Box-drawing chars (U+2500), em dashes (U+2014), and en dashes (U+2013)
in comments, section dividers, log messages, and docstrings are not
representable on legacy code pages like CP1252. Replace them with plain
ASCII dashes so the codebase is consistently ASCII-safe.
User-facing UI strings (placeholders, separators, display text in the
frontend) are left unchanged since they render in the browser which
handles Unicode natively.
* feat(chat): regroup settings sidebar into Model, Sampling, Tools, and Preferences sections
Split the monolithic Settings collapsible into focused sections with
icons. Model section shows context length and KV cache dtype for GGUF
models, trust remote code for non GGUF. Tools section groups auto heal,
max tool calls, and tool call timeout. Preferences section holds auto
title toggle.
* feat(chat): persist collapsible section open/closed state in localStorage
Remember which sections the user expanded or collapsed across sidebar
toggles, mobile sheet reopens, and browser sessions.
* fix(chat): harden collapsible state persistence and restore defaultOpen
- Validate localStorage values are booleans before using them, preventing
corrupted entries like string "false" from being treated as truthy
- Use Object.hasOwn() instead of `in` operator to avoid prototype chain
matches on keys like "constructor" or "toString"
- Restore defaultOpen={true} on Model and Preferences sections so they
are expanded on first visit, matching the old Settings section behavior
- Fix misleading Context Length description to reflect it is read-only
- Downgrade console.error to console.warn for non-critical localStorage
parse failures
* fix(chat): remove redundant disabled styles on Context Length input
The Input component already applies opacity-50 and cursor-not-allowed
via its disabled: variants. Specifying them unconditionally in the
className is redundant.
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* fix: always show chat tool icons, gray out when model doesn't support them
Tool icons (Think, Search, Code) were hidden unless a model was loaded
and supported those features. Now they're always visible so users can
see and pre-select them. If a loaded model doesn't support a feature,
the button gets grayed out and disabled instead of being removed.
* refactor: centralize Qwen thinking params in store
* fix: disable tool buttons when no model is loaded
Change disabled condition from `modelLoaded && !supportsX` to
`!modelLoaded || !supportsX` so buttons are grayed out both when
no model is loaded and when the loaded model lacks the capability.
* Fix Qwen3 param clobbering and restore SuggestionItem capability guards
- Revert setReasoningEnabled() in the store to a pure boolean setter.
Moving the Qwen3 param logic into it caused reconnect/load/refresh
paths (which also call setReasoningEnabled) to silently overwrite
user-customized or server-provided temperature/topP/topK/minP.
- Restore applyQwenThinkingParams() as a standalone function called
only from explicit user toggle click handlers in thread.tsx and
shared-composer.tsx, matching the pre-PR behavior.
- Re-add supportsReasoning/supportsTools guards in the SuggestionItem
click handler so that clicking a suggestion card only activates
tool toggles the loaded model actually supports.
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
PR #4543 removed useScrollLock from ReasoningRoot, causing the thread
viewport to jump when a user collapses a reasoning panel. Restore the
hook to freeze scrollTop during the 200ms collapse animation, matching
the pattern used by tool-fallback.tsx and tool-group.tsx.
* fix(chat): stabilize thinking panel and thread scroll during generation
* fix: match ChatGPT scroll and thinking panel behavior
- Remove autoScroll={false} from thread viewport to restore default
follow-scroll during streaming (pauses when user scrolls up, resumes
at bottom)
- Rewrite reasoning panel state: auto-opens on stream start, user can
close during streaming, auto-collapses when reasoning ends, user can
re-expand after collapse
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* fix(studio): harden system prompt persistence and storage fallback
* Exclude checkpoint from localStorage persistence for PR #4538
checkpoint is backend-owned state -- refresh() already syncs it from
getInferenceStatus() on every page load. Persisting it to localStorage
causes a stale model ID to survive across backend restarts, which
prevents auto-load from triggering when no model is actually loaded.
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
The previous prompt "Show me a live weather dashboard, no API key needed"
was too vague. The new wording explicitly asks for HTML code, which
produces more useful and consistent responses.
* feat(chat): add server-side timings and context display for GGUF
Extract timings/usage metadata from llama-server SSE stream and forward
through the full stack. Replace client-side estimates with accurate
server-reported metrics (prompt eval, tok/s, token counts, cache hits).
Add context window usage bar to chat top nav.
* feat(chat): source badges with hover cards and 2-row collapse
- Add hover cards to source badges showing favicon, title, URL and
snippet description on hover
- Limit source badges to 2 rows with +X more expand/collapse
- Parse snippet from web search results for hover card descriptions
- Replace individual Source rendering with grouped SourcesGroup component
* fix(chat): add null guards for server timings edge cases
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix(chat): reset contextUsage on thread switch, remove unused context-display
* fix(chat): stop double-counting completion tokens in tool-calling path
* fix(chat): skip metadata events in llm_assist consumers
* fix(chat): hide context usage bar in compare mode
* fix(chat): harden timings pipeline and context usage persistence
Accumulate prompt_ms, predicted_ms, and predicted_n from intermediate
tool-detection passes so the final metadata reflects total server work.
Persist contextUsage in message metadata (Dexie) and restore on thread
load. Add type guard in gguf_stream_chunks for unexpected dict events.
Clear contextUsage when entering compare mode.
* feat(chat): make GGUF stream metadata OpenAI-compatible
* fix(chat): address PR review feedback
* feat(chat): address PR review feedback
* [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>
* fix(recipe-studio): prevent fitView from zooming to wrong location on recipe load
* feat: add pymupdf/python-docx deps and unstructured uploads storage root
* feat: add POST /seed/upload-unstructured-file endpoint
* feat: add multi-file chunking with source_file column
* feat: update frontend types and API layer for multi-file upload
* feat: round-robin preview rows across source files
Ensures every uploaded file is represented in the preview table
by cycling through sources instead of just taking the first N rows.
