# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
"""Source-contract guards for the model-picker per-model-config feature.
These are cheap, CPU-only, no-browser checks that read the frontend source and
assert the specific fixes that got the predecessor PR reverted stay in place. If
a future edit reverts one of them (e.g. rounds the context ceiling up again, or
puts the HF token back in the URL), the matching assertion reddens. They pair
with the runtime Playwright checks (which prove the behavior end to end) and the
backend pytest checks (which prove the backend logic).
"""
from __future__ import annotations
import re
from pathlib import Path
WORKDIR = Path(__file__).resolve().parents[2]
FRONTEND = WORKDIR / "studio" / "frontend" / "src"
def _read(rel: str) -> str:
path = FRONTEND / rel
assert path.exists(), f"missing source file: {path}"
return path.read_text(encoding = "utf-8")
def test_models_api_sends_token_via_header_not_query():
"""getModelConfig / checkVisionModel / checkEmbeddingModel must pass the HF
token through hubTokenHeader, never as a ?hf_token= query param (which leaks
the credential into server/proxy access logs)."""
src = _read("features/training/api/models-api.ts")
assert src.count("hubTokenHeader(") >= 3
assert "hf_token=" not in src
assert '"hf_token"' not in src and "'hf_token'" not in src
def test_model_metadata_probe_never_puts_token_in_query():
src = _read("features/model-picker/api/model-metadata.ts")
assert "hf_token=" not in src
assert '"hf_token"' not in src and "'hf_token'" not in src
def test_model_config_page_floors_the_context_ceiling():
"""The model's native max-context must be FLOORED to the step grid, never
rounded up (rounding up can offer/persist a length above the model's real
ceiling and break loading)."""
src = _read("features/model-picker/components/model-config-page.tsx")
assert "floorMaxSeqLength(modelMaxPosition.maxPositionEmbeddings)" in src
assert "normalizeMaxSeqLength(modelMaxPosition.maxPositionEmbeddings)" not in src
def test_compare_load_clears_stale_native_lease():
"""A compare-pane load never comes from the desktop file picker, so it must
clear any prior picked file's lease token + expiry, otherwise a reload can
send a stale lease for the now-active model."""
src = _read("features/chat/shared-composer.tsx")
assert "activeNativePathToken: null" in src
assert "activeNativePathExpiresAtMs: null" in src
def test_autoload_records_backend_loaded_model_identity():
"""An inactive-cache inventory row loads by local path, so startup autoload
must key both the active checkpoint and its summary by the backend's loaded
model identity instead of the catalog repo id."""
src = _read("features/chat/api/chat-adapter.ts")
autoload = src.split("async function loadAutoLoadCandidate", 1)[1]
autoload = autoload.split("\n try {", 1)[0]
assert "const loadedModelId = loadResp.model || modelPath" in autoload
assert "setCheckpoint(loadedModelId," in autoload
assert "id: loadedModelId" in autoload
assert "m.id === loadedModelId" in autoload
def test_rollback_restores_native_lease_expiry_with_token():
"""A failed model switch that rolls back to a previously loaded picked GGUF
must restore the lease expiry paired with the token, never the token alone
(which would look non-expiring and skip the expiry guard)."""
src = _read("features/chat/hooks/use-chat-model-runtime.ts")
assert "previousActiveNativePathExpiresAtMs" in src
assert re.search(
r"activeNativePathExpiresAtMs:\s*previousActiveNativePathToken", src
), "rollback must restore the expiry alongside the token"
def test_default_caches_keyed_on_inventory_version():
"""The chat-template and max-position caches must key on the inventory
version so a model update in the same session invalidates the cached value
instead of showing the stale revision."""
src = _read("features/model-picker/hooks/use-model-defaults.ts")
# Both cache keys (template + max-position) end with the inventory version.
assert src.count("${inventoryVersion}") >= 2
def test_hidden_infra_model_needles_present():
"""The frontend static needle list must keep hiding the RAG embedder and the
llama.cpp validation probe."""
src = _read("features/hub/lib/hidden-models.ts")
assert '"bge-small-en-v1.5"' in src
assert '"ggml-org/models"' in src
assert '"stories260k.gguf"' in src
def test_hidden_models_dynamic_exact_ids_wired():
"""The configured embedder arrives from /api/hub/hidden-models as exact
repo ids; a substring needle would let a generic basename like "model"
hide unrelated chat models."""
src = _read("features/hub/lib/hidden-models.ts")
assert "toLowerStrings(data.exact_ids)" in src
assert "dynamicExactIds.includes(lower)" in src
def test_hidden_model_matchers_refresh_with_inventory_version():
src = _read("features/hub/lib/hidden-models.ts")
assert "const version = getInventoryVersion()" in src
assert "matchersFetchVersion === version" in src
assert "getInventoryVersion() !== version" in src
def test_diffusion_capability_labeled_image_generation():
"""The diffusion capability detects image GENERATORS (FLUX, SDXL,
text-to-image tags); labeling it "Image to text" showed generators when
users asked for captioning models."""
for rel in (
"features/hub/lib/model-capabilities.ts",
"features/hub/lib/model-type-filter.ts",
"features/hub/lib/view-models.ts",
):
src = _read(rel)
assert "Image to text" not in src, rel
assert "Image generation" in src, rel
def test_active_model_config_round_trips_gpu_fields():
"""The active model's config must carry the GPU Memory knobs (GGUF only) so
a sidebar/hub-gear reload cannot silently reset manual GPU settings, and
"Remember settings" cannot persist a GPU-less config over a saved one."""
src = _read("features/model-picker/hooks/use-active-model-config.ts")
for field in ("gpuMemoryMode", "gpuLayers", "nCpuMoe", "selectedGpuIds"):
assert field in src, field
assert "if (!isGguf)" in src and "return base" in src
for rel in (
"features/chat/chat-page.tsx",
"features/hub/catalog/sampling-settings-dialog.tsx",
):
assert "useActiveModelConfig(" in _read(rel), rel
signature = _read("features/model-picker/components/sidebar-model-config.tsx")
assert "gpuFieldsSignature(config)" in signature
shared = _read("features/model-picker/model-config/apply-per-model-config.ts")
assert "export function gpuFieldsSignature" in shared
def test_gpu_picker_round_trips_requested_pool_not_fitted_subset():
"""A GGUF fit may narrow [0, 1] to [0], but load/status hydration must keep
[0, 1] as the editable pool so a later reload can grow back onto GPU 1."""
types = _read("features/chat/types/api.ts")
assert types.count("requested_gpu_ids?: number[] | null") >= 2
store = _read("features/chat/stores/chat-runtime-store.ts")
assert "resp.requested_gpu_ids ?? resp.gpu_ids ?? null" in store
status = _read("features/chat/lib/apply-inference-status-to-store.ts")
assert "status.requested_gpu_ids ?? status.gpu_ids ?? null" in status
def test_compare_load_uses_each_models_gpu_config():
src = _read("features/chat/shared-composer.tsx")
assert "ownConfig.gpuMemoryMode ?? compareLoadKnobs.gpuMemoryMode" in src
assert "ownConfig.gpuLayers ?? compareLoadKnobs.gpuLayers" in src
assert "ownConfig.nCpuMoe ?? compareLoadKnobs.nCpuMoe" in src
assert "if (ownConfig.selectedGpuIds != null)" in src
assert "reconcilePersistedGpuIds(ownConfig.selectedGpuIds)" in src
for field in (
"gpu_memory_mode: effectiveGpuMemoryMode",
"gpu_layers: effectiveGpuLayers",
"n_cpu_moe: effectiveNCpuMoe",
"gpu_ids: effectiveSelectedGpuIds ?? undefined",
):
assert field in src
def test_active_native_gguf_metadata_uses_path_token():
src = _read("features/model-picker/components/model-config-page.tsx")
assert "(isActiveModel ? activeNativePathToken : null)" in src
assert "target.meta.nativePathToken ??" in src
assert "nativePathToken," in src
assert '${nativePathToken ?? ""}' in src
def test_model_default_hooks_do_not_reset_state_in_effect():
src = _read("features/model-picker/hooks/use-model-defaults.ts")
assert "setFetched(null)" not in src
def test_variant_expander_refreshes_after_delete():
"""Deleting a downloaded quant from an expanded repo that still has other
cached quants must bump the expander refresh key, or the deleted quant stays
shown as downloaded and clickable and tries to reload the removed file."""
src = _read("features/model-picker/components/model-selector/pickers.tsx")
del_confirm = re.search(
r"await onDeleteVariant\(v\.quant\);.*?setRefreshKey\(\(key\) => key \+ 1\)",
src,
re.S,
)
assert del_confirm, "delete onConfirm must bump refreshKey after a successful delete"
def test_local_picker_rows_require_chat_capability():
"""Local inventory rows can be classified non-chat (canChat false, e.g. a
folder with only config.json). The picker must filter those out, or selecting
one loads a weightless path; toLocalModelInfo drops capabilities so the memo
is the only place the guard can live."""
