Implement a comprehensive artifacts system that allows users to create, edit,
and manage persistent documents alongside conversations, inspired by Claude's
artifacts feature.
Key Features:
- AI model integration with system prompts teaching artifact usage
- Inline preview cards in chat messages with collapsible previews
- On-demand side panel overlay (replaces split view)
- Preview/Code toggle for rendered markdown vs raw content
- Artifacts sidebar for managing multiple artifacts per thread
- Monaco editor integration for code artifacts
- Autosave with debounced writes and conflict detection
- Diff preview system for proposed updates
- Keyboard shortcuts and quick switcher
- Export/import functionality
Backend (Rust):
- New artifacts module in src-tauri/src/core/artifacts/
- 12 Tauri commands for CRUD, proposals, and export/import
- Atomic file writes with SHA256 hashing
- Sharded history storage with pruning policy
- Path traversal validation and UTF-8 enforcement
Frontend (TypeScript/React):
- ArtifactSidePanel: Claude-style overlay panel from right
- InlineArtifactCard: Preview cards embedded in chat
- ArtifactsSidebar: Floating list for artifact switching
- Enhanced ArtifactActionMessage: Parses AI metadata from content
- useArtifacts: Zustand store with autosave and conflict resolution
Types:
- Extended ThreadMessage.metadata with ArtifactAction
- ProposedContentRef supports inline and temp storage
- MIME-like content_type values for extensibility
Platform:
- Fixed platform detection to check window.__TAURI__
- Web service stubs for browser mode compatibility
- Updated assistant system prompts in both extension and web-app
This implements the complete workflow studied from Claude:
1. AI only creates artifacts when explicitly requested
2. Inline cards appear in chat with preview buttons
3. Side panel opens on demand, not automatic split
4. Users can toggle Preview/Code views and edit content
5. Autosave and version management prevent data loss
* feat: Add GGUF metadata reading functionality
This commit introduces a new Tauri command and a corresponding function to read metadata from GGUF model files.
The new read_gguf_metadata command in the Rust backend uses the byteorder crate to parse the GGUF file format and extract key metadata. This information, including the file's version, tensor count, and a key-value map of other metadata, is then made available to the TypeScript frontend.
This functionality is a foundational step toward providing users with more detailed information about their loaded models directly within the application.
This will be refactored later.
fixes: #6001
* loadMetadata() should return
* Properly throw eror to FE
* Use BufReader to improve performance
