plyable

LLM Functions Documentation

Comprehensive guide to using Plyable's custom LLM functions in Google Sheets™

Google Sheets™ Plugin

Custom LLM Functions

Plyable provides a set of powerful LLM-powered functions that you can use directly in your Google Sheets™. Each function is designed to help you process and analyze text data efficiently using advanced AI models.

LLM_TRANSLATE

Translates text from one language to another using LLMs.

Syntax

=LLM_TRANSLATE(input, targetLanguage, [sourceLanguage], [temperature], [model])

Parameters

  • input Text or range to translate
  • targetLanguage Target language (e.g., "English")
  • sourceLanguage Source language (optional)
  • temperature Model temperature (0 is deterministic, 1 is random)
  • model LLM model to use (e.g., "gpt-4o-mini")

Returns

The translated text

Example

=LLM_TRANSLATE("Bonjour le monde", "English", "French")

LLM_EXTRACT

Extracts structured data from text based on a format pattern.

Syntax

=LLM_EXTRACT(input, pattern, [temperature], [model])

Parameters

  • input Text or range to extract data from
  • pattern Format pattern with placeholders (e.g., "%Name% %Age% %Profession%")
  • temperature Model temperature (0 is deterministic, 1 is random)
  • model LLM model to use (e.g., "gpt-4o-mini")

Returns

The extracted data based on the pattern

Example

=LLM_EXTRACT("John Smith is 42 years old and works as a developer", "%Name% %Age% %Profession%")

LLM_SUMMARIZE

Creates a concise summary of longer text content.

Syntax

=LLM_SUMMARIZE(input, [temperature], [model])

Parameters

  • input Text or range to summarize
  • temperature Model temperature (0 is deterministic, 1 is random)
  • model LLM model to use (e.g., "gpt-4o-mini")

Returns

The summarized text

Example

=LLM_SUMMARIZE(A1:A10)

LLM_CLASSIFY

Classifies text into provided categories.

Syntax

=LLM_CLASSIFY(input, categories, [temperature], [model])

Parameters

  • input Text or range to classify
  • categories Categories to classify into (Array or range)
  • temperature Model temperature (0 is deterministic, 1 is random)
  • model LLM model to use (e.g., "gpt-4o-mini")

Returns

The classification result

Example

=LLM_CLASSIFY("Great product!", ["positive", "negative", "neutral"])

LLM_TAG

Generates or applies tags to text content.

Syntax

=LLM_TAG(input, [tags], [temperature], [model])

Parameters

  • input Text or range to tag
  • tags Optional suggested tags (String, array or range)
  • temperature Model temperature (0 is deterministic, 1 is random)
  • model LLM model to use (e.g., "gpt-4o-mini")

Returns

The generated tags

Example

=LLM_TAG("AI is transforming business", ["Technology", "Business", "Innovation"])

LLM_EDIT

Edits text based on an instruction.

Syntax

=LLM_EDIT(input, instruction, [temperature], [model])

Parameters

  • input Text or range to edit
  • instruction Editing instruction (e.g., "Fix grammar and spelling")
  • temperature Model temperature (0 is deterministic, 1 is random)
  • model LLM model to use (e.g., "gpt-4o-mini")

Returns

The edited text

Example

=LLM_EDIT("Fix this sentense", "Fix grammar and spelling")

LLM

Generic LLM function that takes custom prompts.

Syntax

=LLM(input, prompts, [temperature], [model])

Parameters

  • input Text or range to process
  • prompts Custom prompt or range of prompts
  • temperature Model temperature (0 is deterministic, 1 is random)
  • model LLM model to use (e.g., "gpt-4o-mini")

Returns

The LLM response

Example

=LLM("What is the capital of France?", "Answer the question:")

Need Help?

For more information or support with Plyable's LLM functions, check our Support Center or contact us at support@plyable.com.