How do you implement error handling in OpenAI API applications?

import openai
from openai import OpenAI
import time

client = OpenAI()

def robust_api_call(prompt: str) -> str:
    """Production-ready API call with comprehensive error handling."""
    try:
        response = client.responses.create(
            model="gpt-5.5",
            input=prompt,
            timeout=30.0,
        )
        return response.output_text

    except openai.AuthenticationError as e:
        # 401 - Invalid API key
        raise ValueError("Invalid API key. Check OPENAI_API_KEY.") from e

    except openai.PermissionDeniedError as e:
        # 403 - Access denied to model or feature
        raise PermissionError(f"Permission denied: {e.message}") from e

    except openai.RateLimitError as e:
        # 429 - Rate limited: implement exponential backoff
        for attempt in range(5):
            wait = (2 ** attempt) + 0.1
            time.sleep(wait)
            try:
                return client.responses.create(model="gpt-5.5", input=prompt).output_text
            except openai.RateLimitError:
                continue
        raise

    except openai.BadRequestError as e:
        # 400 - Invalid request (bad parameters, context overflow)
        if "context_length_exceeded" in str(e):
            raise ValueError("Prompt too long - reduce input size.") from e
        raise

    except openai.InternalServerError as e:
        # 500 - OpenAI server error: retry with backoff
        time.sleep(5)
        return client.responses.create(model="gpt-5.5", input=prompt).output_text

    except openai.APIConnectionError as e:
        # Network error: check connectivity
        raise ConnectionError("Network error connecting to OpenAI API.") from e

    except openai.APITimeoutError as e:
        # Request timed out
        raise TimeoutError("API request timed out.") from e