Summarize text, images, or PDFs using LLMs

Wraps the Python cat_stack.summarize() function. Generates summaries of input data using one or more LLM models. Supports single-model and multi-model (ensemble) summarization.

Usage

summarize(
  input_data,
  api_key = NULL,
  description = "",
  instructions = "",
  format = "paragraph",
  max_length = NULL,
  focus = NULL,
  user_model = "gpt-4o",
  model_source = "auto",
  mode = "image",
  input_mode = NULL,
  input_type = "auto",
  pdf_dpi = 150L,
  creativity = NULL,
  thinking_budget = 0L,
  chain_of_thought = TRUE,
  context_prompt = FALSE,
  step_back_prompt = FALSE,
  filename = NULL,
  save_directory = NULL,
  models = NULL,
  max_workers = NULL,
  parallel = NULL,
  auto_download = FALSE,
  safety = FALSE,
  max_retries = 5L,
  batch_retries = 2L,
  retry_delay = 1,
  row_delay = 0,
  fail_strategy = "partial",
  batch_mode = FALSE,
  batch_poll_interval = 30,
  batch_timeout = 86400,
  auto_start_ollama = TRUE
)

Arguments

input_data: A character vector, list, or data.frame column. For images/PDFs, a directory path or character vector of file paths.
api_key: Character or NULL. API key for the model provider (single-model mode). Not required when models is supplied. Default NULL.
description: Character. Context description for the summarization task. Default "".
instructions: Character. Specific instructions for the summary. Default "".
format: Character. Output format: "paragraph" (default) or other supported formats.
max_length: Integer or NULL. Maximum length of the summary. NULL uses the model default. Default NULL.
focus: Character or NULL. Optional focus for the summary. Default NULL.
user_model: Character. Model name. Default "gpt-4o".
model_source: Character. Provider hint: "auto", "openai", "anthropic", "google", etc. Default "auto".
mode: Character. Processing mode for images/PDFs: "image" (default), "text", or "both".
input_mode: Character or NULL. Explicit input mode override. Default NULL.
input_type: Character. Type of input: "auto" (default), "text", "image", or "pdf".
pdf_dpi: Integer. DPI for PDF page rendering. Default 150L.
creativity: Numeric or NULL. Temperature setting. NULL uses the provider default. Default NULL.
thinking_budget: Integer. Extended thinking token budget (0 = off). Default 0L.
chain_of_thought: Logical. Enable chain-of-thought reasoning. Default TRUE.
context_prompt: Logical. Add expert context to prompts. Default FALSE.
step_back_prompt: Logical. Enable step-back prompting. Default FALSE.
filename: Character or NULL. Output filename. Default NULL.
save_directory: Character or NULL. Directory to save results. Default NULL.
models: A list of model specifications for multi-model ensemble mode. Each element is either a 3-element character vector c("model", "provider", "api_key") or a 4-element list list("model", "provider", "api_key", list(creativity = 0.5)). Default NULL.
max_workers: Integer or NULL. Max parallel workers. NULL = auto. Default NULL.
parallel: Logical or NULL. Enable parallel processing. Default NULL.
auto_download: Logical. Auto-download Ollama models. Default FALSE.
safety: Logical. If TRUE, saves progress after each item. Default FALSE.
max_retries: Integer. Max retries per API call. Default 5L.
batch_retries: Integer. Max retries for batch-level failures. Default 2L.
retry_delay: Numeric. Seconds between retries. Default 1.0.
row_delay: Numeric. Seconds between processing each row. Default 0.0.
fail_strategy: Character. How to handle failures: "partial" (default) or "strict".
batch_mode: Logical. Use batch processing mode. Default FALSE.
batch_poll_interval: Numeric. Seconds between batch status polls. Default 30.0.
batch_timeout: Numeric. Maximum seconds to wait for batch completion. Default 86400.0.
auto_start_ollama: Logical. If TRUE (default), automatically call ensure_ollama_running() when model_source = "ollama" or any ensemble entry uses the "ollama" provider. Set FALSE to skip the check.

Value

A data.frame with summarization results.

Examples

if (FALSE) { # \dontrun{
# Single-model summarization
results <- summarize(
  input_data   = c("A long article about climate change...",
                    "A detailed report on economic trends..."),
  description  = "News articles",
  instructions = "Provide a 2-sentence summary",
  api_key      = Sys.getenv("OPENAI_API_KEY")
)

# PDF summarization
results <- summarize(
  input_data = "path/to/documents/",
  input_type = "pdf",
  api_key    = Sys.getenv("OPENAI_API_KEY")
)
} # }