24 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
DoubleMathew
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4c1a6cb962 |
gate on min uv version and shortcut python candidate search if known (#4489)
* gate on min uv version and shortcut python candidate search if known * fix sort -V cross compat issue, run_quiet early exit on llamacpp, autolaunch * update launch message * Fix PR comments * auto launch and find open port * remove dev install * Fix review findings: major-version guard, non-fatal port fallback, tty comment, restore local * Remove autolaunch, clean up dead state and debug noise - Remove find_open_port, TTY-gated autolaunch, and </dev/tty redirection from install.sh; just print launch instructions - Remove unused BEST_MAJOR variable from studio/setup.sh - Remove stray "finished finding best python" debug echo - Fix stale comment "below 3.12" to "below 3.11" * Reject prerelease uv at exact minimum version boundary * Remove 2>/dev/null from version_ge numeric comparisons Let non-numeric version parts surface errors on stderr instead of being silently swallowed. --------- Co-authored-by: Daniel Han <danielhanchen@gmail.com> |
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Manan Shah
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6f129a214b |
Fix Install commands for Windows + 1 line installs (#4447)
* 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> |
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Daniel Han
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7ddb660b0c |
revert: always rebuild frontend, override caching with _NEED_FRONTEND_BUILD=true (#4427)
* revert: remove frontend build caching from setup scripts The mtime-based caching introduced in #4404/#4413 can incorrectly skip frontend builds -- e.g. after git pull when filesystem timestamps are not preserved, or after our Tailwind v4 discovery that the site-packages .gitignore must be hidden before vite build (which the cached path doesn't handle). Always rebuild the frontend on setup. The build takes ~15s and is safer than risking a stale dist/. * revert: disable frontend build caching, keep code commented out Caching disabled by always setting _NEED_FRONTEND_BUILD=true. The mtime-based logic is preserved in comments for future re-enabling. Reasons for disabling: - Git does not preserve file timestamps, so cached dist/ can appear newer than freshly checked-out source after a pull - Tailwind v4 requires hiding site-packages/.gitignore before vite build; the cache path bypasses this, producing broken CSS * revert: always rebuild frontend, remove mtime caching * revert: always rebuild frontend, override caching with _NEED_FRONTEND_BUILD=true |
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Daniel Han
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1f12ba16df |
Combine studio setup fixes: frontend caching, venv isolation, Windows CPU support (#4413)
* Allow Windows setup to complete without NVIDIA GPU setup.ps1 previously hard-exited if nvidia-smi was not found, blocking setup entirely on CPU-only or non-NVIDIA machines. The backend already supports CPU and MLX (Apple Silicon) in chat-only GGUF mode, and the Linux/Mac setup.sh handles missing GPUs gracefully. Changes: - Convert the GPU check from a hard exit to a warning - Guard CUDA toolkit installation behind $HasNvidiaSmi - Install CPU-only PyTorch when no GPU is detected - Build llama.cpp without CUDA flags when no GPU is present - Update doc comment to reflect CPU support * Cache frontend build across setup runs Skip the frontend npm install + build if frontend/dist already exists. Previously setup.ps1 nuked node_modules and package-lock.json on every run, and both scripts always rebuilt even when dist/ was already present. On a git clone editable install, the first setup run still builds the frontend as before. Subsequent runs skip it, saving several minutes. To force a rebuild, delete frontend/dist and re-run setup. * Show pip progress for PyTorch download on Windows The torch CUDA wheel is ~2.8 GB and the CPU wheel is ~300 MB. With | Out-Null suppressing all output, the install appeared completely frozen with no feedback. Remove | Out-Null for the torch install lines so pip's download progress bar is visible. Add