* fix: disable OCR, fix auto-load timing, fix persistence on reload
- Disable pymupdf4llm OCR with write_images=False, show_progress=False
- Replace onAllUploaded callback with useEffect that detects uploading→done
transition (avoids stale closure reading empty file IDs)
- Fix importer to preserve file IDs from saved recipes instead of clearing
(clearing only happens at share time via sanitizeSeedForShare)
* fix: harden unstructured upload with input validation and state fixes
Validate block_id/file_id with alphanumeric regex to prevent path
traversal, use exact stem match for file deletion, add error handling
for metadata writes and empty files, fix React stale closures and
object mutations in upload loop, and correct validation logic for
unstructured seed resolved_paths.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: address PR review - legacy path import, share sanitizer, sync effect
Promote legacy source.path into resolved_paths for old unstructured
recipes, clear source.paths in share sanitizer to prevent leaking local
filesystem paths, and gate file sync effect to dialog open transition
so users can actually delete all uploaded files.
* fix: CSV column fix (BOM + whitespace + unnamed index re-save) for #4470
* fix: harden unstructured upload flow and polish dialog UX
* [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>
* feat: support full model GGUF export, disable incompatible methods in UI
* fix: resolve base model from config.json for venv_t5 export switching
* feat: detect BNB-quantized models and disable all export methods for quantized non-PEFT checkpoints
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: relocate Ollama Modelfile alongside GGUFs during non-PEFT export cleanup
* [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>
* One liner setup for unsloth studio
* Fix install scripts: system deps, activation bugs, curl/wget support
- install.sh: detect platform (macOS/Linux/WSL) and check for missing
system dependencies (cmake, git, build-essential, libcurl4-openssl-dev).
Prompt user once for permission to install all missing packages via
brew (macOS) or sudo apt-get (Linux/WSL). Add wget fallback via
download() helper since curl is not always present on minimal Linux
installs. Fix nested curl|sh stdin stealing by downloading uv installer
to a tempfile first. Replace venv activation (no-op in a pipe subshell)
with explicit --python flag for uv pip install and direct venv binary
invocation. Add idempotency guard for venv creation. Redirect stdin
on unsloth studio setup to prevent pipe consumption. On macOS, check
for Xcode Command Line Tools and trigger install if missing.
- install.ps1: wrap script body in Install-UnslothStudio function so
that errors use return instead of exit (exit kills the terminal when
run via irm|iex). Remove activate.ps1 invocation entirely -- use
explicit --python path for uv pip install and & $UnslothExe for
studio setup. This avoids both the child-scope activation bug (& vs
dot-source) and the execution policy error on default Windows systems.
Add winget availability check with clear error message. Fix PATH
refresh to append registry paths instead of replacing the session PATH.
Add uv installer fallback via astral.sh PowerShell script if winget
install does not put uv on PATH. Broaden Python version check to
accept 3.11-3.13. Add idempotency guard for venv creation.
- README.md: add wget one-liner alternative for systems without curl.
* Fix Tailwind CSS v4 .gitignore bug on Windows (#4444)
- Add .gitignore hiding workaround to setup.ps1 (matching existing
setup.sh logic) so venv .gitignore files containing "*" don't prevent
Tailwind's oxide scanner from finding .tsx source files
- Add CSS size validation to setup.sh, setup.ps1, and build.sh to catch
truncated Tailwind builds early
- Remove stray force-rebuild overrides that made the "skip build if
current" cache check dead code in both setup scripts
- Add rm -rf dist to build.sh to force clean rebuilds for wheel packaging
* Change default port 8000 to 8888, fix installer bugs, improve UX
- Change default Studio port from 8000 to 8888 across all entry points
(run.py, studio.py, ui.py, colab.py, vite.config.ts, setup scripts)
- Update launch banner: "Launching with studio venv..." to
"Launching Unsloth Studio... Please wait..."
- Add "Open your web browser" banner and rename labels
(Local -> Local Access, External -> Worldwide Web Address)
- Fix venv idempotency: check for bin/python instead of just directory
existence, clean up partial venvs on retry
- Fix build.sh CSS validation: handle empty CSS case that silently
bypassed the check with "integer expression expected"
- Fix install.sh sudo handling: try apt-get without sudo first (works
when root), then escalate with per-package tracking and user prompt
- Fix install.ps1: check exit code from studio setup, fail on error
- Add pciutils to WSL GGUF build dependencies
- Apply same smart apt-get escalation pattern to studio/setup.sh
* Use detected Python version for venv, abort on non-apt Linux
- install.ps1: detect existing Python 3.11/3.12/3.13 and use that
version for venv creation instead of always forcing 3.13
- install.sh: exit with error on non-apt Linux distros when required
packages cannot be auto-installed, instead of silently continuing
* Make sudo permission prompt more prominent with warning banner
* Add Accept [Y/n] sudo prompt to studio/setup.sh for consistency
* Fix native command exit code handling and sudo decline flow
install.ps1: Add $LASTEXITCODE checks after winget (Python), uv venv,
and uv pip install calls. $ErrorActionPreference only catches PowerShell
cmdlet errors, not native executable failures. The Python check also
handles winget returning non-zero for "already installed".
setup.sh: Skip llama-server build when user declines sudo or sudo is
unavailable. Previously the script continued to section 8 which would
fail with confusing errors (e.g. "gcc: command not found") since
build-essential was never installed.
* Move rm -rf llama.cpp inside build branch to preserve existing install
When _SKIP_GGUF_BUILD is set (user declined sudo or sudo unavailable),
the previous rm -rf would destroy an already-working llama-server before
the skip check ran. Move it inside the else branch so existing builds
are preserved when the rebuild is skipped.
