chat_history.data.frame

Creates a <code>chat_history</code> object from a data frame.

internal

Easily construct prompts and associated logic for interacting with
large language models (LLMs).
'tidyprompt' introduces the concept of prompt wraps, which are building
blocks that you can use to quickly turn a simple prompt into a complex
one. Prompt wraps do not just modify the prompt text, but also add
extraction and validation functions that will be applied to the response
of the LLM. This ensures that the user gets the desired output.
'tidyprompt' can add various features to prompts and their evaluation
by LLMs, such as structured output, automatic feedback, retries, reasoning
modes, autonomous R function calling, and R code generation and evaluation.
It is designed to be compatible with any LLM provider that offers
chat completion.

Luka Koning

tidyprompt

Prompt Large Language Models and Enhance Their Functionality

Tjark Van de Merwe

Kennispunt Twente 

chat_history.data.frame function

<dl><dt>chat_history</dt>
<dd>A data frame with 'role' and 'content' columns,
where 'role' is either 'user', 'assistant', or 'system', and 'content' is a character string
representing a chat message</dd></dl>

Arguments

Method for chat_history() when the input is a data.frame — chat_history.data.frame

<dl>

<dt>chat_history</dt>
<dd>A data frame with 'role' and 'content' columns,
where 'role' is either 'user', 'assistant', or 'system', and 'content' is a character string
representing a chat message</dd>

</dl>

chat_history.data.frame: Method for `chat_history()` when the input is a `data.frame`

Description

Usage

Value

Arguments