src = _read("features/model-picker/inventory/use-chat-picker-inventory.ts")
memo = re.search(r"const localModels = useMemo\(.*?\[inventory\.localRows\]", src, re.S)
assert memo, "localModels memo not found"
assert "row.capabilities.canChat" in memo.group(0)
def test_model_picker_toolbar_reflows_before_crossing_picker_edge():
"""The content-sized section tabs and fixed-width dropdowns must reflow,
while an oversized tab group must shrink labels but preserve its icons."""
picker = _read("features/model-picker/components/model-selector/pickers.tsx")
assert '"flex flex-wrap items-center gap-2"' in picker
assert 'hasConnected ? "-mr-4" : "-mr-2"' in picker
assert '"flex max-w-full min-w-0 flex-wrap items-center gap-2"' in picker
tabs = _read("features/model-picker/components/model-selector/pill-tabs.tsx")
assert 'fit ? "min-w-0 shrink" : "min-w-0 flex-1"' in tabs
assert '{tab.label}' in tabs
selector = _read("features/model-picker/components/model-selector.tsx")
assert 'icon={StarIcon} className="size-3.5 shrink-0"' in selector
assert 'icon={Download01Icon} className="size-3.5 shrink-0"' in selector
assert 'icon={CloudIcon} className="size-3.5 shrink-0"' in selector
def test_native_picked_gguf_template_read_through_lease():
"""A native (picked / drag-drop) GGUF's path lives only in its signed lease,
and the picker chat-template GET has no lease plumbing, so the default
template must be read through the lease-aware validate probe: mint a
validate-model lease and post include_chat_template. The native token also
has to reach the fetch (threaded through the hook) and be part of the cache
key so two picks of the same basename don't share a template."""
api = _read("features/model-picker/api/templates.ts")
assert 'consumeNativePathToken(nativePathToken, "validate-model")' in api
assert "include_chat_template: true" in api
assert "/api/inference/validate" in api
hook = _read("features/model-picker/hooks/use-model-defaults.ts")
assert "nativePathToken," in hook
assert '${nativePathToken ?? ""}' in hook
def test_model_load_guard_is_cross_instance():
"""The in-flight load guard must consult the shared store pick (not only the
per-hook ref) and ejectModel must refuse while any instance is loading:
three live useChatModelRuntime instances exist (chat page, hub page, hub
gear dialog)."""
src = _read("features/chat/hooks/use-chat-model-runtime.ts")
assert "useChatRuntimeStore.getState().loadingModelPick" in src
assert "clearLoadingModelPick" in src
eject_body = src.split("const ejectModel", 1)[1]
assert "loadingModelPick" in eject_body.split("ejectModel,", 1)[0]
def test_partial_safetensors_download_keeps_delete_menu():
"""A stopped partial safetensors download must keep its options menu (the
Delete affordance) like the GGUF card does, or partial downloads can only
be cleaned up by finishing or leaving them. During an ACTIVE download the
menu stays hidden (every item would be disabled: no Copy path while not
downloaded, no Delete while downloading, pin suppressed in the run bar)."""
src = _read("features/hub/catalog/safetensors-download-card.tsx")
assert "(isDownloaded || (isPartial && !downloading))" in src
def test_pinned_validation_uses_cached_local_variant_listing():
"""Pinned-quant validation must use the TTL-cached hub client with
preferLocalCache (downloaded-ness is local state) instead of one uncached
round-trip per pinned repo on every picker open. Picker deletes must go
through the hub inventory client, whose delete invalidates both the
variants TTL cache and the server-side HF cache scan (the legacy
/api/models/delete-cached route invalidates neither, so a post-delete
inventory refresh would resurrect the deleted row until the scan TTL)."""
src = _read("features/model-picker/components/model-selector/pickers.tsx")
assert "listGgufVariantsCached(" in src
assert "preferLocalCache: true" in src
assert re.search(r'import \{[^}]*\bdeleteCachedModel\b[^}]*\} from "@/features/hub"', src)
hub_api = _read("features/hub/inventory/api.ts")
delete_fn = hub_api.split("export async function deleteCachedModel", 1)[1]
delete_fn = delete_fn.split("export ", 1)[0]
assert "invalidateGgufVariantsCache(" in delete_fn
assert "bumpInventoryVersion(" in delete_fn
def test_chat_autoload_scopes_variant_lookup_to_cached_repo_path():
"""Autoload must probe the exact cache row it will load, including rows
retained from a previously selected Hugging Face cache."""
src = _read("features/chat/api/chat-adapter.ts")
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
# Both cached-repo lookups (remembered model and cascade) route through
# the memoized scanRepoVariants, which carries the cache-scoped params.
scan_fn = auto_load.split("const scanRepoVariants = (", 1)[1]
scan_fn = scan_fn.split("return pending;", 1)[0]
assert "preferLocalCache: true" in scan_fn
assert "localPath," in scan_fn
assert auto_load.count("await scanRepoVariants(repo.repo_id, repo.cache_path)") == 2
chat_api = _read("features/chat/api/chat-api.ts")
variants_fn = chat_api.split("export async function listGgufVariants", 1)[1]
variants_fn = variants_fn.split("export interface KvCacheEstimate", 1)[0]
assert 'params.set("prefer_local_cache", "true")' in variants_fn
assert 'params.set("local_path", localPath)' in variants_fn
def test_cache_location_update_invalidates_frontend_inventory():
"""A successful cache switch must refresh both inventory rows and cached
GGUF variant results before any stale active-cache identity can be reused."""
src = _read("features/settings/api/hugging-face-cache.ts")
update_fn = src.split("export async function updateHuggingFaceCacheSettings", 1)[1]
assert "bumpInventoryVersion();" in update_fn
assert "invalidateGgufVariantsCache();" in update_fn
def test_downloaded_list_offsets_virtual_rows():
"""The On Device virtualized list sits below the Pinned block in the same
scroll element, so it must pass its measured offset as scrollMargin or rows
past the overscan render blank."""
src = _read("features/hub/catalog/models-catalog-lists.tsx")
assert "scrollMargin={scrollMargin}" in src
def test_local_gguf_diagnostics_gate_on_broad_is_gguf():
"""The MTP fallback note and the context/VRAM warning must gate on the broad
isGguf (variant, loaded gguf context, or .gguf suffix), not the variant-only
isLoadedGguf, so direct-file and custom-folder GGUF loads keep those
diagnostics."""
src = _read("features/chat/chat-settings-sheet.tsx")
spec = re.search(r"const showSpecFallback =.*?;", src, re.S)
vram = re.search(r"const showContextVramWarning =.*?;", src, re.S)
assert spec and "isGguf &&" in spec.group(0) and "isLoadedGguf" not in spec.group(0)
assert vram and "isGguf &&" in vram.group(0) and "isLoadedGguf" not in vram.group(0)
def test_fixed_layer_gguf_pins_displayed_context():
"""An already-loaded auto-fit GGUF saved with Manual fixed GPU layers must
pin the shown context, so a later fresh load keeps the fitted placement
instead of sending native/0 and recreating the OOM."""
src = _read("features/model-picker/components/model-config-page.tsx")
assert "const pinFixedLayerContext =" in src
assert 'config.gpuMemoryMode === "manual"' in src
assert "customContextLength: activeLoadedContext" in src
def test_fixed_layer_pin_recomputed_after_committing_gpu_layers():
"""pinFixedLayerContext is computed from the render-time config, before a
same-click GPU Layers draft is committed. handleRun must recompute it from the
committed effectiveConfig; otherwise typing a positive GPU Layers value on an
auto-fit GGUF and clicking Reload saves customContextLength: null, so a later
fresh load sends the native context with fixed layers (the OOM the pin avoids)."""
src = _read("features/model-picker/components/model-config-page.tsx")
assert "const effectivePinFixedLayerContext =" in src
assert 'effectiveConfig.gpuMemoryMode === "manual"' in src
assert "effectiveConfig.gpuLayers != null" in src
assert "effectiveConfig.customContextLength == null" in src
assert "{ ...effectiveConfig, customContextLength: activeLoadedContext }" in src
def test_blur_cache_cleared_on_every_settled_render():
"""The lastBlurCommittedRef bridge is valid only across the single synchronous
same-click gesture that set it. Keying its clear on [value] missed a Reset (or
external edit) that restores the shown value unchanged after the blur dispatched
onChange: value nets back to its prior number, the effect never re-ran, and a
later Load/Save replayed the override Reset removed. Clear it on every settled
render instead."""
