Chapter 2: Routing

Mon, 01 Jan 0001 00:00:00 +0000

Chapter 2: Routing

Routing Pattern Overview

While sequential processing via prompt chaining is a foundational technique for executing deterministic, linear workflows with language models, its applicability is limited in scenarios requiring adaptive responses. Real-world agentic systems must often arbitrate between multiple potential actions based on contingent factors, such as the state of the environment, user input, or the outcome of a preceding operation. This capacity for dynamic decision-making, which governs the flow of control to different specialized functions, tools, or sub-processes, is achieved through a mechanism known as routing.

Appendix A: Advanced Prompting Techniques

Mon, 01 Jan 0001 00:00:00 +0000

Appendix A: Advanced Prompting Techniques

Introduction to Prompting

Prompting, the primary interface for interacting with language models, is the process of crafting inputs to guide the model towards generating a desired output. This involves structuring requests, providing relevant context, specifying the output format, and demonstrating expected response types. Well-designed prompts can maximize the potential of language models, resulting in accurate, relevant, and creative responses. In contrast, poorly designed prompts can lead to ambiguous, irrelevant, or erroneous outputs.

Language Models on AI VOID

Chapter 2: Routing

Chapter 2: Routing

Routing Pattern Overview

Appendix A: Advanced Prompting Techniques

Appendix A: Advanced Prompting Techniques

Introduction to Prompting