- Introduced a new `/analyze` endpoint in the analyst API to process analysis requests, allowing users to receive textual interpretations and chart specifications based on provided prompts.
- Enhanced `analyst_schemas.py` with `AnalyzeRequest` and `ChartSpec` models to structure analysis requests and validate chart specifications.
- Implemented chart validation logic in a new `analyst_chart.py` service, ensuring that chart types and fields are correctly specified and conform to allowed values.
- Updated `AnalystAgent` to handle analysis requests, integrating the new logic for generating responses based on user prompts and data availability.
- Added unit tests to verify the functionality of the new endpoint and validation mechanisms, ensuring robustness and reliability.
This update significantly enhances the analytical capabilities of the application, providing users with improved tools for data interpretation and visualization.
- Enhanced the `AnalystAgent` class to include an `_audit_terminal` method for logging query denials, clarifications, and errors, ensuring compliance and traceability.
- Updated error handling paths to call the new audit method, capturing relevant details such as question, user authentication, and SQL context.
- Introduced new validation checks in `sql_guard.py` to enforce ownership filters for sensitive queries, improving security measures.
- Added unit tests to verify the correct logging behavior and ownership filter enforcement, ensuring robust functionality.
This update significantly strengthens the auditing capabilities of the analyst agent, enhancing security and compliance in query handling.
- Introduced `TemplateService` for managing SQL templates, allowing for parameterized queries based on user input.
- Added functionality to automatically reload templates upon asset creation in `analyst.py`.
- Enhanced `CacheService` to support table generation bumping, ensuring cache invalidation on data changes.
- Updated `RiskRepository` and `GatewayRepository` to trigger cache invalidation for relevant operations.
- Expanded `analyst_schemas.py` to include new fields for template tracking in response metadata.
- Created seed SQL script for populating initial templates and added unit tests for template rendering logic.
This update significantly improves the efficiency of query handling by leveraging SQL templates, reducing reliance on LLM for common queries.
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