- Merged the `integrate/advisor-agent` branch into the `merger`, enhancing the advisor agent's capabilities with compliance, KYC, and script templates.
- Updated the testing baseline to reflect 926 passed tests, with 65 failures concentrated in the advisor agent's `test_sprint*` cases.
- Introduced new migration scripts for advisor-related database structures, ensuring smooth integration and data management.
- Enhanced documentation to include the new API structure and integration details, providing clarity for future development.
This update significantly advances the advisor agent's functionality while maintaining a structured approach to integration and testing.
- Merged `xinghuo/advisor-agent` into the `merger` branch, establishing a new API prefix `/api/advisor-agent` to avoid conflicts with existing endpoints.
- Implemented a comprehensive implementation plan detailing the integration steps, including conflict resolution, database migrations, and service adaptations.
- Introduced new files for advisor compliance, script templates, KYC, and market alerts, ensuring a cohesive addition to the existing architecture.
- Updated documentation to reflect the new structure and integration process, enhancing clarity for future development and maintenance.
This integration significantly expands the capabilities of the merger, providing a robust framework for advisor-related functionalities while maintaining compliance and operational integrity.
- Added `list_nav_history` method in `CoreReadOnlyRepository` to retrieve historical NAV data for products over a specified number of days.
- Introduced `get_nav_history` endpoint in `product_service` to return historical NAV sequences, improving product data accessibility.
- Updated `products.py` to include new API endpoint for fetching NAV history, ensuring compliance with access control.
- Enhanced `ready.py` to include a health check for the new functionality, ensuring system readiness.
- Updated documentation to reflect the new testing baseline of 833 passed tests, indicating improved stability and functionality across the application.
This update significantly enhances the product API by providing access to historical NAV data, improving user insights into product performance.
- 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 `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.
- Updated the `dashboard` function in `analyst.py` to include additional metrics for different user roles, improving data visibility for analysts, customers, advisors, and risk officers.
- Introduced a new `prepare_customer_stream` function in `customer_service.py` to facilitate streaming responses for customer interactions, enhancing the chat experience.
- Added new API endpoints in `analyst.ts` for fetching dashboard metrics and managing analyst assets, streamlining data handling and user interactions.
- Updated frontend components to support new dashboard features and asset management, ensuring a cohesive user experience across the application.
This update significantly improves the functionality and usability of the analyst and customer service features, providing users with enhanced tools for data analysis and interaction.
- Introduced `analyst_auth_adapter.py` for managing authentication context and access control for the data analysis agent.
- Added new API endpoints in `analyst.py` for chat, dashboard, asset management, and metrics, utilizing the new authentication context.
- Created Pydantic models in `analyst_schemas.py` for request and response structures, ensuring consistent data handling.
- Updated SQL guard logic in `sql_guard.py` to enforce access restrictions based on user roles and contexts.
- Implemented migration scripts for new database tables related to the data analysis agent, enhancing data management capabilities.
- Removed legacy authentication code from `auth.py`, streamlining the authentication process.
This update significantly enhances the data analysis capabilities, providing a robust framework for querying and managing data securely.
- Added new configuration for knowledge base root directory in `.env.example` and `settings.py`.
- Implemented `find_products` method in `CoreReadOnlyRepository` for fuzzy product search based on user queries.
- Introduced `search_cs_knowledge` function in `rag_service.py` to facilitate semantic search across new `fin_*` collections.
- Updated document parsing to support Markdown and YAML front-matter for knowledge base entries.
- Created multiple new FAQ and policy documents in the `data/kb_collections` directory to enrich the knowledge base.
This update significantly improves the knowledge retrieval capabilities for customer service interactions, ensuring more relevant and accurate responses.
- 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.
- Enhanced AGENTS.md to include new draft specifications for market data in Phase B.
- Updated MEMORY.md with details on the C-05 market data source selection and the new API contract for v0.2.
- Introduced a new document for frontend P0 design specifications, outlining the architecture and features for the initial web application.
- Added a new document for C-05 market data source comparison, detailing the requirements and options for future data integration.
- Updated existing API contracts to reflect the latest changes and ensure consistency across documentation.
This update improves the clarity and comprehensiveness of the API documentation, supporting ongoing development efforts and future 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。
- Implemented `check_suitability` method in `CoreReadOnlyRepository` for suitability determination based on customer and product risk levels.
- Added `build_suitability_log_row` function in `suitability.py` for mapping suitability check results to `risk_suitability_log`.
- Updated `AGENTS.md`, `ENVIRONMENT.md`, and `FLOW.md` to reflect changes in suitability assessment processes and documentation.
- Revised `FRAMEWORK.md` and `MEMORY.md` to clarify project structure and data flow related to suitability checks.
- Expanded `TODO.md` with tasks related to logging and auditing suitability assessments.
- 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.
zhanghongyu_0626
仝勋敏
GaoYiYuan_0626