Introduce a shared dialog header style (.unified-dialog-header) in app.css and opt dialog components into the new chrome by updating their header markup. Headers now use unified-dialog-icon and unified-dialog-text elements (and import the matching Lucide icons where needed), which standardizes icon placement, title/eyebrow layout, close button styling and responsive behavior. The Command Palette layout was adjusted to include the new header and its grid rows.
The CSS is explicitly opt-in (so page/section headers remain unchanged) and includes hover/focus styles and a theme-sensitive close color variable. This commit is a UI refactor only — no API or behavior logic changes.
Remove local on-device model support and related IPC commands,
consolidating commit-generation to cloud providers and simplifying the
AI crate surface. Local-specific types, generation profiles, caching,
and the local prompt builder were removed while message sanitization and
diff-echo detection were preserved. Also harden repository handling and
runtime: unborn HEADs are handled gracefully so empty repos still report
files, Git LFS sync is skipped for repositories without commits, and
tokio runtime features were enabled.
- Remove local model engine, load/status commands, and local profile code
- Handle unborn HEAD and skip LFS sync for repos without commits
- Enable tokio runtime features and route AI generation to cloud only
Introduces a robust system for running automated, staged diff reviews against various large language models. This feature allows users to submit their changes to external AI services and receive structured feedback on potential bugs, security issues, and maintainability risks before committing.
The implementation covers the entire stack:
* Backend logic was added to handle API communication with OpenAI, Anthropic, and custom endpoints.
* A dedicated parser ensures that complex JSON outputs from LLMs are reliably converted into structured findings (severity, title, description).
* New components and UI elements provide a clear visualization of the AI's assessment and actionable suggestions.
- Supports multiple major LLM providers (OpenAI, Anthropic)
- Parses structured JSON output for consistent review results
- Adds dedicated UI dialog to display AI findings and risk level
Christoph
Christoph Brandau