## 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
* 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
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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>
Instead of downloading the full dataset and then slicing, use
streaming mode to only fetch the rows needed (up to slice_end + 1)
when a manual dataset slice is configured.
- Add 200-sample parallel probe using ThreadPoolExecutor + safe_num_proc
to estimate download speed and failure rate before full conversion
- Abort with clear error if >=30% of probe images fail to download
- Show estimated download time in the training overlay modal
- Parallel batch conversion for URL-based datasets (vs sequential for local)
- Add warning field to /check-format response for URL-based image datasets
- Display URL warning in dataset preview dialog (amber banner)
- Thread progress_callback from trainer through format_and_template_dataset
to convert_to_vlm_format for real-time status updates
Add Start/End index inputs under Advanced in the dataset card,
allowing users to slice a dataset by row range before training.
Wired end-to-end: frontend store, API payload, backend Pydantic
model, and trainer dataset loading (inclusive on both ends).
Add Start/End index inputs under Advanced in the dataset card,
allowing users to slice a dataset by row range before training.
Wired end-to-end: frontend store, API payload, backend Pydantic
model, and trainer dataset loading (inclusive on both ends).
