Overview
Attachments
File upload and attachment management for AI context
filesuploadattachments
Docs
Attachments enable users to provide files as context for AI processing. Whether uploading documents for summarization, images for analysis, or datasets for exploration, this pattern handles the full lifecycle from upload through processing to management. It must communicate file status clearly and handle errors gracefully, since file operations are inherently asynchronous and failure-prone.
Variants
- Drop zone — A drag-and-drop area with a click-to-browse fallback, providing the most intuitive upload experience.
- Compact list — A minimal file list showing names and sizes, suitable for space-constrained layouts.
- Preview cards — File entries with thumbnail previews for images and icons for other types, giving visual context about attachments.
Use Cases
- Document analysis tools that process PDFs and text files
- Image generation tools accepting reference images
- Data analysis platforms ingesting CSVs and spreadsheets
- Multi-modal AI assistants that accept mixed file types
- Code review tools that accept source files for analysis
Best Practices
- Show upload progress for large files and clear error states for failures.
- Validate file types and sizes before upload begins, with helpful error messages.
- Display file metadata (name, size, type) so users can verify what they've attached.
- Support both drag-and-drop and click-to-browse for accessibility.
- Allow removal of individual attachments without affecting others.