop so a
long prompt prefill cannot leave the stream idle past a proxy cap.
- The Anthropic plain and safetensors/MLX no-tool teardowns now drain the
pending next(gen) worker and close the generator on disconnect instead of
leaking the suspended generator.
Other asymmetries:
- Non-streaming _python_exec/_bash_exec always drain via _drain_process_output
(output_callback may be None) so a cancelled run reaps a stdout-holding
grandchild that outlived the leader instead of blocking in communicate(). The
joined bytes are identical to communicate(), so streamed vs non-streamed
results stay byte-identical.
- _build_bypass_env installs the sitecustomize path shim on PYTHONPATH (prepend,
keeping the operator's entries) so /mnt/data remap works in bypass mode too.
- GGUF forwards output_callback to execute_tool only when the callable accepts
it (shared accepts_output_callback), matching safetensors and preserving
legacy monkey-patched signatures.
- tool_stream_exec bounds accepted live output at the producer boundary so a
chatty tool cannot grow the queue without limit under consumer backpressure
and cannot keep the drain spinning and starve heartbeats.
- html_to_md implicit-close now searches past unclosed inline descendants so a
hidden <p>/<li> is closed by a following block; main-content scoping gates on
the largest single <article>/<main> so a swarm of tiny cards cannot pass the
threshold in aggregate and displace the real main.
- preferFullToolOutput re-attaches the "Exit code N:" prefix to the fuller
stream instead of appending the still-prefixed result, so a failed truncated
tool no longer duplicates its stdout in the finished card.
Adds hermetic tests for each.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Preserve short live output on timed-out tools; strip inline-CSS-hidden subtrees and score truncated main-content scopes
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Tighten chat tool streaming comments and docstrings
* Keep HTML READMEs from the GitHub API and preserve interrupted tool output
Convert a 200 HTML README body from the GitHub README API to Markdown
instead of discarding it and falling back to the repo page chrome, and
promote captured live stdout to full output when a tool never reaches
tool_end (stream interrupted or cancelled) so the partial diagnostics
stay on the finished card.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: anchor HTML sniff, keep repeated sandbox writes, reuse textual tool ids
Anchor _looks_like_html to the leading doctype/tag so a Markdown README that
opens with a fenced HTML example stays Markdown (no html_to_markdown
corruption), while bare HTML fragments (<body>/<article>/<section>) are still
detected and converted on a missing/wrong Content-Type.
Let the sandbox write fallback re-serve a target it already healed for the same
invented absolute path, so iterative overwrites of a generated artifact stop
failing with FileNotFoundError while the anti-clobber guard still refuses
unrelated same-basename files.
Reconcile the first textual tool call carrying an explicit id onto the open
provisional TEXT card instead of spawning a duplicate card under that id.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: run implicit-close before skipping tags and keep leading README tables as Markdown
A skipped block (<nav>/<footer>) is an HTML5 optional-end-tag closer of an
open <p>, but handle_starttag returned before the implicit-close bookkeeping,
so a never-closed <p hidden> kept its hidden mark and swallowed every following
sibling. Run _close_implicit before the skip decision so the hidden mark is
released and trailing content renders.
Drop <table> (and its <thead>/<tbody>/<tr>/<td>/<th> children) from the
_looks_like_html leading set: Markdown READMEs routinely open with a raw HTML
<table> badge/layout row, and sniffing that as HTML collapsed the whole
Markdown body through html_to_markdown, exactly like the already-excluded
<div align>/<p align> layout headers.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: make bypass-permissions Popen double faithful to the unified drain path
The non-streaming _python_exec/_bash_exec now share _drain_process_output,
which reads proc.stdout in a reader thread and calls proc.wait(); the test
double only implemented communicate(), so bypass-mode bash returned an
AttributeError instead of the faked output. Give _FakeProc a readable stdout
pipe (yields the fake line then EOF), wait()/poll()/pid, so the test exercises
the real drain path on both the python and bash bypass branches.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: persist sandbox path heals across runs and suppress nested hidden lists
* Studio: run tool Python child unbuffered (-u) so unflushed prints stream live
A long-running snippet doing bare print() without flush=True never reached
the live-output pane: CPython block-buffers stdout when writing to a pipe, so
_drain_process_output's readline() saw nothing until the buffer filled or the
process exited. Launch the child with the interpreter -u flag so stdout is
unbuffered and each print streams as it is produced.
