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🚀 Developer Onboarding Guide

🎯 Welcome to Animation Designer Bot

This guide will help new developers understand the Animation Designer Bot system architecture, get their development environment set up, and start contributing effectively to the project.

📋 Quick Start Checklist

Prerequisites

  • Node.js 18+ installed
  • Python 3.11+ installed
  • Docker and Docker Compose installed
  • Git configured with SSH keys
  • VS Code or preferred IDE
  • Redis running locally (or Docker)

Initial Setup

  • Clone the repository
  • Install dependencies (npm install and pip install -r requirements.txt)
  • Set up environment variables
  • Run the development environment
  • Complete the architecture overview reading
  • Review the technology stack documentation

🏗️ System Architecture Overview

High-Level Architecture

The Animation Designer Bot is a distributed microservices system with the following key components:

  1. Frontend Layer: Next.js web application with conversational interface
  2. AI System: Multi-model orchestration (LLM, Image Gen, Video Gen, CV)
  3. Knowledge Base: Motion pattern database and template storage
  4. Content Generation: JSON schema generation and layout creation
  5. Render Farm: Distributed workers with Natron engines
  6. Storage Layer: Cloud storage and brand assets management

Data Flow

User Input → Conversational Interface → AI Orchestrator → 
Content Generation → JSON Schema → Natron Conversion → 
Job Queue → Workers → Rendering → Storage → User Output

🔧 Development Environment Setup

1. Repository Setup

# Clone the repository
git clone <repository-url>
cd animation-designer-bot

# Install Node.js dependencies
npm install

# Install Python dependencies
pip install -r requirements.txt

# Set up pre-commit hooks
pre-commit install

2. Environment Configuration

# Copy environment template
cp .env.example .env

# Edit environment variables
nano .env

Required Environment Variables: 

# Database Configuration
POSTGRES_URL=postgresql://user:password@localhost:5432/animation_bot
MONGODB_URL=mongodb://localhost:27017/animation_bot
REDIS_URL=redis://localhost:6379
ELASTICSEARCH_URL=http://localhost:9200

# AI Services
OPENAI_API_KEY=your_openai_key
ANTHROPIC_API_KEY=your_anthropic_key
DALLE_API_KEY=your_dalle_key

# Natron Configuration
NATRON_PATH=/usr/bin/NatronRenderer
NATRON_PYTHON_PATH=/usr/lib/python3.8/site-packages

# AWS Configuration
AWS_ACCESS_KEY_ID=your_aws_key
AWS_SECRET_ACCESS_KEY=your_aws_secret
AWS_S3_BUCKET=your_bucket_name

# Development Settings
NODE_ENV=development
DEBUG=true
LOG_LEVEL=debug

3. Database Setup

# Start PostgreSQL
docker run -d --name postgres \
  -e POSTGRES_DB=animation_bot \
  -e POSTGRES_USER=user \
  -e POSTGRES_PASSWORD=password \
  -p 5432:5432 postgres:15

# Start MongoDB
docker run -d --name mongodb \
  -p 27017:27017 mongo:6

# Start Redis
docker run -d --name redis \
  -p 6379:6379 redis:7

# Start Elasticsearch
docker run -d --name elasticsearch \
  -e "discovery.type=single-node" \
  -p 9200:9200 elasticsearch:8

4. Development Server

# Start the development environment
npm run dev

# Or start individual services
npm run dev:frontend    # Next.js frontend
npm run dev:backend     # Node.js API server
npm run dev:ai          # Python AI services
npm run dev:workers     # Worker processes

📚 Essential Documentation

Must-Read Documents

  1. Architecture Overview - Complete system architecture
  2. Technology Stack - All technologies used
  3. Team Structure - Roles and responsibilities
  4. Processing Modules - Core system logic

Specialized Documentation

🎯 Development Workflow

1. Understanding Your Role

Based on your specialization, focus on these areas:

Frontend Developer

  • Primary Focus: Next.js, React, TypeScript, Tailwind CSS
  • Key Files: /frontend/, /components/, /pages/
  • Documentation: Frontend architecture and component library

Backend Developer

  • Primary Focus: Node.js, Python, FastAPI, databases
  • Key Files: /backend/, /api/, /services/
  • Documentation: API specifications and data models

AI/ML Engineer

  • Primary Focus: OpenAI, computer vision, ML pipelines
  • Key Files: /ai/, /ml/, /computer-vision/
  • Documentation: AI model architecture and training

DevOps Engineer

  • Primary Focus: Docker, Kubernetes, AWS, monitoring
  • Key Files: /infrastructure/, /deployment/, /monitoring/
  • Documentation: Infrastructure and deployment guides

Computer Graphics Specialist

  • Primary Focus: Natron, rendering, video processing
  • Key Files: /rendering/, /natron/, /video-processing/
  • Documentation: Natron integration and rendering pipeline

