424 lines
15 KiB
Plaintext
424 lines
15 KiB
Plaintext
# Automated Development Pipeline - Complete Project Context & Progress Tracker
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## 🎯 PROJECT VISION & OBJECTIVES
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### **Core Vision**
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Create a fully automated development pipeline that takes developer requirements in natural language and outputs a complete, production-ready application with minimal human intervention.
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### **Success Metrics**
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- 80-90% reduction in manual coding for standard applications
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- Complete project delivery in under 30 minutes
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- Production-ready code quality (80%+ test coverage)
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- Zero developer intervention for deployment pipeline
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- Support for both monolithic and microservices architectures
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### **Developer Experience Goal**
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1. Developer opens simple web interface
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2. Describes what they want in plain English
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3. Answers a few clarifying questions (if needed)
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4. Clicks "Generate"
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5. Gets a live, deployed application with URL
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6. Can access source code if needed
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---
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## 🏗️ COMPLETE SYSTEM ARCHITECTURE
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### **High-Level Flow**
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```
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Developer Interface (React)
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↓
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API Gateway (Node.js + JWT)
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↓
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n8n Orchestration Engine
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↓
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┌─────────────┬─────────────┬─────────────┐
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│ AI Services │ Code Services│ Infra Services│
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│- Requirements│- Generator │- Testing │
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│- Tech Stack │- Architecture│- Deployment │
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│- Quality │- Templates │- Monitoring │
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└─────────────┴─────────────┴─────────────┘
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↓
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Data Layer (PostgreSQL + MongoDB + Redis + RabbitMQ)
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↓
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Generated Applications (Local + CloudtopiAA)
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```
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### **Technology Stack Matrix**
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**Phase 1 Implementation (Weeks 1-4):**
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1. **React + Node.js + PostgreSQL** (Full JavaScript)
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2. **React + .NET Core + PostgreSQL** (Enterprise)
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3. **Vue.js + Python FastAPI + PostgreSQL** (Modern flexible)
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**Phase 2 Implementation (Weeks 5-8):**
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4. **Angular + Java Spring Boot + PostgreSQL** (Enterprise Java)
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5. **Svelte + Go + PostgreSQL** (Performance)
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6. **Next.js + Node.js + MongoDB** (Modern full-stack)
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**Phase 3 Implementation (Weeks 9-12):**
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7. **React + Python Django + PostgreSQL** (Data-heavy)
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8. **Vue.js + Ruby Rails + PostgreSQL** (Rapid development)
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9. **Angular + .NET Core + SQL Server** (Microsoft ecosystem)
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---
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## 📁 PROJECT STRUCTURE
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```
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automated-dev-pipeline/
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├── infrastructure/
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│ ├── docker/ # Docker configurations
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│ ├── terraform/ # Infrastructure as Code
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│ ├── kubernetes/ # K8s manifests
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│ ├── jenkins/ # CI/CD configurations
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│ └── rabbitmq/ # Message queue configs
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├── orchestration/
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│ └── n8n/ # Master workflow engine
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│ ├── workflows/ # n8n workflow definitions
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│ └── custom-nodes/ # Custom n8n nodes
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├── services/
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│ ├── api-gateway/ # Central API gateway (Node.js)
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│ ├── requirement-processor/ # AI requirement analysis (Python)
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│ ├── tech-stack-selector/ # Technology selection AI (Python)
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│ ├── architecture-designer/ # System architecture AI (Python)
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│ ├── code-generator/ # Multi-framework code gen (Python)
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│ ├── test-generator/ # Automated testing (Python)
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│ └── deployment-manager/ # Deployment automation (Python)
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├── frontend/
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│ └── developer-interface/ # React developer UI
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├── databases/
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│ └── scripts/ # DB schemas and migrations
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├── monitoring/
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│ └── configs/ # Prometheus, Grafana configs
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├── generated_projects/ # Output directory
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├── scripts/
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│ └── setup/ # Management scripts
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└── docs/ # Documentation
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```
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---
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## 🔧 CORE SYSTEM DESIGN DECISIONS
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### **1. Service Communication Architecture**
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- **Primary Flow**: Frontend → API Gateway → n8n → Services
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- **Direct Communication**: Services ↔ Services (performance-critical)