src = _read("features/model-picker/components/numeric-value-input.tsx")
# The clearing effect must run on every commit, not be gated on [value] alone.
assert not re.search(r"lastBlurCommittedRef\.current = null;\s*\}, \[value\]\);", src)
assert re.search(
r"useEffect\(\(\) => \{\s*lastBlurCommittedRef\.current = null;\s*\}\);",
src,
)
def test_auto_defaults_not_persisted_as_overrides():
"""Auto GPU memory mode and Auto/default speculative type are follow-global
defaults; normalization must not persist them as per-model overrides, else a
model stops following later changes to the global preference."""
src = _read("features/model-picker/model-config/per-model-config.ts")
assert 'if (partial.gpuMemoryMode === "manual") {' in src
assert 'partial.gpuMemoryMode === "auto" || partial.gpuMemoryMode === "manual"' not in src
spec = re.search(r'if \(s === "auto" \|\| s === "default"\) \{\s*return ([^;]+);', src)
assert spec and spec.group(1).strip() == "null"
def test_compare_pane_context_from_own_config_only():
"""A compare pane's context comes from its own config only (a saved pin, else
null for Auto/native); it must not inherit the active model's shared snapshot,
which resolveFitMaxSeqLength would treat as an explicit pin (VRAM/OOM)."""
src = _read("features/chat/shared-composer.tsx")
assert "const effectiveCustomContextLength = ownConfig.customContextLength;" in src
assert "compareLoadKnobs.customContextLength" not in src
def test_reset_max_seq_length_falls_back_to_app_default():
"""After Reset clears maxSeqLength (null), a non-GGUF active model's shown
max sequence length must fall back to the app default, never the loaded
runtime snapshot, or a remembered/active override can never be cleared."""
src = _read("features/model-picker/components/model-config-page.tsx")
# The null fallback resolves to the app-default constant, not a runtime value.
assert "clampMaxSeqLength(DEFAULT_MAX_SEQ_LENGTH, nativeMaxSeqLength)" in src
# The buggy runtime-seeded fallback must not come back.
assert "clampMaxSeqLength(initialMaxSeqLength" not in src
def test_reset_persists_null_max_length_and_substitutes_only_for_load():
"""The persisted per-model record must keep config.maxSeqLength (null after
Reset) so isDefaultConfig can clear a remembered override; the concrete
fallback is substituted only into the load request, not the saved record."""
src = _read("features/model-picker/components/model-config-page.tsx")
# Load-only substitution of the resolved value (recomputed from any committed
# same-click Max Seq Length draft, so it is never dropped).
assert "maxSeqLength: effectiveMaxSeqLengthValue" in src
assert "const effectiveLoadConfig" in src
# The persisted record is saved from effectiveRuntimeConfig; the load request
# carries effectiveLoadConfig (with any committed context input).
assert "onRun(effectiveLoadConfig)" in src
assert "savePerModelConfig(" in src
def test_initial_load_uses_staged_config_payload():
"""Run-settings Load must pass the staged config through to /load even when
React has not flushed NumericValueInput blur commits into the store yet."""
runtime = _read("features/chat/hooks/use-chat-model-runtime.ts")
assert "const pendingLoadConfig =" in runtime
assert "pendingLoadConfig?.kvCacheDtype" in runtime
assert "pendingLoadConfig?.customContextLength" in runtime
page = _read("features/model-picker/components/model-config-page.tsx")
assert "contextInputRef" in page
assert "contextInputRef.current?.commit()" in page
numeric = _read("features/model-picker/components/numeric-value-input.tsx")
assert "export type NumericValueInputHandle" in numeric
assert "commit:" in numeric
# P1: commit returns null unless the user actually edited the field,
# so Load/Save with untouched Auto does not pin native context.
assert "dirtyRef.current" in numeric
assert "return null;" in numeric
# P2: blur clears dirtyRef after commit so Reset/slider cannot be
# overwritten by a stale draft on a later Load.
assert "dirtyRef.current = false;" in numeric
assert "draftRef.current = String(final);" in numeric
# Same-click Load after blur still sees the committed draft.
assert "lastBlurCommittedRef" in numeric
# Invalid drafts must not turn Auto into an explicit pin.
assert "const commitDraft = (raw: string): number | null" in numeric
assert re.search(r"if \(!Number\.isFinite\(parsed\)\) \{\s*return null;", numeric)
assert re.search(
r"if \(final == null\) \{\s*"
r"draftRef\.current = String\(value\);\s*"
r"lastBlurCommittedRef\.current = null;",
numeric,
)
# handleRun only promotes commit() when non-null.
assert "committedContext != null" in page
assert "pendingPatch.customContextLength = committedContext;" in page
def test_same_click_commit_covers_all_numeric_inputs():
"""The same-click blur bridge must flush every NumericValueInput-backed
setting, not just Context Length. Max Seq Length (non-GGUF), GPU Layers and
MoE Layers (GGUF) also stage their draft only on blur, so handleRun must
imperatively commit each and fold the value into the staged load config;
otherwise a value the user typed right before clicking Load/Reload is lost."""
page = _read("features/model-picker/components/model-config-page.tsx")
# Each numeric input owns an imperative handle that handleRun commits, and the
# handle is forwarded down to the actual NumericValueInput.
for ref in ("maxSeqLengthInputRef", "gpuLayersInputRef", "moeLayersInputRef"):
assert f"const {ref} = useRef(null);" in page
assert f"{ref}.current?.commit()" in page
assert f"inputRef={{{ref}}}" in page
# The leaf sub-components accept and forward the handle as a ref.
assert page.count("inputRef?: Ref;") >= 2
assert "ref={inputRef}" in page
# Committed drafts are folded into the staged config, gated on non-null so an
# untouched field never fabricates an override.
assert "committedMaxSeqLength != null" in page
assert "committedGpuLayers != null" in page
assert "committedMoeLayers != null" in page
assert "pendingPatch.gpuLayers = committedGpuLayers;" in page
assert "pendingPatch.nCpuMoe = committedMoeLayers;" in page
# The non-GGUF load path substitutes the committed Max Seq Length draft.
assert "const effectiveMaxSeqLengthValue =" in page
assert "maxSeqLength: effectiveMaxSeqLengthValue" in page
def test_context_commit_rechecks_persistence_only_shortcut():
"""Committed context changes must bypass persistence-only saves."""
src = _read("features/model-picker/components/model-config-page.tsx")
assert "const effectiveConfig =" in src
assert "perModelConfigsEqual(effectiveConfig, baseline)" in src
assert "const effectivePersistenceOnly =" in src
assert "if (effectivePersistenceOnly)" in src
def test_reset_enabled_for_explicit_context_pin_at_native():
"""An explicit customContextLength that equals the native ceiling is still a
user override, so contextAtDefault must require customContextLength == null.
The buggy form treated `contextValue === native` alone as default, wedging
the Reset button disabled for a deliberate pin-to-native."""
src = " ".join(_read("features/model-picker/components/model-config-page.tsx").split())
assert (
"const contextAtDefault = !target.isGguf || "
"(config.customContextLength == null && "
"(nativeContextLength == null || contextValue === nativeContextLength));" in src
)
# The old form that ignored an explicit pin equal to native must not return.
assert (
"(nativeContextLength == null ? config.customContextLength == null : "
"contextValue === nativeContextLength)" not in src
)
# The app-default constant is the single source of truth (imported, not local).
assert "DEFAULT_MAX_SEQ_LENGTH," in src
assert "const DEFAULT_MAX_SEQ_LENGTH = 4096" not in src
def test_compare_pane_non_gguf_falls_back_to_app_default():
"""A non-GGUF compare pane with no saved maxSeqLength must fall back to the
shared app default, not the active model's runtime snapshot; otherwise an
unconfigured pane inherits a saved 128K neighbor's context and can OOM."""
per_model = _read("features/model-picker/model-config/per-model-config.ts")
assert "export const DEFAULT_MAX_SEQ_LENGTH = 4096;" in per_model
barrel = _read("features/model-picker/index.ts")
assert "DEFAULT_MAX_SEQ_LENGTH," in barrel
src = " ".join(_read("features/chat/shared-composer.tsx").split())
assert "DEFAULT_MAX_SEQ_LENGTH," in src
assert (
"const effectiveMaxSeqLength = ownConfig.customContextLength ?? "
"normalizeMaxSeqLength(ownConfig.maxSeqLength) ?? "
"(isGgufLoad ? 0 : DEFAULT_MAX_SEQ_LENGTH);" in src
)
# The buggy fallback to the active model's shared runtime value must not return.
assert "(isGgufLoad ? 0 : maxSeqLength)" not in src
assert "const maxSeqLength = store.params.maxSeqLength;" not in src
def test_default_gpu_mode_clears_manual_knobs():
"""Switching GPU Memory back to Default must clear the Manual-only knobs
(gpuLayers/nCpuMoe/selectedGpuIds); otherwise a remembered config keeps stale
pins that a later load re-applies when the global preference is Manual."""
src = _read("features/model-picker/components/model-config-page.tsx")
assert 'gpuMemoryMode: "auto",' in src
assert "gpuLayers: undefined," in src
assert "nCpuMoe: undefined," in src
assert "selectedGpuIds: undefined," in src
def test_legacy_migration_is_idempotent_and_non_destructive():
"""The v1->v2 localStorage migration (unsloth_load_settings ->
unsloth_model_configs) is invoked on every store read, so it must be
idempotent: repeated reads, browser reloads, and Studio restarts must never
re-migrate, duplicate records, or overwrite a newer per-model config. This
was the class of regression that reverted the predecessor PR, so pin all
three idempotency layers at source level; dropping any of them reddens here.
