v1.2.1

Auto-tuning that knows the model, a roomier config panel, and a built-in update check. Bundles the work tracked internally as 1.1.0 + 1.2.0 + 1.2.1 into one release off 1.0.0.

Added

• Auto-tune reads the model card — after a sweep, TurboLLM reads the model's Hugging Face card and prefills the profile's sampling (temperature / top_k / top_p / min_p) with the author's recommended values, shown in the results dialog and applied on Save. Hybrid extraction: a deterministic scan first, then the just-tuned model itself as a fallback for prose-only cards. No card / no recommendation → your sampling is left unchanged.
• Base-model fallback for recommended sampling — most local GGUFs are third-party requants whose card omits the recommendation, so TurboLLM resolves the original model (via HF base_model) and reads its card. Well-known models (Gemma, Qwen, GLM, …) now get their recommended sampling even from a bare requant repo. Gated bases (e.g. Gemma) need a configured HuggingFace token.
• Complete tuned config as a table in the auto-tune results dialog — runtime (GPU layers, MoE offload, context, KV cache, flash attention), the full sampling (card values tagged "from card"), and measured speed / VRAM / first-token latency.
• App self-update check — Settings → About shows the running version and, when a newer TurboLLM is published on npm, an "update available" chip with a copy-paste npm i -g turbollm command. Cached 24h; silent when offline; never auto-updates.

Changed

• Model config is now a resizable side panel — load/tune settings open as a right-docked panel that resizes the page instead of overlaying it (drag to resize; width remembered), shared by the Models screen and the Chat header. On narrow screens it becomes a full-screen takeover.

Fixed

• Card-sampling extraction now works on reasoning models (Gemma 4, Qwen3) — thinking is disabled for the extraction step, so they emit usable JSON instead of empty or truncated output.
• Large model cards (e.g. Qwen3.5, ~80–95k chars) — the recommended-settings block deep in the card is now within the extraction window; values inside usage code blocks are ignored so demo numbers aren't mistaken for recommendations.