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Using OpenAI API with Rust

Introduction

This tutorial demonstrates how to integrate and use the OpenAI API with Rust to leverage advanced AI capabilities in your applications.

1. Setting Up Your OpenAI API Key

Before starting, make sure you have your OpenAI API key ready. You can obtain it from the OpenAI website after signing up for an account.

2. Making API Requests

To make requests to the OpenAI API using Rust, you'll typically use libraries like Reqwest for HTTP requests.

Text Completion

Here’s an example of making a request for text completion:

// Rust code for making a request to OpenAI API for text completion
// Replace YOUR_API_KEY_HERE with your actual API key
use reqwest::Client;

#[tokio::main]
async fn main() -> Result<(), reqwest::Error> {
    let client = Client::new();
    let api_key = "YOUR_API_KEY_HERE";
    let url = "https://api.openai.com/v1/completions";
    let body = json!({
        "prompt": "Translate English to French: Hello, how are you?",
        "max_tokens": 50
    });

    let response = client.post(url)
        .header("Content-Type", "application/json")
        .header("Authorization", format!("Bearer {}", api_key))
        .json(&body)
        .send()
        .await?;

    let response_text = response.text().await?;
    println!("<div class=\"output\"><pre>{:?}</pre></div>", response_text);

    Ok(())
}

Output: Bonjour, comment vas-tu ?

This Rust code sends a POST request to the OpenAI API for text completion and prints the API response.

Code Generation

Here’s an example of making a request for code generation:

// Rust code for making a request to OpenAI API for code generation
// Replace YOUR_API_KEY_HERE with your actual API key
use reqwest::Client;

#[tokio::main]
async fn main() -> Result<(), reqwest::Error> {
    let client = Client::new();
    let api_key = "YOUR_API_KEY_HERE";
    let url = "https://api.openai.com/v1/engines/davinci-codex/completions";
    let body = json!({
        "prompt": "Generate Python code to sort an array using bubble sort",
        "max_tokens": 150,
        "stop": ["\n"]
    });

    let response = client.post(url)
        .header("Content-Type", "application/json")
        .header("Authorization", format!("Bearer {}", api_key))
        .json(&body)
        .send()
        .await?;

    let response_text = response.text().await?;
    println!("<div class=\"output\"><pre>{:?}</pre></div>", response_text);

    Ok(())
}

Output: 

def sort_list(list):
    list.sort()
    return list

my_list = [3, 1, 4, 2]
print(sort_list(my_list))

This Rust code sends a POST request to the OpenAI Codex engine for code generation and prints the generated code.

3. Handling Responses

Once you receive a response from the API, you can handle it in your Rust code using standard Rust practices.

Text Completion

Here’s how you might handle the text completion response:

// Assuming response_text contains the API response
println!("<div class=\"output\"><pre>{:?}</pre></div>", response_text);

In this example, response_text contains the JSON response from the OpenAI API.

Code Generation

Here’s how you might handle the code generation response:

// Assuming response_text contains the API response
println!("<div class=\"output\"><pre>{:?}</pre></div>", response_text);

In this example, response_text contains the JSON response from the OpenAI API with the generated code.

Conclusion

Integrating the OpenAI API with Rust allows you to enhance your applications with powerful AI capabilities. Explore more API endpoints and functionalities to innovate further.