[UX] Model loading experience and first-run onboarding
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- javascript
Research direction
Start by reading ModelStatus.jsx and WebGPUFallback.jsx, then inspect how the plugin settings page and sidebar expose model loading. Map the first-run, fallback, and cached-model states against the listed questions. Done means documented copy and UX recommendations plus a first-run flow design covering full-page and sidebar experiences.
Written by the indexing model from the issue text.
Description
Goal
Design the experience for first-time users who need to download the AI model (1.2GB) before they can use the chat.
Current State
ModelStatus.jsxshows a loading progress bar on the plugin settings page- No onboarding or explanation of what's happening
- Users with no WebGPU support see
WebGPUFallback.jsx
Questions to Answer
- How do we explain "downloading a 1.2GB AI model to your browser" to a non-technical admin?
- What expectations do we set about download time and GPU usage?
- Should we show a "try it first" demo with canned responses before the model loads?
- How does the loading experience work in the sidebar (smaller space than full page)?
- What happens on subsequent visits (model is cached — how do we communicate this)?
Deliverables
- Copy/UX recommendations for the loading states
- First-run flow design (what the user sees the very first time)
Skills needed
UX/Design, Writers
- Dominant language
- JavaScript
- Stars
- 28
- Forks
- 6
- Avg merge
- 9h 16m
- Merged PRs (30d)
- 2
Getting set up
- No Dockerfile or Docker Compose file
- Has a pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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