---------
Co-authored-by: Daniel Han <danielhanchen@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
- tool-ui-python.tsx: use explicit tuple type instead of `as const` to
match the mutable `[BundledTheme, BundledTheme]` expected by Streamdown
- chat-adapter.ts: add missing `argsText` field required by
ToolCallMessagePart and fix `args` type to use ReadonlyJSONObject
* Add elapsed timer to tool status pill in Studio
Show a count-up seconds timer (0s, 1s, 2s, ...) next to the tool status
text in the composer area. Helps users gauge how long a tool call (web
search, code execution) has been running. Timer resets when a new tool
starts and disappears when all tools finish.
* Fix tool call parsing, add tool outputs panel and reasoning copy button
Backend:
- Rewrite tool call XML parser to use balanced-brace JSON extraction
instead of greedy regex, fixing truncation on nested braces in
code/JSON arguments
- Handle optional closing tags (</tool_call>, </function>, </parameter>)
that models frequently omit
- Support bare <function=...> tags without <tool_call> wrapper
- Strip tool call markup from streamed content so raw XML never leaks
into the chat UI
- Use a persistent ~/studio_sandbox/ working directory for tool
execution so files persist across calls within a session
- Emit tool_start/tool_end SSE events so the frontend can display
tool inputs and outputs
Frontend:
- Add collapsible "Tool Outputs" panel below assistant messages showing
each tool call's input and output with copy buttons
- Add copy button to reasoning blocks
- Add elapsed timer to tool status pill
- Update project URLs in pyproject.toml (http -> https, add docs link)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add interactive HTML preview with fullscreen toggle for code blocks
HTML code fences now render an interactive sandboxed iframe preview
below the syntax-highlighted code, similar to how SVG fences show
an image preview. The iframe uses sandbox="allow-scripts" to allow
JavaScript execution while blocking access to the parent page.
Includes a fullscreen toggle (enlarge/minimize button) that expands
the preview into a viewport overlay, dismissible via button, Escape
key, or backdrop click. A streaming placeholder prevents partial
HTML from rendering mid-stream.
* Add tool call settings: auto-heal toggle, max iterations, timeout
Add three user-configurable tool call settings to the Studio Settings panel:
- Auto Heal Tool Calls: toggle to control fallback XML parsing of malformed
tool calls from model output (default: on)
- Max Tool Calls Per Message: slider 0-40 + Max to cap tool call iterations
per message (default: 10)
- Max Tool Call Duration: slider 1-30 minutes + Max to set per-tool-call
execution timeout (default: 5 minutes)
All settings persist to localStorage and flow through the full stack:
frontend store -> API request -> Pydantic model -> route -> llama_cpp -> tools.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix tool call timeout: respect no-limit and apply to web search
- Use a sentinel to distinguish timeout=None (no limit) from the default
(300s). Previously None was silently replaced with _EXEC_TIMEOUT.
- Pass the configured timeout to DDGS() for web searches so the setting
applies uniformly to all tool types.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add input validation bounds and per-thread sandbox isolation
- Add ge=0 constraint to max_tool_calls_per_message (rejects negative values)
- Add ge=1 constraint to tool_call_timeout (minimum 1 second)
- Thread session_id from frontend through backend to tool execution
- Scope sandbox directories per conversation: ~/studio_sandbox/{thread_id}/
- Backwards compatible: API callers without session_id use ~/studio_sandbox/
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix non-monotonic streaming and Python temp script path
- Split tool markup stripping into closed-only (mid-stream) and full
(final flush) to prevent cumulative text from shrinking mid-stream
- Enforce monotonicity: only emit when cleaned text grows, so the
proxy's delta logic (cumulative[len(prev_text):]) never breaks
- Place Python temp scripts in the sandbox workdir instead of /tmp so
sys.path[0] points to the sandbox and cross-call imports work
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Sanitize session_id to prevent path traversal in sandbox
Strip path separators and parent-dir references from session_id before
using it as a directory name. Verify the resolved path stays under
~/studio_sandbox/ as a second guard.
* feat(chat): proper assistant-ui tool call UIs with sources
Replace custom metadata-based ToolOutputsGroup with native assistant-ui
tool-call content parts. Backend SSE tool_start/tool_end events now emit
proper { type: "tool-call" } parts from the adapter, enabling per-tool
UIs registered via tools.by_name in MessagePrimitive.Parts.
- Web search: Globe icon, Source badges with favicons, auto-collapse
when LLM starts responding
- Python: Code icon, syntax-highlighted code via Streamdown/shiki,
output block with copy
- Terminal: Terminal icon, command in trigger, output with copy
- ToolGroup wraps consecutive tool calls (skips for single calls)
- Sources component renders URL badges at end of message
- Flattened code block CSS (single border, no nested boxes)
* fix(inference): respect empty enabled_tools allowlist
`if payload.enabled_tools:` is falsy for [], falling through to
ALL_TOOLS. Use `is not None` so an explicit empty list disables
all tools as intended.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Shine1i <wasimysdev@gmail.com>
* feat(studio): infinite scroll for recommended models list
The model selector showed a hard cap of 4 GGUFs + 4 safetensors in the
Recommended section. Users who wanted to browse more had to search
manually on Hugging Face.
Backend: increase the default model pool from 8+8 to 40+40 (the HF
fetch already pulls 80, so no extra network cost).
Frontend: replace the static 4+4 cap with on-demand lazy loading.
A page counter tracks how many groups of 4 to show per category.
An IntersectionObserver on a sentinel div at the bottom of the list
increments the page when the user scrolls down. Models are interleaved
in groups of 4 GGUFs then 4 hub models per page for a balanced view.
