Vercel AI SDK

Floe actions are bound to the Vercel AI SDK via the AgentKit adapter.

npm install floe-agent @coinbase/agentkit @coinbase/agentkit-vercel-ai-sdk ai @ai-sdk/openai

import { AgentKit } from "@coinbase/agentkit";
import { getVercelAITools } from "@coinbase/agentkit-vercel-ai-sdk";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
import { floeActionProvider } from "floe-agent";

const agentkit = await AgentKit.from({
  walletProvider,
  actionProviders: [floeActionProvider({ facilitatorApiKey: process.env.FLOE_API_KEY })],
});
const tools = await getVercelAITools(agentkit);

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  maxSteps: 10,
  prompt: "Call my paid x402 API and tell me what it cost.",
});

Scope. In this example the gpt-4o model tokens are billed by OpenAI against your own @ai-sdk/openai key — a call that bypasses Floe is the one thing a policy can't see. To bring LLM tokens onto the same ledger and caps as your x402 payments, route the model through Floe: keyless via POST /v1/chat/completions (fully-qualified ids like openai/gpt-4o, no provider key), or BYOK via /v1/llm/chat/completions with X-Floe-Provider-Key (host credit-api.floelabs.xyz either way). Then one budget bounds both. See Floe Inference and Spend Controls.

Example

The dedicated Vercel-AI-SDK chatbot example has been retired. For a runnable AgentKit client that pays an x402 endpoint through the Floe proxy, see floe-cookbook/x402-client, or browse the full cookbook index to pick the example closest to your stack.