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The LLI library offers a Rust interface for tokenizing text, specifically tailored for use with OpenAI models, through a seamless integration with Go applications. Utilizing the tiktoken_rs library, LLI provides efficient text tokenization capabilities, making it easier to preprocess text for AI-driven analysis and processing.

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LLI: Rust Library for Tokenization with OpenAI Models

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The LLI library offers a Rust interface for tokenizing text, specifically tailored for use with OpenAI models, through a seamless integration with Go applications. Utilizing the tiktoken_rs library, LLI provides efficient text tokenization capabilities, making it easier to preprocess text for AI-driven analysis and processing.

Features

  • Text tokenization suitable for OpenAI models.
  • Integration support for Go applications.
  • Token count operations for text input.
  • Support for various tokenizer models including Cl100kBase, P50kBase, R50kBase, P50kEdit, and Gpt2.

Prerequisites

Ensure you have Rust and Go installed on your system. This library is not supported on Windows platforms due to specific dependencies.

  • Rust (latest stable version)
  • Go (version 1.15 or higher) Building the Library To build the Rust library:
go generate
//go:generate bash -c "cd lli && cargo build --release"

This command compiles the Rust code into a static library located at target/release/liblli.a, which is then used by the Go wrapper.

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The LLI library offers a Rust interface for tokenizing text, specifically tailored for use with OpenAI models, through a seamless integration with Go applications. Utilizing the tiktoken_rs library, LLI provides efficient text tokenization capabilities, making it easier to preprocess text for AI-driven analysis and processing.

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