- Updated comments and logging messages in the worker and related files to replace "daily-run" with "auto run" for clarity and consistency.
- Adjusted the `WorkerConfig` struct to reflect the new terminology in configuration settings.
- Renamed functions and test cases to align with the updated terminology, enhancing code readability and maintainability.
This change improves the clarity of the AI pipeline's functionality within the tender management system.
- Updated the company service to include a new method for scheduling the refresh of cached AI recommendations after the AI pipeline execution.
- Introduced a new interface for managing cached recommendation refreshes, improving the separation of concerns within the service layer.
- Enhanced the worker initialization to include Redis client support, allowing for better management of recommendation caching.
- Added functionality to list company IDs with existing recommendation caches, ensuring efficient updates post-pipeline runs.
- Implemented unit tests to validate the new recommendation refresh logic and ensure proper handling of various scenarios.
This update significantly improves the handling of AI recommendations by integrating caching mechanisms with the AI pipeline, enhancing overall system performance and responsiveness.
Mazyar