Struct openai_safe::OpenAI

pub struct OpenAI { /* private fields */ }

Chat Completions API

Chat models take a list of messages as input and return a model-generated message as output. Although the chat format is designed to make multi-turn conversations easy, it’s just as useful for single-turn tasks without any conversation.

Implementations

impl OpenAI

pub fn new( open_ai_key: &str, model: OpenAIModels, max_tokens: Option<usize>, temperature: Option<u32> ) -> Self

Examples found in repository

examples/use_openai.rs (line 21)

async fn main() {
    env_logger::init();
    let api_key: String = std::env::var("OPENAI_API_KEY").expect("OPENAI_API_KEY not set");
    let model = OpenAIModels::Gpt3_5Turbo; // Choose the model

    let open_ai = OpenAI::new(&api_key, model, None, None);

    // Example context and instructions
    let instructions =
        "Translate the following English text to all the languages in the response type";

    match open_ai
        .get_answer::<TranslationResponse>(instructions)
        .await
    {
        Ok(response) => println!("Response: {:?}", response),
        Err(e) => eprintln!("Error: {:?}", e),
    }
}

pub fn debug(self) -> Self

pub fn function_calling(self, function_call: bool) -> Self

pub fn set_context<T: Serialize>( self, input_name: &str, input_data: &T ) -> Result<Self>

pub fn check_prompt_tokens<T: JsonSchema + DeserializeOwned>( &self, instructions: &str ) -> Result<usize>

pub async fn get_answer<T: JsonSchema + DeserializeOwned>( self, instructions: &str ) -> Result<T>

Examples found in repository

examples/use_openai.rs (line 28)

async fn main() {
    env_logger::init();
    let api_key: String = std::env::var("OPENAI_API_KEY").expect("OPENAI_API_KEY not set");
    let model = OpenAIModels::Gpt3_5Turbo; // Choose the model

    let open_ai = OpenAI::new(&api_key, model, None, None);

    // Example context and instructions
    let instructions =
        "Translate the following English text to all the languages in the response type";

    match open_ai
        .get_answer::<TranslationResponse>(instructions)
        .await
    {
        Ok(response) => println!("Response: {:?}", response),
        Err(e) => eprintln!("Error: {:?}", e),
    }
}