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Development

Contributing to NeuroLink and extending its capabilities for your specific needs.

🎯 Development Hub

This section covers everything needed for contributing to NeuroLink, understanding its architecture, and extending its functionality.

How to contribute to NeuroLink, including setup, coding standards, and submission guidelines.

Comprehensive testing strategies, test suite organization, and validation procedures.

Deep dive into NeuroLink's architecture, design patterns, and system organization.

Guide for upgrading from older architectures to the new unified factory pattern system.

Documentation for package version overrides, security vulnerabilities, and maintenance procedures.

🚀 Quick Development Setup

# Clone the repository
git clone https://github.com/juspay/neurolink
cd neurolink

# Install dependencies
pnpm install

# Setup git hooks for build rule enforcement
npx husky install

# Complete automated setup
pnpm setup:complete

# Run comprehensive tests
pnpm test:adaptive

# Build the project with validation
pnpm build:complete

# Validate build rules and quality
pnpm run validate:all

# Basic development environment
pnpm install
pnpm env:setup

# Start development
pnpm dev

# Run quick tests
pnpm test:smart

# Install docs dependencies
pip install -r requirements.txt

# Serve documentation locally
mkdocs serve

# Build documentation
mkdocs build

🏗️ Architecture Overview

NeuroLink uses a Factory Pattern architecture that provides:

Core Components

graph TD
    A[NeuroLink SDK] --> B[Provider Factory]
    B --> C[BaseProvider]
    C --> D[OpenAI Provider]
    C --> E[Google AI Provider]
    C --> F[Anthropic Provider]
    C --> G[Other Providers]

    A --> H[MCP System]
    H --> I[Built-in Tools]
    H --> J[Custom Tools]
    H --> K[External Servers]

    A --> L[Analytics System]
    A --> M[Evaluation System]
    A --> N[Streaming System]

Design Principles

  • Unified Interface: All providers implement the same AIProvider interface
  • Type Safety: Full TypeScript support with strict typing
  • Extensibility: Easy to add new providers and tools
  • Performance: Optimized for production use
  • Reliability: Comprehensive error handling and fallbacks

🔧 Development Features

Enterprise Automation (72+ Commands)

NeuroLink includes comprehensive automation for development:

# Environment & Setup
pnpm setup:complete        # Complete project setup
pnpm env:setup             # Environment configuration
pnpm env:validate          # Configuration validation

# Testing & Quality
pnpm test:adaptive         # Intelligent test selection
pnpm test:providers        # AI provider validation
pnpm quality:check         # Full quality pipeline

# Content Generation
pnpm content:screenshots   # Automated screenshot capture
pnpm content:videos        # Video generation
pnpm docs:sync            # Documentation synchronization

# Build & Deployment
pnpm build:complete        # 7-phase enterprise pipeline
pnpm dev:health           # System health monitoring

Smart Testing System

  • Adaptive test selection based on code changes
  • Provider validation across all AI services
  • Performance benchmarking and regression detection
  • Comprehensive coverage reporting

Automated Content Generation

  • Screenshot automation for documentation
  • Video generation for demonstrations
  • Documentation synchronization across files
  • Asset optimization and management

🧪 Testing Philosophy

NeuroLink uses a multi-layered testing approach:

Test Categories

  1. Unit Tests - Individual component testing
  2. Integration Tests - Provider and tool interaction
  3. End-to-End Tests - Complete workflow validation
  4. Performance Tests - Speed and resource usage
  5. Regression Tests - Prevent breaking changes

Test Organization

test/
├── unit/              # Unit tests
├── integration/       # Integration tests
├── e2e/              # End-to-end tests
├── performance/      # Performance benchmarks
├── fixtures/         # Test data and mocks
└── utils/            # Testing utilities

Running Tests

# Smart test runner (recommended)
pnpm test:adaptive

# Full test suite
pnpm test:run

# Specific test categories
pnpm test:unit
pnpm test:integration
pnpm test:e2e

# With coverage
pnpm test:coverage

🎨 Code Style & Standards

TypeScript Configuration

  • Strict mode enabled for maximum type safety
  • Path mapping for clean imports
  • ESLint and Prettier for consistent formatting
  • Documentation comments for all public APIs

Naming Conventions

  • PascalCase for classes and interfaces
  • camelCase for functions and variables
  • kebab-case for file names
  • UPPER_CASE for constants

File Organization

src/
├── cli/              # Command-line interface
├── lib/              # Core library
│   ├── core/         # Core functionality
│   ├── providers/    # AI provider implementations
│   ├── mcp/          # MCP tool system
│   ├── types/        # TypeScript definitions
│   └── utils/        # Utility functions
├── test/             # Test files
└── tools/            # Development tools

🔄 Contribution Workflow

1. Setup Development Environment

# Fork and clone
git clone https://github.com/YOUR_USERNAME/neurolink
cd neurolink
pnpm setup:complete

2. Create Feature Branch

# Create semantic branch
git checkout -b feat/your-feature-name
git checkout -b fix/issue-description
git checkout -b docs/documentation-update

3. Development Process

# Make changes
pnpm dev                # Start development server
pnpm test:adaptive      # Run relevant tests
pnpm quality:check      # Validate code quality

4. Commit & Submit

# Commit with semantic messages
git commit -m "feat: add new provider support"
git commit -m "fix: resolve streaming timeout issue"
git commit -m "docs: update API documentation"

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

📚 Learning Resources

Architecture Deep Dive

Best Practices

  • Error handling patterns and strategies
  • Performance optimization techniques
  • Testing methodologies and coverage
  • Documentation standards and automation

Community

  • GitHub Discussions for questions and ideas
  • Issue tracking for bugs and feature requests
  • Code reviews for learning and improvement
  • Release notes for staying updated