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- **Async Operations**: Services → RabbitMQ → Services
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- **Real-time Updates**: Services → Redis Pub/Sub → Frontend
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### **2. Error Handling Strategy**
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- **Level 1**: Service-Level (3 immediate retries)
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- **Level 2**: n8n Workflow-Level (exponential backoff, 5 attempts)
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- **Level 3**: Dead Letter Queue (manual intervention)
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- **Level 4**: Compensation Transactions (rollback)
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### **3. State Management**
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- **PostgreSQL**: Current state + Event log + Metadata
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- **Redis**: Fast state lookup + Session data + Pub/Sub
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- **MongoDB**: Large objects (generated code, templates)
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- **State Machine**: 15+ project states with audit trail
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### **4. Security Model**
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- **External**: JWT tokens for user authentication
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- **Internal**: mTLS + Service identity tokens
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- **API Gateway**: Rate limiting, input validation, CORS
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- **Data**: Encryption at rest and in transit
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### **5. Code Storage Strategy**
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- **Generated Projects**: Distributed file system (mounted volumes)
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- **Code Templates**: MongoDB (versioned, searchable)
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- **Metadata**: PostgreSQL (relational data)
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- **Version Control**: Gitea/GitLab integration
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---
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## 📅 COMPLETE IMPLEMENTATION TIMELINE
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### **PHASE 1: FOUNDATION (WEEKS 1-2)**
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**Week 1: Infrastructure Setup**
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- ✅ **COMPLETED**: Project directory structure creation
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- ✅ **COMPLETED**: Database schemas (PostgreSQL, MongoDB, Redis)
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- ✅ **COMPLETED**: Docker infrastructure configuration
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- ✅ **COMPLETED**: 6 Python microservices with complete FastAPI code (158 lines each)
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- ✅ **COMPLETED**: 1 Node.js API Gateway with complete Express.js code (113 lines)
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- 🔄 **IN PROGRESS**: RabbitMQ message queue setup
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- 🔄 **IN PROGRESS**: n8n orchestration engine setup
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- ⏳ **PENDING**: Service startup and validation scripts
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**Week 2: Core Service Templates & Basic Integration**
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- ⏳ Service-to-service communication setup
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- ⏳ Basic n8n workflows for service coordination
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- ⏳ Health monitoring and logging implementation
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- ⏳ Basic API Gateway routing to services
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- ⏳ Database connection implementation in all services
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- ⏳ Redis caching integration
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- ⏳ Message queue producer/consumer setup
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### **PHASE 2: AI SERVICES & ORCHESTRATION (WEEKS 3-4)**
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**Week 3: Requirements Processing & Tech Stack Selection**
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- ⏳ Claude API integration for requirement analysis
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- ⏳ Natural language processing for requirement validation
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- ⏳ Technical PRD generation from user input
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- ⏳ AI-powered technology stack selection algorithm
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- ⏳ Framework compatibility matrix implementation
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- ⏳ n8n workflows for AI service coordination
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**Week 4: Architecture Design & Planning**
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- ⏳ Monolithic vs microservices decision engine
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- ⏳ Database schema generation from requirements
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- ⏳ API contract generation
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- ⏳ System architecture diagram generation
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- ⏳ Component relationship mapping
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- ⏳ Infrastructure requirement calculation
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### **PHASE 3: CODE GENERATION ENGINE (WEEKS 5-6)**
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**Week 5: Template System & Code Generation Core**
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- ⏳ Multi-framework template engine (Jinja2-based)
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- ⏳ Code generation for React + Node.js stack
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- ⏳ Project scaffolding automation
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- ⏳ File structure generation
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- ⏳ Dependency management automation
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- ⏳ Docker configuration generation
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**Week 6: Expanded Framework Support**
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- ⏳ React + .NET Core code generation
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- ⏳ Vue.js + Python FastAPI code generation
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- ⏳ Database migration scripts generation
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- ⏳ Environment configuration automation
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- ⏳ CI/CD pipeline generation
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### **PHASE 4: TESTING & QUALITY ASSURANCE (WEEKS 7-8)**
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**Week 7: Automated Test Generation**
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- ⏳ Unit test generation for all frameworks
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- ⏳ Integration test creation
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- ⏳ End-to-end test automation
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- ⏳ Test data generation
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- ⏳ Mock service creation
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- ⏳ Performance test setup
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**Week 8: Quality Gates & Validation**
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- ⏳ Code quality analysis (SonarQube integration)
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- ⏳ Security vulnerability scanning
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- ⏳ Performance benchmarking
