Exploring The Capabilities Of Codex – A Module On Azure OpenAI’s AI-Powered Code Generator

If you’re new to this module, we suggest studying the Azure OpenAI module earlier than continuing to the Codex module. In our earlier module, we coated Davinci, and on this publish, we are going to delve into the Codex module.

Codex for code understanding and technology (together with translation from pure language to code), and Embeddings for using and understanding semantic representations of textual content information.

Potential methods to make use of Codex in numerous situations

Codex can be utilized in varied situations the place there’s a have to generate code rapidly and effectively. Listed below are some examples of how Codex can be utilized:

Code Autocompletion

Codex can be utilized as an clever code autocompletion software. Builders can use Codex to recommend code snippets and autocomplete code blocks primarily based on the context of their present code.

Code Refactoring

Codex may also be used to refactor code. Builders can present pure language enter to Codex, describing how they wish to modify their present code, and Codex can generate the mandatory code to make these modifications.

Code Technology

Codex can be utilized to generate code for varied functions. As an illustration, it may well generate code for machine studying fashions, net functions, cellular functions, or every other software program program.

Prototyping

Codex can be utilized to prototype concepts for brand new initiatives rapidly. Builders can describe their venture concepts in pure language enter, and Codex can generate the preliminary code framework.

Training

Codex can be utilized to show programming to rookies. Codex can generate code for varied programming ideas, and rookies can be taught by exploring the code generated by Codex.

General, Codex has the potential to revolutionize the way in which builders write code and can be utilized in varied situations the place there’s a have to generate code rapidly and effectively.

On this instance, I’ll reveal how you can generate code utilizing Codex by sending a pure language request. The request is to create a Python operate that takes in two numbers and returns their sum.

Be sure you are utilizing mannequin “text-davinci-002”

To make use of C# language, I’ve created a Console software utilizing Visual Studio 2022.

Ship the request to Azure OpenAI to generate the code initially.

var request = "Create a operate in Python that takes in two numbers and returns their sum.";
var end result = await ConnectAzureOpenAI(Url, key, request);
Console.WriteLine(end result);

The module’s response is obtained as proven under.

If this code seems insufficient, submit one other request with extra detailed data. As an illustration, request so as to add a try-catch function to the code this time.

request = "How about including attempt catch to the operate that takes in two numbers and returns their sum.?";       
end result = await ConnectAzureOpenAI(Url, key, request);
Console.WriteLine(end result);

This time module’s response is obtained as proven under

personal static async Process < string > ConnectAzureOpenAI(string url, string key, string message) {
    string abstract = string.Empty;
    attempt {
        utilizing
        var shopper = new HttpClient();
        shopper.BaseAddress = new Uri(url);
        shopper.DefaultRequestHeaders.Settle for.Add(new MediaTypeWithQualityHeaderValue("software/json"));
        shopper.DefaultRequestHeaders.Add("api-key", key);
        var jsonContent = new {
            immediate = message,
                max_tokens = 1024,
                temperature = 0.7,
                frequency_penalty = 0.5,
                presence_penalty = 0,
                top_p = 0.5,
                best_of = 1
        };
        var msg = new HttpRequestMessage(HttpMethod.Publish, url);
        var immediate = new StringContent(JsonConvert.SerializeObject(jsonContent), Encoding.UTF8, "software/json");
        msg.Content material = immediate;
        var res = await shopper.SendAsync(msg).ConfigureAwait(false);
        if (res.IsSuccessStatusCode) {
            // Learn the response content material as a string
            var stringResult = await res.Content material.ReadAsStringAsync().ConfigureAwait(false);
            // Parse the string end result as a JObject
            var end result = JObject.Parse(stringResult);
            // If the "decisions" key exists within the end result and it has at the least one worth
            if (end result["choices"] != null && end result["choices"].Any()) {
                // Extract the abstract textual content from the primary selection within the "decisions" array
                abstract = end result["choices"][0]["text"].ToString();
            }
        } else {
            abstract = "Request has been failed";
        }
    } catch (Exception e) {
        abstract = e.Message;
    }
    return abstract;
}

I hope that with this module, you might have understood the codex for utilizing Azure OpenAI.