-u is applied unconditionally on both the streaming and non-streaming path, so
the child invocation stays byte-identical with and without streaming and the
final joined result is unchanged (buffering/timing only). Unlike the earlier
PYTHONUNBUFFERED=1 env injection that was removed, -u does not pollute the
child's os.environ and is not visible via os.getenv.
* Render only the selected main-content subtree in html_to_markdown
The main-content heuristic sized each <article>/<main> candidate
individually to pick the largest subtree, but then rendered every
matching tag in the document. A page with one real article plus
sibling related-post cards or comment threads passed the size gate on
the real article yet still emitted the unrelated siblings.
Size and render the same chosen subtree so only the selected
main-content subtree reaches the output.
* Studio: tighten chat-tool-streaming fix comments
* Studio: store tool-output-scope separators as unicode escapes
The pane-scope and tool-output-key separators were literal NUL (0x00) bytes, which made git treat the file as binary and hide its diff and blame. Write them as \u0000 escapes instead; the runtime key value is unchanged.
* Studio: bound tool-stream teardown when the client disconnects
stream_tool_execution ran its yield loop with no try/finally, so a gen.close() on client disconnect (GeneratorExit at a yield) skipped the worker join and never signalled cancellation. A tool that does not poll cancel_event mid-flight (web_search, MCP, search_knowledge_base) then kept request teardown blocked until the tool's own timeout. Thread the request cancel_event into the wrapper, set it only on the abnormal-exit path so a clean multi-tool turn is unaffected, and bound the worker join to a few seconds; the daemon worker cannot outlive the process.
* Studio: sandbox path remap no longer masks missing reads
The sandbox sitecustomize shim remapped code-interpreter prefixes (/mnt/data, /workspace, ...) onto the working directory for every open mode, including reads. A read of a path that truly did not exist was silently redirected onto a same-basename workdir file instead of raising on the path the model used, hiding real missing-input errors. Remap writes and creates as before, but remap a read only when the mapped workdir target already exists (re-reading a just-written artifact); otherwise keep the original absolute path so the failure stays truthful.
* Studio: bound web fetch with one overall deadline and cancellation
The web fetch applied timeouts per network operation, so a GitHub README API attempt plus its HTML fallback plus up to five redirect hops could run well past the tool timeout, and nothing aborted once the client had disconnected. Add a single wall-clock deadline shared across the API attempt, the fallback, every redirect hop and the body read, cap each hop's socket timeout at the time left on the budget, and poll cancel_event. SSRF host pinning, per-hop redirect revalidation, the five-hop cap and the size cap are unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: keep tool-stream teardown off the event loop on disconnect
The bounded worker join added for disconnect safety still ran on an abnormal close, so a client disconnect could wait the full join timeout; and the safetensors and Anthropic tool streams closed their generator synchronously on the event loop, unlike the GGUF path. On abnormal exit the daemon worker is abandoned, so join with a zero timeout instead of waiting; offload the safetensors and Anthropic gen.close to a thread to match GGUF; and surface a heartbeat as soon as cancel_event is set while the worker is silent so the route regains control at once instead of after a heartbeat interval.
* Studio: extend the web-fetch deadline to DNS, the body read, and search
The overall fetch deadline did not cover host resolution or the response body read, and query-mode web_search ignored cancellation. Resolve hosts (initial and every redirect) on a budget-polled helper so a slow or pre-cancelled getaddrinfo aborts on time; read the capped body in chunks with the budget re-checked between them so a slow-drip server cannot stretch a single read past the deadline; and gate the blocking DDGS query on cancel_event on both sides. SSRF host pinning, per-hop redirect revalidation, the five-hop cap and the size cap are unchanged.
