praecise-sdk v0.0.1

Praecise SDK

A comprehensive TypeScript SDK for building AI-powered applications with advanced visualization, website generation, agent systems, and data processing capabilities.

Table of Contents

• Praecise SDK
  • Table of Contents
  • Overview
    • Key Benefits
  • Features
    • Core Systems
  • Installation
  • Core Components
    • Model Management
    • Agent System
    • Website Generation
    • UI Generation
    • Visualization
    • Chain Execution
    • Database Integration
  • Development
    • Project Structure
    • Local Development
  • Deployment
    • Publishing to npm
    • Configuration
  • Best Practices
  • Support
  • Contributing
  • License

Overview

Praecise SDK is a powerful toolkit that enables developers to build sophisticated AI applications. It provides a unified interface for:

• AI model orchestration
• Autonomous agent creation
• Website and UI generation
• Data visualization and analysis
• Complex workflow automation

Key Benefits

• Complete AI Development Stack: Everything needed for modern AI applications
• Type Safety: Built with TypeScript for reliable development
• Modern UI Generation: React components with Tailwind CSS
• Flexible Architecture: Modular design for easy customization
• Production Ready: Enterprise-grade reliability and scalability

Features

Core Systems

1. AI Model Integration

   • OpenAI (GPT-4, GPT-3.5)
   • Anthropic (Claude)
   • Custom model support
   • Model chaining and orchestration

2. Agent System

   • Zero-code agent creation
   • Multi-agent orchestration
   • Tool integration
   • Memory systems (Conversation, Vector)
   • Goal-oriented execution

3. Website Generation

   • Full website scaffolding
   • Multiple website types
     • E-commerce
     • Portfolio
     • Blog
     • SaaS
     • Documentation
     • Dashboard
   • Deployment automation
   • SEO optimization

4. UI Generation

   • React component generation
   • Responsive layouts
   • Theme customization
   • Interactive elements
   • Accessibility compliance

5. Visualization

   • Charts and graphs
   • Data dashboards
   • Real-time updates
   • Custom visualization components

6. Data Processing

   • Text analysis
   • Data transformation
   • Statistical analysis
   • ETL operations

7. Database Integration

   • Vector databases
   • Graph databases
   • Document stores
   • SQL databases

Installation

# Using npm
npm install praecise-sdk

# Using yarn
yarn add praecise-sdk

# Using pnpm
pnpm add praecise-sdk

Core Components

Model Management

The ModelRegistry system manages AI model integrations:

import { PraeciseSDK, ModelConfig } from 'praecise-sdk';

const sdk = new PraeciseSDK();

// Register a model
await sdk.modelRegistry.register({
  name: 'gpt-4',
  provider: 'openai',
  apiKey: process.env.OPENAI_API_KEY,
  parameters: {
    temperature: 0.7,
    maxTokens: 2048
  }
});

// Execute model
const result = await sdk.modelRegistry.execute('gpt-4', {
  prompt: 'Analyze this data...'
});

Agent System

Create and manage autonomous agents with customizable AI models:

import { AgentBuilder, AgentConfig } from 'praecise-sdk';

// Create an agent with specific model
const agentConfig: AgentConfig = {
  name: 'DataAnalysisAgent',
  model: {
    provider: 'anthropic',  // 'openai' | 'anthropic' | 'custom'
    name: 'claude-3',       // Model name
    temperature: 0.7,       // Optional parameters
    maxTokens: 4096
  },
  tools: ['DataAnalyzer', 'TextProcessor'],
  goals: ['Analyze data trends', 'Generate insights'],
  memory: {
    type: 'vector',
    config: { dimensions: 1536 }
  }
};

const agent = await sdk.agentBuilder.createAgentFromDescription(`
  Create an agent that analyzes sales data and generates reports
  with visualizations. Use DataAnalyzer and TextProcessor tools.
`);

// Execute agent
const result = await agent.execute({
  task: 'Analyze monthly sales data and create a trend report',
  data: salesData
});

Website Generation

Generate complete websites with custom functionality and model selection:

import { WebsiteGenerator, WebsiteConfig } from 'praecise-sdk';

// Generate an e-commerce website with specific AI model
const websiteConfig: WebsiteConfig = {
  type: 'ecommerce',
  name: 'My Online Store',
  model: {
    name: 'gpt-4',         // Choose AI model for generation
    provider: 'openai',    // 'openai' | 'anthropic' | 'custom'
    temperature: 0.7,      // Optional parameters
    maxTokens: 4096
  },
  features: {
    auth: true,
    cart: true,
    payments: true,
    admin: true
  },
  deployment: {
    platform: 'vercel',
    domain: 'mystore.com'
  }
};

const website = await sdk.websiteGenerator.generateFromPrompt(`
  Create an e-commerce website with:
  - Modern design
  - Product catalog
  - Shopping cart
  - User authentication
  - Payment integration
  - Admin dashboard
`);