2. Code Organization

animation-designer-bot/
├── frontend/                 # Next.js frontend application
│   ├── components/          # React components
│   ├── pages/              # Next.js pages
│   ├── styles/             # CSS and styling
│   └── utils/              # Frontend utilities
├── backend/                 # Node.js backend services
│   ├── api/                # API routes and controllers
│   ├── services/           # Business logic services
│   ├── middleware/         # Express middleware
│   └── utils/              # Backend utilities
├── ai/                     # Python AI services
│   ├── models/             # AI model definitions
│   ├── services/           # AI service implementations
│   ├── computer-vision/    # CV algorithms
│   └── utils/              # AI utilities
├── rendering/              # Rendering and video processing
│   ├── natron/             # Natron integration
│   ├── workers/            # Render workers
│   └── pipelines/          # Rendering pipelines
├── infrastructure/         # DevOps and infrastructure
│   ├── docker/             # Docker configurations
│   ├── kubernetes/         # K8s manifests
│   └── monitoring/         # Monitoring configurations
└── docs/                   # Documentation
    └── Animation_Designer_Bot/  # This documentation

3. Development Practices

Code Standards

  • TypeScript: Strict mode enabled, comprehensive typing
  • Python: PEP 8 compliance, type hints required
  • Testing: Unit tests for all new code
  • Documentation: Docstrings and comments required

Git Workflow

# Create feature branch
git checkout -b feature/your-feature-name

# Make changes and commit
git add .
git commit -m "feat: add new feature"

# Push and create PR
git push origin feature/your-feature-name

Code Review Process

  1. Self-review: Test your code thoroughly
  2. Peer review: At least one team member review
  3. Architecture review: For significant changes
  4. Testing: All tests must pass
  5. Documentation: Update relevant documentation

🧪 Testing and Quality Assurance

Testing Strategy

# Run all tests
npm test

# Run specific test suites
npm run test:frontend
npm run test:backend
npm run test:ai
npm run test:integration

# Run tests with coverage
npm run test:coverage

Quality Checks

# Linting
npm run lint
npm run lint:fix

# Type checking
npm run type-check

# Security audit
npm audit

🐛 Debugging and Troubleshooting

Common Issues

Database Connection Issues

# Check database status
docker ps | grep postgres
docker ps | grep mongodb
docker ps | grep redis

# Restart databases
docker restart postgres mongodb redis

AI Service Issues

# Check API keys
echo $OPENAI_API_KEY
echo $ANTHROPIC_API_KEY

# Test AI services
python scripts/test_ai_services.py

Rendering Issues

# Check Natron installation
which NatronRenderer
NatronRenderer --version

# Test rendering pipeline
python scripts/test_rendering.py

Debugging Tools

  • VS Code Debugger: Set breakpoints in TypeScript/Python
  • Browser DevTools: Frontend debugging
  • Docker Logs: Container debugging
  • Prometheus/Grafana: System monitoring

📈 Performance Optimization

Frontend Optimization

  • Bundle Analysis: npm run analyze
  • Performance Monitoring: Lighthouse audits
  • Code Splitting: Dynamic imports for large components
  • Caching: Redis for API responses

Backend Optimization

  • Database Indexing: Optimize query performance
  • Caching: Redis for frequently accessed data
  • Connection Pooling: Efficient database connections
  • Load Balancing: Distribute traffic across instances

AI/ML Optimization

  • Model Caching: Cache AI model responses
  • Batch Processing: Process multiple requests together
  • GPU Utilization: Optimize for available hardware
  • Memory Management: Efficient memory usage

🚀 Deployment and Production

Local Production Testing

# Build production version
npm run build

# Start production server
npm run start

# Test production build
npm run test:production

Production Deployment

# Deploy to staging
npm run deploy:staging

# Deploy to production
npm run deploy:production

# Monitor deployment
npm run monitor

📞 Getting Help

Internal Resources

  • Team Slack: #animation-designer-bot
  • Code Reviews: GitHub PR discussions
  • Architecture Questions: Tech lead consultation
  • Documentation: This comprehensive guide

External Resources

  • Technology Documentation: Official docs for each technology
  • Community Forums: Stack Overflow, GitHub discussions
  • Training Materials: Online courses and tutorials

Escalation Process

  1. Self-research: Check documentation and existing issues
  2. Team discussion: Ask in team channels
  3. Tech lead consultation: For architectural decisions
  4. External help: Community resources and experts

🎯 Success Metrics

Development Goals

  • Code Quality: Maintain high test coverage (>80%)
  • Performance: Meet response time targets (<2s)
  • Documentation: Keep documentation up-to-date
  • Collaboration: Active participation in code reviews

Learning Objectives

  • System Understanding: Deep knowledge of architecture
  • Technology Mastery: Expertise in assigned technologies
  • Problem Solving: Effective debugging and troubleshooting
  • Team Contribution: Positive impact on team productivity

Welcome to the Animation Designer Bot team! This guide will help you become productive quickly while maintaining the high standards expected in this complex system.

For questions or suggestions about this guide, please create an issue or reach out to the team.