gpt-macro
ChatGPT powered Rust proc macro that generates code at compile-time.
Implemented Macros
auto_impl!{}#[auto_test(...)]
Usage
Get ChatGPT API key and set it to your environment variable OPENAI_API_KEY before run.
auto_impl!{}
Syntax:
auto_impl! {
$STR_LIT
$TOKEN_STREAM
}
where $STR_LIT is a prompt string literal, and $TOKEN_STREAM is target code.
Example:
use gpt_macro::auto_impl;
auto_impl! {
"Return fizz if the number is divisible by 3, buzz if the number is divisible by 5, and fizzbuzz if the number is divisible by both 3 and 5."
fn fizzbuzz(n: u32) -> String {
}
#[test]
fn test_fizzbuzz() {
assert_eq!(fizzbuzz(3), "fizz");
assert_eq!(fizzbuzz(5), "buzz");
assert_eq!(fizzbuzz(15), "fizzbuzz");
assert_eq!(fizzbuzz(1), "1");
}
}
As you can see, the fizzbuzz() implementation is incomplete, so the build fails without auto_impl!{}. The macro parses given prompt and target code, and asks ChatGPT to fill the code when expanding the macro. It replaces the target with code extracted from ChatGPT response. Then Rust compiler continues compiling the code.
Response Example:
fn fizzbuzz(n: u32) -> String {
if n % 3 == 0 && n % 5 == 0 {
return String::from("fizzbuzz");
} else if n % 3 == 0 {
return String::from("fizz");
} else if n % 5 == 0 {
return String::from("buzz");
} else {
return n.to_string();
}
}
#[test]
fn test_fizzbuzz() {
assert_eq!(fizzbuzz(3), "fizz");
assert_eq!(fizzbuzz(5), "buzz");
assert_eq!(fizzbuzz(15), "fizzbuzz");
assert_eq!(fizzbuzz(1), "1");
}
#[auto_test]
See this example:
use gpt_macro::auto_test;
#[auto_test(test_valid, test_div_by_zero)]
fn div_u32(a: u32, b: u32) -> u32 {
if b == 0 {
panic!("attempt to divide by zero");
}
a / b
}
Supported Models
- ChatGPT:
gpt-3.5-turbo(default) - Text Completion:
text-davinci-003(Specifydavincifeature to enable it)
License
gpt-macro is released under the MIT license.
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