Major architectural shift from Next.js to a lightweight Vite + React SPA model ("Puppet Architecture") to better support real-time workflow visualization and strict type safety.
Key Changes:
1. **Architecture & Build**:
- Initialized Vite + React + TypeScript project.
- Configured Tailwind CSS v4 and Shadcn UI.
- Archived legacy Next.js frontend to 'frontend/archive/v2_nextjs'.
2. **Core Features**:
- **Dashboard**: Implemented startup page with Symbol, Market, and Template selection.
- **Report Page**:
- **Workflow Visualization**: Integrated ReactFlow to show dynamic DAG of analysis tasks.
- **Real-time Status**: Implemented Mock SSE logic to simulate task progress, logs, and status changes.
- **Multi-Tab Interface**: Dynamic tabs for 'Overview', 'Fundamental Data', and analysis modules.
- **Streaming Markdown**: Enabled typewriter-style streaming rendering for analysis reports using 'react-markdown'.
- **Config Page**: Implemented settings for AI Providers, Data Sources, and Templates using TanStack Query.
3. **Documentation**:
- Created v2.0 User Guide ('docs/1_requirements/20251122_[Active]_user-guide_v2.md').
- Implemented 'DocsPage' in frontend to render the user guide directly within the app.
4. **Backend Alignment**:
- Created 'docs/frontend/backend_todos.md' outlining necessary backend adaptations (OpenAPI, Progress tracking).
This commit establishes the full frontend 'shell' ready for backend integration.
- Fix `simple_test_analysis` template in E2E test setup to align with Orchestrator's data fetch logic.
- Implement and verify additional E2E scenarios:
- Scenario C: Partial Provider Failure (verified error propagation fix in Orchestrator).
- Scenario D: Invalid Symbol input.
- Scenario E: Analysis Module failure.
- Update `WorkflowStateMachine::handle_report_failed` to correctly scope error broadcasting to the specific task instead of failing effectively silently or broadly.
- Update testing strategy documentation to reflect completed Phase 4 testing.
- Skip Scenario B (Orchestrator Restart) as persistence is not yet implemented (decision made to defer persistence).
- Enhance LlmClient to handle malformed URLs and HTML error responses
- Improve logging in report-generator-service worker
- Update frontend API routes and hooks for analysis
- Update various service configurations and persistence logic
- Backend: Add template_id to DataRequest and AnalysisResult metadata
- Frontend: Add TemplateSelector to Report page
- Frontend: Refactor ReportPage to use AnalysisTemplateSets for dynamic tabs
- Frontend: Strict mode for report rendering based on template_id
- Cleanup: Remove legacy analysis config hooks
This commit introduces a comprehensive, template-based analysis orchestration system, refactoring the entire analysis generation workflow from the ground up.
Key Changes:
1. **Backend Architecture (`report-generator-service`):**
* Replaced the naive analysis workflow with a robust orchestrator based on a Directed Acyclic Graph (DAG) of module dependencies.
* Implemented a full topological sort (`petgraph`) to determine the correct execution order and detect circular dependencies.
2. **Data Models (`common-contracts`, `data-persistence-service`):**
* Introduced the concept of `AnalysisTemplateSets` to allow for multiple, independent, and configurable analysis workflows.
* Created a new `analysis_results` table to persist the output of each module for every analysis run, ensuring traceability.
* Implemented a file-free data seeding mechanism to populate default analysis templates on service startup.
3. **API Layer (`api-gateway`):**
* Added a new asynchronous endpoint (`POST /analysis-requests/{symbol}`) to trigger analysis workflows via NATS messages.
* Updated all configuration endpoints to support the new `AnalysisTemplateSets` model.
4. **Frontend UI (`/config`, `/query`):**
* Completely refactored the "Analysis Config" page into a two-level management UI for "Template Sets" and the "Modules" within them, supporting full CRUD operations.
* Updated the "Query" page to allow users to select which analysis template to use when generating a report.
This new architecture provides a powerful, flexible, and robust foundation for all future development of our intelligent analysis capabilities.
- Fix Dockerfile stub builds; compile full sources (no empty binaries)
- Add ca-certificates and curl in runtime images for TLS/healthchecks
- Enable RUST_LOG and RUST_BACKTRACE for all providers
- Add HTTP /health healthchecks in docker-compose for ports 8000-8004
- Standardize Tushare /health to structured HealthStatus JSON
- Enforce strict config validation (FINNHUB_API_KEY, TUSHARE_API_TOKEN)
- Map provider API keys via .env in docker-compose
- Log provider_services at API Gateway startup for diagnostics
Outcome: provider containers no longer exit silently; missing keys fail fast with explicit errors; health and logs are consistent across modules.