a size hint so users know the download is expected to take a while. Also moves the Triton success message inside the GPU branch so it only prints when Triton was actually installed. * Guard CUDA env re-sanitization behind GPU check in llama.cpp build The CUDA_PATH re-sanitization block (lines 1020-1033) references $CudaToolkitRoot which is only set when $HasNvidiaSmi is true and the CUDA Toolkit section runs. On CPU-only machines, $CudaToolkitRoot is null, causing Split-Path to throw: Split-Path : Cannot bind argument to parameter 'Path' because it is null. Wrap the entire block in `if ($HasNvidiaSmi -and $CudaToolkitRoot)`. * Rebuild frontend when source files are newer than dist/ Instead of only checking if dist/ exists, compare source file timestamps against the dist/ directory. If any file in frontend/src/ is newer than dist/, trigger a rebuild. This handles the case where a developer pulls new frontend changes and re-runs setup -- stale assets get rebuilt automatically. * Fix cmake not found on Windows after winget install Two issues fixed: 1. After winget installs cmake, Refresh-Environment may not pick up the new PATH entry (MSI PATH changes sometimes need a new shell). Added a fallback that probes cmake's default install locations (Program Files, LocalAppData) and adds the directory to PATH explicitly if found. 2. If cmake is still unavailable when the llama.cpp build starts (e.g. winget failed silently or PATH was not updated), the build now skips gracefully with a [SKIP] warning instead of crashing with "cmake : The term 'cmake' is not recognized". * Fix frontend rebuild detection and decouple oxc-validator install Address review feedback: - Check entire frontend/ directory for changes, not just src/. The build also depends on package.json, vite.config.ts, tailwind.config.ts, public/, and other config files. A change to any of these now triggers a rebuild. - Move oxc-validator npm install outside the frontend build gate in setup.sh so it always runs on setup, matching setup.ps1 which already had it outside the gate. * Show cmake errors on failure and retry CUDA VS integration with elevation Two fixes for issue #4405 (Windows setup fails at cmake configure): 1. cmake configure: capture output and display it on failure instead of piping to Out-Null. When the error mentions "No CUDA toolset found", print a hint about the CUDA VS integration files. 2. CUDA VS integration copy: when the direct Copy-Item fails (needs admin access to write to Program Files), retry with Start-Process -Verb RunAs to prompt for elevation. This is the root cause of the "No CUDA toolset found" cmake failure -- the .targets files that let MSBuild compile .cu files are missing from the VS BuildCustomizations directory. * Address reviewer feedback: cmake PATH persistence, stale cache, torch error check 1. Persist cmake PATH to user registry so Refresh-Environment cannot drop it later in the same setup run. Previously the process-only PATH addition at phase 1 could vanish when Refresh-Environment rebuilt PATH from registry during phase 2/3 installs. 2. Clean stale CMake cache before configure. If a previous run built with CUDA and the user reruns without a GPU (or vice versa), the cached GGML_CUDA value would persist. Now the build dir is removed before configure. 3. Explicitly set -DGGML_CUDA=OFF for CPU-only builds instead of just omitting CUDA flags. This prevents cmake from auto-detecting a partial CUDA installation. 4. Fix CUDA cmake flag indentation -- was misaligned from the original PR, now consistently indented inside the if/else block. 5. Fail hard if pip install torch returns a non-zero exit code instead of silently continuing with a broken environment. * Remove extra CUDA cmake flags to align Windows with Linux build Drop GGML_CUDA_FA_ALL_QUANTS, GGML_CUDA_F16, GGML_CUDA_GRAPHS, GGML_CUDA_FORCE_CUBLAS, and GGML_CUDA_PEER_MAX_BATCH_SIZE flags. The Linux build in setup.sh only sets GGML_CUDA=ON and lets llama.cpp use its defaults for everything else. Keep Windows consistent. * Address reviewer round 2: GPU probe fallback, Triton check, stale binary rebuild 1. GPU detection: fallback to default nvidia-smi install locations (Program Files\NVIDIA Corporation\NVSMI, System32) when nvidia-smi is not on PATH. Prevents silent CPU-only provisioning on machines that have a GPU but a broken PATH. 2. Triton: check $LASTEXITCODE after pip install and print [WARN] on failure instead of unconditional [OK]. 