4 Building Context with Chat Completion and Advanced Prompts
This chapter covers
- Building prompt context using Chat History
- Utilizing chat completion for interactive AI conversations
- Enhancing prompts with Kernel Arguments and Execution Settings
- Crafting prompts using templates and factories
In this chapter, we explore Semantic Kernel's essential ability to build interactive AI conversations and create dynamic prompts. We begin by analyzing conversation history, a key mechanism for maintaining context in conversational AI applications. You will learn how to effectively structure and manage chat history, including the use of different message roles.
We will then analyze Chat Completion, which enables interactive conversations with AI models. We will also cover streaming chat completion and chat completion with vision capabilities.
Next, we'll explore how to enhance prompts using Kernel Arguments and Prompt Execution Settings. You will learn techniques for creating dynamic prompts and tweaking AI behavior.
Finally, we will introduce you to various prompt template factories. These are like rendering tools that help you create complex prompts for more sophisticated interactions with AI models.
By the end of this chapter, you'll have a solid understanding of how to use Semantic Kernel to create efficient, dynamic, and context-aware prompts.