// Deploy website
const deploymentUrl = await website.deploy();

UI Generation

Generate React components and layouts with customizable AI models:

import { UIGenerator, UIConfig } from 'praecise-sdk';

// Generate a dashboard UI with specific model
const uiConfig: UIConfig = {
  type: 'dashboard',
  layout: 'grid',
  model: {
    name: 'claude-3',      // Choose AI model for UI generation
    provider: 'anthropic', // 'openai' | 'anthropic' | 'custom'
    temperature: 0.5,      // Optional parameters
    maxTokens: 4096
  },
  components: {
    header: true,
    sidebar: true,
    charts: ['line', 'bar', 'pie']
  },
  theme: 'modern'
};

const ui = await sdk.uiGenerator.generate(uiConfig);

// Generate a specific component
const component = await sdk.uiGenerator.generateComponent(`
  Create a product card component with:
  - Image
  - Title
  - Price
  - Add to cart button
  - Responsive design
`);

Visualization

Create dynamic data visualizations:

import { VisualizationManager, ChartConfig } from 'praecise-sdk';

// Create a dynamic chart
const chartConfig: ChartConfig = {
  type: 'line',
  data: salesData,
  options: {
    responsive: true,
    animations: true
  }
};

const chart = await sdk.visualizationManager.createVisualization(chartConfig);

// Create a dashboard
const dashboard = await sdk.visualizationManager.createDashboard({
  layout: 'grid',
  components: [
    { type: 'chart', config: chartConfig },
    { type: 'metrics', data: metricsData },
    { type: 'table', data: tableData }
  ]
});

Chain Execution

Build and execute complex AI workflows:

import { ChainExecutor, ChainConfig } from 'praecise-sdk';

// Create an execution chain
const chainConfig: ChainConfig = {
  nodes: [
    {
      id: 'analyze',
      type: 'model',
      config: { model: 'gpt-4' }
    },
    {
      id: 'visualize',
      type: 'tool',
      config: { tool: 'DataVisualizer' }
    }
  ],
  edges: [
    { from: 'analyze', to: 'visualize' }
  ]
};

const chain = await sdk.chainExecutor.createChain(chainConfig);
const result = await chain.execute(inputData);

Database Integration

Work with various database types:

import { DatabaseManager, DatabaseConfig } from 'praecise-sdk';

// Connect to a vector database
const vectorDbConfig: DatabaseConfig = {
  type: 'vector',
  provider: 'pinecone',
  apiKey: process.env.PINECONE_API_KEY,
  environment: 'production'
};

const vectorDb = await sdk.databaseManager.connect(vectorDbConfig);

// Store and query vectors
await vectorDb.upsert(vectors, metadata);
const results = await vectorDb.search(queryVector, { maxResults: 10 });

Development

Project Structure

praecise-sdk/
├── src/
│   ├── core/           # Core functionality
│   ├── agents/         # Agent system
│   ├── models/         # AI models
│   ├── generators/     # Website/UI generators
│   ├── visualization/  # Visualization components
│   ├── database/       # Database connectors
│   └── utils/          # Utilities
├── examples/           # Example implementations
├── tests/             # Test suite
└── docs/              # Documentation

Local Development

# Clone repository
git clone https://github.com/yourusername/praecise-sdk.git

# Install dependencies
pnpm install

# Start development environment
pnpm dev

# Run tests
pnpm test

# Build package
pnpm build

Deployment

Publishing to npm

1. Update version:

npm version [major|minor|patch]

2. Build the package:

pnpm build

3. Publish:

npm publish

Configuration

Ensure your package.json includes:

{
  "name": "praecise-sdk",
  "version": "1.0.0",
  "main": "dist/index.js",
  "types": "dist/index.d.ts",
  "files": [
    "dist",
    "README.md",
    "LICENSE"
  ],
  "scripts": {
    "build": "tsup src/index.ts --dts --format cjs,esm",
    "test": "vitest",
    "lint": "eslint .",
    "prepare": "husky install"
  }
}

Best Practices

1. Model Management

   • Always use environment variables for API keys
   • Implement proper error handling
   • Use model configuration validation

2. Agent Development

   • Define clear goals and constraints
   • Implement proper memory management
   • Use appropriate tool selection

3. Website Generation

   • Follow accessibility guidelines
   • Implement responsive design
   • Use proper SEO practices

4. UI Generation

   • Follow component best practices
   • Implement proper state management
   • Use Tailwind CSS utilities correctly

Support

For support: 1. Check the documentation 2. Search existing issues 3. Join our Discord community 4. Create a new issue

Contributing

We welcome contributions! Please: 1. Fork the repository 2. Create a feature branch 3. Submit a pull request

Follow our Contributing Guidelines for detailed information.

License

MIT License - see LICENSE for details.

© 2024 Praecise SDK Team