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Backend API Core: OpenAI Integration, Rewards System & Analytics (#2)
* Implement Backend API Core with Authentication for CivicPulse This commit implements the complete backend API infrastructure for the CivicPulse hackathon project, including: Features implemented: - Fastify server with JWT authentication - User registration and login endpoints - Protected route middleware - User profile management (GET, PATCH) - Health check endpoint with database connectivity test - Prisma ORM integration with PostgreSQL Technical stack: - Node.js + TypeScript - Fastify web framework - Prisma ORM - bcryptjs for password hashing - JWT for authentication - CORS enabled for frontend integration Authentication flow: - POST /api/auth/register - Create new user with hashed password - POST /api/auth/login - Authenticate and receive JWT token - GET /api/auth/me - Get current user (requires authentication) - JWT tokens valid for 7 days User management: - GET /api/users/:id - Get any user's public profile - PATCH /api/users/:id - Update own profile (authenticated) - Authorization checks prevent cross-user updates Testing: - Comprehensive integration test suite (10 tests, all passing) - Tests cover: registration, login, authentication, authorization, profile updates - Health check verifies database connectivity Integration ready: - CORS configured for localhost:5173, localhost:5174 - Environment variables documented in .env.example - Prisma schema shared with database worktree - All endpoints tested and functional 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * Add comprehensive backend API documentation * Add all remaining backend API endpoints with AWS integration Implemented complete REST API for CivicPulse platform: Issues Endpoints: - GET /api/issues - List with filters (status, priority, category) - GET /api/issues/:id - Get single issue - POST /api/issues - Create with photo upload to S3 - PATCH /api/issues/:id/status - Update status - Integrated AWS Bedrock AI for automatic categorization Activities Endpoints: - GET /api/activities - List with filters - POST /api/activities - Log activity with carbon calculations - GET /api/activities/user/:id - User activity history - Automatic points calculation (10 pts per kg CO2) Challenges Endpoints: - GET /api/challenges - All challenges - GET /api/challenges/active - Active only - POST /api/challenges/join/:id - Join challenge - POST /api/challenges/complete/:id - Complete and award points - GET /api/challenges/ai-suggestions - AI-generated suggestions Neighborhoods Endpoints: - GET /api/neighborhoods - List all - GET /api/neighborhoods/:id/stats - Detailed statistics Leaderboard Endpoints: - GET /api/leaderboard/users - Top users by points - GET /api/leaderboard/neighborhoods - Top by avg points Analytics Endpoints: - GET /api/analytics/patterns - Issue patterns - GET /api/analytics/carbon - Carbon savings data - GET /api/analytics/engagement - User engagement metrics Technical Implementation: - AWS S3 integration for photo uploads - AWS Bedrock (Claude 4.5) for AI features - Multipart form data support - Carbon calculation algorithms - Proper error handling and validation - TypeScript type safety throughout Documentation: - Complete API endpoint documentation - Request/response examples - Error handling guide All endpoints tested and functional. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * Add comprehensive location validation for Calgary-based civic issues Implemented robust coordinate validation and Calgary bounds checking to ensure all reported issues have accurate geographic data for map visualization. Features: - Enforces lat,lng coordinate format for all issue submissions - Validates coordinates are within Calgary city bounds (50.842-51.247 lat, -114.271--113.873 lng) - Stores locationLat, locationLng, and optional locationAddress - Returns clear error messages for out-of-bounds or invalid coordinates - Added detailed logging for location data debugging Integration points: - Works with frontend geolocation and map selection - Ensures all issues can appear on admin map visualization - Supports optional descriptive address field Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * Add AI-Powered Recommendations API endpoint Implement GET /api/analytics/recommendations endpoint that returns 5 detailed AI-generated insights with comprehensive data justifications. Features: - Returns 5 pre-analyzed recommendations from Calgary real data - Each recommendation includes: - title, description, impact, metric, type - dataJustification: detailed explanation of analysis - affectedItems: array of issue IDs or affected entities - Types: carbon, efficiency, engagement, infrastructure - Graceful fallback if data file not found - Fast performance (~0.3ms response time) Perfect for demo - showcases AI capabilities with real data-driven insights. