This Rust library provides a high-performance, thread-safe implementation of OpenAI's tiktoken tokenizer, designed for developers and researchers working with large language models. It offers efficient encoding and decoding of text into token IDs, crucial for managing context windows and API costs.

How It Works

The library leverages Rust's performance characteristics and memory safety to deliver a fast and reliable tokenizer. It directly implements the tiktoken algorithm, including support for various encoding types like cl100k_base used by GPT-3.5 and GPT-4. This native implementation avoids the overhead of cross-language bindings, making it ideal for performance-critical applications.

Quick Start & Requirements

• Install via cargo add tiktoken-rs.
• Requires Rust toolchain (stable or nightly).
• See official documentation for detailed usage.

Highlighted Details

• Thread-safe and performant Rust implementation of tiktoken.
• Supports multiple encoding types (cl100k_base, p50k_base, r50k_base).
• Efficiently counts tokens without full encoding.
• Low-level API for direct control.

Maintenance & Community

The project is maintained by zurawiki. Community engagement can be found via GitHub issues.

Licensing & Compatibility

Licensed under the MIT license, allowing for commercial use and integration into closed-source projects.

Limitations & Caveats

The library is a direct implementation and may lag behind official tiktoken updates. It focuses on core tokenization functionality and does not include higher-level text processing utilities.