- 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.
- Replaced `get_auth_context` with `get_platform_auth_context` in `analyst.py` to enhance authentication handling.
- Added a new smoke test script `smoke_analyst.py` for testing the data analysis agent with both fake and live LLM configurations.
- Updated TODO documentation to reflect the completion of Scope B smoke tests, ensuring clarity on testing status.
This update improves the authentication mechanism and introduces a comprehensive testing approach for the data analysis agent.
- 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.
- Changed Redis port mapping in `docker-compose.yml` from `6379:6379` to `6380:6379` to avoid conflicts with Windows Redis.
- Updated `.env.example` to reflect the new Redis URL (`redis://127.0.0.1:6380/0`), ensuring proper configuration for Docker users.
- Enhanced Redis client initialization in `database.py` and `redis_gateway.py` to utilize a new `_redis_kwargs` function for improved compatibility with Windows Redis 3.x and Docker Redis 7.
- Added a new PowerShell script `start-redis.ps1` to facilitate starting Redis in Docker, providing a seamless setup experience for developers.
This update significantly improves the Redis integration, ensuring a smoother development process and better compatibility across environments.
- Introduced new chat components including `ChatPanel` and `VisitorChatWidget` to facilitate real-time conversations for customers and visitors.
- Developed a robust chat API with endpoints for synchronous and streaming interactions, enhancing user engagement.
- Added new pages for customer interactions, including `CustomerChatPage`, `CustomerProfilePage`, `CustomerHoldingsPage`, and `CustomerTradesPage`, integrating chat capabilities seamlessly.
- Enhanced the advisor experience with the `AdvisorCustomersPage` and `RiskAlertsPage`, allowing for efficient management of customer interactions and risk alerts.
- Updated routing and state management to support new chat functionalities, ensuring a cohesive user experience across the application.
This update significantly improves the chat capabilities within the application, providing users with enhanced tools for communication and support.
- 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.
- 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.
Sync the interactive codebase-to-course skill into .cursor/skills so teammates get it from the repo clone.
Co-authored-by: Cursor <cursoragent@cursor.com>
- Introduced a new function `_assistant_content_for_persist` to append disclaimers to assistant responses, ensuring consistency in stored content.
- Updated `chat_api` and `chat_stream_api` to utilize the new function for managing assistant replies, improving data integrity.
- Added tests to verify the correct handling of disclaimers in various scenarios, ensuring compliance with expected output.
This update enhances the chat system's reliability by ensuring that disclaimers are consistently applied to assistant responses, improving user experience and data accuracy.
- 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.
- Modified `chat_stream_api` to use `new_trace()` instead of an empty string for `trace_id`, enhancing traceability.
- Added tests to verify the correct generation and propagation of `trace_id` in responses, ensuring no empty trace IDs are sent to clients.
This update improves the tracking of chat sessions and ensures compliance with traceability standards.
- 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。
- Updated the login endpoint to utilize shared JWT issuer/audience settings, improving consistency across modules.
- Introduced error handling for unknown accounts during token issuance, raising an UnauthorizedError when necessary.
- Enhanced traceability by adding trace and request IDs to responses, ensuring better tracking of requests.
- Refactored exception handling in middleware to properly bubble up application-specific errors, preventing them from being swallowed.
- Added new utility functions for generating trace headers to improve debugging capabilities.
This update strengthens the authentication process and enhances error visibility, contributing to a more robust and maintainable codebase.
- Changed section title from "三份交付物" to "交付物" for clarity.
- Added a new document entry for "04-从需求到公共API开发方法.md" detailing the development methodology from requirements to API.
- Enhanced the explanation of the relationships between documents to better illustrate their interconnections and usage contexts.
- Introduced three key documents:
- **01-每日会议纪要模板与流程.md**: A template for daily meeting minutes and processes.
- **02-项目开发计划.md**: A project-level development plan outlining the project timeline, team roles, and dependencies.
- **03-表设计文档.md**: A readable table design document serving as a dictionary for understanding database structures and relationships.
- Created a README.md to index project management documents and their purposes.
- Enhanced documentation to support a 5-person full-stack novice team in project execution and collaboration.
- Added `auth.py` for mock login and JWT issuance.
- Introduced `chat.py` for handling chat requests with role-based access control.
- Enhanced `main.py` to include new routers and middleware for tracing.
- Implemented input validation in `input_guard.py` to prevent SQL injection.
- Created repositories for managing agent sessions and audit logs.
- Added exception handling for authorization errors.
- Updated settings to include JWT configuration.
- Introduced tests for authentication and input validation.
- Enhanced `ENVIRONMENT.md` with a new section on platform positioning and industry context, detailing the project's role as a comprehensive wealth management institution.
- Updated the service roles table to include insights from the four-role industry research.
- Added new files for "平台与行业背景" and "四角色行业调研" to provide detailed context and operational insights for the project's agents.
- Revised `ITERATION.md` to reflect the addition of these new documents and their relevance to user requirements.
- 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
