Overview
The Otoroshi LLM extension provides a complete prompt engineering toolkit to control, optimize, and standardize interactions with LLMs. You can store reusable prompts, create message templates with dynamic expressions, and inject contextual information around user messages.
Prompt library
The prompt library lets you store reusable prompt texts as named entities. Prompts can be referenced by ID from multiple plugins, guardrails, and other features, providing a single source of truth for your prompt texts.
Prompt templating
Prompt templates let you define standardized message sets with dynamic expression placeholders. When a template is active, it replaces the consumer's messages entirely, giving you full control over what gets sent to the LLM.
Prompt context
Prompt contexts let you inject pre-messages and post-messages around the consumer's messages. This is the primary way to add system prompts, instructions, or framing information to LLM interactions without modifying the consumer's request.
Prompt validator
The prompt validator plugin validates the content of consumer messages against regex-based allow/deny patterns before they reach the LLM provider. This is a lightweight alternative to LLM-based guardrails for pattern-based content filtering.