Key implementation details:
- Callback ref for the sentinel so the observer attaches reliably on
first popover open (useRef would miss the initial mount)
- Observer disconnects after each fire and re-attaches via useEffect
with a 100ms layout delay to prevent runaway page loading
- VRAM info fetched incrementally via useRecommendedModelVram on the
visible slice only
- recommendedSet uses visible IDs so HF search dedup stays correct
* refactor: address review feedback on recommended infinite scroll
- Simplify visibleRecommendedIds: use findIndex to locate the GGUF/hub
split point instead of re-filtering the entire array each time.
recommendedIds is already sorted GGUF-first, so a single slice is
enough.
- Fix VRAM refetch churn: pass the full recommendedIds (stable across
page increments) to useRecommendedModelVram instead of the growing
visibleRecommendedIds slice. The hook derives its stableKey from the
sorted+joined input, so passing the same pool on every page avoids
redundant HF modelInfo requests.
* compare for 2 diff models
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* resolving gemini comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix(studio): refine model-load toast stop action and compare selector sizing (#4369)
Co-authored-by: imagineer99 <samleejackson0@gmail.com>
---------
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: imagineer99 <samleejackson0@gmail.com>
* studio: improve onboarding UX, tooltips, and training defaults
- Change splash text to "Train and run LLMs locally"
- Add "Chat Only" card with BubbleChatIcon to skip directly to chat
- Add Skip/Skip to Chat buttons in sidebar and footer
- Back button on step 1 returns to splash screen instead of being disabled
- Change "Watch video guide" to "Get started with our guide" with new URL
- Update intro text to mention all model types + chat
- Make all tooltips clickable (in addition to hover) via React context
- Strip surrounding quotes from pasted HF tokens
- Rename "Eval Split" to "Evaluation Split"
- Add SparklesIcon to "Auto Detect" format option
- Change step 4 heading to "Choose your training parameters"
- Default max_steps to 60
- Learning rate displayed in scientific notation with +/- stepper
- Context length options capped by model's max_position_embeddings (via AutoConfig)
- Fix "QLORA"/"LORA" to "QLoRA"/"LoRA" in summary step
- Backend: add max_position_embeddings to model config endpoint
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* compare for 2 diff models
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* resolving gemini comments
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: disable thinking for Qwen3.5 <9B and always for AI Assist
- Change Qwen3.5 thinking threshold from <=2B to <9B (0.8B, 2B, 4B
all disable thinking by default; 9B+ enables it)
- Always pass enable_thinking=False in AI Assist helper calls
(_run_with_helper and _generate_with_backend) regardless of chat
thinking settings
* studio: address PR review comments
- Extract _get_max_position_embeddings helper to DRY config extraction
- Fix "Skip to Chat" to navigate to /chat on step 1 (was /studio)
* fix: comment out debug print statements
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: skip Shiki highlighting for incomplete SVG code fences
While streaming SVG content, the syntax highlighter (Shiki) re-parses
the entire growing SVG on every token, blocking the main thread and
freezing the code area until the fence closes. Show a plain-text
preview for incomplete SVG fences instead, similar to how Mermaid
diagrams show a placeholder while streaming.
* studio: fix default top_k from 50/40 to 20 for chat inference
Per Qwen3.5 docs (unsloth.ai/docs/models/qwen3.5), top_k should be 20
for both thinking and non-thinking modes. The model-specific config in
inference_defaults.json already had top_k=20 for Qwen3.5, but the
generic fallback defaults were wrong:
- Frontend DEFAULT_INFERENCE_PARAMS.topK: 50 -> 20
- Backend generate_chat_completion top_k: 40 -> 20
- Backend generate_chat_completion_with_tools top_k: 40 -> 20
- Frontend title generation top_k: 40 -> 20
* studio: set universal inference defaults for unknown models
Default params for any model without specific config:
temperature=0.6, top_p=0.95, top_k=20, min_p=0.01,
presence_penalty=0.0, repetition_penalty=1.0
Models with entries in inference_defaults.json (Qwen3.5, Gemma-3,
Llama, etc.) override these with their recommended values.
Updated in: frontend DEFAULT_INFERENCE_PARAMS, backend Pydantic
request models, and backend generate_chat_completion defaults.
* studio: only trust_remote_code for unsloth/ models in AutoConfig
Only set trust_remote_code=True when the model name starts with
"unsloth/". All other models default to False for safety.
* studio: move Generating spinner above the composer
The "Generating" spinner was below the send message bar, causing
the bar to jump up and down. Move it above the composer in both
the regular thread view and the welcome/empty view.
* studio: adjust toast close button position away from edge
Move the X close button on toasts (like "Starting model...") from
top-1.5 to top-3 and add right-3, giving more breathing room from
the top-right corner.
* studio: make Think button smaller with tighter icon-text gap
Reduce gap from 1.5 to 0.5, padding from px-2.5/py-1 to px-2/py-0.5,
and icon from size-3.5 to size-3.
* studio: multiple onboarding and chat UX improvements
- Move Generating spinner above composer (fixes jumping send bar)
- Make Think button smaller with tighter icon-text gap
- Chat card now inside grid (same size as Audio/Embeddings cards)
- Rename "Chat Only" to "Chat"
- Chat card requires Continue to proceed (no auto-advance)
- Continue on Chat selection skips onboarding and goes to /chat
- Tooltip (i) click on Chat card doesn't trigger navigation
- Step 1 footer Back button goes back to splash (label is "Back")
- Splash "Skip Onboarding" renamed to "Skip to Chat", navigates to /chat
- Toast close button moved away from edge
* studio: align Skip to Chat button, add Skip to footer
- Sidebar "Skip to Chat" now uses primary (green) Button style with
arrow icon, full width, aligned like step items. Shows on all steps.
