The Backend includes the findings_generator.py service which analyzes query results and generates findings. findings_generator.py realizes the Full Findings Visualization Layer capability by producing structured Finding objects including metrics, trends, and outliers. The question_router.py module depends on the FindingsGenerator to generate findings from query results. FindingsGenerator includes findings in the API response for all structured queries. The findings_generator.py service implements the Full Findings Visualization Layer by analyzing query results and generating structured findings.

Progress plan for findings visualization components; includes feature set, design, and integration status.

IronClaw Agent uses FindingsGenerator to generate findings from query results including handling PostgreSQL Decimal types. FindingsGenerator requires support for PostgreSQL Decimal type to correctly process numeric data in findings. FindingsGenerator uses Finding to represent individual analytical findings generated from query results. question_router.py uses FindingsGenerator to generate findings from query results FindingsGenerator results are included in the API response Logging will be added to findings_generator at the start of generate_findings to monitor numeric columns detection and diagnose failure points. Finding is a data structure created and managed by FindingsGenerator during analytical finding generation.

The Frontend Components include the FindingsPanelNew.svelte UI component which serves as a master panel with filtering capabilities for findings. Frontend Integration uses the FindingsPanelNew component to display findings in the agent page. The agentStore.findings data is connected to the FindingsPanelNew component for frontend rendering. The FindingsPanelNew.svelte UI component is part of the Full Findings Visualization Layer serving as a master panel with filtering capabilities. The FindingsPanelNew.svelte UI component is part of the Full Findings Visualization Layer serving as a master panel with filtering capabilities. FindingsPanelNew replaces FindingsBoard in the agent page user interface

The Firewall configuration was updated to open port 6333 to allow the Backend server (theo) to access the Qdrant database on elin.

IronClaw Agent Feature uses the document FIX_AGENT_MIGRATION.md as quick fix guidance for database migration during deployment.

Docling was used to extract 30 tables including from the FL 2022-2028 budget file within the SVGV Budget Analysis Project.

The project dashboard contains a folder-grouped file inventory with tier badges and filtering capabilities.

DataLens's frontend, built with SvelteKit, Tailwind, and shadcn-svelte, offers a user interface including login and project pages. It uses a multi-stage Docker build, integrates with backend APIs, supports Danish language, and is deployed containerized alongside PostgreSQL on theo via Coolify. The frontend ensures end-to-end functionality validation before claiming completion. Frontend service is deployed with Docker Compose orchestration.

The Docker deployment environment contains the Frontend, Backend, PostgreSQL, and Redis services.

The frontend /ask-stream switch uses the backend /ask-stream endpoint to enable streaming query responses and prevent client timeout errors. The frontend /ask-stream switch is implemented in the SvelteKit Framework to provide streaming UI experience and progress states.

The Frontend Components include the MetricCard.svelte UI component for KPI display with stats. The Frontend Components include the TrendChart.svelte UI component which renders SVG line charts with grid. The Frontend Components include the OutlierHighlight.svelte UI component for displaying anomaly detection information. The Frontend Components include the FindingsPanelNew.svelte UI component which serves as a master panel with filtering capabilities for findings. The UI Flow is implemented using Frontend components such as DiscoveryFlow, DiscoveryLoading, ConsolidationReview, and ConsolidationCard. The Data Discovery Feature includes Frontend components implementing DiscoveryFlow, DiscoveryLoading, ConsolidationReview, and ConsolidationCard UI components. The Data Discovery Feature includes frontend components consisting of 4 Svelte UI components with beautiful user experience.

The Frontend DiscoveryFlow component is part of the UI Flow for the Data Discovery feature.

Fixed frontend API call to `/api/v1/projects/{project_id}/files` endpoint to correctly display AI summaries in the project dashboard.

The Frontend UI Translation use case involves modifying Frontend files to implement i18n.

Frontend Integration uses the FindingsPanelNew component to display findings in the agent page. The Multilingual Support (Danish) epic includes the Frontend UI Translation use case. The Frontend UI Translation use case uses SvelteKit i18n plugin to provide UI translations. The Frontend UI Translation use case involves modifying Frontend files to implement i18n. The Frontend UI Translation use case includes providing a language selector on the Login page. The Frontend UI Translation use case includes a language selector on the Projects page.

The message streaming format is used by the frontend rendering to display agent messages and findings.

The frontend service uses the Backend API endpoint, configured via the PUBLIC_API_URL environment variable, to communicate with the backend.

Frontend tests test-agent-e2e.spec.ts are included in the Playwright E2E test suite to validate the IronClaw agent feature. Frontend tests validate the Discovery feature's user interface and experience.

The Data Discovery system uses Frontend UI components including DiscoveryFlow.svelte, DiscoveryLoading.svelte, ConsolidationReview.svelte, and ConsolidationCard.svelte for user interaction. The Data Discovery Feature uses Frontend UI components including 4 Svelte components with modern UX. The DiscoveryFlow page uses Frontend UI components as part of the Data Discovery user experience. The Data Discovery System uses Frontend UI components to provide an intuitive user interface with visual join paths and animations. The Frontend catalog dashboard is a planned component that will be built to interact with the DataLens Platform backend. The frontend UI for Data Discovery is validated by the comprehensive E2E test suite.