Sandboxed Tool Runtime

import { ConnectorRegistry } from "kenpachi";

export const registry = new ConnectorRegistry();

// Register the store API connector on the host
registry.register("store_api", {
  baseUrl: "https://api.yourstore.com/v1",
  authEnvVar: "STORE_API_SECRET_KEY", // Read from host environment variables
  description: "Internal e-commerce store catalog and pricing API",
});

import { Agent, createOpenAIProvider, synthesizeTool } from "kenpachi";
import { registry } from "./server.js";

// 1. Synthesize the tool specification and sandbox logic
const pricingTool = synthesizeTool(
  {
    name: "calculate_discounted_checkout",
    description: "Fetches product base price, applies a 15% VIP discount, and converts to EUR",
    parameters: {
      productId: "string",
      eurExchangeRate: "number",
    },
    // Pure logic body executed safely inside the V8 sandbox
    jsBody: `
      // callConnector appends the base URL and injects the API key automatically
      const product = await callConnector("/products/" + args.productId);
      
      // Perform custom business calculations
      const discountedUSD = product.price * 0.85; // 15% discount
      const finalEUR = discountedUSD * args.eurExchangeRate;

      return {
        productName: product.name,
        originalPriceUSD: product.price,
        finalPriceEUR: Number(finalEUR.toFixed(2))
      };
    `,
    connector: "store_api", // References the registered server connector
  },
  registry
);

// 2. Attach the tool to a kenpachi Agent
const provider = createOpenAIProvider({
  apiKey: process.env.OPENAI_API_KEY!,
  model: "gpt-4o",
});
const agent = new Agent(provider, [pricingTool]);

// 3. Run the Agent (This triggers the LLM call)
async function main() {
  const response = await agent.run(
    "How much will product prod_99182 cost in EUR assuming an exchange rate of 0.92?"
  );

  console.log(response.text);
  // Output: "Product prod_99182 (Wireless Headphones) will cost 78.20 EUR with your VIP discount."
}

main();