ai-sdk-core

name	ai-sdk-core
description	Build backend AI with Vercel AI SDK v5/v6. Covers v6 beta (Agent abstraction, tool approval, reranking), v4→v5 migration (breaking changes), latest models (GPT-5/5.1, Claude 4.x, Gemini 2.5), Workers startup fix, and 12 error solutions (AI_APICallError, AI_NoObjectGeneratedError, streamText silent errors). Use when: implementing AI SDK v5/v6, migrating v4→v5, troubleshooting errors, fixing Workers startup issues, or updating to latest models.
license	MIT
metadata	{"version":"1.2.0","last_verified":"2025-11-22T00:00:00.000Z","ai_sdk_version":"5.0.98 stable / 6.0.0-beta.107","breaking_changes":"true (v4→v5 migration guide included)","production_tested":true,"keywords":["ai sdk core","vercel ai sdk","ai sdk v5","ai sdk v6 beta","ai sdk 6","agent abstraction","tool approval","reranking support","human in the loop","generateText","streamText","generateObject","streamObject","ai sdk node","ai sdk server","zod ai schema","ai schema validation","ai tool calling","ai agent class","openai sdk","anthropic sdk","google gemini sdk","cloudflare workers ai","workers-ai-provider","gpt-5","gpt-5.1","claude 4","claude sonnet 4.5","claude opus 4.1","gemini 2.5","ai streaming backend","multi-provider ai","[Truncated]"]}

AI SDK Core

Backend AI with Vercel AI SDK v5 and v6 Beta.

Installation:

npm install ai @ai-sdk/openai @ai-sdk/anthropic @ai-sdk/google zod
# Beta: npm install ai@beta @ai-sdk/openai@beta

---

AI SDK 6 Beta (November 2025)

Status: Beta (stable release planned end of 2025) Latest: ai@6.0.0-beta.107 (Nov 22, 2025)

New Features

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

1. Parameter Renames

   • maxTokens → maxOutputTokens
   • providerMetadata → providerOptions

2. Tool Definitions

   • parameters → inputSchema
   • Tool properties: args → input, result → output

3. Message Types

   • CoreMessage → ModelMessage
   • Message → UIMessage
   • convertToCoreMessages → convertToModelMessages

4. Tool Error Handling

   • ToolExecutionError class removed
   • Now tool-error content parts
   • Enables automated retry

5. Multi-Step Execution

   • maxSteps → stopWhen
   • Use stepCountIs() or hasToolCall()

6. Message Structure

   • Simple content string → parts array
   • Parts: text, file, reasoning, tool-call, tool-result

7. Streaming Architecture

   • Single chunk → start/delta/end lifecycle
   • Unique IDs for concurrent streams

8. Tool Streaming

   • Enabled by default
   • toolCallStreaming option removed

9. 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

• Update all maxTokens to maxOutputTokens
• Update providerMetadata to providerOptions
• Convert tool parameters to inputSchema
• Update tool execute functions: args → input
• Replace maxSteps with stopWhen(stepCountIs(n))
• Update message types: CoreMessage → ModelMessage
• Remove ToolExecutionError handling
• Update package imports (ai/rsc → @ai-sdk/rsc)
• Test streaming behavior (architecture changed)
• Update TypeScript types

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