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import { generateText } from 'ai';
import { openai } from '@ai-sdk/openai';

const result = await generateText({
  model: openai('gpt-4-turbo'),
  prompt: 'What is TypeScript?',
});

console.log(result.text);

import { streamText } from 'ai';
import { anthropic } from '@ai-sdk/anthropic';

const stream = streamText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  messages: [
    { role: 'user', content: 'Tell me a story' },
  ],
});

for await (const chunk of stream.textStream) {
  process.stdout.write(chunk);
}

import { generateObject } from 'ai';
import { openai } from '@ai-sdk/openai';
import { z } from 'zod';

const result = await generateObject({
  model: openai('gpt-4'),
  schema: z.object({
    name: z.string(),
    age: z.number(),
    skills: z.array(z.string()),
  }),
  prompt: 'Generate a person profile for a software engineer',
});

console.log(result.object);
// { name: "Alice", age: 28, skills: ["TypeScript", "React"] }

async function generateText(options: {
  model: LanguageModel;
  prompt?: string;
  messages?: Array<ModelMessage>;
  system?: string;
  tools?: Record<string, Tool>;
  maxOutputTokens?: number;
  temperature?: number;
  stopWhen?: StopCondition;
  // ... other options
}): Promise<GenerateTextResult>

import { generateText } from 'ai';
import { openai } from '@ai-sdk/openai';

const result = await generateText({
  model: openai('gpt-4-turbo'),
  prompt: 'Explain quantum computing',
  maxOutputTokens: 500,
  temperature: 0.7,
});

console.log(result.text);
console.log(`Tokens: ${result.usage.totalTokens}`);

const result = await generateText({
  model: openai('gpt-4-turbo'),
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'What is the weather?' },
    { role: 'assistant', content: 'I need your location.' },
    { role: 'user', content: 'San Francisco' },
  ],
});

import { tool } from 'ai';
import { z } from 'zod';

const result = await generateText({
  model: openai('gpt-4'),
  tools: {
    weather: tool({
      description: 'Get the weather for a location',
      inputSchema: z.object({
        location: z.string(),
      }),
      execute: async ({ location }) => {
        // API call here
        return { temperature: 72, condition: 'sunny' };
      },
    }),
  },
  prompt: 'What is the weather in Tokyo?',
});

import { AI_APICallError, AI_NoContentGeneratedError } from 'ai';

try {
  const result = await generateText({
    model: openai('gpt-4-turbo'),
    prompt: 'Hello',
  });
  console.log(result.text);
} catch (error) {
  if (error instanceof AI_APICallError) {
    console.error('API call failed:', error.message);
    // Check rate limits, API key, network
  } else if (error instanceof AI_NoContentGeneratedError) {
    console.error('No content generated');
    // Prompt may have been filtered
  } else {
    console.error('Unknown error:', error);
  }
}

function streamText(options: {
  model: LanguageModel;
  prompt?: string;
  messages?: Array<ModelMessage>;
  system?: string;
  tools?: Record<string, Tool>;
  maxOutputTokens?: number;
  temperature?: number;
  stopWhen?: StopCondition;
  // ... other options
}): StreamTextResult

import { streamText } from 'ai';
import { anthropic } from '@ai-sdk/anthropic';

const stream = streamText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  prompt: 'Write a poem about AI',
});

// Stream to console
for await (const chunk of stream.textStream) {
  process.stdout.write(chunk);
}

// Or get final result
const finalResult = await stream.result;
console.log(finalResult.text);

const stream = streamText({
  model: openai('gpt-4'),
  tools: {
    // ... tools definition
  },
  prompt: 'What is the weather?',
});

// Stream text chunks
for await (const chunk of stream.textStream) {
  process.stdout.write(chunk);
}

const stream = streamText({
  model: openai('gpt-4-turbo'),
  prompt: 'Explain AI',
});

// Option 1: Text stream
for await (const text of stream.textStream) {
  console.log(text);
}

// Option 2: Full stream (includes metadata)
for await (const part of stream.fullStream) {
  if (part.type === 'text-delta') {
    console.log(part.textDelta);
  } else if (part.type === 'tool-call') {
    console.log('Tool called:', part.toolName);
  }
}