- Footer: added "Skip" outline button next to Continue that goes
directly to /studio with progress saved (markOnboardingDone)
* studio: change default max steps from 30 to 60 in toggle hook
The DEFAULT_MAX_STEPS in use-max-steps-epochs-toggle.ts was still 30,
used as fallback when toggling from epochs back to max steps.
* studio: extend context length options to 262K
CONTEXT_LENGTHS now includes 65536, 131072, 262144 in addition to
the existing 512-32768 range. The onboarding step filters these by
the model's max_position_embeddings (e.g. Nemotron-3-Nano-4B has
262144), showing powers of 2 up to the model's maximum.
* studio: auto-select LoRA vs QLoRA based on model size and GPU memory
After selecting a model in onboarding, detect the total model weight
file size from HF Hub (safetensors/bin files). Then estimate memory
needed: model_size_gb * 1.5 * context_scale, where context_scale is:
- <=8192 tokens: 1.0x
- >8192 tokens: 1.7x
- >=16384 tokens: 2.0x
- >=32768 tokens: 4.0x
If the estimate fits in free GPU VRAM, default to LoRA (16-bit).
Otherwise default to QLoRA (4-bit).
Backend changes:
- Add model_size_bytes to ModelDetails (models.py)
- Add _get_model_size_bytes() using HfApi.repo_info (routes/models.py)
- Add vram_free_gb to get_gpu_summary (hardware.py)
Frontend changes:
- Add autoSelectTrainingMethod() in training-config-store.ts
- Called after model defaults are loaded
- Add model_size_bytes to ModelConfigResponse type
- Add vramFreeGb to HardwareInfo hook
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: rename "Importing ML libraries..." to "Importing Unsloth..."
* studio: show model/dataset in training status, fix LoRA/QLoRA casing
- Training status now shows 'Training "model_name"' and 'Dataset = ...'
instead of generic "Starting training..."
- Fix Studio progress section to show QLoRA/LoRA instead of QLORA/LORA
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: rename 'Skip to Chat' to 'Skip Onboarding' on splash screen
* studio: add presence_penalty support for chat inference
Add presence_penalty as a parameter across the full stack:
- Backend: llama_cpp.py generate_chat_completion/with_tools, Pydantic
models (inference.py), routes/inference.py pass-through
- Frontend: InferenceParams type, DEFAULT_INFERENCE_PARAMS (0.0),
chat-adapter.ts payload, chat-settings-sheet.tsx slider (0-2),
model defaults loading from inference_defaults.json
- Set Qwen3.5 default presence_penalty to 1.5 per official docs
- Default for unknown models is 0.0 (off)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: fix Chat card deselecting Text and aligning with other cards
* studio: fix presence_penalty not loading from inference defaults
The inference_config.py load_inference_config() was not including
presence_penalty in the returned config dict, so the Qwen3.5
default of 1.5 from inference_defaults.json never reached the
frontend. Added it to the config builder.
* studio: add delete button for cached models in model selector
Add trash icon on each downloaded model row (GGUF and safetensors) with
confirmation dialog. Backend DELETE /api/models/delete-cached endpoint
uses huggingface_hub scan_cache_dir + delete_revisions to cleanly remove
cached repos, refusing if the model is currently loaded.
* studio: restore inference defaults, reasoning, and tools on page refresh
On page refresh with a model already loaded, the frontend was not
re-applying model-specific inference defaults (presence_penalty,
temperature, etc.) or restoring reasoning/tools support flags.
Backend: Add inference config, supports_reasoning, supports_tools,
and context_length to InferenceStatusResponse.
Frontend: In the refresh callback, when an active model is detected,
apply mergeRecommendedInference and restore reasoning/tools flags
with proper Qwen3.5 size-based defaults.
* studio: fix delete dialog closing before async completes
Prevent AlertDialogAction's default close behavior with
e.preventDefault() so the dialog stays open during deletion.
Also block onOpenChange dismiss while deleting is in progress.
* fix: add Dict and Any imports to inference models
* studio: fix Qwen3.5 reasoning threshold in frontend load path
The frontend loadModel handler had the old threshold (<=2) for
disabling reasoning on small Qwen3.5 models. Changed to <9 to
match the backend. This was causing 4B to not properly disable
thinking by default when auto-loaded.
* studio: move GGUF delete to per-variant level
For GGUF repos, the trash icon now appears on each downloaded variant
row inside the quantization expander instead of on the repo-level row.
Backend accepts optional variant param to delete specific GGUF files
(blob + symlink) rather than the entire repo cache.
* studio: restore ggufContextLength on page refresh
The Max Tokens slider was capped at 32768 on page refresh because
ggufContextLength was not restored from the status response.
Now set it from statusRes.context_length on reconnect.
* fix: remove <think> from Qwen3.5 response template marker
The train-on-responses-only feature uses template markers to find
where the assistant response starts. The Qwen3.5 response marker
included '<think>\n' which is only present when thinking mode is
enabled. With thinking disabled (default for <9B), the marker
never matched, causing 100% of samples to be dropped.
Changed response marker from '<|im_start|>assistant\n<think>\n'
to '<|im_start|>assistant\n' which works regardless of thinking mode.
* studio: fix sloth ASCII art alignment in training overlay
* fix: correct sloth ASCII art alignment to match Unsloth banner
* studio: add Python and terminal tool calling to chat
Register python and terminal tools alongside web search. Python
executor validates imports (stdlib only) via unsloth_zoo
rl_environments, runs code in a subprocess sandbox with 5-min
timeout and cancel support. Terminal executor blocks dangerous
commands (rm, sudo, etc.) and runs in a temp directory.
