1. Agent Abstraction Unified interface for building agents with ToolLoopAgent class:

Full control over execution flow, tool loops, and state management
Replaces manual tool calling orchestration

2. Tool Execution Approval (Human-in-the-Loop) Request user confirmation before executing tools:

Static approval: Always ask for specific tools
Dynamic approval: Conditional based on tool inputs
Native human-in-the-loop pattern

3. Reranking Support Improve search relevance by reordering documents:

Supported providers: Cohere, Amazon Bedrock, Together.ai
Specialized reranking models for RAG workflows

4. Structured Output (Stable) Combine multi-step tool calling with structured data generation:

Multiple output strategies: objects, arrays, choices, text formats
Now stable and production-ready in v6

5. Call Options Dynamic runtime configuration:

Type-safe parameter passing
RAG integration, model selection, tool customization
Provider-specific settings adjustments

6. Image Editing (Coming Soon) Native support for image transformation workflows.

Migration from v5

Unlike v4→v5, v6 has minimal breaking changes:

Powered by v3 Language Model Specification
Most users require no code changes
Agent abstraction is additive (opt-in)

Install Beta:

npm install ai@beta @ai-sdk/openai@beta @ai-sdk/react@beta

Official Docs: https://ai-sdk.dev/docs/announcing-ai-sdk-6-beta

Latest AI Models (2025)

OpenAI

GPT-5 (Aug 7, 2025):

45% less hallucination than GPT-4o
State-of-the-art in math, coding, visual perception, health
Available in ChatGPT, API, GitHub Models, Microsoft Copilot

GPT-5.1 (Nov 13, 2025):

Improved speed and efficiency over GPT-5
Available in API platform

import { openai } from '@ai-sdk/openai';
const gpt5 = openai('gpt-5');
const gpt51 = openai('gpt-5.1');

Anthropic

Claude 4 Family (May-Oct 2025):

Opus 4 (May 22): Best for complex reasoning, $15/$75 per million tokens
Sonnet 4 (May 22): Balanced performance, $3/$15 per million tokens
Opus 4.1 (Aug 5): Enhanced agentic tasks, real-world coding
Sonnet 4.5 (Sept 29): Most capable for coding, agents, computer use
Haiku 4.5 (Oct 15): Small, fast, low-latency model

import { anthropic } from '@ai-sdk/anthropic';
const sonnet45 = anthropic('claude-sonnet-4-5-20250929');  // Latest
const opus41 = anthropic('claude-opus-4-1-20250805');
const haiku45 = anthropic('claude-haiku-4-5-20251015');

Google

Gemini 2.5 Family (Mar-Sept 2025):

Pro (March 2025): Most intelligent, #1 on LMArena at launch
Pro Deep Think (May 2025): Enhanced reasoning mode
Flash (May 2025): Fast, cost-effective
Flash-Lite (Sept 2025): Updated efficiency

import { google } from '@ai-sdk/google';
const pro = google('gemini-2.5-pro');
const flash = google('gemini-2.5-flash');
const lite = google('gemini-2.5-flash-lite');

v5 Core Functions (Basics)

generateText() - Text completion with tools streamText() - Real-time streaming generateObject() - Structured output (Zod schemas) streamObject() - Streaming structured data

See official docs for usage: https://ai-sdk.dev/docs/ai-sdk-core

Cloudflare Workers Startup Fix

Problem: AI SDK v5 + Zod causes >270ms startup time (exceeds Workers 400ms limit).

Solution:

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

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

Additional:

Minimize top-level Zod schemas
Move complex schemas into route handlers
Monitor startup time with Wrangler

v5 Tool Calling Changes

Breaking Changes:

parameters → inputSchema (Zod schema)
Tool properties: args → input, result → output
ToolExecutionError removed (now tool-error content parts)
maxSteps parameter removed → Use stopWhen(stepCountIs(n))

New in v5:

Dynamic tools (add tools at runtime based on context)
Agent class (multi-step execution with tools)

Critical v4→v5 Migration

AI SDK v5 introduced extensive breaking changes. If migrating from v4, follow this guide.

