- 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
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.
