Resyncs zero_publication via the canonical ALTER PUBLICATION ... SET
TABLE pattern (mirrors migration 143) to publish a thin live view of
automation_runs for dashboard real-time updates. Heavy JSONB fields
(definition_snapshot, inputs, output, artifacts, error) stay on REST.
- Add MiniMax-M3 to the model selection list (set as the new default)
- Add MiniMax-M2.7 and MiniMax-M2.7-highspeed as alternatives
- Remove deprecated MiniMax-M2.5 / M2.5-highspeed entries
- Update example config and Chinese setup docs to reference M3 (512K context)
- Updated version number to 0.0.26 in VERSION, pyproject.toml, and package.json files for browser, desktop, and web components.
- Ensured consistency in versioning across the project.
- Enhanced lambda function formatting in `_after_commit` for better clarity.
- Simplified generator expression in `_match_condition` for improved readability.
- Streamlined function signature in `_eligible` for consistency.
- Updated imports and refactored anonymous chat routes to use a new agent creation method.
- Added a new function `_load_anon_document` to handle document loading from Redis.
- Improved UI components by replacing legacy structures with modern alternatives, including alerts and separators.
- Refactored quota-related components to utilize new alert structures for better user feedback.
- Cleaned up unused variables and optimized component states for performance.
- Removed the eligibility gate for model selection in the automation creation process, allowing users to choose models directly in the builder.
- Updated the `AutomationBuilderForm` to incorporate model selection logic, ensuring that selected models are validated and preserved during automation creation and editing.
- Simplified the `AutomationsContent` and `AutomationNewContent` components by eliminating unnecessary eligibility checks and alerts.
- Enhanced the user experience by integrating model selection directly into the automation approval process, ensuring that only billable models are used.
- Refactored related tests to cover new model selection behavior and ensure proper validation of user-selected models.