* Studio: defer the sandbox remap notice and tighten os.open create flags
The one-shot remap notice fired while computing the mapping, so a read that kept its original path emitted a false notice and spent the notice a later genuine remap needed. Only emit it once _remap_open commits to the redirect. Separately, os.open classified O_TRUNC / O_APPEND without O_CREAT as creating, but those cannot create a missing file, so a missing target now stays truthful (only O_CREAT maps to the creating mode).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: convert only genuine HTML README bodies, not Markdown with a leading block tag
The GitHub README API returns the raw file, almost always Markdown. _looks_like_html classified a Markdown README opening with a block tag (<ul>, <ol>, <dl>, <pre>, <blockquote>) as HTML, so _fetch_page_text ran it through html_to_markdown and collapsed its headings, lists and fenced code into a single line. Sniff the README body with a stricter document-level check (doctype or a leading <html>/<head>/<body>) so only a real .html README is converted; the general page path is unchanged.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Surface unclassified mid-stream Anthropic errors as SSE error events
The local Anthropic tool-stream and plain-stream paths called
_anthropic_stream_error_event(e) with force defaulting to False, so an
unclassified mid-stream failure (llama-server crash, decode OOM, a
dropped upstream socket) returned no event. The except block then fell
through to emitter.finish(), emitting a normal message_delta and
message_stop that masked a truncated turn as a clean finish.
Pass force = True at both fall-through sites so an unclassified failure
emits a 500 SSE error event and returns, matching the Anthropic
passthrough path that already forces it. Add regression tests covering
both stream paths.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: give each tool run a unique part id so finished cards keep their own output
Backend tool ids restart at call_0 every assistant response, and the
transient toolLiveOutput/toolFullOutput store maps were keyed by pane
scope plus that bare backend id. Two turns in the same pane therefore
shared one key: the stale-clear at tool_start only guards the forward
direction, so when a later call_0 finished and wrote its preserved full
output, every earlier still-mounted finished card reading the same key
re-rendered and displayed the newer tool's output instead of its own.
Mint one per-run-unique part id per backend id (call_0:<uuid>) and route
tool_start/output/args/end through a single resolver so all events for a
call resolve the same id. The durable part carries the unique id, so the
finished-card readers derive a collision-free key with no change, and the
awaiting-confirmation path keeps its own synthesized id. Outbound replay
stays paired (the assistant tool_call id and the role=tool result
tool_call_id both come from the part id) and gains unique ids across
turns, which strict providers require.
* Studio: tighten PR comments
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Studio: add Voice settings tab (dictation, dictionary, read aloud)
New Voice tab in Settings, placed just before About:
- Dictation: microphone picker, browser STT engine, recognition language,
and an inline mic test with a live transcript
- Dictation dictionary: entries rewrite matching speech to their exact
spelling and casing, applied in both dictation paths
- Recent dictations: last 20 final transcripts with copy and clear, so
text can be recovered if it lands in the wrong place
- Read aloud: optional button on assistant responses with two engines,
curated system voices (novelty and legacy voices filtered, quality
ranked, capped at 20) or the TTS audio model loaded in Unsloth via
/audio/generate (e.g. Orpheus), plus speed, pitch, volume and preview
Settings persist in localStorage (unsloth_voice_settings) and are read
at call time so changes apply without reloading the runtime. Adds en
keys plus the tab label for ja, zh-CN and pt-BR.
* Studio: drop the single option STT engine select, rename TTS option
The STT engine dropdown only had one entry, so it added noise without
giving a real choice. The engine row can come back once local STT
models land. Also renames the TTS engine option Unsloth TTS model to
Load TTS model to make the action clearer.
