Type

Name *

Short name *

Slug *

Caption *

Title *

Description *

Context input #1

Input type *

Label *

Placeholder *

Label key *

(use this key in prompt template)

Value key *

(use this key in prompt template)

Maximum input characters *

+ Add context input

GPT Temperature *

What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.

GPT Top P *

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

GPT Frequency penalty *

Number between 0 and 1 that penalizes new tokens based on their existing frequency in the text so far. Decreases the model's likelihood to repeat the same line verbatim.

GPT Presence penalty *

Number between 0 and 1 that penalizes new tokens based on whether they appear in the text so far. Increases the model's likelihood to talk about new topics.

GPT Maximum output characters *

GPT Prompt *

Use TONE to replace with user's selected tone value. Use context input's respective keys to replace during prompt generation. Use ### to separate examples or as defined in 'GPT Stop sequences' input.

Image

Variants *

Info

Output placeholder *

Separate multiple values in new lines with ###.

Key *

Use this value to reference in code.