openai-ergonomic

Ergonomic Rust wrapper for the OpenAI API, providing type-safe builder patterns and async/await support.

Features

• 🛡️ Type-safe - Full type safety with builder patterns using bon
• ⚡ Async/await - Built on tokio and reqwest for modern async Rust
• 🔄 Streaming - First-class support for streaming responses
• 📝 Comprehensive - Covers all OpenAI API endpoints
• 🧪 Well-tested - Extensive test coverage with mock support
• 📚 Well-documented - Rich documentation with examples

Status

🚧 Under Construction - This crate is currently being developed and is not yet ready for production use.

Quick Start

Add openai-ergonomic to your Cargo.toml:

[dependencies]
openai-ergonomic = "0.1"
tokio = { version = "1.0", features = ["full"] }

Basic Usage

use openai_ergonomic::{Client, Config};

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let client = Client::from_env()?
        .api_key("your-api-key-here")
        .build();

    let response = client
        .chat_completions()
        .model("gpt-4")
        .message("user", "Hello, world!")
        .send()
        .await?;

    println!("{}", response.choices[0].message.content);
    Ok(())
}

Streaming Example

use openai_ergonomic::{Client, Config};
use futures::StreamExt;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let client = Client::from_env()?
        .api_key("your-api-key-here")
        .build();

    let mut stream = client
        .chat_completions()
        .model("gpt-4")
        .message("user", "Tell me a story")
        .stream()
        .await?;

    while let Some(chunk) = stream.next().await {
        let chunk = chunk?;
        if let Some(content) = chunk.choices[0].delta.content {
            print!("{}", content);
        }
    }
    Ok(())
}

Documentation

• Getting Started Guide
• Architecture Overview
• API Documentation
• Examples

Examples

The examples/ directory contains comprehensive examples for all major OpenAI API features:

• Basic Usage: Simple chat completions and responses
• Streaming: Real-time response streaming
• Function Calling: Tool integration and function calling
• Vision: Image understanding and analysis
• Audio: Speech-to-text and text-to-speech
• Assistants: Assistant API with file handling
• Embeddings: Vector embeddings generation
• Images: Image generation and editing

Run an example:

cargo run --example quickstart

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

Licensed under either of

• Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
• MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.