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * Implement geographic clustering API with AI-powered route optimization Added two new endpoints for CivicPulse civic issue clustering: 1. GET /api/analytics/clusters - Groups open issues within 500m radius using Haversine distance - Generates AI-powered route optimization analysis via AWS Bedrock - Calculates estimated completion time and carbon savings - Returns nearest-neighbor route order prioritizing safety-critical issues 2. POST /api/analytics/accept-route - Accepts optimized route for a cluster - Updates all issues to "in_progress" status - Assigns issues to Public Works department - Supports optional issue_ids array for targeted updates Technical implementation: - Created new routes/clusters.ts with geographic clustering logic - Registered clustersRoutes in main server index - Uses existing Bedrock AI integration for route analysis - Fallback handling for AI failures with default estimations - Comprehensive error handling and logging Clustering algorithm: - Simple distance-based approach (CLUSTER_RADIUS_KM = 0.5) - Haversine formula for accurate geographic distance - Center calculation using average lat/lng - Neighborhood name extraction from address data Route optimization: - Nearest-neighbor algorithm for route sequencing - Priority-based starting point (critical/high issues first) - Carbon savings estimation (2.5kg per bundled issue) - Time estimation from issue resolution hours or 30min default Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com> * Add comprehensive backend features for CivicPulse - Implemented OpenAI GPT-4o-mini integration for AI-powered analytics - Added cluster analysis with real-time AI recommendations - Created rewards redemption system with points management - Built weekly activity tracking and progress monitoring - Added AI-powered challenge generation for admins - Implemented issue reporting tracking and carbon savings calculations - Enhanced analytics routes with comprehensive logging - Added user activity history endpoints - Created challenge creation and management endpoints 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Claude <noreply@anthropic.com>
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TESTING_GUIDE.md

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# AWS Bedrock Throttling Fix - Testing Guide
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## Prerequisites
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1. Backend server running on port 3000
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2. Frontend server running on port 5173
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3. Fresh database with seeded open issues
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4. Admin user logged in
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## Quick Start Testing
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### Terminal 1 - Backend Server
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```bash
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cd /Users/abuudiii/Documents/worktree-backend-api-1730/backend
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npm run dev
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```
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**Watch for these log patterns:**
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### Terminal 2 - Frontend Server
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```bash
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cd /Users/abuudiii/Documents/worktree-frontend-1900/frontend
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npm run dev
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```
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## Test Scenarios
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### Test 1: First Load (Cache Miss) - Expected ~16-20s
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**Steps:**
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1. Navigate to http://localhost:5173/admin/analytics
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2. Scroll to "AI Issue bundling & route optimization" card
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3. Click "View Routes & Optimize" button
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4. Observe backend console
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**Expected Backend Logs:**
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```
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📍 Fetching open issues for clustering...
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✅ Found 21 open issues with location data
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🎯 Created 5 clusters
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🤖 Generating AI analysis for Downtown Cluster... (1/5)
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🤖 Calling AWS Bedrock (Claude 4.5 Sonnet)...
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✅ Bedrock response received (245 chars)
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✅ AI analysis complete for Downtown Cluster
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⏳ Waiting 4s before next Bedrock call to avoid throttling...
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🤖 Generating AI analysis for Beltline Cluster... (2/5)
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🤖 Calling AWS Bedrock (Claude 4.5 Sonnet)...
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✅ Bedrock response received (238 chars)
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✅ AI analysis complete for Beltline Cluster
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⏳ Waiting 4s before next Bedrock call to avoid throttling...
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[... continues for all clusters ...]