Update llama_cpp tool loop to show tool-specific status messages
and pass cancel_event through to executors. Rename composer
toggle from "Search" to "Tools" and show TerminalIcon for
execution status pills.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: fix Nemotron/transformers 5.x support, onboarding navigation, port binding
Backend:
- Dynamic transformers 5.x detection via tokenizer_config.json fetch
(checks for TokenizersBackend class, cached per-model)
- Bump transformers 5.x version from 5.2.0 to 5.3.0 across all workers,
setup scripts (setup.sh, setup.ps1)
- Auto-enable trust_remote_code for unsloth/* models needing transformers 5.x
(workaround for NemotronH config parsing bug in transformers)
- Auto-install mamba-ssm/causal-conv1d for SSM models (NemotronH, Falcon-H1)
with --no-build-isolation --no-deps to avoid torch version conflicts
- Add SO_REUSEADDR to port check in run.py (fixes Colab proxy stale connection
falsely reporting port as in-use)
Frontend:
- Fix "Skip to Chat" navigation: use window.location.href instead of React
Router navigate() to bypass useEffect redirect race
- Fix "Skip Onboarding" on splash: navigates to /studio (not /chat)
- Fix onboarding guard: only check isOnboardingDone() on initial mount
- Fix Chat card on step 1: add sr-only spacer for consistent alignment
- Fix Chat+Text both selected: clear RadioGroup value when Chat is selected
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: split tools toggle into Search and Code buttons
Replace the single "Tools" toggle with two independent toggles:
- "Search" (globe icon) enables web search only
- "Code" (terminal icon) enables Python and terminal execution
Add enabled_tools list field to the inference payload so the
backend only registers the tools the user has toggled on. Both
toggles appear in the main composer and the compare composer.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: fix tool calling import validation and error logging
Replace unsloth_zoo-dependent import checker with a standalone
ast-based validator using sys.stdlib_module_names. This properly
blocks non-stdlib imports (numpy, requests, etc.) and returns a
clear error message to the model so it can rewrite using only
stdlib.
Add full traceback to tool streaming error logs for debugging.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: parse gpt-oss harmony channels for clean safetensors chat output
gpt-oss models emit multi-channel output via harmony protocol tokens
(<|channel|>analysis<|message|>... and <|channel|>final<|message|>...).
TextIteratorStreamer with skip_special_tokens=True strips the special
tokens but leaves channel names concatenated with content, producing
garbled output like "analysisWe need to...assistantfinalHello!".
Add HarmonyTextStreamer that decodes with skip_special_tokens=False,
parses harmony markup via regex, and emits <think>analysis</think>
for the analysis channel and plain text for the final channel --
reusing the existing frontend reasoning UI.
Also expose supports_reasoning=True for non-GGUF gpt-oss models in
the /status endpoint so the frontend enables the Think toggle.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: use unsloth_zoo for Python sandbox validation
Set UNSLOTH_IS_PRESENT=1 and import check_python_modules and
check_signal_escape_patterns directly from unsloth_zoo instead
of a standalone fallback. This gives us the full Unsloth
validation including stdlib-only import checks and signal/timeout
escape pattern detection.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: allow all imports in Python tool sandbox
Remove stdlib-only import restriction. Keep signal escape
pattern detection via unsloth_zoo for safety.
* studio: fix ReadTimeout on tool streaming final pass
The 0.5s read timeout used for cancel-checking during streaming
also fires when waiting for the first response from llama-server
(e.g. reasoning model thinking for 15+ seconds). Add
_stream_with_retry() context manager that retries on ReadTimeout
while checking cancel_event, so the model has unlimited time to
think before producing the first token. Applied to both the
regular streaming path and the tool-calling final pass.
* fix: rewrite HarmonyTextStreamer with stateful incremental parsing
The delta-on-transformed approach had two critical bugs:
1. Before the full <|channel|>X<|message|> pattern was complete, the
strip-tokens fallback emitted "analysis" as plain text. Then when
the regex matched, _transform returned a completely different format
(<think>...</think>) and the delta was computed against the wrong
base string, producing fragments like "think>", "nk>", ">".
2. Even with full matches, the closing </think> tag shifted position
as content grew, so text[prev_len:] produced garbled deltas.
Replace with stateful incremental parsing that:
- Buffers until a complete channel+message pair is seen
- Emits <think> once when analysis channel first appears
- Streams analysis content deltas (computed on channel content directly)
- Emits </think> once when final channel first appears
- Streams final content deltas
- Closes open think tags in end()
Also skip the generic all_special_tokens stripping in
_clean_generated_text for gpt-oss since HarmonyTextStreamer already
produces clean output and the generic stripping was mangling <think>
tags.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* fix: strip all <|...|> tokens in gpt-oss cleanup, not just harmony subset
The gpt-oss tokenizer has added tokens like <|return|> (id=200002) that
are not part of the harmony channel protocol but can leak into output.
The previous regex only stripped channel|message|start|end tokens.
Broaden the _clean_generated_text regex for gpt-oss to <\|[a-z_]+\|>
which catches all pipe-delimited tokens (return, constrain, reserved,
etc.) without matching <think>/<\/think> tags.
Verified: gpt-oss all_special_tokens are only <|return|>,
<|reserved_200017|>, <|startoftext|> -- none overlap with <think>.
The harmony tokens (channel, message, start, end) are added_tokens
but not in all_special_tokens.
* fix: hide config-only model repos from cached models list
Repos that only have metadata/config files cached (no .safetensors or
.bin weight files) were showing up in the Downloaded list with tiny
sizes like "1.8 KB" or "24 KB". These are just leftover config
snapshots from architecture checks, not usable models.
Filter the cached-models endpoint to only include repos that contain
actual model weight files (.safetensors or .bin).
* studio: fix toast description text contrast in dark mode
Add explicit !text-muted-foreground to toast description classNames
so secondary text (e.g. "Releases VRAM and resets inference state.")
is readable in dark mode.
* studio: fix Chat card icon alignment with size-4 spacer
Replace sr-only span (takes no space) with a size-4 shrink-0 div
matching the RadioGroupItem dimensions in other cards, so the Chat
icon aligns vertically with Text/Audio/Vision/Embeddings icons.
