Regex patterns

First, ensure you have spaCy installed and download the language model you want to use. For English, you can use the `en_core_web_sm` model. ```bash pip install spacy python -m spacy download en_core_web_sm ``` ### Step 2: Import spaCy an…

Now, let's tokenize some text and visualize the process for debugging. ```python # Sample text text = "Hello, world! This is a test sentence with [custom] tokens." # Process the text doc = nlp(text) # Print the tokens for token in doc: …

print("Context is valid") except ValueError as e: print(f"Invalid context: {e}") ``` Can someone help me improve this validation logic to ensure that our LLM queries are properly sanitized? ->-> 4,14 [Turn 2507] Assistant: Certainl…

} resource "aws_s3_bucket" "example" { bucket = "my-bucket" } """ print(check_sensitive_data(config)) ``` ### Conclusion By enhancing your regex patterns, performing contextual analysis, integrating with secrets management tools, and …

return "Sensitive data found but not checked in Vault" else: return "Config is secure" # Example usage config = """ variable "password" { default = "mysecretpassword" } resource "aws_s3_bucket" "example" { bucket =…