Azure AI OpenAI chat GPT-4 client connection

This article presents code that shows how you can connect to OpenAI Chat GPT-4 client connection. The repository for the code presented is the following GitHub repo:

https://github.com/toreaurstadboss/OpenAIDemo

The repo contains useful helper methods to use Azure AI Service and create AzureOpenAIClient or the more generic ChatClient which is a specified chat client for the AzureOpenAIClient that uses a specific ai model, default ai model to use is 'gpt-4'. The creation of chat client is done using a class with a builder pattern. To create a chat client you can simply create it like this :

Program.cs

         const string modelName = "gpt-4";

            var chatClient = AzureOpenAIClientBuilder
                .Instance
                .WithDefaultEndpointFromEnvironmentVariable()
                .WithDefaultKeyFromEnvironmentVariable()
                .BuildChatClient(aiModel: modelName);
                

The builder looks like this:

AzureOpenAIClientBuilder.cs

using Azure.AI.OpenAI;
using OpenAI.Chat;
using System.ClientModel;

namespace ToreAurstadIT.OpenAIDemo
{

    /// <summary>
    /// Creates AzureOpenAIClient or ChatClient (default model is "gpt-4")
    /// Suggestion:
    /// Create user-specific Environment variables for : AZURE_AI_SERVICES_KEY and AZURE_AI_SERVICES_ENDPOINT to avoid exposing endpoint and key in source code.
    /// Then us the 'WithDefault' methods to use the two user-specific environment variables, which must be set.
    /// </summary>
    public class AzureOpenAIClientBuilder
    {

        private const string AZURE_AI_SERVICES_KEY = nameof(AZURE_AI_SERVICES_KEY);
        private const string AZURE_AI_SERVICES_ENDPOINT = nameof(AZURE_AI_SERVICES_ENDPOINT);

        private string? _endpoint = null;
        private ApiKeyCredential? _key = null;

        public AzureOpenAIClientBuilder WithEndpoint(string endpoint) { _endpoint = endpoint; return this; }

        /// <summary>
        /// Usage: Provide user-specific enviornment variable called : 'AZURE_AI_SERVICES_ENDPOINT'
        /// </summary>
        /// <returns></returns>
        public AzureOpenAIClientBuilder WithDefaultEndpointFromEnvironmentVariable() { _endpoint = Environment.GetEnvironmentVariable(AZURE_AI_SERVICES_ENDPOINT, EnvironmentVariableTarget.User); return this; }
       
        
        public AzureOpenAIClientBuilder WithKey(string key) { _key = new ApiKeyCredential(key); return this; }       
        public AzureOpenAIClientBuilder WithKeyFromEnvironmentVariable(string key) { _key = new ApiKeyCredential(Environment.GetEnvironmentVariable(key) ?? "N/A"); return this; }

        /// <summary>
        /// Usage : Provide user-specific environment variable called : 'AZURE_AI_SERVICES_KEY'
        /// </summary>
        /// <returns></returns>
        public AzureOpenAIClientBuilder WithDefaultKeyFromEnvironmentVariable() { _key = new ApiKeyCredential(Environment.GetEnvironmentVariable(AZURE_AI_SERVICES_KEY, EnvironmentVariableTarget.User) ?? "N/A"); return this; }

        public AzureOpenAIClient? Build() => !string.IsNullOrWhiteSpace(_endpoint) && _key != null ? new AzureOpenAIClient(new Uri(_endpoint), _key) : null;

        /// <summary>
        /// Default model will be set 'gpt-4'
        /// </summary>
        /// <returns></returns>
        public ChatClient? BuildChatClient(string aiModel = "gpt-4") => Build()?.GetChatClient(aiModel);

        public static AzureOpenAIClientBuilder Instance => new AzureOpenAIClientBuilder();

    }
}

It is highly recommended to store your endpoint and key to the Azure AI service of course not in the source code repository, but another place, for example on your user-specific environment variable or Azure key vault or similar place hard to obtain for malicious use, for example using your account to route much traffic to Chat GPT-4 only to end up being billed for this traffic. The code provided some 'default methods' which will look for environment variables. Add the key and endpoint to your Azure AI to these user specific environment variables.