---------
Co-authored-by: workspace <user@workspace.local>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Manan17 <shahmanan170602@gmail.com>
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
- Add SVG preview rendering below code blocks using safe data URI
in <img> tag. Includes sanitization to block script/event handlers.
- Fix GGUF streaming crash: cache response.iter_text() iterator
instead of creating a new one on every loop iteration.
- Fix model selector showing "Select model..." after auto-load by
re-reading store state after setCheckpoint before setParams.
- Remove unused warmupToastShown variable (TS6133 build error).
- Change default suggestion to "Draw an SVG of a cute sloth".
Creative: temperature=1.5, min_p=0.1, top_p=Off (1.0), top_k=Off (0)
Precise: temperature=0.1, top_p=0.95, top_k=80, min_p=0.01
Also show "Off" in the slider label for top_p=1.0, top_k=0, and
repetition_penalty=1.0 since those values disable their respective
samplers. Changed top_k slider min from -1 to 0.
* studio: switch helper model to Qwen3.5-4B-GGUF
Replace Qwen3-4B-Instruct-2507-GGUF with Qwen3.5-4B-GGUF as the
default helper model for LLM-assisted dataset detection. Same
UD-Q4_K_XL variant.
* studio: fix stale GGUF metadata when switching models (#4347)
Reset _supports_reasoning, _supports_tools, _context_length, and
_chat_template at the start of _read_gguf_metadata() to prevent
stale settings from a previous model leaking into the next load.
Co-authored-by: Daniel Han <daniel@unsloth.ai>
* studio: change login error to "Incorrect password", add reset-password CLI
- Login error now says "Incorrect password" instead of the generic
"Incorrect username or password" since Studio only has one account.
- Add `unsloth studio reset-password` command that deletes the auth
database so a fresh admin account with a new random password is
created on the next server start.
* studio: include reset command in login error message
* studio: change password setup subtitle wording
## Summary
- Add web search tool calling for GGUF models (Search toggle, DuckDuckGo via ddgs)
- Add KV cache dtype dropdown (f16/bf16/q8_0/q5_1/q4_1) in Chat Settings
- Fix Qwen3/3.5 inference defaults per official docs (thinking on/off params)
- Enable reasoning by default for Qwen3.5 4B and 9B
- Replace "Generating" toast with inline spinner
- Fix stop button via asyncio.to_thread (event loop no longer blocked)
- Fix CUDA 12 compat lib paths for llama-server on CUDA 13 systems
- Fix auto-load model name not appearing in selector
- Training progress messages + dataset_num_proc fix
Integrated PRs:
- #4327 (imagineer99): BETA badge alignment (already in tree)
- #4340 (Manan Shah): prioritize training models in model selection
- #4344 (Roland Tannous): setup.sh macOS python version compatibility
- #4345 (Manan Shah): revamp model+dataset checking logic
* Removing .precommit config
* edited colab comments
* studio: update Unsloth_Studio_Colab.ipynb
* studio: update Unsloth_Studio_Colab.ipynb
* studio: add Colab T4 GPU metadata to force T4 instance
* style: update colab popup to black/white theme with gem icon and play button
* feat: center landscape image in colab notebook
* style: shrink popup to fit content, truncate URL display
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* feat: center landscape image in colab notebook
* feat: use GitHub raw URL for studio landscape image in notebook
* chore: update colab notebook
* feat: add studio landscape colab display image and update notebook
* feat: update notebook with studio landscape image
* style: remove colors, add progress bar, add VERBOSE flag to install output
* docs: add comments explaining VERBOSE flag and progress bar
* chore: update colab notebook
* fix: define VERBOSE, _STEP, _TOTAL at module level to fix NameError
---------
Co-authored-by: LeoBorcherding <LeoBorcherding@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* studio: extract param count from model name as fallback
When HuggingFace API doesn't return totalParams for a model,
extract the param count from the model name (e.g. "Qwen3-0.6B"
-> "0.6B", "Llama-3.2-1B-Instruct" -> "1B"). Applied to both
the recommended list and HF search results.
* studio: read GGUF context_length via fast header parser, set max tokens
- Fast GGUF metadata reader (~30-55ms) parses only KV header, skips
tensor data and large arrays (tokenizer vocab etc)
- Extracts context_length and chat_template from GGUF metadata
- Returns context_length in LoadResponse for frontend to use
- Frontend sets maxTokens to actual context_length for GGUFs (e.g.
262144 for Qwen3.5-9B, 131072 for Qwen2.5-7B)
- Max Tokens slider shows "Max" and is locked for GGUFs
- Auto-load path also uses actual context_length from load response
- Toast auto-dismiss (5s) and close button for auto-load toast
* studio: GGUF TTS audio support (from PR #4318)
Add GGUF TTS audio generation via llama-server. When a GGUF model
loads, the backend probes its vocabulary to detect audio codecs
(SNAC/BiCodec/DAC/CSM/Whisper). If detected, the codec is pre-loaded
and the model is reported as audio to the frontend.
During chat, TTS models route to the audio generation path which sends
a per-codec prompt to llama-server's /completion endpoint, extracts
generated tokens/text, and decodes to WAV using AudioCodecManager.
Also strips base64 audio data from prior assistant messages to prevent
context overflow.
Co-authored-by: Manan Shah <mananshah511@gmail.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Remove package-lock.json from tracking
* studio: per-model inference defaults, GGUF max tokens fix, reasoning toggle
- Add inference_defaults.json with per-model-family sampling parameters
for ~50 families (Qwen3.5, Qwen3, Gemma-3, Llama-3, DeepSeek, etc.).
Values sourced from unslothai/docs and Ollama params blobs.
