Package 'cat.cog'

Score CERAD constructional praxis drawings using LLMs

Description

Wraps the Python cat_cog.cerad_drawn_score() function. Scores drawn shapes (circle, diamond, rectangles, cube) from the CERAD constructional praxis assessment using vision-capable LLMs.

Usage

cerad_drawn_score(
  shape,
  image_input,
  api_key,
  user_model = "gpt-4o",
  creativity = NULL,
  safety = FALSE,
  chain_of_thought = TRUE,
  filename = NULL,
  save_directory = NULL,
  model_source = "auto",
  ...
)

Arguments

shape	Character. The shape being scored: "circle", "diamond", "rectangles", or "cube".
image_input	Character. Path to the image file or directory of images.
api_key	Character. API key for the model provider.
user_model	Character. Model name. Default "gpt-4o".
creativity	Numeric or NULL. Temperature setting. Default NULL.
safety	Logical. Save progress after each item. Default FALSE.
chain_of_thought	Logical. Enable chain-of-thought reasoning. Default TRUE.
filename	Character or NULL. Output CSV filename. Default NULL.
save_directory	Character or NULL. Directory to save results. Default NULL.
model_source	Character. Provider hint: "auto", "openai", "anthropic", "google", etc. Default "auto".
...	Additional arguments passed to the Python function.

Value

A data.frame with scoring results.

Examples

## Not run: 
# Score a single circle drawing
result <- cerad_drawn_score(
  shape       = "circle",
  image_input = "path/to/circle_drawing.png",
  api_key     = Sys.getenv("OPENAI_API_KEY")
)

# Score a directory of cube drawings
results <- cerad_drawn_score(
  shape       = "cube",
  image_input = "path/to/cube_drawings/",
  api_key     = Sys.getenv("OPENAI_API_KEY"),
  user_model  = "claude-sonnet-4-5-20250929",
  model_source = "anthropic"
)

## End(Not run)

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