What are the best practices for handling Serverless Inference errors?

Follow these best practices to handle Serverless Inference errors gracefully and maintain reliable applications.

1. Always implement error handling

Wrap API calls in try-except blocks:

import openai

try:
    response = client.chat.completions.create(
        model="meta-llama/Llama-3.1-8B-Instruct",
        messages=messages
    )
except Exception as e:
    print(f"Error: {e}")
    # Handle error appropriately

2. Use retry logic with exponential backoff

import time
from typing import Optional

def call_inference_with_retry(
    client, 
    messages, 
    model: str,
    max_retries: int = 3,
    base_delay: float = 1.0
) -> Optional[str]:
    for attempt in range(max_retries):
        try:
            response = client.chat.completions.create(
                model=model,
                messages=messages
            )
            return response.choices[0].message.content
        except Exception as e:
            if attempt == max_retries - 1:
                raise
            
            # Calculate delay with exponential backoff
            delay = base_delay * (2 ** attempt)
            print(f"Attempt {attempt + 1} failed, retrying in {delay}s...")
            time.sleep(delay)
    
    return None

3. Monitor your usage

• Track credit usage in the W&B Billing page
• Set up alerts before hitting limits
• Log API usage in your application

4. Handle specific error codes

def handle_inference_error(error):
    error_str = str(error)
    
    if "401" in error_str:
        # Invalid authentication
        raise ValueError("Check your API key and project configuration")
    elif "402" in error_str:
        # Out of credits
        raise ValueError("Insufficient credits")
    elif "429" in error_str:
        # Rate limited
        return "retry"
    elif "500" in error_str or "503" in error_str:
        # Server error
        return "retry"
    else:
        # Unknown error
        raise

5. Set appropriate timeouts

Configure reasonable timeouts for your use case:

# For longer responses
client = openai.OpenAI(
    base_url='https://api.inference.wandb.ai/v1',
    api_key="your-api-key",
    timeout=60.0  # 60 second timeout
)

Additional tips

• Log errors with timestamps for debugging
• Use async operations for better concurrency handling
• Implement circuit breakers for production systems
• Cache responses when appropriate to reduce API calls

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Inference