In justinjm/googleCloudVertexAIR: Google Cloud Vertex AI API Into R

knitr::opts_chunk$set(echo = TRUE)

Setup

library(googleAuthR)
library(googleCloudVertexAIR)

options(googleAuthR.scopes.selected = "https://www.googleapis.com/auth/cloud-platform")

gar_auth_service(json_file = Sys.getenv("GAR_SERVICE_JSON"))

Set global arguements

projectId <- Sys.getenv("GCVA_DEFAULT_PROJECT_ID")
gcva_region_set(region = "us-central1")
gcva_project_set(projectId = projectId)

Test Prompt - Text Generation

https://cloud.google.com/vertex-ai/docs/generative-ai/text/test-text-prompts

result <- gcva_text_gen_predict(
  prompt="Give me ten interview questions for the role of a Python software engineer.",
  modelId="text-bison",
  rawResponse = TRUE
)

# result$predictions  # prediction  response with safteyAttributes 
result$predictions$content # prediction response only

Test Prompt - Text Chat

https://cloud.google.com/vertex-ai/docs/generative-ai/model-reference/text-chat https://github.com/GoogleCloudPlatform/generative-ai/blob/main/language/intro_palm_api.ipynb

# gcva_InputOutputTextPair(
#     input_text="How many moons does Mars have?",
#     output_text="The planet Mars has two moons, Phobos and Deimos."
#   )

# gcva_chat_predict(
#   modelId = "chat-bison@001",
#   context = "My name is Miles. You are an astronomer, knowledgeable about the solar system.",
#   examples = gcva_InputOutputTextPair(
#     input_text="How many moons does Mars have?",
#     output_text="The planet Mars has two moons, Phobos and Deimos."
#   ),
#   messages = "How many planets are there in the solar system?"
# )