- Family-based lookup in inference_config.py: extracts model family from
identifier, matches against patterns (longest match first), merges with
priority: model-specific YAML > family JSON > default.yaml.
- Fix GGUF Max Tokens slider locked at "Max": store ggufContextLength
separately from maxTokens so the slider is adjustable (step=64).
- Fix Ministral YAML: top_p was literal string "default", now 0.95.
- Add reasoning toggle for thinking models (Qwen3.5, Qwen3, DeepSeek-R1,
DeepSeek-V3.1, etc.): detect enable_thinking support from GGUF chat
template metadata, pass --jinja to llama-server, send
chat_template_kwargs per-request. Frontend shows "Reasoning is ON/OFF"
pill button next to attachment button in composer.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: remove default system prompt injection
Backend was injecting "You are a helpful AI assistant." when no system
prompt was provided. Neither unslothai/docs nor Ollama specify a default
system prompt for most models. Now defaults to empty string, letting the
model's own chat template handle system behavior.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: use lightbulb icons and "Think" label for reasoning toggle
Lightbulb on when thinking enabled, lightbulb-off when disabled.
Label is just "Think" in both states; grayed out styling when off.
* studio: fix HTML file upload breaking chat
Replace SimpleTextAttachmentAdapter with custom TextAttachmentAdapter
(excludes text/html) and HtmlAttachmentAdapter that strips tags via
DOMParser, removing scripts/styles and extracting readable text content
instead of dumping raw HTML markup into the conversation.
* studio: show chat template in Configuration panel
Display the model's Jinja2 chat template in a new "Chat Template"
section under Settings (now open by default). For GGUFs, reads from
GGUF metadata; for safetensors, reads from tokenizer.chat_template.
Template is editable with a "Restore default chat template" button
that appears when modified. Section only shows when a model with a
chat template is loaded.
* studio: editable chat template with Apply & Reload
Chat template section now functional:
- Editing the template shows "Apply & Reload" (reloads model with
custom template) and "Revert changes" buttons
- For GGUFs: writes template to temp .jinja file, passes
--chat-template-file to llama-server on reload
- For non-GGUF: passes chat_template_override in load request
- Settings section now open by default
- selectModel supports forceReload to reload same model
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: fix DeepSeek reasoning detection and auto-load metadata
- Set _model_identifier before _read_gguf_metadata so DeepSeek
"thinking" template detection works (was always None before)
- Populate ggufContextLength, supportsReasoning, reasoningEnabled,
defaultChatTemplate in autoLoadSmallestModel GGUF path
* studio: add spacing before BETA badge in navbar
Add gap-1.5 on the logo Link container to space the BETA label
from the wordmark.
Co-authored-by: Imagineer99 <Imagineer99@users.noreply.github.com>
* studio: vertically center BETA badge with logo
---------
Co-authored-by: Manan Shah <mananshah511@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Imagineer99 <Imagineer99@users.noreply.github.com>
* Strip <think> blocks from LLM assist model output
* Add debug logging for raw LLM assist output
* Quiet llama-server logs, use structlog in llm_assist
* Fix think-tag stripping when response is inside tags
* Remove debug logging of raw model output
* Clarify GGUF download logs: show cache hit vs actual download
* Clarify heuristic-detected mapping in UI text
* Default helper model to Qwen3-4B-Instruct-2507 UD-Q4_K_XL
* Remove package-lock.json from tracking, add to .gitignore
* Auto-open mapping dialog on Start Training for custom_heuristic format
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Use last think block when extracting inner content (review feedback)
* [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>
- GGUF: use -c 0 for model's native context size (no 4096 cap)
- GGUF: hide Max Seq Length slider (irrelevant), set Max Tokens to Max
- Non-GGUF: default Max Tokens to 4096
- Max Tokens slider shows "Max" label when at ceiling for GGUFs
- Run non-GGUF load_model in asyncio.to_thread for progress polling
- Auto-load smallest downloaded model when chatting without selection
- Wait for in-progress model load before inference (modelLoading store flag)
- Recommended list: 4 GGUFs + 4 hub models after case-insensitive dedup
- Model selector waits for cached data before rendering
- Toast close button repositioned, Sampling section open by default
- Add logging to _get_repo_size_cached exception handler
- Use -c 0 for llama-server (model's native context size, no 4096 cap)
- Run non-GGUF backend.load_model in asyncio.to_thread for progress polling
- Auto-load smallest downloaded model when user chats without selecting one
- Wait for in-progress model load before inference (no "No model loaded" error)
- Add modelLoading flag to zustand store for cross-component coordination
- Dynamic top models: send 8 GGUFs + 8 hub models, frontend caps 4+4 after dedup
- Case-insensitive dedup: downloaded models correctly hide from recommended list
- Prevent duplicate toasts: guard against double selectModel calls
- Model selector waits for cached data before rendering (no empty flash)
- Toast close button positioned at top-right with proper spacing
- Sampling section expanded by default in chat settings
- Global toast close button styling fix
Change all repetition_penalty defaults from 1.1 (or 1.05/1.2 in
presets) to 1.0 across the entire backend and frontend. Most models
handle repetition well on their own and a non-1.0 penalty can degrade
output quality, especially for code, structured output, and creative
tasks.
Files changed:
- Backend: inference.py, llama_cpp.py, orchestrator.py, worker.py,
models/inference.py (Field defaults)
- Frontend: chat-settings-sheet.tsx (Creative/Precise presets),
runtime-provider.tsx (auto-title generation)
- 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
for more information, see https://pre-commit.ci
* resolving merge conflicts
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* resolving gpt comments
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
* 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
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
* 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
for more information, see https://pre-commit.ci
* addressing the comment
* fixing auth flow
---------
Co-authored-by: Datta Nimmaturi <venkatadattasainimmaturi@gmail.com>
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.
