discussion_flow_v1 {chatAI4R}

discussion_flow_v1: Interactions and Flow Control Between LLM-based Bots (LLBs)

Description

Simulates interactions and flow control between three different roles of LLM-based bots (LLBs).

Usage

discussion_flow_v1(
  issue,
  Domain = "bioinformatics",
  Model = "gpt-4-0613",
  api_key = Sys.getenv("OPENAI_API_KEY"),
  language = "English",
  Summary_nch = 50,
  verbose = TRUE,
  Nonfuture = TRUE,
  sayENorJA = TRUE
)

Arguments

issue

The issue to be discussed. Example: "I want to solve linear programming and create a timetable."

Domain

The domain of the discussion, default is "bioinformatics".

Model

The model to be used, default is "gpt-4-0613".

api_key

The API key for OpenAI, default is retrieved from the system environment variable "OPENAI_API_KEY".

language

The language for the discussion, default is "English".

Summary_nch

The number of characters for the summary, default is 50.

verbose

Logical, whether to print verbose output, default is TRUE.

Nonfuture

Logical, whether to use an asynchronous processing or not, default is not to use (TRUE).

sayENorJA

Logical, whether to say in English or Japanese, default is TRUE. This feature is available on macOS system only.

Details

Interactions and Flow Control Between LLM-based Bots (LLBs)

This function is described to simulate the interactions and flow control between three different roles of LLM-based bots, abbreviated as LLBs, and to reproduce more realistic dialogues and discussions. Here is a brief description of the roles: A (Beginner): This bot generates questions and summaries based on the content of the discussion provided by the user. B (Expert): This bot provides professional answers to questions posed by LLB A. C (Peer Reviewer): This bot reviews the dialog between LLB A and LLB B and suggests improvements or refinements. The three parties independently call the OpenAI API according to their roles. In addition, it keeps track of the conversation history between the bots and performs processes such as questioning, answering, and peer review. The function is designed to work in a "domain," which is essentially a specific area or topic around which conversations revolve. It is recommended to use GPT-4 or a model with higher accuracy than GPT-4. English is recommended as the input language, but the review will also be conducted in Japanese, the native language of the author.

Value

A summary of the conversation between the bots.

Author(s)

Satoshi Kume

Examples

## Not run: 
issue <-  "I want to solve linear programming and create a timetable."

#Run Discussion with the domain of bioinformatics
discussion_flow_v1(issue)

## End(Not run)