3. Stale llama-server: check CMakeCache.txt for GGML_CUDA setting and rebuild if the existing binary does not match the current GPU mode (e.g. CUDA binary on a now-CPU-only rerun, or vice versa). * Fix frontend rebuild detection and npm dependency issues Addresses reviewer feedback on the frontend caching logic: 1. setup.sh: Fix broken find command that caused exit under pipefail. The piped `find | xargs find -newer` had paths after the expression which GNU find rejects. Replaced with a simpler `find -maxdepth 1 -type f -newer dist/` that checks ALL top-level files (catches index.html, bun.lock, etc. that the extension allowlist missed). 2. setup.sh: Guard oxc-validator npm install behind `command -v npm` check. When the frontend build is skipped (dist/ is cached), Node bootstrap is also skipped, so npm may not be available. 3. setup.ps1: Replace Get-ChildItem -Include with explicit path probing for src/ and public/. PowerShell's -Include without a trailing wildcard silently returns nothing, so src/public changes were never detected. Also check ALL top-level files instead of just .json/.ts/.js/.mjs extensions. * Fix studio setup: venv isolation, centralized .venv_t5, uv targeting - All platforms (including Colab) now create ~/.unsloth/studio/.venv with --without-pip fallback for broken ensurepip environments - Add --python sys.executable to uv pip install in install_python_stack.py so uv targets the correct venv instead of system Python - Centralize .venv_t5 bootstrap in transformers_version.py with proper validation (checks required packages exist, not just non-empty dir) - Replace ~150 lines of duplicated install code across 3 worker files with calls to the shared _ensure_venv_t5_exists() helper - Use uv-if-present with pip fallback; do not install uv at runtime - Add site.addsitedir() shim in colab.py so notebook cells can import studio packages from the venv without system-Python double-install - Update .venv_t5 packages: huggingface_hub 1.3.0->1.7.1, add hf_xet - Bump transformers pin 4.57.1->4.57.6 in requirements + constraints - Add Fast-Install helper to setup.ps1 with uv+pip fallback - Keep Colab-specific completion banner in setup.sh * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix nvidia-smi PATH persistence and cmake requirement for CPU-only 1. Store nvidia-smi as an absolute path ($NvidiaSmiExe) on first detection. All later calls (Get-CudaComputeCapability, Get-PytorchCudaTag, CUDA toolkit detection) use this absolute path instead of relying on PATH. This survives Refresh-Environment which rebuilds PATH from the registry and drops process-only additions. 2. Make cmake fatal for CPU-only installs. CPU-only machines depend entirely on llama-server for GGUF chat mode, so reporting "Setup Complete!" without it is misleading. GPU machines can still skip the llama-server build since they have other inference paths. * Fix broken frontend freshness detection in setup scripts - setup.sh: Replace broken `find | xargs find -newer` pipeline with single `find ... -newer` call. The old pipeline produced "paths must precede expression" errors (silently suppressed by 2>/dev/null), causing top-level config changes to never trigger a rebuild. - setup.sh: Add `command -v npm` guard to oxc-validator block so it does not fail when Node was not installed (build-skip path). - setup.ps1: Replace `Get-ChildItem -Include` (unreliable without -Recurse on PS 5.1) with explicit directory paths for src/ and public/ scanning. - Both: Add *.html to tracked file patterns so index.html (Vite entry point) changes trigger a rebuild. - Both: Use -print -quit instead of piping to head -1 for efficiency. * Fix bugs found during review of PRs #4404, #4400, #4399 - setup.sh: Add || true guard to find command that checks frontend/src and frontend/public dirs, preventing script abort under set -euo pipefail when either directory is missing - colab.py: Use sys.path.insert(0, ...) instead of site.addsitedir() so Studio venv packages take priority over system copies. Add warning when venv is missing instead