Vercel AI SDKとの使用

import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
 
const agent = new Agent({
  name: "WeatherAgent",
  instructions: "Instructions for the agent...",
  model: openai("gpt-4-turbo"), // Model comes directly from AI SDK
});
 
const result = await agent.generate("What is the weather like?");

import { mastra } from "@/src/mastra";
 
export async function POST(req: Request) {
  const { messages } = await req.json();
  const myAgent = mastra.getAgent("weatherAgent");
  const stream = await myAgent.stream(messages);
 
  return stream.toDataStreamResponse();
}

import { useChat } from '@ai-sdk/react';
 
export function ChatComponent() {
  const { messages, input, handleInputChange, handleSubmit } = useChat({
    api: '/path-to-your-agent-stream-api-endpoint'
  });
 
  return (
    <div>
      {messages.map(m => (
        <div key={m.id}>
          {m.role}: {m.content}
        </div>
      ))}
      <form onSubmit={handleSubmit}>
        <input
          value={input}
          onChange={handleInputChange}
          placeholder="Say something..."
        />
      </form>
    </div>
  );
}

import { mastra } from "@/src/mastra";
 
export async function POST(req: Request) {
  const { prompt } = await req.json();
  const myAgent = mastra.getAgent("weatherAgent");
  const stream = await myAgent.stream([{ role: "user", content: prompt }]);
 
  return stream.toDataStreamResponse();
}

import { useCompletion } from "@ai-sdk/react";
 
export function CompletionComponent() {
  const {
    completion,
    input,
    handleInputChange,
    handleSubmit,
  } = useCompletion({
  api: '/path-to-your-agent-stream-api-endpoint'
  });
 
  return (
    <div>
      <form onSubmit={handleSubmit}>
        <input
          value={input}
          onChange={handleInputChange}
          placeholder="Enter a prompt..."
        />
      </form>
      <p>Completion result: {completion}</p>
    </div>
  );
}

import { mastra } from "@/src/mastra";
 
export async function POST(req: Request) {
  const body = await req.json();
  const myAgent = mastra.getAgent("weatherAgent");
  const stream = await myAgent.stream(body, {
    output: z.object({
      weather: z.string(),
    }),
  });
 
  return stream.toTextStreamResponse();
}

import { experimental_useObject as useObject } from '@ai-sdk/react';
 
export default function Page() {
  const { object, submit } = useObject({
    api: '/api/use-object',
    schema: z.object({
      weather: z.string(),
    }),
  });
 
  return (
    <div>
      <button onClick={() => submit('example input')}>Generate</button>
      {object?.weather && <p>{object.weather}</p>}
    </div>
  );
}

import { createDataStream } from "ai";
import { Agent } from "@mastra/core/agent";
 
export const weatherAgent = new Agent({
  name: "Weather Agent",
  instructions: `
          You are a helpful weather assistant that provides accurate weather information.
 
          Your primary function is to help users get weather details for specific locations. When responding:
          - Always ask for a location if none is provided
          - If the location name isn't in English, please translate it
          - If giving a location with multiple parts (e.g. "New York, NY"), use the most relevant part (e.g. "New York")
          - Include relevant details like humidity, wind conditions, and precipitation
          - Keep responses concise but informative
 
          Use the weatherTool to fetch current weather data.
    `,
  model: openai("gpt-4o"),
  tools: { weatherTool },
});
 
const stream = createDataStream({
  async execute(dataStream) {
    // Write data
    dataStream.writeData({ value: "Hello" });
 
    // Write annotation
    dataStream.writeMessageAnnotation({ type: "status", value: "processing" });
 
    //mastra agent stream
    const agentStream = await weatherAgent.stream("What is the weather");
 
    // Merge agent stream
    agentStream.mergeIntoDataStream(dataStream);
  },
  onError: (error) => `Custom error: ${error.message}`,
});

import { mastra } from "@/src/mastra";
 
export async function POST(req: Request) {
  const { messages } = await req.json();
  const myAgent = mastra.getAgent("weatherAgent");
  //mastra agent stream
  const agentStream = await myAgent.stream(messages);
 
  const response = createDataStreamResponse({
    status: 200,
    statusText: "OK",
    headers: {
      "Custom-Header": "value",
    },
    async execute(dataStream) {
      // Write data
      dataStream.writeData({ value: "Hello" });
 
      // Write annotation
      dataStream.writeMessageAnnotation({
        type: "status",
        value: "processing",
      });
 
      // Merge agent stream
      agentStream.mergeIntoDataStream(dataStream);
    },
    onError: (error) => `Custom error: ${error.message}`,
  });
 
  return response;
}