| export const systemBrief = { |
| title: "Manufacturing Monitoring System", |
| goal: |
| "A real-time industrial monitoring platform for steel quality inspection with ROI localization, defect segmentation, automated reporting, database logging, and WebSocket-driven live operations.", |
| architectureFlow: [ |
| { |
| title: "Camera and Image Intake", |
| detail: "Collect uploaded inspection images or live browser camera frames from the shop floor.", |
| }, |
| { |
| title: "Steel ROI and Defect Engine", |
| detail: "Localize the steel inspection region first, then run defect segmentation only inside that ROI to reduce false positives.", |
| }, |
| { |
| title: "Inspection Formatter", |
| detail: "Normalize decisions, recommendations, defect summaries, and annotated preview output.", |
| }, |
| { |
| title: "Operational Data Layer", |
| detail: "Store JSON reports locally and persist inspection records to PostgreSQL when configured.", |
| }, |
| { |
| title: "FastAPI Control Layer", |
| detail: "Expose REST endpoints for reports, analytics, uploads, camera frames, and system health.", |
| }, |
| { |
| title: "WebSocket Event Stream", |
| detail: "Broadcast inspection snapshots and live updates to all connected operator dashboards.", |
| }, |
| { |
| title: "React Monitoring Console", |
| detail: "Present live status, history, analytics, and camera-based inspection in a clean UI.", |
| }, |
| ], |
| backend: { |
| responsibilities: [ |
| "Serve inspection data through REST endpoints.", |
| "Push real-time updates through WebSocket connections.", |
| "Connect to PostgreSQL through Supabase or fall back to local report storage.", |
| ], |
| files: [ |
| { |
| title: "api/main.py", |
| detail: "FastAPI app, REST endpoints, and /ws WebSocket entry point.", |
| }, |
| { |
| title: "core/database.py", |
| detail: "Safe database access layer with optional runtime fallback.", |
| }, |
| { |
| title: "core/config.py", |
| detail: "Environment-backed application settings and path configuration.", |
| }, |
| { |
| title: "core/logger.py", |
| detail: "Structured logging for debugging and operational tracing.", |
| }, |
| ], |
| }, |
| aiPipeline: { |
| files: [ |
| { |
| title: "live_camera.py", |
| detail: "Simulated camera loop for offline inspection playback with the trained model.", |
| }, |
| { |
| title: "inspection/service.py", |
| detail: "Unified runtime service for upload inspection, camera-frame inference, and preview overlays.", |
| }, |
| { |
| title: "inspection/output_formatter.py", |
| detail: "Formats defect data, writes reports, stores records, and triggers live broadcasts.", |
| }, |
| ], |
| flow: [ |
| { |
| title: "Capture", |
| detail: "Acquire a shop-floor image from upload, live camera, or the simulation loop.", |
| }, |
| { |
| title: "Validate Surface", |
| detail: "Localize the steel ROI or reject the frame before segmentation so faces, tools, and background objects do not enter the defect pipeline.", |
| }, |
| { |
| title: "Infer", |
| detail: "Run segmentation only inside the approved steel ROI and extract contours, defect boxes, severity, and geometry.", |
| }, |
| { |
| title: "Decide", |
| detail: "Generate PASS, REVIEW, or FAIL decisions with operational recommendations.", |
| }, |
| { |
| title: "Persist", |
| detail: "Save reports locally and write to PostgreSQL when a database is configured.", |
| }, |
| { |
| title: "Broadcast", |
| detail: "Stream the inspection event to dashboards through WebSocket updates.", |
| }, |
| ], |
| }, |
| database: { |
| table: "inspections", |
| columns: [ |
| "id", |
| "timestamp", |
| "total_defects", |
| "minor", |
| "moderate", |
| "critical", |
| "decision", |
| "raw_data (JSON)", |
| ], |
| }, |
| frontend: { |
| structure: [ |
| "src/components/Sidebar.jsx", |
| "src/pages/Dashboard.jsx", |
| "src/pages/History.jsx", |
| "src/pages/Live.jsx", |
| "src/pages/Analytics.jsx", |
| "src/App.jsx", |
| ], |
| routing: [ |
| "/ -> Dashboard", |
| "/history -> Inspection logs", |
| "/live -> Live monitoring", |
| "/analytics -> Charts and insights", |
| ], |
| features: [ |
| "Dashboard -> live status, defect counts, active alerts, and WebSocket updates.", |
| "History -> searchable inspection logs with report detail selection.", |
| "Live -> upload detection and browser camera inspection with annotated output.", |
| "Analytics -> Recharts-based trends, defect mix, and source usage.", |
| ], |
| }, |
| realtime: { |
| flow: [ |
| "New inspection captured", |
| "Inspection formatted", |
| "Local and DB storage written", |
| "WebSocket event broadcast", |
| "Dashboard, history, and analytics refresh", |
| ], |
| }, |
| currentState: { |
| working: [ |
| "AI detection pipeline", |
| "Steel ROI gate before defect segmentation", |
| "Local report persistence", |
| "REST API", |
| "Frontend routing", |
| "Dashboard UI", |
| "WebSocket live updates", |
| "Upload and camera inspection endpoints", |
| ], |
| inProgress: [ |
| "Detector model training with larger curated steel data", |
| "Cloud LLM API key configuration per deployment", |
| ], |
| }, |
| improvements: { |
| backend: [ |
| "Async-safe WebSocket broadcasting.", |
| "Dropped-connection handling.", |
| "Graceful database fallback.", |
| ], |
| frontend: [ |
| "Organized industrial dashboard layout.", |
| "Clear loading and empty states.", |
| "Live connection feedback and camera workflow polish.", |
| ], |
| realtime: [ |
| "WebSocket-first streaming.", |
| "Heartbeat and reconnect handling.", |
| "Inspection preview return for live camera frames.", |
| ], |
| features: [ |
| "Live monitoring with upload and camera options.", |
| "Steel ROI localization before segmentation.", |
| "Analytics with inspection trends.", |
| "Alerts with visual and audio cues.", |
| ], |
| }, |
| finalSummary: |
| "This is a full-stack manufacturing monitoring system that localizes the steel inspection region, detects surface defects in real time, stores inspection data, and visualizes live operations through a responsive dashboard.", |
| } |
|
|
