What is an effective method to preprocess prompts using custom code before sending them to an LLM?

Question

Options

• ADirectly modify the LLM's internal architecture to include preprocessing steps
• BIt is better not to introduce custom code to preprocess prompts as the LLM has not been trained
• CRather than preprocessing prompts, it's more effective to postprocess the LLM outputs to align
• DWrite a MLflow PyFunc model that has a separate function to process the prompts