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- ⏳ Code coverage enforcement
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- ⏳ Automated code review suggestions
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- ⏳ Quality score calculation
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### **PHASE 5: DEPLOYMENT & DEVOPS (WEEKS 9-10)**
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**Week 9: Local Development Environment**
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- ⏳ Docker Compose generation for local dev
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- ⏳ Hot reload configuration
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- ⏳ Local database seeding
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- ⏳ Development proxy setup
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- ⏳ Environment variable management
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- ⏳ Debug configuration setup
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**Week 10: CloudtopiAA Integration**
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- ⏳ CloudtopiAA API integration
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- ⏳ Automated infrastructure provisioning
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- ⏳ Staging environment deployment
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- ⏳ Production environment setup
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- ⏳ Domain and SSL configuration
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- ⏳ Monitoring and alerting setup
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### **PHASE 6: FRONTEND & USER EXPERIENCE (WEEKS 11-12)**
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**Week 11: Developer Interface**
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- ⏳ React frontend development
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- ⏳ Real-time progress tracking (WebSocket)
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- ⏳ Project creation wizard
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- ⏳ Code preview and download
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- ⏳ Deployment status monitoring
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- ⏳ Error handling and user feedback
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**Week 12: Polish & Advanced Features**
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- ⏳ Advanced configuration options
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- ⏳ Project templates and presets
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- ⏳ Collaboration features
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- ⏳ Analytics and usage tracking
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- ⏳ Documentation generation
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- ⏳ Performance optimization
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---
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## 📋 CURRENT STATUS & PROGRESS
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### **✅ COMPLETED ITEMS**
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1. **Project Structure**: Complete directory structure with all necessary folders
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2. **Database Design**:
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- PostgreSQL schemas with 8 main tables
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- MongoDB initialization for templates and code storage
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- Redis configuration for caching and real-time data
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3. **Microservices**:
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- 6 Python FastAPI services (158 lines each):
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- requirement-processor (port 8001)
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- tech-stack-selector (port 8002)
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- architecture-designer (port 8003)
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- code-generator (port 8004)
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- test-generator (port 8005)
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- deployment-manager (port 8006)
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- 1 Node.js Express API Gateway (113 lines, port 8000)
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4. **Docker Configuration**: Complete docker-compose.yml with all infrastructure services
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5. **Environment Setup**: .env files, .gitignore, and basic configuration
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### **🔄 CURRENTLY IN PROGRESS (Step 1.5-1.6)**
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1. **RabbitMQ Setup**: Message queue configuration for service communication
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2. **Startup Scripts**: Automated startup and health checking scripts
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3. **Service Integration**: Connecting all services together
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### **⏳ IMMEDIATE NEXT STEPS**
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1. **Complete Phase 1** (Remaining 2-3 hours):
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- Finish RabbitMQ setup
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- Create and test startup scripts
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- Validate all services start correctly
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- Test inter-service communication
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2. **Begin Phase 2** (Week 3):
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- Add n8n orchestration engine
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- Implement basic workflows
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- Add Claude API integration
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- Create requirement processing logic
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---
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## 🎛️ SERVICE SPECIFICATIONS
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### **API Gateway (Node.js - Port 8000)**
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- **Technology**: Express.js + Socket.io + JWT
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- **Functions**: Authentication, routing, rate limiting, WebSocket management
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- **Endpoints**: `/health`, `/api/v1/status`, WebSocket connections
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- **Status**: ✅ Complete (113 lines)
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### **Requirement Processor (Python - Port 8001)**
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- **Technology**: FastAPI + Claude API + LangChain
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- **Functions**: Natural language processing, PRD generation, requirement validation
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- **Endpoints**: `/health`, `/api/v1/process`, `/api/v1/cache/{project_id}`
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- **Status**: ✅ Basic structure complete (158 lines)
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### **Tech Stack Selector (Python - Port 8002)**
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- **Technology**: FastAPI + AI Decision Engine
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- **Functions**: Technology selection, compatibility checking, recommendation generation
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- **Status**: ✅ Basic structure complete (158 lines)
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### **Architecture Designer (Python - Port 8003)**
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- **Technology**: FastAPI + Claude + Mermaid
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- **Functions**: Architecture decisions, database design, API contracts