* Studio: harden Voice settings against edge cases found in simulation
Simulated the feature across Chromium, Firefox and WebKit plus node
level unit runs and backend contract checks. Fixes from the findings:
- Dictionary rewrite used a replacement string, so entries containing
dollar patterns corrupted transcripts (A$$AP became A$AP, $& injected
the match). Switched to the callback form of String.replace
- Persisted voice settings now validate types on hydration: non string
micDeviceId, dictationLanguage and ttsVoiceURI, and non boolean
ttsEnabled fall back to defaults instead of flowing into the UI
- Dictionary entries are trimmed, capped at 120 chars and re-sanitized
on hydration
- The Test dictation panel now falls back to the default microphone
when the saved device is unplugged, matching the composer adapter
Test coverage: 46 unit assertions (dictionary regex edge cases across
unicode, word boundaries and injection, voice curation for simulated
macOS, Windows and Linux voice inventories, corrupt storage merge),
13 backend contract checks against /audio/generate on an isolated
instance, and 60 browser assertions across the three engines covering
rendering, degradation without SpeechRecognition, curation in a real
DOM, dictionary persistence with unicode and dollar entries, the
no-model preview error path and corrupt localStorage recovery.
* Studio: address Voice settings review feedback
Verified each review comment before acting. Confirmed and fixed:
- Editing a dictionary entry was broken in two ways: the store trimmed
on every keystroke so spaces could not be typed, and clearing the
field deleted the entry and unmounted the input mid edit. Updates now
keep the raw value and a blur commit trims or removes the entry
- The unplugged mic fallback checked instanceof DOMException, but a
cross browser probe showed Firefox and WebKit throw
OverconstrainedError objects that are not DOMExceptions, so the
fallback never fired there. Matching on the error name now
- When the browser ended a dictation test on its own (silence timeout),
the mic stream stayed open. All recognition end paths now stop the
tracks and save the transcript through a single finalize path
- The studio TTS audio element now releases its WAV data URL as soon as
playback ends, fails or is cancelled
- Allow microphone now reports insecure contexts (no mediaDevices)
accurately instead of claiming access was blocked
- Voice tab copy moved into i18n keys per src/i18n/AGENTS.md, so locale
overlays can translate it; en is the baseline and parity passes
- unsloth_voice_settings added to the Reset all local preferences key
list so voice preferences obey the reset
- Non default microphones note that the system default is used when the
browser speech engine cannot bind a specific device, since browsers
without the start(track) overload ignore the argument silently
Re-ran the full simulation set after the changes: 46 unit assertions,
13 backend contract checks and 60 browser assertions across Chromium,
Firefox and WebKit all pass, plus a dedicated browser probe for the
dictionary editing behavior.
* Studio: use the chat mic icon in Voice settings for consistency
The Voice tab and its buttons used the hugeicons Mic02 glyph while the
chat composer uses a custom filled mic. Extract that composer icon into
a shared lib/mic-icon component, drop the duplicate inline copies in
thread.tsx and shared-composer.tsx, and use it for the Voice tab icon
and the tab's mic buttons so the microphone looks the same everywhere.
* Studio: address second round of Voice settings review feedback
Verified each new comment against the current code first. One item was
already fixed in the previous round (recording transcripts when the
browser ends a dictation test on its own). Confirmed and fixed:
- The microphone row showed a picker with generic names when browsers
enumerate unlabeled devices before permission, leaving no way to
grant access from the row. It now branches on whether labels are
visible and shows Allow microphone otherwise
- Compare chat dictation ignored the selected microphone. It now opens
the chosen device with the same fallback rules as the main adapter,
passes the track to recognition where supported and releases the
stream when recognition ends
- Closing the Voice tab cancelled the shared speechSynthesis even when
read aloud was playing a chat message. Cleanup now only cancels when
the tab owns an active preview
- Double clicking Start test could race two recognizers and leak the
first stream. A starting flag set before the getUserMedia await makes
start reentrancy safe
- Turning off the read aloud setting mid playback removed the only stop
control. The stop button now renders whenever a message is speaking
- When an engine lacks the start(track) overload, both dictation paths
now release the selected device stream before retrying with the
default microphone instead of holding it open
- Read aloud support no longer requires Web Speech synthesis: the
Unsloth TTS engine only needs audio playback, so it stays available
in WebViews without speechSynthesis, with a clear error if the system
engine is chosen there
Not addressed here: cancelling in flight backend TTS generation on
stop. The route runs generation in a worker thread without a
cancellation path, which is shared pre existing behavior with audio
chat generation and belongs in a backend change.