Breaking Changes Overview

Parameter Renames
- maxTokens → maxOutputTokens
- providerMetadata → providerOptions
Tool Definitions
- parameters → inputSchema
- Tool properties: args → input, result → output
Message Types
- CoreMessage → ModelMessage
- Message → UIMessage
- convertToCoreMessages → convertToModelMessages
Tool Error Handling
- ToolExecutionError class removed
- Now tool-error content parts
- Enables automated retry
Multi-Step Execution
- maxSteps → stopWhen
- Use stepCountIs() or hasToolCall()
Message Structure
- Simple content string → parts array
- Parts: text, file, reasoning, tool-call, tool-result
Streaming Architecture
- Single chunk → start/delta/end lifecycle
- Unique IDs for concurrent streams
Tool Streaming
- Enabled by default
- toolCallStreaming option removed
Package Reorganization
- ai/rsc → @ai-sdk/rsc
- ai/react → @ai-sdk/react
- LangChainAdapter → @ai-sdk/langchain

Migration Examples

Before (v4):

import { generateText } from 'ai';

const result = await generateText({
  model: openai.chat('gpt-4'),
  maxTokens: 500,
  providerMetadata: { openai: { user: 'user-123' } },
  tools: {
    weather: {
      description: 'Get weather',
      parameters: z.object({ location: z.string() }),
      execute: async (args) => { /* args.location */ },
    },
  },
  maxSteps: 5,
});

After (v5):

import { generateText, tool, stopWhen, stepCountIs } from 'ai';

const result = await generateText({
  model: openai('gpt-4'),
  maxOutputTokens: 500,
  providerOptions: { openai: { user: 'user-123' } },
  tools: {
    weather: tool({
      description: 'Get weather',
      inputSchema: z.object({ location: z.string() }),
      execute: async ({ location }) => { /* input.location */ },
    }),
  },
  stopWhen: stepCountIs(5),
});

Migration Checklist

Automated Migration

AI SDK provides a migration tool:

npx ai migrate

This will update most breaking changes automatically. Review changes carefully.

Official Migration Guide: https://ai-sdk.dev/docs/migration-guides/migration-guide-5-0

Top 12 Errors & Solutions

1. AI_APICallError

Cause: API request failed (network, auth, rate limit).

Solution:

import { AI_APICallError } from 'ai';

try {
  const result = await generateText({
    model: openai('gpt-4'),
    prompt: 'Hello',
  });
} catch (error) {
  if (error instanceof AI_APICallError) {
    console.error('API call failed:', error.message);
    console.error('Status code:', error.statusCode);
    console.error('Response:', error.responseBody);

    // Check common causes
    if (error.statusCode === 401) {
      // Invalid API key
    } else if (error.statusCode === 429) {
      // Rate limit - implement backoff
    } else if (error.statusCode >= 500) {
      // Provider issue - retry
    }
  }
}

Prevention:

Validate API keys at startup
Implement retry logic with exponential backoff
Monitor rate limits
Handle network errors gracefully

2. AI_NoObjectGeneratedError

Cause: Model didn't generate valid object matching schema.

Solution:

import { AI_NoObjectGeneratedError } from 'ai';

try {
  const result = await generateObject({
    model: openai('gpt-4'),
    schema: z.object({ /* complex schema */ }),
    prompt: 'Generate data',
  });
} catch (error) {
  if (error instanceof AI_NoObjectGeneratedError) {
    console.error('No valid object generated');

    // Solutions:
    // 1. Simplify schema
    // 2. Add more context to prompt
    // 3. Provide examples in prompt
    // 4. Try different model (gpt-4 better than gpt-3.5 for complex objects)
  }
}

Prevention:

Start with simple schemas, add complexity incrementally
Include examples in prompt: "Generate a person like: { name: 'Alice', age: 30 }"
Use GPT-4 for complex structured output
Test schemas with sample data first

3. Worker Startup Limit (270ms+)

Cause: AI SDK v5 + Zod initialization overhead in Cloudflare Workers exceeds startup limits.

Solution:

// BAD: Top-level imports cause startup overhead
import { createWorkersAI } from 'workers-ai-provider';
import { complexSchema } from './schemas';

const workersai = createWorkersAI({ binding: env.AI });

// GOOD: Lazy initialization inside handler
export default {
  async fetch(request, env) {
    const { createWorkersAI } = await import('workers-ai-provider');
    const workersai = createWorkersAI({ binding: env.AI });

    // Use workersai here
  }
}

Prevention:

Move AI SDK imports inside route handlers
Minimize top-level Zod schemas
Monitor Worker startup time (must be <400ms)
Use Wrangler's startup time reporting

GitHub Issue: Search for "Workers startup limit" in Vercel AI SDK issues

4. streamText Fails Silently

Cause: Stream errors can be swallowed by createDataStreamResponse.

