auto-rust is an experimental project that aims to automatically generate Rust code with LLM (Large Language Models) during compilation, utilizing procedural macros.

Related tags

Command-line ai gpt-3 openai-api gpt-4 llm ai-functions autogpt
Overview

Auto Rust

auto-rust is an experimental project that aims to automatically generate Rust code with LLM (Large Language Models) during compilation, utilizing procedural macros.

⚠️ Warning

Please note that Auto-Rust is currently under development and is not yet suitable for production use. While you are welcome to try it out and provide feedback, we caution that it may have an incomplete implementation and may not function as intended.

Installation

[dependencies]
auto-rust = "0.1.0"

You need to create a .env file in the root of your project with the following content:

OPENAI_API_KEY=<your-openai-api-key>

Example

use auto_rust::auto_implement;

#[auto_implement]
#[doc = "This function calculates if the input is a valid email address without use regex."]
fn is_email(input: String) -> bool {
    todo!()
}

fn main() {
    let result = is_email("bregyminsky.cc".to_string());
    println!("result: {}", result);
}

Limitations

  • LLMs are non-deterministic. If you don't get what you want from the first attempt - iterate, experiment with it.
  • Actually, the context is limited by whatever code is in your function definition, no knowledge of project structure or other files.
  • The extension doesn't add imports when new dependencies are introduced in the created code.

Contributing

Contributions are welcome. Feel free to open an issue if you have any questions or want to suggest an improvement.

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Comments
  • Implement a runtime version for `auto-implement`

    Implement a runtime version for `auto-implement`

    Create a runtime version for auto-implement, this must to use a one different method to calculate the response of the function. The main idea is create a macro that implement a "compiled query" to code to invoke OpenAI API at runtime stage, we can capture the input nature at compilation time and calculate the output based on the input at runtime time. I think a good starter point is read and explore the marvin's implementation: https://github.com/PrefectHQ/marvin/blob/35582ba2142d2fb6826e97416e7f0afc84d4c721/src/marvin/ai_functions/base.py

    opened by bregydoc 0
Owner
Minsky
Our goal is to promote the research, development, and use of open technologies in an accessible way for the majority of society.
Minsky
GitHub https://crates.io/crates/auto-rust
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