Android WebView blocks third-party cookies by default. This patch:
- Returns session token in login/register response body
- Stores token in localStorage, sends via Authorization: Bearer header
- Backend getCurrentUser supports Authorization header fallback
Co-Authored-By: Claude <noreply@anthropic.com>
- Import `diseaseCatalogSeed` to use as a fallback data source in `catalog-page.tsx`.
- Implement logic to merge backend API responses with local seed data, ensuring `imageUrl` and `medicineRecommendations` are populated.
- Fix an issue where disease images and specific treatments were not rendering due to missing fields in the database payload.
- Enhance UI resilience by displaying accurate visual and medical data without requiring immediate backend updates.
- Convert static PNG image assets to WebP format and remove old PNG files to significantly reduce image payload size and improve page load performance.
- Enhance overall UI resilience and frontend speed.
- Updated @moonrepo/cli to version 2.2.5 and typescript to version 6.0.3 in package.json and shared package.json.
- Modified build script in package.json to run shared, api, and web builds.
- Removed unnecessary type and language declarations from shared moon.yml.
- Added ignoreDeprecations option in tsconfig.base.json to handle TypeScript 6.0 deprecations.
- Extend shared types for image classification, including PredictionProbability, UploaderMetadata, and ImageClassificationRecord.
- Create image_classifications table in the database with necessary fields and foreign key constraints.
- Implement disease mappers to convert database rows to shared disease records.
- Develop uploader client to handle image uploads to external service.
- Create image model service to load and classify images using TensorFlow.js.
- Add API routes for image classification, including GET for history and POST for new classifications.
- Implement frontend components for image classification form and display results.
- Update dashboard to integrate image classification functionality and display results.
- Document implementation plan for backend image classification.
- Add disease detail page component with data fetching and error handling
- Create shared types for diseases and classifications
- Implement API routes for diseases, classifications, and dashboard summary
- Develop reusable components for risk badge and disease card
- Build catalog page with search and filter functionality
- Update dashboard page with data-backed summary and manual classification form
- Register new routes in the web application
- Ensure type safety and consistency across shared modules
