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Zhongwei Li
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references/top-errors.md
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references/top-errors.md
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# AI SDK Core - Top 12 Errors & Solutions
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Comprehensive guide to the most common AI SDK Core errors with actionable solutions.
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---
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## 1. AI_APICallError
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**Type:** Network/API Error
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**Frequency:** Very Common
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**Severity:** High
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### Cause
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API request to provider failed due to:
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- Invalid API key
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- Network connectivity issues
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- Rate limit exceeded
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- Provider service outage
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### Solution
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```typescript
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import { AI_APICallError } from 'ai';
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try {
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const result = await generateText({
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model: openai('gpt-4'),
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prompt: 'Hello',
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});
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} catch (error) {
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if (error instanceof AI_APICallError) {
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console.error('API call failed:', error.message);
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console.error('Status code:', error.statusCode);
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console.error('Response:', error.responseBody);
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// Handle specific status codes
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if (error.statusCode === 401) {
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// Invalid API key
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console.error('Check OPENAI_API_KEY environment variable');
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} else if (error.statusCode === 429) {
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// Rate limit - implement exponential backoff
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await wait(Math.pow(2, retryCount) * 1000);
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// retry...
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} else if (error.statusCode >= 500) {
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// Provider issue - retry later
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console.error('Provider service issue, retry in 1 minute');
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}
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}
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}
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```
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### Prevention
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- Validate API keys at application startup
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- Implement retry logic with exponential backoff
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- Monitor rate limits via response headers
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- Handle network errors gracefully
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- Set reasonable timeouts
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### Resources
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- Docs: https://ai-sdk.dev/docs/reference/ai-sdk-errors/ai-api-call-error
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---
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## 2. AI_NoObjectGeneratedError
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**Type:** Generation Error
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**Frequency:** Common
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**Severity:** Medium
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### Cause
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Model didn't generate a valid object matching the Zod schema:
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- Schema too complex for model
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- Prompt doesn't provide enough context
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- Model capabilities exceeded
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- Safety filters triggered
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### Solution
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```typescript
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import { AI_NoObjectGeneratedError } from 'ai';
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try {
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const result = await generateObject({
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model: openai('gpt-4'),
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schema: z.object({
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// Complex schema
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name: z.string(),
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age: z.number(),
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nested: z.object({ /* ... */ }),
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}),
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prompt: 'Generate a person',
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});
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} catch (error) {
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if (error instanceof AI_NoObjectGeneratedError) {
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console.error('No valid object generated');
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// Solutions:
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// 1. Simplify schema
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const simpler = z.object({
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name: z.string(),
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age: z.number(),
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});
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// 2. Add more context
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const betterPrompt = 'Generate a person profile with name (string) and age (number, 18-80)';
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// 3. Try different model
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const result2 = await generateObject({
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model: openai('gpt-4'), // GPT-4 better than 3.5 for complex objects
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schema: simpler,
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prompt: betterPrompt,
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});
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}
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}
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```
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### Prevention
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- Start with simple schemas, add complexity gradually
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- Include examples in prompt: `"Generate like: { name: 'Alice', age: 30 }"`
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- Use GPT-4 or Claude for complex structured output
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- Test schemas with sample data first
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- Add descriptions to schema fields using `.describe()`
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### Resources
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- Docs: https://ai-sdk.dev/docs/reference/ai-sdk-errors/ai-no-object-generated-error
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---
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## 3. Worker Startup Limit (270ms+)
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**Type:** Cloudflare Workers Issue
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**Frequency:** Common (Workers only)
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**Severity:** High (blocks deployment)
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### Cause
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AI SDK v5 + Zod initialization overhead exceeds Cloudflare Workers startup limit (must be <400ms):
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- Top-level imports of AI SDK packages
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- Complex Zod schemas at module level
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- Provider initialization at startup
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### Solution
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```typescript
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// ❌ BAD: Top-level imports cause startup overhead
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import { createWorkersAI } from 'workers-ai-provider';
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import { generateText } from 'ai';
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import { complexSchema } from './schemas'; // Heavy Zod schemas
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const workersai = createWorkersAI({ binding: env.AI }); // Runs at startup!
