ai-sdk-6-skills

import { tool } from 'ai';
import { z } from 'zod';
 
const paymentTool = tool({
  description: 'Process a payment',
  inputSchema: z.object({
    amount: z.number(),
    recipient: z.string(),
  }),
  needsApproval: true, // Require approval
  execute: async ({ amount, recipient }) => {
    return { success: true, id: 'txn-123' };
  },
});

export function PaymentToolView({ invocation, addToolApprovalResponse }) {
  if (invocation.state === 'approval-requested') {
    return (
      <div>
        <p>Process payment of ${invocation.input.amount} to {invocation.input.recipient}?</p>
        <button
          onClick={() =>
            addToolApprovalResponse({
              id: invocation.approval.id,
              approved: true,
            })
          }
        >
          Approve
        </button>
        <button
          onClick={() =>
            addToolApprovalResponse({
              id: invocation.approval.id,
              approved: false,
            })
          }
        >
          Deny
        </button>
      </div>
    );
  }
  return null;
}

import { ToolLoopAgent, Output } from 'ai';
import { z } from 'zod';
 
const agent = new ToolLoopAgent({
  model: 'groq/llama-3.3-70b-versatile',
  tools: { /* ... */ },
  output: Output.object({
    schema: z.object({
      summary: z.string(),
      temperature: z.number(),
      recommendation: z.string(),
    }),
  }),
});
 
const { output } = await agent.generate({
  prompt: 'What is the weather in San Francisco and what should I wear?',
});
 
console.log(output);
// { summary: '...', temperature: 72, recommendation: '...' }

import { rerank } from 'ai';
import { cohere } from '@ai-sdk/cohere';
 
const { ranking } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents: [
    'sunny day at the beach',
    'rainy afternoon in the city',
    'snowy night in the mountains',
  ],
  query: 'talk about rain',
  topN: 2,
});
 
console.log(ranking);
// [
//   { originalIndex: 1, score: 0.9, document: 'rainy afternoon...' },
//   { originalIndex: 0, score: 0.3, document: 'sunny day...' }
// ]

pnpm add @ai-sdk/groq

GROQ_API_KEY=your_groq_api_key

import { groq } from '@ai-sdk/groq';
import { generateText } from 'ai';
 
const { text } = await generateText({
  model: groq('llama-3.3-70b-versatile'),
  prompt: 'Write a TypeScript function to compute Fibonacci.',
});
 
console.log(text);

import { groq } from '@ai-sdk/groq';
import { generateObject } from 'ai';
import { z } from 'zod';
 
const result = await generateObject({
  model: groq('llama-3.3-70b-versatile'),
  schema: z.object({
    recipe: z.object({
      name: z.string(),
      ingredients: z.array(z.string()),
      instructions: z.array(z.string()),
    }),
  }),
  prompt: 'Generate a simple pasta recipe.',
  providerOptions: {
    groq: {
      structuredOutputs: true, // Enable for supported models
    },
  },
});
 
console.log(JSON.stringify(result.object, null, 2));

import { groq } from '@ai-sdk/groq';
import { generateText, tool } from 'ai';
import { z } from 'zod';
 
const weatherTool = tool({
  description: 'Get weather for a city',
  inputSchema: z.object({ city: z.string() }),
  execute: async ({ city }) => ({ temp: 72, condition: 'sunny' }),
});
 
const { text } = await generateText({
  model: groq('llama-3.3-70b-versatile'),
  prompt: 'What is the weather in NYC and LA?',
  tools: { weather: weatherTool },
});
 
console.log(text);

import { groq } from '@ai-sdk/groq';
import { generateText } from 'ai';
 
const { text } = await generateText({
  model: groq('qwen/qwen3-32b'),
  providerOptions: {
    groq: {
      reasoningFormat: 'parsed', // 'parsed', 'hidden', or 'raw'
      reasoningEffort: 'default', // low, medium, high
    },
  },
  prompt: 'How many "r"s are in the word "strawberry"?',
});
 
console.log(text);

import { groq } from '@ai-sdk/groq';
import { generateText } from 'ai';
 
const { text } = await generateText({
  model: groq('meta-llama/llama-4-scout-17b-16e-instruct'), // Multi-modal model
  messages: [
    {
      role: 'user',
      content: [
        { type: 'text', text: 'What is in this image?' },
        { type: 'image', image: 'https://example.com/image.jpg' },
      ],
    },
  ],
});
 
console.log(text);

AI_GATEWAY_API_KEY=your_gateway_api_key

import { createGateway } from 'ai';
 
const gateway = createGateway({
  apiKey: process.env.AI_GATEWAY_API_KEY,
});

# Start dev with automatic token management
vercel dev

import { generateText } from 'ai';
 
// Plain model string format: creator/model-name
const { text } = await generateText({
  model: 'openai/gpt-5',
  prompt: 'Explain quantum computing.',
});
 
console.log(text);

import { createGateway } from 'ai';
 
const gateway = createGateway({
  apiKey: process.env.AI_GATEWAY_API_KEY,
});
 
const { text } = await generateText({
  model: gateway('anthropic/claude-sonnet-4'),
  prompt: 'Write a haiku about AI.',
});
 
console.log(text);

import { gateway } from 'ai';
 
const availableModels = await gateway.getAvailableModels();
 
availableModels.models.forEach((model) => {
  console.log(`${model.id}: ${model.name}`);
  if (model.pricing) {
    console.log(`  Input: $${model.pricing.input}/token`);
    console.log(`  Output: $${model.pricing.output}/token`);
  }
});
 
