- Updated the job structure to include `anmod_id`, allowing for multiple mathematical models to be processed for each field and disease combination.
- Enhanced the batch processing logic to discover and execute jobs for `(field, disease, anmod_id)` instead of just `(field, disease)`.
- Modified the output file naming convention to include `anmod_id`, ensuring unique output for each model.
- Adjusted database interactions to accommodate the new primary key structure based on `pathogen_model_id`.
- Updated relevant documentation in `README.md` to reflect changes in job discovery, execution, and output generation.
- Enhanced unit tests to validate the new functionality and ensure correct behavior across various scenarios.
- Updated `config.yaml` to change the advice storage table from `advice` to `advisories` and adjusted the `thinking_budget` from 11264 to 9216.
- Modified `README.md` to reflect the new `advisories` table in the advisory generation process.
- Refactored SQL queries in `batch.py`, `job.py`, and `advice_context.py` to align with the new table structure.
- Enhanced the advice generation logic in `advice.py` to accommodate changes in the data model, including updates to the JSON structure for advice output.
- Updated relevant functions and documentation to ensure consistency across the codebase regarding the new advisory schema.
- Moved the assignment of `phenology_phase` in assemble.py to ensure it is included only for valid days.
- Updated the docstring in disease.py to clarify the rounding behavior of decimal values, enhancing the understanding of the formatting logic.
- Removed unnecessary checks in the decimal formatting function to streamline the code.