"""
raw = _read("features/model-picker/model-config/per-model-config.ts")
src = " ".join(raw.split())
# Migration runs from readMap (every store read), so it must be safe to repeat.
assert (
"function readMap(): StoredMap { migrateLegacyLoadSettingsOnce(); "
"return readMapRaw(); }" in src
)
# Layer 1: in-memory once-per-session guard so repeated readMap() calls
# migrate at most once.
assert "let legacyMigrationChecked = false;" in src
assert "if (legacyMigrationChecked || !canUseStorage()) {" in src
assert "legacyMigrationChecked = true;" in src
# Layer 2: persistent cross-session flag so a completed migration is never
# redone. Set in every terminal branch (malformed data, nothing to migrate,
# successful write); a failed quota write leaves it unset so the next session
# retries. Three set-sites encode exactly that.
assert 'const LEGACY_MIGRATION_FLAG = "unsloth_model_configs_migrated";' in src
assert "if (localStorage.getItem(LEGACY_MIGRATION_FLAG)) {" in src
assert src.count('localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");') >= 3
# Layer 3: non-overwriting merge skips an existing (or default) key, so even a
# forced re-run cannot duplicate or clobber a user's config.
assert "if (isDefaultConfig(migrated) || Object.hasOwn(map, key)) {" in src
# ---------------------------------------------------------------------------
# Send-with-no-model auto-load (issue #7374): on-device discovery must cover
# every picker inventory source, the remembered model must survive local
# (non-cache) loads, and the send path must never start a remote download.
# ---------------------------------------------------------------------------
def _autoload_section() -> str:
src = _read("features/chat/api/chat-adapter.ts")
return src.split("async function autoLoadOnDeviceModel", 1)[1]
def test_send_path_cannot_reach_hardcoded_default_download():
"""Pressing Send with no model loaded must never fetch the hard-coded
default repo from Hugging Face (the unconsented download in the bug
report). Any recommended download must stay an explicit user action."""
src = _read("features/chat/api/chat-adapter.ts")
assert "Qwen3.5-4B-MTP-GGUF" not in src
assert "Downloading a small model" not in src
assert "No downloaded models found" not in src
# The old entry point must not linger anywhere.
assert "autoLoadSmallestModel" not in src
# The renamed entry point runs exactly once per send, so the submitted
# prompt executes exactly once after a successful load.
assert src.count("await autoLoadOnDeviceModel())") == 1
def test_autoload_no_model_error_is_actionable():
"""With no valid on-device candidate the user is told to select or
explicitly download a model instead of getting a silent remote load."""
src = _read("features/chat/api/chat-adapter.ts")
assert "Select a model in the top bar, or download one from the Hub, then retry." in src
def test_autoload_inventory_failure_is_not_empty_inventory():
"""A failed cached/local inventory request must stop the automatic
selection path, not be swallowed into an empty list that used to fall
through to the remote default download."""
src = _read("features/chat/api/chat-adapter.ts")
assert ".catch(() => [])" not in src
auto_load = _autoload_section()
assert "inventoryErrorSurfaced: true" in auto_load
# All three inventory sources are queried together and fail closed.
for needle in (
"listCachedGguf(hfToken)",
"listCachedModels(hfToken)",
"listLocalModels()",
):
assert needle in auto_load, needle
def test_autoload_uses_unified_backend_inventory():
"""Auto-load must consume the same non-React backend inventory the
unified picker uses (no second frontend filesystem scanner), covering
the models dir, LM Studio dirs, and custom scan folders."""
src = _read("features/chat/api/chat-adapter.ts")
assert re.search(
r'import \{[^}]*listLocalModels[^}]*\} from "@/features/hub/inventory/api"',
src,
re.S,
)
sources = re.search(r"const AUTO_LOAD_LOCAL_SOURCES[^;]*;", src, re.S)
assert sources, "AUTO_LOAD_LOCAL_SOURCES not found"
for source in ('"models_dir"', '"lmstudio"', '"custom"'):
assert source in sources.group(0), source
def test_autoload_filters_match_picker_policy():
"""Only complete, chat-capable, non-hidden rows may auto-load: partial
downloads, weightless/non-chat folders, and infrastructure models are
excluded with the same policy the picker applies."""
src = _read("features/chat/api/chat-adapter.ts")
local_fn = src.split("function isAutoLoadableLocalRow", 1)[1]
local_fn = local_fn.split("\nfunction ", 1)[0]
assert "row.capabilities?.can_chat !== true" in local_fn
assert "row.partial" in local_fn
# Adapters resolve their base model on load; a Hub-id base would start
# the implicit remote fetch a background auto-load must never trigger.
assert 'row.model_format === "adapter"' in local_fn
assert "isHiddenModelId(row.model_id, row.id, row.path)" in local_fn
# The name-based marker only applies to direct .gguf files; a directory
# named e.g. /models/foo-be says nothing about the files inside it, which
# are filtered per-file during variant resolution.
assert 'row.path.toLowerCase().endsWith(".gguf") &&' in local_fn
assert "hasBigEndianGgufMarker(row.path, row.format_variant)" in local_fn
cached_fn = src.split("function isAutoLoadableCachedRepo", 1)[1]
cached_fn = cached_fn.split("\nconst ", 1)[0]
assert "repo.partial" in cached_fn
# Cached adapter repos are chat-capable too and resolve a base model on
# load, so they must be excluded exactly like local adapter rows.
assert 'repo.model_format === "adapter"' in cached_fn
assert "repo.capabilities?.can_chat === false" in cached_fn
assert "isHiddenModelId(repo.repo_id)" in cached_fn
def test_autoload_local_rows_load_via_backend_target():
"""Indexed local rows (models dir, LM Studio, custom scan folders) must
load through the backend-provided target and record their stable
inventory identity, never a reconstructed path or synthetic variant."""
src = _read("features/chat/api/chat-adapter.ts")
assert "function localRowLoadTarget" in src
assert "row.load_id || row.id" in src
candidate_fn = src.split("function localRowToCandidate", 1)[1]
candidate_fn = candidate_fn.split("\n/**", 1)[0]
assert "loadId: localRowLoadTarget(row)" in candidate_fn
assert "inventoryId: row.inventory_id ?? null" in candidate_fn
# Inactive-cache rows keep loading by their backend load_id.
auto_load = _autoload_section()
assert auto_load.count("loadId: repo.load_id") >= 3
def test_autoload_remembers_last_model_across_all_sources():
"""The remembered model resolves against managed caches AND the indexed
local inventory; a stale entry only falls through to other on-device
candidates (there is no remote branch left to reach)."""
auto_load = _autoload_section()
assert "isManagedCacheSource(lastLoaded.source)" in auto_load
assert "matchesRememberedLocalRow(candidateRow, lastLoaded)" in auto_load
assert "await resolveLocalRowCandidate(" in auto_load
assert "lastLoaded.ggufVariant," in auto_load
# Managed-cache candidates record their provenance for later resolution.
assert auto_load.count('source: "hf_cache"') >= 4
def test_autoload_deduplicates_cached_and_local_candidates():
"""Candidates resolving to the same load target (e.g. a custom scan
folder pointing into an HF cache) must not be tried twice, but the
dedupe must key on actual load targets/paths only: a local copy that
merely shares a repo model_id is a distinct set of files and must stay
available when the cached copy fails or has no usable quant."""
auto_load = _autoload_section()
assert "const seenLoadTargets = new Set()" in auto_load
# Keys carry the model kind: a folder emitting both GGUF and safetensors
# rows shares a path while holding two different models.
assert "seenLoadTargets.add(`${kind}:${normalizeLoadTargetKey(alias)}`)" in auto_load
assert 'markSeen("gguf", repo.load_id || repo.repo_id, repo.cache_path)' in auto_load
assert 'markSeen("model", repo.load_id || repo.repo_id, repo.cache_path)' in auto_load
assert "isSeen(localCandidate.kind, row.load_id, row.id, row.path)" in auto_load
# The repo-id-based dedupe that shadowed distinct local copies is gone.
assert "isSeen(row.load_id, row.id, row.path, row.model_id)" not in auto_load
assert "markSeen(repo.repo_id," not in auto_load
def test_local_quant_resolution_skips_failed_quants():
"""When a folder's smallest quant already failed or was blocked, the
resolver must return the next complete quant instead of abandoning the
whole folder (which made Send falsely report no model)."""