of silently failing. - transformers_version.py: _venv_t5_is_valid() now checks installed package versions via .dist-info metadata, not just directory presence. Prevents false positives from stale or wrong-version packages. - transformers_version.py: _install_to_venv_t5() now passes --upgrade so pip replaces existing stale packages in the target directory. - setup.ps1: CPU-only PyTorch install uses --index-url for cpu wheel and all install commands use Fast-Install (uv with pip fallback). * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix _venv_t5_is_valid dist-info loop exiting after first directory Remove premature break that caused the loop over .dist-info directories to exit after the first match even if it had no METADATA file. Now continues iterating until a valid METADATA is found or all dirs are exhausted. * Capture error output on failure instead of discarding with Out-Null setup.ps1: 6 locations changed from `| Out-Null` to `| Out-String` with output shown on failure -- PyTorch GPU/CPU install, Triton install, venv_t5 package loop, cmake llama-server and llama-quantize builds. transformers_version.py: clean stale .venv_t5 directory before reinstall when validation detects missing or version-mismatched packages. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix ModuleNotFoundError when CLI imports studio.backend.core The backend uses bare "from utils.*" imports everywhere, relying on backend/ being on sys.path. Workers and routes add it at startup, but the CLI imports studio.backend.core as a package -- backend/ was never added. Add sys.path setup at the top of core/__init__.py so lazy imports resolve correctly regardless of entry point. Fixes: unsloth inference unsloth/Qwen3-8B "who are you" crashing with "No module named 'utils'" * Fix frontend freshness check to detect all top-level file changes The extension allowlist (*.json, *.ts, *.js, *.mjs, *.html) missed files like bun.lock, so lockfile-only dependency changes could skip the frontend rebuild. Check all top-level files instead. * Add tiktoken to .venv_t5 for Qwen-family tokenizers Qwen models use tiktoken-based tokenizers which fail when routed through the transformers 5.x overlay without tiktoken installed. Add it to the setup scripts (with deps for Windows) and runtime fallback list. Integrates PR #4418. * Fix tiktoken crash in _venv_t5_is_valid and stray brace in setup.ps1 _venv_t5_is_valid() crashed with ValueError on unpinned packages like "tiktoken" (no ==version). Handle by splitting safely and skipping version check for unpinned packages (existence check only). Also remove stray closing brace in setup.ps1 tiktoken install block. --------- Co-authored-by: Daniel Han <danielhanchen@users.noreply.github.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> |
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Daniel Han
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0acd1c7eec |
studio: improve onboarding UX, tooltips, and training defaults (#4355)
* 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> |
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Datta Nimmaturi
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33dc47da72 |
Fix spacing in setup.sh echo statements | ||
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Daniel Han
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eeffa4c065 |
studio: web search, KV cache dtype, training progress, inference fixes
## 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 |
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Leo Borcherding
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df98569f12 |
studio: improve Colab notebook, redesign ready popup, and clean up install output (#4339)
* 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> |
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Daniel Han
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6c2a593522 |
Fix setup.sh crash on Mac with empty gitignore array
The `set -u` (nounset) flag in setup.sh causes `${_HIDDEN_GITIGNORES[@]}`
to fail with "unbound variable" when no parent .gitignore with `*` is
found (common on Mac where the install is not inside a Python venv).
Use the `${arr[@]+"${arr[@]}"}` idiom to safely expand empty arrays
under nounset mode.
