Redis Cache Implementation

self.sub_tasks.append((sub_task_name, estimated_time)) def calculate_total_time(self): total_time = sum(sub_task[1] for sub_task in self.sub_tasks) return total_time def display_sub_tasks(self): for…

- **Environment Variables**: Consider using environment variables to configure the initial delay and other settings. - **Monitoring and Alerts**: Implement monitoring and alerts to notify you if the API rate limit is consistently being exce…

# Generate ground truth for evaluation ground_truth_indices = np.random.choice(len(db.vectors), size=10, replace=False) # Evaluate the accuracy accuracy = calculate_accuracy(db, query_vector, ground_truth_indices) print(f"Search accuracy: …

Here's how you can update your matrix to include these additional metrics: ```python import pandas as pd # Define the engines to compare engines = ['DPR', 'Dense Passage Retriever', 'Sparse Retrieval', 'Faiss', 'Hnswlib', 'Qdrant'] # Def…

client = weaviate.Client("http://localhost:8080") # Define the schema schema = { "class": "MyClass", "properties": [ {"name": "my_text_property", "dataType": ["text"]}, {"name": "my_vector_property", "dataType": ["v…

def forward(self, x): x = torch.relu(self.fc1(x)) return x # Initialize the network and input tensor net = Net() input_tensor = torch.randn(1, 128) # Prepare the model for quantization net.qconfig = torch.quantization.…

3. **Review and Validate Assignments:** - Print out the assignments and validate them to ensure clarity. ### Sample Code ```python import random # Define roles and their responsibilities roles = { "Role1": ["Responsibility1", "Res…

print(f"Message sent successfully: {result}") except KafkaError as e: print(f"Failed to send message: {e}") if isinstance(e, KafkaTimeoutError): print("Error: KafkaTimeoutError") elif isinstance(e, KafkaConnectionErr…

print(f"Metadata extraction complete in {total_time:.2f} seconds.") print(f"Average latency: {avg_latency:.2f} ms") if __name__ == "__main__": main() ``` ### Explanation 1. **ThreadPoolExecutor**: The `concurrent.futures.Thre…

return self.cache[key] result = self.index[key] self.cache[key] = result return result def batch_query(self, keys): results = [] with ThreadPoolExecutor(max_workers=10) as executor: …

Here's an optimized version of your code using `IndexIVFFlat` and enabling multi-threading: ```python import faiss import numpy as np # Assume we have a dataset of 100,000 vectors vectors = np.random.rand(100000, 128).astype('float32') #…

dense_scores = np.random.rand(num_queries, num_documents) # Test queries test_queries = np.random.rand(num_queries, num_documents) predictions = [] for i in range(num_queries): query = test_queries[i] sparse_scores_i = sparse_scor…

from prometheus_client import start_http_server, Summary, Counter app = FastAPI() # Prometheus metrics REQUEST_TIME = Summary('request_processing_seconds', 'Time spent processing request') TOTAL_REQUESTS = Counter('total_requests', 'Total…

- Use `torch.no_grad()` to disable gradient computation during inference. 4. **Performance Monitoring**: - Monitor the performance and stability of the model during testing. ### Improved Code Structure Here's an improved version of…

# Define the context window with feedback strategies and their descriptions context_window = { "strategy1": "Description of strategy 1", "strategy2": "Description of strategy 2", "strategy3": "Description of strategy 3", "st…

- Implement robust error handling and recovery mechanisms to maintain high uptime. Here's an optimized and secure version of your code: ### Optimized and Secure Code ```python import torch import torch.nn as nn import torch.optim as o…

Based on the analysis, refine the key rotation logic to handle the identified issues effectively. ### Updated Code with Enhanced Logging Here's an updated version of your code with enhanced logging: ```python import logging import traceb…

redis_client.set(f"synonym:{term}", json.dumps(expanded_synonyms), ex=3600) return expanded_synonyms else: return [] tasks = [expand_term(term) for term in ter…