src = _read("features/chat/api/chat-adapter.ts")
resolve_fn = src.split("async function resolveLocalRowCandidate", 1)[1]
resolve_fn = resolve_fn.split("\nfunction ", 1)[0]
assert "for (const entry of downloaded)" in resolve_fn
assert "if (isSkippedCandidate?.(candidate)) continue;" in resolve_fn
# The fallback loop feeds the skip set into resolution.
auto_load = _autoload_section()
assert "isSkippedAutoLoadCandidate," in auto_load
def test_autoload_trust_guard_still_blocks_background_loads():
"""A model needing custom-code approval or a security review is never
silently auto-loaded, and a blocked candidate can only cascade to other
on-device candidates."""
auto_load = _autoload_section()
assert "validation.requires_trust_remote_code" in auto_load
assert "validation.requires_security_review" in auto_load
assert "MAX_AUTO_LOAD_ATTEMPTS" in auto_load
def test_remembered_model_record_supports_local_sources():
"""last-local-model-load must represent managed-cache models AND
backend-indexed local models: a local GGUF is valid with a null variant,
legacy v1 records keep resolving as managed-cache entries, and no
secrets (tokens/leases) are ever persisted."""
src = _read("features/chat/utils/last-local-model-load.ts")
# Same storage key: v1 records parse backward-compatibly, no migration.
assert 'const STORAGE_KEY = "unsloth.last-local-model-load.v1";' in src
# Legacy records carry no source and default to the managed cache.
assert "isLastLocalModelSource(parsed.source)" in src
assert ': "hf_cache";' in src
# The GGUF-variant requirement is scoped to managed-cache records; a
# local GGUF's load target identifies the file, so null stays valid.
assert src.count('source === "hf_cache" && !ggufVariant') == 2
# Indexed local scan sources are representable.
for source in ('"models_dir"', '"lmstudio"', '"custom"'):
assert source in src, source
# Identity only: never tokens, native path leases, or approvals.
assert "nativePath" not in src
assert "hfToken" not in src and "hf_token" not in src
assert "fingerprint" not in src
def test_interactive_local_loads_are_remembered_without_lease_bypass():
"""A successful interactive load of a backend-indexed local model
(picker source "local") must be remembered so auto-load can reuse it,
while native-picked files (signed, expiring path lease) and other
arbitrary paths must never be recorded."""
src = _read("features/chat/hooks/use-chat-model-runtime.ts")
record_block = src.split("const indexedLocalSelection", 1)[1]
record_block = record_block.split("} catch (error) {", 1)[0]
assert 'selection.source === "local"' in src
assert "!nativePathToken &&" in record_block
assert "(indexedLocalSelection || !isLocalModelPath(modelId))" in record_block
assert 'source: "local",' in record_block
def test_remembered_local_row_match_requires_kind_agreement():
"""A folder holding both GGUF and safetensors weights yields two inventory
rows with the same path/load target, so the remembered kind must gate the
identifier match or a remembered safetensors load can resolve to the GGUF
row (and vice versa)."""
src = _read("features/chat/api/chat-adapter.ts")
match_fn = src.split("function matchesRememberedLocalRow", 1)[1]
match_fn = match_fn.split("\nasync function ", 1)[0].split("\nfunction ", 1)[0]
assert '(row.model_format === "gguf") !== (remembered.kind === "gguf")' in match_fn
def test_directory_gguf_rows_resolve_variant_like_picker():
"""Directory-based local GGUFs (LM Studio, models dir, custom folders) are
flagged requires_variant by the backend, so the fallback must resolve a
quant through the variants API (as the picker card does) instead of
silently dropping every directory row; non-GGUF variant-requiring rows
have no background resolution and stay excluded."""
src = _read("features/chat/api/chat-adapter.ts")
resolve_fn = src.split("async function resolveLocalRowCandidate", 1)[1]
resolve_fn = resolve_fn.split("\nfunction ", 1)[0]
assert "row.capabilities?.requires_variant === true" in resolve_fn
assert "if (!isGguf) return null;" in resolve_fn
# Quants must be resolved from the folder the row will load from, not
# from a same-id HF cache repo whose quants may be absent locally.
assert "const variantScanTarget = isLocalModelPath(row.id) ? row.id : row.path;" in resolve_fn
assert "listGgufVariantsBounded(variantScanTarget" in resolve_fn
assert "localPath: row.path" in resolve_fn
assert "entry.downloaded && !entry.partial && isAutoLoadableGgufVariant(entry)" in resolve_fn
# The cascade must keep directory GGUF rows as candidates.
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
assert 'row.model_format === "gguf" ||' in auto_load
assert "await resolveLocalRowCandidate(" in auto_load
def test_remembered_local_failure_does_not_block_folder_fallback():
"""A failed remembered model must exclude only that exact candidate key,
not mark the whole row or repo as seen; otherwise a folder or cache repo
with another complete quant can never fall back and Send falsely reports
no model. Applies to local rows and managed-cache repos alike."""
src = _read("features/chat/api/chat-adapter.ts")
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
remembered_block = auto_load.split("if (lastLoaded) {", 1)[1]
remembered_block = remembered_block.split("// On-device fallback", 1)[0]
assert (
"markSeen(" not in remembered_block
), "remembered paths must not pre-mark their row/repo as deduped"
assert "autoLoadSkipKey(rememberedCandidate)" in remembered_block
def test_fallback_orders_by_resolved_quant_size():
"""A GGUF folder or cache repo row's size_bytes sums every quant in it, so
the smallest-first fallback must order both local rows and cached repos by
the resolved quant's own size; otherwise a repo holding one small quant
loses to a larger single-quant model."""
src = _read("features/chat/api/chat-adapter.ts")
resolve_fn = src.split("async function resolveLocalRowCandidate", 1)[1]
resolve_fn = resolve_fn.split("\nfunction ", 1)[0]
assert "sizeBytes: sizeOrUnknownBytes(entry.size_bytes)" in resolve_fn
auto_load = _autoload_section()
# Local rows order on the resolved quant size.
assert "sizeBytes: resolved.sizeBytes" in auto_load
# Cached GGUF repos order on the resolved quant size too.
assert "const resolveCachedGgufEntry" in auto_load
assert "sizeBytes: sizeOrUnknownBytes(variant.size_bytes)" in auto_load
# Non-GGUF cached repos order on the SELECTED snapshot's size (falling
# back to the all-revisions row sum for older backends).
seed_block = auto_load.split("for (const repo of platform.chatOnly ? [] : modelRepos)", 1)[1]
seed_block = seed_block.split("const resolveCachedGgufEntry", 1)[0]
assert "repo.snapshot_size_bytes ?? repo.size_bytes" in seed_block
def test_cascade_retries_next_quant_after_load_failure():
"""A failed /api/inference/load (not just a blocked validation) must mark
that quant skipped and re-enter the folder's or repo's next complete quant
into the GLOBAL size order (still ahead of the safetensors group) instead
of retrying inline, so one folder of failing quants cannot starve a
smaller model elsewhere; single-candidate rows resolve to null once
skipped, and the attempt cap bounds total loads."""
src = _read("features/chat/api/chat-adapter.ts")
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
# No inline retry loop: retries re-enter the shared ordered pool.
assert "while (localCandidate" not in auto_load
assert "retry: true," in auto_load
assert "insertReady({ ...next, retry: true })" in auto_load
# Ordered insertion respects the GGUF-before-safetensors group boundary
# and the ascending size order among the remaining candidates.
assert "!isModelKindEntry(readyPool[at])" in auto_load
assert "readyPool[at].sizeBytes <= entry.sizeBytes" in auto_load
# Requeued entries bypass the seen gate; fresh rows still dedupe.
assert "if (!candidate.retry) {" in auto_load
# The cascade catch records the failed quant before requeueing.
assert "skippedAutoLoadCandidates.add(skipKey)" in auto_load
assert "skippedAutoLoadCandidates.add(autoLoadSkipKey(localCandidate))" in auto_load
# Termination guard: a skipped single candidate resolves to null.
resolve_fn = src.split("async function resolveLocalRowCandidate", 1)[1]
resolve_fn = resolve_fn.split("\nfunction ", 1)[0]
assert "if (isSkippedCandidate?.(candidate)) return null;" in resolve_fn
def test_cached_rows_deduped_against_local_aliases():
"""A cached repo and an indexed local row can alias the same files (e.g.