• AZURE_AI_SERVICES_KEY
• AZURE_AI_SERVICES_ENDPOINT

To use the chat client the following code shows how to do this:

ChatGptDemo.cs

    public async Task<string?> RunChatGptQuery(ChatClient? chatClient, string msg)
        {
            if (chatClient == null)
            {
                Console.WriteLine("Sorry, the demo failed. The chatClient did not initialize propertly.");
                return null;
            }

            var stopWatch = Stopwatch.StartNew();

            string reply = await chatClient.GetStreamedReplyStringAsync(msg, outputToConsole: true);

            Console.WriteLine($"The operation took: {stopWatch.ElapsedMilliseconds} ms");


            Console.WriteLine();

            return reply;
        }
        
        

The communication against Azure AI service with Open AI Chat-GPT service is this line:

ChatGptDemo.cs

    string reply = await chatClient.GetStreamedReplyStringAsync(msg, outputToConsole: true);

The Chat GPT-4 service will return the data streamed so you can output the result as quickly as possible. I have tested it out using Standard Service S0 tier, it is a bit slower than the default speed you get inside the browser using Copilot, but it works and if you output to the console, you get a similar experience. The code here can be used in different environments, the repo contains a console app with .NET 8.0 Framework, written in C# as shown in the code. Here is the helper methods for the ChatClient, provided as extension methods.

ChatclientExtensions.cs

using OpenAI.Chat;
using System.ClientModel;
using System.Text;

namespace OpenAIDemo
{
    public static class ChatclientExtensions
    {

        /// <summary>
        /// Provides a stream result from the Chatclient service using AzureAI services.
        /// </summary>
        /// <param name="chatClient">ChatClient instance</param>
        /// <param name="message">The message to send and communicate to the ai-model</param>
        /// <returns>Streamed chat reply / result. Consume using 'await foreach'</returns>
        public static AsyncCollectionResult<StreamingChatCompletionUpdate> GetStreamedReplyAsync(this ChatClient chatClient, string message) =>
            chatClient.CompleteChatStreamingAsync(
                [new SystemChatMessage("You are an helpful, wonderful AI assistant"), new UserChatMessage(message)]);

        public static async Task<string> GetStreamedReplyStringAsync(this ChatClient chatClient, string message, bool outputToConsole = false)
        {
            var sb = new StringBuilder();
            await foreach (var update in GetStreamedReplyAsync(chatClient, message))
            {
                foreach (var textReply in update.ContentUpdate.Select(cu => cu.Text))
                {
                    sb.Append(textReply);
                    if (outputToConsole)
                    {
                        Console.Write(textReply);
                    }
                }
            }
            return sb.ToString();
        }

    }
}

The code presented here should make it a bit easier to communicate with the Azure AI Open AI Chat GPT-4 service. See the repository to test out the code. Screenshot below shows the demo in use in a console running against the Azure AI Chat GPT-4 service :

Url encoding base 64 strings in .NET 9

This article shows new functionality how to url encode base 64 strings in .NET 9. In .NET 8 you would do multiple steps to url encode base 64 strings like this: Program.cs

using System.Buffers.Text;
using System.Net;
using System.Text;
using System.Text.Encodings.Web;

byte[] data = Encoding.UTF8.GetBytes("Hello there, how yall doin");
var base64 = Convert.ToBase64String(data);
var base64UrlEncoded = WebUtility.UrlEncode(base64);

Console.WriteLine(base64UrlEncoded);

We here first convert the string to a bytes in a byte array and then we base 64 encode the byte array into a Base64 string. Finally we url encode the string into a URL safe string. Let's see how simple this is in .NET 9 : Program.cs (v2)

using System.Buffers.Text;
using System.Net;
using System.Text;
using System.Text.Encodings.Web;

byte[] data = Encoding.UTF8.GetBytes("Hello there, how yall doin");
var base64UrlEncodedInNet9 = Base64Url.EncodeToString(data);

Console.WriteLine(base64UrlEncodedInNet9);

If we use ImplicitUsings here in the .csproj file the code above just becomes :

byte[] data = Encoding.UTF8.GetBytes("Hello there, how yall doin");
var base64UrlEncodedInNet9 = Base64Url.EncodeToString(data);
Console.WriteLine(base64UrlEncodedInNet9);

This shows we can skip the intermediate step where we first convert the bytes into a base64-string and then into a Url safe string and instead do a base-64 encoding and then an url encoding in one go. This way is more optimized, it is also possible here to use ReadOnlySpan (that works for both .NET 8 and .NET 9). Putting together we get:

using System.Buffers.Text;
using System.Net;
using System.Text;
using System.Text.Encodings.Web;

ReadOnlySpan data = Encoding.UTF8.GetBytes("Hello there, how yall doin");
var base64 = Convert.ToBase64String(data);
var base64UrlEncoded = WebUtility.UrlEncode(base64);

var base64UrlEncodedInNet9 = Base64Url.EncodeToString(data);

Console.WriteLine(base64UrlEncoded);
Console.WriteLine(base64UrlEncodedInNet9);

The output is the following :

SGVsbG8gdGhlcmUsIGhvdyB5YWxsIGRvaW4%3D
SGVsbG8gdGhlcmUsIGhvdyB5YWxsIGRvaW4

As we can see, the .NET 9 Base64.UrlEncode skips the the padding characters, so beware of that.



