Prompt engineering techniques - Azure OpenAI | Microsoft Learn Prompt construction can be difficult In practice, the prompt acts assist the model complete the desired task, but it's more of an art than a science, often requiring experience and intuition to craft a successful prompt The goal of this article is to help get you started with this learning process
Best practices for prompt engineering with the OpenAI API Due to the way OpenAI models are trained, there are specific prompt formats that work particularly well and lead to more useful model outputs The official prompt engineering guide by OpenAI is usually the best place to start for prompting tips
Azure OpenAI Advanced Prompt Engineering - GitHub This repository is dedicated to writing, optimizing, and engineering prompts for Azure OpenAI's latest language models It covers best practices and advanced techniques for prompt engineering, as highlighted in the OpenAI Prompt Engineering Guide and supports the latest models, including GPT-4 1, GPT-4o, and other deployed versions
Best Practices for Prompt Engineering in Azure OpenAI Applications Summary: This post explores the art and science of prompt engineering for Azure OpenAI applications, covering techniques to craft effective prompts, optimize token usage, and implement robust error handling for production-ready AI features in NET applications
Image prompt engineering techniques - Azure OpenAI Learn how to craft engaging and informative prompts with Microsoft Copilot This module will teach you the basic concepts of prompt engineering, the elements of an effective prompt, and best practices in prompting
Prompt engineering - OpenAI API In the OpenAI dashboard, you can develop reusable prompts that you can use in API requests, rather than specifying the content of prompts in code This way, you can more easily build and evaluate your prompts, and deploy improved versions of your prompts without changing your integration code