gptstudio_create_skeleton: Create a Request Skeleton

In gptstudio: Use Large Language Models Directly in your Development Environment

Create a Request Skeleton

Description

This function dynamically creates a request skeleton for different AI text generation services.

Usage

gptstudio_create_skeleton(
  service = "openai",
  prompt = "Name the top 5 packages in R.",
  history = list(list(role = "system", content = "You are an R chat assistant")),
  stream = TRUE,
  model = "gpt-3.5-turbo",
  ...
)

Arguments

service	The text generation service to use. Currently supports "openai", "huggingface", "anthropic", "google", "azure_openai", "ollama", and "perplexity".
prompt	The initial prompt or question to pass to the text generation service.
history	A list indicating the conversation history, where each element is a list with elements "role" (who is speaking; e.g., "system", "user") and "content" (what was said).
stream	Logical; indicates if streaming responses should be used. Currently, this option is not supported across all services.
model	The specific model to use for generating responses. Defaults to "gpt-3.5-turbo".
...	Additional arguments passed to the service-specific skeleton creation function.

Value

Depending on the selected service, returns a list that represents the configured request ready to be passed to the corresponding API.

Examples

## Not run: 
request_skeleton <- gptstudio_create_skeleton(
  service = "openai",
  prompt = "Name the top 5 packages in R.",
  history = list(list(role = "system", content = "You are an R assistant")),
  stream = TRUE,
  model = "gpt-3.5-turbo"
)

## End(Not run)

gptstudio documentation built on May 29, 2024, 12:30 p.m.