SignalFlow — AI-Powered Behavioral Messaging Platform#1
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Core scaffolding for the AI-powered behavioral messaging platform: - Domain models: signals, messages, channels, campaigns - Service stubs: signal ingestion with campaign matching, AI message generation - Channel registry with adapter pattern (SMS, email, WhatsApp, Instagram DM) - Express API with versioned signal ingestion endpoint (POST /api/v1/signals) - Validated environment config (Zod), structured logging (Pino) - TypeScript strict mode, ESM-ready project configuration https://claude.ai/code/session_01Pw8qob1AFnxZZu3qNHTsK6
- In-memory data store for signals, campaigns, and messages - Pipeline orchestrator: signal → campaign match → message generation → delivery - Campaign CRUD routes (POST, GET, PUT /api/v1/campaigns) - Message read routes (GET /api/v1/messages with filters) - Trigger rule evaluation (signalType + payload conditions matching) - API key authentication middleware (skips in dev when unconfigured) - Global error handling middleware with async route wrapper https://claude.ai/code/session_01Pw8qob1AFnxZZu3qNHTsK6
- 19 tests (unit + integration) via Vitest with supertest — all passing - Per-shopper rate limiting (sliding window, configurable max/window) - Campaign analytics tracking (signals, messages, delivery success/failure) - GET /api/v1/campaigns/:id/analytics endpoint - Request ID middleware for traceability (X-Request-Id header) - Extracted createApp() factory for testability https://claude.ai/code/session_01Pw8qob1AFnxZZu3qNHTsK6
- Web dashboard served at / with campaign overview and live signal feed - Campaign detail page with analytics bar charts and message history - Server-Sent Events (SSE) at /api/v1/signals/stream for real-time updates - EventBus service decoupling pipeline from SSE transport - GET /api/v1/shoppers/:id for shopper profile aggregation - Dark-themed responsive UI (HTML/CSS/JS, no build tooling) https://claude.ai/code/session_01Pw8qob1AFnxZZu3qNHTsK6
- Fix TypeScript build errors (ESM types, Express 5 param types) - Add Dockerfile with multi-stage build - Add render.yaml for one-click Render deploy - Add "type": "module" and engines field to package.json - Exclude test files from tsc build https://claude.ai/code/session_01Pw8qob1AFnxZZu3qNHTsK6
pino-pretty was a devDependency but needed at runtime when NODE_ENV is not explicitly set to production. Moved to dependencies to fix Render deployment error. https://claude.ai/code/session_01Pw8qob1AFnxZZu3qNHTsK6
- Extract IStore interface from MemoryStore (15 async methods) - Create PrismaStore implementing IStore via Neon HTTP adapter - Prisma schema with Signal, Campaign, Message tables + indexes - All consumers now depend on IStore, not MemoryStore directly - Server auto-selects PrismaStore when DATABASE_URL is set, falls back to MemoryStore - Seed script with 5 campaigns, 25 signals, ~40 messages (idempotent) - All 19 existing tests pass unchanged (they use MemoryStore) - Build command updated for Render: includes prisma generate https://claude.ai/code/session_01Pw8qob1AFnxZZu3qNHTsK6
Ensures database tables are created/synced on every Render deploy. https://claude.ai/code/session_01Pw8qob1AFnxZZu3qNHTsK6
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Summary
Complete implementation of SignalFlow — an AI-powered behavioral messaging platform for D2C brands.
Phase 1 — Foundation
Phase 2 — Full Pipeline
Phase 3 — Production Readiness
Phase 4 — Web Dashboard & Real-time
/with campaign overviewAPI Endpoints
/health/api/v1/signals/api/v1/signals/stream/api/v1/campaigns/api/v1/campaigns/api/v1/campaigns/:id/api/v1/campaigns/:id/analytics/api/v1/messages/api/v1/shoppers/:idTest plan
npm test— 19 tests passingnpm run build— TypeScript compiles cleanly🤖 Generated with Claude Code
https://claude.ai/code/session_01Pw8qob1AFnxZZu3qNHTsK6
Generated by Claude Code