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https://github.com/zurawiki/tiktoken-rs

Ready-made tokenizer library for working with GPT and tiktoken
https://github.com/zurawiki/tiktoken-rs

bpe openai rust tokenizer

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Ready-made tokenizer library for working with GPT and tiktoken

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## `tiktoken-rs`

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Rust library for tokenizing text with OpenAI models using tiktoken.

This library provides a set of ready-made tokenizer libraries for working with GPT, tiktoken and related OpenAI models. Use cases covers tokenizing and counting tokens in text inputs.

This library is built on top of the `tiktoken` library and includes some additional features and enhancements for ease of use with rust code.

# Examples

For full working examples for all supported features, see the [examples](https://github.com/zurawiki/tiktoken-rs/tree/main/tiktoken-rs/examples) directory in the repository.

# Usage

1. Install this tool locally with `cargo`

```sh
cargo add tiktoken-rs
```

Then in your rust code, call the API

## Counting token length

```rust
use tiktoken_rs::o200k_base;

let bpe = o200k_base().unwrap();
let tokens = bpe.encode_with_special_tokens(
"This is a sentence with spaces"
);
println!("Token count: {}", tokens.len());
```

## Counting max_tokens parameter for a chat completion request

```rust
use tiktoken_rs::{get_chat_completion_max_tokens, ChatCompletionRequestMessage};

let messages = vec![
ChatCompletionRequestMessage {
content: Some("You are a helpful assistant that only speaks French.".to_string()),
role: "system".to_string(),
name: None,
function_call: None,
},
ChatCompletionRequestMessage {
content: Some("Hello, how are you?".to_string()),
role: "user".to_string(),
name: None,
function_call: None,
},
ChatCompletionRequestMessage {
content: Some("Parlez-vous francais?".to_string()),
role: "system".to_string(),
name: None,
function_call: None,
},
];
let max_tokens = get_chat_completion_max_tokens("o1-mini", &messages).unwrap();
println!("max_tokens: {}", max_tokens);
```

## Counting max_tokens parameter for a chat completion request with [async-openai](https://crates.io/crates/async-openai)

Need to enable the `async-openai` feature in your `Cargo.toml` file.

```rust
use tiktoken_rs::async_openai::get_chat_completion_max_tokens;
use async_openai::types::{ChatCompletionRequestMessage, Role};

let messages = vec![
ChatCompletionRequestMessage {
content: Some("You are a helpful assistant that only speaks French.".to_string()),
role: Role::System,
name: None,
function_call: None,
},
ChatCompletionRequestMessage {
content: Some("Hello, how are you?".to_string()),
role: Role::User,
name: None,
function_call: None,
},
ChatCompletionRequestMessage {
content: Some("Parlez-vous francais?".to_string()),
role: Role::System,
name: None,
function_call: None,
},
];
let max_tokens = get_chat_completion_max_tokens("o1-mini", &messages).unwrap();
println!("max_tokens: {}", max_tokens);
```

`tiktoken` supports these encodings used by OpenAI models:

| Encoding name | OpenAI models |
| ----------------------- | ------------------------------------------------------------------------- |
| `o200k_base` | GPT-4o models, o1 models |
| `cl100k_base` | ChatGPT models, `text-embedding-ada-002` |
| `p50k_base` | Code models, `text-davinci-002`, `text-davinci-003` |
| `p50k_edit` | Use for edit models like `text-davinci-edit-001`, `code-davinci-edit-001` |
| `r50k_base` (or `gpt2`) | GPT-3 models like `davinci` |

See the [examples](https://github.com/zurawiki/tiktoken-rs/tree/main/tiktoken-rs/examples) in the repo for use cases. For more context on the different tokenizers, see the [OpenAI Cookbook](https://github.com/openai/openai-cookbook/blob/66b988407d8d13cad5060a881dc8c892141f2d5c/examples/How_to_count_tokens_with_tiktoken.ipynb)

# Encountered any bugs?

If you encounter any bugs or have any suggestions for improvements, please open an issue on the repository.

# Acknowledgements

Thanks @spolu for the original code, and `.tiktoken` files.

# License

This project is licensed under the [MIT License](./LICENSE).