- 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.
- 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.
- Enhanced `ITERATION.md` to include new entries for front-end/API optimizations and Chat session management improvements.
- Expanded `TODO.md` with a daily work summary, completed tasks, and upcoming priorities, ensuring clarity on project status and next steps.
- Added a new summary document for 2026-09-10, detailing work completed across various components, including front-end fixes and API enhancements.
This update improves documentation clarity and provides a comprehensive overview of recent developments and future tasks.
- Added `status` query parameter to `list_sessions_api` for filtering sessions by their status (active/closed).
- Introduced `close_all_sessions_api` endpoint to allow users to close all active sessions for the current actor.
- Updated `SessionRepository` to support status filtering in session listing and implemented logic for closing active sessions.
- Improved Redis connection settings for better performance and reliability.
This update enhances the chat functionality by providing more control over session management, improving user experience and system efficiency.
- Updated `AnalystQueryPage` to display tags for template hits and cache hits, improving user feedback on query performance.
- Adjusted SQL result label to streamline information presentation.
- Enhanced documentation to reflect the latest testing baseline with 804 passed tests, indicating improved stability and functionality across the application.
This update significantly enhances the user experience by providing clearer insights into query processing and results.
- Introduced `battery_report.json` for local data analysis, excluding it from the database.
- Enhanced `AGENTS.md` to reflect updated test baseline with 795 passed tests.
- Added new metrics for trade flow in `dict_service.py`, improving transaction data analysis.
- Updated regex patterns in `guardrail.py` to better handle numeric extraction and prevent misinterpretation of tokens.
- Expanded course modules with new content on FR-8/9/10 capabilities and L3 role management.
- Improved concurrency handling in transaction processing to ensure accurate alert generation.
This update enhances data analysis capabilities and improves the overall structure and clarity of course materials.
- 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.
- Added a new visitor chat API endpoint (`/api/chat/visitor`) to allow unauthenticated users to engage in conversations without requiring customer data.
- Introduced a visitor context dependency to manage visitor interactions seamlessly.
- Enhanced the chat API to support explicit session termination and improved response handling for customer service interactions.
- Updated the database configuration to include Redis client support for caching visitor data.
- Added a new customer note repository to persist user notes independently of the L1 profile slots.
This update significantly improves the customer service experience by enabling visitor interactions and ensuring efficient data handling for both registered and unregistered users.
- Established the P0 scaffolding for the frontend, including login, layout, and routing for four roles.
- Integrated the Customer Wealth Dashboard, Advisor Clients Dashboard, Analyst Market Dashboard, and Risk Alerts Dashboard.
- Updated the API client to support fetching customer and product data, enhancing the overall functionality of the dashboard.
- Added error handling components to improve user experience during data fetching.
- Enhanced charting capabilities using Ant Design Charts for better data visualization.
This update lays the groundwork for further development of the frontend application, ensuring a robust structure for future features and integrations.
- 新增《接口契约-代销平台API-v0.1.md》，定义代销平台 REST API 的路由风格、命名规范及端点清单。
- 更新 AGENTS.md，包含代销平台 API 契约的路径信息。
- 修改 ITERATION.md 和 MEMORY.md，反映代销平台 API 的实施进度及相关文档的状态。
- 更新 TODO.md，明确代销平台 API 的实现优先级。
此更新为代销平台 API 的开发提供了清晰的指导，确保各模块间的接口一致性与可维护性。
- Introduced `MYSQL_CORE_DATABASE` in `.env.example` and `settings.py` for core database configuration.
- Added `CoreReadOnlyRepository` for read-only access to the `jinrong_core` database.
- Updated `AGENTS.md`, `README.md`, and various documentation files to reflect new agent onboarding processes and project structure.
- Revised requirements in `requirements.txt` to include `langgraph` and `langchain-core`.
- Enhanced `FLOW.md` with local bootstrap instructions for setting up the core simulation environment.
- Added new scripts for database creation and seeding for the core simulation library.
- Improved overall documentation for clarity on project architecture and memory management.
- Updated `TODO.md` to reflect current development priorities and tasks.
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