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- **Status**: ✅ Basic structure complete (158 lines)
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### **Code Generator (Python - Port 8004)**
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- **Technology**: FastAPI + Template Engines + Multi-framework support
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- **Functions**: Code generation for 9+ framework combinations
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- **Status**: ✅ Basic structure complete (158 lines)
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### **Test Generator (Python - Port 8005)**
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- **Technology**: FastAPI + Testing frameworks
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- **Functions**: Unit, integration, E2E test generation
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- **Status**: ✅ Basic structure complete (158 lines)
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### **Deployment Manager (Python - Port 8006)**
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- **Technology**: FastAPI + Docker + CloudtopiAA APIs
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- **Functions**: Local and cloud deployment automation
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- **Status**: ✅ Basic structure complete (158 lines)
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---
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## 🗃️ DATABASE ARCHITECTURE
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### **PostgreSQL Tables**
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1. **projects**: Main project entity with status tracking
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2. **tech_stack_decisions**: Technology selection results
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3. **system_architectures**: Architecture design artifacts
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4. **code_generations**: Generated code tracking
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5. **test_results**: Test execution results
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6. **deployment_logs**: Deployment history
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7. **service_health**: Service monitoring
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8. **project_state_transitions**: Audit trail
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### **MongoDB Collections**
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1. **code_templates**: Framework-specific templates
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2. **framework_configs**: Technology configurations
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3. **generated_projects**: Complete project storage
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4. **ai_prompts**: AI prompt templates
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### **Redis Usage**
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1. **Caching**: API responses, computed results
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2. **Sessions**: User session management
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3. **Pub/Sub**: Real-time updates
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4. **Queues**: Background task processing
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---
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## 🔗 INTEGRATION POINTS
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### **External APIs**
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- **Claude API**: Natural language processing, code generation
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- **CloudtopiAA API**: Cloud deployment and infrastructure
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- **Git APIs**: Repository management (Gitea/GitLab)
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### **Internal Communication**
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- **HTTP REST**: Service-to-service API calls
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- **RabbitMQ**: Async message passing
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- **WebSocket**: Real-time frontend updates
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- **Redis Pub/Sub**: Event broadcasting
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---
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## 🚨 CRITICAL SUCCESS FACTORS
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1. **AI Quality**: Robust prompt engineering for consistent outputs
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2. **Error Handling**: Comprehensive error recovery at all levels
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3. **Performance**: Sub-30-minute end-to-end generation time
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4. **Scalability**: Handle 100+ concurrent generations
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5. **Quality Gates**: Ensure generated code meets production standards
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6. **Monitoring**: Real-time visibility into all pipeline stages
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---
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## 🛠️ IMMEDIATE ACTION ITEMS
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### **To Complete Phase 1 (Next Session)**
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1. **Run**: RabbitMQ configuration commands
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2. **Create**: Startup and stop scripts
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3. **Test**: `./scripts/setup/start.sh` command
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4. **Verify**: All services start and respond to health checks
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5. **Validate**: Database connections and message queue operation
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### **Commands Ready to Execute**
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```bash
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# Complete Step 1.5 - RabbitMQ Setup
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mkdir -p infrastructure/rabbitmq && [RabbitMQ config commands]
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# Complete Step 1.6 - Startup Scripts
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cat > scripts/setup/start.sh << 'EOF' && [startup script content]
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# Test Phase 1
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./scripts/setup/start.sh
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```
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---
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## 🎯 CONTEXT RESTORATION CHECKLIST
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**When resuming this project, verify:**
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1. ✅ Are we in the `automated-dev-pipeline` directory?
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2. ✅ Do all 7 services exist with proper line counts?
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3. ✅ Is docker-compose.yml present with all infrastructure services?
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4. ✅ Are database scripts in place?
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5. 🔄 Have we completed RabbitMQ setup? (Step 1.5)
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6. 🔄 Have we completed startup scripts? (Step 1.6)
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7. ⏳ Can we successfully run `./scripts/setup/start.sh`?
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**Current Position**: Phase 1, Step 1.4 ✅ Complete, Step 1.5-1.6 🔄 In Progress
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**Next Milestone**: Complete Phase 1 Foundation → Begin Phase 2 AI Services Integration
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This context document ensures project continuity regardless of session interruptions. |