Added the content and code snippets for AzureBaseService class.

Author: VidyalakshmiMani

MAUI/DataForm/AI-Powered-Smart-Paste-DataForm.md

@@ -26,52 +26,120 @@ To enable AI functionality in your .NET MAUI Scheduler, first ensure that you ha
 
 ### Step 3: Connect to the Azure OpenAI
 
-To connect your .NET MAUI app to Azure OpenAI, create a service class that handles communication with the AI model. Start by initializing the OpenAIClient using your Azure endpoint and API key.
+To connect your .NET MAUI app to Azure OpenAI, create a service class that handles communication with the AI model. 
 
-In this service, define a method called GetAnswerFromGPT. This method takes a user prompt as input, sends it to the deployed model, and returns the AI-generated response. 
+```
+/// <summary>
+/// Helper class to interact with Azure AI.
+/// </summary>
+internal class AzureOpenAIServiceConnector : AzureBaseService
+{
+
+}
+```
+
+In this service, define a method called `GetAnswerFromGPT`. This method takes a user prompt from the SfAIAssistView control as input, sends it to the deployed model (e.g., GPT35Turbo), and returns the AI-generated response.
+
+```
+/// <summary>
+/// Helper class to interact with Azure AI.
+/// </summary>
+internal class AzureOpenAIServiceConnector : AzureBaseService
+{
+
+    /// <summary>
+    /// Retrieves an answer from the deployment name model using the provided user prompt.
+    /// </summary>
+    /// <param name="userPrompt">The user prompt.</param>
+    /// <returns>The AI response.</returns>
+    internal async Task<string> GetAnswerFromGPT(string userPrompt)
+    {
+        ChatHistory = string.Empty;
+        if (IsCredentialValid && Client != null && ChatHistory != null)
+        {
+            // Add the user's prompt as a user message to the conversation.
+            ChatHistory = ChatHistory + "You are a predictive analytics assistant.";
+            // Add the user's prompt as a user message to the conversation.
+            ChatHistory = ChatHistory + userPrompt;
+            try
+            {
+                //// Send the chat completion request to the OpenAI API and await the response.
+                var response = await Client.CompleteAsync(ChatHistory);
+                return response.ToString();
+            }
+            catch
+            {
+                // If an exception occurs (e.g., network issues, API errors), return an empty string.
+                return "";
+            }
+        }
 
+        return "";
+    }
+}
 ```
- /// <summary>
- /// Helper class to interact with Azure AI.
- /// </summary>
- internal class AzureOpenAIServiceConnector : AzureBaseService
+
+Within the base service class (AzureBaseService), initialize the OpenAIClient with your Azure endpoint, deployment name, and API key.
+
+```
+ public abstract class AzureBaseService
  {
+     #region Fields
+     /// <summary>
+     /// The EndPoint
+     /// </summary>
+     internal const string Endpoint = "YOUR_END_POINT_NAME";
 
      /// <summary>
-     /// Retrieves an answer from the deployment name model using the provided user prompt.
+     /// The Deployment name
      /// </summary>
-     /// <param name="userPrompt">The user prompt.</param>
-     /// <returns>The AI response.</returns>
-     internal async Task<string> GetAnswerFromGPT(string userPrompt)
-     {
-         ChatHistory = string.Empty;
-         if (IsCredentialValid && Client != null && ChatHistory != null)
-         {
-             // Add the user's prompt as a user message to the conversation.
-             ChatHistory = ChatHistory + "You are a predictive analytics assistant.";
-             // Add the user's prompt as a user message to the conversation.
-             ChatHistory = ChatHistory + userPrompt;
-             try
-             {
-                 //// Send the chat completion request to the OpenAI API and await the response.
-                 var response = await Client.CompleteAsync(ChatHistory);
-                 return response.ToString();
-             }
-             catch
-             {
-                 // If an exception occurs (e.g., network issues, API errors), return an empty string.
-                 return "";
-             }
-         }
+     internal const string DeploymentName = "DEPLOYMENT_NAME";
+
+     /// <summary>
+     /// The Image Deployment name
+     /// </summary>
+     internal const string ImageDeploymentName = "IMAGE_DEPOLYMENT_NAME";
+
+     /// <summary>
+     /// The API key
+     /// </summary>
+     internal const string Key = "API_KEY";
+
+     /// <summary>
+     /// The already credential validated field
+     /// </summary>
+     private static bool isAlreadyValidated = false;
+
+     /// <summary>
+     /// Indicating whether an credentials are valid or not
+     /// </summary>
+     private static bool _isCredentialValid;
 
-         return "";
+     #endregion
+
+     public AzureBaseService()
+     {
+         ValidateCredential();
      }
- }
- ```
 
+    internal IChatClient? Client { get; set; }
+
+    /// <summary>
+    /// To get the Azure open ai method
+    /// </summary>
+    private void GetAzureOpenAI()
+    {
+        try
+        {
+            var client = new AzureOpenAIClient(new Uri(Endpoint), new AzureKeyCredential(Key)).AsChatClient(modelId: DeploymentName);
+            this.Client = client;
+        }
+        catch (Exception)
+        {
+        }
+    }
+ }
  ```
-this.client = new OpenAIClient(new Uri(endpoint), new AzureKeyCredential(key));
-```
 
 ## Integrating AI-powered Smart Paste in .NET MAUI DataForm