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Daniel Han
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a8f02c9f3f |
Fix studio frontend build producing empty Tailwind CSS
Two issues caused the studio frontend to render without any styling when installed via `pip install` (non-editable): 1. `pyproject.toml` package-data only included `frontend/dist/**/*`. The `include-package-data = true` setting relies on `git ls-files`, which fails in isolated builds (pip/uv copy source to a temp dir without `.git`). This meant `frontend/src/`, `package.json`, `vite.config.ts`, and other build files were missing from the installed package. Tailwind had no source files to scan. 2. Python venvs auto-create a `.gitignore` with a bare `*` pattern. Tailwind v4's oxide scanner walks parent directories and respects `.gitignore` -- so even when source files are present, the venv's `*` pattern causes the scanner to skip all `.tsx` files. The result is a 34KB CSS skeleton with zero utility classes instead of the expected 265KB. Additionally, Vite adds `crossorigin` to script/link tags by default. This forces CORS mode on font subresource loads, which Firefox HTTPS-Only Mode does not exempt -- causing all @font-face downloads to fail silently when Studio is served over HTTP. Changes: - pyproject.toml: Expand package-data to include frontend source, config files, setup scripts, and backend requirements using glob patterns (no node_modules) - studio/setup.sh: Temporarily hide parent .gitignore files containing a bare `*` during `npm run build`, with trap-based restoration - studio/backend/main.py: Strip `crossorigin` attributes from HTML at serve time so fonts load correctly on any protocol |
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Daniel Han
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a7a66a66b9 |
studio: address review feedback
install_python_stack.py: - Print uv error output on failure for debuggability - Refactor pip_install() to use early return after uv success, removing duplicated pip command path setup.sh: - Guard nvidia-smi command substitution with || true so it does not abort the script under set -euo pipefail when nvidia-smi fails (e.g., containerized environments, driver quirks) - Read all GPU compute capabilities and deduplicate, so mixed-GPU hosts get kernels built for all present architectures instead of only the first GPU |
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Daniel Han
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6dda8c4c23 |
studio: revert combined targets, keep separate builds
Restore separate cmake --build calls for llama-server and llama-quantize on both setup.sh and setup.ps1. The combined approach made llama-quantize failure fatal, but it was originally best-effort (|| true on Linux, [WARN] on Windows). The timing savings from combining was only ~2.7s, not worth the semantic change. The Ninja + arch detection speedups are preserved (55s vs 1m 37s). |
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Daniel Han
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f8dc7c9a5c |
studio: speed up llama.cpp build with Ninja + arch detection
Three improvements to the llama.cpp build step in setup.sh: 1. Detect GPU compute capability via nvidia-smi and limit CMAKE_CUDA_ARCHITECTURES to the current GPU. Without this, cmake builds for all default CUDA architectures which is very slow. 2. Use Ninja build generator when available. Ninja has better parallelism than Make for CUDA compilation. 3. Build both llama-server and llama-quantize targets in a single cmake --build invocation for better parallelism. 4. Add --threads=0 to CMAKE_CUDA_FLAGS for multi-threaded nvcc compilation. Measured on 192-core machine with B200 (sm_100): Make (all archs): very slow (minutes for each arch) Make (single arch): 1m 37s Ninja (single arch): 55s Speedup: ~1.7x Combined with the uv change, total setup goes from ~4m 35s to ~1m 40s. |
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Roland Tannous
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b95242a80f | fix: only skip frontend build for PyPI prebuilt (site-packages + dist check) | ||
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Roland Tannous
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0e0325127d |
Revert "site-packages + dist check"
This reverts commit
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Roland Tannous
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82063d8edb | site-packages + dist check | ||
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Roland Tannous
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8ce2b64df7 | allow install from source | ||
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Roland Tannous
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8108f1bf11 | Fix nvm/npmrc prefix conflict in setup.sh | ||
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Roland Tannous
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47654cb91c | Final cleanup | ||
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Roland Tannous
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220a7bb1ed | Update setup.sh | ||
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Roland Tannous
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1087216cb5 | Merge branch 'fix/pre-merge-cleanup' into feature/merge-build-final | ||
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Manan17
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fbccac8cee | shifting setup & co inside studio | ||
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Roland Tannous
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daa50d0756 |
Revert "Merge pull request #347 from unslothai/feature/studio-storage-roots"
This reverts commit |
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Manan17
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32569fc8a8 | shifting setup & co inside studio |
Renamed from setup.sh (Browse further)