All suites re-run green: 46 unit, 13 backend contract and 60 browser
matrix assertions across Chromium, Firefox and WebKit, plus probes for
the unlabeled device branch and the double click race.
* Studio: drop empty and duplicate voiceURIs so the Voice tab never renders a crashing Select item
* Studio: guard dictation mic lifecycle in Voice test and Compare composer
Release a microphone opened after the component unmounts, and stop Compare
dictation on a permission or security failure instead of silently recording
from the default device, matching the main chat adapter.
* Studio: fix dictation and read-aloud lifecycle edge cases in Voice settings
- Join final dictation chunks with a space so recorded transcripts do not merge words
- Ignore a stale recognizer onend so a quick stop then restart is not torn down
- Use previewingRef so a double click on TTS preview does not orphan the first request
- Keep the read-aloud stop control visible when a new run starts while a message is spoken
- Stop the dictionary remove button from deleting an adjacent entry on a blur then click race
* Studio: trim redundant Voice settings comments
* Studio: fix Voice preview and Compare dictation edge cases
- Only cancel the shared speechSynthesis for a system-voice preview, so stopping
a Studio preview no longer stops an unrelated chat read-aloud
- Release the Studio preview audio and its WAV data URL on normal completion
- Iterate every finalized result in Compare dictation so batched phrases are kept
- Cap persisted recent dictations to the last 20 on hydration
* Studio: use clipboard fallback for recents and release failed preview audio
- Copy recent dictations via the copyToClipboard helper so the execCommand
fallback works in Safari and insecure http LAN contexts
- Release the Studio preview audio when play() rejects, not just on ended/error
* Studio: surface dictation and read-aloud failures instead of failing silently
- Compare dictation reports microphone and speech-recognition errors via toast,
reusing the main chat adapter's describeMediaError and describeSpeechError
- Read-aloud toasts genuine model or synthesis failures while ignoring cancellations
* Harden cross-browser microphone errors
* Surface voice test recognition errors and fall back to Studio TTS
- Voice test now toasts non-abort speech-recognition failures instead of
ending silently, matching the main and Compare dictation paths.
- Read-aloud routes to the backend model when the runtime lacks Web Speech
synthesis (audio-only WebView), so it no longer errors immediately.
* Fix read-aloud fallback controls
* Guard read-aloud stop when deleting a non-speaking message
aui.message().stopSpeaking() throws unless this message is the one being
read aloud, so calling it unconditionally rejected the delete handler before
the message was removed. Only stop speech when this message is speaking.
* Cap recent dictation transcript length before persisting
Recent dictations only limited entry count, so a long transcript stored the
full text in the persisted voice settings and a few could exceed the
localStorage quota, throwing synchronously from the uncaught dictation cleanup
path. Truncate each entry on save and on hydration, matching the dictionary cap.
* Harden read-aloud stop on delete and surface preview playback errors
- Deleting a message now stops read-aloud when the spoken message is among
those removed (including a user prompt's cascaded assistant replies), read at
click time and guarded so a playback end between render and click cannot
abort the delete.
- Voice preview now reports playback failures instead of silently resetting
the button, matching the read-aloud path.
* Remove stray review notes; notify TTS subscribers; drop regex lookbehind
- Remove plans/review_*.md scratch files accidentally committed earlier.
- Studio read-aloud now notifies speech subscribers on the async
starting -> running transition so status does not stay stuck at starting.
- Dictionary correction captures the leading boundary instead of a lookbehind
so it works on engines with dictation but no lookbehind (Safari < 16.4).
* Fix keyboard deletion of an emptied dictionary entry
Tabbing to a just-emptied row's Remove button blurred the input and
commit-spliced the empty row, so with index-keyed rows the button's keyboard
activation deleted the next entry. Skip the commit when focus moves to that
row's Remove button; the existing mouse guard is kept.
* Reapply Studio TTS playback rate on loadedmetadata
Some browsers reset an Audio element's playbackRate to 1 once the source
loads, so the selected speed could be dropped for read-aloud and voice
preview. Reapply it on loadedmetadata in both paths.
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Co-authored-by: danielhanchen <danielhanchen@gmail.com>
Daniel Han