📄 ai-sdk/cookbook/rsc/call-tools

Some models allow developers to provide a list of tools that can be called at any time during a generation. This is useful for extending the capabilities of a language model to either use logic or data to interact with systems external to the model.

http://localhost:3000

User: How is it going?

Assistant: All good, how may I help you?

What is 24 celsius in fahrenheit?

Send Message

Client

Let's create a simple conversation between a user and model and place a button that will call continueConversation.

app/page.tsx

'use client';
import { useState } from 'react';import { Message, continueConversation } from './actions';
// Allow streaming responses up to 30 secondsexport const maxDuration = 30;
export default function Home() {  const [conversation, setConversation] = useState<Message[]>([]);  const [input, setInput] = useState<string>('');
  return (    <div>      <div>        {conversation.map((message, index) => (          <div key={index}>            {message.role}: {message.content}          </div>        ))}      </div>
      <div>        <input          type="text"          value={input}          onChange={event => {            setInput(event.target.value);          }}        />        <button          onClick={async () => {            const { messages } = await continueConversation([              ...conversation,              { role: 'user', content: input },            ]);
            setConversation(messages);          }}        >          Send Message        </button>      </div>    </div>  );}

Server

Now, let's implement the continueConversation action that uses generateText to generate a response to the user's question. We will use the tools parameter to specify our own function called celsiusToFahrenheit that will convert a user given value in celsius to fahrenheit.

We will use zod to specify the schema for the celsiusToFahrenheit function's parameters.

app/actions.ts

'use server';
import { generateText } from 'ai';import { openai } from '@ai-sdk/openai';import { z } from 'zod';
export interface Message {  role: 'user' | 'assistant';  content: string;}
export async function continueConversation(history: Message[]) {  'use server';
  const { text, toolResults } = await generateText({    model: openai('gpt-3.5-turbo'),    system: 'You are a friendly assistant!',    messages: history,    tools: {      celsiusToFahrenheit: {        description: 'Converts celsius to fahrenheit',        inputSchema: z.object({          value: z.string().describe('The value in celsius'),        }),        execute: async ({ value }) => {          const celsius = parseFloat(value);          const fahrenheit = celsius * (9 / 5) + 32;          return `${celsius}°C is ${fahrenheit.toFixed(2)}°F`;        },      },    },  });
  return {    messages: [      ...history,      {        role: 'assistant' as const,        content:          text || toolResults.map(toolResult => toolResult.result).join('\n'),      },    ],  };}

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Call Tools

Client

Server

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