Create Paid AI Agent

A powerful CLI tool for creating production-ready AI agent projects with modern frameworks like Vercel AI SDK and LangGraph. Similar to create-react-app, but specifically designed for building sophisticated, monetizable AI agents with built-in usage tracking and billing.

Quick Start

# Create a new AI agent project (replace 'my-paid-agent' with your desired project name)
npx @paid-ai/create-paid-ai-agent my-paid-agent --api-key <your-paid-token>

Prerequisites

• Node.js: Version 18.0.0 or higher
• npm: Version 8.0.0 or higher
• OpenAI API Key: For GPT-4o-mini and DALL-E access
• Paid.ai Account: For usage tracking and billing

Getting Started

First, create a Paid.ai account to retrieve your paid token for usage tracking and billing:

1. Sign up at https://app.paid.ai/
2. Go to Developers
3. Select Generate API Key

Then create your new project:

npx @paid-ai/create-paid-ai-agent <your-new-project-name> --api-key <your-paid-token>

Parameters:

• <your-new-project-name> - The name for your new AI agent project (this will be the directory name and project name)
• <your-paid-token> - Your Paid.ai API key from the Developers section

Example

npx @paid-ai/create-paid-ai-agent my-awesome-agent --api-key abc123...

This creates a new project directory called my-awesome-agent and sets up your AI agent project.

This will:

1. Ask you to choose an AI framework (AI SDK or LangGraph)
2. Ask you to choose a project type (Fullstack or CLI)
3. Setup an AI agent with the specified name
4. Generate a unique agent ID for tracking - save this agent ID for your .env file

Interactive Setup

The CLI will guide you through the setup process:

? Choose your AI framework:
  ❯ AI SDK (Recommended)
    LangGraph (Advanced)

? Choose your project type:
  ❯ Fullstack (Next.js + API routes)
    CLI Only (Coming Soon)

? Project name: my-ai-agent

Options

AI Frameworks

AI SDK (Recommended)

• Vercel AI SDK v5 integration with Agent class
• Built-in tool orchestration and step counting
• Streaming responses for real-time chat experience
• Easy deployment to Vercel with serverless functions
• Simplified development with minimal boilerplate

LangGraph (Advanced)

• LangChain LangGraph support with StateGraph
• Advanced agent workflows with conditional routing
• Explicit state management with custom reducers
• Fine-grained control over agent behavior
• Complex multi-step reasoning capabilities

Project Types

Fullstack (Next.js + API routes)

• Complete web application with frontend and backend
• API routes for agent endpoints and health checks
• Built-in authentication ready for user management
• Real-time chat interface with streaming responses
• Production deployment optimized for Vercel

CLI Only (Coming Soon)

• Command-line interface for automation
• Perfect for integration with existing tools
• Lightweight deployment options
• Batch processing capabilities

Built-in Tools

All templates include four powerful tools for complete agent development:

1. createElevatorPitch

• Generates compelling elevator pitches for AI agents
• Structured object generation with Zod schemas
• Target audience customization
• Structured output with key points and call-to-action

2. generateLogo

• Creates logos using OpenAI's DALL-E image generation
• Image generation with OpenAI's DALL-E API
• Incorporates extracted vibes for consistent branding
• High-quality 1024x1024 images

3. describeArchitecture

• Provides comprehensive technical architecture recommendations
• Streaming text generation for real-time responses
• Language and framework suggestions
• Deployment considerations

4. extractVibes

• Extracts 3-10 brand descriptors from agent descriptions
• Silent tool handling and RAG-powered context from similar agents
• Uses RAG-powered context from similar agents
• Silent execution (AI SDK) or explicit routing (LangGraph)

Environment Setup

1. Copy the environment template:

   cp .env.example .env

2. Fill out your credentials:

   # Edit .env.local file with your actual API keys
   OPENAI_API_KEY=sk-your-actual-openai-key
   AGENT_ID=your-actual-agent-id
   PAID_API_KEY=your-actual-paid-api-key

3. Never commit .env to version control

Troubleshooting

Common Issues

1. OpenAI API Key Error

Error: Invalid API key

• Verify your OPENAI_API_KEY in .env.local
• Ensure the key has sufficient credits
• Check API key permissions

2. Paid.ai Integration Error

Error: Failed to record usage

• Verify AGENT_ID and PAID_API_KEY in .env.local
• Check Paid.ai dashboard for account status
• Ensure agent ID matches your Paid.ai configuration

Getting Help

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Documentation: Check individual template READMEs for detailed guides

License

MIT License - see LICENSE file for details.