Technical Last updated: January 2024

Technical Issues & API Errors: Troubleshooting Guide

API errors can bring your AI-powered applications to a halt. This comprehensive guide covers the most common technical issues with OpenAI and Anthropic APIs, along with proven solutions.

Common API Errors

Authentication Errors (401 Unauthorized)

The most basic but often most frustrating errors. They can stem from multiple causes:

  • Invalid or expired API keys
  • Incorrect key format in requests
  • Keys revoked due to account issues
  • Environment variable misconfigurations

Quick fix: Regenerate your API key and ensure it's properly set in all environments.

Rate Limiting (429 Too Many Requests)

Rate limits protect API infrastructure but can disrupt production systems.

OpenAI rate limits vary by:

  • Account tier and usage history
  • Model being used
  • Request type (chat, completion, embedding)

Anthropic/Claude considerations:

  • Tier-based limits
  • Concurrent request limits
  • Tokens-per-minute restrictions

Timeouts & Connection Issues

Long-running requests or network problems can cause timeouts:

  • Request timeout (usually 30-120 seconds)
  • Connection reset errors
  • Intermittent 502/503 errors
  • Slow response times during peak hours

Model-Specific Errors

Different models have different constraints:

  • Context length exceeded
  • Model temporarily unavailable
  • Invalid parameters for specific models
  • Deprecated model versions

Solutions & Best Practices

Implementing Retry Logic

Exponential backoff with jitter is essential for handling rate limits:

// Pseudocode for retry logic
max_retries = 5
base_delay = 1 second

for attempt in range(max_retries):
    try:
        response = api.call()
        return response
    except RateLimitError:
        delay = base_delay * (2 ** attempt) + random_jitter()
        sleep(delay)
    except FatalError:
        raise

Request Optimization

  • Batch requests where possible
  • Implement request queuing
  • Use streaming for long responses
  • Cache frequently used responses

Monitoring & Alerting

Don't wait for users to tell you something's wrong:

  • Track error rates by type
  • Monitor latency percentiles
  • Set up alerts for abnormal patterns
  • Log request IDs for debugging with support

When to Seek Expert Help

Some technical issues require deeper expertise:

  • Persistent errors despite following documentation
  • Complex multi-service architectures
  • Performance optimization needs
  • Custom integration requirements
  • Scaling challenges

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