SmartFAQs.ai
Back to Learn
Intermediate

Prompt Augmentation

Prompt Augmentation is the process of dynamically enriching a base query by injecting external context, such as retrieved document snippets or system-level metadata, into the model's input. It bridges the gap between a generic user request and a grounded response, though it requires balancing increased token latency and cost against the quality of the generated output.

Definition

Prompt Augmentation is the process of dynamically enriching a base query by injecting external context, such as retrieved document snippets or system-level metadata, into the model's input. It bridges the gap between a generic user request and a grounded response, though it requires balancing increased token latency and cost against the quality of the generated output.

Disambiguation

Distinguish from static prompt engineering; augmentation is a dynamic, data-driven enrichment step occurring at runtime.

Visual Metaphor

"A legal brief being stuffed with relevant case-law exhibits right before a trial begins."

Key Tools
LangChain (PromptTemplates)LlamaIndexDSPySemantic Kernel
Related Connections

Conceptual Overview

Prompt Augmentation is the process of dynamically enriching a base query by injecting external context, such as retrieved document snippets or system-level metadata, into the model's input. It bridges the gap between a generic user request and a grounded response, though it requires balancing increased token latency and cost against the quality of the generated output.

Disambiguation

Distinguish from static prompt engineering; augmentation is a dynamic, data-driven enrichment step occurring at runtime.

Visual Analog

A legal brief being stuffed with relevant case-law exhibits right before a trial begins.

Related Articles