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# Replace with your actual API key validation logic return api_key == os.environ.get('API_KEY') # Decorator for API key validation def require_api_key(view_func): @wraps(view_func) def decorated_function(*args, **kwargs): …

- **Docker Compose**: `docker-compose.yml` defines the services, their dependencies, and the network configuration. This setup provides a basic scalable microservice architecture using Docker and Docker Compose. You can expand upon this by…

data = { "fields": { "project": {"key": "YOUR_PROJECT_KEY"}, "summary": name, "description": description, "issuetype": {"name": "Task"}, "priority": {"name": "High" if …

"temperature": temperature, "top_k": top_k, "top_p": top_p, "repetition_penalty": repetition_penalty, "seed": seed } try: response = requests.post(endpoint, headers=headers, json=…

Another approach is to version the cache keys. When user data changes, update the version number in the cache key. This ensures that the old cache entry is bypassed, and a new one is fetched from the API. ### Example Implementation Here's…

Here's an updated version of your code with these considerations: ```python import requests import time import logging # Configure logging logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) def refresh_token(): …

You need to customize the `refresh_token()` function to match your actual token refresh logic. This typically involves calling an endpoint to obtain a new token and updating the headers accordingly. ### Example Token Refresh Logic Here's …

response = requests.post(url, headers=headers, json=payload) return response.json() def update_item_column(board_id, item_id, column_id, new_value): url = "https://api.monday.com/v2" headers = { "Authorization": MON…

"type": "org.apache.nifi.processors.standard.ProcessGroup" } } response = requests.post(url, json=payload) if response.status_code == 201: return response.json()["id"] else: raise Exceptio…

"Error Handling Strategy": "Route to Error Processor" } } } handle_failures_response = requests.post(f"{nifi_url}/process-groups/{processor_group_id}/processors", json=handle_f…

### 5. **Use Cache Hit Ratio Monitoring** Monitor the cache hit ratio to ensure that the cache is being used effectively. This can help you fine-tune your caching strategy. #### Example with Monitoring ```python # Increment cache hit coun…

return JSONResponse(content={"error_code": e.status_code, "message": e.detail}, status_code=e.status_code) combined_results = sparse_results["results"] + dense_results["results"] total_results = len(combined_results) …

dense_results = call_dense_retrieval(query) except HTTPException as e: dense_results = {"results": [], "total_results": 0} return JSONResponse(content={"error_code": e.status_code, "message": e.detail}, status_co…

If you prefer to automate the process using the Keycloak Admin REST API, here is an example of how you might define and assign roles programmatically: #### Define Roles ```python import requests KEYCLOAK_URL = "http://localhost:8080/auth…

- 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…