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// ✅ GOOD: Lazy initialization inside handler
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export default {
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async fetch(request, env) {
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// Import inside handler
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const { createWorkersAI } = await import('workers-ai-provider');
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const { generateText } = await import('ai');
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const workersai = createWorkersAI({ binding: env.AI });
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const result = await generateText({
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model: workersai('@cf/meta/llama-3.1-8b-instruct'),
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prompt: 'Hello',
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});
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return new Response(result.text);
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}
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};
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```
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### Alternative Solution (Move Schemas Inside Routes)
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```typescript
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// ❌ BAD: Top-level schema
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import { z } from 'zod';
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const PersonSchema = z.object({ /* complex schema */ });
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// ✅ GOOD: Schema inside handler
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export default {
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async fetch(request, env) {
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const { z } = await import('zod');
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const PersonSchema = z.object({ /* complex schema */ });
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// Use schema here
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}
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};
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```
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### Prevention
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- Never initialize AI SDK at module top-level in Workers
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- Move all imports inside route handlers
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- Minimize top-level Zod schemas
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- Monitor Worker startup time: `wrangler deploy` shows startup duration
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- Target < 270ms startup time to be safe (limit is 400ms)
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### Resources
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- Cloudflare Workers AI Docs: https://developers.cloudflare.com/workers-ai/configuration/ai-sdk/
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- GitHub: Search "Workers startup limit" in Vercel AI SDK issues
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---
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## 4. streamText Fails Silently
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**Type:** Streaming Error
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**Frequency:** Occasional
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**Severity:** Medium (hard to debug)
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### Cause
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Stream errors are swallowed by `createDataStreamResponse()` or framework response handling:
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- Error occurs during streaming
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- Error handler not set up
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- Response already committed
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- Client disconnects
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### Solution
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```typescript
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// ✅ GOOD: Add explicit error handling
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const stream = streamText({
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model: openai('gpt-4'),
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prompt: 'Hello',
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});
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try {
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for await (const chunk of stream.textStream) {
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process.stdout.write(chunk);
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}
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} catch (error) {
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// Error may not reach here if stream swallows it
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console.error('Stream error:', error);
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}
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// ✅ BETTER: Always log on server side
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console.log('Starting stream...');
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const stream = streamText({
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model: openai('gpt-4'),
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prompt: 'Hello',
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});
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stream.result.then(
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(result) => console.log('Stream success:', result.usage),
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(error) => console.error('Stream failed:', error) // This will catch errors!
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);
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return stream.toDataStreamResponse();
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```
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### Prevention
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- Always check server logs for stream errors
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- Implement server-side error monitoring (e.g., Sentry)
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- Test stream error handling explicitly
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- Use `try-catch` around stream consumption
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- Monitor for unexpected stream terminations
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### Resources
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- GitHub Issue: #4726
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---
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## 5. AI_LoadAPIKeyError
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**Type:** Configuration Error
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**Frequency:** Very Common (setup)
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**Severity:** High (blocks usage)
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### Cause
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API key missing or invalid:
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- `.env` file not loaded
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- Wrong environment variable name
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- API key format invalid
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- Environment variable not set in deployment
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### Solution
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```typescript
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import { AI_LoadAPIKeyError } from 'ai';
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try {
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const result = await generateText({
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model: openai('gpt-4'),
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prompt: 'Hello',
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});
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} catch (error) {
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if (error instanceof AI_LoadAPIKeyError) {
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console.error('API key error:', error.message);
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// Debugging steps:
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console.log('OPENAI_API_KEY exists:', !!process.env.OPENAI_API_KEY);
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console.log('Key starts with sk-:', process.env.OPENAI_API_KEY?.startsWith('sk-'));
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// Common issues:
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// 1. .env not loaded → use dotenv or similar
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// 2. Wrong variable name → check provider docs
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// 3. Key format wrong → verify in provider dashboard
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}
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}
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```
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### Prevention
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```typescript
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// Validate at startup
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function validateEnv() {
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const required = ['OPENAI_API_KEY', 'ANTHROPIC_API_KEY'];
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for (const key of required) {
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if (!process.env[key]) {
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throw new Error(`Missing required environment variable: ${key}`);
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}
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}
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}
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validateEnv();
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```
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### Environment Variable Names
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| Provider | Variable Name |
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|----------|---------------|
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| OpenAI | `OPENAI_API_KEY` |
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| Anthropic | `ANTHROPIC_API_KEY` |
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| Google | `GOOGLE_GENERATIVE_AI_API_KEY` |
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### Resources
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- Docs: https://ai-sdk.dev/docs/reference/ai-sdk-errors/ai-load-api-key-error
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---
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## 6. AI_InvalidArgumentError
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**Type:** Validation Error
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**Frequency:** Common (development)
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**Severity:** Low (easy to fix)
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### Cause
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Invalid parameters passed to AI SDK function:
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- Negative `maxOutputTokens`
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- Invalid temperature (must be 0-2)
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- Wrong parameter types
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- Missing required parameters
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### Solution
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```typescript
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import { AI_InvalidArgumentError } from 'ai';
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try {
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const result = await generateText({
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model: openai('gpt-4'),
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maxOutputTokens: -1, // ❌ Invalid!