Status: ✅ RESOLVED - Fixed in ai@4.1.22 (February 2025)

Solution (Recommended):

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

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

Alternative (Manual try-catch):

// Fallback if not using onError callback
try {
  const stream = streamText({
    model: openai('gpt-4'),
    prompt: 'Hello',
  });

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

Prevention:

Use onError callback for proper error capture (recommended)
Implement server-side error monitoring
Test stream error handling explicitly
Always log on server side in production

GitHub Issue: #4726 (RESOLVED)

5. AI_LoadAPIKeyError

Cause: Missing or invalid API key.

Solution:

import { AI_LoadAPIKeyError } from 'ai';

try {
  const result = await generateText({
    model: openai('gpt-4'),
    prompt: 'Hello',
  });
} catch (error) {
  if (error instanceof AI_LoadAPIKeyError) {
    console.error('API key error:', error.message);

    // Check:
    // 1. .env file exists and loaded
    // 2. Correct env variable name (OPENAI_API_KEY)
    // 3. Key format is valid (starts with sk-)
  }
}

Prevention:

Validate API keys at application startup
Use environment variable validation (e.g., zod)
Provide clear error messages in development
Document required environment variables

6. AI_InvalidArgumentError

Cause: Invalid parameters passed to function.

Solution:

import { AI_InvalidArgumentError } from 'ai';

try {
  const result = await generateText({
    model: openai('gpt-4'),
    maxOutputTokens: -1,  // Invalid!
    prompt: 'Hello',
  });
} catch (error) {
  if (error instanceof AI_InvalidArgumentError) {
    console.error('Invalid argument:', error.message);
    // Check parameter types and values
  }
}

Prevention:

Use TypeScript for type checking
Validate inputs before calling AI SDK functions
Read function signatures carefully
Check official docs for parameter constraints

7. AI_NoContentGeneratedError

Cause: Model generated no content (safety filters, etc.).

Solution:

import { AI_NoContentGeneratedError } from 'ai';

try {
  const result = await generateText({
    model: openai('gpt-4'),
    prompt: 'Some prompt',
  });
} catch (error) {
  if (error instanceof AI_NoContentGeneratedError) {
    console.error('No content generated');

    // Possible causes:
    // 1. Safety filters blocked output
    // 2. Prompt triggered content policy
    // 3. Model configuration issue

    // Handle gracefully:
    return { text: 'Unable to generate response. Please try different input.' };
  }
}

Prevention:

Sanitize user inputs
Avoid prompts that may trigger safety filters
Have fallback messaging
Log occurrences for analysis

8. AI_TypeValidationError

Cause: Zod schema validation failed on generated output.

Solution:

import { AI_TypeValidationError } from 'ai';

try {
  const result = await generateObject({
    model: openai('gpt-4'),
    schema: z.object({
      age: z.number().min(0).max(120),  // Strict validation
    }),
    prompt: 'Generate person',
  });
} catch (error) {
  if (error instanceof AI_TypeValidationError) {
    console.error('Validation failed:', error.message);

    // Solutions:
    // 1. Relax schema constraints
    // 2. Add more guidance in prompt
    // 3. Use .optional() for unreliable fields
  }
}

Prevention:

Start with lenient schemas, tighten gradually
Use .optional() for fields that may not always be present
Add validation hints in field descriptions
Test with various prompts

9. AI_RetryError

Cause: All retry attempts failed.

Solution:

import { AI_RetryError } from 'ai';

try {
  const result = await generateText({
    model: openai('gpt-4'),
    prompt: 'Hello',
    maxRetries: 3,  // Default is 2
  });
} catch (error) {
  if (error instanceof AI_RetryError) {
    console.error('All retries failed');
    console.error('Last error:', error.lastError);

    // Check root cause:
    // - Persistent network issue
    // - Provider outage
    // - Invalid configuration
  }
}

Prevention:

Investigate root cause of failures
Adjust retry configuration if needed
Implement circuit breaker pattern for provider outages
Have fallback providers

10. Rate Limiting Errors

Cause: Exceeded provider rate limits (RPM/TPM).

Solution:

// Implement exponential backoff
async function generateWithBackoff(prompt: string, retries = 3) {
  for (let i = 0; i < retries; i++) {
    try {
      return await generateText({
        model: openai('gpt-4'),
        prompt,
      });
    } catch (error) {
      if (error instanceof AI_APICallError && error.statusCode === 429) {
        const delay = Math.pow(2, i) * 1000;  // Exponential backoff
        console.log(`Rate limited, waiting ${delay}ms`);
        await new Promise(resolve => setTimeout(resolve, delay));
      } else {
        throw error;
      }
    }
  }
  throw new Error('Rate limit retries exhausted');
}

Prevention:

Monitor rate limit headers
Queue requests to stay under limits
Upgrade provider tier if needed
Implement request throttling

11. TypeScript Performance with Zod

Cause: Complex Zod schemas slow down TypeScript type checking.

