- maxTokens: 2048 -> 8192. The old 2048 limit caused generation to
stop mid-output for longer responses (e.g. reasoning/thinking models
that produce long chain-of-thought before the answer).
- repetitionPenalty: 1.1 -> 1.0 (disabled). Most models handle
repetition well on their own. A penalty of 1.1 can hurt quality
for creative tasks like code generation and ASCII art.
- Change welcome message from "Run LLMs or test your fine-tune" to
"Chat with your model".
Merge the toast UX refactor from PR #4304 (by @Shine1i):
- Toast duration 5s default with close button (X) for manual dismiss
- Inline progress bar component (ModelLoadInlineStatus) shown in the
header after toast is dismissed
- Model switch warning only for image compatibility (not generic)
- activeThreadId tracked in store via ActiveThreadSync
- Loading state cleanup via resetLoadingUi helper
- Toast uses Infinity duration during loading with onDismiss handler
Re-applied non-GGUF download progress additions on top:
- getDownloadProgress for all models (not just GGUF)
- hasShownProgress flag, loadingModelRef race condition checks
- First poll at 500ms, bytes-only fallback when expected size unknown
Don't show "Model changed for this chat" toast when the thread has
no messages. On a fresh page load with a stale thread from a previous
session, this warning is confusing. The warning is only useful
mid-conversation to alert about image compatibility with the new model.
When messages.length === 0, silently update the thread's modelId and
proceed with loading.
- Add sloth emoji prefix to "Downloaded" and "Recommended" section
labels in the Hub model picker so they are visually distinct.
- Replace browser network errors ("NetworkError when attempting to
fetch resource" / "Failed to fetch") with a clearer message:
"Studio isn't running -- please relaunch it."
1. Backend: When a model fails with "No config file found" or similar
unsupported-model errors, wrap the message with "This model is not
supported yet. Try a different model." instead of showing the raw
Unsloth exception.
2. Frontend: Compute estimated download size from the HF search API's
safetensors.parameters dtype breakdown (BF16=2B/param, I32=4B/param,
F32=4B/param, etc.) and show it in the model picker instead of just
the param count. For example, Kimi-K2.5 now shows "~554 GB" instead
of "171B" (which was misleading since 171B params != 171GB download).
Three fixes on top of the download progress feature:
1. Backend: Replace broken "no .incomplete = done" completion check
with a 95% byte threshold. HF downloads files sequentially, so
between files there are briefly no .incomplete files even though
the download is far from done (e.g. Kimi-K2.5 reported "done"
after downloading 22KB of config files out of 595GB).
2. Frontend: Track hasShownProgress flag. Only show "Download
complete. Loading into memory..." if we actually displayed
download progress before. For already-cached models where the
first poll returns progress=1.0, this avoids the misleading
"Download complete" message.
3. Frontend: Deduplicate recommended vs downloaded -- filter out
models already in the "Downloaded" section. Cache the fetched
lists at module level so re-mounting the popover does not flash
an empty "Downloaded" section.
Previously only GGUF models showed download progress in Chat. Non-GGUF
models (safetensors, bnb quantized, etc.) showed a static message with
no progress indication. This adds progress tracking for all model types
and fixes several related issues.
Backend:
- Add /api/models/download-progress endpoint that checks the HF cache
blobs directory for completed and .incomplete files. Uses model_info()
(cached per repo) to determine expected total size for percentage.
- Add /api/models/cached-models endpoint that lists non-GGUF model repos
from the HF cache via scan_cache_dir().
- Fix progress stuck at 0.99: when no .incomplete files remain, report
1.0 immediately (blob deduplication can make byte totals mismatch).
Frontend:
- Remove the ggufVariant gate so download progress polling works for all
non-cached models, not just GGUFs.
- Use GGUF-specific endpoint when variant + expectedBytes available,
otherwise use the general download-progress endpoint.
- Fix toast stuck after load: check loadingModelRef.current before and
after the async poll to prevent overwriting the success toast.
- First poll at 500ms instead of waiting for the 2s interval.
- Show downloaded non-GGUF models in the Hub model picker "Downloaded"
section alongside GGUFs.
* user can upload eval dataset, removed bugs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* resolving merge conflicts
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* resolving gpt comments
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* feat(studio): switch to password-only login and simplify first-time setup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: align change-password button state with validation rules
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* chat only with gguf for mac devices
* resolving gpt comments
* add change-password for chat only
* hide lora adaptors dropdown
* solving gpt comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* addressing the comment
* fixing auth flow
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
- Run GGUF load_model in asyncio.to_thread so the event loop stays free
for progress polling during download (was blocking all requests).
- Extract download phase out of the lock in LlamaCppBackend.load_model
so unload_model/cancel can take effect immediately during download.
- Fix "downloaded" badge for split GGUFs: check total cached bytes
across all shards vs expected size, not just first shard existence.
- Respect CUDA_VISIBLE_DEVICES in /api/system GPU reporting so the
frontend GGUF fit estimation uses actual available VRAM.
- Sort tight variants (need CPU offload) smallest-first instead of
largest-first -- closer to GPU budget = faster inference.
- Fix cancel: use refs instead of React state for abort controller and
toast ID so both cancel buttons (text + toast) work reliably. Make
cancel synchronous (fire-and-forget unload) for instant UI response.