// Use first model
const { text } = await generateText({
  model: availableModels.models[0].id,
  prompt: 'Hello world',
});

import { gateway } from 'ai';
 
const credits = await gateway.getCredits();
console.log(`Balance: ${credits.balance} credits`);
console.log(`Total used: ${credits.total_used} credits`);

import { streamText } from 'ai';
 
const { textStream } = await streamText({
  model: 'openai/gpt-5',
  prompt: 'Explain serverless architecture.',
});
 
for await (const chunk of textStream) {
  process.stdout.write(chunk);
}

import { generateText, tool } from 'ai';
import { z } from 'zod';
 
const weatherTool = tool({
  description: 'Get weather',
  inputSchema: z.object({ location: z.string() }),
  execute: async ({ location }) => `Sunny in ${location}`,
});
 
const { text } = await generateText({
  model: 'xai/grok-4', // Via Gateway
  prompt: 'What is the weather in SF?',
  tools: { getWeather: weatherTool },
});
 
console.log(text);

import { generateText } from 'ai';
import type { GatewayProviderOptions } from '@ai-sdk/gateway';
 
const { text } = await generateText({
  model: 'anthropic/claude-sonnet-4',
  prompt: 'Use my Anthropic account',
  providerOptions: {
    gateway: {
      byok: {
        anthropic: [{ apiKey: 'sk-ant-...' }],
      },
    } satisfies GatewayProviderOptions,
  },
});

import { generateText, stepCountIs } from 'ai';
import { openai } from '@ai-sdk/openai';
 
const result = await generateText({
  model: 'openai/gpt-5-mini',
  prompt: 'What is the Vercel AI Gateway?',
  stopWhen: stepCountIs(10),
  tools: {
    web_search: openai.tools.webSearch({}),
  },
});
 
console.log(result.text);

import { generateText } from 'ai';
import type { GatewayProviderOptions } from '@ai-sdk/gateway';
 
const { text } = await generateText({
  model: 'openai/gpt-4o', // Primary model
  prompt: 'Write a TypeScript haiku',
  providerOptions: {
    gateway: {
      order: ['vertex', 'anthropic'], // Try Vertex AI first, then Anthropic
      only: ['vertex', 'anthropic'], // Only allow these providers
      models: ['openai/gpt-5-nano', 'gemini-2.0-flash'], // Fallback models
      user: 'user-123',
      tags: ['code-gen', 'v2'],
    } satisfies GatewayProviderOptions,
  },
});
 
// Fallback sequence:
// 1. Try vertex with openai/gpt-4o
// 2. Try anthropic with openai/gpt-4o
// 3. Try vertex with openai/gpt-5-nano
// 4. Try anthropic with openai/gpt-5-nano
// etc.

import { generateText } from 'ai';
import type { GatewayProviderOptions } from '@ai-sdk/gateway';
 
const { text } = await generateText({
  model: 'anthropic/claude-sonnet-4',
  prompt: 'Summarize this document...',
  providerOptions: {
    gateway: {
      user: 'user-abc-123', // Track per end-user
      tags: ['document-summary', 'premium-feature'],
    } satisfies GatewayProviderOptions,
  },
});
 
// View analytics by user and feature in Vercel Dashboard

import { generateText } from 'ai';
import type { GatewayProviderOptions } from '@ai-sdk/gateway';
 
const { text } = await generateText({
  model: 'anthropic/claude-sonnet-4',
  prompt: 'Process sensitive document...',
  providerOptions: {
    gateway: {
      zeroDataRetention: true, // Enforce zero data retention
    } satisfies GatewayProviderOptions,
  },
});

import { ToolLoopAgent } from 'ai';
import { z } from 'zod';
 
const supportAgent = new ToolLoopAgent({
  model: 'groq/llama-3.3-70b-versatile',
  callOptionsSchema: z.object({
    userId: z.string(),
    accountType: z.enum(['free', 'pro', 'enterprise']),
  }),
  instructions: 'You are a support agent.',
  prepareCall: ({ options, ...settings }) => ({
    ...settings,
    instructions:
      settings.instructions +
      `\nUser: ${options.userId}, Account: ${options.accountType}`,
  }),
});
 
const result = await supportAgent.generate({
  prompt: 'How do I upgrade?',
  options: {
    userId: 'user-456',
    accountType: 'free',
  },
});

import { createAgentUIStreamResponse } from 'ai';
import { useChat } from '@ai-sdk/react';
import { InferAgentUIMessage } from 'ai';
 
// Server-side
export async function POST(request: Request) {
  const { messages } = await request.json();
  return createAgentUIStreamResponse({
    agent: weatherAgent,
    messages,
  });
}
 
// Client-side
type AgentMessage = InferAgentUIMessage<typeof weatherAgent>;
const { messages, sendMessage } = useChat<AgentMessage>();

const ragAgent = new ToolLoopAgent({
  model: 'groq/llama-3.3-70b-versatile',
  tools: {
    searchDocs: tool({
      description: 'Search documentation',
      inputSchema: z.object({ query: z.string() }),
      execute: async ({ query }) => {
        // Call vector DB (Upstash, Pinecone, etc.)
        return { docs: [/* ... */] };
      },
    }),
  },
  instructions: 'Answer questions by searching docs.',
});

const { text } = await generateText({
  model: 'anthropic/claude-sonnet-4',
  prompt: 'Complex task requiring reasoning',
  providerOptions: {
    gateway: {
      models: ['openai/gpt-5', 'gemini-2.0-flash'],
    },
  },
});

const isSensitive = userQuery.includes('payment');
const model = isSensitive 
  ? 'anthropic/claude-sonnet-4' 
  : 'openai/gpt-5-nano';
 
const { text } = await generateText({
  model,
  prompt: userQuery,
});