a scan folder pointing into an HF cache). The fallback must not spend a
second load attempt re-trying files already visited or failed through the
other row: cached branches apply the same seen gate local rows use, and
skip keys are scoped to the backend load target both rows share."""
src = _read("features/chat/api/chat-adapter.ts")
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
assert 'if (isSeen("gguf", repo.load_id || repo.repo_id, repo.cache_path))' in auto_load
assert 'if (isSeen("model", repo.load_id || repo.repo_id, repo.cache_path))' in auto_load
key_fn = src.split("function autoLoadSkipKey", 1)[1]
key_fn = key_fn.split("\nfunction ", 1)[0]
assert "candidate.loadId ?? candidate.id" in key_fn
def test_send_not_blocked_by_full_inventory_resolution():
"""Pressing Send must not wait for every /gguf-variants folder scan before
the first load attempt: candidates resolve through a bounded worker pool
and are consumed incrementally after a short settle grace, so one slow
folder cannot stall the send path behind the transport timeout."""
src = _read("features/chat/api/chat-adapter.ts")
assert "const AUTO_LOAD_RESOLVE_GRACE_MS" in src
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
# The consumer never awaits full resolution; it waits for the grace
# window (cut short when resolution finishes) and then per-completion.
assert "await resolutionDone" not in auto_load
assert "clearTimeout(graceTimer)" in auto_load
assert "await nextProgress();" in auto_load
assert "if (pendingJobs <= 0) {" in auto_load
# Rows that need no backend scan seed the pool before the workers start,
# so they can never queue behind slow folder scans.
assert "const needsVariantScan" in auto_load
assert ".filter((row) => !needsVariantScan(row))" in auto_load
assert auto_load.index(".filter((row) => !needsVariantScan(row))") < auto_load.index(
"const cachedScanJobs"
)
# Cached and local scans interleave so one slow source cannot
# monopolize every worker.
assert "resolutionJobs.push(cachedScanJobs[jobIndex])" in auto_load
assert "resolutionJobs.push(localScanJobs[jobIndex])" in auto_load
def test_pending_gguf_scans_gate_safetensors_candidates():
"""GGUF-first is the documented preference order, and incremental
consumption must not let an instantly-resolved safetensors row claim a
load slot while a pending folder scan can still yield a GGUF candidate;
resolved GGUF entries are never gated."""
src = _read("features/chat/api/chat-adapter.ts")
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
assert "if (isModelKindEntry(candidate) && pendingJobs > 0) {" in auto_load
def test_only_first_attempt_leapfrogs_pending_scans():
"""Fast-resolving candidates whose loads fail must not exhaust the attempt
cap while pending scans can still yield smaller loadable quants: only the
first (latency-critical) attempt may run ahead of pending scans; once any
budget is spent, the remaining attempts wait for the settled global
smallest-first order."""
src = _read("features/chat/api/chat-adapter.ts")
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
assert "if (pendingJobs > 0 && loadAttempts > 0) {" in auto_load
def test_hidden_matcher_fetch_never_blocks_send_unbounded():
"""ensureHiddenModelMatchers has no timeout of its own (unlike the
30s-bounded inventory calls), so the send path must not await it serially:
it runs alongside inventory discovery and is only awaited through a short
grace, after which the static needles filter alone."""
src = _read("features/chat/api/chat-adapter.ts")
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
assert "await ensureHiddenModelMatchers()" not in auto_load
assert "const hiddenMatchersReady = ensureHiddenModelMatchers().catch(" in auto_load
# The platform probe backing the picker's format gates is unbounded too
# (raw fetch, no signal), so it joins the same bounded prefetch wait.
assert "await fetchDeviceType();" not in auto_load
assert "const platformReady: Promise = fetchDeviceType().then(" in auto_load
assert "const BEST_EFFORT_PREFETCH_GRACE_MS" in src
assert "setTimeout(resolve, BEST_EFFORT_PREFETCH_GRACE_MS)" in auto_load
assert "clearTimeout(matcherTimer)" in auto_load
def test_resolution_workers_stop_on_terminal_result():
"""A successful early load (or any other terminal outcome) must stop the
workers from claiming further folder scans, so autoload cannot leave
background scans contending with inference for the backend and disk."""
src = _read("features/chat/api/chat-adapter.ts")
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
assert "let resolutionStopped = false;" in auto_load
assert "while (!resolutionStopped && nextJob < resolutionJobs.length)" in auto_load
# The flag is set in a finally so every exit path (return, break, throw)
# stops the workers.
assert "resolutionStopped = true;" in auto_load
assert auto_load.index("} finally {") < auto_load.index("resolutionStopped = true;")
def test_local_rows_apply_picker_platform_gate():
"""Chat-only installs run GGUF (any host) and MLX (Mac only); the picker
hides other local formats and all cached non-GGUF rows there, so the
background cascade must not load a row the user could not have picked.
The remembered path stays ungated: a recorded load is user precedent."""
src = _read("features/chat/api/chat-adapter.ts")
local_fn = src.split("function isAutoLoadableLocalRow", 1)[1]
local_fn = local_fn.split("\nfunction ", 1)[0]
assert "platform.chatOnly" in local_fn
assert "localRowIsGgufLike(row)" in local_fn
assert "platform.isMac && localRowIsMlxNamed(row)" in local_fn
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
# The platform snapshot hydrates through the bounded best-effort prefetch
# (see test_hidden_matcher_fetch_never_blocks_send_unbounded).
assert "fetchDeviceType().then(" in auto_load
# Cascade seeding of cached non-GGUF repos mirrors the picker's
# chat-only exclusion; the remembered lookup above it stays unfiltered.
assert "platform.chatOnly ? [] : modelRepos" in auto_load
def test_autoload_keys_preserve_posix_path_case():
"""Linux filesystems distinguish /models/Foo from /models/foo, so seen
keys and remembered-model matching must not fold case on POSIX paths;
Windows-style paths and Hub repo ids keep case-insensitive matching."""
src = _read("features/chat/api/chat-adapter.ts")
norm_fn = src.split("function normalizeLoadTargetKey", 1)[1]
norm_fn = norm_fn.split("\nfunction ", 1)[0].split("\nconst ", 1)[0]
assert "looksWindowsPath" in norm_fn
assert 'value.startsWith("/") || value.startsWith("~")' in norm_fn
assert "return value;" in norm_fn
assert "return value.toLowerCase();" in norm_fn
match_fn = src.split("function matchesRememberedLocalRow", 1)[1]
match_fn = match_fn.split("\nfunction ", 1)[0]
assert "normalizeLoadTargetKey" in match_fn
# Inventory ids compare exactly (same backend generator on both sides).
assert "row.inventory_id === remembered.inventoryId" in match_fn
assert "row.inventory_id.toLowerCase()" not in match_fn
# Skip keys use the same semantics: a failure recorded for /models/Foo
# must not also skip /models/foo.
key_fn = src.split("function autoLoadCandidateKey", 1)[1]
key_fn = key_fn.split("\nfunction ", 1)[0]
assert "normalizeLoadTargetKey(id)" in key_fn
assert "id.toLowerCase()" not in key_fn
def test_local_variant_scans_bounded_concurrency():
"""Each /gguf-variants call triggers a recursive backend directory scan,
so pre-resolution must not fan out unbounded over every indexed folder
at once."""
src = _read("features/chat/api/chat-adapter.ts")
assert "const AUTO_LOAD_VARIANT_SCAN_CONCURRENCY" in src
auto_load = src.split("async function autoLoadOnDeviceModel", 1)[1]
assert "Math.min(AUTO_LOAD_VARIANT_SCAN_CONCURRENCY, resolutionJobs.length)" in auto_load
assert "await Promise.all(\n cascadeLocalRows.map(" not in auto_load
BACKEND = WORKDIR / "studio" / "backend"
def _read_backend(rel: str) -> str:
path = BACKEND / rel
assert path.exists(), f"missing backend source file: {path}"
return path.read_text()
def test_background_loads_resolve_local_files_only():
"""A cache populated outside Studio can pass the partial check while
missing shard files, and from_pretrained on a repo id downloads the gaps.