// Option 3: Wait for final result
const result = await stream.result;
console.log(result.text, result.usage);

// Next.js API Route
import { streamText } from 'ai';
import { openai } from '@ai-sdk/openai';

export async function POST(request: Request) {
  const { messages } = await request.json();

  const stream = streamText({
    model: openai('gpt-4-turbo'),
    messages,
  });

  // Return stream to client
  return stream.toDataStreamResponse();
}

// Recommended: Use onError callback (added in v4.1.22)
const stream = streamText({
  model: openai('gpt-4-turbo'),
  prompt: 'Hello',
  onError({ error }) {
    console.error('Stream error:', error);
    // Custom error handling
  },
});

for await (const chunk of stream.textStream) {
  process.stdout.write(chunk);
}

// Alternative: Manual try-catch
try {
  const stream = streamText({
    model: openai('gpt-4-turbo'),
    prompt: 'Hello',
  });

  for await (const chunk of stream.textStream) {
    process.stdout.write(chunk);
  }
} catch (error) {
  console.error('Stream error:', error);
}

async function generateObject<T>(options: {
  model: LanguageModel;
  schema: z.Schema<T>;
  prompt?: string;
  messages?: Array<ModelMessage>;
  system?: string;
  mode?: 'auto' | 'json' | 'tool';
  // ... other options
}): Promise<GenerateObjectResult<T>>

import { generateObject } from 'ai';
import { openai } from '@ai-sdk/openai';
import { z } from 'zod';

const result = await generateObject({
  model: openai('gpt-4'),
  schema: z.object({
    recipe: z.object({
      name: z.string(),
      ingredients: z.array(z.object({
        name: z.string(),
        amount: z.string(),
      })),
      instructions: z.array(z.string()),
    }),
  }),
  prompt: 'Generate a recipe for chocolate chip cookies',
});

console.log(result.object.recipe);

const PersonSchema = z.object({
  name: z.string(),
  age: z.number(),
  address: z.object({
    street: z.string(),
    city: z.string(),
    country: z.string(),
  }),
  hobbies: z.array(z.string()),
});

const result = await generateObject({
  model: openai('gpt-4'),
  schema: PersonSchema,
  prompt: 'Generate a person profile',
});

// Array of objects
const result = await generateObject({
  model: openai('gpt-4'),
  schema: z.object({
    people: z.array(z.object({
      name: z.string(),
      role: z.enum(['engineer', 'designer', 'manager']),
    })),
  }),
  prompt: 'Generate a team of 5 people',
});

// Union types
const result = await generateObject({
  model: openai('gpt-4'),
  schema: z.discriminatedUnion('type', [
    z.object({ type: z.literal('text'), content: z.string() }),
    z.object({ type: z.literal('image'), url: z.string() }),
  ]),
  prompt: 'Generate content',
});

import { AI_NoObjectGeneratedError, AI_TypeValidationError } from 'ai';

try {
  const result = await generateObject({
    model: openai('gpt-4'),
    schema: z.object({ name: z.string() }),
    prompt: 'Generate a person',
  });
} catch (error) {
  if (error instanceof AI_NoObjectGeneratedError) {
    console.error('Model did not generate valid object');
    // Try simplifying schema or adding examples
  } else if (error instanceof AI_TypeValidationError) {
    console.error('Zod validation failed:', error.message);
    // Schema doesn't match output
  }
}

function streamObject<T>(options: {
  model: LanguageModel;
  schema: z.Schema<T>;
  prompt?: string;
  messages?: Array<ModelMessage>;
  mode?: 'auto' | 'json' | 'tool';
  // ... other options
}): StreamObjectResult<T>

import { streamObject } from 'ai';
import { google } from '@ai-sdk/google';
import { z } from 'zod';

const stream = streamObject({
  model: google('gemini-2.5-pro'),
  schema: z.object({
    characters: z.array(z.object({
      name: z.string(),
      class: z.string(),
      stats: z.object({
        hp: z.number(),
        mana: z.number(),
      }),
    })),
  }),
  prompt: 'Generate 3 RPG characters',
});

