rtiktoken

{rtiktoken} is a thin wrapper around tiktoken-rs (and in turn around OpenAI’s Python library tiktoken). It provides functions to encode text into tokens used by OpenAI’s models and decode tokens back into text using BPE tokenizers. It is also useful to count the numbers of tokens in a text to guess how expensive a call to OpenAI’s API would be. Note that all the tokenization happens offline and no internet connection is required.

Another use-case is to compute similarity scores between texts using tokens.

Other use-cases can be found in the OpenAI’s cookbook How to Count Tokens with tiktoken.

To verify the outputs of the functions, see also OpenAI’s Tokenizer Platform.

Installation

You can install rtiktoken like so:

# Dev version
# install.packages("devtools")
# devtools::install_github("DavZim/rtiktoken")

# CRAN version
install.packages("rtiktoken")

Example

library(rtiktoken)

# 1. Encode text into tokens
text <- c(
  "Hello World, this is a text that we are going to use in rtiktoken!",
  "Note that the functions are vectorized! Yay!"
)
tokens <- get_tokens(text, "gpt-4o")
tokens
#> [[1]]
#>  [1] 13225  5922    11   495   382   261  2201   484   581   553  2966   316
#> [13]  1199   306 38742  8251  2488     0
#> 
#> [[2]]
#>  [1]  12038    484    290   9964    553   9727   2110      0 115915      0

# 2. Decode tokens back into text
decoded_text <- decode_tokens(tokens, "gpt-4o")
decoded_text
#> [1] "Hello World, this is a text that we are going to use in rtiktoken!"
#> [2] "Note that the functions are vectorized! Yay!"

# Note that it's not guaranteed to produce the identical text as text-parts
# might be dropped if no token match is found.
identical(text, decoded_text)
#> [1] TRUE

# 3. Count the number of tokens in a text
n_tokens <- get_token_count(text, "gpt-4o")
n_tokens
#> [1] 18 10

Models & Tokenizers

The different OpenAI models use different tokenizers (see also source code of tikoken-rs for a full list).

The following models use the following tokenizers (note that all functions of this package both allow to use the model names as well as the tokenizer names):

Development

rtiktoken is built using extendr and Rust. To build the package, you need to have Rust installed on your machine.

rextendr::document()
devtools::document()