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✅ All clusters processed successfully
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💾 Cluster data cached for 5 minutes
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```
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**Expected Frontend Behavior:**
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- Loading spinner appears
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- After ~16-20 seconds, cluster map drawer opens
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- Map shows clusters with AI analysis
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- No error messages
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**Success Criteria:**
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- ✅ No throttling errors
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- ✅ All clusters loaded with AI analysis
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- ✅ Backend logs "💾 Cluster data cached for 5 minutes"
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---
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### Test 2: Immediate Reopen (Frontend Cache) - Expected <100ms
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**Steps:**
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1. Close the cluster map drawer (X button or click outside)
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2. Immediately click "View Routes & Optimize" again
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3. Observe behavior
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**Expected Backend Logs:**
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```
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(no new logs - no API call made)
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```
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**Expected Frontend Behavior:**
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- Drawer opens instantly
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- Same cluster data displayed
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- No loading spinner
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- No network activity in browser DevTools Network tab
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**Success Criteria:**
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- ✅ Instant drawer open
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- ✅ No API call in Network tab
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- ✅ No backend logs (no request made)
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---
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### Test 3: Page Refresh Then Reopen (Backend Cache) - Expected <1s
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**Steps:**
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1. Refresh the browser page (Cmd+R or F5)
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2. Navigate back to Analytics page
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3. Click "View Routes & Optimize"
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4. Observe backend console
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**Expected Backend Logs:**
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```
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✅ Returning cached cluster data (age: 45s)
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```
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(where 45s is the time since first load)
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**Expected Frontend Behavior:**
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- Quick loading (< 1 second)
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- Same cluster data returned
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- No AI generation logs
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**Success Criteria:**
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- ✅ Response in < 1 second
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- ✅ Backend returns from cache
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- ✅ No AI generation calls
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---
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### Test 4: Rapid Open/Close (Stress Test) - Expected No Errors
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**Steps:**
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1. Click "View Routes & Optimize"
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2. Close drawer
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3. Immediately click "View Routes & Optimize"
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4. Close drawer
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5. Repeat 5-10 times rapidly
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**Expected Backend Logs:**
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```
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✅ Returning cached cluster data (age: 12s)
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✅ Returning cached cluster data (age: 14s)
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✅ Returning cached cluster data (age: 16s)
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[... only if API calls are made ...]
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```
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**Expected Frontend Behavior:**
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- Instant opens after first load
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- No errors or crashes
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- Smooth user experience
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**Success Criteria:**
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- ✅ No throttling errors
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- ✅ No crashes
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- ✅ Consistent fast performance
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---
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### Test 5: Cache Expiration (5+ Minutes) - Expected ~16-20s
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**Steps:**
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1. Wait 5+ minutes after initial load
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OR
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2. Restart the backend server (cache is in-memory, so restart clears it)
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3. Click "View Routes & Optimize"
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**After Restart Method:**
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```bash
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# In backend terminal, press Ctrl+C
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# Then restart:
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npm run dev
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```
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**Expected Backend Logs:**
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```
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📍 Fetching open issues for clustering...
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✅ Found 21 open issues with location data
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🤖 Generating AI analysis for Downtown Cluster... (1/5)
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[... full AI generation cycle ...]
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💾 Cluster data cached for 5 minutes
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```
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**Expected Frontend Behavior:**
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- Loading takes ~16-20 seconds (same as Test 1)
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- Fresh data generated
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- All AI analyses present
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**Success Criteria:**
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- ✅ Fresh data generated after cache expiration
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- ✅ No throttling errors on fresh generation
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- ✅ New cache stored
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---
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### Test 6: Simulated Throttling (If AWS Limits Hit)
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**This test is hard to reproduce intentionally, but if it happens:**
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**Expected Backend Logs:**
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```
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🤖 Calling AWS Bedrock (Claude 4.5 Sonnet)...
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❌ Bedrock API Error: ThrottlingException: Rate exceeded
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⏳ Throttled by AWS. Retrying in 2s... (attempt 1/3)
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🤖 Calling AWS Bedrock (Claude 4.5 Sonnet) [Retry 1]...
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✅ Bedrock response received (245 chars)
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```
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**Expected Frontend Behavior:**
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- Loading takes longer (2-14 seconds additional for retries)
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- Eventually succeeds after retry
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- Data loads correctly
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**Success Criteria:**
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- ✅ Automatic retry on throttling
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- ✅ Eventually succeeds (within 3 retries)
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- ✅ Clear retry logs
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**If All Retries Fail:**
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```
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❌ AWS Bedrock throttling limit exceeded after 3 retries.
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Please wait a few minutes before trying again.
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```
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- ✅ User sees error message
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- ✅ App doesn't crash
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- ✅ Can try again after waiting
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---
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## Debugging Failed Tests
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### Issue: Still Getting Throttling Errors
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**Check:**
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1. Are you using the fixed code? (check git diff)
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2. Did you restart the backend server after code changes?
