- Updated deployment specification to reflect the new architecture involving servers A, B, and C.
- Revised README to describe the new deployment method using Gitea Runner and SSH.
- Modified `compose.production.yaml` to remove build context and use image tags directly.
- Enhanced deployment documentation to clarify configuration steps and environment variable requirements.
- Introduced `deploy-remote.sh` script for handling remote deployment tasks over SSH.
- Added unit tests for deployment scripts to ensure robustness and error handling.
- Updated `deploy-production.sh` to streamline image pulling and deployment processes.
- Introduced a new `WorkspaceTable` component for consistent table styling and behavior.
- Updated `BacktestPage`, `DatasetPage`, and `DataPreparationPage` to utilize the new `WorkspaceTable`.
- Implemented compact row heights and ellipsis for long text in table cells.
- Added validation for online field queries to ensure at least one filter is provided.
- Enhanced error handling and user feedback for invalid input scenarios.
- Improved pagination controls with dynamic page size options.
- Documented table display specifications in `ui-tables.md`.
- Added tests to verify table layout, interaction, and error handling.
- Added new metrics fields: sub_universe_sharpe, robust_universe_sharpe, two_year_sharpe, prod_correlation, pnl, check_type, and neutralization to the Alpha model.
- Updated snapshot_columns function to derive new metrics and check types from platform snapshots.
- Enhanced API to include failed checks and check types in responses.
- Created migration script to backfill existing Alpha records with new metrics and check types.
- Updated frontend components to display new metrics and allow editing of custom tags.
- Improved filtering and sorting capabilities for new metrics in the Alpha list.
- Added tests for new functionality including checks classification and metrics filtering.
- Introduced a comprehensive specification for a dataset catalog focused on single dataset research.
- Defined user stories, implementation decisions, and testing strategies to enhance the research workflow.
- Established clear constraints and visual components to align with Lark design principles.
- Outlined synchronization and persistence strategies for dataset and field management.
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