mudler's LocalAI [bot]
0aaff91ebd
* feat(ui): add installed model lifecycle Models now owns catalog exploration and installed runtime controls under one canonical route. URL-owned state keeps lifecycle context recoverable through links and browser history. Assisted-by: Codex:gpt-5 Playwright * feat(ui): add installed backend lifecycle Backends split discovery from backend-binary management. The canonical page now keeps both lifecycle views under one URL-backed shell while it preserves target-node placement. Assisted-by: Codex:gpt-5 Playwright * fix(ui): repair lifecycle state updates Installed models lost distributed refreshes and kept a deleted selection. Backend searches also stopped tracking URL changes, while batch upgrades stopped after their first error. Preserve background refreshes and finish each requested batch action. Drive catalog results from URL-backed state without losing full metadata. Assisted-by: Codex:gpt-5 [Playwright] * feat(ui): make resource pages canonical Replace Host navigation with canonical Models and Backends lifecycle routes, preserve legacy management URLs, and surface shared host capacity on the Operate overview. Assisted-by: Codex:gpt-5 [Playwright] * feat(ui): complete canonical resource lifecycle Finish the responsive list-to-detail behavior, remove the retired Host implementation, and keep Explore focused on discovery while Installed owns destructive actions. Update regression coverage, localization, documentation, and development binding for the canonical resource pages. Assisted-by: Codex:gpt-5 [Playwright] * docs(ui): record the UI design context Record the approved users, brand character, and design principles so future interface work uses the same product direction. Index the context from the repository's agent instructions. Assisted-by: Codex:gpt-5 --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
1.7 KiB
Design Context
Users
LocalAI serves both single-host users who want to install and try models quickly and experienced developers, ML engineers, system administrators, and DevOps operators who manage production hosts or distributed clusters. The interface must support first-time discovery without hiding the runtime state, configuration, and control that returning operators need.
Brand Personality
Capable, easy to use, and trustworthy. The interface should make sophisticated local-AI infrastructure feel understandable and under control. It should be direct and calm rather than playful, ornamental, or intimidating.
Aesthetic Direction
Use LocalAI's established technical, editorial design language: Geist typography, compact information density, sharp geometry, deep blue-black surfaces, action blue, mint for healthy/local/live state, and amber only for decisions requiring attention. Support both dark and light themes. Avoid generic card dashboards, decorative gradients, glass effects, and visual noise.
Design Principles
- Use progressive disclosure to serve newcomers and operators in the same workflow: make the common path obvious, then reveal operational depth in context.
- Organize navigation around user intent and lifecycle state, not implementation concepts or nested containers.
- Give each resource one canonical home; expose discovery, installed state, and runtime state as clear views of that resource instead of duplicating management surfaces.
- Keep operational status visible and trustworthy through precise labels, explicit scope, and actionable state—not decoration.
- Preserve information density for expert use while flattening navigation and reducing repeated summaries, tabs, rails, and panels.