Solution:

// Instead of deeply nested schemas at top level:
// const complexSchema = z.object({ /* 100+ fields */ });

// Define inside functions or use type assertions:
function generateData() {
  const schema = z.object({ /* complex schema */ });
  return generateObject({ model: openai('gpt-4'), schema, prompt: '...' });
}

// Or use z.lazy() for recursive schemas:
type Category = { name: string; subcategories?: Category[] };
const CategorySchema: z.ZodType<Category> = z.lazy(() =>
  z.object({
    name: z.string(),
    subcategories: z.array(CategorySchema).optional(),
  })
);

Prevention:

Avoid top-level complex schemas
Use z.lazy() for recursive types
Split large schemas into smaller ones
Use type assertions where appropriate

Official Docs: https://ai-sdk.dev/docs/troubleshooting/common-issues/slow-type-checking

12. Invalid JSON Response (Provider-Specific)

Cause: Some models occasionally return invalid JSON.

Solution:

// Use built-in retry and mode selection
const result = await generateObject({
  model: openai('gpt-4'),
  schema: mySchema,
  prompt: 'Generate data',
  mode: 'json',  // Force JSON mode (supported by GPT-4)
  maxRetries: 3,  // Retry on invalid JSON
});

// Or catch and retry manually:
try {
  const result = await generateObject({
    model: openai('gpt-4'),
    schema: mySchema,
    prompt: 'Generate data',
  });
} catch (error) {
  // Retry with different model
  const result = await generateObject({
    model: openai('gpt-4-turbo'),
    schema: mySchema,
    prompt: 'Generate data',
  });
}

Prevention:

Use mode: 'json' when available
Prefer GPT-4 for structured output
Implement retry logic
Validate responses

GitHub Issue: #4302 (Imagen 3.0 Invalid JSON)

More Errors: https://ai-sdk.dev/docs/reference/ai-sdk-errors (28 total)

When to Use This Skill

Use ai-sdk-core when:

Building backend AI features (server-side text generation)
Implementing server-side text generation (Node.js, Workers, Next.js)
Creating structured AI outputs (JSON, forms, data extraction)
Building AI agents with tools (multi-step workflows)
Integrating multiple AI providers (OpenAI, Anthropic, Google, Cloudflare)
Migrating from AI SDK v4 to v5
Encountering AI SDK errors (AI_APICallError, AI_NoObjectGeneratedError, etc.)
Using AI in Cloudflare Workers (with workers-ai-provider)
Using AI in Next.js Server Components/Actions
Need consistent API across different LLM providers

Don't use this skill when:

Building React chat UIs (use ai-sdk-ui skill instead)
Need frontend hooks like useChat (use ai-sdk-ui skill instead)
Need advanced topics like embeddings or image generation (check official docs)
Building native Cloudflare Workers AI apps without multi-provider (use cloudflare-workers-ai skill instead)
Need Generative UI / RSC (see https://ai-sdk.dev/docs/ai-sdk-rsc)

Versions

AI SDK:

Stable: ai@5.0.98 (Nov 20, 2025)
Beta: ai@6.0.0-beta.107 (Nov 22, 2025)
Zod 3.x/4.x both supported (3.23.8 recommended)

Latest Models (2025):

OpenAI: GPT-5.1, GPT-5, o3
Anthropic: Claude Sonnet 4.5, Opus 4.1, Haiku 4.5
Google: Gemini 2.5 Pro/Flash/Lite

Check Latest:

npm view ai version
npm view ai dist-tags  # See beta versions

Official Docs

Core:

AI SDK 6 Beta: https://ai-sdk.dev/docs/announcing-ai-sdk-6-beta
AI SDK Core: https://ai-sdk.dev/docs/ai-sdk-core/overview
v4→v5 Migration: https://ai-sdk.dev/docs/migration-guides/migration-guide-5-0
All Errors (28): https://ai-sdk.dev/docs/reference/ai-sdk-errors
Providers (25+): https://ai-sdk.dev/providers/overview

GitHub:

Repository: https://github.com/vercel/ai
Issues: https://github.com/vercel/ai/issues

Last Updated: 2025-11-22 Skill Version: 1.2.0 AI SDK: 5.0.98 stable / 6.0.0-beta.107

ai-sdk-core

AI SDK Core

AI SDK 6 Beta (November 2025)

New Features