ProxZ

https://proxz.mle.academy	lukeharwood11/openai-proxz

An OpenAI API library for the Zig programming language!

As I've been learning the Zig programming language, I couldn't find a client library for OpenAI that had all the features I needed, so I built one!

Features

• An easy to use interface, similar to that of openai-python
• Built-in retry logic
• Environment variable config support for API keys, org. IDs, project IDs, and base urls
• Response streaming support
• Integration with the most popular OpenAI endpoints with a generic request/requestStream method for missing endpoints

Installation

To install the latest version of proxz, run

 zig fetch --save "git+https://github.com/lukeharwood11/openai-proxz"

To install a specific version, run

zig fetch --save "https://github.com/lukeharwood11/openai-proxz/archive/refs/tags/<version>.tar.gz"

Note

To install the latest version compatible with Zig v0.13.0, use

zig fetch --save "https://github.com/lukeharwood11/openai-proxz/archive/refs/tags/v0.1.0.tar.gz"

And add the following to your build.zig

const proxz = b.dependency("proxz", .{
    .target = target,
    .optimize = optimize,
});

exe.root_module.addImport("proxz", proxz.module("proxz"));

Client Configuration

const proxz = @import("proxz");
const OpenAI = proxz.OpenAI;

// make sure you have an OPENAI_API_KEY environment variable set,
// or pass in a .api_key field to explicitly set!
var openai = try OpenAI.init(allocator, .{});
defer openai.deinit();

Chat Completions

Regular

const ChatMessage = proxz.ChatMessage;

var response = try openai.chat.completions.create(.{
    .model = "gpt-4o",
    .messages = &[_]ChatMessage{
        .{
            .role = "user",
            .content = "Hello, world!",
        },
    },
});
// This will free all the memory allocated for the response
defer response.deinit();
std.log.debug("{s}", .{response.choices[0].message.content});

Streamed Response

var stream = try openai.chat.completions.createStream(.{
    .model = "gpt-4o-mini",
    .messages = &[_]ChatMessage{
        .{
            .role = "user",
            .content = "Write me a poem about lizards. Make it a paragraph or two.",
        },
    },
});
defer stream.deinit();

std.debug.print("\n", .{});
while (try stream.next()) |val| {
    std.debug.print("{s}", .{val.choices[0].delta.content});
}
std.debug.print("\n", .{});

Embeddings

const inputs = [_][]const u8{ "Hello", "Foo", "Bar" };
const response = try openai.embeddings.create(.{
    .model = "text-embedding-3-small",
    .input = &inputs,
});
// Don't forget to free resources!
defer response.deinit();
std.log.debug("Model: {s}\nNumber of Embeddings: {d}\nDimensions of Embeddings: {d}", .{
    response.model,
    response.data.len,
    response.data[0].embedding.len,
});

Models

Get model details

var response = try openai.models.retrieve("gpt-4o");
defer response.deinit();
std.log.debug("Model is owned by '{s}'", .{response.owned_by});

List all models

var response = try openai.models.list();
defer response.deinit();
std.log.debug("The first model you have available is '{s}'", .{response.data[0].id})

Configuring Logging

By default all logs are enabled for your entire application. To configure your application, and set the log level for proxz, include the following in your main.zig.

pub const std_options = std.Options{
    .log_level = .debug, // this sets your app level log config
    .log_scope_levels = &[_]std.log.ScopeLevel{
        .{
            .scope = .proxz,
            .level = .info, // set to .debug, .warn, .info, or .err
        },
    },
};

All logs in proxz use the scope .proxz, so if you don't want to see debug/info logs of the requests being sent, set .level = .err. This will only display when an error occurs that proxz can't recover from.

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