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temperature: 3.0, // ❌ Must be 0-2
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prompt: 'Hello',
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});
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} catch (error) {
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if (error instanceof AI_InvalidArgumentError) {
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console.error('Invalid argument:', error.message);
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// Fix: Check parameter types and values
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}
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}
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```
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### Prevention
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- Use TypeScript for compile-time type checking
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- Validate inputs before calling AI SDK functions
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- Read function signatures carefully
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- Check official docs for parameter constraints
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- Use IDE autocomplete
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### Resources
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- Docs: https://ai-sdk.dev/docs/reference/ai-sdk-errors/ai-invalid-argument-error
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---
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## 7. AI_NoContentGeneratedError
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**Type:** Generation Error
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**Frequency:** Occasional
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**Severity:** Medium
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### Cause
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Model generated no content:
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- Safety filters blocked output
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- Prompt triggered content policy
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- Model configuration issue
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- Empty prompt
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### Solution
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```typescript
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import { AI_NoContentGeneratedError } from 'ai';
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try {
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const result = await generateText({
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model: openai('gpt-4'),
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prompt: 'Some potentially problematic prompt',
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});
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} catch (error) {
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if (error instanceof AI_NoContentGeneratedError) {
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console.error('No content generated');
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// Return user-friendly message
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return {
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text: 'Unable to generate response. Please try different input.',
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error: true,
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};
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}
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}
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```
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### Prevention
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- Sanitize user inputs
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- Avoid prompts that may trigger safety filters
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- Have fallback messaging
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- Log occurrences for analysis
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- Test with edge cases
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### Resources
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- Docs: https://ai-sdk.dev/docs/reference/ai-sdk-errors/ai-no-content-generated-error
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---
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## 8. AI_TypeValidationError
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**Type:** Validation Error
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**Frequency:** Common (with generateObject)
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**Severity:** Medium
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### Cause
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Zod schema validation failed on generated output:
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- Model output doesn't match schema
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- Schema too strict
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- Model misunderstood schema
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- Invalid JSON generated
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### Solution
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```typescript
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import { AI_TypeValidationError } from 'ai';
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try {
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const result = await generateObject({
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model: openai('gpt-4'),
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schema: z.object({
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age: z.number().min(0).max(120), // Strict validation
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email: z.string().email(), // Strict format
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}),
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prompt: 'Generate person',
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});
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} catch (error) {
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if (error instanceof AI_TypeValidationError) {
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console.error('Validation failed:', error.message);
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// Solutions:
