https://github.com/lukeharwood11/openai-proxz
I wanted a simple interface for interacting with OpenAI & compatible APIs and couldn't find one that was MIT licensed and carried the features I needed, so I built one!
As someone who is coming from python, I loved how simple the openai-python package was, so this was modeled after that interface.
📙 ProxZ Docs: https://proxz.mle.academy
Features
- Built-in retry logic
- Environment variable config support for API keys, org. IDs, project IDs, and base urls
- Integration with the most popular OpenAI endpoints with a generic
requestmethod for missing endpoints
Installation
To install proxz, run
zig fetch --save "git+https://github.com/lukeharwood11/openai-proxz"
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"));
Usage
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();
Since OpenAI was one of the first large LLM providers, others modeled their APIs around their contracts! So you can use other providers by setting the OPENAI_BASE_URL environment variable or adjusting the config:
var openai = try OpenAI.init(allocator, .{
.api_key = "my-groq-api-key",
.base_url = "https://api.groq.com/openai/v1",
.max_retries = 5,
});
defer openai.deinit();
Chat Completions
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();
const completions = response.data;
std.log.debug("{s}", .{completions.choices[0].message.content});
Embeddings
const inputs = [_][]const u8{ "Hello", "Foo", "Bar" };
const embeddings_response = try openai.embeddings.create(.{
.model = "text-embedding-3-small",
.input = &inputs,
});
// Don't forget to free resources!
defer embeddings_response.deinit();
const embeddings = embeddings_response.data;
std.log.debug("Model: {s}\nNumber of Embeddings: {d}\nDimensions of Embeddings: {d}", .{
embeddings.model,
embeddings.data.len,
embeddings.data[0].embedding.len,
});
Contributions
Contributions are welcome and encouraged! Submit an issue for any bugs/feature requests and open a PR if you tackled one of them!
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