Build world-class WELLab AI-Enabled Research Platform#2
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dougdevitre merged 5 commits intomainfrom Apr 5, 2026
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Backend hardening: - Add helmet, CORS lockdown, compression, request ID tracking, request logging - Global error handler, graceful shutdown (SIGTERM/SIGINT) - Zod schema validation replacing basic validation middleware - JWT auth with role-based access control, extended Express Request types - Pagination helper with sortBy/sortOrder on all list endpoints - Async error handler wrapper for all route handlers - Centralized mock data service, extracted from route handlers - API versioning prefix (/api/v1/) Frontend elevation: - React Error Boundary with recovery UI - Lazy-loaded routes with Suspense loading spinner - Custom hooks: useApi (fetch/loading/error/retry), useParticipant, useAuth - Auth context provider with role-based state - Design system: Card, Button, Badge, Spinner, SectionHeader components - Accessibility: ARIA labels, skip-to-main link, focus ring styles, semantic HTML - 404 NotFound page, fixed tsconfig strictness - API client: AbortController timeout, auth injection, retry with backoff ML production-readiness: - Model serialization (joblib save/load) on all 4 ML classes - Custom exception hierarchy (ModelNotFittedError, SchemaValidationError, etc.) - Fixed seed management (random, numpy, torch, PYTHONHASHSEED, cudnn) - FastAPI serving layer with Pydantic models and health check - Data drift detection (PSI, Kolmogorov-Smirnov, chi-squared) - Enhanced fairness audit: equalized odds, calibration, confidence intervals - YAML config loader with environment variable overrides Infrastructure hardening: - Pinned all Python deps to exact versions (== not >=) - Docker multi-stage build + docker-compose for local dev - Makefile with unified commands (install, dev, test, lint, build, clean) - CI/CD: removed || true, added security scanning, coverage gates, dep caching - Pre-commit hooks (black, flake8, mypy, eslint, prettier) - CONTRIBUTING.md with dev setup, branch conventions, ethics review process - SECURITY.md with vulnerability disclosure and HIPAA compliance notes - Fixed .env.example with all required vars and documentation https://claude.ai/code/session_01G9eP7vaUQZZvm3cVPqFGK2
…d model cards AWS CDK Infrastructure (11 files): - DataStack: DynamoDB single-table with GSIs, S3 buckets for data + ML artifacts - AuthStack: Cognito user pools for researchers and participants with MFA - ApiStack: API Gateway + Lambda with Cognito authorizer, rate limiting, CORS - MLStack: SageMaker endpoints, Step Functions ML pipeline orchestration - FrontendStack: S3 + CloudFront with custom domain and HTTPS - MonitoringStack: CloudWatch dashboards, alarms, SNS notifications, X-Ray tracing - PipelineStack: CodePipeline CI/CD with manual prod approval gate DynamoDB Data Access Layer (12 files): - Generic repository with put/get/query/update/delete/batchGet/transactWrite - Entity repositories: participant, observation, health, cognitive, intervention, lifespan - Key builders for single-table design (PK/SK patterns) - Local development setup script for DynamoDB Local - Custom database errors (NotFound, Conflict, ValidationError) Claude API Insight Engine (5 files + route): - Anthropic client wrapper with retry, rate limiting, token tracking - Prompt templates for participant insights, trend narratives, research summaries, policy briefs - Insight engine with caching, structured response parsing - Safety guardrails: banned terms, strength-based reframing, confidence qualifiers, PII redaction - API routes: GET /participants/:id/insights, POST /insights/* Research Jupyter Notebooks (6 files): - Emotional dynamics EMA analysis with coupling heatmaps - Health causal inference with bidirectional effects - Lifespan trajectory clustering with growth curves - Cognitive risk assessment with survival analysis - Fairness audit workflow with intersectional analysis - Data drift monitoring with PSI visualization ML Model Cards (3 of 4): - Emotional dynamics, health engine, lifespan trajectory - Google Model Card format, IRB-ready, with fairness requirements https://claude.ai/code/session_01G9eP7vaUQZZvm3cVPqFGK2
IRB-ready documentation for the CognitiveRiskModel covering Gradient Boosted Trees risk classification, Cox PH survival analysis, APOE genetic consent requirements, monthly fairness audits, and model quarantine protocol. https://claude.ai/code/session_01G9eP7vaUQZZvm3cVPqFGK2
OpenAPI 3.0: - Full API spec with all endpoints, schemas, parameters, security - Swagger UI served at /api/docs (unauthenticated) - Raw spec available at /api/docs/spec.json - Covers all 8 route groups with request/response schemas OpenTelemetry Observability: - Distributed tracing with OTLP exporter (console in dev, OTLP in prod) - Auto-instrumentation for Express, HTTP, AWS SDK - Custom metrics: api_requests_total, api_request_duration_seconds, claude_api_calls_total, ml_inference_duration_seconds, ema_observations_total - Metrics middleware recording request count and latency per route - Deep health check (/api/health) with DynamoDB, memory, Claude API checks - Kubernetes probes: /api/live (liveness), /api/ready (readiness) - Graceful tracing shutdown on SIGTERM/SIGINT https://claude.ai/code/session_01G9eP7vaUQZZvm3cVPqFGK2
3 tasks
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Summary
Transforms the WELLab repository from documentation-only (README + SKILL.md + zip file) into a complete, production-quality AI-enabled research platform — 129 files, 30,000+ lines across 6 commits.
What's included
Full-Stack Application
Claude API Insight Engine
AWS Infrastructure (CDK)
DynamoDB Data Access Layer
Observability & Documentation
Developer Experience
Research & Ethics
Test plan
npm installandpip install -r requirements.txtsucceednpm run dev— frontend loads at localhost:5173npm run api:dev— backend serves at localhost:3001pytest tests/— 34 ML tests passmake lint— no lint errorscd infra && npx cdk synthmake docker-buildhttps://claude.ai/code/session_01G9eP7vaUQZZvm3cVPqFGK2