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// 1. Relax schema
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const relaxed = z.object({
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age: z.number(), // Remove min/max
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email: z.string().optional(), // Make optional
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});
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// 2. Add guidance in prompt
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const better = await generateObject({
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model: openai('gpt-4'),
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schema: relaxed,
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prompt: 'Generate person with age 18-80 and valid email',
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});
|
||||
}
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||||
}
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||||
```
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||||
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||||
### Prevention
|
||||
|
||||
- Start with lenient schemas, tighten gradually
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- Use `.optional()` for unreliable fields
|
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- Add validation hints in field descriptions
|
||||
- Test with various prompts
|
||||
- Use mode: 'json' when available
|
||||
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||||
### Resources
|
||||
|
||||
- Docs: https://ai-sdk.dev/docs/reference/ai-sdk-errors/ai-type-validation-error
|
||||
|
||||
---
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||||
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## 9. AI_RetryError
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||||
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||||
**Type:** Network Error
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||||
**Frequency:** Occasional
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||||
**Severity:** High
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||||
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||||
### Cause
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||||
|
||||
All retry attempts failed:
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||||
- Persistent network issue
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- Provider outage
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||||
- Invalid configuration
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- Unreachable API endpoint
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||||
|
||||
### Solution
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||||
|
||||
```typescript
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import { AI_RetryError } from 'ai';
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||||
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||||
try {
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||||
const result = await generateText({
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model: openai('gpt-4'),
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||||
prompt: 'Hello',
|
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maxRetries: 3, // Default is 2
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||||
});
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||||
} catch (error) {
|
||||
if (error instanceof AI_RetryError) {
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||||
console.error('All retries failed');
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||||
console.error('Last error:', error.lastError);
|
||||
console.error('Retry count:', error.retryCount);
|
||||
|
||||
// Implement circuit breaker
|
||||
if (isProviderDown()) {
|
||||
switchToFallbackProvider();
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Prevention
|
||||
|
||||
- Investigate root cause of failures
|
||||
- Adjust retry configuration if needed
|
||||
- Implement circuit breaker pattern
|
||||
- Have fallback providers
|
||||
- Monitor provider status pages
|
||||
|
||||
### Resources
|
||||
|
||||
- Docs: https://ai-sdk.dev/docs/reference/ai-sdk-errors/ai-retry-error
|
||||
|
||||
---
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||||
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||||
## 10. Rate Limiting Errors
|
||||
|
||||
**Type:** API Limit Error
|
||||
**Frequency:** Common (production)
|
||||
**Severity:** High
|
||||
|
||||
### Cause
|
||||
|
||||
Exceeded provider rate limits:
|
||||
- RPM (Requests Per Minute) exceeded
|
||||
- TPM (Tokens Per Minute) exceeded
|
||||
- Concurrent request limit hit
|
||||
- Free tier limits reached
|
||||
|
||||
### Solution
|
||||
|
||||
```typescript
|
||||
// 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: any) {
|
||||
if (error.statusCode === 429) {
|
||||
const delay = Math.pow(2, i) * 1000; // 1s, 2s, 4s, 8s...
|
||||
console.log(`Rate limited, waiting ${delay}ms`);
|
||||
await new Promise(resolve => setTimeout(resolve, delay));
|
||||
} else {
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
}
|
||||
throw new Error('Rate limit retries exhausted');
|
||||
}
|
||||
|
||||
// Or use queue
|
||||
import PQueue from 'p-queue';
|
||||
|
||||
const queue = new PQueue({ concurrency: 5, interval: 60000, intervalCap: 50 });
|
||||
|
||||
async function generateQueued(prompt: string) {
|
||||
return queue.add(() => generateText({ model: openai('gpt-4'), prompt }));
|
||||
}
|
||||
```
|
||||
|
||||
### Prevention
|
||||
|
||||
- Monitor rate limit headers in responses
|
||||
- Queue requests to stay under limits
|
||||
- Upgrade provider tier if needed
|
||||
- Implement request throttling
|
||||
- Cache results when possible
|
||||
|
||||
### Resources
|
||||
|
||||
- OpenAI Rate Limits: https://platform.openai.com/account/rate-limits
|
||||
- Anthropic Rate Limits: https://docs.anthropic.com/en/api/rate-limits
|
||||
|
||||
---
|
||||
|
||||
## 11. TypeScript Performance with Zod
|
||||
|
||||
**Type:** Development Issue
|
||||
**Frequency:** Occasional
|
||||
**Severity:** Low (annoying)
|
||||
|
||||
### Cause
|
||||
|
||||
Complex Zod schemas slow down TypeScript type checking:
|
||||
- Deeply nested schemas
|
||||
- Many union types
|
||||
- Recursive types
|
||||
- Top-level complex schemas
|
||||
|
||||
### Solution
|
||||
|
||||
```typescript
|
||||
// ❌ BAD: Complex schema at top level
|
||||
const ComplexSchema = z.object({
|
||||
// 100+ fields with nested objects...