Check abortCtrl.signal.aborted after loadModel returns to prevent
ghost model state. Skip rollback and suppress errors on cancel.
- Dynamic top 4 GGUF models fetched from HF API sorted by downloads,
prepended to the default recommended list.
- Remove turnAnchor="top" for auto-scroll to bottom during generation.
- Set default toast duration to 10s (was infinite for loading toasts).
- Deduplicate cached GGUF repos using scan_cache_dir API (fixes
Qwen/X-GGUF vs qwen/x-gguf duplicates from lowercased HF cache).
- Pre-compile repo_id validation regex to silence CodeQL ReDoS warning.
- Change welcome text and default suggestion text.
1. Progress endpoint now takes a variant parameter and only counts
.gguf files matching that variant (not all files in the repo cache,
which would include previously downloaded variants)
2. Tracks .incomplete files in HF blobs dir for in-progress single-shard
downloads, capping at 99% until the file is fully committed
3. Fixed loading text: "Loading model..." for cached, "Downloading
model..." for new downloads, with appropriate descriptions
4. Wording: "Downloading and loading model. Large models can take a
while." instead of "This may include downloading."
1. Loading text: shows "Loading model..." for cached models,
"Downloading model..." for new downloads. Toast description
adapts accordingly.
2. Download progress: polls /api/models/gguf-download-progress every
2s during downloads, updating the toast with percentage and GB
downloaded. Progress is estimated by checking the HF cache folder
size against the expected total bytes.
3. Passes isDownloaded and expectedBytes through the full chain from
variant click to selectModel for accurate UI state.
Downloaded variants now take priority over the recommended badge in
sort order. Within the same tier (downloaded+fits, etc.), recommended
still sorts first. Order: downloaded -> recommended -> fits -> tight -> OOM
- Backend: /gguf-variants now checks HF cache for each variant's file
and returns a downloaded flag per variant
- Frontend: downloaded variants sort before non-downloaded (after
recommended), and show a green "downloaded" badge
- Sort order: recommended -> downloaded+fits -> downloaded+tight ->
fits -> tight -> OOM
1. Interruptible downloads: load_model now checks a cancel event
between shard downloads. unload_model sets the event so cancel
stops the download at the next shard boundary.
2. /api/models/cached-gguf endpoint: scans the HF cache for
already-downloaded GGUF repos with their total size and cache path.
3. "Downloaded" section in Hub model picker: shows cached GGUF repos
at the top (before Recommended) so users can quickly re-load
previously downloaded models without re-downloading.
Replace toast.promise with a manual toast.loading that includes a
Cancel action button. Users can now cancel model downloads/loads from
the toast notification itself, not just from the header bar spinner.
Updated GGUF fit classification to match llama-server's --fit behavior:
- fits: model <= 70% of total GPU memory (all GPUs)
- tight: model > 70% GPU but <= 70% GPU + 70% available system RAM
(llama-server uses --fit to offload layers to CPU)
- OOM: model exceeds both GPU and system RAM budgets
useGpuInfo now also returns systemRamAvailableGb from /api/system so the
frontend can compute the combined GPU+RAM budget.
Two fixes for accurate GGUF OOM detection:
1. /api/system now uses nvidia-smi to enumerate all physical GPUs
instead of torch.cuda which only sees CUDA_VISIBLE_DEVICES. This
matches llama-server which can use all GPUs regardless of the env
var. Falls back to torch-based detection if nvidia-smi unavailable.
2. Frontend GGUF OOM check now uses 70% of total GPU memory as the
budget, matching the PR's _select_gpus logic (30% reserved for KV
cache and compute buffers). Previously used checkVramFit's 100%
threshold which was too generous.
Adds a Cancel button next to the "Downloading model..." spinner so
users can abort long downloads. Clicking it aborts the in-flight load,
calls unloadModel to kill any running llama-server process, and clears
the loading state.
OOM variants are more useful sorted ascending by size since smaller ones
are more likely to run with --fit. Non-OOM variants remain largest-first
(best quality).
Two fixes for GGUF variant dropdown:
1. useGpuInfo now sums memory across all GPU devices instead of only
reading devices[0]. This matches llama-server's multi-GPU allocation
where models can be split across GPUs.
2. When the backend-recommended variant (e.g. UD-Q4_K_XL) exceeds total
GPU VRAM, the frontend picks the largest variant that fits instead.
If all variants are OOM, it recommends the smallest one (most likely
to work with --fit).
The useMemo for sortedVariants was placed after the loading/error early
returns, which violated React's rules of hooks (hooks must be called in
the same order every render). Move it before the conditional returns.
Fixes: Minified React error #310
Move the sort logic from the backend to the frontend GgufVariantExpander
component where GPU VRAM info is available. The backend now does a simple
size-descending sort. The frontend pins the recommended variant at the
top, pushes OOM variants to the bottom, and sorts the rest by file size
descending (largest/best quality first).
* miscallenous studio
* chore: upload dataset misc
* chore: redudancy studio cleanup
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix: adress the pr comments
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* fix: adress comments about recipes
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* fix: quotation marks
* diceware passphrase generation
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
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Prevent negative Train Split Start/End values in the dataset advanced UI and sanitize payload mapping so negative slice values are never sent to the backend.
Made-with: Cursor