Background auto-loads therefore send local_files_only and the load route
rewrites the path to the locally resolved snapshot (identity intact), so
an incomplete cache fails over to the next candidate instead of
downloading on Send."""
src = _read("features/chat/api/chat-adapter.ts")
load_fn = src.split("async function loadAutoLoadCandidate", 1)[1]
load_fn = load_fn.split("loadAttempts += 1;", 1)[1]
assert "local_files_only: true," in load_fn
types = _read("features/chat/types/api.ts")
assert "local_files_only?: boolean;" in types
request_model = _read_backend("models/inference.py")
assert "local_files_only: bool = Field(" in request_model
route = _read_backend("routes/inference.py")
assert "request.local_files_only" in route
assert "resolve_local_snapshot_path" in route
assert "config.path = local_snapshot" in route
# Uncached repos fail closed with a conflict, never a download.
rewrite = route.split("request.local_files_only", 1)[1]
rewrite = rewrite.split("config.path = local_snapshot", 1)[0]
assert "status_code = 409" in rewrite
helper = _read_backend("hub/utils/local_snapshot.py")
assert "local_files_only = True" in helper
# The rewrite resolves against the LIVE Studio-managed cache location,
# not huggingface_hub's import-time default.
assert "str(get_hf_cache_paths().hub_cache)," in route
def test_background_candidate_filters_have_no_side_effects():
"""Round-13 gates. Local checkpoint rows carry pickle weights with no Hub
security scan, so they are never background-picked. The canAutoLoad probe
validates with the same local-only policy /load enforces, and the validate
route runs it offline so the metadata probe cannot reach the Hub. Non-GGUF
audio models are refused under local-only in both routes because their
codec runtimes download auxiliaries at load time. Revision-only caches
(refs pruned) still resolve through the snapshot-dir fallback."""
adapter = _read("features/chat/api/chat-adapter.ts")
assert 'if (row.model_format === "checkpoint") {' in adapter
can_fn = adapter.split("async function canAutoLoad", 1)[1]
can_fn = can_fn.split("async function", 1)[0]
assert "local_files_only: true," in can_fn
chat_api = _read("features/chat/api/chat-api.ts")
assert "local_files_only: payload.local_files_only ?? false," in chat_api
request_model = _read_backend("models/inference.py")
validate_schema = request_model.split("class ValidateModelRequest", 1)[1]
assert "local_files_only: bool = Field(" in validate_schema
route = _read_backend("routes/inference.py")
# /load forces offline resolution under local-only; /validate covers its
# whole preflight via the ExitStack wrap (asserted separately below).
assert route.count("with _hf_offline_if_dns_dead(force = request.local_files_only):") == 1
# Audio gate present in both routes, GGUF exempt (llama.cpp path already
# resolves companions cached-or-skipped under the flag).
assert route.count("needs audio codec downloads") == 2
for gate in route.split("needs audio codec downloads")[:-1]:
tail = gate.rsplit("if request.local_files_only", 1)[1]
assert "is_gguf" in tail and "is_audio" in tail
llama = _read_backend("core/inference/llama_cpp.py")
assert "def _hf_offline_if_dns_dead(force: bool = False):" in llama
# force must also override an explicitly falsy HF_HUB_OFFLINE=0 (only a
# TRUTHY env value short-circuits), and overlapping guards are refcounted
# so the env is restored only when the LAST one exits; behavior is
# exercised directly in test_offline_guard_refcount.py.
assert "elif _hf_env_offline() and (not force or _hub_offline_env_truthy()):" in llama
assert "_OFFLINE_GUARD_LOCK" in llama
assert '_OFFLINE_GUARD_STATE["count"] += 1' in llama
helper = _read_backend("hub/utils/local_snapshot.py")
assert "def _snapshot_dir_fallback(" in helper
assert "config.json" in helper
def test_local_only_covers_every_load_and_validate_network_path():
"""Round-14 gates. The Vulkan-ordinal GGUF preflight downloads FIRST, so it
takes the same local-only flag and forced-offline wrap as the Phase 2
download (whose cache-size check would otherwise call get_paths_info).
The validate route keeps its whole metadata/security preflight offline, not
just the identifier probe. The python load path survives the process
boundary: the orchestrator forwards the flag and the route-resolved
snapshot path into the worker, which runs the entire load under a scoped
offline env and passes the flag to the vision processor fallback."""
llama = _read_backend("core/inference/llama_cpp.py")
# Both GGUF download blocks in load_model force offline under local-only.
assert llama.count("with _hf_offline_if_dns_dead(force = local_files_only):") == 2
preflight = llama.split("_preflight_model_path = self._download_gguf(", 1)[1]
preflight = preflight.split(")", 1)[0]
assert "local_files_only = local_files_only," in preflight
route = _read_backend("routes/inference.py")
validate_src = route.split('operation = "validate-model"', 1)[1]
assert (
"_local_only_offline.enter_context(_hf_offline_if_dns_dead(force = True))" in validate_src
)
assert "_local_only_offline.close()" in validate_src
# The non-GGUF load threads the flag into the subprocess backend.
load_call = route.split("backend.load_model,\n config = config,", 1)[1]
load_call = load_call.split(")", 1)[0]
assert "local_files_only = request.local_files_only," in load_call
orchestrator = _read_backend("core/inference/orchestrator.py")
assert '"local_files_only": bool(local_files_only),' in orchestrator
assert '"local_snapshot_path"' in orchestrator
worker = _read_backend("core/inference/worker.py")
assert "def _local_only_offline_env(" in worker
assert "_offline_guard.enter_context(" in worker
assert "_offline_guard.close()" in worker
# The route's snapshot rewrite is re-applied after the worker rebuilds
# its ModelConfig from the identifier.
assert 'snapshot_override = config.get("local_snapshot_path")' in worker
assert "mc.path = snapshot_override" in worker
assert '"local_files_only": bool(config.get("local_files_only", False)),' in worker
inference = _read_backend("core/inference/inference.py")
processor_call = inference.split("processor = AutoProcessor.from_pretrained(", 1)[1]
processor_call = processor_call.split("logger.info", 1)[0]
assert "local_files_only = local_files_only," in processor_call
def test_background_picks_mirror_inventory_and_skip_installers():
"""Round-15 gates. Cached checkpoint repos (pickle weights) are excluded
from background picks like local checkpoint rows. The worker keeps its
ENTIRE bootstrap offline under local-only and never pip-installs SSM
kernels (missing fatal kernels fail into candidate failover). Snapshot
resolution prefers the newest snapshot dir, matching the inventory
scanner's latest_snapshot_dir selection, before consulting refs/main.
MLX loads read config.path so the live-cache rewrite is honored. Cached
non-GGUF ordering uses the selected snapshot's size, not the
all-revisions blob total."""
adapter = _read("features/chat/api/chat-adapter.ts")
cached_filter = adapter.split("function isAutoLoadableCachedRepo", 1)[1]
cached_filter = cached_filter.split("AUTO_LOAD_LOCAL_SOURCES", 1)[0]
assert 'if (repo.model_format === "checkpoint") {' in cached_filter
assert "repo.snapshot_size_bytes ?? repo.size_bytes" in adapter
worker = _read_backend("core/inference/worker.py")
assert "_bootstrap_offline = contextlib.ExitStack()" in worker
# Entered before base resolution / gates / kernels, closed before BOTH
# command loops (MLX and GPU paths).
bootstrap = worker.split("_bootstrap_offline = contextlib.ExitStack()", 1)[1]
assert bootstrap.count("_bootstrap_offline.close()") == 2
ssm_sig = worker.split("def _ensure_ssm_kernels(", 1)[1].split(") -> bool:", 1)[0]
assert "local_files_only: bool = False" in ssm_sig
ssm = worker.split("def _ensure_ssm_kernels", 1)[1]
ssm = ssm.split("def _run_security_gates", 1)[0]
assert "if local_files_only:" in ssm
assert 'importlib.util.find_spec("mamba_ssm") is None' in ssm
helper = _read_backend("hub/utils/local_snapshot.py")
resolve = helper.split("def resolve_local_snapshot_path", 1)[1]
# Newest-snapshot scan runs BEFORE the refs/main-based resolver (compare
# the actual calls, not docstring mentions).
assert resolve.index("resolved = _snapshot_dir_fallback(") < resolve.index(
"return snapshot_download("
)
mlx = _read_backend("core/inference/mlx_inference.py")
assert 'load_source = getattr(config, "path", None) or model_name' in mlx
inventory = _read_backend("hub/services/models/cache_inventory.py")
assert "snapshot_size_bytes" in inventory
assert "def _snapshot_dir_mtime(" in inventory
schema = _read_backend("hub/schemas/inventory.py")
assert "snapshot_size_bytes" in schema
def test_forced_offline_is_hub_specific_and_covers_parent_preflight():
"""Round-16 gates. A forced guard may only no-op when HF_HUB_OFFLINE
itself is truthy (huggingface_hub ignores TRANSFORMERS_OFFLINE), snapshot
selection prefers revisions that hold the inventoried safetensors weights
so a metadata-only newest revision cannot shadow a complete older one,
and the orchestrator's parent-side preflight (transformers tier probe,
GPU sizing via hf model_info) runs under the local-only guard, closed
before the worker spawn so the child does not inherit the env."""