Note that by omitting the padding, it is necessary to pad the base 64 url encoded string if you want to decode it. Consider this helpful extension method to add the necessary padding:

/// <summary>
/// Provides extension methods for Base64 encoding operations.
/// </summary>
public static class Base64Extensions
{
    /// <summary>
    /// Adds padding to a Base64 encoded string to ensure its length is a multiple of 4.
    /// </summary>
    /// <param name="base64">The Base64 encoded string without padding.</param>
    /// <param name="isUrlEncode">Set to true if this is URL encode, will add instead '%3D%' as padding at the end (0-2 such padding chars, same for '=').</param>
    /// <returns>The Base64 encoded string with padding added, or the original string if it is null or whitespace.</returns>
    public static string? AddPadding(this string base64, bool isUrlEncode = false)
    {
        string paddedBase64 = !string.IsNullOrWhiteSpace(base64) ? base64.PadRight(base64.Length + (4 - (base64.Length % 4)) % 4, '=') : base64;
        return !isUrlEncode ? paddedBase64 : paddedBase64?.Replace("=", "%3D");
    }    
}

We can now achieve the same output with this extension method :

using System.Buffers.Text;
using System.Net;
using System.Text;
using System.Text.Encodings.Web;

ReadOnlySpan data = Encoding.UTF8.GetBytes("Hello there, how yall doin");
var base64 = Convert.ToBase64String(data);
var base64UrlEncoded = WebUtility.UrlEncode(base64);

var base64UrlEncodedInNet9 = Base64Url.EncodeToString(data);

// Using the extension method to add padding
base64UrlEncodedInNet9 = base64UrlEncodedInNet9.AddPadding(isUrlEncode: true);

Console.WriteLine(base64UrlEncoded);
Console.WriteLine(base64UrlEncodedInNet9);

Finally, the output using the two different approaching pre .NET 9 and .NET 9 gives the same results:

SGVsbG8gdGhlcmUsIGhvdyB5YWxsIGRvaW4%3D
SGVsbG8gdGhlcmUsIGhvdyB5YWxsIGRvaW4%3D

Enumerating concurrent collections with snapshots in C#

In standard collections in C#, it is not allowed to alter collections you iterate upon using foreach for example, since it throws InvalidOperationException - Collection was modified; enumeration operation may not execute. Concurrent collections can be altered while being iterated. This is the default behavior, allow concurrent behavior while iterating - as locking the entire concurrent collection is costly. You can however enforce a consistent way of iterating the concurrent collection by making a snapshot of it. For concurrent dictionaries, we use the ToArray method.

	var capitals = new ConcurrentDictionary<string, string>{
		["Norway"] = "Oslo",
		["Denmark"] = "Copenhagen",
		["Sweden"] = "Stockholm",
		["Faroe Islands"] = "Torshamn",
		["Finland"] = "Helsinki",
		["Iceland"] = "Reykjavik"
	};

	//make a snapshot of the concurrent dictionary first 
	
	var capitalsSnapshot = capitals.ToArray();
	
	//do some modifications
	
	foreach (var capital in capitals){
		capitals[capital.Key] = capital.Value.ToUpper();
	}

	foreach (var capital in capitalsSnapshot)
	{
		Console.WriteLine($"The capital in {capital.Key} is {capital.Value}");
	}

This outputs:

The capital in Denmark is Copenhagen
The capital in Sweden is Stockholm
The capital in Faroe Islands is Torshamn
The capital in Norway is Oslo
The capital in Finland is Helsinki
The capital in Iceland is Reykjavik  

The snapshot of the concurrent collection was not modified by the modifications done. Let's look at the concurrent collection again and iterate upon it.

	foreach (var capital in capitals)
	{
		Console.WriteLine($"The capital in {capital.Key} is {capital.Value}");
	}

This outputs:

Enumerate capitals in concurrent array - just enumerating with ToArray() - elements can be changed while enumerating. Faster, but more unpredictable
The capital in Denmark is COPENHAGEN
The capital in Sweden is STOCKHOLM
The capital in Faroe Islands is TORSHAMN
The capital in Norway is OSLO
The capital in Finland is HELSINKI
The capital in Iceland is REYKJAVIK

As we can see, the concurrent dictionary has modified its contents and this shows that we can get modifications upon iterating collections. If you do want to get consistent results, using a snapshot should be desired. But note that this will lock the entire collection and involve costly operations of copying the contents. If you do do concurrent collection snapshots, keep the number of snapshots to a minimum and iterate upon these snapshots, preferable only doing one snapshot in one single place in the method for the specific concurrent dictionary.