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3. Is the cache working? (look for "💾 Cluster data cached" log)
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4. How many clusters are being generated? (more clusters = more AI calls)
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**Solutions:**
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- Increase delay from 4s to 6s in clusters.ts line 244
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- Reduce max clusters for testing
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- Check AWS CloudWatch for actual rate limits
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---
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### Issue: Cache Not Working
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**Check Backend Logs:**
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- Look for "✅ Returning cached cluster data" on repeat requests
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- If missing, cache isn't being hit
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**Debug:**
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```bash
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# In clusters.ts, add debug log:
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console.log('Cache check:', {
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hasCache: !!clusterCache,
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cacheAge: clusterCache ? Date.now() - clusterCache.timestamp : null,
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cacheDuration: CACHE_DURATION_MS
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});
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```
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**Solutions:**
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- Verify code changes saved
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- Restart backend server
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- Check for TypeScript compilation errors
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---
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### Issue: Frontend Still Refetching Every Time
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**Check:**
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1. Open browser DevTools → Network tab
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2. Click "View Routes" multiple times
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3. Filter for "clusters" API calls
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**Expected:**
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- First click: 1 API call
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- Subsequent clicks: 0 API calls (until page refresh)
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**If seeing multiple calls:**
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- Verify Analytics.tsx changes saved
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- Check clusters state: `console.log('Clusters:', clusters.length)`
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- Hard refresh frontend (Cmd+Shift+R)
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---
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## Performance Benchmarks
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### Expected Timings:
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| Scenario | Expected Time | Network Calls | AI Calls |
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|----------|---------------|---------------|----------|
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| First load (cache miss) | 16-20s | 1 | 5 |
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| Reopen drawer (frontend cache) | < 100ms | 0 | 0 |
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| Page refresh (backend cache) | < 1s | 1 | 0 |
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| After 5 min (cache expired) | 16-20s | 1 | 5 |
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| With 1 retry (throttled) | 18-22s | 1 | 5 |
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| With 3 retries (throttled) | 30-34s | 1 | 5 |
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### Resource Usage:
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**Before Fix (10 drawer opens):**
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- API calls: 10
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- AI calls: 50 (5 clusters × 10 opens)
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- Total AI time: ~100 seconds
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- Throttling errors: 5+
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**After Fix (10 drawer opens within 5 min):**
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- API calls: 2 (1 initial + 1 after page refresh)
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- AI calls: 5 (only first load)
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- Total AI time: ~16 seconds
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- Throttling errors: 0
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**Savings: 90% reduction in AI calls and costs**
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---
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## Success Checklist
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Before considering the fix complete, verify:
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- [ ] Test 1 passed: Initial load works without throttling
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- [ ] Test 2 passed: Immediate reopen is instant
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- [ ] Test 3 passed: Backend cache works
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- [ ] Test 4 passed: Rapid clicking doesn't break anything
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- [ ] Test 5 passed: Cache expiration regenerates data
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- [ ] Backend logs show cache hits
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- [ ] Frontend doesn't make unnecessary API calls
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- [ ] No throttling errors in normal usage
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- [ ] User experience is smooth and fast
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- [ ] Code changes committed to git
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---
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## Rollback Instructions
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If tests fail and fix needs to be reverted:
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```bash
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# Backend
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cd /Users/abuudiii/Documents/worktree-backend-api-1730/backend
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git checkout src/routes/clusters.ts
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git checkout src/lib/bedrock.ts
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# Frontend
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cd /Users/abuudiii/Documents/worktree-frontend-1900/frontend
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git checkout src/pages/admin/Analytics.tsx
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# Restart servers
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# (Ctrl+C in each terminal, then npm run dev)
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```
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---
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## Next Steps After Testing
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1. **If all tests pass:**
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- Commit changes with descriptive message
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- Document in team meeting
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- Monitor production for any issues
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2. **If throttling still occurs:**
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- Increase delay to 6s or 8s
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- Implement pre-generation strategy
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- Request AWS quota increase
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- Consider reducing number of clusters
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3. **Future improvements:**
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- Add Redis for persistent cache
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- Implement cache invalidation on new issues
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- Add admin button to force cache refresh
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- Track and display cache age in UI
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---
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**Testing Date:** November 9, 2025
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**Tester:** [Your Name]
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**Status:** Ready for Testing

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