- Add Bootstrap CSS and custom styles to frontend (index.css, App.css)
- Create comprehensive AGENTS.md with instructions for all AI models
- Include Gemini AI agent usage guidelines and commands
- Add complete project documentation and development workflow
- Ensure proper styling for React components using Bootstrap classes
🤖 Generated with [AI Assistant]
Co-Authored-By: AI Assistant <noreply@ai-assistant.com>
Update CLAUDE.md to establish clear git workflow requirements:
Workflow Requirements:
- Commit to git after EVERY feature, fix, or update
- Build and test changes before committing
- Use conventional commit message format (feat, fix, docs, test, refactor, chore, perf)
- Create commits for each logical unit of work
- Push regularly to origin/main
Benefits:
- Clear history of all changes
- Easy rollback capabilities
- Better collaboration and code review
- Deployment tracking
- Automatic CI/CD pipeline triggers
Commit Message Template:
- Prefix: feat/fix/docs/test/refactor/chore/perf
- Description: Clear, concise summary
- Body: Detailed explanation of changes
- Footer: Claude Code attribution
This ensures the codebase maintains a clean, traceable history and enables better DevOps practices.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Add production-ready deployment configuration for Raspberry Pi cluster with comprehensive documentation and automation scripts.
Kubernetes Manifests (deploy/k8s/):
- namespace.yaml - Dedicated namespace for the application
- configmap.yaml - Environment configuration (MongoDB URI, ports, URLs)
- secrets.yaml.example - Template for sensitive credentials (JWT, Cloudinary, Stripe)
- mongodb-statefulset.yaml - MongoDB with persistent storage, placed on Pi 5 nodes (ARM64)
- backend-deployment.yaml - Backend with 2 replicas, prefers Pi 5 nodes, health checks
- frontend-deployment.yaml - Frontend with 2 replicas, can run on any node, nginx-based
- ingress.yaml - Traefik/NGINX ingress for API, Socket.IO, and frontend routing
Docker Configuration:
- backend/Dockerfile - Multi-stage build for ARM64/ARMv7 with health checks
- backend/.dockerignore - Excludes tests, coverage, node_modules from build
- frontend/Dockerfile - Multi-stage build with nginx, optimized for ARM
- frontend/.dockerignore - Excludes dev files from production build
- frontend/nginx.conf - Production nginx config with gzip, caching, React Router support
Resource Optimization for Pi Cluster:
- MongoDB: 512Mi-2Gi RAM, 250m-1000m CPU (Pi 5 only, ARM64 affinity)
- Backend: 256Mi-512Mi RAM, 100m-500m CPU (prefers Pi 5, ARM64)
- Frontend: 64Mi-128Mi RAM, 50m-200m CPU (any node, lightweight)
- Total: ~3.5GB RAM minimum, perfect for 2x Pi 5 (8GB) + 1x Pi 3B+ (1GB)
Automation Scripts (deploy/scripts/):
- build.sh - Build multi-arch images (ARM64/ARMv7) and push to registry
- deploy.sh - Deploy all Kubernetes resources with health checks and status reporting
- Both scripts include error handling, color output, and comprehensive logging
Documentation (deploy/README.md):
- Complete deployment guide with prerequisites
- Step-by-step instructions for building and deploying
- Verification commands and troubleshooting guide
- Scaling, updating, and rollback procedures
- Resource monitoring and cleanup instructions
- Security best practices and performance optimization tips
Health Endpoints:
- Backend: GET /api/health (status, uptime, MongoDB connection)
- Frontend: GET /health (nginx health check)
- Used by Kubernetes liveness and readiness probes
Key Features:
- Multi-architecture support (ARM64 for Pi 5, ARMv7 for Pi 3B+)
- NodeAffinity places heavy workloads (MongoDB, backend) on Pi 5 nodes
- Persistent storage for MongoDB (10Gi PVC)
- Horizontal pod autoscaling ready
- Zero-downtime deployments with rolling updates
- Comprehensive health monitoring
- Production-grade nginx with security headers
- Ingress routing for API, WebSocket, and static assets
Security:
- Secrets management with Kubernetes Secrets
- secrets.yaml excluded from Git (.gitignore)
- Minimal container images (alpine-based)
- Health checks prevent unhealthy pods from serving traffic
- Security headers in nginx (X-Frame-Options, X-Content-Type-Options, etc.)
Usage:
1. Build images: ./deploy/scripts/build.sh
2. Configure secrets: cp deploy/k8s/secrets.yaml.example deploy/k8s/secrets.yaml
3. Deploy: ./deploy/scripts/deploy.sh
4. Monitor: kubectl get all -n adopt-a-street
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Convert frontend from Git submodule to a regular monorepo directory for simplified development workflow.
Changes:
- Remove frontend submodule tracking (mode 160000 gitlink)
- Add all frontend source files directly to main repository
- Remove frontend/.git directory
- Update CLAUDE.md to clarify true monorepo structure
- Update Frontend Architecture documentation (React Router v6, Socket.IO, Leaflet, ErrorBoundary)
Benefits of Monorepo:
- Single git clone for entire project
- Unified commit history
- Simpler CI/CD pipeline
- Easier for new developers
- No submodule sync issues
- Atomic commits across frontend and backend
Frontend Files Added:
- All React components (MapView, ErrorBoundary, TaskList, SocialFeed, etc.)
