Crate async_openai

Async Rust library for OpenAI REST API based on OpenAPI spec.

Creating client

use async_openai::{Client, config::OpenAIConfig};

// Create a OpenAI client with api key from env var OPENAI_API_KEY and default base url.
let client = Client::new();

// Above is shortcut for
let config = OpenAIConfig::default();
let client = Client::with_config(config);

// OR use API key from different source and a non default organization
let api_key = "sk-..."; // This secret could be from a file, or environment variable.
let config = OpenAIConfig::new()
    .with_api_key(api_key)
    .with_org_id("the-continental");

let client = Client::with_config(config);

// Use custom reqwest client
let http_client = reqwest::ClientBuilder::new().user_agent("async-openai").build().unwrap();
let client = Client::new().with_http_client(http_client);

Microsoft Azure Endpoints

use async_openai::{Client, config::AzureConfig};

let config = AzureConfig::new()
    .with_api_base("https://my-resource-name.openai.azure.com")
    .with_api_version("2023-03-15-preview")
    .with_deployment_id("deployment-id")
    .with_api_key("...");

let client = Client::with_config(config);

// Note that Azure OpenAI service does not support all APIs and `async-openai`
// doesn't restrict and still allows calls to all of the APIs as OpenAI.

Making requests

 use async_openai::{Client, types::{CreateCompletionRequestArgs}};

 // Create client
 let client = Client::new();

 // Create request using builder pattern
 // Every request struct has companion builder struct with same name + Args suffix
 let request = CreateCompletionRequestArgs::default()
     .model("text-davinci-003")
     .prompt("Tell me the recipe of alfredo pasta")
     .max_tokens(40_u16)
     .build()
     .unwrap();

 // Call API
 let response = client
     .completions()      // Get the API "group" (completions, images, etc.) from the client
     .create(request)    // Make the API call in that "group"
     .await
     .unwrap();

 println!("{}", response.choices.first().unwrap().text);

Examples

For full working examples for all supported features see examples directory in the repository.

Modules

• config
  Client configurations: OpenAIConfig for OpenAI, AzureConfig for Azure OpenAI Service.
• error
  Errors originating from API calls, parsing responses, and reading-or-writing to the file system.
• types
  Types used in OpenAI API requests and responses. These types are created from component schemas in the OpenAPI spec

Structs

• Audio
  Turn audio into text Related guide: Speech to text
• Chat
  Given a chat conversation, the model will return a chat completion response.
• Client
  Client is a container for config, backoff and http_client used to make API calls.
• Completions
  Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position.
• Edits
  Given a prompt and an instruction, the model will return an edited version of the prompt.
• Embeddings
  Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.
• Files
  Files are used to upload documents that can be used with features like Fine-tuning.
• FineTunes
  Manage fine-tuning jobs to tailor a model to your specific training data.
• Images
  Given a prompt and/or an input image, the model will generate a new image.
• Models
  List and describe the various models available in the API. You can refer to the Models documentation to understand what models are available and the differences between them.
• Moderations
  Given a input text, outputs if the model classifies it as violating OpenAI’s content policy.