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predicted_labels = [tokenizer.decode(pred, skip_special_tokens=True) for pred in predictions] # Ground truth labels true_labels = [item['text'] for item in tokenized_datasets['test']] # Calculate accuracy accuracy = accuracy_score(true_la…

- Use a central authentication service to manage user roles and permissions. ### Example Implementation Here's an enhanced version of your code with a more structured approach: ```python import logging # Define roles and their associ…

# Fetch the encryption key from Vault key = get_encryption_key(vault_client) # Encrypt some data data = "Hello, World!" encrypted_data = encrypt_data(data, key) print(f"Encrypted Data: {encrypted_data}") # Decrypt the data decrypted_dat…

def process_segment_with_llm(segment): # Placeholder function to simulate LLM processing return f"Processed {segment}" # Example usage if __name__ == "__main__": max_tokens = 100 # Example max token limit overlap = 20 # E…

# Sprint Board ## Tasks - **Task 1: Implement AES-256 encryption** - **Priority:** Highest - **Labels:** encryption, security - **Task 2: Optimize database queries** - **Priority:** High - **Labels:** optimization, performance - **T…

2. **Concurrency**: Use threading or multiprocessing to handle multiple queries concurrently. 3. **Caching**: Use Redis to cache frequent queries and their reformulated versions to reduce the load on the model. 4. **Efficient Tokenization**…