library(mall)
data("reviews")
llm_use("ollama", "llama3.2", seed = 100, .silent = TRUE)
# Use max_words to set the maximum number of words to use for the summary
llm_summarize(reviews, review, max_words = 5)
#> # A tibble: 3 × 2
#> review .summary
#> <chr> <chr>
#> 1 This has been the best TV I've ever used. Gr… it's a great tv
#> 2 I regret buying this laptop. It is too slow … laptop purchase was a mistake
#> 3 Not sure how to feel about my new washing ma… having mixed feelings about it
# Use 'pred_name' to customize the new column's name
llm_summarize(reviews, review, 5, pred_name = "review_summary")
#> # A tibble: 3 × 2
#> review review_summary
#> <chr> <chr>
#> 1 This has been the best TV I've ever used. Gr… it's a great tv
#> 2 I regret buying this laptop. It is too slow … laptop purchase was a mistake
#> 3 Not sure how to feel about my new washing ma… having mixed feelings about it
# For character vectors, instead of a data frame, use this function
llm_vec_summarize(
"This has been the best TV I've ever used. Great screen, and sound.",
max_words = 5
)
#> [1] "it's a great tv"
# To preview the first call that will be made to the downstream R function
llm_vec_summarize(
"This has been the best TV I've ever used. Great screen, and sound.",
max_words = 5,
preview = TRUE
)
#> ollamar::chat(messages = list(list(role = "user", content = "You are a helpful summarization engine. Your answer will contain no no capitalization and no explanations. Return no more than 5 words. The answer is the summary of the following text:\nThis has been the best TV I've ever used. Great screen, and sound.")),
#> output = "text", model = "llama3.2", seed = 100)Summarize text
llm_summarize
Description
Use a Large Language Model (LLM) to summarize text
Usage
llm_summarize(
.data,
col,
max_words = 10,
pred_name = ".summary",
additional_prompt = ""
)
llm_vec_summarize(x, max_words = 10, additional_prompt = "", preview = FALSE)Arguments
| Arguments | Description |
|---|---|
| .data | A data.frame or tbl object that contains the text to be analyzed |
| col | The name of the field to analyze, supports tidy-eval |
| max_words | The maximum number of words that the LLM should use in the summary. Defaults to 10. |
| pred_name | A character vector with the name of the new column where the prediction will be placed |
| additional_prompt | Inserts this text into the prompt sent to the LLM |
| x | A vector that contains the text to be analyzed |
| preview | It returns the R call that would have been used to run the prediction. It only returns the first record in x. Defaults to FALSE Applies to vector function only. |
Value
llm_summarize returns a data.frame or tbl object. llm_vec_summarize returns a vector that is the same length as x.