In the main menu of LaminarFlow, you'll find a crucial section dedicated to Presets. Mastery of Presets is key to streamlining your workflow, as they offer significant time-saving benefits when used strategically.

What are Presets?

A Preset in LaminarFlow consists of several fields, each serving a distinct purpose:

  • Name: Your chosen identifier for the preset.
  • Description: A brief overview of the preset’s purpose and functionality.
  • System: This field is pivotal. It shapes your query by providing contextual directives to the AI, ensuring precise and relevant responses.
  • Pre-Query: Acts as a fine-tuning mechanism for the System field, used for refining the AI's focus just before the main query.
  • Frequency Penalty: Adjust this to manage how often certain responses are repeated.
  • Presence Penalty: Use this to influence the variety in the AI's responses.
  • Temperature: Controls the level of creativity and randomness in responses.
  • Max Tokens: Sets the limit for the length of the AI's response.
  • Top P: Another lever for managing response diversity.

Presets are especially beneficial when generating numerous Instructions that require a consistent framework.

Example of a Preset

Below is a straightforward illustration showcasing the structure of a typical Preset:


Data Scientist


Free library of prompts


I want you to act as a data scientist. Imagine you're working on a challenging project for a cutting-edge
tech company. You've been tasked with extracting valuable insights from a large dataset related to user
behavior on a new app. Your goal is to provide actionable recommendations to improve user engagement
and retention.


I'm going to ask you something about our marketing campain and you will answer in a maximum of 1000 words.

This example illustrates how Presets can be tailored to specific roles and scenarios, enhancing the relevance and accuracy of AI-generated responses.

Our public library already includes a diverse range of these Presets for your immediate use.