- 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.
- Increased `thinking_budget` in `config.yaml` from 9216 to 11264 to enhance LLM performance.
- Clarified conditions for including `last_applied_treatment` in the advice JSON structure, ensuring it is appended even when `allowed_products` is empty.
- Refactored product filtering logic in `products.py` to implement a new function for checking if the treatment interval is open, improving the accuracy of product recommendations.
- Updated unit tests to validate the new treatment interval logic and ensure correct behavior in various scenarios.