Prompt engineering for text generation: Difference between revisions

==Structure of a Prompt==

Instructions or Task description tells the [[model]] what to do. What do you want, and how to create the output. How to use the context or examples. What to do with the query. Clear instructions enable the model to deliver more accurate and relevant responses.

Context or external information is the additional information for the model that might not exist in the model. They can be manually inserted into the prompt, retrieved via a vector database ([[retrieval augmentation]]), or gathered from other sources such as [[APIs]]. Providing context helps the model generate more informed and precise responses.

===Example(s)===

The user input or query is typically submitted by a human user. Although not always the case, most prompts involve a query input from the user. This input serves as the basis for the model's response and assists in tailoring the output to the user's specific needs.