OpenCommerce SDK Integration with CrewAI

OpenCommerce is a payment network designed for AI agents, enabling them to pay for services in real-time. This guide demonstrates how to integrate OpenCommerce with CrewAI for orchestrating payments between agents and services.

⚠️ Important: OpenCommerce SDK is currently in development and only supports testnet operations. Mainnet support will be added in future releases.

Key Features

• Pay-as-you-go Services: Agents can access and pay for AI services in real-time
• Built-in Account Management: Automatic account creation and balance management
• Service Directory: Centralized directory of available AI services
• Blockchain-based Payments: Secure transactions using USDC on Base network

Quick Start

1. Install Dependencies

pip install opencommerce-sdk crewai

2. Set Up Environment Variables

Create a .env file in your project root:

OPENAI_API_KEY=your_api_key_here

Then load it in your Python code:

from dotenv import load_dotenv
load_dotenv()

3. Initialize OpenCommerce SDK

from opencommerce_sdk import OpenCommerceAccountToolkit

# Initialize the SDK
sdk = OpenCommerceAccountToolkit(network="testnet")
print("✅ SDK initialized successfully")

# Get the account address
address = sdk.get_account_address()
print(f"My account address: {address}")

4. Create Tools for Services

class TavilySearchTool(BaseTool):
    name: str = "Tavily Search"
    description: str = "Search the internet for information using Tavily"
    
    def _run(self, query: str) -> str:
        return self.sdk.use_service('tavily_search', {'query': query})

class GPTResearchTool(BaseTool):
    name: str = "GPT Research"
    description: str = "Conduct detailed analysis using GPT Researcher"
    
    def _run(self, query: str) -> str:
        return self.sdk.use_service('gpt_researcher', {'query': query})

5. Create Agents with Payment Capabilities

market_research_agent = Agent(
    role="Market Research Specialist",
    goal="Gather comprehensive market data",
    tools=[TavilySearchTool(sdk)],
    verbose=True
)

tech_analysis_agent = Agent(
    role="Technology Analyst",
    goal="Analyze technological developments",
    tools=[GPTResearchTool(sdk)],
    verbose=True
)

How It Works

1. Agent Request: Agent requests a service (e.g., Tavily search or GPT research)
2. Service Directory: OpenCommerce gets service details and pricing
3. Payment: SDK handles USDC payment on Base network
4. Service Execution: After payment confirmation, service is executed
5. Results: Service results are returned to the agent

Example Use Case

The included example demonstrates a market research workflow where:

• Market Research Agent uses Tavily Search for data gathering
• Technology Analyst uses GPT Researcher for analysis
• Each service call is automatically paid for using USDC

For the complete example implementation, see the full code in this repository.

Additional Resources

For more detailed information about the OpenCommerce SDK, including:

• Complete API documentation
• Additional code examples
• Service directory details
• Contribution guidelines

Visit the OpenCommerce SDK GitHub Repository.

Funding Options

Currently, OpenCommerce SDK only supports testnet operations for development and testing purposes.

Getting Test USDC

1. Visit the Circle USDC Faucet
2. Select Base Sepolia network
3. Request test USDC tokens

To check your balance:

# Get current balance
balance = sdk.get_balance()
print(f"Current balance: {balance} USDC")