llama = _read_backend("core/inference/llama_cpp.py")
assert "def _hub_offline_env_truthy(" in llama
assert "not force or _hub_offline_env_truthy()" in llama
helper = _read_backend("hub/utils/local_snapshot.py")
assert "def _snapshot_has_weights(" in helper
assert "max(weightful or candidates, key = os.path.getmtime)" in helper
orchestrator = _read_backend("core/inference/orchestrator.py")
preflight = orchestrator.split("def _preflight_offline():", 1)[1]
assert "_hf_offline_if_dns_dead(force = True)" in preflight
# Both metadata call sites are guarded, and the guard closes before spawn.
assert preflight.count("with _preflight_offline():") == 2
tier_probe = preflight.split("with _preflight_offline():", 1)[1]
assert "needs_transformers_5" in tier_probe.split("with _preflight_offline():", 1)[0]
assert "prepare_gpu_selection(" in tier_probe.split("_spawn_subprocess", 1)[0]
def test_generation_and_scan_paths_stay_bounded_and_local():
"""Round-17 gates. Inactive-cache rows emit a weight-bearing snapshot as
their load_id (the load consumes it directly, bypassing the repo-id
resolver). Ordinary offline guards never extend a forced window. The
generation-time native template reload honors the load's local-only flag
and resolved path instead of refetching the repo id online. Every GGUF
variant scan behind the model-kind gate is bounded by an abortable
timeout, and an HF cache snapshot registered as a custom folder dedupes
against its cached row through the shared cache root."""
inventory = _read_backend("hub/services/models/cache_inventory.py")
assert "def _weightful_snapshot_path(" in inventory
resolver = inventory.split("def _cached_model_snapshot_path(", 1)[1]
resolver = resolver.split("def ", 1)[0]
assert "_weightful_snapshot_path(repo_path)" in resolver
llama = _read_backend("core/inference/llama_cpp.py")
join_branch = llama.split('if _OFFLINE_GUARD_STATE["count"] > 0:', 1)[1]
join_branch = join_branch.split("elif", 1)[0]
assert "if force:" in join_branch
helpers = _read_backend("core/inference/chat_template_helpers.py")
reload_block = helpers.split("native_chat_template", 1)[1]
reload_block = reload_block.split("model_info[", 1)[0]
assert 'local_files_only = bool(model_info.get("local_files_only", False))' in reload_block
assert 'template_source = model_info.get("model_path") or template_source' in reload_block
assert "local_files_only = local_files_only," in reload_block
inference = _read_backend("core/inference/inference.py")
assert '"local_files_only": local_files_only,' in inference
mlx = _read_backend("core/inference/mlx_inference.py")
assert '"local_files_only": local_files_only,' in mlx
assert '"model_path": load_source,' in mlx
adapter = _read("features/chat/api/chat-adapter.ts")
assert "AUTO_LOAD_VARIANT_SCAN_TIMEOUT_MS" in adapter
assert "async function listGgufVariantsBounded(" in adapter
assert "controller.abort()" in adapter
# No unbounded scan calls remain in the adapter: every call site routes
# through the bounded wrapper (the wrapper itself holds the one direct
# call, with the timeout signal attached).
assert adapter.count("await listGgufVariants(") == 1
chat_api = _read("features/chat/api/chat-api.ts")
assert "signal: options?.signal," in chat_api
assert "function expandSeenValues(" in adapter
assert adapter.count("expandSeenValues(value)") == 2
def test_local_only_gguf_reuse_and_platform_gates_are_authoritative():
"""Round-18 gates. get_paths_info performs no offline-mode check and
HF_HUB_OFFLINE is baked into hub constants at import, so local-only GGUF
reuse skips the remote size verification per-call instead of relying on
the env guard. Platform format gates only apply once the BACKEND-reported
platform is fetched (the browser fallback may describe a different
machine). snapshot_size_bytes uses the resolvers' complete-revision
predicate (config plus weights in the SAME revision). Cached-repo variant
scans are memoized per run so a stalled repo times out once."""
llama = _read_backend("core/inference/llama_cpp.py")
assert "verify_sizes = not local_files_only," in llama
reuse = llama.split("_cached_complete_candidate(hf_repo, gguf_filename, gguf_extra_shards)", 1)[
1
]
reuse = reuse.split("cached_main is not None", 1)[0]
assert "local_files_only" in reuse and "_cached_candidate_matches_revision_size" in reuse
adapter = _read("features/chat/api/chat-adapter.ts")
assert "chatOnly: platformState.fetched ? platformState.isChatOnly() : false," in adapter
assert "const repoVariantScans = new Map<" in adapter
assert "const scanRepoVariants = (" in adapter
assert adapter.count("await scanRepoVariants(repo.repo_id, repo.cache_path)") == 2
inventory = _read_backend("hub/services/models/cache_inventory.py")
assert "rev_has_config" in inventory
assert 'if selected_category == "safetensors":' in inventory
def test_route_preflights_and_gguf_rows_stay_format_true():
"""Round-19 gates. The /load route's sidecar tier probe and training
guard size local-only candidates against the resolved snapshot path (a
repo id would reach _remote_lora_base's raw HTTP request and hf
model_info, neither of which honors offline mode). GGUF cached rows
select a GGUF-bearing snapshot, so a mixed repo's safetensors revision
cannot become the GGUF row's load target."""
route = _read_backend("routes/inference.py")
assert "_tier_target = config.path if request.local_files_only else config.identifier" in route
guard_block = route.split("_guard_identifier = (", 1)[1]
guard_block = guard_block.split("await asyncio.to_thread(", 1)[0]
assert "config.path" in guard_block
assert "request.local_files_only and not config.is_gguf" in guard_block
assert "model_identifier = _guard_identifier," in route
inventory = _read_backend("hub/services/models/cache_inventory.py")
assert "def _newest_snapshot_where(" in inventory
assert "def _gguf_snapshot_path(" in inventory
assert "def _cached_gguf_repo_snapshot_path(" in inventory
gguf_scan = inventory.split("def _scan_cached_gguf(", 1)[1]
gguf_scan = gguf_scan.split("def ", 1)[0]
assert "_cached_gguf_repo_snapshot_path(repo_path)" in gguf_scan
assert "_cached_model_snapshot_path(repo_path)" not in gguf_scan
def test_gguf_background_loads_never_download_companions():
"""A cached GGUF load can still fetch from the Hub through its optional
companions (mmproj, MTP drafter) or a cache-miss main quant. Background
loads pass local_files_only into the llama.cpp path: companions resolve
cached-or-skipped, and a main-quant cache miss raises instead of
downloading."""
route = _read_backend("routes/inference.py")
gguf_source = route.split("if config.gguf_hf_repo:", 1)[1]
gguf_source = gguf_source.split("else:", 1)[0]
assert "local_files_only = request.local_files_only," in gguf_source
llama = _read_backend("core/inference/llama_cpp.py")
# The flag flows to the main quant and both companion helpers, and the
# crash-replay kwargs keep it so a reload stays local-only.
assert llama.count("local_files_only = local_files_only,") >= 3
assert '"local_files_only": local_files_only,' in llama
# Companions: cached-or-skipped, never fetched.
assert 'logger.info("Skipping %s fetch (local-only load)", label)' in llama
assert "if local_files_only or _hf_env_offline():" in llama
# Main quant: a cache miss fails closed.
download = llama.split("def _download_gguf", 1)[1]
download = download.split("def _download_companion_gguf", 1)[0]
assert "if local_files_only:" in download
assert "select it explicitly to download it." in download
inference = _read_backend("core/inference/inference.py")
# The vision processor fallback stays on the (possibly rewritten local)
# load path instead of refetching by repo id.
assert "config.base_model if config.is_lora else config.path" in inference
assert "config.base_model if config.is_lora else config.identifier" not in inference
def test_vulkan_inference_devices_are_the_pickable_set():
"""GGUF loads run through llama-server, so on a Vulkan build the picker must
offer the inference inventory (ggml ordinals, the space `--device Vulkan`
pins) rather than the torch view, which can miss cards llama-server drives.
The XPU ban must not apply there: it is about torch-xpu ordinals no
applicator speaks, and a Vulkan pick does not use them.
"""
src = " ".join(_read("hooks/use-gpu-info.ts").split())
# The Vulkan inventory is consulted first, and only when it has devices.
assert (
"const inference = data?.inference_gpu; "
'if (inference?.backend === "vulkan" && (inference.devices ?? []).length) {' in src
)
# Pinnable on the ggml ordinal space, gated on the backend's own support flag.
assert "const picksAccepted = inference.gguf_gpu_ids_supported !== false;" in src
assert 'physicalIndex: picksAccepted && d.index_kind === "vulkan",' in src
# The torch fallback keeps its physical-only gate and the XPU ban.
assert 'data?.device_backend !== "xpu" &&' in src
assert 'physicalIndex: pinnableBackend && d.index_kind === "physical",' in src