Stabilize Windows+WSL setup by fixing script line-ending pitfalls, WSL Ollama host detection, and dashboard startup behavior so models are detected reliably in Mission Control.
Co-authored-by: Cursor <cursoragent@cursor.com>
F24: Vision image upload — file picker for vision models, base64 encoding,
passed through stream API to Ollama generate endpoint
F25: Markdown rendering — ReactMarkdown replaces raw <pre> for all
prompt responses and chat assistant messages
F26: Syntax highlighting — Prism-based code blocks with language labels
and oneDark theme via react-syntax-highlighter
F27: <think> block collapse — auto-detect and collapse DeepSeek R1
reasoning traces into expandable details with word count
F28: Ollama library link — button next to Pull input opens ollama.com/library
Next.js 16 dashboard for monitoring and managing the local LLM stack.
Runs on port 3100 with dark theme using ByteLyst design tokens.
API routes:
- GET/POST /api/ollama — model list, running status, load/unload/generate
- GET /api/whisper — binary discovery, GGML model inventory
- GET /api/system — chip info, RAM/disk usage, brew package versions
Dashboard UI:
- Top stats row: Ollama status, model count, Whisper status, RAM usage
- Ollama models panel with load/unload actions, LOADED badge, details
- System panel with progress bars for RAM and disk
- Whisper.cpp panel with binary list and model inventory
- Brew packages panel with version tracking
- Basic prompt modal with Cmd+Enter shortcut
- Auto-refresh every 15 seconds
Also excludes __LOCAL_LLMs/ from root ESLint config (dashboard has its
own config and uses browser globals not available in Node.js context).
Tech: Next.js 16, React 19, TailwindCSS v4, Lucide icons, TypeScript
