- Updated test files to import `AgentSessionLocal` from `advisor_db` instead of directly, preventing session binding to the real database during tests.
- Fixed 6 test cases to use the new login token utility, ensuring consistency across authentication methods.
- Adjusted customer risk codes in `test_convert_confirm.py` to reflect changes in customer classification (C3 to C4).
- Verified that changes resulted in zero database pollution during test runs, maintaining integrity of the testing environment.
- Documented findings and updates in the relevant test logs and memory files, ensuring clarity on the current state of tests and defects.
- Introduced `_recent_days_series_hint` to handle queries related to "最近N天" for time series data aggregation.
- Added `_cn_num_to_int` function to convert Chinese numerals to integers for better query parsing.
- Updated `_nl_sql_hints` to incorporate the new hint generation logic, ensuring accurate SQL output for recent days queries.
- Enhanced documentation to reflect these changes and improve clarity on the new functionalities.
Dev login no longer honors injected roles; self-service simulate/convert
blocks R4 disclosure grades like the UI and chat already do. Reuse of a
convert idempotency key with a different body returns 409. CT6 redeem qty
is derived from T+2 lots instead of a fixed 35000; CT7-05 and CT10-07
assertions follow. Update project memory and v1.1 post-fix test artifacts.
- Completed 203 test cases with 162 passing, 6 failing, and 2 skipped, identifying 2 critical defects (P0: authentication privilege escalation, P1: suitability disclosure not enforced).
- Enhanced test coverage by verifying front-end rendering values against back-end raw responses, addressing previous gaps in validation.
- Documented findings and defects in the new test log and README files, ensuring clarity on test outcomes and areas for improvement.
- Updated the TODO list to reflect the current state of defects and testing priorities, emphasizing the need for immediate attention to identified issues.
This round of testing significantly improves the robustness of the customer trade functionality, ensuring compliance and security standards are met.
- Introduced `convert_meta_api` endpoint to fetch the latest NAV date for conversion processes, restricted to users with the "risk_officer" role.
- Updated `created_at` field in `AgentMessage` to use UTC timezone for consistency in timestamp handling.
- Added `get_max_product_nav_date` method in `CoreReadOnlyRepository` to support the new API functionality.
- Enhanced Milvus template loading in `MilvusTemplateVectorStore` to ensure collections are loaded when they exist.
This update improves the API's capability to handle conversion metadata and ensures accurate timestamp management across the application.
- 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.
- Updated `RiskListAccess` and `ThresholdWriteAccess` to enforce access control in the risk repository and threshold repository, ensuring only authorized roles can perform sensitive operations.
- Introduced new methods in `RiskRepository` for counting pending alerts and listing alerts with access checks, improving data security and compliance.
- Enhanced the `chat.py` and `deps.py` files to integrate compliance roles into the risk management matrix, allowing for more granular access control.
- Updated documentation to reflect the new testing baseline of 825 passed tests, indicating improved stability and functionality across the application.
This update significantly strengthens the risk management capabilities, ensuring robust access control and compliance with organizational policies.
- Introduced new endpoints `/api/analyst/query/{trace_id}/sample` and `/api/analyst/escalate` for sampling query results and escalating issues to human analysts, respectively.
- Enhanced `AnalystAgent` to support sampling of SQL results based on trace ID and to handle escalation requests, improving user experience in error scenarios.
- Updated `analyst_schemas.py` to include `EscalateRequest` for structured escalation requests.
- Added corresponding frontend API calls and UI components to facilitate user interactions with the new features.
- Implemented unit tests to ensure the reliability of the new functionalities.
This update significantly enhances the analytical capabilities of the application, allowing users to retrieve detailed query samples and escalate issues effectively.
- 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.
- Added `interpret` flag to `AnalystChatRequest` for optional immediate interpretation of queries.
- Implemented new `POST /api/analyst/interpret` endpoint for on-demand data interpretation based on the latest query snapshot.
- Updated `AnalystAgent` to handle interpretation logic, including error handling and response formatting.
- Enhanced `AnalystQueryPage` to include a button for triggering interpretations, improving user interaction.
- Updated frontend API calls to support the new interpret functionality, ensuring seamless integration with existing workflows.
This update significantly enhances the analytical capabilities of the application, allowing users to request interpretations of their queries directly.
- Added `ThresholdRepository` for managing customer loss threshold configurations and notifications.
- Introduced `threshold_service` to handle loss threshold alerts based on customer portfolio performance.
- Enhanced `customer_prompts` to include new intent for querying product net values.
- Updated `customer_service` to integrate new threshold alert functionality into existing workflows.
- Implemented `sanitize_postprocess` for improved compliance handling in customer interactions.
- Enhanced course documentation to reflect updates in advisor training modules and interactive elements.
This update significantly improves the customer experience by providing proactive loss threshold notifications and enhancing the overall service framework.
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