// Stream partial updates
for await (const partialObject of stream.partialObjectStream) {
  console.log(partialObject);
  // { characters: [{ name: "Aria" }] }
  // { characters: [{ name: "Aria", class: "Mage" }] }
  // { characters: [{ name: "Aria", class: "Mage", stats: { hp: 100 } }] }
  // ...
}

// Server endpoint
export async function POST(request: Request) {
  const { prompt } = await request.json();

  const stream = streamObject({
    model: openai('gpt-4'),
    schema: z.object({
      summary: z.string(),
      keyPoints: z.array(z.string()),
    }),
    prompt,
  });

  return stream.toTextStreamResponse();
}

// Client (with useObject hook from ai-sdk-ui)
const { object, isLoading } = useObject({
  api: '/api/analyze',
  schema: /* same schema */,
});

// Render partial object as it streams
{object?.summary && <p>{object.summary}</p>}
{object?.keyPoints?.map(point => <li key={point}>{point}</li>)}

import { openai } from '@ai-sdk/openai';
import { generateText } from 'ai';

// API key from environment (recommended)
// OPENAI_API_KEY=sk-...
const model = openai('gpt-4-turbo');

// Or explicit API key
const model = openai('gpt-4', {
  apiKey: process.env.OPENAI_API_KEY,
});

// Available models
const gpt5 = openai('gpt-5');           // Latest (released August 2025)
const gpt4 = openai('gpt-4-turbo');
const gpt35 = openai('gpt-3.5-turbo');

const result = await generateText({
  model: gpt4,
  prompt: 'Hello',
});

const result = await generateText({
  model: openai('gpt-4'),
  prompt: 'Hello',
  maxRetries: 3,  // Built-in retry
});

import { anthropic } from '@ai-sdk/anthropic';

// ANTHROPIC_API_KEY=sk-ant-...
const claude = anthropic('claude-sonnet-4-5-20250929');

// Available models (Claude 4.x family, released 2025)
const sonnet45 = anthropic('claude-sonnet-4-5-20250929');  // Latest, recommended
const sonnet4 = anthropic('claude-sonnet-4-20250522');     // Released May 2025
const opus4 = anthropic('claude-opus-4-20250522');         // Highest quality

// Legacy models (Claude 3.x, deprecated)
// const sonnet35 = anthropic('claude-3-5-sonnet-20241022');  // Use Claude 4.x instead
// const opus3 = anthropic('claude-3-opus-20240229');
// const haiku3 = anthropic('claude-3-haiku-20240307');

const result = await generateText({
  model: sonnet45,
  prompt: 'Explain quantum entanglement',
});

import { google } from '@ai-sdk/google';

// GOOGLE_GENERATIVE_AI_API_KEY=...
const gemini = google('gemini-2.5-pro');

// Available models (all GA since June-July 2025)
const pro = google('gemini-2.5-pro');
const flash = google('gemini-2.5-flash');
const lite = google('gemini-2.5-flash-lite');

const result = await generateText({
  model: pro,
  prompt: 'Analyze this data',
});

import { Hono } from 'hono';
import { generateText } from 'ai';
import { createWorkersAI } from 'workers-ai-provider';

interface Env {
  AI: Ai;
}

const app = new Hono<{ Bindings: Env }>();

app.post('/chat', async (c) => {
  // Create provider inside handler (avoid startup overhead)
  const workersai = createWorkersAI({ binding: c.env.AI });

  const result = await generateText({
    model: workersai('@cf/meta/llama-3.1-8b-instruct'),
    prompt: 'What is Cloudflare?',
  });

  return c.json({ response: result.text });
});

export default app;

{
  "name": "ai-sdk-worker",
  "compatibility_date": "2025-10-21",
  "ai": {
    "binding": "AI"
  }
}

// BAD (startup overhead)
import { createWorkersAI } from 'workers-ai-provider';
const workersai = createWorkersAI({ binding: env.AI });

// GOOD (lazy init)
app.post('/chat', async (c) => {
  const { createWorkersAI } = await import('workers-ai-provider');
  const workersai = createWorkersAI({ binding: c.env.AI });
  // ...
});