retry-condition

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): …

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

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 …

- Test the pipeline to ensure it handles errors and retries correctly. - Verify that the system can handle 3,500 documents per hour with under 200ms processing time. 3. **Monitor Performance**: - Monitor the system to ensure it ac…

- Replace the placeholder documents with your actual documents. 2. **Test the Pipeline**: - Test the pipeline to ensure it handles errors and retries correctly. - Verify that the system can handle 3,500 documents per hour with und…

try: future = producer.send(topic, value=data) record_metadata = future.get(timeout=10) # Wait for the message to be sent print(f"Message sent to topic {record_metadata.topic}, partition {record_…

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…

circuit_breaker.record_failure() raise Exception(f"Failed to expand synonyms after {retries} retries: {response.status_code}") else: raise Exception(f"Failed to expand syno…