Welcome to the Prompt Engineering repository! This document provides an overview of the key topics and guidelines related to prompt engineering. Use the links below to navigate to each topic.
Before diving into the different aspects of prompt engineering, it's important to understand the guidelines that govern the process. These guidelines ensure that the prompts are effective, efficient, and adhere to best practices.
Iterative prompt development is a crucial aspect of creating high-quality prompts. It involves refining and improving prompts through multiple iterations, testing, and feedback. This process helps in identifying and addressing any issues or limitations in the prompts.
Summarisation is the process of condensing a larger piece of text into a shorter, more concise version while retaining the essential information. This is an important skill for AI models, as it allows them to provide users with quick and accurate summaries of lengthy content.
Inferring is the ability of an AI model to draw conclusions or make predictions based on the information provided. This skill is essential for tasks such as answering questions, providing recommendations, and generating insights.
Transforming involves converting text from one form or style to another while maintaining the original meaning. This can include tasks such as paraphrasing, rewriting, or converting text into different formats.
Expanding is the process of taking a short piece of text or an idea and developing it into a more detailed and comprehensive piece of content. This skill is useful for tasks such as generating articles, blog posts, or other long-form content.
Chatbots are AI-powered conversational agents that can interact with users through text or voice. Prompt engineering plays a crucial role in developing chatbots that can understand user inputs, provide relevant responses, and maintain engaging conversations.