AI-Cohort-July-2025

System Overview

High-level architecture and system design of AutoDevHub

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Architecture Overview

AutoDevHub is an AI-powered DevOps tracker that streamlines project management by automatically generating user stories based on project requirements.

Key Components

1. Frontend Application
   • React-based single-page application
   • Vite for fast development and building
   • Modern, responsive UI design
   • Real-time story generation interface
2. Backend API
   • FastAPI framework for high performance
   • RESTful API design
   • OpenAPI/Swagger documentation
   • Async request handling
3. AI Integration
   • OpenAI GPT integration for story generation
   • Intelligent context understanding
   • Automated acceptance criteria generation
   • Story point estimation
4. Database Layer
   • PostgreSQL for reliable data storage
   • SQLAlchemy ORM for database operations
   • Migration support with Alembic
   • Optimized query performance

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System Architecture Diagram

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│                 │     │                 │     │                 │
│  React Frontend │────▶│  FastAPI Backend│────▶│   PostgreSQL    │
│                 │     │                 │     │                 │
└─────────────────┘     └────────┬────────┘     └─────────────────┘
                                 │
                                 ▼
                        ┌─────────────────┐
                        │                 │
                        │   OpenAI API    │
                        │                 │
                        └─────────────────┘

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Data Flow

1. User Input: Users enter project requirements through the React frontend
2. API Request: Frontend sends structured data to FastAPI backend
3. AI Processing: Backend processes request with OpenAI integration
4. Data Storage: Generated stories are stored in PostgreSQL
5. Response: Formatted stories returned to frontend for display

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Technology Stack

Frontend

• Framework: React 18.x
• Build Tool: Vite 7.x
• Styling: CSS Modules
• State Management: React Hooks
• HTTP Client: Fetch API

Backend

• Framework: FastAPI 0.115.x
• Language: Python 3.12
• ORM: SQLAlchemy 2.x
• Server: Uvicorn ASGI
• Validation: Pydantic

Infrastructure

• Database: PostgreSQL 15
• Container: Docker & Docker Compose
• CI/CD: GitHub Actions
• Documentation: Jekyll & GitHub Pages

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Security Features

1. Authentication: JWT-based authentication (planned)
2. Input Validation: Pydantic models for request validation
3. CORS Protection: Configured CORS middleware
4. Environment Variables: Secure configuration management
5. SQL Injection Prevention: ORM-based queries

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Deployment Architecture

Development Environment

• Local Docker Compose setup
• Hot reloading for frontend and backend
• PostgreSQL container for database

Production Environment (Planned)

• Frontend: Static hosting (Vercel/Netlify)
• Backend: Cloud platform (AWS/GCP/Azure)
• Database: Managed PostgreSQL service
• CDN: CloudFlare for static assets

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Performance Considerations

1. API Response Time: < 2 seconds for story generation
2. Database Queries: Indexed for optimal performance
3. Caching: Redis for frequently accessed data (planned)
4. Rate Limiting: API rate limiting for fair usage
5. Monitoring: Application performance monitoring (planned)

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For API details, see API Specification. For database design, see Database Schema.

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