Classify survey responses using LLMs — classify • cat.survey

Wraps the Python cat_survey.classify() function. Adds survey_question context to the base cat.stack classification engine.

Usage

classify(
  input_data,
  categories,
  survey_question = "",
  description = "",
  add_other = "prompt",
  check_verbosity = TRUE,
  api_key = NULL,
  user_model = "gpt-4o",
  mode = "image",
  creativity = NULL,
  safety = FALSE,
  chain_of_verification = FALSE,
  chain_of_thought = FALSE,
  step_back_prompt = FALSE,
  context_prompt = FALSE,
  thinking_budget = 0L,
  example1 = NULL,
  example2 = NULL,
  example3 = NULL,
  example4 = NULL,
  example5 = NULL,
  example6 = NULL,
  filename = NULL,
  save_directory = NULL,
  model_source = "auto",
  max_categories = 12L,
  categories_per_chunk = 10L,
  divisions = 10L,
  research_question = NULL,
  models = NULL,
  consensus_threshold = "unanimous",
  use_json_schema = TRUE,
  max_workers = NULL,
  fail_strategy = "partial",
  max_retries = 5L,
  batch_retries = 2L,
  retry_delay = 1,
  row_delay = 0,
  pdf_dpi = 150L,
  auto_download = FALSE
)

Arguments

input_data: A character vector, list, or data.frame column of survey responses to classify.
categories: A character vector of category names, or "auto" to infer categories from the data.
survey_question: Character. The survey question text. Default "".
description: Character. Additional context for the classification task. Default "".
add_other: Logical or "prompt". Controls addition of an "Other" category. Default "prompt".
check_verbosity: Logical. Check category descriptions. Default TRUE.
api_key: API key for the model provider (single-model mode).
user_model: Character. Model name. Default "gpt-4o".
mode: Character. PDF processing mode. Default "image".
creativity: Numeric or NULL. Temperature. Default NULL.
safety: Logical. Save progress after each item. Default FALSE.
chain_of_verification: Logical. Default FALSE.
chain_of_thought: Logical. Default FALSE.
step_back_prompt: Logical. Default FALSE.
context_prompt: Logical. Default FALSE.
thinking_budget: Integer. Extended thinking budget. Default 0L.
example1, example2, example3, example4, example5, example6: Optional few-shot examples.
filename: Character or NULL. Output CSV filename.
save_directory: Character or NULL. Output directory.
model_source: Character. Provider hint. Default "auto".
max_categories: Integer. Max categories for auto mode. Default 12L.
categories_per_chunk: Integer. Default 10L.
divisions: Integer. Default 10L.
research_question: Character or NULL. Optional research context.
models: List of model specs for ensemble mode.
consensus_threshold: Character or numeric. Default "unanimous".
use_json_schema: Logical. Default TRUE.
max_workers: Integer or NULL. Default NULL.
fail_strategy: Character. Default "partial".
max_retries: Integer. Default 5L.
batch_retries: Integer. Default 2L.
retry_delay: Numeric. Default 1.0.
row_delay: Numeric. Default 0.0.
pdf_dpi: Integer. Default 150L.
auto_download: Logical. Default FALSE.

Value

A data.frame with classification results.

Examples

if (FALSE) { # \dontrun{
results <- classify(
  input_data      = c("Took a new job in Chicago",
                      "Wanted to be closer to grandkids",
                      "Couldn't afford rent in the Bay Area"),
  categories      = c("Job/school", "Family", "Cost of living", "Other"),
  survey_question = "Why did you move?",
  api_key         = Sys.getenv("OPENAI_API_KEY"),
  user_model      = "gpt-4o-mini"
)
} # }