retry loop

- A small random jitter is added to the delay to avoid synchronized retries from multiple clients. - The loop continues until a successful response is received or the maximum number of retries is reached. ### Additional Consideration…

elif response.status_code == 429: # Rate limit exceeded delay = base_delay * (2 ** attempt) + random.uniform(0, 1) print(f"Rate limit exceeded. Retrying in {delay:.2f} seconds...") time.sleep(del…

response = make_request(prompt) if response: return response if attempt < retries: logging.warning(f"Attempt {attempt + 1} failed. Retrying in {delay} seconds...") …

import aiohttp import asyncio import time # Define a function to make an API call with retries async def make_api_call(session, query, max_retries=3): url = f"https://example.com/api/{query}" for attempt in range(max_retries + 1): …

[2025-12-13 14:57] omega [bot]: It sounds like you're referencing a new decision tool that might help with making choices or analyzing options more effectively. Here are a few ways a decision tool could be helpful: 1. **Structured Framew…

[2025-12-06 20:23] uncloseai [bot]: ✨ **Fixed Code** (attempt 2/2): ```python import json import requests import time # Fetch the JSON data from the URL url = "https://russell.ballestrini.net/uploads/russell.ballestrini.resume.json" # Add…

logger.error("Max retries reached. Unable to refresh token and retry.") return None else: logger.error(f"Unexpected HTTP error: {e}") raise return None …

def run(self) -> Optional[str]: file_path = self.source retries = 0 while retries < self.max_retries: if self._upload_file(file_path): logging.info(f"File {file_path} uploaded success…

logging.error(f"Content validation failed for file {file_path}") continue logging.info(f"File {file_path} uploaded successfully.") return file_path retries…

3. **Error Logging**: Log the error with relevant details, including the error status code. 4. **Fallback Mechanism**: Consider a fallback mechanism, such as queuing the document for later processing. ### Example Code Here's an example of…

[Turn 4431] Assistant: Understood! When troubleshooting integration issues, it's important to include error status codes to provide more context and aid in diagnosing the problem. Let's revisit the example of handling a `TimeoutException` w…

1. **Centralized Logging**: Use a centralized logging mechanism to capture and report errors. 2. **Graceful Error Handling**: Ensure that errors are handled gracefully without crashing the entire pipeline. 3. **Retry Mechanism**: Implement …

logging.basicConfig(level=logging.ERROR, format='%(asctime)s - %(levelname)s - %(message)s') # Load the model once model = SentenceTransformer('paraphrase-MiniLM-L6-v2') def vectorize_document(doc, retries=3, delay=1): for attempt in …

[Turn 4751] Assistant: Great! I'm glad you're ready to proceed with the tests. Here are the final steps to ensure your pipeline is robust and meets the performance targets: ### Steps to Follow 1. **Replace Placeholder Data**: - Replace…

send_message('test_topic', value=b'Hello, World!') # Graceful shutdown producer.flush() producer.close() ``` ### Explanation 1. **Logging Configuration**: - Configure logging to capture and log errors and exceptions. 2. **Try-Except …

break except KafkaTimeoutError as e: logger.warning(f"Timeout error on attempt {attempt}: {e}") except KafkaConnectionError as e: logger.warning(f"Connection error on att…

logger.warning(f"Unexpected error on attempt {attempt}: {e}") if attempt == retries: logger.error("Max retries reached. Message consumption failed.") break # Example usage consume_messag…

except Exception as e: print(f'Final error: {e}') ``` ### Explanation 1. **retry_evaluation**: - Takes the evaluation function, maximum number of retries, backoff factor, and allowed exceptions as parameters. - Retries the evalu…

- Consider using asynchronous requests to handle multiple expansions concurrently. 5. **Handle Specific Errors Gracefully**: - Catch specific exceptions and handle them appropriately to avoid cascading failures. ### Example Implemen…