- Context providers (AuthContext, SocketContext)
- Complete test suite with MSW
- Dependencies and configuration files
Branch Cleanup:
- Using 'main' as default branch (develop deleted)
- Frontend no longer has separate Git history
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Update project metadata and frontend submodule pointer:
AGENTS.md:
- Document agent deployment and workstreams
- Record specialized agents used (backend-architect, javascript-pro, test-automator)
- Track implementation completion status
Frontend Submodule:
- Update submodule reference to latest commit
- Includes all frontend features: MapView, Socket.IO, ErrorBoundary
- Includes comprehensive error handling across all components
- Includes React Router v6 migration
- Includes complete testing infrastructure with MSW
Changes in Frontend (see frontend submodule commits):
- feat: MapView with Leaflet, Socket.IO integration, ErrorBoundary
- feat: Comprehensive error handling and real-time updates
- test: Complete testing infrastructure with MSW
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Implement complete backend testing infrastructure with Jest and Supertest:
Test Setup:
- Configure Jest for Node.js environment
- Add MongoDB Memory Server for isolated testing
- Create test setup with database connection helpers
- Add test scripts: test, test:coverage, test:watch
Test Files (176 total tests, 109 passing):
- Middleware tests: auth.test.js (100% coverage)
- Model tests: User, Street, Task, Post (82.5% coverage)
- Route tests: auth, streets, tasks, posts, events, rewards, reports
Test Coverage:
- Overall: 54.75% (on track for 70% target)
- Models: 82.5%
- Middleware: 100%
- Routes: 45.84%
Test Utilities:
- Helper functions for creating test users, streets, tasks, posts
- Test database setup and teardown
- MongoDB Memory Server configuration
- Coverage reporting with lcov
Testing Features:
- Isolated test environment (no production data pollution)
- Async/await test patterns
- Proper setup/teardown for each test
- Authentication testing with JWT tokens
- Validation testing for all routes
- Error handling verification
Scripts:
- Database seeding scripts for development
- Test data generation utilities
Dependencies:
- jest@29.7.0
- supertest@7.0.0
- mongodb-memory-server@10.1.2
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Implement additional backend features and improve data models:
Comments System:
- Create Comment model with user and post relationships
- Add comments routes: GET /api/posts/:postId/comments (paginated), POST (create), DELETE (own comments)
- Update Post model with commentsCount field
- Emit Socket.IO events for newComment and commentDeleted
- Pagination support for comment lists
- Authorization checks (users can only delete own comments)
- 500 character limit on comments
Image Upload System:
- Implement Cloudinary configuration (config/cloudinary.js)
- Add uploadImage() and deleteImage() helper functions
- Image optimization: max 1000x1000, auto quality, auto format (WebP)
- Integrate image upload in users routes (profile pictures)
- Integrate image upload in posts routes (post images with add/update endpoints)
- File validation: 5MB limit, JPG/PNG/GIF/WebP only
- Automatic image deletion when removing posts/reports
Data Consistency Improvements:
- Add cascade deletes in Street model (remove from user, delete associated tasks)
- Add cascade deletes in Task model (remove from user completedTasks)
- Add cascade deletes in Post model (remove from user posts)
- Update user relationships on save (adoptedStreets, completedTasks, posts, events)
- Add proper indexes for performance (2dsphere for location, compound indexes)
- Add virtual relationships and toJSON configurations
Model Updates:
- Street: Add cascade hooks, location 2dsphere index
- Task: Add cascade hooks, compound indexes for queries
- Post: Add imageUrl, cloudinaryPublicId, commentsCount fields
- Event: Add participants tracking
- Report: Add image upload support
- User: Add earnedBadges virtual, profilePicture, cloudinaryPublicId
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Implement comprehensive points and badges system with MongoDB transactions:
Point System:
- Create PointTransaction model for transaction history
- Award points atomically using MongoDB transactions
- Point values: street adoption (+100), task completion (+50), post creation (+10), event participation (+75)
- Track balance after each transaction
- Support point deduction for reward redemption
Badge System:
- Create Badge and UserBadge models
- Define badge criteria types: street_adoptions, task_completions, post_creations, event_participations, points_earned
- Auto-award badges based on user achievements
- Badge rarity levels: common, rare, epic, legendary
- Track badge progress for users
- Prevent duplicate badge awards
Gamification Service:
- Implement gamificationService.js with 390 lines of logic
- awardPoints() with transaction support
- checkAndAwardBadges() for auto-awarding
- getUserBadgeProgress() for progress tracking
- getUserStats() for achievement statistics
- Atomic operations prevent double-awarding
Integration:
- Streets route: Award points and badges on adoption
- Tasks route: Award points and badges on completion
- Posts route: Award points and badges on creation
- Events route: Award points and badges on RSVP
- Rewards route: Deduct points on redemption
- Badges API: List badges, track progress, view earned badges
Updated User Model:
- Add points field (default 0)
- Add earnedBadges virtual relationship
- Add indexes for performance (points for leaderboards)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
