You can find the code for this example in examples/single.ipynb.

​
Setup

Install the agentsjson-core package and the openai package to create and run an agent: 
pip install agentsjson
pip install openai
Load the agents.json file: 
agents_json_url = "https://raw.githubusercontent.com/wild-card-ai/agents-json/refs/heads/master/agents_json/stripe/agents.json"

from agentsjson.core.models import Flow
from agentsjson.core.models.bundle import Bundle
import agentsjson.core as core

# load the agents.json file
data: Bundle = core.load_agents_json(agents_json_url)
flows = data.agentsJson.flows

​
Creating and Running an Agent

Set up your .env file with your API keys. We’ll use Stripe for this agent. 
STRIPE_API_KEY="<your_stripe_api_key>"
OPENAI_API_KEY="<your_openai_api_key>"
Set up your agent: 
from agentsjson.core import ToolFormat

# Format the flows data for the prompt
flows_context = core.flows_prompt(flows)

# Create the system prompt
system_prompt = f"""You are an AI assistant that helps users interact with the Stripe API.
You have access to the following API flows:

{flows_context}

Analyze the user's request and use the appropriate API flows to accomplish the task.
You must give your arguments for the tool call as Structued Outputs JSON with keys `parameters` and `requestBody`"""
Configure authentication: 
from agentsjson.core.models.auth import AuthType, BearerAuthConfig
auth = BearerAuthConfig(type=AuthType.BEARER, token=STRIPE_API_KEY)
Run your agent: 
from openai import OpenAI
from agentsjson.core.executor import execute_flows
client = OpenAI(api_key=OPENAI_API_KEY)

query = "Create a new Stripe product for tie-die tshirts priced at $10, $15, and $30 for small, medium, and large sizes"

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": system_prompt},
        {"role": "user", "content": query}
    ],
    tools=core.flows_tools(flows, format=ToolFormat.OPENAI),
    temperature=0
)

response = execute_flows(response, format=core.ToolFormat.OPENAI, bundle=data, flows=flows, auth=auth)

response