|
||||
});
|
||||
|
||||
// ✅ GOOD: Define inside function
|
||||
function generateData() {
|
||||
const schema = z.object({
|
||||
// Complex schema here
|
||||
});
|
||||
|
||||
return generateObject({ model: openai('gpt-4'), schema, prompt: '...' });
|
||||
}
|
||||
|
||||
// ✅ GOOD: Use z.lazy() for recursive
|
||||
type Category = { name: string; subcategories?: Category[] };
|
||||
|
||||
const CategorySchema: z.ZodType<Category> = z.lazy(() =>
|
||||
z.object({
|
||||
name: z.string(),
|
||||
subcategories: z.array(CategorySchema).optional(),
|
||||
})
|
||||
);
|
||||
|
||||
// ✅ GOOD: Split large schemas
|
||||
const AddressSchema = z.object({ /* ... */ });
|
||||
const PersonSchema = z.object({
|
||||
address: AddressSchema, // Reuse smaller schema
|
||||
});
|
||||
```
|
||||
|
||||
### Prevention
|
||||
|
||||
- Avoid top-level complex schemas
|
||||
- Use `z.lazy()` for recursive types
|
||||
- Split large schemas into smaller ones
|
||||
- Use type assertions where appropriate
|
||||
- Enable `skipLibCheck` in tsconfig.json if desperate
|
||||
|
||||
### Resources
|
||||
|
||||
- Troubleshooting: https://ai-sdk.dev/docs/troubleshooting/common-issues/slow-type-checking
|
||||
|
||||
---
|
||||
|
||||
## 12. Invalid JSON Response (Provider-Specific)
|
||||
|
||||
**Type:** Provider Issue
|
||||
**Frequency:** Rare
|
||||
**Severity:** Medium
|
||||
|
||||
### Cause
|
||||
|
||||
Some models occasionally return invalid JSON:
|
||||
- Model error
|
||||
- Provider API issue
|
||||
- Specific model version bug (e.g., Imagen 3.0)
|
||||
|
||||
### Solution
|
||||
|
||||
```typescript
|
||||
// Use built-in retry and mode selection
|
||||
try {
|
||||
const result = await generateObject({
|
||||
model: openai('gpt-4'),
|
||||
schema: mySchema,
|
||||
prompt: 'Generate data',
|
||||
mode: 'json', // Force JSON mode (GPT-4 supports this)
|
||||
maxRetries: 3, // Retry on invalid JSON
|
||||
});
|
||||
} catch (error) {
|
||||
// Fallback to different model
|
||||
console.error('GPT-4 failed, trying Claude...');
|
||||
const result2 = await generateObject({
|
||||
model: anthropic('claude-3-5-sonnet-20241022'),
|
||||
schema: mySchema,
|
||||
prompt: 'Generate data',
|
||||
});
|
||||
}
|
||||
```
|
||||
|
||||
### Prevention
|
||||
|
||||
- Use `mode: 'json'` when available
|
||||
- Prefer GPT-4/Claude for structured output
|
||||
- Implement retry logic
|
||||
- Validate responses
|
||||
- Have fallback models
|
||||
|
||||
### Resources
|
||||
|
||||
- GitHub Issue: #4302 (Imagen 3.0 Invalid JSON)
|
||||
|
||||
---
|
||||
|
||||
## For More Errors
|
||||
|
||||
See complete error reference (28 total error types):
|
||||
https://ai-sdk.dev/docs/reference/ai-sdk-errors
|
||||
|
||||
---
|
||||
|
||||
**Last Updated:** 2025-10-21
|
||||
Reference in New Issue
Block a user