Error Diagnosis Tool: Leave No Issue Unfound

Intelligently analyze API error causes and provide targeted solutions to help developers quickly locate and fix issues, reducing debugging time.

Common Error Types

🚫 Authentication Errors

  • • Invalid API key
  • • Insufficient permissions
  • • Token expired
  • • Invalid request signature

⚠️ Request Errors

  • • Invalid parameter format
  • • Exceeds length limit
  • • Unsupported model
  • • Invalid options

⏱️ Limitation Errors

  • • Rate limiting
  • • Quota exhausted
  • • Concurrency limit
  • • Account suspended

💥 Service Errors

  • • Internal server error
  • • Gateway timeout
  • • Service unavailable
  • • Overloaded service

Intelligent Diagnosis Example

Error Message

Error: 429 Too Many Requests
{
  "error": {
    "message": "Rate limit exceeded. Please retry after 2 seconds.",
    "type": "rate_limit_error",
    "code": "rate_limit_exceeded"
  }
}

Diagnosis Result

Cause

Your request rate exceeded the API's rate limit. The current limit is 60 requests per minute.

Solutions
  • 1. Wait 2 seconds before retrying
  • 2. Implement an exponential backoff retry mechanism
  • 3. Use batch APIs to reduce the number of requests
  • 4. Consider upgrading to a higher quota plan
Preventive Measures
// Implement rate limiting
const rateLimiter = new RateLimiter({
  requests: 60,
  per: 'minute'
});

// Automatic retry
const retry = async (fn, retries = 3) => {
  try {
    return await fn();
  } catch (error) {
    if (error.code === 'rate_limit_exceeded' && retries > 0) {
      await sleep(2000 * (4 - retries));
      return retry(fn, retries - 1);
    }
    throw error;
  }
};

Error Code Quick Reference

Error CodeMeaningQuick Fix
401UnauthorizedVerify the API key is correct
403ForbiddenCheck account permissions and status
429Too Many RequestsReduce request frequency
500Server ErrorRetry later or contact support
503Service UnavailableWait for service recovery

Debugging Tips

🔍 Request Debugging

// Enable detailed logging
const client = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
  debug: true,
  logger: {
    log: (message) => {
      console.log('[API]', message);
    }
  }
});

// Capture full error details
try {
  const response = await client.chat.completions.create({...});
} catch (error) {
  console.error('Status:', error.status);
  console.error('Headers:', error.headers);
  console.error('Body:', error.body);
}

📊 Performance Monitoring

// Monitor API performance
const monitor = {
  requests: 0,
  errors: 0,
  totalLatency: 0,
  
  track: async (fn) => {
    const start = Date.now();
    monitor.requests++;
    
    try {
      const result = await fn();
      monitor.totalLatency += Date.now() - start;
      return result;
    } catch (error) {
      monitor.errors++;
      throw error;
    }
  },
  
  report: () => ({
    totalRequests: monitor.requests,
    errorRate: monitor.errors / monitor.requests,
    avgLatency: monitor.totalLatency / monitor.requests
  })
};

Best Practices

Error Handling Checklist

✅ Must Implement

  • □ Retry mechanism
  • □ Timeout handling
  • □ Logging
  • □ User-friendly error messages

🎯 Recommended

  • □ Error monitoring and alerts
  • □ Fallback strategies
  • □ Error statistics and analysis
  • □ Automatic recovery mechanisms

Community Solutions

Developer Experience Sharing

👤

@developer123

When encountering 429 errors, I used an exponential backoff strategy with Redis as a request queue, which perfectly solved the rate limiting issue.

Rate limitingRetry strategy
👤

@ai_engineer

To handle token limit issues, I developed middleware that automatically splits long text and intelligently processes over-length inputs.

Token limitText splitting

Quickly Diagnose Your API Issues

Intelligent error analysis and detailed solutions make debugging straightforward.

Start Diagnosis